Cost of health care utilization among homeless frequent emergency department users

Research demonstrates that homelessness is associated with frequent use of emergency department (ED) services, yet prior studies have not adequately examined the relationship between frequent ED use and utilization of non-ED health care services among those experiencing homelessness. There has also been little effort to assess heterogeneity among homeless individuals who make frequent use of ED services. To address these gaps, the present study used Medicaid claims data from 2010 to estimate the association between the number of ED visits and non-ED health care costs for a cohort of 6,338 Boston Health Care for the Homeless Program patients, and to identify distinct subgroups of persons in this cohort who made frequent use of ED services based on their clinical and demographic characteristics. A series of gamma regression models found more frequent ED use to be associated with higher non-ED costs, even after adjusting for demographic and clinical characteristics. Latent class analysis was used to examine heterogeneity among frequent ED users, and the results identified 6 characteristically distinct subgroups among these persons. The subgroup of persons with trimorbid illness had non-ED costs that far exceeded members of all 5 other subgroups. Study findings reinforce the connection between frequent ED use and high health care costs among homeless individuals and suggest that different groups of homeless frequent ED users may benefit from interventions that vary in terms of their composition and intensity

A classification model of homelessness using integrated administrative data: Implications for targeting interventions to improve the housing status, health and well-being of a highly vulnerable population

Homelessness is poorly captured in most administrative data sets making it difficult to understand how, when, and where this population can be better served. This study sought to develop and validate a classification model of homelessness. Our sample included 5,050,639 individuals aged 11 years and older who were included in a linked dataset of administrative records from multiple state-maintained databases in Massachusetts for the period from 2011-2015. We used logistic regression to develop a classification model with 94 predictors and subsequently tested its performance. The model had high specificity (95.4%), moderate sensitivity (77.8%) for predicting known cases of homelessness, and excellent classification properties (area under the receiver operating curve 0.94; balanced accuracy 86.4%). To demonstrate the potential opportunity that exists for using such a modeling approach to target interventions to mitigate the risk of an adverse health outcome, we also estimated the association between model predicted homeless status and fatal opioid overdoses, finding that model predicted homeless status was associated with a nearly 23-fold increase in the risk of fatal opioid overdose. This study provides a novel approach for identifying homelessness using integrated administrative data. The strong performance of our model underscores the potential value of linking data from multiple service systems to improve the identification of housing instability and to assist government in developing programs that seek to improve health and other outcomes for homeless individuals

Using Best-Worst Scaling to Understand Patient Priorities: A Case Example of Papanicolaou Tests for Homeless Women

PURPOSE: Best-worst scaling (BWS) is a survey method for assessing individuals\u27 priorities. It identifies the extremes-best and worst items, most and least important factors, biggest and smallest influences-among sets. In this article, we demonstrate an application of BWS in a primary care setting to illustrate its use in identifying patient priorities for services. METHODS: We conducted a BWS survey in 2014 in Boston, Massachusetts, to assess the relative importance of 10 previously identified attributes of Papanicolaou (Pap) testing services among women experiencing homelessness. Women were asked to evaluate 11 sets of 5 attributes of Pap services, and identify which attribute among each set would have the biggest and smallest influence on promoting uptake. We show how frequency analysis can be used to analyze results. RESULTS: In all, 165 women participated, a response rate of 72%. We identified the most and least salient influences on encouraging Pap screening based on their frequency of report among our sample, with possible standardized scores ranging from+1.0 (biggest influence) to -1.0 (smallest influence). Most important was the availability of support for issues beyond health (+0.39), while least important was the availability of accommodations for personal hygiene (-0.27). CONCLUSIONS: BWS quantifies patient priorities in a manner that is transparent and accessible. It is easily comprehendible by patients and relatively easy to administer. Our application illustrates its use in a vulnerable population, showing that factors beyond those typically provided in health care settings are highly important to women in seeking Pap screening. This approach can be applied to other health care services where prioritization is helpful to guide decisions

Frequent Emergency Department Visits and Hospitalizations Among Homeless People With Medicaid: Implications for Medicaid Expansion

OBJECTIVES: We examined factors associated with frequent hospitalizations and emergency department (ED) visits among Medicaid members who were homeless. METHODS: We included 6494 Massachusetts Medicaid members who received services from a health care for the homeless program in 2010. We used negative binomial regression to examine variables associated with frequent utilization. RESULTS: Approximately one third of the study population had at least 1 hospitalization and two thirds had 1 or more ED visits. More than 70% of hospitalizations and ED visits were incurred by only 12% and 21% of these members, respectively. Homeless individuals with co-occurring mental illness and substance use disorders were at greatest risk for frequent hospitalizations and ED visits (e.g., incidence rate ratios [IRRs] = 2.9-13.8 for hospitalizations). Individuals living on the streets also had significantly higher utilization (IRR = 1.5). CONCLUSIONS: Despite having insurance coverage, homeless Medicaid members experienced frequent hospitalizations and ED visits. States could consider provisions under the Patient Protection and Affordable Care Act (e.g., Medicaid expansion and Health Homes) jointly with housing programs to meet the needs of homeless individuals, which may improve the quality and cost effectiveness of care

Comprehensive Ambulatory Medicine Training for Categorical Internal Medicine Residents

It is challenging to create an educational and satisfying experience in the outpatient setting. We developed a 3-year ambulatory curriculum that addresses the special needs of our categorical medicine residents with distinct learning objectives for each year of training and clinical experiences and didactic sessions to meet these goals. All PGY1 residents spend 1 month on a general medicine ambulatory care rotation. PGY2 residents spend 3 months on an ambulatory block focusing on 8 core medicine subspecialties. Third-year residents spend 2 months on an advanced ambulatory rotation. The curriculum was started in July 2000 and has been highly regarded by the house staff, with statistically significant improvements in the PGY2 and PGY3 evaluation scores. By enhancing outpatient clinical teaching and didactics with an emphasis on the specific needs of our residents, we have been able to reframe the thinking and attitudes of a group of inpatient-oriented residents