Awareness of Racial and Ethnic Bias and Potential Solutions to Address Bias With Use of Health Care Algorithms.
JAMA Health Forum
; 4(6): e231197, 2023 06 02.
Article
em En
| MEDLINE
| ID: mdl-37266959
ABSTRACT
Importance Algorithms are commonly incorporated into health care decision tools used by health systems and payers and thus affect quality of care, access, and health outcomes. Some algorithms include a patient's race or ethnicity among their inputs and can lead clinicians and decision-makers to make choices that vary by race and potentially affect inequities. Objective:
To inform an evidence review on the use of race- and ethnicity-based algorithms in health care by gathering public and stakeholder perspectives about the repercussions of and efforts to address algorithm-related bias. Design, Setting, andParticipants:
Qualitative methods were used to analyze responses. Responses were initially open coded and then consolidated to create a codebook, with themes and subthemes identified and finalized by consensus. This qualitative study was conducted from May 4, 2021, through December 7, 2022. Forty-two organization representatives (eg, clinical professional societies, universities, government agencies, payers, and health technology organizations) and individuals responded to the request for information. Main Outcomes andMeasures:
Identification of algorithms with the potential for race- and ethnicity-based biases and qualitative themes.Results:
Forty-two respondents identified 18 algorithms currently in use with the potential for bias, including, for example, the Simple Calculated Osteoporosis Risk Estimation risk prediction tool and the risk calculator for vaginal birth after cesarean section. The 7 qualitative themes, with 31 subthemes, included the following (1) algorithms are in widespread use and have significant repercussions, (2) bias can result from algorithms whether or not they explicitly include race, (3) clinicians and patients are often unaware of the use of algorithms and potential for bias, (4) race is a social construct used as a proxy for clinical variables, (5) there is a lack of standardization in how race and social determinants of health are collected and defined, (6) bias can be introduced at all stages of algorithm development, and (7) algorithms should be discussed as part of shared decision-making between the patient and clinician. Conclusions and Relevance This qualitative study found that participants perceived widespread and increasing use of algorithms in health care and lack of oversight, potentially exacerbating racial and ethnic inequities. Increasing awareness for clinicians and patients and standardized, transparent approaches for algorithm development and implementation may be needed to address racial and ethnic biases related to algorithms.
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
1_ASSA2030
Base de dados:
MEDLINE
Assunto principal:
Cesárea
/
Atenção à Saúde
Tipo de estudo:
Prognostic_studies
/
Qualitative_research
Aspecto:
Determinantes_sociais_saude
/
Equity_inequality
Limite:
Female
/
Humans
/
Pregnancy
Idioma:
En
Revista:
JAMA Health Forum
Ano de publicação:
2023
Tipo de documento:
Article