physician information needs and electronic health records (EHRs): time to reengineer the clinic note
Open accessAbstract
BACKGROUND: Primary care physicians face cognitive overload daily, perhaps exacerbated by the form of electronic health record documentation. We examined physician information needs to prepare for clinic visits, focusing on past clinic progress notes. METHODS: This study used cognitive task analysis with 16 primary care physicians in the scenario of preparing for office visits. Physicians reviewed simulated acute and chronic care visit notes. We collected field notes and document highlighting and review, and we audio-recorded cognitive interview while on task, with subsequent thematic qualitative analysis. Member checks included the presentation of findings to the interviewed physicians and their faculty peers. RESULTS: The Assessment and Plan section was most important and usually reviewed first. The History of the Present Illness section could provide supporting information, especially if in narrative form. Physicians expressed frustration with the Review of Systems section, lamenting that the forces driving note construction did not match their information needs. Repetition of information contained in other parts of the chart (eg, medication lists) was identified as a source of note clutter. A workflow that included a patient summary dashboard made some elements of past notes redundant and therefore a source of clutter. CONCLUSIONS: Current ambulatory progress notes present more information to the physician than necessary and in an antiquated format. It is time to reengineer the clinic progress note to match the workflow and information needs of its primary consumer.
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.
Integrity signals
Registry
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.
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?
Questions regarding subjective burden and satisfaction in documentation practices remain unanswered.
“Questions regarding subjective burden and satisfaction in documentation practices remain unanswered.”
From Effect of an Electronic Health Record-Based Intervention on Documentation Practices (2024) · cites this paper as [19]
The Emotion and Frustration section reports physicians’ distress and frustration with EHR notes, addressing an aspect of subjective burden. The Discussion says the study examined information needs during simulated visit preparation, but it does not establish that questions about documentation burden and satisfaction remain unanswered; satisfaction was not assessed. (LLM, conf=0.74)
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.
Cites
Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414 · see citing works
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,557 · see citing works
Hietala, M. (1983) · Scandinavian Journal of History · doi:10.1080/03468758308579015 · Cited by 6,232 · see citing works
Plans and the structure of behavior.
Miller, G. A., Galanter, E., & Pribram, K. H. (1960) · doi:10.1037/10039-000 · Cited by 4,630 · see citing works
Nine Ways to Reduce Cognitive Load in Multimedia Learning
Mayer, R. E., & Moreno, R. (2003) · Educational Psychologist · doi:10.1207/s15326985ep3801_6 · Cited by 4,207 · see citing works
Brown, R. W. (1960) · Language · doi:10.2307/411065 · Cited by 3,525 · see citing works
Physicians’ Use Of Electronic Medical Records: Barriers And Solutions
Miller, R. H., & Sim, I. (2004) · Health Affairs · doi:10.1377/hlthaff.23.2.116 · Cited by 869 · see citing works
Cognitive and usability engineering methods for the evaluation of clinical information systems.
Kushniruk, A. W., & Patel, V. L. (2004) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2004.01.003 · Cited by 760 · see citing works
Friedberg, M., Chen, P., Van Busum, K., Aunon, F., Pham, C., Caloyeras, J., Mattke, S., Pitchforth, E., Quigley, D., Brook, R., et al. (2014) · RAND Health Quarterly · doi:10.7249/rhq-03-04-01 · Cited by 707 · see citing works
INFORMATION INPUT OVERLOAD AND PSYCHOPATHOLOGY
Miller, J. G. (1960) · American Journal of Psychiatry · doi:10.1176/ajp.116.8.695 · Cited by 375 · see citing works
A preliminary taxonomy of medical errors in family practice
Dovey, S. M. (2002) · BMJ Quality & Safety · doi:10.1136/qhc.11.3.233 · Cited by 345 · see citing works
Furukawa, M. F., King, J., Patel, V., Hsiao, C., Adler‐Milstein, J., & Jha, A. K. (2014) · Health Affairs · doi:10.1377/hlthaff.2014.0445 · Cited by 273 · see citing works
Physicians, Patients, and the Electronic Health Record: An Ethnographic Analysis
Ventres, W. (2006) · The Annals of Family Medicine · doi:10.1370/afm.425 · Cited by 245 · see citing works
Information Chaos in Primary Care: Implications for Physician Performance and Patient Safety
Beasley, J. W., Wetterneck, T. B., Temte, J. L., Lapin, J. A., Smith, P. D., Rivera-Rodriguez, A. J., & Karsh, B.-T. (2011) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2011.06.100255 · Cited by 242 · see citing works
Goldblatt, H., Karnieli‐Miller, O., & Neumann, M. (2011) · Patient Education and Counseling · doi:10.1016/j.pec.2010.12.016 · Cited by 209 · see citing works
The clinician's perspective on electronic health records and how they can affect patient care
Walsh, S. H. (2004) · BMJ · doi:10.1136/bmj.328.7449.1184 · Cited by 209 · see citing works
Clarke, M. A., Belden, J. L., Koopman, R. J., Steege, L. M. B., Moore, J. L., Canfield, S. M., & Kim, M. S. (2013) · Health Information & Libraries Journal · doi:10.1111/hir.12036 · Cited by 198 · see citing works
Self-citationPlans and the Structure of Behavior.
Rioch, D. M. (1961) · Archives of General Psychiatry · doi:10.1001/archpsyc.1961.01710180104014 · Cited by 193 · see citing works
Physician adoption of electronic health record systems: United States, 2011.
Jamoom, E. W., Beatty, P., Bercovitz, A., Woodwell, D. A., Palso, K., & Rechtsteiner, E. A. (2012) · PubMed · Cited by 168 · see citing works
Koopman, R. J., Kochendorfer, K. M., Moore, J. L., Mehr, D. R., Wakefield, D. S., Yadamsuren, B., Coberly, J. S., Kruse, R. L., Wakefield, B. J., & Belden, J. L. (2011) · The Annals of Family Medicine · doi:10.1370/afm.1286 · Cited by 128 · see citing works
Self-citationCopy and Paste: A Remediable Hazard of Electronic Health Records
Siegler, E. L., & Adelman, R. D. (2009) · The American Journal of Medicine · doi:10.1016/j.amjmed.2009.02.010 · Cited by 120 · see citing works
The Rise of Electronic Health Record Adoption Among Family Physicians
Xierali, I. M., Hsiao, C., Puffer, J. C., Green, L. A., Rinaldo, J., Bazemore, A., Burke, M. T., & Phillips, R. L. (2013) · The Annals of Family Medicine · doi:10.1370/afm.1461 · Cited by 103 · see citing works
Cusack, C. M., Hripcsak, G., Bloomrosen, M., Rosenbloom, S. T., Weaver, C. A., Wright, A., Vawdrey, D. K., Walker, J., & Mamykina, L. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001093 · Cited by 103 · see citing works
Medical Records and Other Stories: a Narratological Framework
Purves, I., & Kay, S. (1996) · Methods of Information in Medicine · doi:10.1055/s-0038-1634648 · Cited by 67 · see citing works
The 2012 EHR User Satisfaction Survey: responses from 3,088 family physicians.
Edsall, R. L., & Adler, K. G. (2013) · PubMed · Cited by 36 · see citing works
Making EHR notes more readable.
(2013) · PubMed · Cited by 4 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [20]20. Rogers EM. Diffusion of innovations. 3rd ed. New York: Free Press; 1983.
Cited by
Sorted by citations
Physician Time Spent Using the Electronic Health Record During Outpatient Encounters
Overhage, J. M., & McCallie, D. P. (2020) · Annals of Internal Medicine · doi:10.7326/m18-3684 · Cited by 249 · see citing works
Burnout Related to Electronic Health Record Use in Primary Care
Budd, J. (2023) · Journal of Primary Care & Community Health · doi:10.1177/21501319231166921 · Cited by 223 · see citing works
Colicchio, T. K., Cimino, J., & Fiol, G. D. (2019) · Journal of Medical Internet Research · doi:10.2196/13313 · Cited by 139 · see citing works
“The use of clinical documentation for nonclinical purposes is increasing and is source of frustration among physicians [50,51].”
BackgroundAsgari, E., Kaur, J., Nuredini, G., Balloch, J., Taylor, A. M., Sebire, N., Robinson, R., Peters, C., Sridharan, S., & Pimenta, D. (2024) · JMIR Medical Informatics · doi:10.2196/55499 · Cited by 142 · see citing works
“Although thorough documentation is key for clinical care, there has been a rise in complex and lengthy documentation of content that is required for billing purposes, quality improvement measures, avoiding malpractice, and signs of compliance [72].”
BackgroundPatient Safety Issues From Information Overload in Electronic Medical Records
Nijor, S., Rallis, G., Lad, N., & Gokcen, E. (2022) · Journal of Patient Safety · doi:10.1097/pts.0000000000001002 · Cited by 137 · see citing works
Opportunities and Challenges in Leveraging Electronic Health Record Data in Oncology
Berger, M. L., Curtis, M. D., Smith, G., Harnett, J., & Abernethy, A. P. (2016) · Future Oncology · doi:10.2217/fon-2015-0043 · Cited by 98 · see citing works
Nguyen, O. T., Jenkins, N. J., Khanna, N., Shah, S., Gartland, A., Turner, K. L., & Merlo, L. J. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa339 · Cited by 97 · see citing works
Colicchio, T. K., & Cimino, J. J. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy155 · Cited by 66 · see citing works
Alba, C., Xue, B., Abraham, J., Kannampallil, T., & Lu, C. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01489-2 · Cited by 46 · see citing works
“This versatility not only enhances the utility of the model but also contributes to a reduction in the cognitive load required by clinicians to decipher potential risk factors manually [47], thereby reducing the risk of clinician burnout, which is presently at near crisis levels [48].”
Automation to optimise physician treatment of individual patients: examples in psychiatry
Bauer, M., Monteith, S., Geddes, J., Gitlin, M. J., Grof, P., Whybrow, P. C., & Glenn, T. (2019) · The Lancet Psychiatry · doi:10.1016/s2215-0366(19)30041-0 · Cited by 44 · see citing works
Koopman, R. J., Canfield, S. M., Belden, J. L., Wegier, P., Shaffer, V. A., Valentine, K. D., Jain, A., Steege, L. M. B., Patil, S. J., Popescu, M., et al. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01194-y · Cited by 43 · see citing works
Self-citationNguyen, O. T., Shah, S., Gartland, A., Parekh, A., Turner, K. L., Feldman, S. S., & Merlo, L. J. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa289 · Cited by 43 · see citing works
Brown, K. N., Leigh, J. P., Kamran, H., Bagshaw, S. M., Fowler, R. A., Dodek, P., Turgeon, A. F., Forster, A. J., Lamontagne, F., Soo, A., et al. (2018) · Critical Care · doi:10.1186/s13054-018-1941-0 · Cited by 41 · see citing works
“The medical record is central to this process because it is the repository for documenting events [22, 23], current issues [24], and services provided [25].”
BackgroundDynamic Electronic Health Record Note Prototype: Seeing More by Showing Less
Belden, J. L., Koopman, R. J., Patil, S. J., Lowrance, N., Petroski, G. F., & Smith, J. B. (2017) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2017.06.170028 · Cited by 37 · see citing works
“We iteratively developed physician clinic note prototypes with features designed to emphasize vital information and de-emphasize less important information, with level of importance identified by clinicians in a previous study.(17) We utilized 4 different visual display models (listed in Table 1 and pictured in Figure…”
BackgroundMethodSelf-citationChallenges and Opportunities to Improve the Clinician Experience Reviewing Electronic Progress Notes
Hultman, G. M., Marquard, J. L., Lindemann, E. A., Arsoniadis, E. G., Pakhomov, S., & Melton, G. B. (2019) · Applied Clinical Informatics · doi:10.1055/s-0039-1692164 · Cited by 35 · see citing works
Belyeu, B. M., Klein, J. W., Reisch, L. M., Peacock, S., Oster, N. V., Elmore, J. G., & Jackson, S. L. (2017) · Health Expectations · doi:10.1111/hex.12641 · Cited by 33 · see citing works
Moon, M. C., Hills, R., & Demiris, G. (2018) · BMJ Health & Care Informatics · doi:10.14236/jhi.v25i2.1011 · Cited by 31 · see citing works
“We created a list of potential participants from five sources that identified high-performing healthcare organisations, which consisted of the Healthcare Information and Management Systems Society (HIMSS) Davies Award winners (33 healthcare organisations); Baldrige Award recipients (9); the 2014–2015 Best Hospitals Ho…”
BackgroundScheitel, M. R., Kessler, M., Shellum, J. L., Peters, S. G., Milliner, D. S., Liu, H., Elayavilli, R. K., Poterack, K. A., Miksch, T. A., Boysen, J. J., et al. (2017) · Applied Clinical Informatics · doi:10.4338/aci-2016-07-ra-0114 · Cited by 28 · see citing works
“Another barrier is the current state of the EHR, containing an overwhelming amount of information in the clinical and structured data elements, not necessarily optimized for clinician workflow [3–4].”
BackgroundEpstein, J. A., Cofrancesco, J., Beach, M. C., Bertram, A., Hedian, H. F., Mixter, S., Yeh, H.-C., & Berkenblit, G. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-020-06188-0 · Cited by 26 · see citing works
Electronic Health Record Innovations for Healthier Patients and Happier Doctors
Krist, A. H. (2015) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2015.03.150097 · Cited by 27 · see citing works
“5 Koopman et al 6 used cognitive task analysis to simulate how clinicians prepare for an office visit to understand what information is needed from encounter notes.”
MethodSinnott, C., Georgiadis, A., Park, J., & Dixon‐Woods, M. (2020) · The Annals of Family Medicine · doi:10.1370/afm.2485 · Cited by 26 · see citing works
User-centered design of a longitudinal care plan for children with medical complexity
Desai, A. D., Wang, G., Wignall, J., Kinard, D., Singh, V., Adams, S. L., & Pratt, W. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa193 · Cited by 25 · see citing works
Mörike, F., Spiehl, H. L., & Feufel, M. A. (2022) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208221087013 · Cited by 21 · see citing works
“Examples from the literature show that HIS may distract from the doctor-patient interaction (Koopman et al., 2015; Pelland et al., 2017), incomplete records in HIS hamper the interaction between healthcare professionals (e.g., Savoy et al., 2021), information retrieval in large HIS often requires…”
BackgroundInvolving Health Care Professionals in the Development of Electronic Health Records: Scoping Review
Busse, T. S., Jux, C., Laser, J., Rasche, P., Vollmar, H. C., Ehlers, J. P., & Kernebeck, S. (2023) · JMIR Human Factors · doi:10.2196/45598 · Cited by 24 · see citing works
Ahlness, E. A., Orlander, J. D., Brunner, J., Cutrona, S. L., Kim, B., Molloy-Paolillo, B. K., Rinne, S. T., Rucci, J. M., Sayre, G. G., & Anderson, E. (2023) · Journal of General Internal Medicine · doi:10.1007/s11606-023-08282-5 · Cited by 21 · see citing works
“This affects users’ distribution and content of work tasks and information flows 16,30,31 and has further implications for systems at large, creating silos and disparities in information access and work processes.”
BackgroundInterest in technology among medical students early in their clinical experience
Avidan, A., Weissman, C., & Zisk‐Rony, R. Y. (2021) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2021.104512 · Cited by 19 · see citing works
Leigh, J. P., Brundin‐Mather, R., Zjadewicz, K., Soo, A., & Stelfox, H. T. (2020) · Journal of Critical Care · doi:10.1016/j.jcrc.2020.01.019 · Cited by 18 · see citing works
Sutton, J., Ash, S. R., Al-Makki, A. A., & Kalakeche, R. (2019) · The Permanente Journal · doi:10.7812/tpp/18-221 · Cited by 17 · see citing works
Savoy, A., Patel, H., Murphy, D. R., Meyer, A. N. D., Herout, J., & Singh, H. (2021) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/00187208211014300 · Cited by 14 · see citing works
“Outcomes associated with information overload included (1) increased Belden et al., 2017; Clarke et al., 2014; Koopman et al., 2015; Weir et al., 2015 - itizing information (Menon et al., 2016; Singh et al., 2013; Smith et al., 2019).”
BackgroundMethodInfluentialSinha, A., Shanafelt, T. D., Trockel, M., Wang, H., & Sharp, C. (2021) · Applied Clinical Informatics · doi:10.1055/s-0041-1731678 · Cited by 13 · see citing works
Yu, A., Quan, H., McRae, A. D., Wagner, G., Hill, M. D., & Coutts, S. B. (2017) · BMJ Open · doi:10.1136/bmjopen-2016-015234 · Cited by 13 · see citing works
“Physicians report that the ‘Assessment and plan’ section is most valued and often reviewed first.(15) In our study, although 82% of the patients received a specialist evaluation, close to one in five charts had no definite diagnosis documented and another one in five charts documented multiple competing diagnoses with…”
BackgroundTran, B. D., Rosenbaum, K., & Zheng, K. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa345 · Cited by 13 · see citing works
Opportunities to use electronic health record audit logs to improve cancer care
Huilgol, Y. S., Adler‐Milstein, J., Ivey, S. L., & Hong, J. C. (2022) · Cancer Medicine · doi:10.1002/cam4.4690 · Cited by 12 · see citing works
Bozan, K., & Berger, A. (2018) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2018.384 · Cited by 12 · see citing works
Overlaying multiple sources of data to identify bottlenecks in clinical workflow
Vankipuram, A., Patel, V. L., Traub, S. J., & Shortliffe, E. H. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.yjbinx.2019.100004 · Cited by 12 · see citing works
Hier, D. B., Carrithers, M. D., Platt, S. K., Nguyen, A. Q., Giannopoulos, I., & Obafemi-Ajayi, T. (2025) · Information · doi:10.3390/info16060446 · Cited by 12 · see citing works
Evaluating Electronic Health Record Limitations and Time Expenditure in a German Medical Center
de Hoop, T., & Neumuth, T. (2021) · Applied Clinical Informatics · doi:10.1055/s-0041-1739519 · Cited by 11 · see citing works
“, 47 – 50 Evaluating EHR Time and Limitations in Germany de Hoop, Neumuth 1087 T h i s do c u m en t w a s do w n l oaded f o r pe r s ona l u s e on l y .”
BackgroundOnyeabor, U. S., Onwuasoigwe, O., Okenwa, W. O., Schaaf, T., Niels Pinkwart, C., & Balzer, F. (2025) · Digital Health · doi:10.1177/20552076251341089 · Cited by 10 · see citing works
Linking physicians’ medical practice information needs, resources and barriers to job satisfaction
Κωσταγιόλας, Π., Gorezis, P., Martzoukou, K., Deligeorgis, D., & Niakas, D. A. (2016) · Journal of Documentation · doi:10.1108/jd-10-2015-0133 · Cited by 10 · see citing works
“Although physicians use a combination of formal and informal sources during information seeking for everyday medical practices, they mostly trust-specific information resources when it comes to satisfying precise information needs that depend on a clinical situation (Koopman et al., 2015).”
BackgroundColicchio, T. K., Dissanayake, P. I., & Cimino, J. J. (2020) · PubMed Central · Cited by 7 · see citing works
Physicians’ perceptions about narrative note sections format and content: A multi-specialty survey
Colicchio, T. K., Dissanayake, P. I., & Cimino, J. J. (2021) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2021.104475 · Cited by 7 · see citing works
Diagnosis Documentation of Critically Ill Children at Admission to a PICU*
Vivtcharenko, V. Y., Ramesh, S., Dukes, K., Singh, H., Herwaldt, L. A., Reisinger, H. S., & Cifra, C. L. (2021) · Pediatric Critical Care Medicine · doi:10.1097/pcc.0000000000002812 · Cited by 7 · see citing works
“Well-organized diagnosis narratives facilitate readers’ comprehension (4, 20).”
BackgroundLiang, J. J., Tsou, C.-H., Dandala, B., Poddar, A., Joopudi, V., Mahajan, D., Prager, J. M., Raghavan, P., & Payne, M. (2021) · PubMed Central · Cited by 7 · see citing works
Onyeabor, U. S., Onwuasoigwe, O., Okenwa, W. O., Schaaf, T., Niels Pinkwart, C., & Balzer, F. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1488880 · Cited by 6 · see citing works
“Furthermore, ineffectively designed systems may lead to cognitive overload and strain, resulting in interference with the patient-physician relationship (18, 19).”
Visualizing Semantic Structure of a Clinical Text Document
Kenei, J., Opiyo, E. T. O., & Oboko, R. O. (2020) · European Journal of Electrical Engineering and Computer Science · doi:10.24018/ejece.2020.4.6.256 · Cited by 6 · see citing works
“Electronic health records (EHRs) can improve the ability to diagnose diseases and reduce or even prevent medical errors, improving patient outcomes [31].”
BackgroundRajaram, A., Judd, M., & Barber, D. (2025) · JMIR AI · doi:10.2196/64279 · Cited by 6 · see citing works
Herasevich, S., Pinevich, Y., Lindroth, H. L., Herasevich, V., Pickering, B. W., & Barwise, A. K. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105118 · Cited by 6 · see citing works
McGrath, S. P., Wells, E. E., McGovern, K. M., Perreard, I. M., Stewart, K., McGrath, D., & Blike, G. T. (2019) · Emerald Group Publishing Limited eBooks · doi:10.1108/s1474-823120190000018006 · Cited by 5 · see citing works
Effect of an Electronic Health Record-Based Intervention on Documentation Practices
Shah, S., Bedgood, M., Devon-Sand, A., Dolphin-Dempsey, C., Cherukuri, V., Weng, K., Lin, S., & Sharp, C. (2024) · Applied Clinical Informatics · doi:10.1055/a-2367-8564 · Cited by 4 · see citing works
“We speci fi cally leveraged prior evidence pertaining to clinical note assessment and optimization, 20 – 22 including resources related to the OpenNotes initiative.”
Almuqbil, M. S., Alturki, H., Aljuffali, L. A., Al-otaibi, N., Awaad, N., Alkhudair, N. A., Alhammad, A., Alsuwayni, B. M., Alrouwaijeh, S., Aljawadi, M. H., et al. (2023) · Saudi Pharmaceutical Journal · doi:10.1016/j.jsps.2023.101795 · Cited by 4 · see citing works
“That was expected as clinicians considered the assessment and plan sections to be the most important and the first thing they would read among all progress note sections (Koopman et al., 2015).”
Mora, E. E. V., Gemmani, M., Zayas-Castro, J. L., & Martínez, D. A. (2015) · Applied Clinical Informatics · doi:10.4338/aci-2015-06-ra-0068 · Cited by 4 · see citing works
“Although previous investigations have made valuable contributions to the knowledge base on informational needs of physicians and patterns of use of HIE systems [45, 46], most of them focus solely on hospital and primary care provider communication.”
BackgroundEarly Performance of the Patients Over Paperwork Initiative among Family Medicine Physicians
Nguyen, O. T., Hanna, K., Merlo, L. J., Parekh, A., Tabriz, A. A., Hong, Y., Feldman, S. S., & Turner, K. L. (2023) · Southern Medical Journal · doi:10.14423/smj.0000000000001526 · Cited by 4 · see citing works
Kennell, T., Dempsey, D. M., & Cimino, J. J. (2016) · PubMed Central · Cited by 4 · see citing works
In Search of Cognitive Dignity
Sorum, P. C. (2016) · Medical Decision Making · doi:10.1177/0272989x16662643 · Cited by 4 · see citing works
Canfield, S. M., Stanley, Y., Ghosh, P., Braddock, A. S., & Foraker, R. (2025) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-025-07632-x · Cited by 3 · see citing works
“The interview guide was developed by the principal investigator (SC), a PhD-trained researcher with expertise in EHR interventions, HDP, and qualitative research, in collaboration with a lead research analyst specializing in qualitative methods (PG) [15, 26, 33–35].”
Self-citationTowards a theoretical model of dashboard acceptance and use in healthcare domain
Mashinchi, M. I., Ojo, A., & Sullivan, F. J. (2021) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2021.446 · Cited by 3 · see citing works
“Moreover, advances in cognitive science and technology have led to increasing interest in the use of interactive visual information displays to support decision making in healthcare [2], [3], [5].”
BackgroundAlmidani, E., Khadawardi, E., Alshareef, T., Saadeh, S. A., Alrowaily, F., Elsaidawi, W., Qeretli, R., Alobari, R., Al-Hajjar, S. H., & Al-Mofada, S. M. (2018) · International Journal of Pediatrics and Adolescent Medicine · doi:10.1016/j.ijpam.2018.05.002 · Cited by 3 · see citing works
“The debate about its content and structure is still needed to be examined more to achieve a good quality andmore user-friendly content [9,16,17].”
BackgroundIs Electronic Health Record Safety a Paradox?
Harrington, L. (2021) · AACN Advanced Critical Care · doi:10.4037/aacnacc2021406 · Cited by 3 · see citing works
Kenei, J., & Opiyo, E. T. O. (2022) · International Conference on Medical and Health Informatics (ICMHI) · doi:10.1145/3545729.3545746 · Cited by 2 · see citing works
Moon, S., Liu, S., Kshatriya, B. S. A., Fu, S., Moser, E. D., Bielinski, S. J., Fan, J. W., & Liu, H. (2023) · PLoS ONE · doi:10.1371/journal.pone.0283800 · Cited by 2 · see citing works
“Meanwhile, the “Review of System” does not sufficiently record medical history [26].”
BackgroundResultEHR Conversion on the PreOp Care: A Pre-Post Workflow Comparison.
Zheng, L., Duncan, B. J., Kaufman, D. R., Furniss, S. K., Grando, A., Poterack, K. A., Helmers, R. A., Miksch, T. A., & Doebbeling, B. N. (2020) · PubMed Central · Cited by 2 · see citing works
LabVis: usability testing of a prototype tool for integrating timeline graphs and clinical notes
Torsvik, T., Brun, A., Benjaminsen, B. S., & Steinsbekk, A. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-025-03173-7 · Cited by 1 · see citing works
“As patients age and more treat-ment options become available, their medical records can quickly become unmanageably large, making it time-consuming and labor-intensive to compile a coherent overview [2, 3].”
Park, S., Marquard, J. L., Austin, R. R., Martin, C. L., Pieczkiewicz, D. S., & Delaney, C. W. (2025) · Applied Clinical Informatics · doi:10.1055/a-2688-4056 · Cited by 1 · see citing works
McGlynn, M. C., Mirpuri, K. K., Bereitschaft, C., Blazin, L., Ilowite, M. F., Mack, J. W., DuBois, J. M., & Sisk, B. A. (2026) · Pediatric Blood & Cancer · doi:10.1002/1545-5017.70018 · Cited by 1 · see citing works
Rhodes, B., Short, A., & Shaben, T. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-805362-1.00015-2 · Cited by 1 · see citing works
Aljarbooa, E. F., & Sekhar, C. (2023) · Cureus · doi:10.7759/cureus.48536 · Cited by 1 · see citing works
“In the study by Koopman et al., the design of the EHR was discussed, revealing that the current ambulatory progress notes present more information to the physician than is necessary [3].”
BackgroundClinical Documents Summarization using Text Visualization Technique
Kenei, J., Opiyo, E. T. O., Moso, J. C., & Oboko, R. O. (2018) · Cited by 1 · see citing works
O Futuro da Gestão de Identidades Digitais
Wangham, M. S., Marins, A. L. A., Ferraz, C. A. G., da Silva, C. E., Saade, D. C. M., Silva, E. F., de Mello, E. R., de Oliveira, F. B., Seixas, F. L., Oliveira, L. B., et al. (2018) · Simpósio Brasileiro de Cibersegurança (SBSeg) · doi:10.5753/sbseg_estendido.2018.4152 · Cited by 1 · see citing works
“[Koopman et al. 2015] Koopman, R. J., Steege, L. M. B., Moore, J. L., Clarke, M. A., Canfield, S. M., Kim, M. S., and Belden, J. L. (2015).”
BackgroundSudiarmini, L., Sudiarmini, L., Bagus, F. M. I., & Nyoman, H. S. I. (2020) · WMJ (Warmadewa Medical Journal) · doi:10.22225/wmj.5.2.1636.60-69 · Cited by 1 · see citing works
Hicks, W. B. (2021) · NCSU Libraries Repository (North Carolina State University Libraries) · Cited by 1 · see citing works
Goldman, A., & Kathrins, M. N. (2022) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2021.11.008 · Cited by 1 · see citing works
Impact of clinical note format on diagnostic accuracy and efficiency
Payton, E. M., Graber, M. L., Bachiashvili, V., Mehta, T. S., Dissanayake, P. I., & Berner, E. S. (2023) · Health Information Management Journal · doi:10.1177/18333583231151979 · Cited by 1 · see citing works
“Some previous studies have indicated that clinicians feel constrained by the limitations of creating structured EHR notes (Koopman et al., 2015; Rosenbloom et al., 2011).”
Informing the Design and Deployment of Health Information Technology to Improve Care Coordination
Martínez, D. A. (2015) · Digital Commons - University of South Florida (University of South Florida)
Berkenblit, G. V., Koehler, E., & Epstein, J. A. (2017) · Springer eBooks · doi:10.1007/978-3-319-68267-9_16
Diagnostic error will bring about a new era of digitalized medicine
Nakano, K., Watari, T., Akazawa, K., Kitagawa, I., & Watanuki, S. (2019) · Journal of General and Family Medicine · doi:10.1002/jgf2.233
Yaghini, J., Aminzadeh, A., Abed, A. M., Saeidi, A., & Naghsh, N. (2018) · Journal of Advanced Periodontology & Implant Dentistry · doi:10.15171/jpid.2017.001
Melnick, B. K. S. K. F. L. I. T. G. B. N. R. G. H. E. R. (2017) · ACI Open · doi:10.1055/s-00034447
Ong, S. Y., O’Shea, J., & Rosenbaum, J. R. (2019) · doi:10.2196/preprints.17021
Implementation of a Web-Based Communication System for Primary Care Providers and Cancer Specialists
Petrovic, B., Bender, J. L., Liddy, C. E., Afkham, A., McGee, S. F., Morgan, S. C., SEGAL, R. J., O’Brien, M. A., Julian, J. A., SUSSMAN, J. S., et al. (2023) · Current Oncology · doi:10.3390/curroncol30030269
“Perhaps part of the resistance to adopting the eOncoNote system is related to the information overload that physicians experience through the use of EMRs [24], as well as frustration with having separate systems that are not integrated [8].”
BackgroundRefining Clinician Workflow as a Means to Improving Catheter Quality Measures
Clarke, M. A., Wardian, J., Fleharty, B. S., Reha, C. G., & Birge, J. (2023) · ACI Open · doi:10.1055/s-0043-1771237
Self-citationThe Impact of Medical Record Documentation on Healthcare Provider Productivity: (Review Artical)
ALRSHIDI, M. N. M. S. A. A. S. M., MOHAMMAD, A. S. B., & Alshammari, . N. K. (2023) · The Medical Journal of Cairo University/The Medical Journal of Cairo University · doi:10.21608/mjcu.2023.356630
Rajaram, A., Judd, M., & Barber, D. (2024) · doi:10.2196/preprints.64279
Mator, J. D., & Still, J. D. (2025) · Interacting with Computers · doi:10.1093/iwc/iwaf043
Rewriting the Note with Technology
Chadha, R., Salmon, T. R., Goodman, L. A., & Srour, H. (2025) · Medical Clinics of North America · doi:10.1016/j.mcna.2025.07.002 · Cited by 1 · see citing works
Kutscher, E. C., Halket, D., Feinberg, A., Blum, C. J., Koransky, A., Tamler, R., Federman, A. D., & Fishman, M. B. (2026) · Journal of General Internal Medicine · doi:10.1007/s11606-026-10858-w
Addressing administrative burden in family medicine: a local quality improvement initiative
Sundareswaran, M., & Moloney, M. (2026) · BMJ Open Quality · doi:10.1136/bmjoq-2025-004072
The Ambulatory Patient Experience with Ambient Artificial Intelligence Scribes: A Qualitative Study
Nguyen, O. T., Afshar, M., Jaeb, M. A., Baumann, M. R., Resnik, F., Sullivan, A. G., Wills, G., Dambach, J., Mrotek, L. A., Quinn, M., et al. (2026) · Journal of General Internal Medicine · doi:10.1007/s11606-026-10931-4
Emén, A., Torsvik, T., Berntsen, G., Broks, M., & Steinsbekk, A. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1954602
- Authors
- Koopman, R. J., Steege, L. M. B., Moore, J. L., Clarke, M. A., Canfield, S. M., Kim, M. S., & Belden, J. L.
- Affiliations
- University of Wisconsin–Madison (US)
- Venue
- The Journal of the American Board of Family Medicine
- Published
- 2015-05-01
- Volume
- 28
- Issue
- 3
- Pages
- 316-323
- ISSN
- 1557-2625 (ISSN-L)
- 1558-7118
- OpenAlex
- W1931861466
- Semantic Scholar
- e869234a562c11c13b20a7df48d7849987bb8837
- Cited by
- 90
- References
- 26
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 4 · 2023: 13 · 2022: 5 · 2021: 11 · 2020: 12 · 2019: 8 · 2018: 8 · 2017: 7 · 2016: 4 · 2015: 3
- FWCI
- 14.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journal of the American Board of Family Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Missouri
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Keywords
- electronic health records, clinical progress notes, physician information needs, cognitive overload, primary care physicians, cognitive task analysis, history of present illness, review of systems
- MeSH terms
- Attitude of Health Personnel, Cognition, Documentation, Female, Humans, Male, Primary Health Care, Needs Assessment, Qualitative Research, Workflow, Electronic Health Records, Physicians, Primary Care, Quality Improvement
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
