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1.
Semin Vasc Surg ; 37(2): 188-209, 2024 Jun.
Article in English | MEDLINE | ID: mdl-39151998

ABSTRACT

Intermittent claudication (IC) is a phenotype of peripheral artery disease that is characterized by pain in the lower extremity muscles during activity that is relieved by rest. Medical management, risk factor control, smoking cessation, and exercise therapy have historically been the mainstays of treatment for IC, but advances in endovascular technology have led to increasing use of peripheral vascular interventions in this patient population. There are meaningful differences in published society guidelines and appropriate use criteria relevant to the management of IC, especially regarding indications for peripheral vascular interventions. The current review aims to highlight similarities and differences between major society recommendations for the management of IC, and to discuss practice trends, disparities, and evidence gaps in the use of peripheral vascular interventions for IC in the context of existing guidelines.


Subject(s)
Intermittent Claudication , Practice Guidelines as Topic , Vascular Surgical Procedures , Humans , Endovascular Procedures/adverse effects , Endovascular Procedures/standards , Europe , Evidence-Based Medicine/standards , Healthcare Disparities/standards , Intermittent Claudication/physiopathology , Intermittent Claudication/therapy , Intermittent Claudication/diagnosis , Intermittent Claudication/surgery , Practice Guidelines as Topic/standards , Practice Patterns, Physicians'/standards , Risk Factors , Societies, Medical/standards , Treatment Outcome , United States , Vascular Surgical Procedures/standards , Vascular Surgical Procedures/adverse effects
2.
BMJ Open Qual ; 13(3)2024 Jul 24.
Article in English | MEDLINE | ID: mdl-39053915

ABSTRACT

BACKGROUND: Quality improvement (QI) is used by healthcare organisations internationally to improve care. Unless QI explicitly addresses equity, projects that aim to improve care may exacerbate health and care inequalities for disadvantaged groups. There are several QI frameworks used in primary care, but we do not know the extent to which they consider equity. This work aimed to investigate whether primary care QI frameworks consider equity. METHODS: We conducted a search of MEDLINE, EMBASE and key websites to compile a list of the QI frameworks used in primary care. This list was refined by an expert panel. Guidance documents for each of the QI frameworks were identified from national websites or QI organisations. We undertook a document analysis of the guidance using NVivo. RESULTS: We analysed 15 guidance documents. We identified the following themes: (1) there was a limited discussion of equity or targeted QI for disadvantaged groups in the documents, (2) there were indirect considerations of inequalities via patient involvement or targeting QI to patient demographics and (3) there was a greater focus on efficiency than equity in the documents. CONCLUSION: There is limited consideration of equity in QI frameworks used in primary care. Where equity is discussed, it is implicit and open to interpretation. This research demonstrates a need for frameworks to be revised with an explicit equity focus to ensure the distribution of benefits from QI is equitable.


Subject(s)
Primary Health Care , Quality Improvement , Humans , Primary Health Care/standards , Primary Health Care/statistics & numerical data , Health Equity/standards , Health Equity/statistics & numerical data , Healthcare Disparities/statistics & numerical data , Healthcare Disparities/standards
3.
Can J Physiol Pharmacol ; 102(9): 538-551, 2024 Sep 01.
Article in English | MEDLINE | ID: mdl-38917485

ABSTRACT

The cardiac rehabilitation quality indicators (CRQIs) developed by the Canadian Cardiovascular Society provide a means to standardize program assessment and identify sex-related inequities. No formal evaluation of the CRQIs has been conducted in Manitoba. An environmental scan for the CRQIs was performed using data in the electronic medical record at two cardiac rehabilitation (CR) sites in Winnipeg for 2016-2019 referrals. Of the 8116 referrals, 7758 (5491 males and 2267 females) had geographical access and were eligible for CR. The Manitoba Centre for Health Policy Data Quality Framework informed the data quality assessment. Thirteen CRQIs were available; four were considered high quality; nine demonstrated moderate to significant missing data. In addition to missing values, potential misclassification of risk (CR-4) and physiologically implausible and invalid dates were assessed and identified (CR-13 and CR-17). Each site had a physician medical director (CR-31) and a documented emergency response strategy (CR-32). Only high-quality data were evaluated for sex-related differences using chi-square and median tests. Women had lower enrollment (CR-3), and more women enrolled after the median of 41 days (CR-2b). Engagement with CR partners, including frontline staff, and utilizing strategies to assess and limit physiologically implausible values and dates will enhance data capture and quality.


Subject(s)
Cardiac Rehabilitation , Feasibility Studies , Quality Indicators, Health Care , Humans , Manitoba , Female , Cardiac Rehabilitation/standards , Cardiac Rehabilitation/statistics & numerical data , Male , Quality Indicators, Health Care/standards , Middle Aged , Aged , Sex Factors , Healthcare Disparities/standards , Healthcare Disparities/statistics & numerical data
4.
HPB (Oxford) ; 26(8): 1022-1032, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38796347

ABSTRACT

BACKGROUND: There is lack of data on the association between socioeconomic factors, guidelines compliance and clinical outcomes among patients with acute biliary pancreatitis (ABP). METHODS: Post-hoc analysis of the international MANCTRA-1 registry evaluating the impact of regional disparities as indicated by the Human Development Index (HDI), and guideline compliance on ABP clinical outcomes. Multivariable logistic regression models were employed to identify prognostic factors associated with mortality and readmission. RESULTS: Among 5313 individuals from 151 centres across 42 countries marked disparities in comorbid conditions, ABP severity, and medical procedure usage were observed. Patients from lower HDI countries had higher guideline non-compliance (p < 0.001) and mortality (5.0% vs. 3.2%, p = 0.019) in comparison with very high HDI countries. On adjusted analysis, ASA score (OR 1.810, p = 0.037), severe ABP (OR 2.735, p < 0.001), infected necrosis (OR 2.225, p = 0.006), organ failure (OR 4.511, p = 0.001) and guideline non-compliance (OR 2.554, p = 0.002 and OR 2.178, p = 0.015) were associated with increased mortality. HDI was a critical socio-economic factor affecting both mortality (OR 2.452, p = 0.007) and readmission (OR 1.542, p = 0.046). CONCLUSION: These data highlight the importance of collaborative research to characterise challenges and disparities in global ABP management. Less developed regions with lower HDI scores showed lower adherence to clinical guidelines and higher rates of mortality and recurrence.


Subject(s)
Guideline Adherence , Healthcare Disparities , Pancreatitis , Registries , Humans , Male , Female , Middle Aged , Pancreatitis/mortality , Pancreatitis/therapy , Healthcare Disparities/standards , Practice Guidelines as Topic , Adult , Aged , Risk Factors , Acute Disease , Patient Readmission , Socioeconomic Factors , Treatment Outcome , Severity of Illness Index
5.
JAMA ; 332(1): 72-74, 2024 07 02.
Article in English | MEDLINE | ID: mdl-38754010

ABSTRACT

This retrospective study uses electronic health record data to investigate the sex differences in guideline-based management outcomes between male and female patients with chronic kidney disease.


Subject(s)
Healthcare Disparities , Primary Health Care , Renal Insufficiency, Chronic , Aged , Female , Humans , Male , Disease Management , Primary Health Care/standards , Renal Insufficiency, Chronic/blood , Renal Insufficiency, Chronic/therapy , Sex Factors , United States , Cystatin C/blood , Practice Guidelines as Topic , Aged, 80 and over , Healthcare Disparities/standards
6.
BMJ Open Qual ; 13(2)2024 May 28.
Article in English | MEDLINE | ID: mdl-38806206

ABSTRACT

The clinical quality improvement initiatives, led by the organisation's Health Equity Working Group (HEWG), aim to support healthcare providers to provide equitable, quality hypertension care worldwide. After coordinating with the India team, we started monitoring the deidentified patient data collected through electronic health records between January and May 2021. After stratifying data by age, sex and residence location, the team found an average of 55.94% of our hypertensive patients control their blood pressure, with an inequity of 11.91% between male and female patients.The objective of this study was to assess the effectiveness of using clinical quality improvement to improve hypertension care in the limited-resourced, mobile healthcare setting in Mumbai slums. We used the model for improvement, developed by Associates in Process Improvement. After 9-month Plan-Do-Study-Act (PDSA) cycles, the average hypertensive patients with controlled blood pressure improved from 55.94% to 89.86% at the endpoint of the initiative. The gender gap reduced significantly from 11.91% to 2.19%. We continued to monitor the blood pressure and found that the average hypertensive patients with controlled blood pressure remained stable at 89.23% and the gender gap slightly increased to 3.14%. Hypertensive patients have 6.43 times higher chance of having controlled blood pressure compared with the preintervention after the 9-month intervention (p<0.001).This paper discusses the efforts to improve hypertension care and reduce health inequities in Mumbai's urban slums. We highlighted the methods used to identify and bridge health inequity gaps and the testing of PDSA cycles to improve care quality and reduce disparities. Our findings have shown that clinical quality improvement initiatives and the PDSA cycle can successfully improve health outcomes and decrease gender disparity in the limited-resource setting.


Subject(s)
Healthcare Disparities , Hypertension , Poverty Areas , Quality Improvement , Humans , India , Hypertension/therapy , Male , Female , Healthcare Disparities/statistics & numerical data , Healthcare Disparities/standards , Middle Aged , Adult , Aged , Urban Population/statistics & numerical data
9.
Circ Cardiovasc Qual Outcomes ; 17(5): e010791, 2024 May.
Article in English | MEDLINE | ID: mdl-38618717

ABSTRACT

The US health care industry has broadly adopted performance and quality measures that are extracted from electronic health records and connected to payment incentives that hope to improve declining life expectancy and health status and reduce costs. While the development of a quality measurement infrastructure based on electronic health record data was an important first step in addressing US health outcomes, these metrics, reflecting the average performance across diverse populations, do not adequately adjust for population demographic differences, social determinants of health, or ecosystem vulnerability. Like society as a whole, health care must confront the powerful impact that social determinants of health, race, ethnicity, and other demographic variations have on key health care performance indicators and quality metrics. Tools that are currently available to capture and report the health status of Americans lack the granularity, complexity, and standardization needed to improve health and address disparities at the local level. In this article, we discuss the current and future state of electronic clinical quality measures through a lens of equity.


Subject(s)
Electronic Health Records , Health Equity , Healthcare Disparities , Quality Indicators, Health Care , Social Determinants of Health , Humans , Quality Indicators, Health Care/standards , Healthcare Disparities/standards , Electronic Health Records/standards , Health Equity/standards , Quality Improvement/standards , Social Justice , Cultural Diversity , Health Status Disparities , Social Inclusion , United States , Diversity, Equity, Inclusion
10.
J Stroke Cerebrovasc Dis ; 33(6): 107639, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38369165

ABSTRACT

INTRODUCTION: Despite global progress in stroke care, challenges persist, especially in Low- and Middle-Income countries (LMIC). The Middle East and North Africa Stroke and Interventional Neurotherapies Organization (MENA-SINO) Stroke Program Accreditation Initiative aims to improve stroke care regionally. MATERIAL & METHOD: A 2022 survey assessed stroke unit readiness in the Middle East and North Africa (MENA) + region, revealing significant regional disparities in stroke care between high-income and low-income countries. Additionally, it demonstrated interest in the accreditation procedure and suggested that regional stroke program accreditation will improve stroke care for the involved centers. CONCLUSION: An accreditation program that is specifically tailored to the regional needs in the MENA + countries might be the solution. In this brief review, we will discuss potential challenges faced by such a program and we will put forward a well-defined 5-step accreditation process, beginning with a letter of intent, through processing the request and appointment of reviewers, the actual audit, the certification decisions, and culminating in granting a MIENA-SINO tier-specific certificate with recertification every 5 years.


Subject(s)
Accreditation , Stroke , Humans , Accreditation/standards , Stroke/therapy , Stroke/diagnosis , Middle East , Africa, Northern , Quality Improvement/standards , Quality Indicators, Health Care/standards , Healthcare Disparities/standards , Developing Countries , Health Care Surveys , Program Evaluation
11.
Anticancer Res ; 43(11): 5025-5030, 2023 Nov.
Article in English | MEDLINE | ID: mdl-37909973

ABSTRACT

BACKGROUND/AIM: The purpose of this study was to determine socioeconomic and demographic factors which may contribute to inequities in time to treat thyroid cancer. PATIENTS AND METHODS: We used data from the National Cancer Database, 2004-2019, to conduct an analysis of thyroid cancer patients. All (434,083) patients with thyroid cancer, including papillary (395,598), follicular (23,494), medullary (7,638), and anaplastic (7,353) types were included. We compared the wait time from diagnosis to first treatment, surgery, radiotherapy, and chemotherapy for patients based on age, race, sex, location, and socioeconomic status (SES). RESULTS: A total of 434,083 patients with thyroid cancer were included. Hispanic patients had significantly longer wait times to all treatments compared to non-Hispanic patients (first treatment 33.44 vs. 20.45 days, surgery 40.06 vs. 26.49 days, radiotherapy 114.68 vs. 96.42 days, chemotherapy 92.70 vs. 58.71 days). Uninsured patients, patients at academic facilities, and patients in metropolitan areas also had the longest wait times to treatment. CONCLUSION: This study identified multiple disparities related to SES and demographics that correspond to delays in time to treatment. It is crucial that this topic is investigated further to help mitigate these incongruities in thyroid cancer care in the future.


Subject(s)
Healthcare Disparities , Thyroid Neoplasms , Treatment Delay , Humans , Databases, Factual/statistics & numerical data , Hispanic or Latino/statistics & numerical data , Radiation Oncology , Thyroid Neoplasms/diagnosis , Thyroid Neoplasms/epidemiology , Thyroid Neoplasms/ethnology , Thyroid Neoplasms/therapy , Healthcare Disparities/ethnology , Healthcare Disparities/standards , Healthcare Disparities/statistics & numerical data , Time-to-Treatment/standards , Time-to-Treatment/statistics & numerical data , Treatment Delay/standards , Treatment Delay/statistics & numerical data
12.
BMJ ; 383: e074908, 2023 10 25.
Article in English | MEDLINE | ID: mdl-37879735

ABSTRACT

OBJECTIVE: To characterize racial differences in receipt of low value care (services that provide little to no benefit yet have potential for harm) among older Medicare beneficiaries overall and within health systems in the United States. DESIGN: Retrospective cohort study SETTING: 100% Medicare fee-for-service administrative data (2016-18). PARTICIPANTS: Black and White Medicare patients aged 65 or older as of 2016 and attributed to 595 health systems in the United States. MAIN OUTCOME MEASURES: Receipt of 40 low value services among Black and White patients, with and without adjustment for patient age, sex, and previous healthcare use. Additional models included health system fixed effects to assess racial differences within health systems and separately, racial composition of the health system's population to assess the relative contributions of individual patient race and health system racial composition to low value care receipt. RESULTS: The cohort included 9 833 304 patients (6.8% Black; 57.9% female). Of 40 low value services examined, Black patients had higher adjusted receipt of nine services and lower receipt of 20 services than White patients. Specifically, Black patients were more likely to receive low value acute diagnostic tests, including imaging for uncomplicated headache (6.9% v 3.2%) and head computed tomography scans for dizziness (3.1% v 1.9%). White patients had higher rates of low value screening tests and treatments, including preoperative laboratory tests (10.3% v 6.5%), prostate specific antigen tests (31.0% v 25.7%), and antibiotics for upper respiratory infections (36.6% v 32.7%; all P<0.001). Secondary analyses showed that these differences persisted within given health systems and were not explained by Black and White patients receiving care from different systems. CONCLUSIONS: Black patients were more likely to receive low value acute diagnostic tests and White patients were more likely to receive low value screening tests and treatments. Differences were generally small and were largely due to differential care within health systems. These patterns suggest potential individual, interpersonal, and structural factors that researchers, policy makers, and health system leaders might investigate and address to improve care quality and equity.


Subject(s)
Delivery of Health Care , Healthcare Disparities , Low-Value Care , Medicare , Aged , Female , Humans , Male , Black People , Healthcare Disparities/ethnology , Healthcare Disparities/standards , Healthcare Disparities/statistics & numerical data , Medicare/statistics & numerical data , Race Factors , Retrospective Studies , United States/epidemiology , Delivery of Health Care/ethnology , Delivery of Health Care/standards , White/statistics & numerical data , Black or African American/statistics & numerical data
13.
Am J Surg ; 226(4): 463-470, 2023 10.
Article in English | MEDLINE | ID: mdl-37230870

ABSTRACT

BACKGROUND: The availability and accuracy of data on a patient's race/ethnicity varies across databases. Discrepancies in data quality can negatively impact attempts to study health disparities. METHODS: We conducted a systematic review to organize information on the accuracy of race/ethnicity data stratified by database type and by specific race/ethnicity categories. RESULTS: The review included 43 studies. Disease registries showed consistently high levels of data completeness and accuracy. EHRs frequently showed incomplete and/or inaccurate data on the race/ethnicity of patients. Databases had high levels of accurate data for White and Black patients but relatively high levels of misclassification and incomplete data for Hispanic/Latinx patients. Asians, Pacific Islanders, and AI/ANs are the most misclassified. Systems-based interventions to increase self-reported data showed improvement in data quality. CONCLUSION: Data on race/ethnicity that is collected with the purpose of research and quality improvement appears most reliable. Data accuracy can vary by race/ethnicity status and better collection standards are needed.


Subject(s)
Data Management , Ethnicity , Racial Groups , Humans , Asian , Data Management/organization & administration , Data Management/standards , Data Management/statistics & numerical data , Ethnicity/statistics & numerical data , Healthcare Disparities/ethnology , Healthcare Disparities/standards , Healthcare Disparities/statistics & numerical data , Hispanic or Latino , Racial Groups/ethnology , Racial Groups/statistics & numerical data , White , Black or African American , Pacific Island People , American Indian or Alaska Native
14.
Int J Equity Health ; 22(1): 68, 2023 04 14.
Article in English | MEDLINE | ID: mdl-37060065

ABSTRACT

BACKGROUND: Colorectal cancer is a leading cause of morbidity and mortality across U.S. racial/ethnic groups. Existing studies often focus on a particular race/ethnicity or single domain within the care continuum. Granular exploration of disparities among different racial/ethnic groups across the entire colon cancer care continuum is needed. We aimed to characterize differences in colon cancer outcomes by race/ethnicity across each stage of the care continuum. METHODS: We used the 2010-2017 National Cancer Database to examine differences in outcomes by race/ethnicity across six domains: clinical stage at presentation; timing of surgery; access to minimally invasive surgery; post-operative outcomes; utilization of chemotherapy; and cumulative incidence of death. Analysis was via multivariable logistic or median regression, with select demographics, hospital factors, and treatment details as covariates. RESULTS: 326,003 patients (49.6% female, 24.0% non-White, including 12.7% Black, 6.1% Hispanic/Spanish, 1.3% East Asian, 0.9% Southeast Asian, 0.4% South Asian, 0.3% AIAE, and 0.2% NHOPI) met inclusion criteria. Relative to non-Hispanic White patients: Southeast Asian (OR 1.39, p < 0.01), Hispanic/Spanish (OR 1.11 p < 0.01), and Black (OR 1.09, p < 0.01) patients had increased odds of presenting with advanced clinical stage. Southeast Asian (OR 1.37, p < 0.01), East Asian (OR 1.27, p = 0.05), Hispanic/Spanish (OR 1.05 p = 0.02), and Black (OR 1.05, p < 0.01) patients had increased odds of advanced pathologic stage. Black patients had increased odds of experiencing a surgical delay (OR 1.33, p < 0.01); receiving non-robotic surgery (OR 1.12, p < 0.01); having post-surgical complications (OR 1.29, p < 0.01); initiating chemotherapy more than 90 days post-surgery (OR 1.24, p < 0.01); and omitting chemotherapy altogether (OR 1.12, p = 0.05). Black patients had significantly higher cumulative incidence of death at every pathologic stage relative to non-Hispanic White patients when adjusting for non-modifiable patient factors (p < 0.05, all stages), but these differences were no longer statistically significant when also adjusting for modifiable factors such as insurance status and income. CONCLUSIONS: Non-White patients disproportionately experience advanced stage at presentation. Disparities for Black patients are seen across the entire colon cancer care continuum. Targeted interventions may be appropriate for some groups; however, major system-level transformation is needed to address disparities experienced by Black patients.


Subject(s)
Colonic Neoplasms , Ethnicity , Health Services Accessibility , Healthcare Disparities , Racial Groups , Female , Humans , Male , Black or African American/statistics & numerical data , Colonic Neoplasms/epidemiology , Colonic Neoplasms/ethnology , Colonic Neoplasms/mortality , Colonic Neoplasms/therapy , Ethnicity/statistics & numerical data , Healthcare Disparities/ethnology , Healthcare Disparities/standards , Healthcare Disparities/statistics & numerical data , Hispanic or Latino/statistics & numerical data , United States/epidemiology , Race Factors/statistics & numerical data , Treatment Outcome , Health Services Accessibility/statistics & numerical data , East Asian People/statistics & numerical data , Southeast Asian People/statistics & numerical data , South Asian People/statistics & numerical data , Native Hawaiian or Other Pacific Islander/statistics & numerical data , Asian/statistics & numerical data , Databases, Factual/statistics & numerical data , American Indian or Alaska Native/statistics & numerical data , Racial Groups/statistics & numerical data
15.
Clin Gastroenterol Hepatol ; 21(8): 1992-2000, 2023 07.
Article in English | MEDLINE | ID: mdl-37061105

ABSTRACT

There are well-described racial and ethnic disparities in the burden of chronic liver diseases. Hispanic persons are at highest risk for developing nonalcoholic fatty liver disease, the fastest growing cause of liver disease. Hepatitis B disproportionately affects persons of Asian or African descent. The highest rates of hepatitis C occur in American Indian and Alaskan Native populations. In addition to disparities in disease burden, there are also marked racial and ethnic disparities in access to treatments, including liver transplantation. Disparities also exist by gender and geography, especially in alcohol-related liver disease. To achieve health equity, we must address the root causes that drive these inequities. Understanding the role that social determinants of health play in the disparate health outcomes that are currently observed is critically important. We must forge and/or strengthen collaborations between patients, community members, other key stakeholders, health care providers, health care institutions, professional societies, and legislative bodies. Herein, we provide a high-level review of current disparities in chronic liver disease and describe actionable strategies that have potential to bridge gaps, improve quality, and promote equity in liver care.


Subject(s)
Health Equity , Healthcare Disparities , Liver Diseases , Non-alcoholic Fatty Liver Disease , Humans , Health Equity/standards , Healthcare Disparities/ethnology , Healthcare Disparities/standards , Hispanic or Latino , Racial Groups , United States , Liver Diseases/ethnology , Chronic Disease/ethnology , Asian , Black People , American Indian or Alaska Native , Cost of Illness , Health Services Accessibility
16.
BMC Ophthalmol ; 23(1): 82, 2023 Mar 02.
Article in English | MEDLINE | ID: mdl-36864395

ABSTRACT

BACKGROUND: Communication barriers are a major cause of health disparities for patients with limited English proficiency (LEP). Medical interpreters play an important role in bridging this gap, however the impact of interpreters on outpatient eye center visits has not been studied. We aimed to evaluate the differences in length of eyecare visits between LEP patients self-identifying as requiring a medical interpreter and English speakers at a tertiary, safety-net hospital in the United States. METHODS: A retrospective review of patient encounter metrics collected by our electronic medical record was conducted for all visits between January 1, 2016 and March 13, 2020. Patient demographics, primary language spoken, self-identified need for interpreter and encounter characteristics including new patient status, patient time waiting for providers and time in room were collected. We compared visit times by patient's self-identification of need for an interpreter, with our main outcomes being time spent with ophthalmic technician, time spent with eyecare provider, and time waiting for eyecare provider. Interpreter services at our hospital are typically remote (via phone or video). RESULTS: A total of 87,157 patient encounters were analyzed, of which 26,443 (30.3%) involved LEP patients identifying as requiring an interpreter. After adjusting for patient age at visit, new patient status, physician status (attending or resident), and repeated patient visits, there was no difference in the length of time spent with technician or physician, or time spent waiting for physician, between English speakers and patients identifying as needing an interpreter. Patients who self-identified as requiring an interpreter were more likely to have an after-visit summary printed for them, and were also more likely to keep their appointment once it was made when compared to English speakers. CONCLUSIONS: Encounters with LEP patients who identify as requiring an interpreter were expected to be longer than those who did not indicate need for an interpreter, however we found that there was no difference in the length of time spent with technician or physician. This suggests providers may adjust their communication strategy during encounters with LEP patients identifying as needing an interpreter. Eyecare providers must be aware of this to prevent negative impacts on patient care. Equally important, healthcare systems should consider ways to prevent unreimbursed extra time from being a financial disincentive for seeing patients who request interpreter services.


Subject(s)
Health Status Disparities , Healthcare Disparities , Language , Limited English Proficiency , Ophthalmology , Outpatient Clinics, Hospital , Humans , Healthcare Disparities/standards , Healthcare Disparities/statistics & numerical data , Ambulatory Care/standards , Ambulatory Care/statistics & numerical data , Safety-net Providers/standards , Safety-net Providers/statistics & numerical data , Outpatient Clinics, Hospital/standards , Outpatient Clinics, Hospital/statistics & numerical data , United States/epidemiology , Ophthalmology/standards , Ophthalmology/statistics & numerical data , Retrospective Studies
17.
JAMA ; 329(4): 306-317, 2023 01 24.
Article in English | MEDLINE | ID: mdl-36692561

ABSTRACT

Importance: Stroke is the fifth-highest cause of death in the US and a leading cause of serious long-term disability with particularly high risk in Black individuals. Quality risk prediction algorithms, free of bias, are key for comprehensive prevention strategies. Objective: To compare the performance of stroke-specific algorithms with pooled cohort equations developed for atherosclerotic cardiovascular disease for the prediction of new-onset stroke across different subgroups (race, sex, and age) and to determine the added value of novel machine learning techniques. Design, Setting, and Participants: Retrospective cohort study on combined and harmonized data from Black and White participants of the Framingham Offspring, Atherosclerosis Risk in Communities (ARIC), Multi-Ethnic Study for Atherosclerosis (MESA), and Reasons for Geographical and Racial Differences in Stroke (REGARDS) studies (1983-2019) conducted in the US. The 62 482 participants included at baseline were at least 45 years of age and free of stroke or transient ischemic attack. Exposures: Published stroke-specific algorithms from Framingham and REGARDS (based on self-reported risk factors) as well as pooled cohort equations for atherosclerotic cardiovascular disease plus 2 newly developed machine learning algorithms. Main Outcomes and Measures: Models were designed to estimate the 10-year risk of new-onset stroke (ischemic or hemorrhagic). Discrimination concordance index (C index) and calibration ratios of expected vs observed event rates were assessed at 10 years. Analyses were conducted by race, sex, and age groups. Results: The combined study sample included 62 482 participants (median age, 61 years, 54% women, and 29% Black individuals). Discrimination C indexes were not significantly different for the 2 stroke-specific models (Framingham stroke, 0.72; 95% CI, 0.72-073; REGARDS self-report, 0.73; 95% CI, 0.72-0.74) vs the pooled cohort equations (0.72; 95% CI, 0.71-0.73): differences 0.01 or less (P values >.05) in the combined sample. Significant differences in discrimination were observed by race: the C indexes were 0.76 for all 3 models in White vs 0.69 in Black women (all P values <.001) and between 0.71 and 0.72 in White men and between 0.64 and 0.66 in Black men (all P values ≤.001). When stratified by age, model discrimination was better for younger (<60 years) vs older (≥60 years) adults for both Black and White individuals. The ratios of observed to expected 10-year stroke rates were closest to 1 for the REGARDS self-report model (1.05; 95% CI, 1.00-1.09) and indicated risk overestimation for Framingham stroke (0.86; 95% CI, 0.82-0.89) and pooled cohort equations (0.74; 95% CI, 0.71-0.77). Performance did not significantly improve when novel machine learning algorithms were applied. Conclusions and Relevance: In this analysis of Black and White individuals without stroke or transient ischemic attack among 4 US cohorts, existing stroke-specific risk prediction models and novel machine learning techniques did not significantly improve discriminative accuracy for new-onset stroke compared with the pooled cohort equations, and the REGARDS self-report model had the best calibration. All algorithms exhibited worse discrimination in Black individuals than in White individuals, indicating the need to expand the pool of risk factors and improve modeling techniques to address observed racial disparities and improve model performance.


Subject(s)
Black People , Healthcare Disparities , Prejudice , Risk Assessment , Stroke , White People , Female , Humans , Male , Middle Aged , Atherosclerosis/epidemiology , Cardiovascular Diseases/epidemiology , Ischemic Attack, Transient/epidemiology , Retrospective Studies , Stroke/diagnosis , Stroke/epidemiology , Stroke/ethnology , Risk Assessment/standards , Reproducibility of Results , Sex Factors , Age Factors , Race Factors/statistics & numerical data , Black People/statistics & numerical data , White People/statistics & numerical data , United States/epidemiology , Machine Learning/standards , Bias , Prejudice/prevention & control , Healthcare Disparities/ethnology , Healthcare Disparities/standards , Healthcare Disparities/statistics & numerical data , Computer Simulation/standards , Computer Simulation/statistics & numerical data
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