Meeting Social Needs in a Crisis Context: Lessons Learned from Integrating the 'Take Care Initiative' into New York City's Testing and Contact Tracing Program.

The COVID-19 pandemic highlighted the importance of addressing social needs in a crisis context. Some US jurisdictions integrated a social service component into case investigation and contact tracing (CI/CT) programs, including the New York City (NYC) Test & Trace (T2) Program; the Take Care initiative referred NYC residents who tested positive or were exposed to COVID-19 to services to support isolation and quarantine and meet basic needs. More research is needed to determine effective implementation strategies for integrating social needs provision into CI/CT programs. To identify barriers and facilitators to the implementation of the Take Care initiative, we conducted key informant interviews with program staff, community-based organization partners, and cases and contacts as part of a larger evaluation of the T2 program. Interviews were recorded, transcribed, and analyzed using rapid qualitative methods. Key facilitators to implementation included utilizing a case management software system, employing strategies to encourage service uptake, leveraging cross-agency collaborations, and partnering with community-based organizations for resource navigation. Barriers identified included external management of the software system, challenges reaching and engaging the public, administrative complications due to shifting collaborations, and management of CBO partners' structure and hiring. Based on our findings, we provide recommendations to support effective planning and implementation of social needs service provision in a crisis context. Future research should focus on testing promising implementation strategies highlighted in this study and applying them to varied contexts and crisis situations.

Scale-Up of COVID-19 Testing Services in NYC, 2020-2021: Lessons Learned to Maximize Reach, Equity and Timeliness.

During infectious disease epidemics, accurate diagnostic testing is key to rapidly identify and treat cases, and mitigate transmission. When a novel pathogen is involved, building testing capacity and scaling testing services at the local level can present major challenges to healthcare systems, public health agencies, and laboratories. This mixed methods study examined lessons learned from the scale-up of SARS-CoV-2 testing services in New York City (NYC), as a core part of NYC's Test & Trace program. Using quantitative and geospatial analyses, the authors assessed program success at maximizing reach, equity, and timeliness of SARS-CoV-2 diagnostic testing services across NYC neighborhoods. Qualitative analysis of key informant interviews elucidated key decisions, facilitators, and barriers involved in the scale-up of SARS-CoV-2 testing services. A major early facilitator was the ability to establish working relationships with private sector vendors and contractors to rapidly procure and manufacture necessary supplies locally. NYC residents were, on average, less than 25 min away from free SARS-CoV-2 diagnostic testing services by public transport, and services were successfully directed to most neighborhoods with the highest transmission rates, with only one notable exception. A key feature was to direct mobile testing vans and rapid antigen testing services to areas based on real-time neighborhood transmission data. Municipal leaders should prioritize fortifying supply chains, establish cross-sectoral partnerships to support and extend testing services, plan for continuous testing and validation of assays, ensure open communication feedback loops with CBO partners, and maintain infrastructure to support mobile services during infectious disease emergencies.

Lessons Learned from the Launch and Implementation of the COVID-19 Contact Tracing Program in New York City: a Qualitative Study.

On June 1, 2020, NYC Health + Hospitals, in partnership with the NYC Department of Health and Mental Hygiene, other city agencies, and a large network of community partners, launched the New York City Test & Trace (T2) COVID-19 response program to identify and isolate cases, reduce transmission through contact tracing, and provide support to residents during isolation or quarantine periods. In this paper, we describe lessons learned with respect to planning and implementation of case notification and contact tracing. Our findings are based on extensive document review and analysis of 74 key informant interviews with T2 leadership and frontline staff, cases, and contacts conducted between January and September 2022. Interviews elicited respondent background, history of program development, program leadership and structure, goals of the program, program evolution, staffing, data systems, elements of community engagement, trust with community, program reach, timeliness, equity, general barriers and challenges, general facilitators and best practices, and recommendations/improvement for the program. Facilitators and barriers revealed in the interviews primarily revolved around hiring and managing staff, data and technology, and quality of interactions with the public. Based on these facilitators and barriers, we identify suggestions to support effective planning and response for future case notification and contact tracing programs, including recommendations for planning during latent periods, case management and data systems, and processes for outreach to cases and contacts.

Evaluation of the New York City COVID-19 case investigation and contact tracing program: a cascade of care analysis.

BACKGROUND: New York City (NYC) was the first COVID-19 epicenter in the United States and home to one of the country's largest contact tracing programs, NYC Test & Trace (T2). Understanding points of attrition along the stages of program implementation and follow-up can inform contact tracing efforts for future epidemics or pandemics. The objective of this study was to evaluate the completeness and timeliness of T2 case and contact notification and monitoring using a "cascade of care" approach. METHODS: This cross-sectional study included all SARS-CoV-2 cases and contacts reported to T2 from May 31, 2020 to January 1, 2022. Attrition along the "cascade of care" was defined as: (1) attempted, (2) reached, (3) completed intake (main outcome), (4) eligible for monitoring, and (5) successfully monitored. Timeliness was assessed: (1) by median days from a case's date of testing until their positive result was reported to T2, (2) from result until the case was notified by T2, and (3) from a case report of a contact until notification of the contact. RESULTS: A total of 1.45 million cases and 1.38 million contacts were reported to T2 during this period. For cases, attrition occurred evenly across the first three cascade steps (~-12%) and did not change substantially until the Omicron wave in December 2021. During the Omicron wave, the proportion of cases attempted dropped precipitously. For contacts, the largest attrition occurred between attempting and reaching (-27%), and attrition rose with each COVID-19 wave as contact volumes increased. Attempts to reach contacts discontinued entirely during the Omicron wave. Overall, 67% of cases and 49% of contacts completed intake interviews (79% and 57% prior to Omicron). T2 was timely, with a median of 1 day to receive lab results, 2 days to notify cases, and < 1 day to notify contacts. CONCLUSIONS: T2 provided a large volume of NYC residents with timely notification and monitoring. Engagement in the program was lower for contacts than cases, with the largest gap coming from inability to reach individuals during call attempts. To strengthen future test-and-trace efforts, strategies are needed to encourage acceptance of local contact tracer outreach attempts.

Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network.

INTRODUCTION: Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved. METHODS AND ANALYSIS: The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0-17 years only (component A), three centres conduct surveillance in young adults aged 18-44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression. ETHICS AND DISSEMINATION: The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

Addressing Financial Barriers to Health Care Among People Who are Low-Income and Insured in New York City, 2014-2017.

While health care-associated financial burdens among uninsured individuals are well described, few studies have systematically characterized the array of financial and logistical complications faced by insured individuals with low household incomes. In this mixed methods paper, we conducted 6 focus groups with a total of 55 residents and analyzed programmatic administrative records to characterize the specific financial and logistic barriers faced by residents living in public housing in East and Central Harlem, New York City (NYC). Participants included individuals who enrolled in a municipal community health worker (CHW) program designed to close equity gaps in health and social outcomes. Dedicated health advocates (HAs) were explicitly paired with CHWs to provide health insurance and health care navigational assistance. We describe the needs of 150 residents with reported financial barriers to care, as well as the navigational and advocacy strategies taken by HAs to address them. Finally, we outline state-level policy recommendations to help ameliorate the problems experienced by participants. The model of paired CHW-HAs may be helpful in addressing financial barriers for insured populations with low household income and reducing health disparities in other communities.

The use of electronic health records to inform cancer surveillance efforts: a scoping review and test of indicators for public health surveillance of cancer prevention and control.

INTRODUCTION: State cancer prevention and control programs rely on public health surveillance data to set objectives to improve cancer prevention and control, plan interventions, and evaluate state-level progress towards achieving those objectives. The goal of this project was to evaluate the validity of using electronic health records (EHRs) based on common data model variables to generate indicators for surveillance of cancer prevention and control for these public health programs. METHODS: Following the methodological guidance from the PRISMA Extension for Scoping Reviews, we conducted a literature scoping review to assess how EHRs are used to inform cancer surveillance. We then developed 26 indicators along the continuum of the cascade of care, including cancer risk factors, immunizations to prevent cancer, cancer screenings, quality of initial care after abnormal screening results, and cancer burden. Indicators were calculated within a sample of patients from the New York City (NYC) INSIGHT Clinical Research Network using common data model EHR data and were weighted to the NYC population using post-stratification. We used prevalence ratios to compare these estimates to estimates from the raw EHR of NYU Langone Health to assess quality of information within INSIGHT, and we compared estimates to results from existing surveillance sources to assess validity. RESULTS: Of the 401 identified articles, 15% had a study purpose related to surveillance. Our indicator comparisons found that INSIGHT EHR-based measures for risk factor indicators were similar to estimates from external sources. In contrast, cancer screening and vaccination indicators were substantially underestimated as compared to estimates from external sources. Cancer screenings and vaccinations were often recorded in sections of the EHR that were not captured by the common data model. INSIGHT estimates for many quality-of-care indicators were higher than those calculated using a raw EHR. CONCLUSION: Common data model EHR data can provide rich information for certain indicators related to the cascade of care but may have substantial biases for others that limit their use in informing surveillance efforts for cancer prevention and control programs.