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Abstract

Missed appointments have been linked to adverse outcomes known to affect racial/ethnic minorities. However, the association of missed appointments with race/ethnicity has not been determined. We sought to determine the relationships between race/ethnicity and missed appointments by performing a cross-sectional study of 161 350 patients in a safety net health system. Several race/ethnicity categories were significantly associated with missed appointment rates, including Hispanic/Latino patients, American Indian/Alaskan Native patients, and Black/African American patients, as compared with White non-Hispanic patients. Other significant predictors included Mexico as country of origin, medical complexity, and major mental illness. We recommend additional research to determine which interventions best reduce missed appointments for minority populations in order to improve the care of vulnerable patients.

Keywords

primary care missed appointments no shows health disparities racial disparities ethnic disparities

Introduction

Missed appointments (“no shows”) are prevalent and problematic. At a large urban center in Baltimore, 20% of patients missed more than 30% of their appointments.¹ Missed appointments are associated with lower socioeconomic status, medical complexity, mental illness, and appointment wait times.² However, the association of missed appointments with racial/ethnic minorities has not been determined. Missed appointments have been linked to adverse outcomes known to affect racial/ethnic minorities, including lower care quality and excess health care utilization.^1-2 Therefore, we sought to determine the relationships between race/ethnicity and missed appointments among a patient population visiting an urban safety net health system (2011, study period).

Methods

To assess predictors of missed appointments, we performed a cross-sectional study of 161 350 patients in a safety net health system. Our analysis was informed by a theoretical model that links health disparities to health system environments, medical complexity, and barriers to care.³ Data were drawn from 2011 electronic medical records (EPIC Clarity). Measures included missed appointment (yes/no), age, sex, race/ethnicity, country of origin, language, medical complexity (Medicare hierarchical condition score and categories), presence of major mental illness (eg, major depression, bipolar disorder, schizophrenia, substance use disorder), primary care provider assignment, payer (public, private, other), and utilization (eg, counts/year of emergency room visits, office visits, and inpatient admissions). Multivariate logistic regressions were conducted using missed appointments as the dependent variable (100 413 missed appointments vs 436 580 completed visits).

Results

In 2011, 161 350 patients were seen for 436 580 completed outpatient visits. The average missed appointment rate for office visits was 23% (range: 0% to 58%) across 44 primary and specialty care clinics. The mean patient age was 37 years and 62% of patients were non-White. One-third of patients were born outside the United States and 23% were non-English speaking. Major mental illness, including substance use disorder, was diagnosed in 9.4% of patients. In bivariate analyses, missed appointments were associated with specialty appointments versus primary care (27.4% vs 19.7%, P < .0001) and with appointments scheduled >28 days out versus earlier dates (P < .0001 for trend).

In multivariate analyses, several race/ethnicity categories were significantly associated with missed appointment rates (Table 1). Odds of missed appointments were 1.8 times higher for Black/African Americans (odds ratio [OR] 1.82, 95% confidence interval [CI] 1.62-2.04) and 2 times higher for American Indian/Alaskan Natives (OR 2.29, 95% CI 1.84-2.85) and Hispanic/Latinos (OR 2.02, 95% CI 1.72-2.38) as compared with White non-Hispanic patients. Other significant predictors were Mexico as country of origin (OR 1.25, 95% CI 1.06-1.47), medical complexity (OR 1.41, 95% CI 1.30-1.53), and major mental illness (OR 1.42, 95% CI 1.24-1.63). Emergency room visits were associated with higher odds of missed appointments (OR 1.04, 95% CI 1.02-1.06).

Table 1.

Predictors of Missed Appointments for 161 350 Patients in an Urban Safety Net Hospital (2011).^a

Predictors	Outcome: Missing Appointments
Predictors	Odds Ratio^b,c	95% Confidence Interval
Race/ethnicity (reference: White)^d
Black/African American	1.82	1.62-2.04
American Indian/Alaskan Native	2.29	1.84-2.85
Hispanic/Latino	2.02	1.72-2.38
Multiracial/other	1.52	1.05-2.21
Asian	1.00	0.70-1.40
Country of origin: Mexico (reference: US)	1.25	1.06-1.47
Medical complexity	1.41	1.30-1.53
Major mental illness (yes/no)	1.42	1.24-1.63
Emergency room use (count)	1.04	1.02-1.06

Data were drawn from Epic Clarity electronic medical record data (2011). Main dependent variable includes whether or not a patient missed an appointment (no show).

Adjusted models controlled for individual age, sex, primary care provider assignment, and insurance payer (eg, public [Medicare, Medicaid, Dual Eligibles]; Private; Self-Pay; Other).

Other variables include race/ethnicity (White vs Black/African American, American Indian/Alaskan Native, Hispanic/Latino, Multiracial, Asian, other, refused/decline/unknown), country of origin (US, Mexico, Somalia, Ethiopia, other), language (English, Spanish, Amharic, Hmong, Somali, other), disease complexity (Center for Medical Services hierarchical condition score and categories), major mental illness (major depression, bipolar disorder), schizophrenia, chemical dependence and utilization (counts of emergency room visits, office visits, inpatient admissions, and miscellaneous other utilization variables including telephone calls, ambulance rides, and incarceration).

Race is not mutually exclusive.

Discussion

In a sample of culturally diverse patients at a safety net hospital, race and ethnicity were strongly associated with likelihood to miss appointments. Missed appointments also were associated with medical complexity, major mental illness, and emergency room utilization. Thus, efforts to decrease missed appointments may need to focus on sub-populations with these demographic and clinical profiles.

A qualitative study found several reasons why culturally diverse patients do not attend primary care appointments, including perceived disrespect for their beliefs and lack of understanding of scheduling systems.⁴ The Minimizing Error, Maximizing Outcome (MEMO) study found that minority patients were unable to attend appointments with specialists due to transportation and other challenges.⁵ Thus, remedying the problem of missed appointments may require greater attention to social, logistical, and interpersonal issues. Future studies may wish to investigate approaches to alleviating social and logistical barriers for patients.

Limitations of the study include its cross-sectional design during 1 study period (2011), not controlling for other potentially confounding variables, and the inability to determine causality. However, the findings can help guide health system-wide responses to decrease missed appointments.

The paradigm of routinely scheduled clinic appointments may not optimally provide care to minority populations. Development of alternative models is needed, such as walk-in access, home visits, or electronic visits. We recommend additional research to further investigate scheduling practices, integrated care delivery (eg, delivery of preventive care along with mental health management) and other factors (eg, subpopulation characteristics, recommended preventive visits) that may be associated with reduce missed appointments for minority populations.

Footnotes

Acknowledgements

We would like to thank our colleagues at Hennepin County Medical Center, Center for Patient and Provider Experience, and Minneapolis Medical Research Foundation for their support of this research study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Scott Shimotsu, PhD, MPH CPHQ, was a senior health care analyst in the Analytic Center of Excellence at Hennepin County Medical Center in Minneapolis, MN, during the research study. With over 14 years of healthcare experience, his research areas include healthcare services, diabetes care, health behavior, and social determinants of chronic disease.

Anne Roehrl is a principal data analyst at Hennepin County Medical Center. She holds a Master of Science in Health Services Management and has 15 years of experience designing, developing and analyzing data centric solutions in a across a broad spectrum of healthcare organizations.

Maribet McCarty, PhD, RN, is the director of the Analytic Center of Excellence at Hennepin County Medical Center in Minneapolis, MN. Maribet trained as a behavioral epidemiologist and has worked for over ten years in hospital-based quality improvement and data analytics.

Katherine Vickery is a primary care physician and investigator at Hennepin County Medical Center. She studies the influence of integrated care delivery systems on health outcomes and patient/provider experiences for medically, behaviorally, and socially complex patients.

Laura Guzman-Corrales, MPH, is a senior project coordinator in the Department of Medicine at Hennepin County Medical Center. Her background is in community-based public health intervention and evaluation and qualitative research.

Mark Linzer is division director of General Internal Medicine at Hennepin County Medical Center in Minneapolis MN. He is a primary care physician, teacher and researcher, with interests in health services research and clinician worklife.

Nancy Garrett, PhD, is chief analytics officer at Hennepin County Medical Center, where she leads the analytics and information technology functions. Previous to HCMC, Nancy worked at Boston Scientific, Blue Cross Blue Shield of Minnesota, and HealthPartners in analytics roles. She holds a PhD in Demography from the University of Illinois at Urbana-Champaign.

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Increased Likelihood of Missed Appointments (“No Shows”) for Racial/Ethnic Minorities in a Safety Net Health System