Joseph M Geskey, Jodi Kodish-Wachs, Heather Blonsky, Samuel F Hohman, Steve Meurer
{"title":"National Documentation and Coding Practices of Noncompliance: The Importance of Social Determinants of Health and the Stigma of African-American Bias.","authors":"Joseph M Geskey, Jodi Kodish-Wachs, Heather Blonsky, Samuel F Hohman, Steve Meurer","doi":"10.1097/JMQ.0000000000000112","DOIUrl":null,"url":null,"abstract":"<p><p>Patient records serve many purposes, one of which includes monitoring the quality of care provided that they can be analyzed through coding and documentation. Z-codes can provide additional information beyond a specific clinical disorder that may still warrant treatment. Social Determinants of Health have specific Z-codes that may help clinicians address social factors that may contribute to patients' health care outcomes. However, there are Z-codes that specify patient noncompliance which has a pejorative connotation that may stigmatize patients and prevent clinicians from examining nonadherence from a social determinant of health perspective. A retrospective cross-sectional study was performed to examine the associations of patient and encounter characteristics with the coding of patient noncompliance. Included in the study were all patients >18 years of age who were admitted to hospitals participating in the Vizient Clinical Data Base (CDB) between January 1, 2019 and December 31, 2019. Almost 9 million US inpatients were included in the study. Of those, 6.3% had a noncompliance Z-code. Use of noncompliance Z-codes was associated with the following odds estimate ratio in decreasing order: the presence of a social determinant of health (odds ratio [OR], 4.817), African American race (OR, 2.010), Medicaid insurance (OR, 1.707), >3 chronic medical conditions (OR, 1.546), living in an economically distressed community (OR, 1.320), male gender (OR, 1.313), nonelective admission status (OR, 1.245), age <65 years (OR, 1.234). More than 1 in 15 patient hospitalizations had a noncompliance code. Factors associated with these codes are difficult, if not impossible, for patients to modify. Disproportionate representation of Africa-Americans among hospitalizations with noncompliance coding is concerning and urgently deserves further exploration to determine the degree to which it may be a product of clinician bias, especially if the term noncompliance prevents health care providers from looking into socioeconomic factors that may contribute to patient nonadherence.</p>","PeriodicalId":7539,"journal":{"name":"American Journal of Medical Quality","volume":"38 2","pages":"87-92"},"PeriodicalIF":1.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ea/20/jmq-38-87.PMC9973443.pdf","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Medical Quality","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/JMQ.0000000000000112","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 1
Abstract
Patient records serve many purposes, one of which includes monitoring the quality of care provided that they can be analyzed through coding and documentation. Z-codes can provide additional information beyond a specific clinical disorder that may still warrant treatment. Social Determinants of Health have specific Z-codes that may help clinicians address social factors that may contribute to patients' health care outcomes. However, there are Z-codes that specify patient noncompliance which has a pejorative connotation that may stigmatize patients and prevent clinicians from examining nonadherence from a social determinant of health perspective. A retrospective cross-sectional study was performed to examine the associations of patient and encounter characteristics with the coding of patient noncompliance. Included in the study were all patients >18 years of age who were admitted to hospitals participating in the Vizient Clinical Data Base (CDB) between January 1, 2019 and December 31, 2019. Almost 9 million US inpatients were included in the study. Of those, 6.3% had a noncompliance Z-code. Use of noncompliance Z-codes was associated with the following odds estimate ratio in decreasing order: the presence of a social determinant of health (odds ratio [OR], 4.817), African American race (OR, 2.010), Medicaid insurance (OR, 1.707), >3 chronic medical conditions (OR, 1.546), living in an economically distressed community (OR, 1.320), male gender (OR, 1.313), nonelective admission status (OR, 1.245), age <65 years (OR, 1.234). More than 1 in 15 patient hospitalizations had a noncompliance code. Factors associated with these codes are difficult, if not impossible, for patients to modify. Disproportionate representation of Africa-Americans among hospitalizations with noncompliance coding is concerning and urgently deserves further exploration to determine the degree to which it may be a product of clinician bias, especially if the term noncompliance prevents health care providers from looking into socioeconomic factors that may contribute to patient nonadherence.
期刊介绍:
The American Journal of Medical Quality (AJMQ) is focused on keeping readers informed of the resources, processes, and perspectives contributing to quality health care services. This peer-reviewed journal presents a forum for the exchange of ideas, strategies, and methods in improving the delivery and management of health care.