CoChat
Sign Up
Cited by 87Electronic Health Records SystemsHealthcare professionals’ stress and burnoutStress and Burnout Research

Evaluating the Prevalence of Burnout Among Health Care Professionals Related to Electronic Health Record Use: Systematic Review and Meta-Analysis

Open access
Wu, Yuxuan, Wu, Mingyue, Wang, Changyu, Lin, Jie, Liu, Jialin, Liu, Siru·2024·JMIR Medical Informatics
DOI 10.2196/54811PMC PMC11208837

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Background: Burnout among health care professionals is a significant concern, with detrimental effects on health care service quality and patient outcomes. The use of the electronic health record (EHR) system has been identified as a significant contributor to burnout among health care professionals. Objective: This systematic review and meta-analysis aims to assess the prevalence of burnout among health care professionals associated with the use of the EHR system, thereby providing evidence to improve health information systems and develop strategies to measure and mitigate burnout. Methods: We conducted a comprehensive search of the PubMed, Embase, and Web of Science databases for English-language peer-reviewed articles published between January 1, 2009, and December 31, 2022. Two independent reviewers applied inclusion and exclusion criteria, and study quality was assessed using the Joanna Briggs Institute checklist and the Newcastle-Ottawa Scale. Meta-analyses were performed using R (version 4.1.3; R Foundation for Statistical Computing), with EndNote X7 (Clarivate) for reference management. Results: The review included 32 cross-sectional studies and 5 case-control studies with a total of 66,556 participants, mainly physicians and registered nurses. The pooled prevalence of burnout among health care professionals in cross-sectional studies was 40.4% (95% CI 37.5%-43.2%). Case-control studies indicated a higher likelihood of burnout among health care professionals who spent more time on EHR-related tasks outside work (odds ratio 2.43, 95% CI 2.31-2.57). Conclusions: The findings highlight the association between the increased use of the EHR system and burnout among health care professionals. Potential solutions include optimizing EHR systems, implementing automated dictation or note-taking, employing scribes to reduce documentation burden, and leveraging artificial intelligence to enhance EHR system efficiency and reduce the risk of burnout. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42021281173; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021281173

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/54811

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 73

  1. [1]Aldosari B Patients' safety in the era of EMR/EHR automation Inform Med Unlocked 2017 9 230 233 10.1016/j.imu.2017.10.001 · DOI
  2. [2]Gatiti P Ndirangu E Mwangi J Mwanzu A Ramadhani T Enhancing healthcare quality in hospitals through electronic health records: a systematic review J Health Inform Dev Ctries 2021 15 2 1 25
  3. [3]Woldemariam MT Jimma W Adoption of electronic health record systems to enhance the quality of healthcare in low-income countries: a systematic review BMJ Health Care Inform 2023 06 30 1 e100704 10.1136/bmjhci-2022-100704 37308185 bmjhci-2022-100704 PMC10277040 37308185 · DOI
  4. [4]Li C Parpia C Sriharan A Keefe DT Electronic medical record-related burnout in healthcare providers: a scoping review of outcomes and interventions BMJ Open 2022 08 19 12 8 e060865 10.1136/bmjopen-2022-060865 35985785 bmjopen-2022-060865 PMC9396159 35985785 · DOI · Paper page
  5. [5]Heponiemi T Gluschkoff K Vehko T Kaihlanen AM Saranto K Nissinen S Nadav J Kujala S Electronic health record implementations and insufficient training endanger nurses' well-being: cross-sectional survey study J Med Internet Res 2021 12 23 23 12 e27096 10.2196/27096 34941546 v23i12e27096 34941546 PMC8738988 · DOI
  6. [6]Tajirian T Stergiopoulos V Strudwick G Sequeira L Sanches M Kemp J Ramamoorthi K Zhang T Jankowicz D The influence of electronic health record use on physician burnout: cross-sectional survey J Med Internet Res 2020 07 15 22 7 e19274 10.2196/19274 32673234 v22i7e19274 32673234 PMC7392132 · DOI · Paper page
  7. [7]Palojoki S Saranto K Reponen E Skants N Vakkuri A Vuokko R Classification of electronic health record-related patient safety incidents: development and validation study JMIR Med Inform 2021 08 31 9 8 e30470 10.2196/30470 34245558 v9i8e30470 34245558 PMC8441612 · DOI
  8. [9]Jankovic I Chen JH Clinical decision support and implications for the clinician burnout crisis Yearb Med Inform 2020 08 29 1 145 154 10.1055/s-0040-1701986 32823308 32823308 PMC7442505 · DOI · Paper page
  9. [10]Thomas Craig Kelly J Willis VC Gruen D Rhee K Jackson GP The burden of the digital environment: a systematic review on organization-directed workplace interventions to mitigate physician burnout J Am Med Inform Assoc 2021 04 23 28 5 985 997 10.1093/jamia/ocaa301 33463680 6104341 33463680 PMC8068437 · DOI · Paper page
  10. [11]Mohan V Garrison C Gold JA Using a new model of electronic health record training to reduce physician burnout: a plan for action JMIR Med Inform 2021 09 20 9 9 e29374 10.2196/29374 34325400 v9i9e29374 34325400 PMC8491113 · DOI
  11. [12]Melnick ER Harry E Sinsky CA Dyrbye LN Wang H Trockel MT West CP Shanafelt T Perceived electronic health record usability as a predictor of task load and burnout among US physicians: mediation analysis J Med Internet Res 2020 12 22 22 12 e23382 10.2196/23382 33289493 v22i12e23382 33289493 PMC7785404 · DOI
  12. [13]Mertz H Electronic health record reform: an alternative response to physician burnout Am J Med 2021 134 9 e498 10.1016/j.amjmed.2021.04.022 34462089 S0002-9343(21)00315-6 34462089 · DOI
  13. [15]Kumar S Burnout and doctors: prevalence, prevention and intervention Healthcare (Basel) 2016 4 3 37 10.3390/healthcare4030037 27417625 healthcare4030037 27417625 PMC5041038 · DOI · Paper page
  14. [16]Gesner E Gazarian P Dykes P The burden and burnout in documenting patient care: an integrative literature review Stud Health Technol Inform 2019 264 1194 1198 10.3233/SHTI190415 31438114 SHTI190415 31438114 · DOI
  15. [17]Kang C Sarkar IN Interventions to reduce electronic health record-related burnout: a systematic review Appl Clin Inform 2024 15 1 10 25 10.1055/a-2203-3787 37923381 37923381 PMC10764123 · DOI
  16. [18]Johnson KB Neuss MJ Detmer DE Electronic health records and clinician burnout: a story of three eras J Am Med Inform Assoc 2021 28 5 967 973 10.1093/jamia/ocaa274 33367815 6053200 33367815 PMC8068425 · DOI
  17. [19]Williams MS Misdiagnosis: burnout, moral injury, and implications for the electronic health record J Am Med Inform Assoc 2021 28 5 1047 1050 10.1093/jamia/ocaa244 33164089 5961437 33164089 PMC8068430 · DOI
  18. [20]Baxter SL Saseendrakumar BR Cheung M Savides TJ Longhurst CA Sinsky CA Millen M Tai-Seale M Association of electronic health record inbasket message characteristics with physician burnout JAMA Netw Open 2022 5 11 e2244363 10.1001/jamanetworkopen.2022.44363 36449288 2799074 36449288 PMC9713605 · DOI
  19. [21]Liberati A Altman DG Tetzlaff J Mulrow C Gøtzsche PC Ioannidis JPA Clarke M Devereaux PJ Kleijnen J Moher D The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration Ann Intern Med 2009 151 4 W65 W94 10.7326/0003-4819-151-4-200908180-00136 19622512 0000605-200908180-00136 19622512 · DOI · Paper page
  20. [25]Munn Z Stone JC Aromataris E Klugar M Sears K Leonardi-Bee J Barker TH Assessing the risk of bias of quantitative analytical studies: introducing the vision for critical appraisal within JBI systematic reviews JBI Evid Synth 2023 03 01 21 3 467 471 10.11124/JBIES-22-00224 36476419 02174543-990000000-00108 36476419 · DOI
  21. [26]Stang A Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses Eur J Epidemiol 2010 25 9 603 605 10.1007/s10654-010-9491-z 20652370 20652370 · DOI · Paper page
  22. [27]Higgins JPT Thompson SG Deeks JJ Altman DG Measuring inconsistency in meta-analyses BMJ 2003 09 06 327 7414 557 60 10.1136/bmj.327.7414.557 12958120 327/7414/557 12958120 PMC192859 · DOI · Paper page
  23. [29]Egger M Davey Smith G Schneider M Minder C Bias in meta-analysis detected by a simple, graphical test BMJ 1997 09 13 315 7109 629 34 10.1136/bmj.315.7109.629 9310563 9310563 PMC2127453 · DOI · Paper page
  24. [30]Tawfik DS Phibbs CS Sexton JB Kan P Sharek PJ Nisbet CC Rigdon J Trockel M Profit J Factors associated with provider burnout in the NICU Pediatrics 2017 05 139 5 e20164134 10.1542/peds.2016-4134 28557756 peds.2016-4134 28557756 PMC5404731 · DOI
  25. [32]Tawfik DS Sinha A Bayati M Adair KC Shanafelt TD Sexton JB Profit J Frustration with technology and its relation to emotional exhaustion among health care workers: cross-sectional observational study J Med Internet Res 2021 23 7 e26817 10.2196/26817 34255674 v23i7e26817 34255674 PMC8292941 · DOI
  26. [34]Tai-Seale M Dillon EC Yang Y Nordgren R Steinberg RL Nauenberg T Lee TC Meehan A Li J Chan AS Frosch DL Physicians' well-being linked to in-basket messages generated by algorithms in electronic health records Health Aff (Millwood) 2019 38 7 1073 1078 10.1377/hlthaff.2018.05509 31260371 31260371 · DOI
  27. [35]Apaydin EA Rose D Meredith LS McClean M Dresselhaus T Stockdale S Association between difficulty with VA patient-centered medical home model components and provider emotional exhaustion and intent to remain in practice J Gen Intern Med 2020 35 7 2069 2075 10.1007/s11606-020-05780-8 32291716 10.1007/s11606-020-05780-8 32291716 PMC7352025 · DOI
  28. [36]Livaudais M Deng D Frederick T Grey-Theriot F Kroth PJ Perceived value of the electronic health record and its association with physician burnout Appl Clin Inform 2022 13 4 778 784 10.1055/s-0042-1755372 35981548 35981548 PMC9388222 · DOI · Paper page
  29. [37]Tran B Lenhart A Ross R Dorr DA Burnout and EHR use among academic primary care physicians with varied clinical workloads AMIA Jt Summits Transl Sci Proc 2019 2019 136 144 31258965 31258965 PMC6568076
  30. [38]Marckini DN Samuel BP Parker JL Cook SC Electronic health record associated stress: a survey study of adult congenital heart disease specialists Congenit Heart Dis 2019 14 3 356 361 10.1111/chd.12745 30825270 30825270 · DOI
  31. [39]Gardner RL Cooper E Haskell J Harris DA Poplau S Kroth PJ Linzer M Physician stress and burnout: the impact of health information technology J Am Med Inform Assoc 2019 26 2 106 114 10.1093/jamia/ocy145 30517663 5230918 30517663 PMC7647171 · DOI · Paper page
  32. [40]Hilliard RW Haskell J Gardner RL Are specific elements of electronic health record use associated with clinician burnout more than others? J Am Med Inform Assoc 2020 27 9 1401 1410 10.1093/jamia/ocaa092 32719859 5876976 32719859 PMC7647296 · DOI
  33. [41]Higgins MCSS Siddiqui AA Kosowsky T Unan L Mete M Rowe S Marchalik D Burnout, professional fulfillment, intention to leave, and sleep-related impairment among radiology trainees across the United States (US): a multisite epidemiologic study Acad Radiol 2022 29 Suppl 5 S118 S125 10.1016/j.acra.2022.01.022 35241358 S1076-6332(22)00105-2 35241358 · DOI
  34. [42]Czernik Z Yu A Pell J Feinbloom D Jones CD Hospitalist perceptions of electronic health records: a multi-site survey J Gen Intern Med 2022 37 1 269 271 10.1007/s11606-020-06558-8 33479933 10.1007/s11606-020-06558-8 33479933 PMC8739398 · DOI
  35. [43]Hauer A Waukau HJ Welch P Physician burnout in Wisconsin: an alarming trend affecting physician wellness WMJ 2018 117 5 194 200 30674095 30674095
  36. [44]Gajra A Bapat B Jeune-Smith Y Nabhan C Klink AJ Liassou D Mehta S Feinberg B Frequency and causes of burnout in US community oncologists in the era of electronic health records JCO Oncol Pract 2020 16 4 e357 e365 10.1200/JOP.19.00542 32275848 32275848 · DOI
  37. [45]Adler-Milstein J Zhao W Willard-Grace R Knox M Grumbach K Electronic health records and burnout: time spent on the electronic health record after hours and message volume associated with exhaustion but not with cynicism among primary care clinicians J Am Med Inform Assoc 2020 27 4 531 538 10.1093/jamia/ocz220 32016375 5722322 32016375 PMC7647261 · DOI
  38. [46]Somerson JS Patton A Ahmed AA Ramey S Holliday EB Burnout among United States orthopaedic surgery residents J Surg Educ 2020 77 4 961 968 10.1016/j.jsurg.2020.02.019 32171748 S1931-7204(20)30053-2 32171748 · DOI
  39. [48]Coleman DM Money SR Meltzer AJ Wohlauer M Drudi LM Freischlag JA Hallbeck S Halloran B Huber TS Shanafelt T Sheahan MG Vascular surgeon wellness and burnout: a report from the Society for Vascular Surgery Wellness Task Force J Vasc Surg 2021 73 6 1841 1850.e3 10.1016/j.jvs.2020.10.065 33248123 S0741-5214(20)32466-6 33248123 · DOI
  40. [49]Abraham CM Zheng K Norful AA Ghaffari A Liu J Topaz M Poghosyan L Use of multifunctional electronic health records and burnout among primary care nurse practitioners J Am Assoc Nurse Pract 2021 33 12 1182 1189 10.1097/JXX.0000000000000533 33534286 01741002-202112000-00013 33534286 PMC8351449 · DOI
  41. [50]Kondrich JE Han R Clark S Platt SL Burnout in pediatric emergency medicine physicians: a predictive model Pediatr Emerg Care 2022 38 2 e1003 e1008 10.1097/PEC.0000000000002425 35100790 00006565-202202000-00119 35100790 · DOI
  42. [51]Kroth PJ Morioka-Douglas N Veres S Babbott S Poplau S Qeadan F Parshall C Corrigan K Linzer M Association of electronic health record design and use factors with clinician stress and burnout JAMA Netw Open 2019 2 8 e199609 10.1001/jamanetworkopen.2019.9609 31418810 2748054 31418810 PMC6704736 · DOI
  43. [52]Mandeville B Cooper E Haskell J Viner-Brown S Gardner RL Use of health information technology by Rhode Island physicians and advanced practice providers, 2019 R I Med J (2013) 2020 103 1 21 24 32013299 32013299
  44. [53]Tiwari V Kavanaugh A Martin G Bergman M High burden of burnout on rheumatology practitioners J Rheumatol 2020 47 12 1831 1834 10.3899/jrheum.191110 32238512 jrheum.191110 32238512 · DOI
  45. [54]Sinha A Shanafelt TD Trockel M Wang H Sharp C Novel nonproprietary measures of ambulatory electronic health record use associated with physician work exhaustion Appl Clin Inform 2021 12 3 637 646 10.1055/s-0041-1731678 34261173 34261173 PMC8279819 · DOI
  46. [55]Anderson JC Bilal M Burke CA Gaidos JK Lopez R Oxentenko AS Surawicz CM Burnout among US gastroenterologists and fellows in training: identifying contributing factors and offering solutions J Clin Gastroenterol 2023 57 10 1063 1069 10.1097/MCG.0000000000001781 36477385 00004836-990000000-00082 36477385 · DOI
  47. [56]Nair D Brereton L Hoge C Plantinga LC Agrawal V Soman SS Choi MJ Jaar BG Burnout among nephrologists in the United States: a survey study Kidney Med 2022 4 3 100407 10.1016/j.xkme.2022.100407 35386610 S2590-0595(22)00001-2 35386610 PMC8978053 · DOI
  48. [57]Jha SS Shah S Calderon MD Soin A Manchikanti L The effect of COVID-19 on interventional pain management practices: a physician burnout survey Pain Physician 2020 23 4S S271 S282 32942787 32942787
  49. [58]Esmaeilzadeh P Mirzaei T Using electronic health records to mitigate workplace burnout among clinicians during the COVID-19 pandemic: field study in Iran JMIR Med Inform 2021 9 6 e28497 10.2196/28497 34033578 v9i6e28497 34033578 PMC8176947 · DOI
  50. [59]Holzer KJ Lou SS Goss CW Strickland J Evanoff BA Duncan JG Kannampallil T Impact of changes in EHR use during COVID-19 on physician trainee mental health Appl Clin Inform 2021 12 3 507 517 10.1055/s-0041-1731000 34077972 34077972 PMC8172260 · DOI
  51. [60]Wilkie T Tajirian T Thakur A Mistry S Islam F Stergiopoulos V Evolution of a physician wellness, engagement and excellence strategy: lessons learnt in a mental health setting BMJ Lead 2023 7 3 182 188 10.1136/leader-2022-000595 37200187 leader-2022-000595 37200187 · DOI
  52. [61]Eschenroeder HC Manzione LC Adler-Milstein J Bice C Cash R Duda C Joseph C Lee JS Maneker A Poterack KA Rahman SB Jeppson J Longhurst C Associations of physician burnout with organizational electronic health record support and after-hours charting J Am Med Inform Assoc 2021 04 23 28 5 960 966 10.1093/jamia/ocab053 33880534 6242740 33880534 PMC8068427 · DOI
  53. [62]Sharp M Burkart KM Adelman MH Ashton RW Biddison LD Bosslet GT Doyle ST Eckmann T Khan MMKS Lenz PH McCallister JW O'Toole J Rand CS Riekert KA Soffler MI Winter GR Zaeh S Eakin MN A national survey of burnout and depression among fellows training in pulmonary and critical care medicine: a special report by the association of pulmonary and critical care medicine program directors Chest 2021 159 2 733 742 10.1016/j.chest.2020.08.2117 32956717 S0012-3692(20)34511-6 32956717 PMC7856531 · DOI
  54. [63]Peccoralo LA Kaplan CA Pietrzak RH Charney DS Ripp JA The impact of time spent on the electronic health record after work and of clerical work on burnout among clinical faculty J Am Med Inform Assoc 2021 28 5 938 947 10.1093/jamia/ocaa349 33550392 6130084 33550392 PMC8068423 · DOI
  55. [64]Harris DA Haskell J Cooper E Crouse N Gardner R Estimating the association between burnout and electronic health record-related stress among advanced practice registered nurses Appl Nurs Res 2018 43 36 41 10.1016/j.apnr.2018.06.014 30220361 S0897-1897(18)30135-6 30220361 · DOI
  56. [65]Robertson SL Robinson MD Reid A Electronic health record effects on work-life balance and burnout within the I population collaborative J Grad Med Educ 2017 9 4 479 484 10.4300/JGME-D-16-00123.1 28824762 Customer: JGME-D-16-00123 28824762 PMC5559244 · DOI · Paper page
  57. [66]Shanafelt TD Boone S Tan L Dyrbye LN Sotile W Satele D West CP Sloan J Oreskovich MR Burnout and satisfaction with work-life balance among US physicians relative to the general US population Arch Intern Med 2012 172 18 1377 1385 10.1001/archinternmed.2012.3199 22911330 1351351 22911330 · DOI · Paper page
  58. [68]Green-McKenzie J Somasundaram P Lawler T O'Hara E Shofer FS Prevalence of burnout in occupational and environmental medicine physicians in the United States J Occup Environ Med 2020 62 9 680 685 10.1097/JOM.0000000000001913 32890204 00043764-202009000-00003 32890204 · DOI
  59. [69]Nguyen OT Turner K Charles D Sprow O Perkins R Hong YR Islam JY Khanna N Tabriz AS Hallanger-Johnson J Young JB Moore CE Implementing digital scribes to reduce electronic health record documentation burden among cancer care clinicians: a mixed-methods pilot study JCO Clin Cancer Inform 2023 7 e2200166 10.1200/CCI.22.00166 36972488 36972488 · DOI
  60. [70]Ghatnekar S Faletsky A Nambudiri VE Digital scribe utility and barriers to implementation in clinical practice: a scoping review Health Technol (Berl) 2021 11 4 803 809 10.1007/s12553-021-00568-0 34094806 568 34094806 PMC8169416 · DOI
  61. [71]Lourie EM Utidjian LH Ricci MF Webster L Young C Grenfell SM Reducing electronic health record-related burnout in providers through a personalized efficiency improvement program J Am Med Inform Assoc 2021 28 5 931 937 10.1093/jamia/ocaa248 33166384 5964085 33166384 PMC8068431 · DOI
  62. [72]DeWitt D Harrison LE The potential impact of scribes on medical school applicants and medical students with the new clinical documentation guidelines J Gen Intern Med 2018 33 11 2002 2004 10.1007/s11606-018-4582-8 30066114 10.1007/s11606-018-4582-8 30066114 PMC6206368 · DOI
  63. [73]Liu S McCoy AB Wright AP Carew B Genkins JZ Huang SS Peterson JF Steitz B Wright A Leveraging large language models for generating responses to patient messages—a subjective analysis J Am Med Inform Assoc 2024 ocae052 10.1093/jamia/ocae052 38497958 7630962 PMC11105129 38497958 · DOI
  64. [74]Liu S McCoy AB Wright AP Nelson SS Huang SS Ahmad HB Carro SE Franklin J Brogan J Wright A Why do users override alerts? Utilizing large language model to summarize comments and optimize clinical decision support J Am Med Inform Assoc 2024 ocae041 10.1093/jamia/ocae041 38452289 7624148 PMC11105133 38452289 · DOI
  65. [75]Payne TH Alonso WD Markiel JA Lybarger K Lordon R Yetisgen M Zech JM White AA Using voice to create inpatient progress notes: effects on note timeliness, quality, and physician satisfaction JAMIA Open 2018 1 2 218 226 10.1093/jamiaopen/ooy036 31984334 ooy036 31984334 PMC6951907 · DOI
  66. [76]Wang JX Sullivan DK Wells AC Chen JH ClinicNet: machine learning for personalized clinical order set recommendations JAMIA Open 2020 3 2 216 224 10.1093/jamiaopen/ooaa021 32734162 ooaa021 32734162 PMC7382624 · DOI
  67. [77]Dymek C Kim B Melton GB Payne TH Singh H Hsiao CJ Building the evidence-base to reduce electronic health record-related clinician burden J Am Med Inform Assoc 2021 28 5 1057 1061 10.1093/jamia/ocaa238 33340326 6042116 33340326 PMC8068419 · DOI
  68. [79]Liu J Wang C Liu S Utility of ChatGPT in clinical practice J Med Internet Res 2023 25 e48568 10.2196/48568 37379067 v25i1e48568 37379067 PMC10365580 · DOI · Paper page
  69. [80]Liu S McCoy AB Peterson JF Lasko TA Sittig DF Nelson SD Andrews J Patterson L Cobb CM Mulherin D Morton CT Wright A Leveraging explainable artificial intelligence to optimize clinical decision support J Am Med Inform Assoc 2024 31 4 968 974 10.1093/jamia/ocae019 38383050 7610153 38383050 PMC10990514 · DOI
  70. [81]Atutxa A Perez A Casillas A Atutxa A Perez A Casillas A Machine learning approaches on diagnostic term encoding with the ICD for clinical documentation IEEE J Biomed Health Inform 2018 22 4 1323 1329 10.1109/JBHI.2017.2743824 28858819 28858819 · DOI
  71. [82]Khairat S Coleman C Ottmar P Jayachander DI Bice T Carson SS Association of electronic health record use with physician fatigue and efficiency JAMA Netw Open 2020 3 6 e207385 10.1001/jamanetworkopen.2020.7385 32515799 2766836 32515799 PMC7284310 · DOI · Paper page
  72. [83]Murphy DR Satterly T Giardina TD Sittig DF Singh H Practicing clinicians' recommendations to reduce burden from the electronic health record inbox: a mixed-methods study J Gen Intern Med 2019 34 9 1825 1832 10.1007/s11606-019-05112-5 31292905 10.1007/s11606-019-05112-5 31292905 PMC6712240 · DOI
  73. [85]Liu S Wright AP Patterson BL Wanderer JP Turer RW Nelson SD McCoy AB Sittig DF Wright A Using AI-generated suggestions from ChatGPT to optimize clinical decision support J Am Med Inform Assoc 2023 30 7 1237 1245 10.1093/jamia/ocad072 37087108 7136722 37087108 PMC10280357 · DOI · Paper page

Cited by

Sorted by citations

Authors
Wu, Y., Wu, M., Wang, C., Lin, J., Liu, J., & Liu, S.
Affiliations
  • Sichuan University (CN)
  • Vanderbilt University Medical Center (US)
Corresponding author
Liu, Jialin
ORCID
Venue
JMIR Medical Informatics
Publisher
JMIR Publications Inc.
Published
2024-06-12
Volume
12
Pages
e54811
ISSN
2291-9694 (ISSN-L)
DOI
10.2196/54811
PMC
PMC11208837
OpenAlex
W4394886516
Cited by
87
References
9
Citations by year
2026: 59 · 2025: 26 · 2024: 2
FWCI
6.83
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR Medical Informatics (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (acceptedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Health Professions › General Health Professions › Healthcare professionals’ stress and burnout
  • Social Sciences › Psychology › Social Psychology › Stress and Burnout Research
Keywords
burnout, electronic health records, healthcare workers, prevalence, physicians, registered nurses, documentation burden, scribes, artificial intelligence, health information systems

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review