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Iqbal FM, Aggarwal R, Joshi M, King D, Martin G, Khan S, Wright M, Ashrafian H, Darzi A. Barriers to and Facilitators of Key Stakeholders Influencing Successful Digital Implementation of Remote Monitoring Solutions: Mixed Methods Analysis. JMIR Hum Factors 2024; 11:e49769. [PMID: 37338929 PMCID: PMC11106697 DOI: 10.2196/49769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 01/26/2024] [Accepted: 04/07/2024] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND Implementation of remote monitoring solutions and digital alerting tools in health care has historically been challenging, despite the impetus provided by the COVID-19 pandemic. To date, a health systems-based approach to systematically describe barriers and facilitators across multiple domains has not been undertaken. OBJECTIVE We aimed to undertake a comprehensive mixed methods analysis of barriers and facilitators for successful implementation of remote monitoring and digital alerting tools in complex health organizations. METHODS A mixed methods approach using a modified Technology Acceptance Model questionnaire and semistructured interviews mapped to the validated fit among humans, organizations, and technology (HOT-fit) framework was undertaken. Likert frequency responses and deductive thematic analyses were performed. RESULTS A total of 11 participants responded to the questionnaire and 18 participants to the interviews. Key barriers and facilitators could be mapped onto 6 dimensions, which incorporated aspects of digitization: system use (human), user satisfaction (human), environment (organization), structure (organization), information and service quality (technology), and system quality (technology). CONCLUSIONS The recommendations proposed can enhance the potential for future remote sensing solutions to be more successfully integrated in health care practice, resulting in more successful use of "virtual wards." TRIAL REGISTRATION ClinicalTrials.gov NCT05321004; https://www.clinicaltrials.gov/study/NCT05321004.
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Affiliation(s)
| | - Ravi Aggarwal
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Meera Joshi
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Dominic King
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Guy Martin
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Sadia Khan
- West Middlesex University Hospital, London, United Kingdom
| | - Mike Wright
- Innovation Business Partner, Chelsea and Westminster NHS Trust, London, United Kingdom
| | - Hutan Ashrafian
- Division of Surgery, Imperial College London, London, United Kingdom
| | - Ara Darzi
- Division of Surgery, Imperial College London, London, United Kingdom
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Spoladore D, Colombo V, Campanella V, Lunetta C, Mondellini M, Mahroo A, Cerri F, Sacco M. A Knowledge-based Decision Support System for recommending safe recipes to individuals with dysphagia. Comput Biol Med 2024; 171:108193. [PMID: 38387382 DOI: 10.1016/j.compbiomed.2024.108193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 02/13/2024] [Accepted: 02/18/2024] [Indexed: 02/24/2024]
Abstract
BACKGROUND Dysphagia is a disorder that can be associated to several pathological conditions, including neuromuscular diseases, with significant impact on quality of life. Dysphagia often leads to malnutrition, as a consequence of the dietary changes made by patients or their caregivers, who may deliberately decide to reduce or avoid specific food consistencies (because they are not perceived as safe), and the lack of knowledge in how to process foods are critics. Such dietary changes often result in unbalanced nutrients intake, which can have significant consequences for frail patients. This paper presents the development of a prototypical novel ontology-based Decision Support System (DSS) to support neuromuscular patients with dysphagia (following a per-oral nutrition) and their caregivers in preparing nutritionally balanced and safe meals. METHOD After reviewing scientific literature, we developed in collaboration with Ear-Nose-Throat (ENT) specialists, neurologists, and dieticians the DSS formalizes expert knowledge to suggest recipes that are considered safe according to patient's consistency limitations and dysphagia severity and also nutritionally well-balanced. RESULTS The prototype can be accessed via digital applications both by physicians to generate and verify the recommendations, and by the patients and their caregivers to follow the step-by-step procedures to autonomously prepare and process one or more recipe. The system is evaluated with 9 clinicians to assess the quality of the DSS's suggested recipes and its acceptance in clinical practice. CONCLUSIONS Preliminary results suggest a global positive outcome for the recipes inferred by the DSS and a good usability of the system.
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Affiliation(s)
- Daniele Spoladore
- Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing -National Research Council, (CNR-STIIMA), Lecco, Italy.
| | - Vera Colombo
- Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing -National Research Council, (CNR-STIIMA), Lecco, Italy
| | - Vania Campanella
- Neuromuscular Omnicentre (NEMO), Fondazione Serena Onlus, Milan, Italy
| | - Christian Lunetta
- Neuromuscular Omnicentre (NEMO), Fondazione Serena Onlus, Milan, Italy; Istituti Clinici Scientifici Maugeri IRCCS, Department of Neurorehabilitation of Milan Institute, Milan, Italy
| | - Marta Mondellini
- Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing -National Research Council, (CNR-STIIMA), Lecco, Italy
| | - Atieh Mahroo
- Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing -National Research Council, (CNR-STIIMA), Lecco, Italy
| | - Federica Cerri
- Neuromuscular Omnicentre (NEMO), Fondazione Serena Onlus, Milan, Italy
| | - Marco Sacco
- Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing -National Research Council, (CNR-STIIMA), Lecco, Italy
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Kočo L, Siebers CCN, Schlooz M, Meeuwis C, Oldenburg HSA, Prokop M, Mann RM. The Facilitators and Barriers of the Implementation of a Clinical Decision Support System for Breast Cancer Multidisciplinary Team Meetings-An Interview Study. Cancers (Basel) 2024; 16:401. [PMID: 38254891 PMCID: PMC10813995 DOI: 10.3390/cancers16020401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/07/2024] [Accepted: 01/11/2024] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND AI-driven clinical decision support systems (CDSSs) hold promise for multidisciplinary team meetings (MDTMs). This study aimed to uncover the hurdles and aids in implementing CDSSs during breast cancer MDTMs. METHODS Twenty-four core team members from three hospitals engaged in semi-structured interviews, revealing a collective interest in experiencing CDSS workflows in clinical practice. All interviews were audio recorded, transcribed verbatim and analyzed anonymously. A standardized approach, 'the framework method', was used to create an analytical framework for data analysis, which was performed by two independent researchers. RESULTS Positive aspects included improved data visualization, time-saving features, automated trial matching, and enhanced documentation transparency. However, challenges emerged, primarily concerning data connectivity, guideline updates, the accuracy of AI-driven suggestions, and the risk of losing human involvement in decision making. Despite the complexities involved in CDSS development and integration, clinicians demonstrated enthusiasm to explore its potential benefits. CONCLUSIONS Acknowledging the multifaceted nature of this challenge, insights into the barriers and facilitators identified in this study offer a potential roadmap for smoother future implementations. Understanding these factors could pave the way for more effective utilization of CDSSs in breast cancer MDTMs, enhancing patient care through informed decision making.
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Affiliation(s)
- Lejla Kočo
- Department of Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Carmen C. N. Siebers
- Department of Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Margrethe Schlooz
- Department of Surgery, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Carla Meeuwis
- Department of Radiology, Rijnstate, Wagnerlaan 55, 6815 AD Arnhem, The Netherlands;
| | - Hester S. A. Oldenburg
- Department of Surgery, The Netherlands Cancer Institute (Antoni van Leeuwenhoek), Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Mathias Prokop
- Department of Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Ritse M. Mann
- Department of Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
- Department of Surgery, The Netherlands Cancer Institute (Antoni van Leeuwenhoek), Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
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Šteinmiller J, Ross P. General practitioners' user experience of the nationwide digital decision support system in primary care. Digit Health 2024; 10:20552076241271816. [PMID: 39247092 PMCID: PMC11378188 DOI: 10.1177/20552076241271816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 07/02/2024] [Indexed: 09/10/2024] Open
Abstract
Objectives The aim of the study is to describe the user experiences of a nationwide digital decision support system (DDSS). Summary of background data DDSSs have the potential to improve the quality and safety of healthcare services by supporting clinical decision-making with evidence-based recommendations. Due to a lack of knowledge, it is difficult to assess whether DDSSs are fulfilling their purpose. In Estonia, a nationwide DDSS for general practitioners (GPs) was implemented in 2020. To understand the impact of DDSS on the quality of care in the Estonian context and meet the demands of healthcare, it is necessary to gather information about the experiences of the users. This is the first study that examines the experiences of GPs on the use of DDSS nationwide. Methods A qualitative descriptive study was conducted based on snowball sampling. Semi-structured interviews were performed in February-March 2022 with nine GPs. Data were analyzed by thematic analysis. A total of six themes and 16 subthemes emerged from the data. Results A total of six themes and 16 subthemes emerged from the data. The following themes were identified: user-friendliness, DDSS use in clinical practice, benefits of the DDSS, and the impact of the DDSS on GPs' work, barriers to using the DDSS, and suggestions for improving the user experience. The results of the study are important, as they address and contribute to the relevant aspects of digital health in primary care. Conclusion GPs shared their individual user experiences, including user-perceived barriers and enabling factors that influence the implementation and use of a decision support system in primary care settings. It is revealed that GPs have different benefits and barriers depending on the topic discussed. Future research should evaluate the functioning of the DDSS and the quality of the decisions it provides by observing and evaluating patient records. Systematic user experiences need to be collected and examined to ensure the usability and sustainability of the DDSS.
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Affiliation(s)
- Jekaterina Šteinmiller
- Department of Healthcare Technologies, School of IT, Tallinn University of Technology, Tallinn, Estonia
| | - Peeter Ross
- Department of Healthcare Technologies, School of IT, Tallinn University of Technology, Tallinn, Estonia
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Granviken F, Meisingset I, Vasseljen O, Bach K, Bones AF, Klevanger NE. Acceptance and use of a clinical decision support system in musculoskeletal pain disorders - the SupportPrim project. BMC Med Inform Decis Mak 2023; 23:293. [PMID: 38114970 PMCID: PMC10731802 DOI: 10.1186/s12911-023-02399-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 12/08/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND We have developed a clinical decision support system (CDSS) based on methods from artificial intelligence to support physiotherapists and patients in the decision-making process of managing musculoskeletal (MSK) pain disorders in primary care. The CDSS finds the most similar successful patients from the past to give treatment recommendations for a new patient. Using previous similar patients with successful outcomes to advise treatment moves management of MSK pain patients from one-size fits all recommendations to more individually tailored treatment. This study aimed to summarise the development and explore the acceptance and use of the CDSS for MSK pain patients. METHODS This qualitative study was carried out in the Norwegian physiotherapy primary healthcare sector between October and November 2020, ahead of a randomised controlled trial. We included four physiotherapists and three of their patients, in total 12 patients, with musculoskeletal pain in the neck, shoulder, back, hip, knee or complex pain. We conducted semi-structured telephone interviews with all participants. The interviews were analysed using the Framework Method. RESULTS Overall, both the physiotherapists and patients found the system acceptable and usable. Important findings from the analysis of the interviews were that the CDSS was valued as a preparatory and exploratory tool, facilitating the therapeutic relationship. However, the physiotherapists used the system mainly to support their previous and current practice rather than involving patients to a greater extent in decisions and learning from previous successful patients. CONCLUSIONS The CDSS was acceptable and usable to both the patients and physiotherapists. However, the system appeared not to considerably influence the physiotherapists' clinical reasoning and choice of treatment based on information from most similar successful patients. This could be due to a smaller than optimal number of previous patients in the CDSS or insufficient clinical implementation. Extensive training of physiotherapists should not be underestimated to build understanding and trust in CDSSs.
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Affiliation(s)
- Fredrik Granviken
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, Trondheim, 7491, Norway.
- Clinic of Rehabilitation, St. Olavs Hospital, Trondheim, Norway.
| | - Ingebrigt Meisingset
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, Trondheim, 7491, Norway
- Unit for Physiotherapy Services, Trondheim Municipality, Trondheim, Norway
| | - Ottar Vasseljen
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, Trondheim, 7491, Norway
| | - Kerstin Bach
- Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Anita Formo Bones
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, Trondheim, 7491, Norway
| | - Nina Elisabeth Klevanger
- Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Postboks 8905, Trondheim, 7491, Norway
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Tokgöz P, Hafner J, Dockweiler C. [Factors influencing the implementation of AI-based decision support systems for antibiotic prescription in hospitals: a qualitative analysis from the perspective of health professionals]. DAS GESUNDHEITSWESEN 2023; 85:1220-1228. [PMID: 37451276 PMCID: PMC10713341 DOI: 10.1055/a-2098-3108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
BACKGROUND Decision support systems based on artificial intelligence might optimize antibiotic prescribing in hospitals and prevent the development of antimicrobial resistance. The aim of this study was to identify impeding and facilitating factors for successful implementation from the perspective of health professionals. METHODS Problem-centered individual interviews were conducted with health professionals working in hospitals. Data evaluation was based on the structured qualitative content analysis according Kuckartz. RESULTS Attitudes of health professionals were presented along the Human-Organization -Technology-fit model. Technological and organizational themes were the most important factors for system implementation. Especially, compatibility with existing systems and user-friendliness were seen to play a major role in successful implementation. Additionally, the training of potential users and the technical equipment of the organization were considered essential. Finally, the importance of promoting technical skills of potential users in the long term and creating trust in the benefits of the system were highlighted. CONCLUSION The identified factors provide a basis for prioritizing and quantifying needs and attitudes in a next step. It becomes clear that, beside technological factors, attention to context-specific and user-related conditions are of fundamental importance to ensure successful implementation and system trust in the long term.
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Affiliation(s)
- Pinar Tokgöz
- Department für Digitale Gesundheitswissenschaften und
Biomedizin; Professur für Digital Public Health, Universität
Siegen Fakultät V Lebenswissenschaftliche Fakultät,
Germany
| | - Jessica Hafner
- Department für Digitale Gesundheitswissenschaften und
Biomedizin; Professur für Digital Public Health, Universität
Siegen Fakultät V Lebenswissenschaftliche Fakultät,
Germany
| | - Christoph Dockweiler
- Department für Digitale Gesundheitswissenschaften und
Biomedizin; Professur für Digital Public Health, Universität
Siegen Fakultät V Lebenswissenschaftliche Fakultät,
Germany
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Vijayakumar S, Lee VV, Leong QY, Hong SJ, Blasiak A, Ho D. Physicians' Perspectives on AI in Clinical Decision Support Systems: Interview Study of the CURATE.AI Personalized Dose Optimization Platform. JMIR Hum Factors 2023; 10:e48476. [PMID: 37902825 PMCID: PMC10644191 DOI: 10.2196/48476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 08/24/2023] [Accepted: 09/10/2023] [Indexed: 10/31/2023] Open
Abstract
BACKGROUND Physicians play a key role in integrating new clinical technology into care practices through user feedback and growth propositions to developers of the technology. As physicians are stakeholders involved through the technology iteration process, understanding their roles as users can provide nuanced insights into the workings of these technologies that are being explored. Therefore, understanding physicians' perceptions can be critical toward clinical validation, implementation, and downstream adoption. Given the increasing prevalence of clinical decision support systems (CDSSs), there remains a need to gain an in-depth understanding of physicians' perceptions and expectations toward their downstream implementation. This paper explores physicians' perceptions of integrating CURATE.AI, a novel artificial intelligence (AI)-based and clinical stage personalized dosing CDSSs, into clinical practice. OBJECTIVE This study aims to understand physicians' perspectives of integrating CURATE.AI for clinical work and to gather insights on considerations of the implementation of AI-based CDSS tools. METHODS A total of 12 participants completed semistructured interviews examining their knowledge, experience, attitudes, risks, and future course of the personalized combination therapy dosing platform, CURATE.AI. Interviews were audio recorded, transcribed verbatim, and coded manually. The data were thematically analyzed. RESULTS Overall, 3 broad themes and 9 subthemes were identified through thematic analysis. The themes covered considerations that physicians perceived as significant across various stages of new technology development, including trial, clinical implementation, and mass adoption. CONCLUSIONS The study laid out the various ways physicians interpreted an AI-based personalized dosing CDSS, CURATE.AI, for their clinical practice. The research pointed out that physicians' expectations during the different stages of technology exploration can be nuanced and layered with expectations of implementation that are relevant for technology developers and researchers.
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Affiliation(s)
- Smrithi Vijayakumar
- The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - V Vien Lee
- The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - Qiao Ying Leong
- The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - Soo Jung Hong
- Department of Communications and New Media, National University of Singapore, Singapore, Singapore
| | - Agata Blasiak
- The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Dean Ho
- The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
- The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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Kotsis F, Bächle H, Altenbuchinger M, Dönitz J, Njipouombe Nsangou YA, Meiselbach H, Kosch R, Salloch S, Bratan T, Zacharias HU, Schultheiss UT. Expectation of clinical decision support systems: a survey study among nephrologist end-users. BMC Med Inform Decis Mak 2023; 23:239. [PMID: 37884906 PMCID: PMC10605935 DOI: 10.1186/s12911-023-02317-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 09/29/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are crucial for long-term patient outcomes. Physicians need to integrate different data levels, e.g., clinical parameters, biomarkers, and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. Knowledge about the awareness and implementation of CDSS in Germany within the field of nephrology is scarce. PURPOSE Nephrologists' attitude towards any CDSS and potential CDSS features of interest, like adverse event prediction algorithms, is important for a successful implementation. This survey investigates nephrologists' experiences with and expectations towards a useful CDSS for daily medical routine in the outpatient setting. METHODS The 38-item questionnaire survey was conducted either by telephone or as a do-it-yourself online interview amongst nephrologists across all of Germany. Answers were collected and analysed using the Electronic Data Capture System REDCap, as well as Stata SE 15.1, and Excel. The survey consisted of four modules: experiences with CDSS (M1), expectations towards a helpful CDSS (M2), evaluation of adverse event prediction algorithms (M3), and ethical aspects of CDSS (M4). Descriptive statistical analyses of all questions were conducted. RESULTS The study population comprised 54 physicians, with a response rate of about 80-100% per question. Most participants were aged between 51-60 years (45.1%), 64% were male, and most participants had been working in nephrology out-patient clinics for a median of 10.5 years. Overall, CDSS use was poor (81.2%), often due to lack of knowledge about existing CDSS. Most participants (79%) believed CDSS to be helpful in the management of CKD patients with a high willingness to try out a CDSS. Of all adverse event prediction algorithms, prediction of CKD progression (97.8%) and in-silico simulations of disease progression when changing, e. g., lifestyle or medication (97.7%) were rated most important. The spectrum of answers on ethical aspects of CDSS was diverse. CONCLUSION This survey provides insights into experience with and expectations of out-patient nephrologists on CDSS. Despite the current lack of knowledge on CDSS, the willingness to integrate CDSS into daily patient care, and the need for adverse event prediction algorithms was high.
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Affiliation(s)
- Fruzsina Kotsis
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Helena Bächle
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Michael Altenbuchinger
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
| | - Jürgen Dönitz
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
- Institute of Computational Biology, Helmholtz Zentrum München, Munich, Germany
| | | | - Heike Meiselbach
- Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Robin Kosch
- Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany
| | - Sabine Salloch
- Institute for Ethics, History and Philosophy of Medicine, Hannover Medical School, Hanover, Germany
| | - Tanja Bratan
- Competence Center Emerging Technologies, Fraunhofer Institute for Systems and Innovation Research ISI, Karlsruhe, Germany
| | - Helena U Zacharias
- Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Hanover, Germany
| | - Ulla T Schultheiss
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
- Department of Medicine IV - Nephrology and Primary Care, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.
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Ng HJH, Kansal A, Abdul Naseer JF, Hing WC, Goh CJM, Poh H, D’souza JLA, Lim EL, Tan G. Optimizing Best Practice Advisory alerts in electronic medical records with a multi-pronged strategy at a tertiary care hospital in Singapore. JAMIA Open 2023; 6:ooad056. [PMID: 37538232 PMCID: PMC10393867 DOI: 10.1093/jamiaopen/ooad056] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 05/23/2023] [Accepted: 07/26/2023] [Indexed: 08/05/2023] Open
Abstract
Objective Clinical decision support (CDS) alerts can aid in improving patient care. One CDS functionality is the Best Practice Advisory (BPA) alert notification system, wherein BPA alerts are automated alerts embedded in the hospital's electronic medical records (EMR). However, excessive alerts can change clinician behavior; redundant and repetitive alerts can contribute to alert fatigue. Alerts can be optimized through a multipronged strategy. Our study aims to describe these strategies adopted and evaluate the resultant BPA alert optimization outcomes. Materials and Methods This retrospective single-center study was done at Jurong Health Campus. Aggregated, anonymized data on patient demographics and alert statistics were collected from January 1, 2018 to December 31, 2021. "Preintervention" period was January 1-December 31, 2018, and "postintervention" period was January 1-December 31, 2021. The intervention period was the intervening period. Categorical variables were reported as frequencies and proportions and compared using the chi-square test. Continuous data were reported as median (interquartile range, IQR) and compared using the Wilcoxon rank-sum test. Statistical significance was defined at P < .05. Results There was a significant reduction of 59.6% in the total number of interruptive BPA alerts, despite an increase in the number of unique BPAs from 54 to 360 from pre- to postintervention. There was a 74% reduction in the number of alerts from the 7 BPAs that were optimized from the pre- to postintervention period. There was a significant increase in percentage of overall interruptive BPA alerts with action taken (8 [IQR 7.7-8.4] to 54.7 [IQR 52.5-58.9], P-value < .05) and optimized BPAs with action taken (32.6 [IQR 32.3-32.9] to 72.6 [IQR 64.3-73.4], P-value < .05). We estimate that the reduction in alerts saved 3600 h of providers' time per year. Conclusions A significant reduction in interruptive alert volume, and a significant increase in action taken rates despite manifold increase in the number of unique BPAs could be achieved through concentrated efforts focusing on governance, data review, and visualization using a system-embedded tool, combined with the CDS Five Rights framework, to optimize alerts. Improved alert compliance was likely multifactorial-due to decreased repeated alert firing for the same patient; better awareness due to stakeholders' involvement; and less fatigue since unnecessary alerts were removed. Future studies should prospectively focus on patients' clinical chart reviews to assess downstream effects of various actions taken, identify any possibility of harm, and collect end-user feedback regarding the utility of alerts.
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Affiliation(s)
- Hannah Jia Hui Ng
- Corresponding Author: Hannah Jia Hui Ng, MBBS, MRCS, Department of Medical Informatics, Ng Teng Fong General Hospital, 1 Jurong East Street 21, Singapore 609606, Singapore;
| | - Amit Kansal
- Department of Medical Informatics, Ng Teng Fong General Hospital, Singapore, Singapore
| | | | - Wee Chuan Hing
- Department of Medical Informatics, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Carmen Jia Man Goh
- Department of Medical Informatics, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Hermione Poh
- Department of Medical Informatics, Ng Teng Fong General Hospital, Singapore, Singapore
| | | | - Er Luen Lim
- Department of Medical Informatics, Ng Teng Fong General Hospital, Singapore, Singapore
| | - Gamaliel Tan
- Department of Medical Informatics, Ng Teng Fong General Hospital, Singapore, Singapore
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Albahar F, Abu-Farha RK, Alshogran OY, Alhamad H, Curtis CE, Marriott JF. Healthcare Professionals’ Perceptions, Barriers, and Facilitators towards Adopting Computerised Clinical Decision Support Systems in Antimicrobial Stewardship in Jordanian Hospitals. Healthcare (Basel) 2023; 11:healthcare11060836. [PMID: 36981493 PMCID: PMC10047934 DOI: 10.3390/healthcare11060836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 02/24/2023] [Accepted: 03/08/2023] [Indexed: 03/14/2023] Open
Abstract
Understanding healthcare professionals’ perceptions towards a computerised decision support system (CDSS) may provide a platform for the determinants of the successful adoption and implementation of CDSS. This cross-sectional study examined healthcare professionals’ perceptions, barriers, and facilitators to adopting a CDSS for antibiotic prescribing in Jordanian hospitals. This study was conducted among healthcare professionals in Jordan’s two tertiary and teaching hospitals over four weeks (June–July 2021). Data were collected in a paper-based format from senior and junior prescribers and non-prescribers (n = 254) who agreed to complete a questionnaire. The majority (n = 184, 72.4%) were aware that electronic prescribing and electronic health record systems could be used specifically to facilitate antibiotic use and prescribing. The essential facilitator made CDSS available in a portable format (n = 224, 88.2%). While insufficient training to use CDSS was the most significant barrier (n = 175, 68.9%). The female providers showed significantly lower awareness (p = 0.006), and the nurses showed significantly higher awareness (p = 0.041) about using electronic prescribing and electronic health record systems. This study examined healthcare professionals’ perceptions of adopting CDSS in antimicrobial stewardship (AMS) and shed light on the perceived barriers and facilitators to adopting CDSS in AMS, reducing antibiotic resistance, and improving patient safety. Furthermore, results would provide a framework for other hospital settings concerned with implementing CDSS in AMS and inform policy decision-makers to react by implementing the CDSS system in Jordan and globally. Future studies should concentrate on establishing policies and guidelines and a framework to examine the adoption of the CDSS for AMS.
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Affiliation(s)
- Fares Albahar
- Department of Clinical Pharmacy, Faculty of Pharmacy, Zarqa University, P.O. Box 2000, Zarqa 13110, Jordan
- Correspondence:
| | - Rana K. Abu-Farha
- Department of Clinical Pharmacy and Therapeutics, Faculty of Pharmacy, Applied Science Private University, P.O. Box 541350, Amman 11937, Jordan
| | - Osama Y. Alshogran
- Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan
| | - Hamza Alhamad
- Department of Clinical Pharmacy, Faculty of Pharmacy, Zarqa University, P.O. Box 2000, Zarqa 13110, Jordan
| | - Chris E. Curtis
- Department of Pharmacy, College of Medical & Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK
| | - John F. Marriott
- Department of Pharmacy, College of Medical & Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK
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Seliaman ME, Albahly MS. The Reasons for Physicians and Pharmacists' Acceptance of Clinical Support Systems in Saudi Arabia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3132. [PMID: 36833832 PMCID: PMC9962582 DOI: 10.3390/ijerph20043132] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 01/31/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
This research aims to identify the technological and non-technological factors influencing user acceptance of the CDSS in a group of healthcare facilities in Saudi Arabia. The study proposes an integrated model that indicates the factors to be considered when designing and evaluating CDSS. This model is developed by integrating factors from the "Fit between Individuals, Task, and Technology" (FITT) framework into the three domains of the human, organization, and technology-fit (HOT-fit) model. The resulting FITT-HOT-fit integrated model was tested using a quantitative approach to evaluate the currently implemented CDSS as a part of Hospital Information System BESTCare 2.0 in the Saudi Ministry of National Guard Health Affairs. For data collection, a survey questionnaire was conducted at all Ministry of National Guard Health Affairs hospitals. Then, the collected survey data were analyzed using Structural Equation Modeling (SEM). This analysis included measurement instrument reliability, discriminant validity, convergent validity, and hypothesis testing. Moreover, a CDSS usage data sample was extracted from the data warehouse to be analyzed as an additional data source. The results of the hypotheses test show that usability, availability, and medical history accessibility are critical factors influencing user acceptance of CDSS. This study provides prudence about healthcare facilities and their higher management to adopt CDSS.
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Affiliation(s)
- Mohamed Elhassan Seliaman
- Department of Information Systems, College of Computer Science and Information Technology, King Faisal University, Al Ahsa 31982, Saudi Arabia
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12
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Berge GT, Granmo OC, Tveit TO, Munkvold BE, Ruthjersen AL, Sharma J. Machine learning-driven clinical decision support system for concept-based searching: a field trial in a Norwegian hospital. BMC Med Inform Decis Mak 2023; 23:5. [PMID: 36627624 PMCID: PMC9832658 DOI: 10.1186/s12911-023-02101-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Natural language processing (NLP) based clinical decision support systems (CDSSs) have demonstrated the ability to extract vital information from patient electronic health records (EHRs) to facilitate important decision support tasks. While obtaining accurate, medical domain interpretable results is crucial, it is demanding because real-world EHRs contain many inconsistencies and inaccuracies. Further, testing of such machine learning-based systems in clinical practice has received limited attention and are yet to be accepted by clinicians for regular use. METHODS We present our results from the evaluation of an NLP-driven CDSS developed and implemented in a Norwegian Hospital. The system incorporates unsupervised and supervised machine learning combined with rule-based algorithms for clinical concept-based searching to identify and classify allergies of concern for anesthesia and intensive care. The system also implements a semi-supervised machine learning approach to automatically annotate medical concepts in the narrative. RESULTS Evaluation of system adoption was performed by a mixed methods approach applying The Unified Theory of Acceptance and Use of Technology (UTAUT) as a theoretical lens. Most of the respondents demonstrated a high degree of system acceptance and expressed a positive attitude towards the system in general and intention to use the system in the future. Increased detection of patient allergies, and thus improved quality of practice and patient safety during surgery or ICU stays, was perceived as the most important advantage of the system. CONCLUSIONS Our combined machine learning and rule-based approach benefits system performance, efficiency, and interpretability. The results demonstrate that the proposed CDSS increases detection of patient allergies, and that the system received high-level acceptance by the clinicians using it. Useful recommendations for further system improvements and implementation initiatives are reducing the quantity of alarms, expansion of the system to include more clinical concepts, closer EHR system integration, and more workstations available at point of care.
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Affiliation(s)
- G. T. Berge
- grid.23048.3d0000 0004 0417 6230Department of Information Systems, University of Agder, Kristiansand, Norway ,grid.417290.90000 0004 0627 3712Department of Technology and eHealth, Sørlandet Hospital Trust, Kristiansand, Norway
| | - O. C. Granmo
- grid.23048.3d0000 0004 0417 6230Department of ICT, University of Agder, Grimstad, Norway
| | - T. O. Tveit
- grid.417290.90000 0004 0627 3712Department of Technology and eHealth, Sørlandet Hospital Trust, Kristiansand, Norway ,grid.417290.90000 0004 0627 3712Department of Anaesthesia and Intensive Care, Sørlandet Hospital Trust, Kristiansand, Norway ,grid.417290.90000 0004 0627 3712Research Department, Sørlandet Hospital Trust, Kristiansand, Norway
| | - B. E. Munkvold
- grid.23048.3d0000 0004 0417 6230Department of Information Systems, University of Agder, Kristiansand, Norway
| | - A. L. Ruthjersen
- grid.417290.90000 0004 0627 3712Department of Technology and eHealth, Sørlandet Hospital Trust, Kristiansand, Norway
| | - J. Sharma
- grid.417290.90000 0004 0627 3712Department of Technology and eHealth, Sørlandet Hospital Trust, Kristiansand, Norway ,grid.23048.3d0000 0004 0417 6230Department of ICT, University of Agder, Grimstad, Norway
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Sung M, He J, Zhou Q, Chen Y, Ji JS, Chen H, Li Z. Using an Integrated Framework to Investigate the Facilitators and Barriers of Health Information Technology Implementation in Noncommunicable Disease Management: Systematic Review. J Med Internet Res 2022; 24:e37338. [PMID: 35857364 PMCID: PMC9350822 DOI: 10.2196/37338] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/25/2022] [Accepted: 06/27/2022] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Noncommunicable disease (NCD) management is critical for reducing attributable health burdens. Although health information technology (HIT) is a crucial strategy to improve chronic disease management, many health care systems have failed in implementing HIT. There has been a lack of research on the implementation process of HIT for chronic disease management. OBJECTIVE We aimed to identify the barriers and facilitators of HIT implementation, analyze how these factors influence the implementation process, and identify key areas for future action. We will develop a framework for understanding implementation determinants to synthesize available evidence. METHODS We conducted a systematic review to understand the barriers and facilitators of the implementation process. We searched MEDLINE, Cochrane, Embase, Scopus, and CINAHL for studies published between database inception and May 5, 2022. Original studies involving HIT-related interventions for NCD management published in peer-reviewed journals were included. Studies that did not discuss relevant outcome measures or did not have direct contact with or observation of stakeholders were excluded. The analysis was conducted in 2 parts. In part 1, we analyzed how the intrinsic attributes of HIT interventions affect the successfulness of implementation by using the intervention domain of the Consolidated Framework for Implementation Research (CFIR). In part 2, we focused on the extrinsic factors of HIT using an integrated framework, which was developed based on the CFIR and the levels of change framework by Ferlie and Shortell. RESULTS We identified 51 papers with qualitative, mixed-method, and cross-sectional methodologies. Included studies were heterogeneous regarding disease populations and HIT interventions. In part 1, having a relative advantage over existing health care systems was the most prominent intrinsic facilitator (eg, convenience, improvement in quality of care, and increase in access). Poor usability was the most noted intrinsic barrier of HIT. In part 2, we mapped the various factors of implementation to the integrated framework (the coordinates are shown as level of change-CFIR). The key barriers to the extrinsic factors of HIT included health literacy and lack of digital skills (individual-characteristics of individuals). The key facilitators included physicians' suggestions, cooperation (interpersonal-process), integration into a workflow, and adequate management of data (organizational-inner setting). The importance of health data security was identified. Self-efficacy issues of patients and organizational readiness for implementation were highlighted. CONCLUSIONS Internal factors of HIT and external human factors of implementation interplay in HIT implementation for chronic disease management. Strategies for improvement include ensuring HIT has a relative advantage over existing health care; tackling usability issues; and addressing underlying socioeconomic, interpersonal, and organizational conditions. Further research should focus on studying various stakeholders, such as service providers and administrative workforces; various disease populations, such as those with obesity and mental diseases; and various countries, including low- and middle-income countries.
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Affiliation(s)
- Meekang Sung
- College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Jinyu He
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Qi Zhou
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Yaolong Chen
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Haotian Chen
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Zhihui Li
- Vanke School of Public Health, Tsinghua University, Beijing, China.,Institute for Healthy China, Tsinghua Universtiy, Beijing, China
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Artificial Intelligence: A Shifting Paradigm in Cardio-Cerebrovascular Medicine. J Clin Med 2021; 10:jcm10235710. [PMID: 34884412 PMCID: PMC8658222 DOI: 10.3390/jcm10235710] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 12/02/2021] [Indexed: 12/21/2022] Open
Abstract
The future of healthcare is an organic blend of technology, innovation, and human connection. As artificial intelligence (AI) is gradually becoming a go-to technology in healthcare to improve efficiency and outcomes, we must understand our limitations. We should realize that our goal is not only to provide faster and more efficient care, but also to deliver an integrated solution to ensure that the care is fair and not biased to a group of sub-population. In this context, the field of cardio-cerebrovascular diseases, which encompasses a wide range of conditions-from heart failure to stroke-has made some advances to provide assistive tools to care providers. This article aimed to provide an overall thematic review of recent development focusing on various AI applications in cardio-cerebrovascular diseases to identify gaps and potential areas of improvement. If well designed, technological engines have the potential to improve healthcare access and equitability while reducing overall costs, diagnostic errors, and disparity in a system that affects patients and providers and strives for efficiency.
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15
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van Gils AM, Visser LN, Hendriksen HM, Georges J, Muller M, Bouwman FH, van der Flier WM, Rhodius-Meester HF. Assessing the Views of Professionals, Patients, and Care Partners Concerning the Use of Computer Tools in Memory Clinics: International Survey Study. JMIR Form Res 2021; 5:e31053. [PMID: 34870612 PMCID: PMC8686488 DOI: 10.2196/31053] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/07/2021] [Accepted: 09/18/2021] [Indexed: 12/20/2022] Open
Abstract
Background Computer tools based on artificial intelligence could aid clinicians in memory clinics in several ways, such as by supporting diagnostic decision-making, web-based cognitive testing, and the communication of diagnosis and prognosis. Objective This study aims to identify the preferences as well as the main barriers and facilitators related to using computer tools in memory clinics for all end users, that is, clinicians, patients, and care partners. Methods Between July and October 2020, we sent out invitations to a web-based survey to clinicians using the European Alzheimer’s Disease Centers network and the Dutch Memory Clinic network, and 109 clinicians participated (mean age 45 years, SD 10; 53/109, 48.6% female). A second survey was created for patients and care partners. They were invited via Alzheimer Europe, Alzheimer’s Society United Kingdom, Amsterdam Dementia Cohort, and Amsterdam Aging Cohort. A total of 50 patients with subjective cognitive decline, mild cognitive impairment, or dementia (mean age 73 years, SD 8; 17/34, 34% female) and 46 care partners (mean age 65 years, SD 12; 25/54, 54% female) participated in this survey. Results Most clinicians reported a willingness to use diagnostic (88/109, 80.7%) and prognostic (83/109, 76.1%) computer tools. User-friendliness (71/109, 65.1%); Likert scale mean 4.5, SD 0.7), and increasing diagnostic accuracy (76/109, 69.7%; mean 4.3, SD 0.7) were reported as the main factors stimulating the adoption of a tool. Tools should also save time and provide clear information on reliability and validity. Inadequate integration with electronic patient records (46/109, 42.2%; mean 3.8, SD 1.0) and fear of losing important clinical information (48/109, 44%; mean 3.7, SD 1.2) were most frequently indicated as barriers. Patients and care partners were equally positive about the use of computer tools by clinicians, both for diagnosis (69/96, 72%) and prognosis (73/96, 76%). In addition, most of them thought favorably regarding the possibility of using the tools themselves. Conclusions This study showed that computer tools in memory clinics are positively valued by most end users. For further development and implementation, it is essential to overcome the technical and practical barriers of a tool while paying utmost attention to its reliability and validity.
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Affiliation(s)
- Aniek M van Gils
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands
| | - Leonie Nc Visser
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands.,Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
| | - Heleen Ma Hendriksen
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands
| | | | - Majon Muller
- Department of Internal Medicine, Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands
| | - Femke H Bouwman
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands
| | - Wiesje M van der Flier
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands.,Department of Epidemiology and Data Science, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands
| | - Hanneke Fm Rhodius-Meester
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands.,Department of Internal Medicine, Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC, Location VUmc, Amsterdam, Netherlands
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17
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Olakotan OO, Mohd Yusof M. The appropriateness of clinical decision support systems alerts in supporting clinical workflows: A systematic review. Health Informatics J 2021; 27:14604582211007536. [PMID: 33853395 DOI: 10.1177/14604582211007536] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
A CDSS generates a high number of inappropriate alerts that interrupt the clinical workflow. As a result, clinicians silence, disable, or ignore alerts, thereby undermining patient safety. Therefore, the effectiveness and appropriateness of CDSS alerts need to be evaluated. A systematic review was carried out to identify the factors that affect CDSS alert appropriateness in supporting clinical workflow. Seven electronic databases (PubMed, Scopus, ACM, Science Direct, IEEE, Ovid Medline, and Ebscohost) were searched for English language articles published between 1997 and 2018. Seventy six papers met the inclusion criteria, of which 26, 24, 15, and 11 papers are retrospective cohort, qualitative, quantitative, and mixed-method studies, respectively. The review highlights various factors influencing the appropriateness and efficiencies of CDSS alerts. These factors are categorized into technology, human, organization, and process aspects using a combination of approaches, including socio-technical framework, five rights of CDSS, and Lean. Most CDSS alerts were not properly designed based on human factor methods and principles, explaining high alert overrides in clinical practices. The identified factors and recommendations from the review may offer valuable insights into how CDSS alerts can be designed appropriately to support clinical workflow.
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Grossi A, Hoxhaj I, Gabutti I, Specchia ML, Cicchetti A, Boccia S, de Waure C. Hospital contextual factors affecting the implementation of health technologies: a systematic review. BMC Health Serv Res 2021; 21:407. [PMID: 33933068 PMCID: PMC8088675 DOI: 10.1186/s12913-021-06423-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 04/19/2021] [Indexed: 12/05/2022] Open
Abstract
Background To keep a high quality of assistance it is important for hospitals to invest in health technologies (HTs) that have the potential of improving health outcomes. Even though guidance exists on how HTs should be introduced, used and dismissed, there is a surprising gap in literature concerning the awareness of hospitals in the actual utilization of HTs. Methods We performed a systematic literature review of qualitative and quantitative studies aimed at investigating hospital contextual factors that influence the actual utilization of HTs. PubMed, Scopus, Web of Science, Econlit and Ovid Medline electronic databases were searched to retrieve articles published in English and Italian from January 2000 to January 2019. The quality of the included articles was assessed using the Critical Appraisal Skills Programme checklist for qualitative studies, Newcastle-Ottawa Scale for the cross-sectional studies and the Mixed Methods Appraisal Tool for mixed method studies. Results We included 33 articles, which were of moderate to high methodological quality. The included articles mostly addressed the contextual factors that impact the implementation of information and communication technologies (ICTs). Overall, for all HTs, the hospital contextual factors were part of four categories: hospital infrastructure, human resource management, financial resources and leadership styles. Conclusion Our systematic review reported that the contextual factors influencing the HTs utilization at hospital level are mainly explored for ICTs. Several factors should be considered when planning the implementation of a new HTs at hospital level. A potential publication bias might be present in our work, since we included articles published only in English and Italian Language, from January 2000 to January 2019. There remains a gap in the literature on the facilitators and barriers influencing the implementation and concrete utilization of medical and surgical HTs, suggesting the need for further studies for a better understanding. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-021-06423-2.
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Affiliation(s)
- Adriano Grossi
- Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Largo Francesco Vito, 1, 00168, Rome, Italy
| | - Ilda Hoxhaj
- Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Largo Francesco Vito, 1, 00168, Rome, Italy.
| | - Irene Gabutti
- Graduate School of Health Economics and Management (ALTEMS), Faculty of Economics, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Maria Lucia Specchia
- Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Largo Francesco Vito, 1, 00168, Rome, Italy.,Clinical Governance Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Americo Cicchetti
- Graduate School of Health Economics and Management (ALTEMS), Faculty of Economics, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Stefania Boccia
- Section of Hygiene, University Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Largo Francesco Vito, 1, 00168, Rome, Italy.,Department of Woman and Child Health and Public Health - Public Health Area, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Chiara de Waure
- Department of Medicine and Surgery, University of Perugia, Perugia, Italy
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Jansen-Kosterink S, van Velsen L, Cabrita M. Clinician acceptance of complex clinical decision support systems for treatment allocation of patients with chronic low back pain. BMC Med Inform Decis Mak 2021; 21:137. [PMID: 33906665 PMCID: PMC8077885 DOI: 10.1186/s12911-021-01502-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 04/09/2021] [Indexed: 11/10/2022] Open
Abstract
Background The uptake of complex clinical decision support systems (CDSS) in daily practice remains low, despite the proven potential to reduce medical errors and to improve the quality of care. To improve successful implementation of a complex CDSS this study aims to identify the factors that hinder, or alleviate the acceptance of, clinicians toward the use of a complex CDSS for treatment allocation of patients with chronic low back pain. Methods We tested a research model in which the intention to use a CDSS by clinicians is influenced by the perceived usefulness; this usefulness, in turn is influenced by the perceived service benefits and perceived service risks. An online survey was created to test our research model and the data was analysed using Partial Least Squares Structural Equation Modelling. The study population consisted of clinicians. The online questionnaire started with demographic questions and continued with a video animation of the complex CDSS followed by the set of measurement items. The online questionnaire ended with two open questions enquiring the reasons to use and not use, a complex CDSS. Results Ninety-eight participants (46% general practitioners, 25% primary care physical therapists, and 29% clinicians at a rehabilitation centre) fully completed the questionnaire. Fifty-two percent of the respondents were male. The average age was 48 years (SD ± 12.2). The causal model suggests that perceived usefulness is the main factor contributing to the intention to use a complex CDSS. Perceived service benefits and risks are both significant antecedents of perceived usefulness and perceived service risks are affected by the perceived threat to autonomy and trusting beliefs, particularly benevolence and competence. Conclusions To improve the acceptance of complex CDSSs it is important to address the risks, but the main focus during the implementation phase should be on the expected improvements in patient outcomes and the overall gain for clinicians. Our results will help the development of complex CDSSs that fit more into the daily clinical practice of clinicians.
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Affiliation(s)
- Stephanie Jansen-Kosterink
- eHealth Group, Roessingh Research and Development, Roessinghsbleekweg 33b, 7522 AL, Enschede, The Netherlands. .,Faculty of Electrical Engineering, Mathematics and Computer Science, Telemedicine Group, University of Twente, Enschede, the Netherlands.
| | - Lex van Velsen
- eHealth Group, Roessingh Research and Development, Roessinghsbleekweg 33b, 7522 AL, Enschede, The Netherlands.,Faculty of Electrical Engineering, Mathematics and Computer Science, Telemedicine Group, University of Twente, Enschede, the Netherlands
| | - Miriam Cabrita
- eHealth Group, Roessingh Research and Development, Roessinghsbleekweg 33b, 7522 AL, Enschede, The Netherlands.,Faculty of Electrical Engineering, Mathematics and Computer Science, Telemedicine Group, University of Twente, Enschede, the Netherlands
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Jauk S, Kramer D, Avian A, Berghold A, Leodolter W, Schulz S. Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study. J Med Syst 2021; 45:48. [PMID: 33646459 PMCID: PMC7921052 DOI: 10.1007/s10916-021-01727-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 02/18/2021] [Indexed: 12/02/2022]
Abstract
Early identification of patients with life-threatening risks such as delirium is crucial in order to initiate preventive actions as quickly as possible. Despite intense research on machine learning for the prediction of clinical outcomes, the acceptance of the integration of such complex models in clinical routine remains unclear. The aim of this study was to evaluate user acceptance of an already implemented machine learning-based application predicting the risk of delirium for in-patients. We applied a mixed methods design to collect opinions and concerns from health care professionals including physicians and nurses who regularly used the application. The evaluation was framed by the Technology Acceptance Model assessing perceived ease of use, perceived usefulness, actual system use and output quality of the application. Questionnaire results from 47 nurses and physicians as well as qualitative results of four expert group meetings rated the overall usefulness of the delirium prediction positively. For healthcare professionals, the visualization and presented information was understandable, the application was easy to use and the additional information for delirium management was appreciated. The application did not increase their workload, but the actual system use was still low during the pilot study. Our study provides insights into the user acceptance of a machine learning-based application supporting delirium management in hospitals. In order to improve quality and safety in healthcare, computerized decision support should predict actionable events and be highly accepted by users.
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Affiliation(s)
- Stefanie Jauk
- Steiermärkische Krankenanstaltengesellschaft m.b.H. (KAGes), Information and Process Management, Graz, Austria. .,Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036, Graz, Austria.
| | - Diether Kramer
- Steiermärkische Krankenanstaltengesellschaft m.b.H. (KAGes), Information and Process Management, Graz, Austria
| | - Alexander Avian
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036, Graz, Austria
| | - Andrea Berghold
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036, Graz, Austria
| | - Werner Leodolter
- Steiermärkische Krankenanstaltengesellschaft m.b.H. (KAGes), Information and Process Management, Graz, Austria
| | - Stefan Schulz
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036, Graz, Austria
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Shahmoradi L, Safdari R, Ahmadi H, Zahmatkeshan M. Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects. Med J Islam Repub Iran 2021; 35:27. [PMID: 34169039 PMCID: PMC8214039 DOI: 10.47176/mjiri.35.27] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2019] [Indexed: 01/24/2023] Open
Abstract
Background: Clinical decision support systems (CDSSs) interventions were used to improve the life quality and safety in patients and also to improve practitioner performance, especially in the field of medication. Therefore, the aim of the paper was to summarize the available evidence on the impact, outcomes and significant factors on the implementation of CDSS in the field of medicine. Methods: This study is a systematic literature review. PubMed, Cochrane Library, Web of Science, Scopus, EMBASE, and ProQuest were investigated by 15 February 2017. The inclusion requirements were met by 98 papers, from which 13 had described important factors in the implementation of CDSS, and 86 were medicated-related. We categorized the system in terms of its correlation with medication in which a system was implemented, and our intended results were examined. In this study, the process outcomes (such as; prescription, drug-drug interaction, drug adherence, etc.), patient outcomes, and significant factors affecting the implementation of CDSS were reviewed. Results: We found evidence that the use of medication-related CDSS improves clinical outcomes. Also, significant results were obtained regarding the reduction of prescription errors, and the improvement in quality and safety of medication prescribed. Conclusion: The results of this study show that, although computer systems such as CDSS may cause errors, in most cases, it has helped to improve prescribing, reduce side effects and drug interactions, and improve patient safety. Although these systems have improved the performance of practitioners and processes, there has not been much research on the impact of these systems on patient outcomes.
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Affiliation(s)
- Leila Shahmoradi
- Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Reza Safdari
- Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Hossein Ahmadi
- OIM Department, Aston Business School, Aston University, Birmingham B4 7ET, United Kingdom
| | - Maryam Zahmatkeshan
- Noncommunicable Diseases Research Center, School of Medicine, Fasa University of Medical Sciences, Fasa, Iran
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Laka M, Milazzo A, Merlin T. Factors That Impact the Adoption of Clinical Decision Support Systems (CDSS) for Antibiotic Management. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18041901. [PMID: 33669353 PMCID: PMC7920296 DOI: 10.3390/ijerph18041901] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 02/08/2021] [Accepted: 02/11/2021] [Indexed: 01/22/2023]
Abstract
The study evaluated individual and setting-specific factors that moderate clinicians’ perception regarding use of clinical decision support systems (CDSS) for antibiotic management. A cross-sectional online survey examined clinicians’ perceptions about CDSS implementation for antibiotic management in Australia. Multivariable logistic regression determined the association between drivers of CDSS adoption and different moderators. Clinical experience, CDSS use and care setting were important predictors of clinicians’ perception concerning CDSS adoption. Compared to nonusers, CDSS users were less likely to lack confidence in CDSS (OR = 0.63, 95%, CI = 0.32, 0.94) and consider it a threat to professional autonomy (OR = 0.47, 95%, CI = 0.08, 0.83). Conversely, there was higher likelihood in experienced clinicians (>20 years) to distrust CDSS (OR = 1.58, 95%, CI = 1.08, 2.23) due to fear of comprising their clinical judgement (OR = 1.68, 95%, CI = 1.27, 2.85). In primary care, clinicians were more likely to perceive time constraints (OR = 1.96, 95%, CI = 1.04, 3.70) and patient preference (OR = 1.84, 95%, CI = 1.19, 2.78) as barriers to CDSS adoption for antibiotic prescribing. Our findings provide differentiated understanding of the CDSS implementation landscape by identifying different individual, organisational and system-level factors that influence system adoption. The individual and setting characteristics can help understand the variability in CDSS adoption for antibiotic management in different clinicians.
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Affiliation(s)
- Mah Laka
- School of Public Health, University of Adelaide, Adelaide 5005, Australia; (M.L.); (A.M.)
| | - Adriana Milazzo
- School of Public Health, University of Adelaide, Adelaide 5005, Australia; (M.L.); (A.M.)
| | - Tracy Merlin
- Adelaide Health Technology Assessment (AHTA), School of Public Health, University of Adelaide, Adelaide 5005, Australia
- Correspondence: ; Tel.: +61-(8)-8313-3575
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Van Dort BA, Zheng WY, Sundar V, Baysari MT. Optimizing clinical decision support alerts in electronic medical records: a systematic review of reported strategies adopted by hospitals. J Am Med Inform Assoc 2021; 28:177-183. [PMID: 33186438 PMCID: PMC7810441 DOI: 10.1093/jamia/ocaa279] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 10/27/2020] [Indexed: 11/12/2022] Open
Abstract
OBJECTIVE To identify and summarize the current internal governance processes adopted by hospitals, as reported in the literature, for selecting, optimizing, and evaluating clinical decision support (CDS) alerts in order to identify effective approaches. MATERIALS AND METHODS Databases (Medline, Embase, CINAHL, Scopus, Web of Science, IEEE Xplore Digital Library, CADTH, and WorldCat) were searched to identify relevant papers published from January 2010 to April 2020. All paper types published in English that reported governance processes for selecting and/or optimizing CDS alerts in hospitals were included. RESULTS Eight papers were included in the review. Seven papers focused specifically on medication-related CDS alerts. All papers described the use of a multidisciplinary committee to optimize alerts. Other strategies included the use of clinician feedback, alert data, literature and drug references, and a visual dashboard. Six of the 8 papers reported evaluations of their CDS alert modifications following the adoption of optimization strategies, and of these, 5 reported a reduction in alert rate. CONCLUSIONS A multidisciplinary committee, often in combination with other approaches, was the most frequent strategy reported by hospitals to optimize their CDS alerts. Due to the limited number of published processes, variation in system changes, and evaluation results, we were unable to compare the effectiveness of different strategies, although employing multiple strategies appears to be an effective approach for reducing CDS alert numbers. We recommend hospitals report on descriptions and evaluations of governance processes to enable identification of effective strategies for optimization of CDS alerts in hospitals.
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Affiliation(s)
- Bethany A Van Dort
- Discipline of Biomedical Informatics and Digital Health, School of Medical Sciences, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Wu Yi Zheng
- Discipline of Biomedical Informatics and Digital Health, School of Medical Sciences, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
| | - Vivek Sundar
- Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia
| | - Melissa T Baysari
- Discipline of Biomedical Informatics and Digital Health, School of Medical Sciences, Charles Perkins Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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Abedi V, Khan A, Chaudhary D, Misra D, Avula V, Mathrawala D, Kraus C, Marshall KA, Chaudhary N, Li X, Schirmer CM, Scalzo F, Li J, Zand R. Using artificial intelligence for improving stroke diagnosis in emergency departments: a practical framework. Ther Adv Neurol Disord 2020; 13:1756286420938962. [PMID: 32922515 PMCID: PMC7453441 DOI: 10.1177/1756286420938962] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 06/02/2020] [Indexed: 12/02/2022] Open
Abstract
Stroke is the fifth leading cause of death in the United States and a major cause of severe disability worldwide. Yet, recognizing the signs of stroke in an acute setting is still challenging and leads to loss of opportunity to intervene, given the narrow therapeutic window. A decision support system using artificial intelligence (AI) and clinical data from electronic health records combined with patients' presenting symptoms can be designed to support emergency department providers in stroke diagnosis and subsequently reduce the treatment delay. In this article, we present a practical framework to develop a decision support system using AI by reflecting on the various stages, which could eventually improve patient care and outcome. We also discuss the technical, operational, and ethical challenges of the process.
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Affiliation(s)
- Vida Abedi
- Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA
- Biocomplexity Institute, Virginia Tech, Blacksburg, VA, USA
| | - Ayesha Khan
- Neuroscience Institute, Geisinger Health System, Danville, PA, USA
| | | | - Debdipto Misra
- Division of Informatics, Geisinger Health System, Danville, PA, USA
| | - Venkatesh Avula
- Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA
| | - Dhruv Mathrawala
- Division of Informatics, Geisinger Health System, Danville, PA, USA
| | - Chadd Kraus
- Department of Emergency Medicine, Geisinger Health System, Danville, PA, USA
| | - Kyle A. Marshall
- Department of Emergency Medicine, Geisinger Health System, Danville, PA, USA
| | | | - Xiao Li
- Genentech/Roche inc., South San Francisco, CA, USA
| | | | - Fabien Scalzo
- Department of Neurology, University of California, Los Angeles, CA, USA
- Department of Computer Science, University of California, Los Angeles, CA, USA
| | - Jiang Li
- Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA, USA
| | - Ramin Zand
- Neuroscience Institute, Geisinger Health System, Stroke Program, Geisinger Northeast Region, GRA Stroke Task Force, American Heart Association, Department of Neurosciences, 100 N Academy Ave, Danville, PA 17822-2101, USA
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Clinical Decision Support Systems in Breast Cancer: A Systematic Review. Cancers (Basel) 2020; 12:cancers12020369. [PMID: 32041094 PMCID: PMC7072392 DOI: 10.3390/cancers12020369] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 01/29/2020] [Accepted: 01/31/2020] [Indexed: 12/12/2022] Open
Abstract
Breast cancer is the most frequently diagnosed cancer in women, with more than 2.1 million new diagnoses worldwide every year. Personalised treatment is critical to optimising outcomes for patients with breast cancer. A major advance in medical practice is the incorporation of Clinical Decision Support Systems (CDSSs) to assist and support healthcare staff in clinical decision-making, thus improving the quality of decisions and overall patient care whilst minimising costs. The usage and availability of CDSSs in breast cancer care in healthcare settings is increasing. However, there may be differences in how particular CDSSs are developed, the information they include, the decisions they recommend, and how they are used in practice. This systematic review examines various CDSSs to determine their availability, intended use, medical characteristics, and expected outputs concerning breast cancer therapeutic decisions, an area that is known to have varying degrees of subjectivity in clinical practice. Utilising the methodology of Kitchenham and Charter, a systematic search of the literature was performed in Springer, Science Direct, Google Scholar, PubMed, ACM, IEEE, and Scopus. An overview of CDSS which supports decision-making in breast cancer treatment is provided along with a critical appraisal of their benefits, limitations, and opportunities for improvement.
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Heselmans A, Delvaux N, Laenen A, Van de Velde S, Ramaekers D, Kunnamo I, Aertgeerts B. Computerized clinical decision support system for diabetes in primary care does not improve quality of care: a cluster-randomized controlled trial. Implement Sci 2020; 15:5. [PMID: 31910877 PMCID: PMC6947861 DOI: 10.1186/s13012-019-0955-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 11/27/2019] [Indexed: 12/23/2022] Open
Abstract
Background The EBMeDS system is the computerized clinical decision support (CCDS) system of EBPNet, a national computerized point-of-care information service in Belgium. There is no clear evidence of more complex CCDS systems to manage chronic diseases in primary care practices (PCPs). The objective of this study was to assess the effectiveness of EBMeDS use in improving diabetes care. Methods A cluster-randomized trial with before-and-after measurements was performed in Belgian PCPs over 1 year, from May 2017 to May 2018. We randomly assigned 51 practices to either the intervention group (IG), to receive the EBMeDS system, or to the control group (CG), to receive usual care. Primary and secondary outcomes were the 1-year pre- to post-implementation change in HbA1c, LDL cholesterol, and systolic and diastolic blood pressure. Composite patient and process scores were calculated. A process evaluation was added to the analysis. Results were analyzed at 6 and 12 months. Linear mixed models and logistic regression models based on generalized estimating equations were used where appropriate. Results Of the 51 PCPs that were enrolled and randomly assigned (26 PCPs in the CG and 25 in the IG), 29 practices (3815 patients) were analyzed in the study: 2464 patients in the CG and 1351 patients in the IG. No change differences existed between groups in primary or secondary outcomes. Change difference between CG and IG after 1-year follow-up was − 0.09 (95% CI − 0.18; 0.01, p-value = 0.06) for HbA1c; 1.76 (95% CI − 0.46; 3.98, p-value = 0.12) for LDL cholesterol; and 0.13 (95% CI − 0.91; 1.16, p-value = 0.81) and 0.12 (95% CI − 1.25;1.49, p-value = 0.86) for systolic and diastolic blood pressure respectively. The odds ratio of the IG versus the CG for the probability of no worsening and improvement was 1.09 (95% CI 0.73; 1.63, p-value = 0.67) for the process composite score and 0.74 (95% CI 0.49; 1.12, p-value = 0.16) for the composite patient score. All but one physician was satisfied with the EBMeDS system. Conclusions The CCDS system EBMeDS did not improve diabetes care in Belgian primary care. The lack of improvement was mainly caused by imperfections in the organizational context of Belgian primary care for chronic disease management and shortcomings in the system requirements for the correct use of the EBMeDS system (e.g., complete structured records). These shortcomings probably caused low-use rates of the system. Trial registration ClinicalTrials.gov, NCT01830569, Registered 12 April 2013.
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Affiliation(s)
- Annemie Heselmans
- Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33 blok j, 3000, Leuven, Belgium.
| | - Nicolas Delvaux
- Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33 blok j, 3000, Leuven, Belgium
| | - Annouschka Laenen
- Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33 blok j, 3000, Leuven, Belgium
| | - Stijn Van de Velde
- Centre for Informed Health Choices, Division for Health Services, Norwegian Institute of Public Health, PO Box 222, Skøyen, 0213, Oslo, Norway
| | - Dirk Ramaekers
- Leuven Institute for Healthcare Policy, KU Leuven, Kapucijnenvoer 35 blok d, 3000, Leuven, Belgium
| | - Ilkka Kunnamo
- Duodecim, Scientific Society of Finnish Physicians, PO Box 874, Kaivokatu 10, 00101, Helsinki, Finland
| | - Bert Aertgeerts
- Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 33 blok j, 3000, Leuven, Belgium
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Van Dort BA, Zheng WY, Baysari MT. Prescriber perceptions of medication-related computerized decision support systems in hospitals: A synthesis of qualitative research. Int J Med Inform 2019; 129:285-295. [DOI: 10.1016/j.ijmedinf.2019.06.024] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 05/24/2019] [Accepted: 06/24/2019] [Indexed: 01/01/2023]
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Kersting C, Weltermann B. Evaluating the Feasibility of a Software Prototype Supporting the Management of Multimorbid Seniors: Mixed Methods Study in General Practices. JMIR Hum Factors 2019; 6:e12695. [PMID: 31274115 PMCID: PMC6637727 DOI: 10.2196/12695] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 02/25/2019] [Accepted: 03/30/2019] [Indexed: 01/27/2023] Open
Abstract
Background Longitudinal, patient-centered care represents a challenge for general practices. Decision support and reminder systems can offer targeted support. Objective The objective of this study was to follow a user-oriented, stepwise approach to develop an add-on for German electronic health record (EHR) systems, which aims to support longitudinal care management of multimorbid seniors, using a flag system displaying patient-centered information relevant for comprehensive health care management. This study evaluated the prototype’s feasibility from both a technical and users’ perspective. Methods The study was conducted with 18 general practitioners (GPs) and practice assistants (PAs) from 9 general practices using a mixed methods approach. In all practices, 1 GP and 1 PA tested the software each for 4 multimorbid seniors selected from the practice patient data. Technical feasibility was evaluated by documenting all technical problems. To evaluate the feasibility from the users’ perspective, participants’ responses during the software test were documented. In addition, they completed a self-administered questionnaire, including the validated System Usability Scale (SUS). Data were merged by transforming qualitative data into quantitative data. Analyses were performed using univariate statistics in IBM SPSS statistics. Results From a technical perspective, the new software was easy to install and worked without problems. Difficulties during the installation occurred in practices lacking a 64-bit system or a current version of Microsoft .NET. As EHRs used in German practices do not provide an interface to extract the data needed, additional software was required. Incomplete flags for some laboratory data occurred, although this function was implemented in our software as shown in previous tests. From the users’ perspective, the new add-on provided a better overview of relevant patient information, reminded more comprehensively about upcoming examinations, and better supported guideline-based care when compared with their individual practice strategies. A total of 14 out of 18 participants (78%) were interested in using the software long-term. Furthermore, 8 of 9 GPs were willing to pay 5 to 25 Euros (mean 14.75, SD 5.93) monthly for its use. The usability was rated as 75% (43%-95%). Conclusions The new EHR add-on was well accepted and achieved a good usability rating measured by the validated SUS. In perspective, the legally consolidated, standardized interface to German EHRs will facilitate the technical integration. In view of the high feasibility, we plan to study the software’s effectiveness in everyday primary care. Trial Registration German Clinical Trials Register DRKS00008777; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00008777
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Affiliation(s)
- Christine Kersting
- Institute for General Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Birgitta Weltermann
- Institute for General Medicine, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.,Institute of General Practice and Family Medicine, University Hospital Bonn, University of Bonn, Bonn, Germany
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Priority Setting in Improving Hospital Care for Older Patients Using Clinical Decision Support. J Am Med Dir Assoc 2019; 20:1045-1047. [PMID: 31056454 DOI: 10.1016/j.jamda.2019.03.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 03/16/2019] [Indexed: 11/24/2022]
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Blanco N, O'Hara LM, Robinson GL, Brown J, Heil E, Brown CH, Stump BD, Sigler BW, Belani A, Miller HL, Chiplinski AN, Perlmutter R, Wilson L, Morgan DJ, Leekha S. Health care worker perceptions toward computerized clinical decision support tools for Clostridium difficile infection reduction: A qualitative study at 2 hospitals. Am J Infect Control 2018; 46:1160-1166. [PMID: 29803592 DOI: 10.1016/j.ajic.2018.04.204] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 04/06/2018] [Accepted: 04/07/2018] [Indexed: 12/31/2022]
Abstract
BACKGROUND Clostridium difficile infection (CDI) is associated with significant morbidity and mortality. Computerized clinical decision support (CCDS) tools can aid process improvement in infection prevention and antibiotic stewardship, but implementation and health care workers (HCWs) uptake of these tools is often variable. The objective of this study was to describe HCWs' perceptions of barriers and facilitators related to uptake of CCDS tools as part of a CDI reduction bundle. METHODS We conducted a qualitative study among HCWs at 2 acute care hospitals in Maryland. Semi-structured interviews and structured surveys were completed by HCWs to evaluate their perception to CCDS tools at 2 different stages: predevelopment and preimplementation. Emergent themes and patterns in the data were identified and condensed. RESULTS Gaps in CDI-related knowledge and in communication between HCWs were identified throughout the evaluation. HCWs agreed on the potential of the tools to improve CDI diagnosis, prevention, and control. An important barrier for uptake was the perceived loss of autonomy and clinical judgment, whereas standardization and error reduction were perceived advantages. CONCLUSIONS These observations shaped the development and implementation of the CDI reduction bundle. Qualitative findings can provide valuable contextual information during the development stages of CCDS tools in infection prevention and antibiotic stewardship.
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Affiliation(s)
- Natalia Blanco
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD.
| | - Lyndsay M O'Hara
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
| | - Gwen L Robinson
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
| | - Jeanine Brown
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
| | - Emily Heil
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD; Department of Pharmacy Practice and Science, University of Maryland School of Pharmacy, Baltimore, MD
| | - Clayton H Brown
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
| | | | | | | | | | | | - Rebecca Perlmutter
- Emerging Infections Program, Maryland Department of Health, Baltimore, MD
| | - Lucy Wilson
- Emerging Infections Program, Maryland Department of Health, Baltimore, MD
| | - Daniel J Morgan
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD; VA Maryland Healthcare System, Baltimore, MD
| | - Surbhi Leekha
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD
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Rieckert A, Sommerauer C, Krumeich A, Sönnichsen A. Reduction of inappropriate medication in older populations by electronic decision support (the PRIMA-eDS study): a qualitative study of practical implementation in primary care. BMC FAMILY PRACTICE 2018; 19:110. [PMID: 29986668 PMCID: PMC6038343 DOI: 10.1186/s12875-018-0789-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 05/31/2018] [Indexed: 01/27/2023]
Abstract
BACKGROUND Within the EU-funded project PRIMA-eDS (Polypharmacy in chronic diseases: Reduction of Inappropriate Medication and Adverse drug events in older populations by electronic Decision Support) an electronic decision support tool (the "PRIMA-eDS-tool") was developed for general practitioners (GPs) to reduce inappropriate medication in their older polypharmacy patients. After entering patient data relevant to prescribing in an electronic case report form the physician received a comprehensive medication review (CMR) on his/her screen displaying recommendations regarding missing indications, necessary laboratory tests, evidence-base of current medication, dose adjustments for renal malfunction, potentially harmful drug-drug interactions, contra-indications, and possible adverse drug events. We set out to explore the usage of the PRIMA-eDS tool and the adoption of the recommendations provided by the CMR to optimise the tool and prepare it for its future implementation. METHODS In a qualitative study carried out in North Rhine-Westphalia, Germany, 21 GPs using the PRIMA-eDS tool within the PRIMA-eDS study were interviewed. Interviews encompassed the GPs' attitudes regarding use of the electronic case report form and the CMR, their response to the recommendations, and the implementation of the tool into daily practice routine. The collected data were analysed applying thematic qualitative text analysis. RESULTS GPs found the patient data entry into the electronic case report form to be inconvenient and time-consuming. The CMR was conducted often outside practice hours and without the patient present. GPs found that the PRIMA-eDS CMR provided relevant information for and had several positive effects on the caring process. However, they encountered several barriers when wanting to change medication. CONCLUSIONS It is unlikely that the PRIMA-eDS CMR will be used in the future as it is now as patient data entry is too time-consuming. Several barriers towards deprescribing medications were found which are common in deprescribing studies. Given the positive attitude towards the CMR, a new way of entering patient data into the PRIMA-eDS tool to create the CMR needs to be developed.
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Affiliation(s)
- Anja Rieckert
- Institute of General Practice and Family Medicine, Faculty of Health, Witten/Herdecke University, Alfred-Herrhausen-Str. 50, 58448, Witten, Germany.
| | - Christina Sommerauer
- Institute of General Practice and Family Medicine, Faculty of Health, Witten/Herdecke University, Alfred-Herrhausen-Str. 50, 58448, Witten, Germany
| | - Anja Krumeich
- Department of Health, Ethics, and Society, Faculty of Health, Medicine, and Lifesciences, Maastricht University, Debyeplein 1, 6229 HA, Maastricht, The Netherlands
| | - Andreas Sönnichsen
- Institute of General Practice and Family Medicine, Faculty of Health, Witten/Herdecke University, Alfred-Herrhausen-Str. 50, 58448, Witten, Germany.,Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, University of Manchester, Oxford Rd 176, Manchester, M13 9PL, UK
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Van de Velde S, Kortteisto T, Spitaels D, Jamtvedt G, Roshanov P, Kunnamo I, Aertgeerts B, Vandvik PO, Flottorp S. Development of a Tailored Intervention With Computerized Clinical Decision Support to Improve Quality of Care for Patients With Knee Osteoarthritis: Multi-Method Study. JMIR Res Protoc 2018; 7:e154. [PMID: 29891466 PMCID: PMC6018233 DOI: 10.2196/resprot.9927] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Revised: 04/06/2018] [Accepted: 05/07/2018] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Clinical practice patterns greatly diverge from evidence-based recommendations to manage knee osteoarthritis conservatively before resorting to surgery. OBJECTIVE This study aimed to tailor a guideline-based computerized decision support (CDS) intervention that facilitates the conservative management of knee osteoarthritis. METHODS Experts with backgrounds in clinical medicine, research, implementation, or health informatics suggested the most important recommendations for implementation, how to develop an implementation strategy, and how to form the CDS algorithms. In 6 focus group sessions, 8 general practitioners and 22 patients from Norway, Belgium, and Finland discussed the suggested CDS intervention and identified factors that would be most critical for the success of the intervention. The focus group moderators used the GUideline Implementation with DEcision Support checklist, which we developed to support consideration of CDS success factors. RESULTS The experts prioritized 9 out of 22 recommendations for implementation. We formed the concept for 6 CDS algorithms to support implementation of these recommendations. The focus group suggested 59 unique factors that could affect the success of the presented CDS intervention. Five factors (out of the 59) were prioritized by focus group participants in every country, including the perceived potential to address the information needs of both patients and general practitioners; the credibility of CDS information; the timing of CDS for patients; and the need for personal dialogue about CDS between the general practitioner and the patient. CONCLUSIONS The focus group participants supported the CDS intervention as a tool to improve the quality of care for patients with knee osteoarthritis through shared, evidence-based decision making. We aim to develop and implement the CDS based on these study results. Future research should address optimal ways to (1) provide patient-directed CDS, (2) enable more patient-specific CDS within the context of patient complexity, and (3) maintain user engagement with CDS over time.
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Affiliation(s)
- Stijn Van de Velde
- Centre for Informed Health Choices, Norwegian Institute of Public Health, Oslo, Norway
| | - Tiina Kortteisto
- Department of Internal Medicine, Tampere University Hospital, Tampere, Finland
| | - David Spitaels
- Department of Public Health and Primary Care, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Gro Jamtvedt
- Oslo and Akershus University College of Applied Sciences, Oslo, Norway
| | - Pavel Roshanov
- Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Ilkka Kunnamo
- Duodecim, Scientific Society of Finnish Physicians, Helsinki, Finland
| | - Bert Aertgeerts
- Department of Public Health and Primary Care, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Per Olav Vandvik
- Centre for Informed Health Choices, Norwegian Institute of Public Health, Oslo, Norway.,Institute of Health and Society, University of Oslo, Oslo, Norway.,Making GRADE the Irresistible Choice (MAGIC), Oslo, Norway
| | - Signe Flottorp
- Centre for Informed Health Choices, Norwegian Institute of Public Health, Oslo, Norway.,Institute of Health and Society, University of Oslo, Oslo, Norway
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Sim EY, Tan DJA, Abdullah HR. The use of computerized physician order entry with clinical decision support reduces practice variance in ordering preoperative investigations: A retrospective cohort study. Int J Med Inform 2017; 108:29-35. [DOI: 10.1016/j.ijmedinf.2017.09.015] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Revised: 05/12/2017] [Accepted: 09/26/2017] [Indexed: 12/19/2022]
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Medlock S, Eslami S, Askari M, Arts DL, van de Glind EM, Brouwer HJ, van Weert HC, de Rooij SE, Abu-Hanna A. For which clinical rules do doctors want decision support, and why? A survey of Dutch general practitioners. Health Informatics J 2017; 25:1076-1090. [PMID: 29148311 PMCID: PMC6769284 DOI: 10.1177/1460458217740407] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Despite the promise of decision support for improving care, alerts are often overridden or ignored. We evaluated Dutch general practitioners’ intention to accept decision support in a proposed implementation based on clinical rules regarding care for elderly patients, and their reasons for wanting or not wanting support. We developed a survey based on literature and structured interviews and distributed it to all doctors who would receive support in the proposed implementation (n = 43), of which 65 percent responded. The survey consisted of six questions for each of 20 clinical rules. Despite concerns about interruption, doctors tended to choose more interruptive forms of support. Doctors wanted support when they felt the rule represented minimal care, perceived a need to improve care, and felt responsible for the action and that they might forget to perform the action; doctors declined support due to feeling that it was unnecessary and due to concerns about interruption.
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Affiliation(s)
| | - Saeid Eslami
- Amsterdam Public Health Research Institute, The Netherlands; Mashhad University of Medical Sciences, The Islamic Republic of Iran
| | - Marjan Askari
- Amsterdam Public Health Research Institute, The Netherlands; Universiteit Utrecht, The Netherlands
| | - Derk L Arts
- Amsterdam Public Health Research Institute, The Netherlands; University of Amsterdam, The Netherlands
| | | | | | | | - Sophia E de Rooij
- University of Amsterdam, The Netherlands; University of Groningen, The Netherlands
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Liberati EG, Ruggiero F, Galuppo L, Gorli M, González-Lorenzo M, Maraldi M, Ruggieri P, Friz HP, Scaratti G, Kwag KH, Vespignani R, Moja L. What hinders the uptake of computerized decision support systems in hospitals? A qualitative study and framework for implementation. Implement Sci 2017; 12:113. [PMID: 28915822 PMCID: PMC5602839 DOI: 10.1186/s13012-017-0644-2] [Citation(s) in RCA: 140] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 09/04/2017] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Advanced Computerized Decision Support Systems (CDSSs) assist clinicians in their decision-making process, generating recommendations based on up-to-date scientific evidence. Although this technology has the potential to improve the quality of patient care, its mere provision does not guarantee uptake: even where CDSSs are available, clinicians often fail to adopt their recommendations. This study examines the barriers and facilitators to the uptake of an evidence-based CDSS as perceived by diverse health professionals in hospitals at different stages of CDSS adoption. METHODS Qualitative study conducted as part of a series of randomized controlled trials of CDSSs. The sample includes two hospitals using a CDSS and two hospitals that aim to adopt a CDSS in the future. We interviewed physicians, nurses, information technology staff, and members of the boards of directors (n = 30). We used a constant comparative approach to develop a framework for guiding implementation. RESULTS We identified six clusters of experiences of, and attitudes towards CDSSs, which we label as "positions." The six positions represent a gradient of acquisition of control over CDSSs (from low to high) and are characterized by different types of barriers to CDSS uptake. The most severe barriers (prevalent in the first positions) include clinicians' perception that the CDSSs may reduce their professional autonomy or may be used against them in the event of medical-legal controversies. Moving towards the last positions, these barriers are substituted by technical and usability problems related to the technology interface. When all barriers are overcome, CDSSs are perceived as a working tool at the service of its users, integrating clinicians' reasoning and fostering organizational learning. CONCLUSIONS Barriers and facilitators to the use of CDSSs are dynamic and may exist prior to their introduction in clinical contexts; providing a static list of obstacles and facilitators, irrespective of the specific implementation phase and context, may not be sufficient or useful to facilitate uptake. Factors such as clinicians' attitudes towards scientific evidences and guidelines, the quality of inter-disciplinary relationships, and an organizational ethos of transparency and accountability need to be considered when exploring the readiness of a hospital to adopt CDSSs.
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Affiliation(s)
- Elisa G. Liberati
- Cambridge Centre for Health Services Research (CCHSR), Department of Public Health and Primary Care, University of Cambridge School of Clinical Medicine, Forvie Site, Robinson Way, Cambridge, CB2 0SR UK
| | - Francesca Ruggiero
- Unità di Epidemiologia Clinica, IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161 Milan, Italy
- Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Via Carlo Pascal 36, 20133 Milan, Italy
| | - Laura Galuppo
- Dipartimento di Psicologia, Università Cattolica del Sacro Cuore, Largo Agostino Gemelli 1, 20123 Milan, Italy
| | - Mara Gorli
- Dipartimento di Psicologia, Università Cattolica del Sacro Cuore, Largo Agostino Gemelli 1, 20123 Milan, Italy
| | - Marien González-Lorenzo
- Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Via Carlo Pascal 36, 20133 Milan, Italy
| | - Marco Maraldi
- Clinica Ortopedica, Università degli Studi di Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Pietro Ruggieri
- Clinica Ortopedica, Università degli Studi di Padova, Via Giustiniani 3, 35128 Padova, Italy
| | - Hernan Polo Friz
- Dipartimento Internistico, Ospedale di Vimercate, Via Santi Cosma e Damiano 10, 20871 Vimercate, Italy
| | - Giuseppe Scaratti
- Dipartimento di Psicologia, Università Cattolica del Sacro Cuore, Largo Agostino Gemelli 1, 20123 Milan, Italy
| | - Koren H. Kwag
- Medical School of International Health, Ben Gurion University of the Negev, P.O. Box 653, 84105 Beersheva, Israel
| | - Roberto Vespignani
- IRST Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori IRCCS, Via Piero Maroncelli 40, 47014 Meldola, Italy
| | - Lorenzo Moja
- Unità di Epidemiologia Clinica, IRCCS Istituto Ortopedico Galeazzi, Via Riccardo Galeazzi 4, 20161 Milan, Italy
- Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Via Carlo Pascal 36, 20133 Milan, Italy
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Modeling the Construct of an Expert Evidence-Adaptive Knowledge Base for a Pressure Injury Clinical Decision Support System. INFORMATICS 2017. [DOI: 10.3390/informatics4030020] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Porat T, Delaney B, Kostopoulou O. The impact of a diagnostic decision support system on the consultation: perceptions of GPs and patients. BMC Med Inform Decis Mak 2017; 17:79. [PMID: 28576145 PMCID: PMC5457602 DOI: 10.1186/s12911-017-0477-6] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 05/25/2017] [Indexed: 11/17/2022] Open
Abstract
Background Clinical decision support systems (DSS) aimed at supporting diagnosis are not widely used. This is mainly due to usability issues and lack of integration into clinical work and the electronic health record (EHR). In this study we examined the usability and acceptability of a diagnostic DSS prototype integrated with the EHR and in comparison with the EHR alone. Methods Thirty-four General Practitioners (GPs) consulted with 6 standardised patients (SPs) using only their EHR system (baseline session); on another day, they consulted with 6 different but matched for difficulty SPs, using the EHR with the integrated DSS prototype (DSS session). GPs were interviewed twice (at the end of each session), and completed the Post-Study System Usability Questionnaire at the end of the DSS session. The SPs completed the Consultation Satisfaction Questionnaire after each consultation. Results The majority of GPs (74%) found the DSS useful: it helped them consider more diagnoses and ask more targeted questions. They considered three user interface features to be the most useful: (1) integration with the EHR; (2) suggested diagnoses to consider at the start of the consultation and; (3) the checklist of symptoms and signs in relation to each suggested diagnosis. There were also criticisms: half of the GPs felt that the DSS changed their consultation style, by requiring them to code symptoms and signs while interacting with the patient. SPs sometimes commented that GPs were looking at their computer more than at them; this comment was made more often in the DSS session (15%) than in the baseline session (3%). Nevertheless, SP ratings on the satisfaction questionnaire did not differ between the two sessions. Conclusions To use the DSS effectively, GPs would need to adapt their consultation style, so that they code more information during rather than at the end of the consultation. This presents a potential barrier to adoption. Training GPs to use the system in a patient-centred way, as well as improvement of the DSS interface itself, could facilitate coding. To enhance patient acceptability, patients should be informed about the potential of the DSS to improve diagnostic accuracy. Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0477-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Talya Porat
- Department of Primary Care and Public Health Sciences, King's College London, 3rd floor Addison House, Guy's Campus, London, SE1 3QD, UK.
| | - Brendan Delaney
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Olga Kostopoulou
- Department of Surgery and Cancer, Imperial College London, London, UK
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Moriarity AK, Green A, Klochko C, O'Brien M, Halabi S. Evaluating the Effect of Unstructured Clinical Information on Clinical Decision Support Appropriateness Ratings. J Am Coll Radiol 2017; 14:737-743. [PMID: 28434848 DOI: 10.1016/j.jacr.2017.02.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2016] [Revised: 02/01/2017] [Accepted: 02/02/2017] [Indexed: 10/19/2022]
Abstract
OBJECTIVE To determine the appropriateness rating (AR) of advanced inpatient imaging requests that were not rated by prospective, point-of-care clinical decision support (CDS) using computerized provider order entry. MATERIALS AND METHODS During 30-day baseline and intervention periods, CDS generated an AR for advanced inpatient imaging requests (nuclear medicine, CT, and MRI) using provider-selected structured indications from pull-down menus in the computerized provider order entry portal. The AR was only displayed during the intervention, and providers were required to acknowledge the AR to finalize the request. Subsequently, the unstructured free text information accompanying all requests was reviewed, and the AR was revised when possible. The percentage of unrated requests and the overall AR, before and after radiologist review, were compared between periods and by provider type. RESULTS CDS software prospectively generated an AR for only 25.4% and 28.4% of baseline and intervention imaging requests, respectively; however, radiologist review generated an AR for 82.4% and 93.6% of the same requests. During the respective periods, the percentage of baseline and intervention imaging requests considered appropriate was 18.7% and 22.9% by prospective CDS software rating and increased to 82.4% and 88.7% with radiologist review. CONCLUSION Despite limited effective use of CDS software, the percentage of requests containing additional, relevant clinical information increased, and the majority of requests had overall high appropriateness when reviewed by a radiologist. Additional work is needed to improve the amount and quality of clinical information available to CDS software and to facilitate the entry of this information by appropriate end users.
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Affiliation(s)
- Andrew K Moriarity
- Advanced Radiology Services, Grand Rapids, Michigan; Division of Radiology and Biomedical Imaging, Michigan State University College of Human Medicine, Grand Rapids, Michigan.
| | - Aaron Green
- Wayne State University School of Medicine, Detroit, Michigan
| | - Chad Klochko
- Department of Diagnostic Radiology, Henry Ford Health System, Detroit, Michigan
| | - Matthew O'Brien
- Department of Diagnostic Radiology, Henry Ford Health System, Detroit, Michigan
| | - Safwan Halabi
- Department of Radiology, Lucile Salter Packard Children's Hospital at Stanford, Palo Alto, California
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Nash DM, Ivers NM, Young J, Jaakkimainen RL, Garg AX, Tu K. Improving Care for Patients With or at Risk for Chronic Kidney Disease Using Electronic Medical Record Interventions: A Pragmatic Cluster-Randomized Trial Protocol. Can J Kidney Health Dis 2017; 4:2054358117699833. [PMID: 28607686 PMCID: PMC5453629 DOI: 10.1177/2054358117699833] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Accepted: 01/26/2017] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Many patients with or at risk for chronic kidney disease (CKD) in the primary care setting are not receiving recommended care. OBJECTIVE The objective of this study is to determine whether a multifaceted, low-cost intervention compared with usual care improves the care of patients with or at risk for CKD in the primary care setting. DESIGN A pragmatic cluster-randomized trial, with an embedded qualitative process evaluation, will be conducted. SETTING The study population comes from the Electronic Medical Record Administrative data Linked Database®, which includes clinical data for more than 140 000 rostered adults cared for by 194 family physicians in 34 clinics across Ontario, Canada. The 34 primary care clinics will be randomized to the intervention or control group. INTERVENTION The intervention group will receive resources from the "CKD toolkit" to help improve care including practice audit and feedback, printed educational materials for physicians and patients, electronic decision support and reminders, and implementation support. MEASUREMENTS Patients with or at risk for CKD within participating clinics will be identified using laboratory data in the electronic medical records. Outcomes will be assessed after dissemination of the CKD tools and after 2 rounds of feedback on performance on quality indicators have been sent to the physicians using information from the electronic medical records. The primary outcome is the proportion of patients aged 50 to 80 years with nondialysis-dependent CKD who are on a statin. Secondary outcomes include process of care measures such as screening tests, CKD recognition, monitoring tests, angiotensin-converting enzyme inhibitor or angiotensin receptor blocker prescriptions, blood pressure targets met, and nephrologist referral. Hierarchical analytic modeling will be performed to account for clustering. Semistructured interviews will be conducted with a random purposeful sample of physicians in the intervention group to understand why the intervention achieved the observed effects. CONCLUSIONS If our intervention improves care, then the CKD toolkit can be adapted and scaled for use in other primary care clinics which use electronic medical records. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02274298.
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Affiliation(s)
- Danielle M. Nash
- Institute for Clinical Evaluative Sciences Western, London, Ontario, Canada
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
| | - Noah M. Ivers
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
- Department of Family and Community Medicine, University of Toronto, Ontario, Canada
- Women’s College Hospital, Toronto, Ontario, Canada
| | - Jacqueline Young
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
| | - R. Liisa Jaakkimainen
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
- Department of Family and Community Medicine, University of Toronto, Ontario, Canada
- Sunnybrook Academic Family Health Team, Toronto, Ontario, Canada
| | - Amit X. Garg
- Institute for Clinical Evaluative Sciences Western, London, Ontario, Canada
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario, Canada
- Department of Medicine, London Health Sciences Centre, Ontario, Canada
| | - Karen Tu
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
- Department of Family and Community Medicine, University of Toronto, Ontario, Canada
- Toronto Western Hospital Family Health Team, University Health Network, Toronto, Ontario, Canada
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Development of a clinical decision support system for diabetes care: A pilot study. PLoS One 2017; 12:e0173021. [PMID: 28235017 PMCID: PMC5325565 DOI: 10.1371/journal.pone.0173021] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2016] [Accepted: 02/14/2017] [Indexed: 11/21/2022] Open
Abstract
Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention.
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Kilsdonk E, Peute L, Jaspers M. Factors influencing implementation success of guideline-based clinical decision support systems: A systematic review and gaps analysis. Int J Med Inform 2017; 98:56-64. [DOI: 10.1016/j.ijmedinf.2016.12.001] [Citation(s) in RCA: 112] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Revised: 12/02/2016] [Accepted: 12/04/2016] [Indexed: 01/19/2023]
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Weiss MJ, Kramer C, Tremblay S, Côté L. Attitudes of pediatric intensive care unit physicians towards the use of cognitive aids: a qualitative study. BMC Med Inform Decis Mak 2016; 16:53. [PMID: 27206410 PMCID: PMC4875623 DOI: 10.1186/s12911-016-0291-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2015] [Accepted: 05/08/2016] [Indexed: 11/14/2022] Open
Abstract
Background Cognitive aids are increasingly recommended in clinical practice, yet little is known about the attitudes of physicians towards these tools. Methods We employed a qualitative, descriptive design to explore physician attitudes towards cognitive aids in pediatric intensive care units (PICUs). Semi-structured interviews elicited the opinions of a convenience sample of practicing PICU physicians towards the use of cognitive aids. We analyzed interview data for thematic content to examine the three factors of intention to use cognitive aids as defined by the Theory of Planned Behavior (TPB), attitudes, social norms, and perceived control. Results Analysis of 14 interviews suggested that in the PICU setting, cognitive aids are widely used. Discovered themes related to their use touched on all three TPB factors of intention and included: aids are perceived to improve team communication; aids may improve patient safety; aids may hinder clinician judgment; physicians may resist implementation if it occurs prior to demonstration of benefit; effective adoption requires cognitive aids to be integrated into local workplace culture; and implementation should take physician concerns into account. Conclusions Our sample of PICU physicians were open to cognitive aids in their practice, as long as such aids preserve the primacy of clinical judgment, focus on team communication, demonstrate effectiveness through preliminary testing, and are designed and implemented with the local culture and work environment in mind. Future knowledge translation efforts to implement cognitive aids would benefit from consideration of these issues.
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Affiliation(s)
- Matthew J Weiss
- Division of Pediatric Critical Care, Centre Mère-Enfant Soleil du Centre Hospitalier Universitaire de Québec, 2705 boul Laurier Local R1735, Québec, QC, G1V 4G2, Canada. .,Department of Pediatrics, Université Laval, Faculty of Medicine, Québec, Canada.
| | - Chelsea Kramer
- School of Psychology, Université Laval, Faculty of Social Sciences, Pavillon Félix-Antoine-Savard, 2325, rue des Bibliothèques, Québec, G1V 0A6, Canada
| | - Sébastien Tremblay
- School of Psychology, Université Laval, Faculty of Social Sciences, Pavillon Félix-Antoine-Savard, 2325, rue des Bibliothèques, Québec, G1V 0A6, Canada
| | - Luc Côté
- Department of Family and Emergency Medicine, Université Laval, Faculty of Medicine, Pavillon Ferdinand-Vandry, 1050, avenue de la Médecine Local 2207A, Québec, G1V 0A6, Canada
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Weltermann B, Kersting C. Feasibility study of a clinical decision support system for the management of multimorbid seniors in primary care: study protocol. Pilot Feasibility Stud 2016; 2:16. [PMID: 27965836 PMCID: PMC5154089 DOI: 10.1186/s40814-016-0057-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2015] [Accepted: 03/02/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Care for seniors is complex because patients often have more than one disease, one medication, and one physician. It is a key challenge for primary care physicians to structure the various aspects of each patient's care, to integrate each patient's preferences, and to maintain a long-term overview. This article describes the design for the development and feasibility testing of the clinical decision support system (CDSS) eCare*Seniors© which is electronic health record (EHR)-based allowing for a long-term, comprehensive, evidence-based, and patient preference-oriented management of multimorbid seniors. METHODS/DESIGN This mixed-methods study is designed in three steps. First, focus groups and practice observations will be conducted to develop criteria for software design from a physicians' and practice assistants' perspective. Second, based on these criteria, a CDSS prototype will be developed. Third, the prototype's feasibility will be tested by five primary care practices in the care of 30 multimorbid seniors. Primary outcome is the usability of the software measured by the validated system usability scale (SUS) after 3 months. Secondary outcomes are the (a) willingness to routinely use the CDSS, (b) degree of utilization of the CDSS, (c) acceptance of the CDSS, (d) willingness of the physicians to purchase the CDSS, and (e) willingness of the practice assistants to use the CDSS in the long term. These outcomes will be measured using semi-structured interviews and software usage data. If the SUS score reaches ≥70 %, feasibility testing will be judged successful. Otherwise, the CDSS prototype will be refined according to the users' needs and retested by the physicians and practice assistants until it is fully adapted to their requirements and reaches a usability score ≥70 %. DISCUSSION The study will support the development of a CDSS which is primary care-defined, user-friendly, easy-to-comprehend, workflow-oriented, and comprehensive. The software will assist physicians and practices in their long-term, individualized care for multimorbid seniors. TRIAL REGISTRATION German Clinical Trials Register, DRKS00008777.
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Affiliation(s)
- Birgitta Weltermann
- Institute for General Medicine, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147 Essen, Germany
| | - Christine Kersting
- Institute for General Medicine, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, 45147 Essen, Germany
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Van de Velde S, Roshanov P, Kortteisto T, Kunnamo I, Aertgeerts B, Vandvik PO, Flottorp S. Tailoring implementation strategies for evidence-based recommendations using computerised clinical decision support systems: protocol for the development of the GUIDES tools. Implement Sci 2016; 11:29. [PMID: 26946141 PMCID: PMC4779557 DOI: 10.1186/s13012-016-0393-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2016] [Accepted: 02/25/2016] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND A computerised clinical decision support system (CCDSS) is a technology that uses patient-specific data to provide relevant medical knowledge at the point of care. It is considered to be an important quality improvement intervention, and the implementation of CCDSS is growing substantially. However, the significant investments do not consistently result in value for money due to content, context, system and implementation issues. The Guideline Implementation with Decision Support (GUIDES) project aims to improve the impact of CCDSS through optimised implementation based on high-quality evidence-based recommendations. To achieve this, we will develop tools that address the factors that determine successful CCDSS implementation. METHODS/DESIGN We will develop the GUIDES tools in four steps, using the methods and results of the Tailored Implementation for Chronic Diseases (TICD) project as a starting point: (1) a review of research evidence and frameworks on the determinants of implementing recommendations using CCDSS; (2) a synthesis of a comprehensive framework for the identified determinants; (3) the development of tools for use of the framework and (4) pilot testing the utility of the tools through the development of a tailored CCDSS intervention in Norway, Belgium and Finland. We selected the conservative management of knee osteoarthritis as a prototype condition for the pilot. During the process, the authors will collaborate with an international expert group to provide input and feedback on the tools. DISCUSSION This project will provide guidance and tools on methods of identifying implementation determinants and selecting strategies to implement evidence-based recommendations through CCDSS. We will make the GUIDES tools available to CCDSS developers, implementers, researchers, funders, clinicians, managers, educators, and policymakers internationally. The tools and recommendations will be generic, which makes them scalable to a large spectrum of conditions. Ultimately, the better implementation of CCDSS may lead to better-informed decisions and improved care and patient outcomes for a wide range of conditions. PROTOCOL REGISTRATION PROSPERO, CRD42016033738.
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Affiliation(s)
| | | | | | - Ilkka Kunnamo
- Duodecim, Scientific Society of Finnish Physicians, Helsinki, Finland
| | - Bert Aertgeerts
- Department of Public Health and Primary Care, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Per Olav Vandvik
- MAGIC Non-Profit Research and Innovation Programme, Norwegian Institute of Public Health, Oslo, Norway
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Precision diagnosis: a view of the clinical decision support systems (CDSS) landscape through the lens of critical care. J Clin Monit Comput 2016; 31:261-271. [DOI: 10.1007/s10877-016-9849-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 02/17/2016] [Indexed: 10/22/2022]
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Blagec K, Romagnoli KM, Boyce RD, Samwald M. Examining perceptions of the usefulness and usability of a mobile-based system for pharmacogenomics clinical decision support: a mixed methods study. PeerJ 2016; 4:e1671. [PMID: 26925317 PMCID: PMC4768706 DOI: 10.7717/peerj.1671] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Accepted: 01/19/2016] [Indexed: 12/12/2022] Open
Abstract
Background. Pharmacogenomic testing has the potential to improve the safety and efficacy of pharmacotherapy, but clinical application of pharmacogenetic knowledge has remained uncommon. Clinical Decision Support (CDS) systems could help overcome some of the barriers to clinical implementation. The aim of this study was to evaluate the perception and usability of a web- and mobile-enabled CDS system for pharmacogenetics-guided drug therapy–the Medication Safety Code (MSC) system–among potential users (i.e., physicians and pharmacists). Furthermore, this study sought to collect data on the practicability and comprehensibility of potential layouts of a proposed personalized pocket card that is intended to not only contain the machine-readable data for use with the MSC system but also human-readable data on the patient’s pharmacogenomic profile. Methods. We deployed an emergent mixed methods design encompassing (1) qualitative interviews with pharmacists and pharmacy students, (2) a survey among pharmacogenomics experts that included both qualitative and quantitative elements and (3) a quantitative survey among physicians and pharmacists. The interviews followed a semi-structured guide including a hypothetical patient scenario that had to be solved by using the MSC system. The survey among pharmacogenomics experts focused on what information should be printed on the card and how this information should be arranged. Furthermore, the MSC system was evaluated based on two hypothetical patient scenarios and four follow-up questions on the perceived usability. The second survey assessed physicians’ and pharmacists’ attitude towards the MSC system. Results. In total, 101 physicians, pharmacists and PGx experts coming from various relevant fields evaluated the MSC system. Overall, the reaction to the MSC system was positive across all investigated parameters and among all user groups. The majority of participants were able to solve the patient scenarios based on the recommendations displayed on the MSC interface. A frequent request among participants was to provide specific listings of alternative drugs and concrete dosage instructions. Negligence of other patient-specific factors for choosing the right treatment such as renal function and co-medication was a common concern related to the MSC system, while data privacy and cost-benefit considerations emerged as the participants’ major concerns regarding pharmacogenetic testing in general. The results of the card layout evaluation indicate that a gene-centered and tabulated presentation of the patient’s pharmacogenomic profile is helpful and well-accepted. Conclusions. We found that the MSC system was well-received among the physicians and pharmacists included in this study. A personalized pocket card that lists a patient’s metabolizer status along with critically affected drugs can alert physicians and pharmacists to the availability of essential therapy modifications.
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Affiliation(s)
- Kathrin Blagec
- Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna , Vienna , Austria
| | - Katrina M Romagnoli
- Department of Biomedical Informatics, University of Pittsburgh , Pittsburgh, Pennsylvania , United States
| | - Richard D Boyce
- Department of Biomedical Informatics, University of Pittsburgh , Pittsburgh, Pennsylvania , United States
| | - Matthias Samwald
- Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna , Vienna , Austria
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Alagiakrishnan K, Wilson P, Sadowski CA, Rolfson D, Ballermann M, Ausford A, Vermeer K, Mohindra K, Romney J, Hayward RS. Physicians' use of computerized clinical decision supports to improve medication management in the elderly - the Seniors Medication Alert and Review Technology intervention. Clin Interv Aging 2016; 11:73-81. [PMID: 26869776 PMCID: PMC4734726 DOI: 10.2147/cia.s94126] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Background Elderly people (aged 65 years or more) are at increased risk of polypharmacy (five or more medications), inappropriate medication use, and associated increased health care costs. The use of clinical decision support (CDS) within an electronic medical record (EMR) could improve medication safety. Methods Participatory action research methods were applied to preproduction design and development and postproduction optimization of an EMR-embedded CDS implementation of the Beers’ Criteria for medication management and the Cockcroft–Gault formula for estimating glomerular filtration rates (GFR). The “Seniors Medication Alert and Review Technologies” (SMART) intervention was used in primary care and geriatrics specialty clinics. Passive (chart messages) and active (order-entry alerts) prompts exposed potentially inappropriate medications, decreased GFR, and the possible need for medication adjustments. Physician reactions were assessed using surveys, EMR simulations, focus groups, and semi-structured interviews. EMR audit data were used to identify eligible patient encounters, the frequency of CDS events, how alerts were managed, and when evidence links were followed. Results Analysis of subjective data revealed that most clinicians agreed that CDS appeared at appropriate times during patient care. Although managing alerts incurred a modest time burden, most also agreed that workflow was not disrupted. Prevalent concerns related to clinician accountability and potential liability. Approximately 36% of eligible encounters triggered at least one SMART alert, with GFR alert, and most frequent medication warnings were with hypnotics and anticholinergics. Approximately 25% of alerts were overridden and ~15% elicited an evidence check. Conclusion While most SMART alerts validated clinician choices, they were received as valuable reminders for evidence-informed care and education. Data from this study may aid other attempts to implement Beers’ Criteria in ambulatory care EMRs.
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Affiliation(s)
| | - Patricia Wilson
- Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Cheryl A Sadowski
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada
| | - Darryl Rolfson
- Department of Medicine, Division of Geriatric Medicine, University of Alberta, Edmonton, AB, Canada
| | - Mark Ballermann
- Chief Medical Information Office, Alberta Health Services, University of Alberta, Edmonton, AB, Canada; Division of Critical Care, Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Allen Ausford
- Department of Family Medicine, University of Alberta, Edmonton, AB, Canada; Lynwood Family Physician, University of Alberta, Edmonton, AB, Canada
| | - Karla Vermeer
- Lynwood Family Physician, University of Alberta, Edmonton, AB, Canada
| | - Kunal Mohindra
- eClinician EMR, Alberta Health Services-Information Systems, University of Alberta, Edmonton, AB, Canada
| | - Jacques Romney
- Department of Medicine, Division of Endocrinology, University of Alberta, Edmonton, AB, Canada
| | - Robert S Hayward
- Division of General Internal Medicine, University of Alberta, Edmonton, AB, Canada
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Koskela T, Sandström S, Mäkinen J, Liira H. User perspectives on an electronic decision-support tool performing comprehensive medication reviews - a focus group study with physicians and nurses. BMC Med Inform Decis Mak 2016; 16:6. [PMID: 26801630 PMCID: PMC4724080 DOI: 10.1186/s12911-016-0245-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2015] [Accepted: 01/16/2016] [Indexed: 11/12/2022] Open
Abstract
Background Although a number of studies have evaluated the effectiveness of computerized decision-support systems (CDSS), there is lack of data on user perspectives, barriers, and facilitators to the implementation of CDSSs in real-life surroundings. The aim of this study was to assess individually perceived barriers, facilitators and ideas influencing the CDSS implementation and usability. Methods In this qualitative study, five focus groups were carried out with physicians and nurses separately at the Tampere City Health Center, Finland. The participants were end-users of the EBMeDS computerized decision support system. An explorative data content analysis was applied. Results The most important barrier to benefitting from CDSS was the lack of structured and coded diagnosis documentation and outdated medication information in the electronic health records. This led to false alerts and distrust towards the system. Among the major facilitators found were e.g. the beneficial reminders that helped practitioners take into account matters otherwise ignored; automatic glomerular filtration rate (GFR) calculations; medication safety checks; and the summaries in the single medication review at a glance. Conclusions Physicians’ and nurses’ are keen to use the CDSS and it may enhance their inter-professional collaboration. Documenting patient information in a structured, uniform and easy manner is the essential starting point for electronic decision support. When implementing CDSS, managers need to focus on common practices in documenting structured data in their organizations in order to prevent undermining trust in the system.
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Affiliation(s)
- Tuomas Koskela
- University of Tampere, Department of General Practice, Lääkärinkatu 1, 33014, Tampereen yliopisto, Finland. .,Duodecim Medical Publications Ltd, PO Box 874, 00101, Helsinki, Finland.
| | - Saana Sandström
- Nordic Healthcare Group Ltd (at the time of the study), Vattuniemenranta 2, 00210, Helsinki, Finland.
| | - Joonas Mäkinen
- Duodecim Medical Publications Ltd, PO Box 874, 00101, Helsinki, Finland.
| | - Helena Liira
- School of Primary, Aboriginal and Rural Health Care, University of Western Australia (M706), 35 Stirling Highway, Crawley, WA, 6009, Australia.
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Schuh C, de Bruin JS, Seeling W. Clinical decision support systems at the Vienna General Hospital using Arden Syntax: Design, implementation, and integration. Artif Intell Med 2015; 92:24-33. [PMID: 26706047 DOI: 10.1016/j.artmed.2015.11.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2015] [Revised: 11/05/2015] [Accepted: 11/08/2015] [Indexed: 11/30/2022]
Abstract
INTRODUCTION The Allgemeines Krankenhaus Informations Management (AKIM) project was started at the Vienna General Hospital (VGH) several years ago. This led to the introduction of a new hospital information system (HIS), and the installation of the expert system platform (EXP) for the integration of Arden-Syntax-based clinical decision support systems (CDSSs). In this report we take a look at the milestones achieved and the challenges faced in the creation and modification of CDSSs, and their integration into the HIS over the last three years. MATERIALS AND METHODS We introduce a three-stage development method, which is followed in nearly all CDSS projects at the Medical University of Vienna and the VGH. Stage one comprises requirements engineering and system conception. Stage two focuses on the implementation and testing of the system. Finally, stage three describes the deployment and integration of the system in the VGH HIS. The HIS provides a clinical work environment for healthcare specialists using customizable graphical interfaces known as parametric medical documents. Multiple Arden Syntax servers are employed to host and execute the CDSS knowledge bases: two embedded in the EXP for production and development, and a further three in clinical routine for production, development, and quality assurance. RESULTS Three systems are discussed; the systems serve different purposes in different clinical areas, but are all implemented with Arden Syntax. MONI-ICU is an automated surveillance system for monitoring healthcare-associated infections in the intensive care setting. TSM-CDS is a CDSS used for risk prediction in the formation of cutaneous melanoma metastases. Finally, TacroDS is a CDSS for the manipulation of dosages for tacrolimus, an immunosuppressive agent used after kidney transplantation. Problems in development and integration were related to data quality or availability, although organizational difficulties also caused delays in development and integration. DISCUSSION AND CONCLUSION Since the inception of the AKIM project at the VGH and its ability to support standards such as Arden Syntax and integrate CDSSs into clinical routine, the clinicians' interest in, and demand for, decision support has increased substantially. The use of Arden Syntax as a standard for CDSSs played a substantial role in the ability to rapidly create high-quality CDSS systems, whereas the ability to integrate these systems into the HIS made CDSSs more popular among physicians. Despite these successes, challenges such as lack of (consistent and high-quality) electronic data, social acceptance among healthcare personnel, and legislative issues remain. These have to be addressed effectively before CDSSs can be more widely accepted and adopted.
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Affiliation(s)
- Christian Schuh
- Section for Medical Expert and Knowledge-Based Systems, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria; IT Systems & Communications, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria
| | - Jeroen S de Bruin
- Section for Medical Expert and Knowledge-Based Systems, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria.
| | - Walter Seeling
- Section for Medical Expert and Knowledge-Based Systems, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria; IT Systems & Communications, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria
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Lugtenberg M, Pasveer D, van der Weijden T, Westert GP, Kool RB. Exposure to and experiences with a computerized decision support intervention in primary care: results from a process evaluation. BMC FAMILY PRACTICE 2015; 16:141. [PMID: 26474603 PMCID: PMC4608282 DOI: 10.1186/s12875-015-0364-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2015] [Accepted: 10/08/2015] [Indexed: 01/22/2023]
Abstract
Background Trials evaluating the effects of interventions usually provide little insight into the factors responsible for (lack of) changes in desired outcomes. A process evaluation alongside a trial can shed light on the mechanisms responsible for the outcomes of a trial. The aim of this study was to investigate exposure to and experiences with a computerized decision support system (CDSS) intervention, in order to gain insight into the intervention’s impact and to provide suggestions for improvement. Methods A process evaluation was conducted as part of a large-scale cluster-randomized controlled trial investigating the effects of the CDSS NHGDoc on quality of care. Data on exposure to and experiences with the intervention were collected during the trial period among participants in both the intervention and control group - whenever applicable - by means of the NHGDoc server and an electronic questionnaire. Multiple data were analyzed using descriptive statistics. Results Ninety-nine percent (n = 229) of the included practices generated data for the NHGDoc server and 50 % (n = 116) responded to the questionnaire: both general practitioners (GPs; n = 112; 49 %) and practice nurses (PNs; n = 52; 37 %) participated. The actual exposure to the NHGDoc system and specific heart failure module was limited with 52 % of the GPs and 42 % of the PNs reporting to either never or rarely use the system. Overall, users had a positive attitude towards CDSSs. The most perceived barriers to using NHGDoc were a lack of learning capacity of the system, the additional time and work it requires to use the CDSS, irrelevant alerts, too high intensity of alerts and insufficient knowledge regarding the system. Conclusions Several types of barriers may have negatively affected the impact of the intervention. Although users are generally positive about CDSSs, a large share of them is insufficiently aware of the functions of NHGDoc and, finds the decision support not always useful or relevant and difficult to integrate into daily practice. In designing CDSS interventions we suggest to more intensely involve the end-users and increase the system’s flexibility and learning capacity. To improve implementation a proper introduction of a CDSS among its target group including adequate training is advocated. Trial registration Clinical trials NCT01773057. Electronic supplementary material The online version of this article (doi:10.1186/s12875-015-0364-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marjolein Lugtenberg
- Scientific Institute for Quality of Healthcare (IQ healthcare), Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. .,Scientific Center for Care and Welfare (Tranzo), Tilburg School of Social and Behavioral Sciences, Tilburg University, P.O. Box 90153, 5000 LE, Tilburg, The Netherlands.
| | - Dennis Pasveer
- Scientific Institute for Quality of Healthcare (IQ healthcare), Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - Trudy van der Weijden
- School for Public Health and Primary Care (CAPHRI), Department of General Practice, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.
| | - Gert P Westert
- Scientific Institute for Quality of Healthcare (IQ healthcare), Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - Rudolf B Kool
- Scientific Institute for Quality of Healthcare (IQ healthcare), Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
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