Analysis of Consistency in Emergency Department Physician Variation in Propensity for Admission Across Patient Sociodemographic Groups

Social Determinants of Health and Cardiologist Involvement in the Care of Adults Hospitalized for Heart Failure

Importance

Involvement of a cardiologist in the care of adults during a hospitalization for heart failure (HF) is associated with reduced rates of in-hospital mortality and hospital readmission. However, not all patients see a cardiologist when they are hospitalized for HF.

Objective

To determine whether social determinants of health (SDOH) are associated with cardiologist involvement in the management of adults hospitalized for HF.

Design, Setting, and Participants

This retrospective cohort study used data from the Reasons for Geographic and Racial Difference in Stroke (REGARDS) cohort. Participants included adults who experienced an adjudicated hospitalization for HF between 2009 and 2017 in all 48 contiguous states in the US. Data analysis was performed from November 2022 to January 2023.

Exposures

A total of 9 candidate SDOH, aligned with the Healthy People 2030 conceptual model, were examined: Black race, social isolation, social network and/or caregiver availability, educational attainment less than high school, annual household income less than $35 000, living in rural area, living in a zip code with high poverty, living in a Health Professional Shortage Area, and living in a state with poor public health infrastructure.

Main Outcomes and Measures

The primary outcome was cardiologist involvement, defined as involvement of a cardiologist as the primary responsible clinician or as a consultant. Bivariate associations between each SDOH and cardiologist involvement were examined using Poisson regression with robust SEs.

Results

The study included 1000 participants (median [IQR] age, 77.8 [71.5-84.0] years; 479 women [47.9%]; 414 Black individuals [41.4%]; and 492 of 876 with low income [56.2%]) hospitalized at 549 unique US hospitals. Low annual household income (<$35 000) was the only SDOH with a statistically significant association with cardiologist involvement (relative risk, 0.88; 95% CI, 0.82-0.95). In a multivariable analysis adjusting for age, race, sex, HF characteristics, comorbidities, and hospital characteristics, low income remained inversely associated with cardiologist involvement (relative risk, 0.89; 95% CI, 0.82-0.97).

Conclusions and Relevance

This cohort study found that adults with low household income were 11% less likely than adults with higher incomes to have a cardiologist involved in their care during a hospitalization for HF. These findings suggest that socioeconomic status may bias the care provided to patients hospitalized for HF.

Clinician factors associated with delayed diagnosis of appendicitis

OBJECTIVES

To evaluate the association of clinician demographics and practice patterns with delayed diagnosis of appendicitis.

METHODS

We included children with appendicitis at 13 regional emergency departments (EDs). We screened patients with a previous ED visit within 7 days for delayed diagnosis by chart review. We evaluated the association of clinician characteristics using logistic regression with random intercepts for site and clinician and delay as the outcome.

RESULTS

Among 7,452 children with appendicitis, 105 (1.4%) had delayed diagnosis. Clinicians in the lowest quartile of obtaining blood in their general practice were more likely to have delayed diagnosis (odds ratio 4.9 compared to highest quartile, 95% confidence interval 1.8, 13.8). Clinicians' imaging rates, specialty, sex, and experience were not associated with delayed diagnosis.

CONCLUSIONS

Clinicians who used more blood tests in their general practice had a lower risk of delayed diagnosis of appendicitis, possible evidence that lower risk tolerance has benefits.

Social Determinants of Health and Cardiologist Involvement in the Care of Adults Hospitalized for Heart Failure

Introduction

The involvement of a cardiologist in the care of adults during a hospitalization for heart failure (HF) is associated with reduced rates of in-hospital mortality and hospital readmission. However, not all patients see a cardiologist when they are hospitalized for HF. Since reasons for this are not entirely clear, we sought to determine whether social determinants of health (SDOH) are associated with cardiologist involvement in the management of adults hospitalized for HF. We hypothesized that SDOH would be inversely associated with cardiologist involvement in the care of adults hospitalized for HF.

Methods

We included adult participants from the national REasons for Geographic And Racial Difference in Stroke (REGARDS) cohort, who experienced an adjudicated hospitalization for HF between 2009 and 2017. We excluded participants who were hospitalized at institutions that lacked cardiology services (n=246). We examined nine candidate SDOH, which align with the Healthy People 2030 conceptual model: Black race, social isolation (0-1 visits from a family or friend in the past month), social network/caregiver availability (having someone to care for them if ill), educational attainment < high school, annual household income < $35,000, living in rural areas, living in a zip code with high poverty, living in a Health Professional Shortage Area, and residing in a state with poor public health infrastructure. The primary outcome was cardiologist involvement, a binary variable which was defined as involvement of a cardiologist as the primary responsible clinician or as a consultant, collected via chart review. We examined associations between each SDOH and cardiologist involvement using Poisson regression with robust standard errors. Candidate SDOH with statistically significant associations (p<0.10) were retained for multivariable analysis. Potential confounders/covariates for the multivariable analysis included age, race, sex, HF characteristics, comorbidities, and hospital characteristics.

Results

We examined 876 participants hospitalized at 549 unique US hospitals. The median age was 77.5 years (IQR 71.0-83.7), 45.9% were female, 41.4% were Black, and 56.2% had low income. Low household income (<$35,000/year) was the only SDOH that had a statistically significant association with cardiologist involvement in a bivariate analysis (RR: 0.88 [95% CI: 0.82-0.95]). After adjusting for potential confounders, low income remained inversely associated (RR: 0.89 [95% CI: 0.82-0.97]).

Conclusions

Adults with low household income were 11% less likely to have a cardiologist involved in their care during a hospitalization for HF. This suggests that socioeconomic status may implicitly bias the care provided to patients hospitalized for HF.

Weak correlations in health services research: Weak relationships or common error?

OBJECTIVE

To examine whether the correlation between a provider's effect on one population of patients and the same provider's effect on another population is underestimated if the effects for each population are estimated separately as opposed to being jointly modeled as random effects, and to characterize how the impact of the estimation procedure varies with sample size.

DATA SOURCES

Medicare claims and enrollment data on emergency department (ED) visits, including patient characteristics, the patient's hospitalization status, and identification of the doctor responsible for the decision to hospitalize the patient.

STUDY DESIGN

We used a three-pronged investigation consisting of analytical derivation, simulation experiments, and analysis of administrative data to demonstrate the fallibility of stratified estimation. Under each investigation method, results are compared between the joint modeling approach to those based on stratified analyses.

DATA COLLECTION/EXTRACTION METHODS

We used data on ED visits from administrative claims from traditional (fee-for-service) Medicare from January 2012 through September 2015.

PRINCIPAL FINDINGS

The simulation analysis demonstrates that the joint modeling approach is generally close to unbiased, whereas the stratified approach can be severely biased in small samples, a consequence of joint modeling benefitting from bivariate shrinkage and the stratified approach being compromised by measurement error. In the administrative data analyses, the estimated correlation of doctor admission tendencies between female and male patients was estimated to be 0.98 under the joint model but only 0.38 using stratified estimation. The analogous correlations for White and non-White patients are 0.99 and 0.28 and for Medicaid dual-eligible and non-dual-eligible patients are 0.99 and 0.31, respectively. These results are consistent with the analytical derivations.

CONCLUSIONS

Joint modeling targets the parameter of primary interest. In the case of population correlations, it yields estimates that are substantially less biased and higher in magnitude than naive estimators that post-process the estimates obtained from stratified models.