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Estrela M, Magalhães Silva T, Pisco Almeida AM, Regueira C, Zapata-Cachafeiro M, Figueiras A, Roque F, Herdeiro MT. A roadmap for the development and evaluation of the eHealthResp online course. Digit Health 2022; 8:20552076221089088. [PMID: 35360007 PMCID: PMC8961349 DOI: 10.1177/20552076221089088] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 03/06/2022] [Indexed: 11/29/2022] Open
Abstract
Background Inappropriate antibiotic use constitutes one of the most concerning public
health issues, being one of the main causes of antibiotic resistance. Hence,
to tackle this issue, it is important to encourage the development of
educational interventions for health practitioners, namely by using digital
health tools. This study focuses on the description of the development and
validation process of the eHealthResp online course, a web platform directed
to physicians and pharmacists, with the overall goal of improving antibiotic
use for respiratory tract infections, along with the assessment of its
usability. Methods The eHealthResp platform and the courses, developed with a user-centered
design and based on Wordpress and MySQL, were based on a previously
developed online course. A questionnaire to assess the usability was
distributed among physicians (n = 6) and pharmacists (n = 6). Based on the
obtained results, statistical analyses were conducted to calculate the
usability score and appraise the design of the online course, as well as to
compare the overall scores attributed by both groups. Further qualitative
comments provided by the participants have also been analyzed. Results The eHealthResp contains two online courses directed to physicians and
pharmacists aiming to aid in the management of respiratory tract infections.
The average usability score of the eHealthResp online courses for physicians
and pharmacists was of 78.33 (±11.57, 95%CI), and 83.75 (±15.90, 95%CI),
respectively. Qualitative feedback emphasized the usefulness of the course,
including overall positive reviews regarding user-friendliness and
consistency. Conclusions This study led us to conclude that the eHealthResp online course is not
recognized as a complex web platform, as both qualitative and quantitative
feedback obtained were globally positive.
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Affiliation(s)
- Marta Estrela
- iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Tânia Magalhães Silva
- iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | | | - Carlos Regueira
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, 15702 Santiago de Compostela, Spain.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiology and Public Health - CIBERESP), Santiago de Compostela, Spain
| | - Maruxa Zapata-Cachafeiro
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, 15702 Santiago de Compostela, Spain.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiology and Public Health - CIBERESP), Santiago de Compostela, Spain.,Health Research Institute of Santiago de Compostela (IDIS), University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Adolfo Figueiras
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, 15702 Santiago de Compostela, Spain.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiology and Public Health - CIBERESP), Santiago de Compostela, Spain.,Health Research Institute of Santiago de Compostela (IDIS), University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Fátima Roque
- Research Unit for Inland Development, Guarda Polytechnic Institute (UDI-IPG), Guarda, Portugal.,Health Sciences Research Center, University of Beira Interior (CICS-UBI), Covilhã, Portugal
| | - Maria Teresa Herdeiro
- iBiMED - Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
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Agarwal S, Glenton C, Tamrat T, Henschke N, Maayan N, Fønhus MS, Mehl GL, Lewin S. Decision-support tools via mobile devices to improve quality of care in primary healthcare settings. Cochrane Database Syst Rev 2021; 7:CD012944. [PMID: 34314020 PMCID: PMC8406991 DOI: 10.1002/14651858.cd012944.pub2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND The ubiquity of mobile devices has made it possible for clinical decision-support systems (CDSS) to become available to healthcare providers on handheld devices at the point-of-care, including in low- and middle-income countries. The use of CDSS by providers can potentially improve adherence to treatment protocols and patient outcomes. However, the evidence on the effect of the use of CDSS on mobile devices needs to be synthesized. This review was carried out to support a World Health Organization (WHO) guideline that aimed to inform investments on the use of decision-support tools on digital devices to strengthen primary healthcare. OBJECTIVES To assess the effects of digital clinical decision-support systems (CDSS) accessible via mobile devices by primary healthcare providers in the context of primary care settings. SEARCH METHODS We searched CENTRAL, MEDLINE, Embase, Global Index Medicus, POPLINE, and two trial registries from 1 January 2000 to 9 October 2020. We conducted a grey literature search using mHealthevidence.org and issued a call for papers through popular digital health communities of practice. Finally, we conducted citation searches of included studies. SELECTION CRITERIA Study design: we included randomized trials, including full-text studies, conference abstracts, and unpublished data irrespective of publication status or language of publication. Types of participants: we included studies of all cadres of healthcare providers, including lay health workers and other individuals (administrative, managerial, and supervisory staff) involved in the delivery of primary healthcare services using clinical decision-support tools; and studies of clients or patients receiving care from primary healthcare providers using digital decision-support tools. Types of interventions: we included studies comparing digital CDSS accessible via mobile devices with non-digital CDSS or no intervention, in the context of primary care. CDSS could include clinical protocols, checklists, and other job-aids which supported risk prioritization of patients. Mobile devices included mobile phones of any type (but not analogue landline telephones), as well as tablets, personal digital assistants, and smartphones. We excluded studies where digital CDSS were used on laptops or integrated with electronic medical records or other types of longitudinal tracking of clients. DATA COLLECTION AND ANALYSIS A machine learning classifier that gave each record a probability score of being a randomized trial screened all search results. Two review authors screened titles and abstracts of studies with more than 10% probability of being a randomized trial, and one review author screened those with less than 10% probability of being a randomized trial. We followed standard methodological procedures expected by Cochrane and the Effective Practice and Organisation of Care group. We used the GRADE approach to assess the certainty of the evidence for the most important outcomes. MAIN RESULTS Eight randomized trials across varying healthcare contexts in the USA,. India, China, Guatemala, Ghana, and Kenya, met our inclusion criteria. A range of healthcare providers (facility and community-based, formally trained, and lay workers) used digital CDSS. Care was provided for the management of specific conditions such as cardiovascular disease, gastrointestinal risk assessment, and maternal and child health. The certainty of evidence ranged from very low to moderate, and we often downgraded evidence for risk of bias and imprecision. We are uncertain of the effect of this intervention on providers' adherence to recommended practice due to the very low certainty evidence (2 studies, 185 participants). The effect of the intervention on patients' and clients' health behaviours such as smoking and treatment adherence is mixed, with substantial variation across outcomes for similar types of behaviour (2 studies, 2262 participants). The intervention probably makes little or no difference to smoking rates among people at risk of cardiovascular disease but probably increases other types of desired behaviour among patients, such as adherence to treatment. The effect of the intervention on patients'/clients' health status and well-being is also mixed (5 studies, 69,767 participants). It probably makes little or no difference to some types of health outcomes, but we are uncertain about other health outcomes, including maternal and neonatal deaths, due to very low-certainty evidence. The intervention may slightly improve patient or client acceptability and satisfaction (1 study, 187 participants). We found no studies that reported the time between the presentation of an illness and appropriate management, provider acceptability or satisfaction, resource use, or unintended consequences. AUTHORS' CONCLUSIONS We are uncertain about the effectiveness of mobile phone-based decision-support tools on several outcomes, including adherence to recommended practice. None of the studies had a quality of care framework and focused only on specific health areas. We need well-designed research that takes a systems lens to assess these issues.
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Affiliation(s)
- Smisha Agarwal
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, Maryland (MD), USA
| | | | - Tigest Tamrat
- Department of Sexual and Reproductive Health, World Health Organization, Geneva, Switzerland
| | | | | | | | - Garrett L Mehl
- Department of Sexual and Reproductive Health, World Health Organization, Geneva, Switzerland
| | - Simon Lewin
- Norwegian Institute of Public Health, Oslo, Norway
- Health Systems Research Unit, South African Medical Research Council, Cape Town, South Africa
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Carvalho É, Estrela M, Zapata-Cachafeiro M, Figueiras A, Roque F, Herdeiro MT. E-Health Tools to Improve Antibiotic Use and Resistances: A Systematic Review. Antibiotics (Basel) 2020; 9:antibiotics9080505. [PMID: 32806583 PMCID: PMC7460242 DOI: 10.3390/antibiotics9080505] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 08/10/2020] [Accepted: 08/11/2020] [Indexed: 12/04/2022] Open
Abstract
(1) Background: e-Health tools, especially in the form of clinical decision support systems (CDSSs), have been emerging more quickly than ever before. The main objective of this systematic review is to assess the influence of these tools on antibiotic use for respiratory tract infections. (2) Methods: The scientific databases, MEDLINE-PubMed and EMBASE, were searched. The search was conducted by two independent researchers. The search strategy was mainly designed to identify relevant studies on the effectiveness of CDSSs in improving antibiotic use, as a primary outcome, and on the acceptability and usability of CDSSs, as a secondary outcome. (3) Results: After the selection, 22 articles were included. The outcomes were grouped either into antibiotics prescription practices or adherence to guidelines concerning antibiotics prescription. Overall, 15 out of the 22 studies had statistically significant outcomes related to the interventions. (4) Conclusions: Overall, the results show a positive impact on the prescription and conscientious use of antibiotics for respiratory tract infections, both with respect to patients and prescribing healthcare professionals. CDSSs have been shown to have great potential as powerful tools for improving both clinical care and patient outcomes.
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Affiliation(s)
- Érico Carvalho
- iBiMED–Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, 3800 Aveiro, Portugal; (É.C.); (M.E.)
| | - Marta Estrela
- iBiMED–Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, 3800 Aveiro, Portugal; (É.C.); (M.E.)
| | - Maruxa Zapata-Cachafeiro
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, 15702 Santiago de Compostela, Spain; (M.Z.-C.); (A.F.)
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiology and Public Health-CIBERESP), 28001 Madrid, Spain
| | - Adolfo Figueiras
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, 15702 Santiago de Compostela, Spain; (M.Z.-C.); (A.F.)
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiology and Public Health-CIBERESP), 28001 Madrid, Spain
- Health Research Institute of Santiago de Compostela (IDIS), 15706 Santiago de Compostela, Spain
| | - Fátima Roque
- Research Unit for Inland Development-Polytechnic of Guarda (UDI-IPG), 6300 Guarda, Portugal;
- Health Sciences Research Centre, University of Beira Interior (CICS-UBI), 6200 Covilhã, Portugal
| | - Maria Teresa Herdeiro
- iBiMED–Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, 3800 Aveiro, Portugal; (É.C.); (M.E.)
- Correspondence:
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Mishuris RG, Yoder J, Wilson D, Mann D. Integrating data from an online diabetes prevention program into an electronic health record and clinical workflow, a design phase usability study. BMC Med Inform Decis Mak 2016; 16:88. [PMID: 27401606 PMCID: PMC4940704 DOI: 10.1186/s12911-016-0328-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 07/03/2016] [Indexed: 12/18/2022] Open
Abstract
Background Health information is increasingly being digitally stored and exchanged. The public is regularly collecting and storing health-related data on their own electronic devices and in the cloud. Diabetes prevention is an increasingly important preventive health measure, and diet and exercise are key components of this. Patients are turning to online programs to help them lose weight. Despite primary care physicians being important in patients’ weight loss success, there is no exchange of information between the primary care provider (PCP) and these online weight loss programs. There is an emerging opportunity to integrate this data directly into the electronic health record (EHR), but little is known about what information to share or how to share it most effectively. This study aims to characterize the preferences of providers concerning the integration of externally generated lifestyle modification data into a primary care EHR workflow. Methods We performed a qualitative study using two rounds of semi-structured interviews with primary care providers. We used an iterative design process involving primary care providers, health information technology software developers and health services researchers to develop the interface. Results Using grounded-theory thematic analysis 4 themes emerged from the interviews: 1) barriers to establishing healthy lifestyles, 2) features of a lifestyle modification program, 3) reporting of outcomes to the primary care provider, and 4) integration with primary care. These themes guided the rapid-cycle agile design process of an interface of data from an online diabetes prevention program into the primary care EHR workflow. Conclusions The integration of external health-related data into the EHR must be embedded into the provider workflow in order to be useful to the provider and beneficial for the patient. Accomplishing this requires evaluation of that clinical workflow during software design. The development of this novel interface used rapid cycle iterative design, early involvement by providers, and usability testing methodology. This provides a framework for how to integrate external data into provider workflow in efficient and effective ways. There is now the potential to realize the importance of having this data available in the clinical setting for patient engagement and health outcomes.
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Affiliation(s)
- Rebecca Grochow Mishuris
- Boston University School of Medicine, 801 Massachusetts Avenue, Crosstown 2nd floor, Boston, MA, 02118, USA.
| | - Jordan Yoder
- Boston University School of Medicine, 801 Massachusetts Avenue, Crosstown 2nd floor, Boston, MA, 02118, USA
| | | | - Devin Mann
- Boston University School of Medicine, 801 Massachusetts Avenue, Crosstown 2nd floor, Boston, MA, 02118, USA
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Lehmann CU, Gundlapalli AV. Improving Bridging from Informatics Practice to Theory. Methods Inf Med 2015; 54:540-5. [PMID: 26577504 DOI: 10.3414/me15-01-0138] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 10/22/2015] [Indexed: 11/09/2022]
Abstract
BACKGROUND In 1962, Methods of Information in Medicine ( MIM ) began to publish papers on the methodology and scientific fundamentals of organizing, representing, and analyzing data, information, and knowledge in biomedicine and health care. Considered a companion journal, Applied Clinical Informatics ( ACI ) was launched in 2009 with a mission to establish a platform that allows sharing of knowledge between clinical medicine and health IT specialists as well as to bridge gaps between visionary design and successful and pragmatic deployment of clinical information systems. Both journals are official journals of the International Medical Informatics Association. OBJECTIVES As a follow-up to prior work, we set out to explore congruencies and interdependencies in publications of ACI and MIM. The objectives were to describe the major topics discussed in articles published in ACI in 2014 and to determine if there was evidence that theory in 2014 MIM publications was informed by practice described in ACI publications in any year. We also set out to describe lessons learned in the context of bridging informatics practice and theory and offer opinions on how ACI editorial policies could evolve to foster and improve such bridging. METHODS We conducted a retrospective observational study and reviewed all articles published in ACI during the calendar year 2014 (Volume 5) for their main theme, conclusions, and key words. We then reviewed the citations of all MIM papers from 2014 to determine if there were references to ACI articles from any year. Lessons learned in the context of bridging informatics practice and theory and opinions on ACI editorial policies were developed by consensus among the two authors. RESULTS A total of 70 articles were published in ACI in 2014. Clinical decision support, clinical documentation, usability, Meaningful Use, health information exchange, patient portals, and clinical research informatics emerged as major themes. Only one MIM article from 2014 cited an ACI article. There are several lessons learned including the possibility that there may not be direct links between MIM theory and ACI practice articles. ACI editorial policies will continue to evolve to reflect the breadth and depth of the practice of clinical informatics and articles received for publication. Efforts to encourage bridging of informatics practice and theory may be considered by the ACI editors. CONCLUSIONS The lack of direct links from informatics theory-based papers published in MIM in 2014 to papers published in ACI continues as was described for papers published during 2012 to 2013 in the two companion journals. Thus, there is little evidence that theory in MIM has been informed by practice in ACI.
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Affiliation(s)
| | - A V Gundlapalli
- Adi V. Gundlapalli, MD, PhD, MS, Chief Health Informatics Officer, VA Salt Lake City Health Care System, Salt Lake City, UT 84148, USA, E-mail:
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Gordon CL, Weng C. Combining expert knowledge and knowledge automatically acquired from electronic data sources for continued ontology evaluation and improvement. J Biomed Inform 2015. [PMID: 26212414 DOI: 10.1016/j.jbi.2015.07.014] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
INTRODUCTION A common bottleneck during ontology evaluation is knowledge acquisition from domain experts for gold standard creation. This paper contributes a novel semi-automated method for evaluating the concept coverage and accuracy of biomedical ontologies by complementing expert knowledge with knowledge automatically extracted from clinical practice guidelines and electronic health records, which minimizes reliance on expensive domain expertise for gold standards generation. METHODS We developed a bacterial clinical infectious diseases ontology (BCIDO) to assist clinical infectious disease treatment decision support. Using a semi-automated method we integrated diverse knowledge sources, including publically available infectious disease guidelines from international repositories, electronic health records, and expert-generated infectious disease case scenarios, to generate a compendium of infectious disease knowledge and use it to evaluate the accuracy and coverage of BCIDO. RESULTS BCIDO has three classes (i.e., infectious disease, antibiotic, bacteria) containing 593 distinct concepts and 2345 distinct concept relationships. Our semi-automated method generated an ID knowledge compendium consisting of 637 concepts and 1554 concept relationships. Overall, BCIDO covered 79% (504/637) of the concepts and 89% (1378/1554) of the concept relationships in the ID compendium. BCIDO coverage of ID compendium concepts was 92% (121/131) for antibiotic, 80% (205/257) for infectious disease, and 72% (178/249) for bacteria. The low coverage of bacterial concepts in BCIDO was due to a difference in concept granularity between BCIDO and infectious disease guidelines. Guidelines and expert generated scenarios were the richest source of ID concepts and relationships while patient records provided relatively fewer concepts and relationships. CONCLUSIONS Our semi-automated method was cost-effective for generating a useful knowledge compendium with minimal reliance on domain experts. This method can be useful for continued development and evaluation of biomedical ontologies for better accuracy and coverage.
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Affiliation(s)
- Claire L Gordon
- Department of Medicine, Columbia University Medical Center, 630 West 168th Street, New York, USA; Department of Biomedical Informatics, Columbia University Medical Center, 622 West 168th Street, New York, NY 10032, USA; Department of Medicine, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Medical Center, 622 West 168th Street, New York, NY 10032, USA.
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Kannry J, McCullagh L, Kushniruk A, Mann D, Edonyabo D, McGinn T. A Framework for Usable and Effective Clinical Decision Support: Experience from the iCPR Randomized Clinical Trial. EGEMS 2015; 3:1150. [PMID: 26290888 PMCID: PMC4537146 DOI: 10.13063/2327-9214.1150] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
INTRODUCTION The promise of Clinical Decision Support (CDS) has always been to transform patient care and improve patient outcomes through the delivery of timely and appropriate recommendations that are patient specific and, more often than not, are appropriately actionable. However, the users of CDS-providers-are frequently bombarded with inappropriate and inapplicable CDS that often are not informational, not integrated into the workflow, not patient specific, and that may present out of date and irrelevant recommendations. METHODS The integrated clinical prediction rule (iCPR) project was a randomized clinical trial (RCT) conducted to determine if a novel form of CDS, i.e., clinical prediction rules (CPRs), could be efficiently integrated into workflow and result in changes in outcomes (e.g., antibiotic ordering) when embedded within a commercial electronic health record (EHR). We use the lessons learned from the iCPR project to illustrate a framework for constructing usable, useful, and effective actionable CDS while employing off-the-shelf functionality in a production system. Innovations that make up the framework combine the following: (1) active and actionable decision support, (2) multiple rounds of usability testing with iterative development for user acceptance, (3) numerous context sensitive triggers, (4) dedicated training and support for users of the CDS tool for user adoption, and (5) support from clinical and administrative leadership. We define "context sensitive triggers" as being workflow events (i.e., context) that result in a CDS intervention. DISCUSSION Success of the framework can be measured by CDS adoption (i.e., intervention is being used), acceptance (compliance with recommendations), and clinical outcomes (where appropriate). This framework may have broader implications for the deployment of Health Information Technology (HIT). RESULTS AND CONCLUSION iCPR was well adopted(57.4% of users) and accepted (42.7% of users). Usability testing identified and fixed many issues before the iCPR RCT. The level of leadership support and clinical guidance for iCPR was key in establishing a culture of acceptance for both the tool and its recommendations contributing to adoption and acceptance. The dedicated training and support lead to the majority of the residents reporting a high level of comfort with both iCPR tools strep pharyngitis (64.4 percent) and pneumonia (62.7 percent) as well as a high likelihood of using the tools in the future. A surprising framework addition resulted from usability testing: context sensitive triggers.
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