Thirty-Day Inpatient Readmissions for Asian American and Pacific Islander Subgroups Compared With Whites

Factors Related to Pediatric Readmissions of Four Major Diagnostic Categories in Hawai`i

Readmissions are a key quality measure for health care decision making and understanding variables associated with readmissions has become a crucial research area. This study identified patient-level factors that might be associated with pediatric readmissions using a database that included inpatient data from 2008 to 2017 from Hawai`i. Four major diagnostic categories with the most pediatric readmissions in the state were identified: respiratory, digestive, mental, and nervous system diseases and disorders. The associations between readmission and patient-level variables, such as age, sex, race/ethnicity, insurance status, and Charlson Comorbidity Index (CCI), were determined for each diagnosis and for overall readmissions. CCI and insurance were the strongest predictors when all diagnoses were combined. However, for some diagnoses, there was weak or no association between CCI, insurance, and readmission. This suggests that diagnosis-specific analysis of predictors of readmission may be more useful than looking at predictors of readmission for all diagnoses combined. While this study focused on patient variables, future studies should also incorporate how hospital variables may also be related to diagnosis.

Osteoporosis treatment rates after hip fracture 2011-2019 in Hawaii: Undertreatment of men after hip fractures

Objectives

To investigate trends of osteoporosis treatment rates, and factors affecting osteoporosis treatment after hip fracture admission within a single health care system in Hawaii.

Methods

A retrospective chart review was conducted of patients aged 50 years or older and hospitalized for hip fractures between January 1, 2011 and December 31, 2019 at Hawaii Pacific Health, a large health care system in Hawaii. We collected data on basic demographics and osteoporosis medication prescription from electronic medical records. We evaluated trends of osteoporosis treatment rates and performed logistic regression to determine factors associated with osteoporosis treatment.

Results

The mean for treatment rates for osteoporosis from 2011 to 2019 was 17.2% (range 8.8%–26.0%). From 2011 to 2019 there was a small increase in treatment rates from 16.3% in 2011 to 24.1% in 2019. Men were less likely to receive osteoporosis treatment after admission for hip fracture. Patients discharged to a facility were more likely to receive osteoporosis treatment. As compared to women, men who had a hip fracture were less likely to receive dual-energy X-ray absorptiometry scan, and osteoporosis medication before hip fracture admission.

Conclusions

The use of osteoporosis medication for secondary prevention after admission for hip fracture in Hawaii from 2011 to 2019 was low. However, there was a small increase in treatment rates from 2011 to 2019. Disparities in treatment of osteoporosis after hip fracture were noted in men. Significant work is needed to increase treatment rates further, and to address the disparity in osteoporosis treatment between men and women.

Racial Disparities in 7-Day Readmissions from an Adult Hospital Medicine Service

Background

Health systems have targeted hospital readmissions to promote health equity as there may be racial and ethnic disparities across different patient groups. However, 7-day readmissions have been understudied in adult hospital medicine.

Design

This is a retrospective study. We performed multivariable logistic regression between patient race/ethnicity and 7-day readmission. Mediation analysis was performed for limited English proficiency (LEP) status. Subgroup analyses were performed for patients with initial admissions for congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), and cancer.

Patients

We identified all adults discharged from the adult hospital medicine service at UCSF Medical Center between July 2016 and June 2019.

Main Measures

The primary outcome was 7-day all-cause readmission back to the discharging hospital.

Results

There were 18,808 patients in our dataset who were discharged between July 2016 and June 2019. A total of 1,297 (6.9%) patients were readmitted within 7 days. Following multivariable regression, patients who identified as Black (OR 1.35, 95% CI 1.15–1.58, p <0.001) and patients who identified as Asian (OR 1.26, 95% CI 1.06–1.50, p = 0.008) had higher odds of readmission compared to white patients. Multivariable regression at the subgroup level for CHF, COPD, and cancer readmissions did not demonstrate significant differences between the racial and ethnic groups.

Conclusions

Black patients and Asian patients experienced higher rates of 7-day readmission than patients who identified as white, confirmed on adjusted analysis.

Insights in Public Health: Outpatient Care Gaps for Patients Hospitalized with Ambulatory Care Sensitive Conditions in Hawai'i: Beyond Access and Continuity of Care

Ambulatory care sensitive conditions (ACSCs) are conditions that can generally be managed in community-based healthcare settings, and, if managed well, should not require hospital admission. A 5-year, mixed methods study was recently concluded that (1) documented disparities in hospitalizations for ACSCs in Hawai'i through quantitative analysis of state-wide hospital discharge data; and (2) identified contributing factors for these hospitalizations through patient interviews. This Public Health Insights article provides deeper context for, and consideration of, a striking study finding: the differences between typical measures of access to care and the quality of patient/provider interactions as reported by study participants. The themes that emerged from the patients' stories of their own potentially preventable hospital admissions shed light on the importance of being heard, trust, communication, and health knowledge in their relationships with their providers. We conclude that improving the quality of the relationship and level of engagement between the patient and community/outpatient providers may help reduce hospitalizations for ACSCs in Hawai'i and beyond. These interpersonal-level goals should be supported by systems-level efforts to improve health care delivery and address health disparities.

Living Alone and Homelessness as Predictors of 30-Day Potentially Preventable Hospital Readmission

Introduction

The effect of social factors on health care outcomes is widely recognized. Health care systems are encouraged to add social and behavioral measures to electronic health records (EHRs), but limited research demonstrates how to leverage this information. We assessed 2 social factors collected from EHRs — social isolation and homelessness — in predicting 30-day potentially preventable readmissions (PPRs) to hospital.

Methods

EHR data were collected from May 2015 through April 2017 from inpatients at 2 urban hospitals on O‘ahu, Hawai‘i (N = 21,274). We performed multivariable logistic regression models predicting 30-day PPR by living alone versus living with others and by documented homelessness versus no documented homelessness, controlling for relevant factors, including age group, race/ethnicity, sex, and comorbid conditions.

Results

Among the 21,274 index hospitalizations, 16.5% (3,504) were people living alone and 11.2% (2,385) were homeless; 4.2% (899) hospitalizations had a 30-day PPR. In bivariate analysis, living alone did not significantly affect likelihood of a 30-day PPR (16.6% [3,376 hospitalizations] without PPR vs 14.4% [128 hospitalizations] with PPR; P = .09). However, documented homelessness did show a significant effect on the likelihood of 30-day PPR in the bivariate analysis (11.1% [2,259 hospitalizations] without PPR vs 14.1% [126 hospitalizations] with PPR; P = .006). In multivariable models, neither living alone nor homelessness was significantly associated with PPR. Factors that were significantly associated with PPR were comorbid conditions, discharge disposition, and use of an assistive device.

Conclusion

Homelessness predicted PPR in descriptive analyses. Neither living alone nor homelessness predicted PPR once other factors were controlled. Instead, indicators of physical frailty (ie, use of an assistive device) and medical complexity (eg, hospitalizations that required assistive care post-discharge, people with a high number of comorbid conditions) were significant. Future research should focus on refining, collecting, and applying social factor data obtained through acute care EHRs.

Racial and Ethnic Composition of Hospitals' Service Areas and the Likelihood of Being Penalized for Excess Readmissions by the Medicare Program

BACKGROUND

The Hospital Readmission Reduction Program (HRRP) disproportionately penalizes hospitals serving minority communities. The National Academy of Science, Engineering, and Medicine has recommended that the Centers for Medicare and Medicaid Services (CMS) consider adjusting for social risk factors in their risk adjustment methodology. This study examines the association between the racial and ethnic composition of a hospital market and the impact of other social risk factors on the probability of a hospital being penalized under the HRRP.

RESEARCH METHODS AND DATA

This study analyzes data from CMS, the American Hospital Association, and the American Community Survey for 3168 hospitals from 2013 to 2017. We used logistic regression models to estimate the association between the penalty status under HRRP and the racial and ethnic composition of a hospital market, and explored whether this association was moderated by other social risk factors.

RESULTS

Our results indicate that the probability of being penalized increases with the percentage of black and Asian residents in the hospital service area (HSA) and decreased with the percentage of Hispanic residents in the HSA. This association was reduced and became statistically insignificant when we controlled for other social risk factors. The strongest predictors of penalty status were the hospital's share of Medicaid patients and the percent of persons without a high school diploma in the HSA.

CONCLUSIONS

By incorporating relevant social risk factors in the reimbursement methodology, CMS could mitigate the negative effects of HRRP on hospitals serving minority communities.