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      Physician Use of Stigmatizing Language in Patient Medical Records

      1 , 2 , , MD, MPH 1 , 2 , 3 , , PhD 4 , , RN, PhD 5 , , MD, MPH , 2 , 6 , 7

      JAMA Network Open

      American Medical Association

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          Key Points


          What types of stigmatizing language are written by physicians about patients in their medical records?


          This qualitative study of 600 encounter notes from 138 physicians found 6 ways that physicians express positive feelings toward patients in medical records, including compliments, approval, and personalization. This study also found 5 ways that physicians express negative feelings toward patients, including disapproval, discrediting, and stereotyping.


          These findings suggest that physicians should increase their awareness of stigmatizing language in patient records to ensure that their notes are informative and respectful.


          This qualitative study examines both negative and positive attitudes expressed by physicians about patients in electronic medical records.



          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.


          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.


          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.

          Related collections

          Most cited references 36

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          Three approaches to qualitative content analysis.

          Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
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            Low health literacy and health outcomes: an updated systematic review.

            Approximately 80 million Americans have limited health literacy, which puts them at greater risk for poorer access to care and poorer health outcomes. To update a 2004 systematic review and determine whether low health literacy is related to poorer use of health care, outcomes, costs, and disparities in health outcomes among persons of all ages. English-language articles identified through MEDLINE, CINAHL, PsycINFO, ERIC, and Cochrane Library databases and hand-searching (search dates for articles on health literacy, 2003 to 22 February 2011; for articles on numeracy, 1966 to 22 February 2011). Two reviewers independently selected studies that compared outcomes by differences in directly measured health literacy or numeracy levels. One reviewer abstracted article information into evidence tables; a second reviewer checked information for accuracy. Two reviewers independently rated study quality by using predefined criteria, and the investigative team jointly graded the overall strength of evidence. 96 relevant good- or fair-quality studies in 111 articles were identified: 98 articles on health literacy, 22 on numeracy, and 9 on both. Low health literacy was consistently associated with more hospitalizations; greater use of emergency care; lower receipt of mammography screening and influenza vaccine; poorer ability to demonstrate taking medications appropriately; poorer ability to interpret labels and health messages; and, among elderly persons, poorer overall health status and higher mortality rates. Poor health literacy partially explains racial disparities in some outcomes. Reviewers could not reach firm conclusions about the relationship between numeracy and health outcomes because of few studies or inconsistent results among studies. Searches were limited to articles published in English. No Medical Subject Heading terms exist for identifying relevant studies. No evidence concerning oral health literacy (speaking and listening skills) and outcomes was found. Low health literacy is associated with poorer health outcomes and poorer use of health care services. Agency for Healthcare Research and Quality.
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              Physicians and implicit bias: how doctors may unwittingly perpetuate health care disparities.

              Although the medical profession strives for equal treatment of all patients, disparities in health care are prevalent. Cultural stereotypes may not be consciously endorsed, but their mere existence influences how information about an individual is processed and leads to unintended biases in decision-making, so called "implicit bias". All of society is susceptible to these biases, including physicians. Research suggests that implicit bias may contribute to health care disparities by shaping physician behavior and producing differences in medical treatment along the lines of race, ethnicity, gender or other characteristics. We review the origins of implicit bias, cite research documenting the existence of implicit bias among physicians, and describe studies that demonstrate implicit bias in clinical decision-making. We then present the bias-reducing strategies of consciously taking patients' perspectives and intentionally focusing on individual patients' information apart from their social group. We conclude that the contribution of implicit bias to health care disparities could decrease if all physicians acknowledged their susceptibility to it, and deliberately practiced perspective-taking and individuation when providing patient care. We further conclude that increasing the number of African American/Black physicians could reduce the impact of implicit bias on health care disparities because they exhibit significantly less implicit race bias.

                Author and article information

                JAMA Netw Open
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                14 July 2021
                July 2021
                14 July 2021
                : 4
                : 7
                [1 ]Oregon Health and Science University, Portland
                [2 ]Division of General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
                [3 ]Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland, Oregon
                [4 ]Applied Physics Laboratory, Johns Hopkins University, Baltimore, Maryland
                [5 ]Johns Hopkins School of Nursing, Johns Hopkins University, Baltimore, Maryland
                [6 ]Berman Institute of Bioethics, Johns Hopkins University, Baltimore, Maryland
                [7 ]Center for Health Equity, Johns Hopkins University, Baltimore, Maryland
                Author notes
                Article Information
                Accepted for Publication:
                Open Access: CC-BY License JAMA Network Open
                Corresponding Author: Mary Catherine Beach, MD, MPH, Johns Hopkins University, 2024 E Monument St, Baltimore, MD, 21287 ( mcbeach@ 123456jhmi.edu ).
                Author Contributions :
                Concept and design:
                Acquisition, analysis, or interpretation of data:
                Drafting of the manuscript:
                Critical revision of the manuscript for important intellectual content:
                Statistical analysis:
                Obtained funding:
                Administrative, technical, or material support:
                Conflict of Interest Disclosures:
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                Copyright 2021 Park J et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

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