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Miake-Lye IM, Cogan AM, Mak S, Brunner J, Rinne S, Brayton CE, Krones A, Ross TE, Burton JT, Weiner M. Transitioning from One Electronic Health Record to Another: A Systematic Review. J Gen Intern Med 2023; 38:956-964. [PMID: 37798580 PMCID: PMC10593710 DOI: 10.1007/s11606-023-08276-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 06/13/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND Transitioning to a new electronic health record (EHR) presents different challenges than transitions from paper to electronic records. We synthesized the body of peer-reviewed literature on EHR-to-EHR transitions to evaluate the generalizability of published work and identify knowledge gaps where more evidence is needed. METHODS We conducted a broad search in PubMed through July 2022 and collected all publications from two prior reviews. Peer-reviewed publications reporting on data from an EHR-to-EHR transition were included. We extracted data on study design, setting, sample size, EHR systems involved, dates of transition and data collection, outcomes reported, and key findings. RESULTS The 40 included publications were grouped into thematic categories for narrative synthesis: clinical care outcomes (n = 15), provider perspectives (n = 11), data migration (n = 8), patient experience (n = 4), and other topics (n = 5). Many studies described single sites that are early adopters of technology with robust research resources, switching from a homegrown system to a commercial system, and emphasized the dynamic effect of transitioning on important clinical care and other outcomes over time. DISCUSSION The published literature represents a heterogeneous mix of study designs and outcome measures, and while some of the stronger studies in this review used longitudinal approaches to compare outcomes across more sites, the current literature is primarily descriptive and is not designed to offer recommendations that can guide future EHR transitions. Transitioning from one EHR to another constitutes a major organizational change that requires nearly every person in the organization to change how they do their work. Future research should include human factors as well as diverse methodological approaches such as mixed methods and implementation science.
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Affiliation(s)
- Isomi M Miake-Lye
- Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
- Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, CA, USA.
| | - Alison M Cogan
- Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Mrs. T. H. Chan Division of Occupational Science and Occupational Therapy, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, CA, USA
| | - Selene Mak
- Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Julian Brunner
- Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Seppo Rinne
- Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, USA
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Catherine E Brayton
- Center for the Study of Healthcare Innovation, Implementation and Policy (CSHIIP), VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Ariella Krones
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Pulmonary and Critical Care Medicine, VA West Roxbury Medical Center, West Roxbury, MA, USA
| | - Travis E Ross
- Pain Research, Informatics, Multi-Morbidities, and Education (PRIME) Center, VA West Haven Medical Center, West Haven, CT, USA
- Yale Center for Medical Informatics, New Haven, CT, USA
| | - Jason T Burton
- Louise M. Darling Biomedical Library, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael Weiner
- Center for Health Information and Communication, Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service CIN 13-416, Richard L. Roudebush VA Medical Center, IN, Indianapolis, USA
- Regenstrief Institute, Inc., Indianapolis, IN, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
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Ozonze O, Scott PJ, Hopgood AA. Automating Electronic Health Record Data Quality Assessment. J Med Syst 2023; 47:23. [PMID: 36781551 PMCID: PMC9925537 DOI: 10.1007/s10916-022-01892-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 11/15/2022] [Indexed: 02/15/2023]
Abstract
Information systems such as Electronic Health Record (EHR) systems are susceptible to data quality (DQ) issues. Given the growing importance of EHR data, there is an increasing demand for strategies and tools to help ensure that available data are fit for use. However, developing reliable data quality assessment (DQA) tools necessary for guiding and evaluating improvement efforts has remained a fundamental challenge. This review examines the state of research on operationalising EHR DQA, mainly automated tooling, and highlights necessary considerations for future implementations. We reviewed 1841 articles from PubMed, Web of Science, and Scopus published between 2011 and 2021. 23 DQA programs deployed in real-world settings to assess EHR data quality (n = 14), and a few experimental prototypes (n = 9), were identified. Many of these programs investigate completeness (n = 15) and value conformance (n = 12) quality dimensions and are backed by knowledge items gathered from domain experts (n = 9), literature reviews and existing DQ measurements (n = 3). A few DQA programs also explore the feasibility of using data-driven techniques to assess EHR data quality automatically. Overall, the automation of EHR DQA is gaining traction, but current efforts are fragmented and not backed by relevant theory. Existing programs also vary in scope, type of data supported, and how measurements are sourced. There is a need to standardise programs for assessing EHR data quality, as current evidence suggests their quality may be unknown.
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Affiliation(s)
- Obinwa Ozonze
- School of Computing, University of Portsmouth, Buckingham Building, Lion Terrace, Portsmouth, PO1 3HE, UK
| | - Philip J Scott
- Institute of Management and Health, University of Wales Trinity Saint David, Lampeter, SA48 7ED, UK
| | - Adrian A Hopgood
- School of Computing, University of Portsmouth, Buckingham Building, Lion Terrace, Portsmouth, PO1 3HE, UK.
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Sittig DF, Lakhani P, Singh H. Applying requisite imagination to safeguard electronic health record transitions. J Am Med Inform Assoc 2022; 29:1014-1018. [PMID: 35022741 PMCID: PMC9006683 DOI: 10.1093/jamia/ocab291] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/17/2021] [Accepted: 12/29/2021] [Indexed: 02/05/2023] Open
Abstract
Over the next decade, many health care organizations (HCOs) will transition from one electronic health record (EHR) to another; some forced by hospital acquisition and others by choice in search of better EHRs. Herein, we apply principles of Requisite Imagination, or the ability to imagine key aspects of the future one is planning, to offer 6 recommendations on how to proactively safeguard these transitions. First, HCOs should implement a proactive leadership structure that values communication. Second, HCOs should implement proactive risk assessment and testing processes. Third, HCOs should anticipate and reduce unwarranted variation in their EHR and clinical processes. Fourth, HCOs should establish a culture of conscious inquiry with routine system monitoring. Fifth, HCOs should foresee and reduce information access problems. Sixth, HCOs should support their workforce through difficult EHR transitions. Proactive approaches using Requisite Imagination principles outlined here can help ensure safe, effective, and economically sound EHR transitions.
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Affiliation(s)
- Dean F Sittig
- University of Texas/Memorial Hermann Center for Healthcare Quality & Safety, School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, USA
| | - Priti Lakhani
- Formerly at Office of Electronic Health Record Modernization, U.S. Department of Veterans Affairs, Washington, DC, USA
| | - Hardeep Singh
- Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey Veterans Affairs Medical Center and Baylor College of Medicine, Houston, TX, USA
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MacKenzie B, Anaya G, Hu J, Brickman A, Elkin PL, Panesar M. Defining Data Migration Across Multidisciplinary Ambulatory Clinics Using Participatory Design. Appl Clin Inform 2021; 12:251-258. [PMID: 33792009 DOI: 10.1055/s-0041-1726032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVE This study aimed to develop an institutional approach for defining data migration based on participatory design principles. METHODS We outline a collaborative approach to define data migration as part of an electronic health record (EHR) transition at an urban hospital with 20 ambulatory clinics, based on participatory design. We developed an institution-specific list of data for migration based on physician end-user feedback. In this paper, we review the project planning phases, multidisciplinary governance, and methods used. RESULTS Detailed data migration feedback was obtained from 90% of participants. Depending on the specialty, requests for historical laboratory values ranged from 2 to as many as 145 unique laboratory types. Lookback periods requested by physicians varied and were ultimately assigned to provide the most clinical data. This clinical information was then combined to synthesize an overall proposed data migration request on behalf of the institution. CONCLUSION Institutions undergoing an EHR transition should actively involve physician end-users and key stakeholders. Physician feedback is vital for developing a clinically relevant EHR environment but is often difficult to obtain. Challenges include physician time constraints and overall knowledge about health information technology. This study demonstrates how a participatory design can serve to improve the clinical end-user's understanding of the technical aspects of an EHR implementation, as well as enhance the outcomes of such projects.
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Affiliation(s)
- Brianne MacKenzie
- Department of Biomedical Informatics, The State University of New York at Buffalo, Buffalo, New York, United States
| | - Gabriel Anaya
- Department of Biomedical Informatics, The State University of New York at Buffalo, Buffalo, New York, United States
| | - Jinwei Hu
- Department of Biomedical Informatics, The State University of New York at Buffalo, Buffalo, New York, United States
| | - Arlen Brickman
- Department of Biomedical Informatics, The State University of New York at Buffalo, Buffalo, New York, United States
| | - Peter L Elkin
- Department of Biomedical Informatics, The State University of New York at Buffalo, Buffalo, New York, United States.,Department of Veterans Affairs, Western New York, Buffalo, United States
| | - Mandip Panesar
- Department of Biomedical Informatics, The State University of New York at Buffalo, Buffalo, New York, United States.,Erie County Medical Center, Buffalo, New York, United States
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Huang C, Koppel R, McGreevey JD, Craven CK, Schreiber R. Transitions from One Electronic Health Record to Another: Challenges, Pitfalls, and Recommendations. Appl Clin Inform 2020; 11:742-754. [PMID: 33176389 DOI: 10.1055/s-0040-1718535] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
Abstract
OBJECTIVE We address the challenges of transitioning from one electronic health record (EHR) to another-a near ubiquitous phenomenon in health care. We offer mitigating strategies to reduce unintended consequences, maximize patient safety, and enhance health care delivery. METHODS We searched PubMed and other sources to identify articles describing EHR-to-EHR transitions. We combined these references with the authors' extensive experience to construct a conceptual schema and to offer recommendations to facilitate transitions. RESULTS Our PubMed query retrieved 1,351 citations: 43 were relevant for full paper review and 18 met the inclusion criterion of focus on EHR-to-EHR transitions. An additional PubMed search yielded 1,014 citations, for which we reviewed 74 full papers and included 5. We supplemented with additional citations for a total of 70 cited. We distinguished 10 domains in the literature that overlap yet present unique and salient opportunities for successful transitions and for problem mitigation. DISCUSSION There is scant literature concerning EHR-to-EHR transitions. Identified challenges include financial burdens, personnel resources, patient safety threats from limited access to legacy records, data integrity during migration, cybersecurity, and semantic interoperability. Transition teams must overcome inadequate human infrastructure, technical challenges, security gaps, unrealistic providers' expectations, workflow changes, and insufficient training and support-all factors affecting potential clinician burnout. CONCLUSION EHR transitions are remarkably expensive, laborious, personnel devouring, and time consuming. The paucity of references in comparison to the topic's salience reinforces the necessity for this type of review and analysis. Prudent planning may streamline EHR transitions and reduce expenses. Mitigating strategies, such as preservation of legacy data, managing expectations, and hiring short-term specialty consultants can overcome some of the greatest hurdles. A new medical subject headings (MeSH) term for EHR transitions would facilitate further research on this topic.
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Affiliation(s)
- Chunya Huang
- Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania, United States.,Department of Anesthesiology and Perioperative Medicine, University of Louisville School of Medicine-Louisville, Kentucky, United States
| | - Ross Koppel
- Deparments of Biomedical Informatics and of Sociology, University of Pennsylvania, Philadelphia, Pennsylvania, United States.,Department of Biomedical Informatics, University at Buffalo (SUNY), Buffalo, New York, United States
| | - John D McGreevey
- Division of General Internal Medicine, Section of Hospital Medicine, Perelman School of Medicine at the University of Pennsylvania, University of Pennsylvania Health System, Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Catherine K Craven
- Department of Population Health Science and Policy, Clinical Informatics Group, IT Department, Mount Sinai Health System, Institute for Healthcare Delivery Science, Icahn School of Medicine at Mount Sinai, New York, New York, United States
| | - Richard Schreiber
- Physician Informatics and Department of Medicine, Geisinger Holy Spirit, Geisinger Commonwealth School of Medicine, Camp Hill, Pennsylvania, United States
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Gambino O, Rundo L, Cannella V, Vitabile S, Pirrone R. A framework for data-driven adaptive GUI generation based on DICOM. J Biomed Inform 2018; 88:37-52. [DOI: 10.1016/j.jbi.2018.10.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2018] [Revised: 10/22/2018] [Accepted: 10/29/2018] [Indexed: 11/17/2022]
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Penrod LE. Electronic Health Record Transition Considerations. PM R 2018; 9:S13-S18. [PMID: 28527498 DOI: 10.1016/j.pmrj.2017.01.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Revised: 01/27/2017] [Accepted: 01/30/2017] [Indexed: 10/19/2022]
Abstract
After an initial phase of electronic health record (EHR) solutions for both independent practices and larger health care organizations, we are now entering a period in which transitioning between EHRs is becoming more common. Many of the decisions and implementation processes for an EHR transition are similar to those encountered during the transition from paper records to an EHR. Detailed project planning and management are essential to keep the effort on track and within budget to a successful conclusion. One major difference between the 2 situations is the possibility of migrating patient data by using automation. Understanding the implications of structured and unstructured data to manage the data migration between EHR systems is important to ensure success of the effort. Access to legacy data after the transition for both patient care and release of information to external parties is also critical to understand and manage proactively.
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Affiliation(s)
- Louis E Penrod
- Chief Medical Information Officer, Baptist Health System, 841 Prudential Dr., Suite 650, Jacksonville, FL 32207(∗).
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Schuster C, Vitoux RR. Methodology for Ensuring Accuracy and Validity of Infusion Pump Alarm Data. Biomed Instrum Technol 2018; 52:192-198. [PMID: 29771576 DOI: 10.2345/0899-8205-52.3.192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
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9
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Zhang XY, Zhang PY. Hospital information technology in home care. Exp Ther Med 2016; 12:2408-2410. [PMID: 27698741 PMCID: PMC5038446 DOI: 10.3892/etm.2016.3664] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Accepted: 08/26/2016] [Indexed: 11/11/2022] Open
Abstract
The utilization of hospital information technology (HIT) as a tool for home care is a recent trend in health science. Subjects gaining benefits from this new endeavor include middle-aged individuals with serious chronic illness living at home. Published data on the utilization of health care information technology especially for home care in chronic illness patients have increased enormously in recent past. The common chronic illnesses reported in these studies were primarily on heart and lung diseases. Furthermore, health professionals have confirmed in these studies that HIT was beneficial in gaining better access to information regarding their patients and they were also able to save that information easily for future use. On the other hand, some health professional also observed that the use of HIT in home care is not suitable for everyone and that individuals cannot be replaced by HIT. On the whole it is clear that the use of HIT could complement communication in home care. The present review aims to shed light on these latest aspects of the health care information technology in home care.
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Affiliation(s)
- Xiao-Ying Zhang
- Nanjing University of Chinese Medicine, Information Institute, Nanjing, Jiangsu 210029, P.R. China
| | - Pei-Ying Zhang
- Xuzhou Central Hospital, The Affiliated Xuzhou Hospital of Medical College of Southeast University, Xuzhou, Jiangsu 221009, P.R. China
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