Implementing Data to Care-What Are the Costs for the Health Department?

Using the exploration, preparation, implementation, sustainment (EPIS) framework to assess the cooperative re-engagement controlled trial (CoRECT)

Background

"Data to Care" (D2C) is a strategy which relies on a combination of public health surveillance data supplemented by clinic data to support continuity of HIV care. The Cooperative Re-Engagement Controlled Trial (CoRECT) was a CDC-sponsored randomized controlled trial of a D2C model, which provided an opportunity to examine the process of implementing an intervention for people with HIV (PWH) who are out-of-care across three public health department jurisdictions. Using the EPIS (Exploration, Preparation, Implementation, Sustainment) framework, we aimed to retrospectively describe the implementation process for each site to provide insights and guidance to inform future D2C activities implemented by public health agencies and their clinical and community partners.

Methods

After completion of CoRECT, the three (Connecticut, Massachusetts, Philadelphia) trial sites reviewed study protocols and held iterative discussions to describe and compare their processes regarding case identification, interactions with partnering clinics and patients, and sustainability. The EPIS framework provided a structure for comparing key organizational and operational practices and was applied to the entire implementation process.

Results

The trial sites varied in their implementation processes and the specific elements of the intervention. Factors including prior D2C experience, data management and analytic infrastructure, staff capacity, and relationships with clinic partners informed intervention development and implementation. Additionally, this review identified key lessons learned including to: (1) explore new supplemental sources for public health surveillance data; (2) work with stakeholders representing core functions/components in the early stages of the intervention design process; (3) build flexibility into all components of the follow-up activities; and (4) integrate data sharing, project management, and follow-up activities within existing DPH organizational structure.

Conclusion

The CoRECT study provides a general blueprint and lessons learned for implementing a D2C intervention for re-engagement in HIV care. Interventions should be tailored to local operational and structural factors, and responsive to evolving clinical and public health practices.

Costs and cost-effectiveness of a collaborative data-to-care intervention for HIV treatment and care in the United States

INTRODUCTION

Data-to-care programmes utilize surveillance data to identify persons who are out of HIV care, re-engage them in care and improve HIV care outcomes. We assess the costs and cost-effectiveness of re-engagement in an HIV care intervention in the United States.

METHODS

The Cooperative Re-engagement Control Trial (CoRECT) employed a data-to-care collaborative model between health departments and HIV care providers, August 2016-July 2018. The health departments in Connecticut (CT), Massachusetts (MA) and Philadelphia (PHL) collaborated with HIV clinics to identify newly out-of-care patients and randomize them to receive usual linkage and engagement in care services (standard-of-care control arm) or health department-initiated active re-engagement services (intervention arm). We used a microcosting approach to identify the activities and resources involved in the CoRECT intervention, separate from the standard-of-care, and quantified the costs. The cost data were collected at the start-up and recurrent phases of the trial to incorporate potential variation in the intervention costs. The costs were estimated from the healthcare provider perspective.

RESULTS

The CoRECT trial in CT, MA and PHL randomly assigned on average 327, 316 and 305 participants per year either to the intervention arm (n = 166, 159 and 155) or the standard-of-care arm (n = 161, 157 and 150), respectively. Of those randomized, the number of participants re-engaged in care within 90 days in the intervention and standard-of-care arms was 85 and 70 in CT, 84 and 70 in MA, and 98 and 67 in PHL. The additional number of participants re-engaged in care in the intervention arm compared with those in the standard-of-care arm was 15 (CT), 14 (MA) and 31 (PHL). We estimated the annual total cost of the CoRECT intervention at $490,040 in CT, $473,297 in MA and $439,237 in PHL. The average cost per participant enrolled was $2952, $2977 and $2834 and the average cost per participant re-engaged in care was $5765, $5634 and $4482. We estimated an incremental cost per participant re-engaged in care at $32,669 (CT), $33,807 (MA) and $14,169 (PHL).

CONCLUSIONS

The costs of the CoRECT intervention that identified newly out-of-care patients and re-engaged them in HIV care are comparable with other similar interventions, suggesting a potential for its cost-effectiveness in the US context.

Economic Impact of Universal Hepatitis C Virus Testing for Middle-Aged Adults Who Inject Drugs

INTRODUCTION

The objective of this study was to estimate the economic impact of providing universal hepatitis C virus testing in commercially insured middle-aged persons who inject drugs in the U.S.

METHODS

This study developed a dynamic 10-year economic model to project the clinical and economic outcomes associated with hepatitis C virus testing among middle-aged adult persons who inject drugs, from a payer's perspective. Costs related to hepatitis C virus testing, direct-acting antiviral, and liver-related outcomes between the (1) current hepatitis C virus testing rate (i.e., 8%) and (2) universal hepatitis C virus testing rate (i.e., 100%) were compared. Among patients testing positive, 21% of those without cirrhosis and 48% of those with cirrhosis were assumed to initiate direct-acting antivirals. Sensitivity analyses were performed to identify variables (e.g., direct-acting antiviral drug costs, hepatitis C virus testing costs, direct-acting antiviral treatment rate) influencing this study's conclusion.

RESULTS

The model predicts that during the 10-year period, universal hepatitis C virus testing will cost an additional $242 per person who injects drugs to the payers' healthcare budgets compared with the current scenario. Sensitivity analyses showed values ranging from $1,656 additional costs to $1,085 cost savings across all varied parameters and scenarios. A total of 80% of the current direct-acting antiviral costs indicated that cost savings will be $383 per person who injects drugs.

CONCLUSIONS

Universal hepatitis C virus testing among persons who inject drugs would not achieve cost savings within 10 years, with the cost of direct-acting antivirals contributing the most to the spending. To promote universal hepatitis C virus testing among persons who inject drugs, decreasing direct-acting antiviral costs and sustainable funding streams for hepatitis C virus testing should be considered.

Advancing data to care strategies for persons with HIV using an innovative reconciliation process

Background

UN AIDS has set ambitious 95-95-95 HIV care continuum targets for global HIV elimination by 2030. The U.S. HIV Care Continuum in 2018 showed that 65% of persons with HIV(PWH) are virally suppressed and 58% retained in care. Incomplete care-engagement not only affects individual health but drives ongoing HIV transmission. Data to Care (D2C) is a strategy using public health surveillance data to identify and re-engage out-of-care (OOC) PWH. Optimization of this strategy is needed.

Setting

Statewide partnership with Connecticut Department of Public Health (CT DPH), 23 HIV clinics and Yale University School of Medicine (YSM). Our site was one of 3 participants in the CDC-sponsored RCT evaluating the efficacy of DPH-employed Disease Intervention Specialists (DIS) for re-engagement in care.

Methods

From 11/2016-7/2018, a data reconciliation process using public health surveillance and clinic visit data was used to identify patients eligible for randomization (defined as in-Care for 12 months and OOC for subsequent 6-months) to receive DIS intervention. Clinic staff further reviewed this list and designated those who would not be randomized based on established criteria.

Results

2958 patients were eligible for randomization; 655 (22.1%) were randomized. Reasons for non-randomizing included: well patient [499 (16.9%)]; recent visit [946 (32.0%)]; upcoming visit [398 (13.5%)]. Compared to non-randomized patients, those who were randomized were likely to be younger (mean age 46.1 vs. 51.6, p < .001), Black (40% vs 35%)/Hispanic (37% vs 32.8%) [(p < .001)], have CD4<200 cells/ul (15.9% vs 8.5%, p < .001) and viral load >20 copies/ml (43.8% vs. 24.1%, 0<0.001). Extrapolating these estimates to a statewide HIV care continuum suggests that only 8.3% of prevalent PWH are truly OOC.

Conclusions

A D2C process that integrated DPH surveillance and clinic data successfully refined the selection of newly OOC PWH eligible for DIS intervention. This approach more accurately reflects real world care engagement and can help prioritize DPH resources.

Strategies to improve HIV care outcomes for people with HIV who are out of care

OBJECTIVE

The aim of this study was to evaluate the effectiveness of five intervention strategies: patient navigation, appointment help/alerts, psychosocial support, transportation/appointment accompaniment, and data-to-care on HIV care outcomes among persons with HIV (PWH) who are out of care (OOC).

DESIGN

A systematic review with meta-analysis.

METHODS

We searched CDC's Prevention Research Synthesis (PRS) Project's cumulative HIV database to identify intervention studies conducted in the U.S., published between 2000 and 2020 that included comparisons between groups or prepost, and reported at least one relevant outcome (i.e. re-engagement or retention in HIV care, and viral suppression). Effect sizes were meta-analyzed using random-effect models to assess intervention effectiveness.

RESULTS

Thirty-nine studies reporting on 42 unique interventions met the inclusion criteria. Overall, intervention strategies are effective in improving re-engagement in care [odds ratio (OR) = 1.79;95% confidence interval (95% CI): 1.36-2.36, k = 14], retention in care (OR = 2.01; 95% CI: 1.64-2.64, k = 22), and viral suppression (OR = 2.50;95% CI: 1.87-3.34, k = 27). Patient navigation, appointment help/alerts, psychosocial support, and transportation/appointment accompaniment improved all three HIV care outcomes. Data-to-care improved re-engagement and retention but had insufficient evidence for viral suppression.

CONCLUSION

Several strategies are effective for improving HIV care outcomes among PWH who are OOC. More work is still needed for consistent definitions of OOC and HIV care outcomes, better reporting of intervention and cost data, and identifying how best to implement and scale-up effective strategies to engage and retain OOC PWH in care and reach the ending the HIV epidemic goals.

"Is a Bird in the Hand Worth 5 in the Bush?": A Comparison of 3 Data-to-Care Referral Strategies on HIV Care Continuum Outcomes in San Francisco

Background

Health departments utilize HIV surveillance data to identify people with HIV (PWH) who need re-linkage to HIV care as part of an approach known as Data to Care (D2C.) The most accurate, effective, and efficient method of identifying PWH for re-linkage is unknown.

Methods

We evaluated referral and care continuum outcomes among PWH identified using 3 D2C referral strategies: health care providers, surveillance, and a combination list derived by matching an electronic medical record registry to HIV surveillance. PWH who were enrolled in the re-linkage intervention received short-term case management for up to 90 days. Relative risks and 95% confidence intervals were calculated to compare proportions of PWH retained and virally suppressed before and after re-linkage. Durable viral suppression was defined as having suppressed viral loads at all viral load measurements in the 12 months after re-linkage.

Results

After initial investigation, 233 (24%) of 954 referrals were located and enrolled in navigation. Although the numbers of surveillance and provider referrals were similar, 72% of enrolled PWH were identified by providers, 16% by surveillance, and 12% by combination list. Overall, retention and viral suppression improved, although relative increases in retention and viral suppression were only significant among individuals identified by surveillance or providers. Seventy percent of PWH who achieved viral suppression after the intervention remained durably virally suppressed.

Conclusions

PWH referred by providers were more likely to be located and enrolled in navigation than PWH identified by surveillance or combination lists. Overall, D2C re-linkage efforts improved retention, viral suppression, and durable viral suppression.