Physician Use of Stigmatizing Language in Patient Medical Records
Open accessAbstract
Importance: Negative attitudes toward patients can adversely impact health care quality and contribute to health disparities. Stigmatizing language written in a patient's medical record can perpetuate negative attitudes and influence decision-making of clinicians subsequently caring for that patient. Objective: To identify and describe physician language in patient health records that may reflect, or engender in others, negative and positive attitudes toward the patient. Design, Setting, and Participants: This qualitative study analyzed randomly selected encounter notes from electronic medical records in the ambulatory internal medicine setting at an urban academic medical center. The 600 encounter notes were written by 138 physicians in 2017. Data were analyzed in 2019. Main Outcomes and Measures: Common linguistic characteristics reflecting an overall positive or negative attitude toward the patient. Results: A total of 138 clinicians wrote encounter notes about 507 patients. Of these patients, 350 (69%) were identified as female, 406 (80%) were identified as Black/African American, and 76 (15%) were identified as White. Of 600 encounter notes included in this study, there were 5 major themes representing negative language and 6 themes representing positive language. The majority of negative language was not explicit and generally fell into one or more of the following categories: (1) questioning patient credibility, (2) expressing disapproval of patient reasoning or self-care, (3) stereotyping by race or social class, (4) portraying the patient as difficult, and (5) emphasizing physician authority over the patient. Positive language was more often more explicit and included (1) direct compliments, (2) expressions of approval, (3) self-disclosure of the physician's own positive feelings toward the patient, (4) minimization of blame, (5) personalization, and (6) highlighting patient authority for their own decisions. Conclusions and Relevance: This qualitative study found that physicians express negative and positive attitudes toward patients when documenting in the medical record. Although often not explicit, this language could potentially transmit bias and affect the quality of care that patients subsequently receive. These findings suggest that increased physician awareness when writing and reading medical records is needed to prevent the perpetuation of negative bias in medical care.
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?
Data drift could affect automated gold label generation, making evaluation unreliable.
“In these cases, data drift could affect the automated gold label generation thus making the evaluation unreliable (e.g., if there is an increase in obese patients, the increased general negativity present in the clinical notes of obese patients 22,23 , could negatively impact the accuracy of gold labels created by neural language models).”
From Empirical data drift detection experiments on real-world medical imaging data (2024) · cites this paper as [23]
The Introduction (page unavailable) says that people with obesity may be viewed negatively by health professionals, and the Discussion describes negative language in patient records. The paper does not establish that notes about patients with obesity are more negative than other notes. Data drift and unreliable automated gold labels are the citing authors’ proposed consequence, not a finding attributed to this source. (LLM, conf=0.82)
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
Three Approaches to Qualitative Content Analysis
Hsieh, H.-F., & Shannon, S. E. (2005) · Qualitative Health Research · doi:10.1177/1049732305276687 · Cited by 44,601 · see citing works
Unequal treatment: confronting racial and ethnic disparities in health care
(2003) · Choice Reviews Online · doi:10.5860/choice.40-5843 · Cited by 7,043 · see citing works
Low Health Literacy and Health Outcomes: An Updated Systematic Review
Berkman, N. D., Sheridan, S. L., Donahue, K. E., Halpern, D. J., & Crotty, K. (2011) · Annals of Internal Medicine · doi:10.7326/0003-4819-155-2-201107190-00005 · Cited by 5,505 · see citing works
Capps, L. (2003) · JAMA · doi:10.1001/jama.290.18.2487-b · Cited by 4,558 · see citing works
Psychological Aspects of Natural Language Use: Our Words, Our Selves
Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. G. (2003) · Annual Review of Psychology · doi:10.1146/annurev.psych.54.101601.145041 · Cited by 2,624 · see citing works
Medical Professionalism in the New Millennium: A Physician Charter
Project of the ABIM Foundation, A. F. (2002) · Annals of Internal Medicine · doi:10.7326/0003-4819-136-3-200202050-00012 · Cited by 1,624 · see citing works
The unequal burden of pain: confronting racial and ethnic disparities in pain
Green, C. R., Anderson, K. O., Baker, T. A., Campbell, L. C., Decker, S., Fillingim, R. B., Kaloukalani, D. A., Lasch, K. E., Myers, C., Tait, R. C., et al. (2003) · Pain Medicine · doi:10.1046/j.1526-4637.2003.03034.x · Cited by 1,248 · see citing works
Physicians and Implicit Bias: How Doctors May Unwittingly Perpetuate Health Care Disparities
Chapman, E., Kaatz, A., & Carnes, M. (2013) · Journal of general internal medicine · doi:10.1007/s11606-013-2441-1 · Cited by 1,167 · see citing works
Medical professionalism in the new millennium: a physician charter
(2002) · Obstetrics & Gynecology · doi:10.1016/s0029-7844(02)02082-3 · Cited by 1,021 · see citing works
Ethnicity as a Risk Factor for Inadequate Emergency Department Analgesia
Todd, K. H. (1993) · JAMA · doi:10.1001/jama.1993.03500120075029 · Cited by 880 · see citing works
Chen, M. I.-C., & Bargh, J. A. (1997) · Journal of Experimental Social Psychology · doi:10.1006/jesp.1997.1329 · Cited by 526 · see citing works
Kelly, J. F., & Westerhoff, C. M. (2009) · International Journal of Drug Policy · doi:10.1016/j.drugpo.2009.10.010 · Cited by 481 · see citing works
Do Words Matter? Stigmatizing Language and the Transmission of Bias in the Medical Record
P. Goddu, A., O’Conor, K. J., Lanzkron, S., Saheed, M. O., Saha, S., Peek, M. E., Haywood, C., & Beach, M. C. (2018) · Journal of General Internal Medicine · doi:10.1007/s11606-017-4289-2 · Cited by 437 · see citing works
Self-citationThe role of language in emotion: predictions from psychological constructionism
Lindquist, K. A., MacCormack, J. K., & Shablack, H. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00444 · Cited by 400 · see citing works
Physician overestimation of patient literacy: A potential source of health care disparities
Kelly, P. A., & Haidet, P. (2006) · Patient Education and Counseling · doi:10.1016/j.pec.2006.10.007 · Cited by 360 · see citing works
Why do providers contribute to disparities and what can be done about it?
Burgess, D. J., Fu, S. S., & Ryn, M. (2004) · Journal of General Internal Medicine · doi:10.1111/j.1525-1497.2004.30227.x · Cited by 310 · see citing works
Walker, J., Leveille, S., Bell, S., Chimowitz, H., Dong, Z., Elmore, J. G., Fernandez, L., Fossa, A., Gerard, M., Fitzgerald, P., et al. (2019) · Journal of Medical Internet Research · doi:10.2196/13876 · Cited by 309 · see citing works
Reducing racial disparities in pain treatment: The role of empathy and perspective-taking
Drwecki, B. B., Moore, C. F., Ward, S. E., & Prkachin, K. M. (2011) · Pain · doi:10.1016/j.pain.2010.12.005 · Cited by 281 · see citing works
Kelly, J. F., Dow, S. J., & Westerhoff, C. (2010) · Journal of Drug Issues · doi:10.1177/002204261004000403 · Cited by 192 · see citing works
Obesity, stigma and public health planning
MacLean, L. M., Edwards, N. C., Garrard, M., Sims-Jones, N., Clinton, K. M., & Ashley, L. (2008) · Health Promotion International · doi:10.1093/heapro/dan041 · Cited by 151 · see citing works
Unconscious Biases: Racial Microaggressions in American Indian Health Care
Walls, M. L., Gonzalez, J., Gladney, T., & Onello, E. C. (2015) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2015.02.140194 · Cited by 141 · see citing works
Physicians are less willing to treat suicidal ideation in older patients
Uncapher, H., & Areán, P. A. (2000) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2000.tb03910.x · Cited by 137 · see citing works
Attitudes of Beginning Medical Students Toward Older Persons: A Five‐Campus Study
Reuben, D. B., Fullerton, J. T., Tschann, J. M., et al. (1995) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.1995.tb06626.x · Cited by 137 · see citing works
Linguistic Bases of Social Perception
Berry, D. S., Pennebaker, J. W., Mueller, J., & Hiller, W. S. (1997) · Personality and Social Psychology Bulletin · doi:10.1177/0146167297235008 · Cited by 119 · see citing works
Emergency Provider Analgesic Practices and Attitudes Toward Patients With Sickle Cell Disease
Glassberg, J., Tanabe, P. J., Chow, A. L., Harper, K. L., Haywood, C., DeBaun, M. R., & Richardson, L. D. (2013) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2013.02.004 · Cited by 116 · see citing works
Inequities in Healthcare: A Review of Bias and Discrimination in Obesity Treatment
Forhan, M. A., & Salas, X. R. (2013) · Canadian Journal of Diabetes · doi:10.1016/j.jcjd.2013.03.362 · Cited by 88 · see citing works
Hall, J. M., & Fields, B. (2015) · Global Qualitative Nursing Research · doi:10.1177/2333393615591569 · Cited by 61 · see citing works
Glassberg, J., Tanabe, P. J., Richardson, L., & DeBaun, M. R. (2013) · American Journal of Hematology · doi:10.1002/ajh.23441 · Cited by 56 · see citing works
Racial bias in presentation of cases
Finucane, T., & Carrese, J. (1990) · Journal of general internal medicine · doi:10.1007/bf02600511 · Cited by 53 · see citing works
Beukeboom, C. J., & Burgers, C. F. (2017) · Oxford Research Encyclopedia of Communication · doi:10.1093/acrefore/9780190228613.013.439 · Cited by 40 · see citing works
Alpert, J. M., Morris, B. B., Thomson, M. D., et al. (2019) · Patient Education and Counseling · doi:10.1016/j.pec.2019.05.008 · Cited by 26 · see citing works
Haywood, C., Lanzkron, S., Hughes, M., Brown, R., Saha, S., & Beach, M. C. (2015) · Journal of the National Medical Association · doi:10.1016/s0027-9684(15)30029-8 · Cited by 23 · see citing works
Self-citationA Prospective Examination of Racial Microaggressions in the Medical Encounter
Miller, L. R., & Peck, B. M. (2019) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-019-00680-y · Cited by 21 · see citing works
Merlin, J. S., Turan, J. M., Herbey, I. I., Westfall, A. O., Starrels, J. L., Kertesz, S. G., Saag, M. S., & Ritchie, C. S. (2014) · Pain Medicine · doi:10.1111/pme.12533 · Cited by 20 · see citing works
Decision-Making Capacity to Execute a Health Care Proxy: Development and Testing of Guidelines
Mezey, M., Teresi, J., Ramsey, G., et al. (2000) · Journal of the American Geriatrics Society · doi:10.1111/jgs.2000.48.issue-2 · Cited by 11 · see citing works
Attitudes of Beginning Medical Students Toward Older Persons: A Five-Campus Study
Reuben, D. B., Fullerton, J. T., Tschann, J. M., et al. (1995) · Journal of the American Geriatrics Society · doi:10.1111/jgs.1995.43.issue-12 · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Sun, M., Oliwa, T., Peek, M. E., & Tung, E. L. (2022) · Health Affairs · doi:10.1377/hlthaff.2021.01423 · Cited by 340 · see citing works
Empirical data drift detection experiments on real-world medical imaging data
Kore, A., Abbasi Bavil, E., Subasri, V., Abdalla, M., Fine, B., Dolatabadi, E., & Abdalla, M. (2024) · Nature Communications · doi:10.1038/s41467-024-46142-w · Cited by 124 · see citing works
“…automated gold label generation thus making the evaluation unreliable (e.g., if there is an increase in obese patients, the increased general negativity present in the clinical notes of obese patients 22,23 , could negatively impact the accuracy of gold labels created by neural language models).”
The Sociodemographic Biases in Machine Learning Algorithms: A Biomedical Informatics Perspective
Franklin, G., Stephens, R., Piracha, M., Tiosano, S., Lehouillier, F., Koppel, R., & Elkin, P. (2024) · Life · doi:10.3390/life14060652 · Cited by 76 · see citing works
Leveraging large language models to foster equity in healthcare
Rodriguez, J. A., Alsentzer, E., & Bates, D. W. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae055 · Cited by 32 · see citing works
Adam, H., Yang, M. Y., Cato, K., Baldini, I., Senteio, C., Celi, L. A., Zeng, J., Singh, M., & Ghassemi, M. (2022) · Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society · doi:10.1145/3514094.3534203 · Cited by 33 · see citing works
ChatGPT in Answering Queries Related to Lifestyle-Related Diseases and Disorders
Mondal, H., Dash, I., Mondal, S., & Behera, J. K. (2023) · Cureus · doi:10.7759/cureus.48296 · Cited by 32 · see citing works
- Authors
- Park, J., Saha, S., Chee, B., Taylor, J., & Beach, M. C.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Beach, Mary Catherine
- Venue
- JAMA Network Open
- Publisher
- American Medical Association (AMA)
- Published
- 2021-07-14
- Volume
- 4
- Issue
- 7
- Pages
- e2117052
- ISSN
- 2574-3805 (ISSN-L)
- PMC
- PMC8281008
- OpenAlex
- W3180412891
- Cited by
- 239
- References
- 36
- Citations by year
- 2026: 49 · 2025: 56 · 2024: 53 · 2023: 50 · 2022: 29 · 2021: 2
- FWCI
- 37.64
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JAMA Network Open (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Veterans Affairs (K24 DA037804)
- Robert Wood Johnson Foundation (75750)
- National Institute on Drug Abuse (DA037804, K24DA037804)
- Topics
- Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
- Health Sciences › Health Professions › Pharmacy › Obesity and Health Practices
- Health Sciences › Medicine › Psychiatry and Mental health › Empathy and Medical Education
- Keywords
- stigmatizing language, clinical documentation, racial stereotyping, health disparities, implicit bias, physician-patient relationship, electronic health records
- MeSH terms
- Academic Medical Centers, Adult, Attitude of Health Personnel, Emotions, Female, Humans, Internal Medicine, Language, Linguistics, Male, Middle Aged, Physician-Patient Relations, Physicians, Quality of Health Care, Stereotyping, Qualitative Research, 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
