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Murad MH, Vaa Stelling BE, West CP, Hasan B, Simha S, Saadi S, Firwana M, Viola KE, Prokop LJ, Nayfeh T, Wang Z. Measuring Documentation Burden in Healthcare. J Gen Intern Med 2024:10.1007/s11606-024-08956-8. [PMID: 39073484 DOI: 10.1007/s11606-024-08956-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Accepted: 07/17/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND The enactment of the Health Information Technology for Economic and Clinical Health Act and the wide adoption of electronic health record (EHR) systems have ushered in increasing documentation burden, frequently cited as a key factor affecting the work experience of healthcare professionals and a contributor to burnout. This systematic review aims to identify and characterize measures of documentation burden. METHODS We integrated discussions with Key Informants and a comprehensive search of the literature, including MEDLINE, Embase, Scopus, and gray literature published between 2010 and 2023. Data were narratively and thematically synthesized. RESULTS We identified 135 articles about measuring documentation burden. We classified measures into 11 categories: overall time spent in EHR, activities related to clinical documentation, inbox management, time spent in clinical review, time spent in orders, work outside work/after hours, administrative tasks (billing and insurance related), fragmentation of workflow, measures of efficiency, EHR activity rate, and usability. The most common source of data for most measures was EHR usage logs. Direct tracking such as through time-motion analysis was fairly uncommon. Measures were developed and applied across various settings and populations, with physicians and nurses in the USA being the most frequently represented healthcare professionals. Evidence of validity of these measures was limited and incomplete. Data on the appropriateness of measures in terms of scalability, feasibility, or equity across various contexts were limited. The physician perspective was the most robustly captured and prominently focused on increased stress and burnout. DISCUSSION Numerous measures for documentation burden are available and have been tested in a variety of settings and contexts. However, most are one-dimensional, do not capture various domains of this construct, and lack robust validity evidence. This report serves as a call to action highlighting an urgent need for measure development that represents diverse clinical contexts and support future interventions.
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Affiliation(s)
- M Hassan Murad
- Mayo Clinic Evidence-Based Practice Center, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA.
| | - Brianna E Vaa Stelling
- Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Colin P West
- Division of General Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Bashar Hasan
- Mayo Clinic Evidence-Based Practice Center, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA
| | - Suvyaktha Simha
- Mayo Clinic Evidence-Based Practice Center, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA
| | - Samer Saadi
- Mayo Clinic Evidence-Based Practice Center, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA
| | - Mohammed Firwana
- Mayo Clinic Evidence-Based Practice Center, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA
| | - Kelly E Viola
- Mayo Clinic Evidence-Based Practice Center, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA
| | | | - Tarek Nayfeh
- Mayo Clinic Evidence-Based Practice Center, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA
| | - Zhen Wang
- Mayo Clinic Evidence-Based Practice Center, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA
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Munsiff SS, Burgoyne C, Dobson E, Yamshchikov A. Making the EHR Work for You-Modifications of an Electronic Health Record System to Improve Tracking and Management of Patients Receiving Outpatient Parenteral Antibiotic Therapy. Open Forum Infect Dis 2024; 11:ofae005. [PMID: 38412509 PMCID: PMC10866571 DOI: 10.1093/ofid/ofae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 01/05/2024] [Indexed: 02/29/2024] Open
Abstract
Background Managing the complex needs of outpatient parenteral antibiotic therapy (OPAT) patients is challenging and time-consuming. We describe development of multimodal interventions to facilitate patient management within an Epic® (Epic Systems Corporation)-based electronic health record (EHR) platform. Methods During 2016-2018, a multidisciplinary team created several modifications in our local EHR to improve gaps in OPAT care, including shared note templates, shared patient lists, automatically triggered notifications, and comprehensive order sets. A SmartForm was created, allowing collection of discrete, self-contained extractable data about each OPAT episode. We reviewed OPAT episodes from January 2019 through December 2022. Results The multimodal EHR interventions culminated in the creation of a patient report, the "OPAT Monitoring View" collating OPAT-relevant data from multiple sections of the chart onto 1 screen display. This view is accessible both within the patient chart and from multiple list-based, in-basket, and snapshot-anchored preview functions in the EHR. Implementation of the EHR bundle facilitated management of 3402 OPAT episodes from 2019 to 2022 (850 episodes/year), about 50% higher than anticipated based on 540 OPAT courses in 2016. The OPAT EHR bundle allowed efficient (<3 hours) multidisciplinary rounds for management of 130-145 patients each week, streamlining of care transitions, and increasing staff satisfaction. Conclusions Bundled multimodal modifications to the local EHR increased patient care efficiency and staff satisfaction and facilitated data collection to support a large OPAT program. These modifications apply commonly available EHR functionalities to OPAT care and could be adapted to other settings with different EHR platforms.
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Affiliation(s)
- Sonal S Munsiff
- Division of Infectious Diseases, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Colleen Burgoyne
- Division of Infectious Diseases, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Erica Dobson
- Department of Pharmacy, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Alexandra Yamshchikov
- Division of Infectious Diseases, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
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Nahm ES, Zhu S, Seidl K, Chen L, Day J, Seong H. Real-World Data for Interdisciplinary Health Care Research: A Case Example. ANS Adv Nurs Sci 2023; 46:349-362. [PMID: 37102714 DOI: 10.1097/ans.0000000000000496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Real-word data (RWD) refer to data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources, including electronic health records, medical claims data, and patient-generated data. Data sets that combine personal health data stored in different sources can provide a more complete picture of an individual's health and can be used to improve population health through research and practice. The 2-tiered aim of this article is to provide a brief introduction to using RWD in health care research and to present a case study that demonstrates data curation and data merge from different sources while highlighting the benefits and limitations of using RWD. The current digital health ecosystem and value-based care approach highlight the need to use RWD to catalyze the advancement of health care research and practice. This is an excellent field that nurse researchers can lead, as they have an innate understanding of such data and data sources.
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Affiliation(s)
- Eun-Shim Nahm
- Department of Organizational Systems and Adult Health, University of Maryland School of Nursing, Baltimore (Drs Nahm, Zhu, and Chen); and Department of Quality and Safety (Dr Seidl) and Director of Nursing Inquiry (Dr day), University of Maryland Medical Center, Baltimore. Mr Seong is a doctoral student at University of Maryland School of Nursing, Baltimore
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Dhingra LS, Shen M, Mangla A, Khera R. Cardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record. Am J Cardiol 2023; 203:136-148. [PMID: 37499593 PMCID: PMC10865722 DOI: 10.1016/j.amjcard.2023.06.104] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/24/2023] [Accepted: 06/29/2023] [Indexed: 07/29/2023]
Abstract
The electronic health record (EHR) represents a rich source of patient information, increasingly being leveraged for cardiovascular research. Although its primary use remains the seamless delivery of health care, the various longitudinally aggregated structured and unstructured data elements for each patient within the EHR can define the computational phenotypes of disease and care signatures and their association with outcomes. Although structured data elements, such as demographic characteristics, laboratory measurements, problem lists, and medications, are easily extracted, unstructured data are underused. The latter include free text in clinical narratives, documentation of procedures, and reports of imaging and pathology. Rapid scaling up of data storage and rapid innovation in natural language processing and computer vision can power insights from unstructured data streams. However, despite an array of opportunities for research using the EHR, specific expertise is necessary to adequately address confidentiality, accuracy, completeness, and heterogeneity challenges in EHR-based research. These often require methodological innovation and best practices to design and conduct successful research studies. Our review discusses these challenges and their proposed solutions. In addition, we highlight the ongoing innovations in federated learning in the EHR through a greater focus on common data models and discuss ongoing work that defines such an approach to large-scale, multicenter, federated studies. Such parallel improvements in technology and research methods enable innovative care and optimization of patient outcomes.
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Affiliation(s)
| | - Miles Shen
- Section of Cardiovascular Medicine, Department of Internal Medicine; Department of Internal Medicine
| | - Anjali Mangla
- Section of Cardiovascular Medicine, Department of Internal Medicine; Department of Neuroscience, Yale School of Medicine, New Haven, Connecticut
| | - Rohan Khera
- Section of Cardiovascular Medicine, Department of Internal Medicine; Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, Connecticut; Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut.; Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut.
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Chary AN, Brickhouse E, Torres B, Santangelo I, Carpenter CR, Liu SW, Godwin KM, Naik AD, Singh H, Kennedy M. Leveraging the Electronic Health Record to Implement Emergency Department Delirium Screening. Appl Clin Inform 2023; 14:478-486. [PMID: 37054983 PMCID: PMC10284630 DOI: 10.1055/a-2073-3736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 04/06/2023] [Indexed: 04/15/2023] Open
Abstract
OBJECTIVE The aim of this study is to understand how emergency departments (EDs) use health information technology (HIT), and specifically the electronic health record (EHR), to support implementation of delirium screening. METHODS We conducted semi-structured interviews with 23 ED clinician-administrators, representing 20 EDs, about how they used HIT resources to implement delirium screening. Interviews focused on challenges participants experienced when implementing ED delirium screening and EHR-based strategies they used to overcome them. We coded interview transcripts using dimensions from the Singh and Sittig sociotechnical model, which addresses use of HIT in complex adaptive health care systems. Subsequently, we analyzed data for common themes across dimensions of the sociotechnical model. RESULTS Three themes emerged about how the EHR could be used to address challenges in implementation of delirium screening: (1) staff adherence to screening, (2) communication among ED team members about a positive screen, and (3) linking positive screening to delirium management. Participants described several HIT-based strategies including visual nudges, icons, hard stop alerts, order sets, and automated communications that facilitated implementation of delirium screening. An additional theme emerged about challenges related to the availability of HIT resources. CONCLUSION Our findings provide practical HIT-based strategies for health care institutions planning to adopt geriatric screenings. Building delirium screening tools and reminders to perform screening into the EHR may prompt adherence to screening. Automating related workflows, team communication, and management of patients who screen positive for delirium may help save staff members' time. Staff education, engagement, and access to HIT resources may support successful screening implementation.
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Affiliation(s)
- Anita N. Chary
- Department of Emergency Medicine, Baylor College of Medicine, Houston, Texas, United States
- Department of Medicine, Baylor College of Medicine, Houston, Texas, United States
- Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas, United States
| | - Elise Brickhouse
- School of Medicine, Baylor College of Medicine, Houston, Texas, United States
| | - Beatrice Torres
- University of Texas School of Public Health, UT Health Science Center, Houston, Texas, United States
| | - Ilianna Santangelo
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States
| | - Christopher R. Carpenter
- Department of Emergency Medicine, Barnes Jewish Hospital, Washington University School of Medicine, Emergency Care Research Core, St. Louis, Missouri, United States
| | - Shan W. Liu
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States
- Harvard Medical School, Boston, Massachusetts, United States
| | - Kyler M. Godwin
- Department of Medicine, Baylor College of Medicine, Houston, Texas, United States
- Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas, United States
| | - Aanand D. Naik
- Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas, United States
- University of Texas School of Public Health, UT Health Science Center, Houston, Texas, United States
- University of Texas Health Consortium on Aging, Houston, Texas, United States
| | - Hardeep Singh
- Department of Medicine, Baylor College of Medicine, Houston, Texas, United States
- Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas, United States
| | - Maura Kennedy
- Department of Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States
- Harvard Medical School, Boston, Massachusetts, United States
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Aydin G, Kumru S. Paving the way for increased e-health record use: elaborating intentions of Gen-Z. Health Syst (Basingstoke) 2022; 12:281-298. [PMID: 37860594 PMCID: PMC10583638 DOI: 10.1080/20476965.2022.2129471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 09/21/2022] [Indexed: 10/10/2022] Open
Abstract
This paper presents the determinants of personal e-health records adoption by the Gen-Z population and reveals barriers to use. Gen-Z members are one of the most prominent users of digital health services that have an influence on older generations' technology adoption but have often been overlooked in scholarly research. A survey of 1,000 Gen-Z university students based on modified UTAUT was used to address this research gap. The analysis revealed the vital role of social influence in paving the way for higher adoption among Gen-Z. Moreover, significant influences of performance expectancy, facilitating conditions, and e-health literacy on behavioural intentions were detected. Effort expectancy was found to be insignificant in impacting Gen-Z's intentions to adopt electronic health record systems. Moreover, privacy concerns acted as a barrier to adoption, yet the offsetting effect of users' trust in health systems was shown to be instrumental in overcoming such privacy-related barriers.
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Affiliation(s)
- Gökhan Aydin
- School of Business and Law, University of Brighton, Brighton, UK
- Health Management, Istanbul Medipol University, Istanbul, Turkey
| | - Seda Kumru
- Health Management, Bakircay University, Izmir, Turkey
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