Cited by 97Electronic Health Records SystemsHospital Admissions and OutcomesMedical Coding and Health Information

Transitions from One Electronic Health Record to Another: Challenges, Pitfalls, and Recommendations

Open access
Huang, Chunya, Koppel, Ross, McGreevey, John D., Craven, Catherine K., Schreiber, Richard·2020·Applied Clinical Informatics

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.

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 · 10.1055/s-0040-1718535

Cites

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?

  • Challenges such as system construction variability, missing data, and dependence on original systems lead to conversion errors such as corrupted data and mismatched patient records, disrupting clinical workflows and compromising patient safety.

    “However, challenges, such as system construction variability, missing data, and dependence on original systems, lead to conversion errors such as corrupted data and mismatched patient records [167], disrupting clinical workflows and compromising patient safety [168].”

    From Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors (2026) · cites this paper as [168]

    Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

Self-check

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

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

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

References 54 · Cited by 97

Research works printed but not linked: 50

  1. Price S. Making the CEHRT Switch: EHR upgrade required for incentive payment programs. Tex Med 2019;115(01):40-42
  2. Lammers EJ, Zheng K. Characteristics associated with hospital health IT vendor switching and dropping. AMIA Annu Symp Proc 2011;2011:742-749
  3. Adler KG, Edsall RL. EHR switch survey: responses from 305 family physicians. Fam Pract Manag 2015;22(01):13-18
  4. Zandieh SO, Abramson EL, Pfoh ER, Yoon-Flannery K, Edwards A, Kaushal R. Transitioning between ambulatory EHRs: a study of practitioners' perspectives. J Am Med Inform Assoc 2012;19(03): 401-406
  5. Zandieh SO, Mills SA, Yoon-Flannery K, Yoon-Flannery K, Kuper- man GJ, Kaushal R. Providers' expectations of ambulatory elec- tronic health records (EHRs). AMIA Annu Symp Proc 2008:1191 PMID:18998972
  6. Wilson L. EHR DO-OVER? Providers begin replacing electronic patient record systems. Health Data Manag 2017;25(01):56-58
  7. Barkholz D. Vanderbilt is a case study for the dreaded EHR conversion. Mod Healthc 2017;47(19):10-11
  8. Jones HW. Exploring HIT Contract Cadavers to Avoid HIT Mana- gerial Malpractice. In: HIT or Miss: Lessons Learned from Health Information Technology Implementations 3rd ed Bethesda, Maryland: AHIMA Press; 2019:209-222
  9. Koppel R. Great promises of healthcare information technology deliver less. In: Weaver CA, Ball MJ, Kim GR, Kiel JM, eds. Healthcare Information Management Systems: Cases, Strategies, and Solutions. Switzerland: Springer International Publishing; 2016:101-125
  10. Braverman JA, Blumenthal-Barby JS. Assessment of the sunk-cost effect in clinical decision-making. Soc Sci Med 2012;75(01): 186-192
  11. Schreiber R, Garber L. Data migration: a thorny issue in electronic health record transitions-case studies and review of the litera- ture. ACI Open. 2020;04:e48-e58
  12. Gettinger A, Csatari A. Transitioning from a legacy EHR to a commercial, vendor-supplied, EHR: one academic health system's experience. Appl Clin Inform 2012;3(04):367-376
  13. McEvoy D, Barnett ML, Sittig DF, Aaron S, Mehrotra A, Wright A. Changes in hospital bond ratings after the transition to a new electronic health record. J Am Med Inform Assoc 2018;25(05): 572-574
  14. Yuan N, Dudley RA, Boscardin WJ, Lin GA. Electronic health records systems and hospital clinical performance: a study of nationwide hospital data. J Am Med Inform Assoc 2019;26(10): 999-1009
  15. Adler-Milstein J, Everson J, Lee S-YD. EHR Adoption and Hospital Performance: Time-Related Effects. Health Serv Res 2015;50(06): 1751-1771
  16. Ray JM, Ratwani RM, Sinsky CA, et al. Six habits of highly successful health information technology: powerful strategies for design and implementation. J Am Med Inform Assoc 2019; 26(10):1109-1114
  17. Magrabi F, Liaw ST, Arachi D, Runciman W, Coiera E, Kidd MR. Identifying patient safety problems associated with information technology in general practice: an analysis of incident reports. BMJ Qual Saf 2016;25(11):870-880
  18. Pfoh ER, Abramson E, Zandieh S, Edwards A, Kaushal R. Satisfac- tion after the transition between electronic health record systems at six ambulatory practices. J Eval Clin Pract 2012;18(06): 1133-1139
  19. Saleem JJ, Herout J. Transitioning from one electronic health record (EHR) to another: a narrative literature review. Proc Hum Factors Ergon Soc Annu Meet 2018;62(01):489-493
  20. Bornstein S. An integrated EHR at Northern California Kaiser Permanente: pitfalls, challenges, and benefits experienced in transitioning. Appl Clin Inform 2012;3(03):318-325
  21. Lin J, Ranslam K, Shi F, Figurski M, Liu Z. Data migration from operating EMRs to OpenEMR with Mirth Connect. Stud Health Technol Inform 2019;257:288-292
  22. Epstein RH, Dexter F, Schwenk ES. Provider access to legacy electronic anesthesia records following implementation of an electronic health record system. J Med Syst 2019;43(05):105
  23. D'Amore JD, Mandel JC, Kreda DA, et al. Are Meaningful Use Stage 2 certified EHRs ready for interoperability? Findings from the SMART C-CDA Collaborative. J Am Med Inform Assoc 2014;21(06): 1060-1068
  24. Mandel JC, Kreda DA, Mandl KD, Kohane IS, Ramoni RB. SMART on FHIR: a standards-based, interoperable apps platform for elec- tronic health records. J Am Med Inform Assoc 2016;23(05): 899-908
  25. Yang Y, Zhang Y. Application of Mirth Connect interface integra- tion engine in medical data transmission. Industrial Control Computer. 2016;29:112-113
  26. Camacho Rodriguez JC, Stäubert S, Löbe M. Automated import of clinical data from HL7 messages into OpenClinica and tranSMART using Mirth Connect. Stud Health Technol Inform 2016; 228:317-321
  27. Bortis G. Experiences with Mirth: an open source health care integration engine. In: Proceedings of the 30th International Con- ference on Software Engineering. ICSE '08. Association for Comput- ing Machinery 2008:649-652. Doi: 10.1145/1368088.1368179 · DOI
  28. Binney G, Cole-Poklewski T, Roomian T, et al. Effect of an elec- tronic health record transition on the provision of recommended well child services in pediatric primary care practices. Clin Pediatr (Phila) 2020;59(02):188-197
  29. Abramson EL, Patel V, Malhotra S, et al. Physician experiences transitioning between an older versus newer electronic health record for electronic prescribing. Int J Med Inform 2012;81(08): 539-548
  30. Girard NJ. DRESSed for failure. AORN J 2015;101(04):504, 464
  31. Whalen K, Lynch E, Moawad I, John T, Lozowski D, Cummings BM. Transition to a new electronic health record and pediatric medi- cation safety: lessons learned in pediatrics within a large aca- demic health system. J Am Med Inform Assoc 2018;25(07): 848-854
  32. Classen DC, Resar R, Griffin F, et al. 'Global trigger tool' shows that adverse events in hospitals may be ten times greater than previously measured. Health Aff (Millwood) 2011;30(04):581- 589
  33. McGreevey JD III, Mallozzi CP, Perkins RM, Shelov E, Schreiber R. Reducing alert burden in electronic health records: state of the art recommendations from four health systems. Appl Clin Inform 2020;11(01):1-12
  34. Wright A, Aaron S, Seger DL, Samal L, Schiff GD, Bates DW. Reduced effectiveness of interruptive drug-drug interaction alerts after conversion to a commercial electronic health record. J Gen Intern Med 2018;33(11):1868-1876
  35. Zandieh SO, Yoon-Flannery K, Kuperman GJ, Langsam DJ, Hyman D, Kaushal R. Challenges to EHR implementation in electronic- versus paper-based office practices. J Gen Intern Med 2008;23 (06):755-761
  36. Colicchio TK, Del Fiol G, Scammon DL, Facelli JC, Bowes WA III, Narus SP. Comprehensive methodology to monitor longitudinal change patterns during EHR implementations: a case study at a large health care delivery network. J Biomed Inform 2018; 83:40-53
  37. Noblin A, Cortelyou-Ward K, Cantiello J, et al. EHR implementa- tion in a new clinic: a case study of clinician perceptions. J Med Syst 2013;37(04):9955
  38. Zandieh SO, Yoon-Flannery K, Yoon-Flannery K, Kuperman GJ, Hyman D, Kaushal R. Correlates of expected satisfaction with electronic health records in office practices by practitioners. AMIA Annu Symp Proc. Published online November 6, 2008; 1190
  39. Reynolds TL, Clay B, Rudkin SE, et al. Migrating from one comprehensive commercial EHR to another: perceptions of front-line clinicians and staff. AMIA Annu Symp Proc 2020; 2019:765-773
  40. North F, Pecina JL, Tulledge-Scheitel SM, Chaudhry R, Matulis JC, Ebbert JO. Is a switch to a different electronic health record associated with a change in patient satisfaction? J Am Med Inform Assoc 2020;27(06):867-876
  41. Pandit RR, Boland MV. The impact of an electronic health record transition on a glaucoma subspecialty practice. Ophthalmology 2013;120(04):753-760
  42. Pirtle CJ, Reeder RR, Lehmann CU, Unertl KM, Lorenzi NM. Physician perspectives on training for an EHR implementation. Stud Health Technol Inform 2019;264:1318-1322
  43. Sieja A, Markley K, Pell J, et al. Optimization sprints: improving clinician satisfaction and teamwork by rapidly reducing electron- ic health record burden. Mayo Clin Proc 2019;94(05):793-802
  44. Silverman HD, Steen EB, Carpenito JN, Ondrula CJ, Williamson JJ, Fridsma DB. Domains, tasks, and knowledge for clinical informat- ics subspecialty practice: results of a practice analysis. J Am Med Inform Assoc 2019;26(07):586-593
  45. Johnson KB, Sternberg P Jr., Dubree M. An EPIC switch: observa- tions and opportunities after go-live. J Med Syst 2018;42(09):174
  46. Kannry J, Sengstack P, Thyvalikakath TP, et al. The chief clinical informatics officer (CCIO): AMIA task force report on CCIO knowl- edge, education, and skillset requirements. Appl Clin Inform 2016;7(01):143-176 62
  47. Pageler NM, Grazier G'Sell MJ, Chandler W, Mailes E, Yang C, Longhurst CA. A rational approach to legacy data validation when transitioning between electronic health record systems. J Am Med Inform Assoc 2016;23(05):991-994
  48. Wisniewski PJ, Knijnenburg BP, Lipford HR. Making privacy personal: Profiling social network users to inform privacy educa- tion and nudging. Int J Hum Comput Stud 2017;98:95-108
  49. Craven CK, Sievert MC, Hicks LL, Alexander GL, Hearne LB, Holmes JH. CAH to CAH: EHR implementation advice to critical access hospitals from peer experts and other key informants. Appl Clin Inform 2014;5(01):92-117
  50. Keenan G. Committing leadership resources: A CMIO and CPOE governance. In: Leviss J, Charney P, Corbit C, eds. HIT or Miss: Lessons Learned from Health Information Technology Implemen- tations. Bethesda, Maryland: AHIMA Press; 2019:123-126

Authors
Huang, C., Koppel, R., McGreevey, J. D., Craven, C. K., & Schreiber, R.
Affiliations
  • University of Louisville (US)
  • University at Buffalo, State University of New York (US)
  • University of Pennsylvania Health System (US)
  • Mount Sinai Health System (US)
  • Geisinger College of Health Sciences (US)
Corresponding author
Schreiber, Richard
Venue
Applied Clinical Informatics
Published
2020-10
Volume
11
Issue
05
Pages
742-754
ISSN
1869-0327 (ISSN-L)
OpenAlex
W3101984434
Cited by
97
References
54
Citations by year
2026: 26 · 2025: 18 · 2024: 19 · 2023: 23 · 2022: 7 · 2021: 4
FWCI
7.41
Type
journal article
Language
en
Open access
Locations
  • Applied Clinical Informatics (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
University of Pennsylvania
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Emergency Medicine › Hospital Admissions and Outcomes
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Keywords
patient safety, data integrity, semantic interoperability, cybersecurity, clinician burnout, transition planning, health information technology adoption, workflow changes
MeSH terms
Burnout, Professional, Humans, PubMed, Workflow, Electronic Health Records

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