An intervention to improve care and reduce costs for high-risk patients with frequent hospital admissions: a pilot study

<p>Abstract</p> <p>Background</p> <p>A small percentage of high-risk patients accounts for a large proportion of Medicaid spending in the United States, which has become an urgent policy issue. Our objective was to pilot a novel patient-centered intervention for high-risk patients with frequent hospital admissions to determine its potential to improve care and reduce costs.</p> <p>Methods</p> <p>Community and hospital-based care management and coordination intervention with pre-post analysis of health care utilization. We enrolled Medicaid fee-for-service patients aged 18-64 who were admitted to an urban public hospital and identified as being at high risk for hospital readmission by a validated predictive algorithm. Enrolled patients were evaluated using qualitative and quantitative interview techniques to identify needs such as transportation to/advocacy during medical appointments, mental health/substance use treatment, and home visits. A community housing partner initiated housing applications in-hospital for homeless patients. Care managers facilitated appropriate discharge plans then worked closely with patients in the community using a harm reduction approach.</p> <p>Results</p> <p>Nineteen patients were enrolled; all were male, 18/19 were substance users, and 17/19 were homeless. Patients had a total of 64 inpatient admissions in the 12 months before the intervention, versus 40 in the following 12 months, a 37.5% reduction. Most patients (73.3%) had fewer inpatient admissions in the year after the intervention compared to the prior year. Overall ED visits also decreased after study enrollment, while outpatient clinic visits increased. Yearly study hospital Medicaid reimbursements fell an average of $16,383 per patient.</p> <p>Conclusions</p> <p>A pilot intervention for high-cost patients shows promising results for health services usage. We are currently expanding our model to serve more patients at additional hospitals to see if the pilot's success can be replicated.</p> <p>Trial registration</p> <p>Clinicaltrials.gov Identifier: <a href="http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1292096">NCT01292096</a></p

Assessments of residential and global positioning system activity space for food environments, body mass index and blood pressure among low-income housing residents in New York City

Research has examined how the food environment affects the risk of cardiovascular disease (CVD). Many studies have focused on residential neighbourhoods, neglecting the activity spaces of individuals. The objective of this study was to investigate whether food environments in both residential and global positioning system (GPS)-defined activity space buffers are associated with body mass index (BMI) and blood pressure (BP) among low-income adults. Data came from the New York City Low Income Housing, Neighborhoods and Health Study, including BMI and BP data (n=102, age=39.3±14.1 years), and one week of GPS data. Five food environment variables around residential and GPS buffers included: fast-food restaurants, wait-service restaurants, corner stores, grocery stores, and supermarkets. We examined associations between food environments and BMI, systolic and diastolic BP, controlling for individual- and neighbourhood-level sociodemographics and population density. Within residential buffers, a higher grocery store density was associated with lower BMI (β=- 0.20 kg/m2, P<0.05), and systolic and diastolic BP (β =-1.16 mm Hg; and β=-1.02 mm Hg, P<0.01, respectively). In contrast, a higher supermarket density was associated with higher systolic and diastolic BP (β=1.74 mm Hg, P<0.05; and β=1.68, P<0.01, respectively) within residential buffers. In GPS neighbourhoods, no associations were documented. Examining how food environments are associated with CVD risk and how differences in relationships vary by buffer types have the potential to shed light on determinants of CVD risk. Further research is needed to investigate these relationships, including refined measures of spatial accessibility/exposure, considering individual’s mobility

Food environment does not predict self-reported SSB consumption in New York City: A cross sectional study.

The purpose of this research was to examine whether the local food environment, specifically the distance to the nearest sugar sweetened beverage (SSB) vendor, a measure of SSB availability and accessibility, was correlated with the likelihood of self-reported SSB consumption among a sample of fast food consumers. As part of a broader SSB behavior study in 2013-2014, respondents were surveyed outside of major chain fast food restaurants in New York City (NYC). Respondents were asked for the intersection closest to their home and how frequently they consume SSBs. Comprehensive, administrative food outlet databases were used to geo-locate the SSB vendor closest to the respondents' home intersections. We then used a logistic regression model to estimate the association between the distance to the nearest SSB vendor (overall and by type) and the likelihood of daily SSB consumption. Our results show that proximity to the nearest SSB vendor was not statistically significantly associated with the likelihood of daily SSB consumption, regardless of type of vendor. Our results are robust to alternative model specifications, including replacing the linear minimum distance measure with count of the total number of SSB vendors or presence of a SSB vendor within a buffer around respondents' home intersections. We conclude that there is not a strong relationship between proximity to nearest SSB vendor, or proximity to a specific type of SSB vendor, and frequency of self-reported SSB consumption among fast food consumers in NYC. This suggests that policymakers focus on alternative strategies to curtail SSB consumption, such as improving the within-store food environment or taxing SSBs

Regression results predicting the purchase of a SSB once a day, overall and by food outlet type.

Regression results predicting the purchase of a SSB once a day, overall and by food outlet type.</p

Demographic characteristic of study sample, overall and by exposure specification.

Demographic characteristic of study sample, overall and by exposure specification.</p

Financial Hardship, Motivation to Quit and Post-Quit Spending Plans among Low-Income Smokers Enrolled in a Smoking Cessation Trial

Background: Tobacco spending may exacerbate financial hardship in low-income populations by using funds that could go toward essentials. This study examined post-quit spending plans among low-income smokers and whether financial hardship was positively associated with motivation to quit in the sample. Methods: We analyzed data from the baseline survey of a randomized controlled trial testing novel a smoking cessation intervention for low-income smokers in New York City ( N = 410). Linear regression was used to examine the relationship between financial distress, food insecurity, smoking-induced deprivation (SID) and motivation to quit (measured on a 0-10 scale). We performed summative content analyses of open-ended survey questions to identify the most common plans among participants with and without SID for how to use their tobacco money after quitting. Results: Participants had an average level of motivation to quit of 7.7 ( SD = 2.5). Motivation to quit was not significantly related to having high financial distress or food insecurity ( P &gt; .05), but participants reporting SID had significantly lower levels of motivation to quit than those without SID ( M = 7.4 versus 7.9, P = .04). Overall, participants expressed an interest in three main types of spending for after they quit: Purchases, Activities, and Savings/Investing, which could be further conceptualized as spending on Oneself or Family, and on Needs or Rewards. The top three spending plans among participants with and without SID were travel, clothing and savings. There were three needs-based spending plans unique to a small number of participants with SID: housing, health care and education. Conclusions: Financial distress and food insecurity did not enhance overall motivation to quit, while smokers with SID were less motivated to quit. Most low-income smokers, including those with SID, did not plan to use their tobacco money on household essentials after quitting. </jats:sec