Jay Bainbridge

A Population-Based Assessment of the Health of Homeless Families in New York City, 2001–2003

OBJECTIVES We compared estimated population-based health outcomes for New York City (NYC) homeless families with NYC residents overall and in low-income neighborhoods. METHODS We matched a NYC family shelter user registry to mortality, tuberculosis, HIV/AIDS, and blood lead test registries maintained by the NYC Department of Health and Mental Hygiene (2001-2003). RESULTS Overall adult age-adjusted death rates were similar among the 3 populations. HIV/AIDS and substance-use deaths were 3 and 5 times higher for homeless adults than for the general population; only substance-use deaths were higher than for low-income adults. Children who experienced homelessness appeared to be at an elevated risk of mortality (41.3 vs 22.5 per 100,000; P < .05). Seven in 10 adult and child deaths occurred outside shelter. Adult HIV/AIDS diagnosis rates were more than twice citywide rates but comparable with low-income rates, whereas tuberculosis rates were 3 times higher than in both populations. Homeless children had lower blood lead testing rates and a higher proportion of lead levels over 10 micrograms per deciliter than did both comparison populations. CONCLUSIONS Morbidity and mortality levels were comparable between homeless and low-income adults; homeless childrens slightly higher risk on some measures possibly reflects the impact of poverty and poor-quality, unstable housing.

Efficient Targeting of Homelessness Prevention Services for Families

OBJECTIVES We developed and evaluated a model to target homelessness prevention services to families more efficiently. METHODS We followed 11,105 families who applied for community-based services to prevent homelessness in New York City from October 1, 2004, to June 30, 2008, through administrative records, using Cox regression to predict shelter entry. RESULTS Over 3 years, 12.8% of applicants entered shelter. Both the complete Cox regression and a short screening model based on 15 risk factors derived from it were superior to worker judgments, with substantially higher hit rates at the same level of false alarms. We found no evidence that some families were too risky to be helped or that specific risk factors were particularly amenable to amelioration. CONCLUSIONS Despite some limitations, an empirical risk model can increase the efficiency of homelessness prevention services. Serving the same proportion of applicants but selecting those at highest risk according to the model would have increased correct targeting of families entering shelter by 26% and reduced misses by almost two thirds. Parallel models could be developed elsewhere.

Using Learning Analytics to Predict At-Risk Students in Online Graduate Public Affairs and Administration Education

Abstract In this global information age, schools that teach public affairs and administration must meet the needs of students. Increasingly, this means providing students information in online classrooms to help them reach their highest potential. The acts of teaching and learning online generate data, but to date, that information has remained largely untapped for assessing student performance. Using data generated by students in an online Master of Public Administration program, drawn from the Marist College Open Academic Analytics Initiative,1 we identify and analyze characteristics and behaviors that best provide early indication of a student being academically at risk, paying particular attention to the usage of online tools. We find that fairly simple learning analytics models achieve high levels of sensitivity (over 80% of at-risk students identified) with relatively low false positive rates (13.5%). Results will be used to test interventions for improving student performance in real time.

The Use of Data to Assist in the Design of a New Service System for Homeless Veterans in New York City

ObjectiveOperation Home is an agreement between the City of New York and the US Department of Veterans Affairs to design a new service system to help end veteran homelessness in New York City. The authors’ task was to obtain data to inform the design of this new system.MethodsA variety of methods were used. The group reviewed relevant literature and data from street homeless survey samples, analyzed shelter data, and consulted with VA homeless program staff on the findings. We then surveyed case managers at a veterans’ shelter regarding their clients and determined their housing eligibility using a standardized logic model, and led two focus groups of veterans at this shelter regarding their views of the current shelter system and services for homeless veterans and how these might be improved.ResultsAmong those resident in shelters during 2006, 37.2% of self-identified veterans compared to 0.9% of others reported their prior residence as supported housing, suggesting the need for more intensive case management at veterans’ supported housing sites to help them sustain their tenure. The lack of interconnectedness among the various information systems made it more difficult to collect and analyze pertinent data. To begin to address this, a data match was undertaken to estimate the proportion of veterans resident in the veterans’ shelter who were not in receipt of VA benefits to which they may be entitled.ConclusionThe data obtained through collaboration between staff from NYC’s Department of Homelessness Services, US Department of Veterans Affairs facilities in the New York/New Jersey region and Common Ground Community led to information that informed the evaluation design of the new system. The identification of gaps in available data on homeless veterans will lead to projects both to improve and share data.

Aging Trends in Homeless Populations

Longitudinal data suggests that the single adult homeless population is going through a demographic transition, where the overall population is aging but there are indications that a younger cohort may be emerging. Scholars Dennis P. Culhane, Stephen Metraux, Thomas Byrne, Magdi Stino, and Jay Bainbridge argue that interventions at both ends of this transition: housing the aging and increasingly infirm elements of this population while diverting at-risk younger populations from homelessness, have the potential to make a lasting reduction in this population.

International Sanitation Management and Performance Measurement: Taking Out the Trash

Internationally, sanitation management has been a critical area of contention, especially in recent years with tightening budgets and resource reductions to public services. Our article reviews the management strategies, actions, and developments that have led to sanitation incidents of piling trash and public health concerns. These incidents will be reviewed from a public management perspective underscoring the role of performance measurement and management. The key influences associated with the varying cases are discussed. Both the negative and positive factors of international cases of sanitation management are reviewed.