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  1. Article ; Online: How Should Clinicians' Performance Be Assessed When Health Care Organizations Implement Behavioral Architecture That Generates Negative Consequences?

    Richardson, Safiya

    AMA journal of ethics

    2020  Volume 22, Issue 9, Page(s) E760–766

    Abstract: Behavioral interventions have been shown to have powerful effects on human behavior both outside of and within the context of health care. As organizations increasingly adopt behavioral architecture, care must be taken to consider its potential negative ... ...

    Abstract Behavioral interventions have been shown to have powerful effects on human behavior both outside of and within the context of health care. As organizations increasingly adopt behavioral architecture, care must be taken to consider its potential negative consequences. An evidenced-based approach is best, whereby interventions that might have a significant deleterious effect on patients' health outcomes are first tested and rigorously evaluated before being systematically rolled out. In the case of clinical decision support, brief and thorough instructions should be provided for use. Physician performance when using these systems is best measured relatively, in the context of peers with similar training. Responsibility for errors must be shared with clinical team members and system designers.
    MeSH term(s) Decision Support Systems, Clinical ; Delivery of Health Care ; Humans ; Physicians
    Language English
    Publishing date 2020-09-01
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ISSN 2376-6980
    ISSN (online) 2376-6980
    DOI 10.1001/amajethics.2020.760
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  2. Article ; Online: Centering health equity in large language model deployment.

    Singh, Nina / Lawrence, Katharine / Richardson, Safiya / Mann, Devin M

    PLOS digital health

    2023  Volume 2, Issue 10, Page(s) e0000367

    Language English
    Publishing date 2023-10-24
    Publishing country United States
    Document type Journal Article
    ISSN 2767-3170
    ISSN (online) 2767-3170
    DOI 10.1371/journal.pdig.0000367
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  3. Article ; Online: Centering health equity in large language model deployment.

    Nina Singh / Katharine Lawrence / Safiya Richardson / Devin M Mann

    PLOS Digital Health, Vol 2, Iss 10, p e

    2023  Volume 0000367

    Keywords Computer applications to medicine. Medical informatics ; R858-859.7
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: A framework for digital health equity.

    Richardson, Safiya / Lawrence, Katharine / Schoenthaler, Antoinette M / Mann, Devin

    NPJ digital medicine

    2022  Volume 5, Issue 1, Page(s) 119

    Abstract: We present a comprehensive Framework for Digital Health Equity, detailing key digital determinants of health (DDoH), to support the work of digital health tool creators in industry, health systems operations, and academia. The rapid digitization of ... ...

    Abstract We present a comprehensive Framework for Digital Health Equity, detailing key digital determinants of health (DDoH), to support the work of digital health tool creators in industry, health systems operations, and academia. The rapid digitization of healthcare may widen health disparities if solutions are not developed with these determinants in mind. Our framework builds on the leading health disparities framework, incorporating a digital environment domain. We examine DDoHs at the individual, interpersonal, community, and societal levels, discuss the importance of a root cause, multi-level approach, and offer a pragmatic case study that applies our framework.
    Language English
    Publishing date 2022-08-18
    Publishing country England
    Document type Journal Article ; Review
    ISSN 2398-6352
    ISSN (online) 2398-6352
    DOI 10.1038/s41746-022-00663-0
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  5. Article ; Online: A framework for digital health equity

    Safiya Richardson / Katharine Lawrence / Antoinette M. Schoenthaler / Devin Mann

    npj Digital Medicine, Vol 5, Iss 1, Pp 1-

    2022  Volume 6

    Abstract: Abstract We present a comprehensive Framework for Digital Health Equity, detailing key digital determinants of health (DDoH), to support the work of digital health tool creators in industry, health systems operations, and academia. The rapid digitization ...

    Abstract Abstract We present a comprehensive Framework for Digital Health Equity, detailing key digital determinants of health (DDoH), to support the work of digital health tool creators in industry, health systems operations, and academia. The rapid digitization of healthcare may widen health disparities if solutions are not developed with these determinants in mind. Our framework builds on the leading health disparities framework, incorporating a digital environment domain. We examine DDoHs at the individual, interpersonal, community, and societal levels, discuss the importance of a root cause, multi-level approach, and offer a pragmatic case study that applies our framework.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7
    Language English
    Publishing date 2022-08-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: The Paradox of STEMI Regionalization: Widened Disparities Despite Some Benefits.

    Roswell, Robert O / Brown, Rachel-Maria / Richardson, Safiya

    JAMA network open

    2020  Volume 3, Issue 11, Page(s) e2027283

    MeSH term(s) Adult ; Humans ; Minority Groups ; Myocardial Infarction/diagnosis ; ST Elevation Myocardial Infarction/diagnosis
    Language English
    Publishing date 2020-11-02
    Publishing country United States
    Document type Journal Article ; Comment
    ISSN 2574-3805
    ISSN (online) 2574-3805
    DOI 10.1001/jamanetworkopen.2020.27283
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  7. Article ; Online: Considerations for using predictive models that include race as an input variable: The case study of lung cancer screening.

    Stevens, Elizabeth R / Caverly, Tanner / Butler, Jorie M / Kukhareva, Polina / Richardson, Safiya / Mann, Devin M / Kawamoto, Kensaku

    Journal of biomedical informatics

    2023  Volume 147, Page(s) 104525

    Abstract: Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from ... ...

    Abstract Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. Thus, there is a need for a pragmatic framework to help model users think through how to include race in their chosen model so as to avoid inadvertently exacerbating disparities. In this paper, we use the case study of lung cancer screening to propose a simple framework to guide how model users can approach the use (or non-use) of race inputs in the predictive models they are tasked with leveraging in electronic health records and clinical workflows.
    MeSH term(s) Humans ; United States ; Early Detection of Cancer ; Lung Neoplasms/diagnosis ; Electronic Health Records
    Language English
    Publishing date 2023-10-14
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, P.H.S. ; Research Support, N.I.H., Extramural
    ZDB-ID 2057141-0
    ISSN 1532-0480 ; 1532-0464
    ISSN (online) 1532-0480
    ISSN 1532-0464
    DOI 10.1016/j.jbi.2023.104525
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  8. Article ; Online: Automated Pulmonary Embolism Risk Assessment Using the Wells Criteria: Validation Study.

    Zhang, Nasen Jonathan / Rameau, Philippe / Julemis, Marsophia / Liu, Yan / Solomon, Jeffrey / Khan, Sundas / McGinn, Thomas / Richardson, Safiya

    JMIR formative research

    2022  Volume 6, Issue 2, Page(s) e32230

    Abstract: Background: Computed tomography pulmonary angiography (CTPA) is frequently used in the emergency department (ED) for the diagnosis of pulmonary embolism (PE), while posing risk for contrast-induced nephropathy and radiation-induced malignancy.: ... ...

    Abstract Background: Computed tomography pulmonary angiography (CTPA) is frequently used in the emergency department (ED) for the diagnosis of pulmonary embolism (PE), while posing risk for contrast-induced nephropathy and radiation-induced malignancy.
    Objective: We aimed to create an automated process to calculate the Wells score for pulmonary embolism for patients in the ED, which could potentially reduce unnecessary CTPA testing.
    Methods: We designed an automated process using electronic health records data elements, including using a combinatorial keyword search method to query free-text fields, and calculated automated Wells scores for a sample of all adult ED encounters that resulted in a CTPA study for PE at 2 tertiary care hospitals in New York, over a 2-month period. To validate the automated process, the scores were compared to those derived from a 2-clinician chart review.
    Results: A total of 202 ED encounters resulted in a completed CTPA to form the retrospective study cohort. Patients classified as "PE likely" by the automated process (126/202, 62%) had a PE prevalence of 15.9%, whereas those classified as "PE unlikely" (76/202, 38%; Wells score >4) had a PE prevalence of 7.9%. With respect to classification of the patient as "PE likely," the automated process achieved an accuracy of 92.1% when compared with the chart review, with sensitivity, specificity, positive predictive value, and negative predictive value of 93%, 90.5%, 94.4%, and 88.2%, respectively.
    Conclusions: This was a successful development and validation of an automated process using electronic health records data elements, including free-text fields, to classify risk for PE in ED visits.
    Language English
    Publishing date 2022-02-28
    Publishing country Canada
    Document type Journal Article
    ISSN 2561-326X
    ISSN (online) 2561-326X
    DOI 10.2196/32230
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  9. Article ; Online: Association of race/ethnicity with mortality in patients hospitalized with COVID-19.

    Richardson, Safiya / Martinez, Johanna / Hirsch, Jamie S / Cerise, Jane / Lesser, Martin / Roswell, Robert O / Davidson, Karina W

    PloS one

    2022  Volume 17, Issue 8, Page(s) e0267505

    Abstract: Objective: To evaluate racial and ethnic differences in mortality among patients hospitalized with coronavirus disease 2019 (COVID-19) after adjusting for baseline characteristics and comorbidities.: Methods: This retrospective cohort study at 13 ... ...

    Abstract Objective: To evaluate racial and ethnic differences in mortality among patients hospitalized with coronavirus disease 2019 (COVID-19) after adjusting for baseline characteristics and comorbidities.
    Methods: This retrospective cohort study at 13 acute care facilities in the New York City metropolitan area included sequentially hospitalized patients between March 1, 2020, and April 27, 2020. Last day of follow up was July 31, 2020. Patient demographic information, including race/ethnicity and comorbidities, were collected. The primary outcome was in-hospital mortality.
    Results: A total of 10 869 patients were included in the study (median age, 65 years [interquartile range (IQR) 54-77; range, 18-107 years]; 40.5% female). In adjusted time-to-event analysis, increased age, male sex, insurance type (Medicare and Self-Pay), unknown smoking status, and a higher score on the Charlson Comorbidity Index were significantly associated with higher in-hospital mortality. Adjusted risk of hospital mortality for Black, Asian, Hispanic, multiracial/other, and unknown race/ethnicity patients were similar to risk for White patients.
    Conclusions: In a large diverse cohort of patients hospitalized with COVID-19, patients from racial/ethnic minorities experienced similar mortality risk as White patients.
    MeSH term(s) Aged ; COVID-19 ; Ethnicity ; Female ; Hospital Mortality/ethnology ; Hospitalization ; Humans ; Male ; Medicare ; Middle Aged ; Racial Groups ; Retrospective Studies ; SARS-CoV-2 ; United States ; White People
    Language English
    Publishing date 2022-08-04
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0267505
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  10. Article ; Online: Comparison of Chest Radiograph Impressions for Diagnosing Pneumonia: Accounting for Categories of Language Certainty.

    Makhnevich, Alexander / Sinvani, Liron / Feldhamer, Kenneth H / Zhang, Meng / Richardson, Safiya / McGinn, Thomas G / Cohen, Stuart L

    Journal of the American College of Radiology : JACR

    2022  Volume 19, Issue 10, Page(s) 1130–1137

    Abstract: Objectives: Uncertain language in chest radiograph (CXR) reports for the diagnosis of pneumonia is prevalent. The purpose of this study is to validate an a priori stratification of CXR results for diagnosing pneumonia based on language of certainty.: ... ...

    Abstract Objectives: Uncertain language in chest radiograph (CXR) reports for the diagnosis of pneumonia is prevalent. The purpose of this study is to validate an a priori stratification of CXR results for diagnosing pneumonia based on language of certainty.
    Design: Retrospective chart review.
    Setting and participants: CXR reports of 2,411 patient visits ≥ 18 years, admitted to medicine, who received a CXR and noncontrast chest CT within 48 hours of emergency department registration at two large academic hospitals (tertiary and quaternary care) were reviewed.
    Methods: The CXR and CT report impressions were categorized as negative, uncertain, or positive. Uncertain CXRs were further stratified into four categories based on language modifiers for the degree of pneumonia certainty. Comparison of CXR and CT results were determined using χ
    Results: CXR reports for the diagnosis of pneumonia revealed the following distribution: 61% negative, 32% uncertain, and 7% positive; CT reports were 55% negative, 22% uncertain, and 23% positive for the diagnosis of pneumonia. There were significant differences between CXR categories compared with CT categories for diagnosis of pneumonia (P < .001). Negative CXR results were not significantly different than the uncertain category with the most uncertain language (P = .030) but were significantly different from all other uncertain categories and positive CXR results (each P < .001). Positive CXR results were not significantly different than the least uncertain category (most certain language) (P = .130) but were significantly different from all other categories (each P < .001).
    Conclusions and implications: Language used in CXR reports to diagnose pneumonia exists in categories of varying certainty and should be considered when evaluating patients for pneumonia.
    MeSH term(s) Emergency Service, Hospital ; Humans ; Pneumonia/diagnostic imaging ; Radiography ; Radiography, Thoracic/methods ; Retrospective Studies ; Tomography, X-Ray Computed
    Language English
    Publishing date 2022-07-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2274861-1
    ISSN 1558-349X ; 1546-1440
    ISSN (online) 1558-349X
    ISSN 1546-1440
    DOI 10.1016/j.jacr.2022.05.020
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