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Abstract
PURPOSE OF REVIEW Coordination of glucose monitoring, mealtimes, and insulin delivery in the hospital is complex, involving interactions between multiple key agents and overlapping workflows. The purpose of this review is to evaluate the scope of the problem as well as to assess evidence for interventions. RECENT FINDINGS In recent years, there has been an emphasis on systems-based approaches which address multiple contributing components of the problem at once in an effort to more seamlessly integrate workflows. Technological advances, such as decision support systems and advances in automated insulin delivery, and strategies that minimize the need for complex insulin regimens hold promise for future study. Evaluation of the coordination of insulin delivery is limited by a lack of standardized metrics and systematically collected mealtimes. Nevertheless, successful efforts include system-wide multicomponent interventions, though advances in therapeutic approaches may be of value.
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Affiliation(s)
- Kathleen Dungan
- Division of Endocrinology, Diabetes and Metabolism, The Ohio State University, Columbus, OH, 43210, USA.
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Shahmoradi L, Liraki Z, Karami M, Savareh BA, Nosratabadi M. Development of Decision Support System to Predict Neurofeedback Response in ADHD: an Artificial Neural Network Approach. Acta Inform Med 2019; 27:186-191. [PMID: 31762576 PMCID: PMC6853721 DOI: 10.5455/aim.2019.27.186-191] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 08/05/2019] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Clinical decision support system (CDSS) is an analytical tool that converts raw data into useful information to help clinicians make better decisions for patients. AIM The purpose of this study was to investigate the efficacy of neurofeedback (NF), in Attention Deficit Hyperactivity Disorder (ADHD) by the development of CDSS based on artificial neural network (ANN). METHODS This study analyzed 122 patients with ADHD who underwent NF in the Parand-Human Potential Empowerment Institute in Tehran. The patients were divided into two groups according to the effects of NF: effective and non-effective groups. The patients' record information was mined by data mining techniques to identify effective features. Based on unsaturated condition of data and imbalanced classes between the patient groups (patients with successful NF response and those without it), the SMOTE technique was applied on dataset. Using MATLAB 2014a, a modular program was designed to test both multiple architectures of neural networks and their performance. Selected architecture of the neural networks was then applied in the procedure. RESULTS Eleven features from 28 features of the initial dataset were selected as effective features. Using the SMOTE technique, number of the samples rose to around 300 samples. Based on the multiple neural networks architecture testing, a network by 11-20-16-2 neurons was selected (specify>00.91%, sensivity=100%) and applied in the software. CONCLUSION The ANN used in this study has led to good results in sensivity, specificity, and AUC. The ANN and other intelligent techniques can be used as supportive tools for decision making by healthcare providers.
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Affiliation(s)
- Leila Shahmoradi
- Halal Research Center of IRI, FDA, Tehran, Iran
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Zahra Liraki
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahtab Karami
- Department of Health, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Behrouz Alizadeh Savareh
- Department of Health Information Technology and Management, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Masoud Nosratabadi
- Department of Clinical Psychology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
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Imani MM, Safaei M, Afnaniesfandabad A, Moradpoor H, Sadeghi M, Golshah A, Sharifi R, Mozaffari HR. Efficacy of CPP-ACP and CPP-ACPF for Prevention and Remineralization of White Spot Lesions in Orthodontic Patients: a Systematic Review of Randomized Controlled Clinical Trials. Acta Inform Med 2019; 27:199-204. [PMID: 31762578 PMCID: PMC6853720 DOI: 10.5455/aim.2019.27.199-204] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 08/08/2019] [Indexed: 11/26/2022] Open
Abstract
INTRODUCTION Enamel subsurface lesions or white spot lesions (WSLs) are commonly found in orthodontic patients with a prevalence of 5% to 97%. AIM This systematic review aimed to evaluate the efficacy of casein phosphopeptide amorphous calcium phosphate (CPP-ACP) and casein phosphopeptide amorphous calcium phosphate fluoride (CPP-ACPF) for prevention and remineralization of WSLs in orthodontic patients in human randomized controlled clinical trials (RCTs). METHODS Relevant articles were retrieved by searching the Web of Science, Scopus, PubMed, and Cochrane Library databases up to November 2018 with no language or date restriction. The collected data included examination method, groups included in each study with number of patients in each group, study design, follow-up period and summary of important findings of each study. The risk of bias of each study was assessed according to the guidelines of the Cochrane Collaboration's tool. RESULTS Of 213 articles retrieved, 13 RCTs were included in this systematic review (none of them were included in the meta-analysis). Three articles showed superior efficacy of CPP-ACP for remineralization of WSLs while four studies reported the superior clinical efficacy of CPP-ACPF for this purpose. CONCLUSION Both CPP-ACP and CPP-ACPF can decrease the prevalence and increase the remineralization of WSLs during/after orthodontic treatment.
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Affiliation(s)
- Mohammad Moslem Imani
- Department of Orthodontics, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mohsen Safaei
- Oral and Dental Sciences Research Laboratory, School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Aida Afnaniesfandabad
- Students Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Hedaiat Moradpoor
- Department of Prosthodontics, School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Masoud Sadeghi
- Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Amin Golshah
- Department of Orthodontics, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Roohollah Sharifi
- Department of Endodontics, School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Hamid Reza Mozaffari
- Department of Oral and Maxillofacial Medicine, School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran
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Veinot TC, Senteio CR, Hanauer D, Lowery JC. Comprehensive process model of clinical information interaction in primary care: results of a "best-fit" framework synthesis. J Am Med Inform Assoc 2018; 25:746-758. [PMID: 29025114 PMCID: PMC7646963 DOI: 10.1093/jamia/ocx085] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2017] [Revised: 07/18/2017] [Accepted: 08/01/2017] [Indexed: 01/04/2023] Open
Abstract
Objective To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research. Materials and Methods We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research. Results The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process. Discussion The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations. Conclusion The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.
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Affiliation(s)
- Tiffany C Veinot
- School of Information and School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Charles R Senteio
- Department of Library and Information Science, School of Communication and Information, Rutgers University, New Brunswick, NJ, USA
| | - David Hanauer
- Department of Pediatrics, Medical School, University of Michigan, Ann Arbor, MI, USA
| | - Julie C Lowery
- Center for Clinical Management, Research, VA Ann Arbor Healthcare System, University of Michigan, Ann Arbor, MI, USA
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Alwan D, Chipps E, Yen PY, Dungan K. Evaluation of the timing and coordination of prandial insulin administration in the hospital. Diabetes Res Clin Pract 2017; 131:18-32. [PMID: 28668719 DOI: 10.1016/j.diabres.2017.06.021] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 06/08/2017] [Accepted: 06/15/2017] [Indexed: 11/29/2022]
Abstract
AIMS The objective of this study was to examine the relationship between measures of coordinated insulin delivery and capillary blood glucose (CBG) levels among hospitalized patients and to assess nurse perceptions of insulin administration. METHODS Hospitalized patients (n=451) receiving rapid acting insulin analog (RAIA) using carbohydrate counting were retrospectively analyzed. Nurses (n=35) were asked to complete an 18-item anonymous survey assessing perception of RAIA dosing. RESULTS The median time from breakfast CBG to RAIA dose was 93 (IQR 57-138) min. There was no association between timeliness measures and mean CBG at lunch or dinner. Hypoglycemia was rare (N=2). More than half (54%) of nurses were confident all of the time in determining the correct dose of RAIA, though none were confident in administering it on time. The majority of nurses perceived an electronic dosing calculator and a patient reminder to notify the nurse at the end of the meal favorably. CONCLUSIONS The data demonstrate suboptimal coordination of CBG monitoring and insulin doses using a flexible meal insulin dosing strategy, though there was minimal impact on glycemic control. Nurses reported high confidence in the ability to calculate the correct insulin dose but not in the ability to administer it on time.
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Affiliation(s)
- Dhuha Alwan
- The Ohio State University, College of Public Health, United States
| | - Esther Chipps
- The Ohio State University, College of Nursing, The Ohio State University Wexner Medical Center, 600 Ackerman Road, E2016, Columbus, OH, United States
| | - Po-Yin Yen
- The Ohio State University Department of Biomedical Informatics, 250 Lincoln Tower, 1800 Cannon Drive, Columbus, OH, United States
| | - Kathleen Dungan
- The Ohio State University, Division of Endocrinology, Diabetes & Metabolism, United States.
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Kuziemsky CE, Randell R, Borycki EM. Understanding Unintended Consequences and Health Information Technology:. Contribution from the IMIA Organizational and Social Issues Working Group. Yearb Med Inform 2016:53-60. [PMID: 27830231 DOI: 10.15265/iy-2016-027] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE No framework exists to identify and study unintended consequences (UICs) with a focus on organizational and social issues (OSIs). To address this shortcoming, we conducted a literature review to develop a framework for considering UICs and health information technology (HIT) from the perspective of OSIs. METHODS A literature review was conducted for the period 2000- 2015 using the search terms "unintended consequences" and "health information technology". 67 papers were screened, of which 18 met inclusion criteria. Data extraction was focused on the types of technologies studied, types of UICs identified, and methods of data collection and analysis used. A thematic analysis was used to identify themes related to UICs. RESULTS We identified two overarching themes. One was the definition and terminology of how people classify and discuss UICs. Second was OSIs and UICs. For the OSI theme, we also identified four sub-themes: process change and evolution, individual-collaborative interchange, context of use, and approaches to model, study, and understand UICs. CONCLUSIONS While there is a wide body of research on UICs, there is a lack of overall consensus on how they should be classified and reported, limiting our ability to understand the implications of UICs and how to manage them. More mixed-methods research and better proactive identification of UICs remain priorities. Our findings and framework of OSI considerations for studying UICs and HIT extend existing work on HIT and UICs by focusing on organizational and social issues.
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Affiliation(s)
- C E Kuziemsky
- Craig Kuziemsky, Telfer School of Management, University of Ottawa, Ottawa, ON, Canada, Tel: +1 613 562 5800 ext 4792, E-mail:
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A Critical Review of the Theoretical Frameworks and the Conceptual Factors in the Adoption of Clinical Decision Support Systems. Comput Inform Nurs 2015; 33:555-70. [DOI: 10.1097/cin.0000000000000196] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Evaluation of a comprehensive EHR based on the DeLone and McLean model for IS success: approach, results, and success factors. Int J Med Inform 2013; 82:940-53. [PMID: 23827768 DOI: 10.1016/j.ijmedinf.2013.05.010] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2012] [Revised: 05/29/2013] [Accepted: 05/30/2013] [Indexed: 12/27/2022]
Abstract
OBJECTIVE The article describes the methodological approach to, and results of an evaluation of a comprehensive electronic health record (EHR) in the shake down phase, shortly after its implementation at a regional hospital in Denmark. DESIGN A formative evaluation based on a mixed-methods case study, designed to be interactive and concurrent was conducted at two hospital departments based on the updated DeLone and McLean framework for evaluating information systems success. METHODS To ascertain user assessments of the EHR, we distributed a questionnaire two months after implementation to four groups of staff (physicians, nurses, medical secretaries, and physiotherapists; n=244), and at the same time we conducted thirteen individual, semi-structured interviews with representatives from these four groups. Subsequently, seven follow-up focus group interviews were conducted with the four above-mentioned groups, in order to go deeper into specific user assessments. Simultaneously, focus group interviews with two IT departments and the implementation team were conducted, to gain insight into system provider assessments of the implementation process and the EHR. Before, during, and after implementation, 88 h of ethnographic observation were carried out, to give the researchers an understanding of the daily routine of staff, and their use of health records. Finally, daily system performance data were obtained, to gather factual information on system response and downtime. RESULTS Overall, staff had positive experiences with the EHR and its operational reliability, response time, login and support. Performance was acceptable. Medical secretaries found the use of the patient administration module cumbersome, and physicians found the establishment of the overview of professionally relevant data challenging. There were demands for improvements to these and other functionalities, and for the EHR to be integrated with other systems and databases. LIMITATIONS Evaluations immediately following implementation are inherently difficult, but was required because a key role was to inform decision-making upon enrollment at other hospitals and systematically identify barriers in this respect. The strength of the evaluation is the mixed-methods approach. Further, the evaluation was based on assessments from staff in two departments that comprise around 50% of hospital staff. A weakness may be that staff assessment plays a major role in interviews and survey. These though are supplemented by performance data and observation. Also, the evaluation primarily reports upon the dimension 'user satisfaction', since use of the EHR is mandatory. Finally, generalizability may be low, since the evaluation was not based on a validated survey. All in all, however, the evaluation proposes an evaluation design in constrained circumstances. CONCLUSIONS Despite inherent limitations, evaluation of a comprehensive EHR shortly after implementation may be necessary, can be conducted, and may inform political decision making. The updated DeLone and McLean framework was constructive in the overall design of the evaluation of the EHR implementation, and allowed the model to be adapted to the health care domain by being methodological flexible. The mixed-methods case study produced valid and reliable results, and was accepted by staff, system providers, and political decision makers. The successful implementation may be attributed to the configurability of the EHR and to factors such as an experienced, competent implementation organization at the hospital, upgraded soft- and hardware, and a high degree of user involvement.
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Wagholikar KB, MacLaughlin KL, Henry MR, Greenes RA, Hankey RA, Liu H, Chaudhry R. Clinical decision support with automated text processing for cervical cancer screening. J Am Med Inform Assoc 2012; 19:833-9. [PMID: 22542812 PMCID: PMC3422840 DOI: 10.1136/amiajnl-2012-000820] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2012] [Accepted: 03/31/2012] [Indexed: 01/16/2023] Open
Abstract
OBJECTIVE To develop a computerized clinical decision support system (CDSS) for cervical cancer screening that can interpret free-text Papanicolaou (Pap) reports. MATERIALS AND METHODS The CDSS was constituted by two rulebases: the free-text rulebase for interpreting Pap reports and a guideline rulebase. The free-text rulebase was developed by analyzing a corpus of 49 293 Pap reports. The guideline rulebase was constructed using national cervical cancer screening guidelines. The CDSS accesses the electronic medical record (EMR) system to generate patient-specific recommendations. For evaluation, the screening recommendations made by the CDSS for 74 patients were reviewed by a physician. RESULTS AND DISCUSSION Evaluation revealed that the CDSS outputs the optimal screening recommendations for 73 out of 74 test patients and it identified two cases for gynecology referral that were missed by the physician. The CDSS aided the physician to amend recommendations in six cases. The failure case was because human papillomavirus (HPV) testing was sometimes performed separately from the Pap test and these results were reported by a laboratory system that was not queried by the CDSS. Subsequently, the CDSS was upgraded to look up the HPV results missed earlier and it generated the optimal recommendations for all 74 test cases. LIMITATIONS Single institution and single expert study. CONCLUSION An accurate CDSS system could be constructed for cervical cancer screening given the standardized reporting of Pap tests and the availability of explicit guidelines. Overall, the study demonstrates that free text in the EMR can be effectively utilized through natural language processing to develop clinical decision support tools.
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Affiliation(s)
- Kavishwar B Wagholikar
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota 55905, USA.
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Nirantharakumar K, Chen YF, Marshall T, Webber J, Coleman JJ. Clinical decision support systems in the care of inpatients with diabetes in non-critical care setting: systematic review. Diabet Med 2012; 29:698-708. [PMID: 22150466 DOI: 10.1111/j.1464-5491.2011.03540.x] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Computerized clinical decision support systems have been claimed to reduce prescription errors and improve patient care. They may play an important role in the care of hospitalized patients with diabetes. AIM To collate evidence for the use of clinical decision support systems in improving the care of hospitalized patients with diabetes in a non-critical care setting and to assess their effectiveness. METHODS We searched four databases from 1980 to 2010 without language restrictions. All types of studies other than case reports were included. Data extraction and quality assessment were carried out based on the Centre for Review and Dissemination guidance. A narrative synthesis was conducted. RESULTS Fourteen studies met the inclusion criteria, including two cluster randomized controlled trials, eight before-and-after studies and four other descriptive studies. Generally, the quality of the studies was not very high. Nine out of 10 studies reported reduction in mean blood glucose or similar measures (patient-day-weighted mean blood glucose) during inpatient stay. The reduction using computerized physician order entry system in patient-day-weighted mean blood glucose ranged from 0.6 to 0.8 mmol/l (10.8-15.6 mg/dl). Other beneficial effects during inpatient stay included reduced use of sliding scale insulin and greater use of basal-bolus insulin regimen. Only one study found a significant increase in hypoglycaemic events. CONCLUSIONS Clinical decision support systems have been used, often as part of a complex programme, to improve the care of hospitalized patients with diabetes. There is some evidence that they may have a beneficial effect, but this needs further confirmation.
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Bouw JW, Campbell N, Hull MA, Juneja R, Guzman O, Overholser BR. A retrospective cohort study of a nurse-driven computerized insulin infusion program versus a paper-based protocol in critically ill patients. Diabetes Technol Ther 2012; 14:125-30. [PMID: 22011007 DOI: 10.1089/dia.2011.0130] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND There is variability in the extent of outcome achievement between computerized insulin infusion programs (CIIPs) and paper-based protocols (PBPs). This reported variability may be improved by intensive CIIP training prior to implementation. The objective was to evaluate the impact of a CIIP following intensive nurse training versus a PBP in a critical care setting. METHODS A retrospective cohort study was performed on patients admitted to a mixed intensive care unit comparing glucose control between the CIIP following intensive training and a PBP. Consecutive patients on each protocol were assessed to obtain glucose concentrations and outcomes. The primary measure was the percentage of blood glucose values within target range (90-130 mg/dL). Patient glucose values were pooled and assessed using the χ(2) test for independence. RESULTS In total, 61 patients with 5,495 glucose tests were included in the PBP group, and 51 patients with 5,645 glucose tests in the CIIP group. A greater percentage of glucose tests was within target range in the CIIP group (68.4% vs. 36.5%, P<0.001). In the CIIP group, time-to-target (median [interquartile range] 5 [3-8] h vs. 7 [4-20] h, P=0.02) and severe hypoglycemic events were reduced (26 vs. 6, P<0.0001). CONCLUSIONS The nurse-driven CIIP led to a higher percentage of glucose values within target range, faster achievement of target glucose values, and a reduction in the number of severe hypoglycemic events. This improved outcome achievement compared with previous reports may be associated with intensive user training.
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Affiliation(s)
- Justin W Bouw
- Department of Pharmacy, Roudebush VA Medical Center, Indianapolis, Indiana, USA
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Waitman LR, Warren JJ, Manos EL, Connolly DW. Expressing observations from electronic medical record flowsheets in an i2b2 based clinical data repository to support research and quality improvement. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2011; 2011:1454-63. [PMID: 22195209 PMCID: PMC3243191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
While nursing documentation in electronic medical record (EMR) flowsheets may represent the largest investment of clinician time with information systems, organizations lack tools to visualize and repurpose this data for research and quality improvement. Incorporating flowsheet documentation into a clinical data repository and methods to reduce the flowsheet ontology's redundancy are described. 411 million flowsheet observations, derived from an EMR predominantly used in inpatient, outpatient oncology, and emergency room settings, were incorporated into a repository using the i2b2 framework. The local flowsheet ontology contained 720 "templates" employing 5,379 groups (2,678 distinct), 37,836 measures (13,659 distinct) containing 226,666 choices for a total size of 270,641. Aggressive pruning and clustering resulted in 150 templates, 743 groups (615 distinct), 6,950 measures (4,066 distinct) with 22,497 choices, and size of 30,371. Making nursing data accessible within i2b2 provides a new perspective for contributing clinical organizations and heightens collaboration between the academic and clinical activities.
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Affiliation(s)
- Lemuel R Waitman
- Division of Medical Informatics, Department of Biostatistics, University of Kansas Medical Center, Kansas City, KS, USA
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Campion TR, Waitman LR, Lorenzi NM, May AK, Gadd CS. Barriers and facilitators to the use of computer-based intensive insulin therapy. Int J Med Inform 2011; 80:863-71. [PMID: 22019280 DOI: 10.1016/j.ijmedinf.2011.10.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2011] [Revised: 08/15/2011] [Accepted: 10/03/2011] [Indexed: 01/04/2023]
Abstract
PURPOSE Computerized clinical decision support systems (CDSSs) for intensive insulin therapy (IIT) are increasingly common. However, recent studies question IIT's safety and mortality benefit. Researchers have identified factors influencing IIT performance, but little is known about how workflow affects computer-based IIT. We used ethnographic methods to evaluate IIT CDSS with respect to other clinical information systems and care processes. METHODS We conducted direct observation of and unstructured interviews with nurses using IIT CDSS in the surgical and trauma intensive care units at an academic medical center. We observed 49h of intensive care unit workflow including 49 instances of nurses using IIT CDSS embedded in a provider order entry system. Observations focused on the interaction of people, process, and technology. By analyzing qualitative field note data through an inductive approach, we identified barriers and facilitators to IIT CDSS use. RESULTS Barriers included (1) workload tradeoffs between computer system use and direct patient care, especially related to electronic nursing documentation, (2) lack of IIT CDSS protocol reminders, (3) inaccurate user interface design assumptions, and (4) potential for error in operating medical devices. Facilitators included (1) nurse trust in IIT CDSS combined with clinical judgment, (2) nurse resilience, and (3) paper serving as an intermediary between patient bedside and IIT CDSS. CONCLUSION This analysis revealed sociotechnical interactions affecting IIT CDSS that previous studies have not addressed. These issues may influence protocol performance at other institutions. Findings have implications for IIT CDSS user interface design and alerts, and may contribute to nascent general CDSS theory.
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Affiliation(s)
- Thomas R Campion
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, United States.
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Campion TR, May AK, Waitman LR, Ozdas A, Lorenzi NM, Gadd CS. Characteristics and effects of nurse dosing over-rides on computer-based intensive insulin therapy protocol performance. J Am Med Inform Assoc 2011; 18:251-8. [PMID: 21402737 DOI: 10.1136/amiajnl-2011-000129] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE To determine characteristics and effects of nurse dosing over-rides of a clinical decision support system (CDSS) for intensive insulin therapy (IIT) in critical care units. DESIGN Retrospective analysis of patient database records and ethnographic study of nurses using IIT CDSS. MEASUREMENTS The authors determined the frequency, direction-greater than recommended (GTR) and less than recommended (LTR)- and magnitude of over-rides, and then compared recommended and over-ride doses' blood glucose (BG) variability and insulin resistance, two measures of IIT CDSS associated with mortality. The authors hypothesized that rates of hypoglycemia and hyperglycemia would be greater for recommended than over-ride doses. Finally, the authors observed and interviewed nurse users. RESULTS 5.1% (9075) of 179,452 IIT CDSS doses were over-rides. 83.4% of over-ride doses were LTR, and 45.5% of these were ≥ 50% lower than recommended. In contrast, 78.9% of GTR doses were ≤ 25% higher than recommended. When recommended doses were administered, the rate of hypoglycemia was higher than the rate for GTR (p = 0.257) and LTR (p = 0.033) doses. When recommended doses were administered, the rate of hyperglycemia was lower than the rate for GTR (p = 0.003) and LTR (p < 0.001) doses. Estimates of patients' insulin requirements were higher for LTR doses than recommended and GTR doses. Nurses reported trusting IIT CDSS overall but appeared concerned about recommendations when administering LTR doses. CONCLUSION When over-riding IIT CDSS recommendations, nurses overwhelmingly administered LTR doses, which emphasized prevention of hypoglycemia but interfered with hyperglycemia control, especially when BG was >150 mg/dl. Nurses appeared to consider the amount of a recommended insulin dose, not a patient's trend of insulin resistance, when administering LTR doses overall. Over-rides affected IIT CDSS protocol performance.
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Affiliation(s)
- Thomas R Campion
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
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Black AD, Car J, Pagliari C, Anandan C, Cresswell K, Bokun T, McKinstry B, Procter R, Majeed A, Sheikh A. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med 2011; 8:e1000387. [PMID: 21267058 PMCID: PMC3022523 DOI: 10.1371/journal.pmed.1000387] [Citation(s) in RCA: 636] [Impact Index Per Article: 48.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2009] [Accepted: 11/19/2010] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND There is considerable international interest in exploiting the potential of digital solutions to enhance the quality and safety of health care. Implementations of transformative eHealth technologies are underway globally, often at very considerable cost. In order to assess the impact of eHealth solutions on the quality and safety of health care, and to inform policy decisions on eHealth deployments, we undertook a systematic review of systematic reviews assessing the effectiveness and consequences of various eHealth technologies on the quality and safety of care. METHODS AND FINDINGS We developed novel search strategies, conceptual maps of health care quality, safety, and eHealth interventions, and then systematically identified, scrutinised, and synthesised the systematic review literature. Major biomedical databases were searched to identify systematic reviews published between 1997 and 2010. Related theoretical, methodological, and technical material was also reviewed. We identified 53 systematic reviews that focused on assessing the impact of eHealth interventions on the quality and/or safety of health care and 55 supplementary systematic reviews providing relevant supportive information. This systematic review literature was found to be generally of substandard quality with regards to methodology, reporting, and utility. We thematically categorised eHealth technologies into three main areas: (1) storing, managing, and transmission of data; (2) clinical decision support; and (3) facilitating care from a distance. We found that despite support from policymakers, there was relatively little empirical evidence to substantiate many of the claims made in relation to these technologies. Whether the success of those relatively few solutions identified to improve quality and safety would continue if these were deployed beyond the contexts in which they were originally developed, has yet to be established. Importantly, best practice guidelines in effective development and deployment strategies are lacking. CONCLUSIONS There is a large gap between the postulated and empirically demonstrated benefits of eHealth technologies. In addition, there is a lack of robust research on the risks of implementing these technologies and their cost-effectiveness has yet to be demonstrated, despite being frequently promoted by policymakers and "techno-enthusiasts" as if this was a given. In the light of the paucity of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, it is vital that future eHealth technologies are evaluated against a comprehensive set of measures, ideally throughout all stages of the technology's life cycle. Such evaluation should be characterised by careful attention to socio-technical factors to maximise the likelihood of successful implementation and adoption.
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Affiliation(s)
- Ashly D. Black
- eHealth Unit, Department of Primary Care and Public Health, Imperial College London, London, United Kingdom
| | - Josip Car
- eHealth Unit, Department of Primary Care and Public Health, Imperial College London, London, United Kingdom
| | - Claudia Pagliari
- eHealth Research Group, Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Chantelle Anandan
- eHealth Research Group, Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Kathrin Cresswell
- eHealth Research Group, Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Tomislav Bokun
- eHealth Unit, Department of Primary Care and Public Health, Imperial College London, London, United Kingdom
| | - Brian McKinstry
- eHealth Research Group, Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Rob Procter
- National Centre for e-Social Science, University of Manchester, Manchester, United Kingdom
| | - Azeem Majeed
- Department of Primary Care and Public Health, Imperial College London, London, United Kingdom
| | - Aziz Sheikh
- eHealth Research Group, Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, United Kingdom
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Bloomrosen M, Starren J, Lorenzi NM, Ash JS, Patel VL, Shortliffe EH. Anticipating and addressing the unintended consequences of health IT and policy: a report from the AMIA 2009 Health Policy Meeting. J Am Med Inform Assoc 2011; 18:82-90. [PMID: 21169620 PMCID: PMC3005876 DOI: 10.1136/jamia.2010.007567] [Citation(s) in RCA: 117] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2010] [Accepted: 11/03/2010] [Indexed: 11/03/2022] Open
Abstract
Federal legislation (Health Information Technology for Economic and Clinical Health (HITECH) Act) has provided funds to support an unprecedented increase in health information technology (HIT) adoption for healthcare provider organizations and professionals throughout the U.S. While recognizing the promise that widespread HIT adoption and meaningful use can bring to efforts to improve the quality, safety, and efficiency of healthcare, the American Medical Informatics Association devoted its 2009 Annual Health Policy Meeting to consideration of unanticipated consequences that could result with the increased implementation of HIT. Conference participants focused on possible unintended and unanticipated, as well as undesirable, consequences of HIT implementation. They employed an input-output model to guide discussion on occurrence of these consequences in four domains: technical, human/cognitive, organizational, and fiscal/policy and regulation. The authors outline the conference's recommendations: (1) an enhanced research agenda to guide study into the causes, manifestations, and mitigation of unintended consequences resulting from HIT implementations; (2) creation of a framework to promote sharing of HIT implementation experiences and the development of best practices that minimize unintended consequences; and (3) recognition of the key role of the Federal Government in providing leadership and oversight in analyzing the effects of HIT-related implementations and policies.
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Campion TR, May AK, Waitman LR, Ozdas A, Gadd CS. Effects of blood glucose transcription mismatches on a computer-based intensive insulin therapy protocol. Intensive Care Med 2010; 36:1566-70. [PMID: 20352190 DOI: 10.1007/s00134-010-1868-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2009] [Accepted: 03/14/2010] [Indexed: 11/27/2022]
Abstract
PURPOSE Computerized clinical decision support systems (CDSS) for intensive insulin therapy (IIT) generate recommendations using blood glucose (BG) values manually transcribed from testing devices to computers, a potential source of error. We quantified the frequency and effect of blood glucose transcription mismatches on IIT protocol performance. METHODS We examined 38 months of retrospective data for patients treated with CDSS IIT in two intensive care units at one teaching hospital. A manually transcribed BG value not equal to a corresponding device value was deemed mismatched. For mismatches we recalculated CDSS recommendations using device BG values. We compared matched and mismatched data in terms of CDSS alerts, blood glucose variability, and dosing. RESULTS Of 189,499 CDSS IIT instances, 5.3% contained mismatched BG values. Mismatched data triggered 93 false alerts and failed to issue 170 alerts for nurses to notify physicians. Four of six BG variability measures differed between matched and mismatched data. Overall insulin dose was greater for matched than mismatched [matched 3.8 (1.6-6.0), median (interquartile range, IQR), versus 3.6 (1.6-5.7); p < 0.001], but recalculated and actual dose were similar. In mismatches preceding hypoglycemia, recalculated insulin dose was significantly lower than actual dose [recalculated 2.7 (0.4-5.0), median (IQR), versus 3.5 (1.4-5.6)]. In mismatches preceding hyperglycemia, recalculated insulin dose was significantly greater than actual dose [recalculated 4.7 (3.3-6.2), median (IQR), versus 3.3 (2.4-4.3); p < 0.001]. Administration of recalculated doses might have prevented blood glucose excursions. CONCLUSIONS Mismatched blood glucose values can influence CDSS IIT protocol performance.
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Affiliation(s)
- Thomas R Campion
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, 400 Eskind Biomedical Library, 2209 Garland Avenue, Nashville, TN 37232, USA.
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