Adapting Survey Data Collection to Respond to the COVID-19 Pandemic: Experiences From a Local Health Department.

The New York City (NYC) Department of Health and Mental Hygiene ("Health Department") conducts routine surveys to describe the health of NYC residents. During the COVID-19 pandemic, the Health Department adjusted existing surveys and developed new ones to improve our understanding of the impact of the pandemic on physical health, mental health, and social determinants of health and to incorporate more explicit measures of racial inequities. The longstanding Community Health Survey was adapted in 2020 to ask questions about COVID-19 and recruit respondents for a population-based severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurvey. A new survey panel, Healthy NYC, was launched in June 2020 and is being used to collect data on COVID-19, mental health, and social determinants of health. In addition, 7 Health Opinion Polls were conducted from March 2020 through March 2021 to learn about COVID-19-related knowledge, attitudes, and opinions, including vaccine intentions. We describe the contributions that survey data have made to the emergency response in NYC in ways that address COVID-19 and the profound inequities of the pandemic. (Am J Public Health. 2021;111(12):2176-2185. https://doi.org/10.2105/AJPH.2021.306515).

Identifying profiles of need among psychiatric inpatients approaching discharge in New York City: a latent class analysis.

PURPOSE: Understanding the needs of individuals transitioning to the community following a psychiatric hospitalization can inform community service planning. This study is among the first to examine the needs of a sample of psychiatric inpatients approaching discharge in a large urban area in the USA. METHODS: Representative data were drawn from 1129 acutely hospitalized psychiatric inpatients from eight New York City hospitals. Descriptive statistics were used to estimate patient needs at discharge across nine domains: housing, employment, income, transportation, education, time use, social support, and help accessing medical and mental health care. Latent class analysis (LCA) was applied to identify subgroups of patients based on needs profiles. Multinomial logistic regression was used to investigate socio-demographic associations with class membership. RESULTS: Respondents were most likely to have needs related to income (50.7%), housing (49.2%), and employment (48.7%). Results from the LCA suggested a five class solution of patient needs: three domain-specific classes whose members endorsed needs for 'housing and employment' (22.5%), 'social support and time use' (15.0%) and 'access to care' (6.4%) and two classes where overall member needs were high ('high needs,'18.4%) or low ('low needs,' 37.7%) across all needs. Compared to the 'low needs' class, members of the 'high needs' class had significantly greater odds of being black or Latino, male, uninsured, and parents of a child under 18 years. CONCLUSION: Patients have unique profiles of need that are significantly associated with the socio-demographic characteristics. These findings may help practitioners and policymakers improve mental health services.

Identification of risk factors for early psychiatric rehospitalization.

Identifying risk factors for early psychiatric rehospitalization (EPR, rehospitalization within 90 days) can inform strategies to reduce rehospitalization rates. Random forest (RF), a tree-based classification algorithm, can be useful for identifying potential risk factors for EPR from a large number of patient factors. Patient characteristics were collected from 519 psychiatric inpatients at eight New York City hospitals. RF was used to identify potential risk factors for EPR. Multiple logistic regression was performed to assess the association between the identified risk factors and rehospitalization. Top risk factors identified by RF were previous psychiatric hospitalizations, number of post-discharge needs, social isolation, and sense of belonging in one's community. Follow-up analyses confirmed the significant association between EPR and number of previous psychiatric hospitalizations, number of endorsed post-discharge needs, and social isolation after adjusting for demographic variables. Understanding the contributors to EPR can better inform mental health service planning, policies, and programs that promote recovery.

The New York City Mental Health Needs Assessment Study (MHNAS): Objectives, design, and methods.

OBJECTIVES: This paper describes the objectives, design, and methods of the Mental Health Needs Assessment Study (MHNAS). The objective of the MHNAS was to assess the needs of individuals transitioning to the community following psychiatric hospitalization and again 3-5 months later to inform community service planning. Needs were defined broadly to include domains like housing, employment, treatment, and social support. METHODS: The MHNAS used a 2-stage clustered sampling approach where the primary sampling units were hospitals and secondary sampling units were patients. The study included an in-person patient interview, an assessment of need from a key hospital worker, and a follow-up telephone interview 3-5 months after discharge. RESULTS: One thousand one hundred twenty-nine patients from 8 randomly selected hospitals participated. The overall response rate was 54.3% with a cooperation rate of 71.8%. The sample was similar to the overall population of psychiatric patients with respect to several key demographics. CONCLUSION: The MHNAS demonstrates the feasibility of conducting a needs assessment with a random sample of psychiatric inpatients in a large urban setting. Results from this study may improve community service planning to better meet individuals' needs, with the ultimate goal of reducing rehospitalization and promoting recovery.