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Epidemiology

Cost-Effectiveness of HRSA's Ryan White HIV/AIDS Program?

Goyal, Ravi PhDa; Luca, Dara PhDa; Klein, Pamela W. PhDb; Morris, Eric MSa; Mandsager, Paul MSPHb; Cohen, Stacy M. MPHb; Hu, Cindy PhDa; Hotchkiss, John MSa; Gao, Jessica BAa; Jones, Andrew MAc; Addison, Westc; O'Brien-Strain, Margaret PhDc; Cheever, Laura W. MD, ScMb; Gilman, Boyd PhDa

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: February 1, 2021 - Volume 86 - Issue 2 - p 174-181
doi: 10.1097/QAI.0000000000002547
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Abstract

INTRODUCTION

The Ryan White HIV/AIDS Program (RWHAP), administered by the Health Resources and Services Administration with the U.S. Department of Health and Human Services, provides a comprehensive and integrated system of care for more than 500,000 low-income people with HIV, representing more than half of everyone living with diagnosed HIV in the United States.1 As the largest federal program focused exclusively on HIV care and treatment, the RWHAP's multidisciplinary approach to providing medical and support services addresses the complex needs of low-income people with HIV and reduces barriers that may otherwise impede improvements in HIV health outcomes.2

The RWHAP represents a substantial investment of public resources—representing the third largest source of federal funding for HIV care and treatment in the United States after Medicare and Medicaid.3,4 Understanding the cost-effectiveness of the program is critically important to funding decisions. Patients who receive care from RWHAP-funded facilities are more likely to receive antiretroviral therapy (ART) adherence counseling and other support services, remain in care, and reach viral suppression compared with those receiving services from non–RWHAP-funded facilities, after adjusting for differences in patient characteristics between the 2 types of facilities.5–7 However, little analysis has been done to quantify the long-term public health and economic impacts of the program. Nor has any study weighed the health care cost and outcomes related to the presence of the RWHAP relative to those that would exist without the program.

HIV cost-effectiveness models have long been used to assess single interventions, such as opportunistic infection prophylaxis, initiation of ART, routine HIV testing, pre-exposure prophylaxis, care coordination, and treatment adherence counseling.8–18 The results of these studies have been generally favorable and provide strong evidence that providing HIV medical care and treatment is cost-effective. However, capturing the impact of a complex system of care such as the RWHAP poses several unique challenges. Cost-effectiveness analyses of systems of care must, first, define the intervention being modeled and, second, identify the counterfactual under which people with HIV would no longer have access to program-funded services—both of which require complex decisions.

To investigate the long-term public health and economic impact of the RWHAP, we developed a mathematical model that captures the complexities of the HIV care system in the United States. The design and technical details of the model are described in a separate article published in this issue of the journal.19 In this study, we assume the reader understands the structure of the model and start by specifying the RWHAP-funded services being analyzed. We then define the counterfactual by estimating the percentage of people with HIV who would lose access to RWHAP-funded services without the program. Finally, using model simulation techniques, we estimate the long-term costs and population health impacts of the RWHAP relative to the counterfactual, and compare them to other recent studies of HIV care coordination. We also test the sensitivity of the results to the key model parameters.

METHODS

Overview of Mathematical Model

The cost-effectiveness of the RWHAP was estimated using an agent-based, stochastic model parameterized to represent the overall HIV epidemic in the United States. The model includes people with HIV who access services through the RWHAP and those who do not (including the undiagnosed), and people without HIV who are at non-negligible risk of contracting the virus. The model simulates an individual's progression through 7 stages (from diagnosis to viral suppression) and health states (by CD4 count and viral load) over a 50-year horizon.19 The model inputs are divided into 5 modules relating to (1) the demographic and risk characteristics of the population, and their service needs and receipt; (2) the transmission of HIV through sexual contact and injection drug use; (3) disease progression over time; (4) the probability of transitioning from one stage to another; and (5) monthly costs and quality of life.19

Defining Intervention Services and Their Impact on Retention and Viral Suppression

The model simulates the impact of 5 types of RWHAP-defined services on a person's care stage and health trajectory: outpatient ambulatory health services (OAHS), ART, medical case management (MCM), mental health and substance abuse (MH/SA) services, and other services. Health Resources and Services Administration defines OAHS as the provision of professional diagnostic and therapeutic services by a health care professional certified to prescribe ART in an outpatient setting.20 The other services category is a catch-all category that includes all other RWHAP-defined service categories, such as non-MCM and transportation.20 For presentation and to distinguish them from OAHS and ART, which are necessary components of care for all people with HIV, we refer to MCM, MH/SA, and other services jointly as ancillary services.

In the model, a person's HIV care stage and health state trajectory depend on the services they both need and receive. We assume that all people with HIV need OAHS and ART (which we refer to as core services), but not necessarily ancillary services. We also assume that the need for ancillary services among people with HIV varies based on their demographic and risk group characteristics. We assume that, after controlling for demographic and risk group characteristics, the need for core and ancillary services is the same for people who receive HIV care under the RWHAP and those who do not. By calculating need at the subgroup level (based on age, gender, race, and risk group) and allowing the proportion of people in each subgroup to vary between RWHAP and non-RWHAP systems, our model implies that the need for services is correlated with income (as reflected in RWHAP eligibility). Finally, we assume the proportion of people who receive a needed core or ancillary service varies depending on whether they are eligible for RWHAP-funded services.19

We estimated ancillary service need and receipt under both systems of care based on data from the Centers for Disease Control and Prevention's Medical Monitoring Project. Depending on the service, the proportion of patients with an unmet need is between 10% and 70% higher at non-RWHAP-funded than at RWHAP-funded facilities.7 Assuming they receive the ancillary services they need, they have a monthly probability of transitioning from care and treatment to viral suppression or to left care based on inputs from published sources.21 However, if they need but do not receive an ancillary service (ie, they have an unmet need), their probability of remaining in care or reaching viral suppression declines, whereas their probability of transitioning back to care and treatment without being virally suppressed or falling out of care increases. The diminishment in these transition probabilities increases as the number of different types of ancillary services a person needs but does not receive increases.19

Defining the Non-RWHAP Scenario

In the primary analysis, we measure the cost-effectiveness of the RWHAP as currently funded and implemented relative to a counterfactual scenario representing the absence of the RWHAP, which is defined by the lack of availability of the core and ancillary services the program pays for. Because many RWHAP clients access a subset of services under alternative sources of funding,22 we make a conservative assumption that, in the absence of the RWHAP, only uninsured clients would lose access to the medical and support services they need. We calculate the proportion of uninsured RWHAP clients by demographic and risk characteristics based on the client-level data reported in the 2016 RWHAP Services Report (RSR)22 and the 2016 AIDS Drug Assistance Program (ADAP) Data Report.23

Under the counterfactual scenario, the proportion of RWHAP clients who receive OAHS and ART (after subtracting the uninsured) falls from 100% to 57.6% (Table 1). Among those who need the service, the proportion of RWHAP clients who receive MCM because of loss of coverage falls from 93.5% to 75.9%, the proportion who receive MH/SA services falls from 84.0% to 72.2%, and the proportion who receive support and other noncore medical services falls from 78.7% to 62.0%. All other model parameters (including the proportion of people outside the RWHAP system who need and receive services) remain the same.

TABLE 1. - Definition of Unmet Need Among RWHAP Clients Under Counterfactual
All RWHAP Clients Uninsured RWHAP Clients RWHAP Clients Uninsured (%) Percentage of RWHAP Clients Who Received a Needed Service (%):
Before Uninsured Offset is Applied After Uninsured Offset is Applied
OAHS/ART 614,781 260,423 42.4 100.0 57.6
MCM 111,394 20,932 18.8 93.5 75.9
MH/SA 72,328 10,143 14.0 84.0 72.2
Support+ 342,747 72,721 21.2 78.7 62.0
Source: RWHAP Services Report and AIDS Drug Assistance Program Data Report, 2016.
Uninsured clients are defined as those who were reported in the RSR as having no health care coverage plus thus who received medication services under the ADAP. Receipt of medication services means that ADAP paid for 100 percent of the cost for a medication for a client. If ADAP is paying 100 percent of the cost for a medication, the client either has no insurance or functionally no insurance. We excluded 71,135 clients with missing values for race/ethnicity, risk factor, age, or gender, and clients younger than 13, older than 100, or transgender, and those not known to be HIV-positive. Uninsured offsets were calculated separately for each unique age, gender, race/ethnicity, and risk factor subgroup in the model. Offsets are applied against the percentage of RWHAP clients who need each type of service.
Support+, support and other noncore medical services.

Two factors explain the relatively large percentage of uninsured clients in the OAHS/ART category. First, a large proportion of RWHAP clients receives medication services (as opposed to insurance services, which includes coverage for premiums, copays, and deductibles) under ADAP, indicating that the RWHAP paid 100 percent of the cost of the medication. We assume that if the RWHAP pays 100 percent of the cost of the medication, the client either has no insurance or functionally (for the purpose of this analysis) no insurance as the plan does not cover ART. As a result, we assume that 42.4% of clients whose OAHS/ART is paid for by the RWHAP would not have another payer for these services in the absence of the program. Second, as the payer of last resort, the RWHAP cannot cover medical care if other payers (such as Medicaid or Medicare) are obligated to pay for the service. However, the program would be able to cover other wraparound and support services that are not covered by the client's insurance. Approximately 80 percent of RWHAP clients have some form of health care coverage. These clients are most likely accessing services beyond OAHS/ART, because their regular health care coverage does not support those services.

Population Health Outcomes and Cost Analysis

The economic analysis represents the perspective of the overall U.S. health care system (reflecting the cost of delivering services, rather than the amount paid by any given individual or payer), with incremental costs per quality-adjusted life year (QALY) used as the measure of cost-effectiveness. We also examined differences in the number of new HIV infections, deaths among people with HIV, and total health care costs between the 2 scenarios over 50 years. Following the guidelines of the U.S. Public Health Service Task Force, we discounted health outcomes and health care costs at an annual rate of 3 percent to reflect the lower economic value of a delayed benefit or expense.24,25 We adjusted costs for inflation assuming a 2.03 percent annual increase in medical expenses after the first year, based on the medical care component of the consumer price index. We estimated QALYs by CD4 count using utility weights from Tengs and Lin.26 We used an annual U.S. adult population growth rate of 0.57 percent.

We assumed that a person accumulates monthly costs from model entry to death or the end of the 50-year simulation. We estimated the average cost of medical care for people with HIV across the 5 RWHAP-eligible service categories defined above, plus hospital inpatient and emergency department (ED) services, which the RWHAP does not fund. We obtained cost estimates for hospital inpatient and ED services, OAHS, ART, and MH/SA services from the literature.27–29 Average costs for inpatient and ED services vary by health state and are inversely related to CD4 count. Average costs for OAHS, ART, and MH/SA services are constant across health states and CD4 count. We derived average cost estimates for MCM and support and other noncore medical services from the 2016 RSR and 2016 RWHAP allocation reports.22,23

Sensitivity Analyses

We conducted one-way sensitivity analyses to assess the impact of key model parameters on the incremental cost-effectiveness ratio (ICER). We focused on model parameters that had a relatively high degree of uncertainty or were likely to be important determinants of cost-effectiveness (Table 2). Whenever possible, we used variance estimates reported in the literature to inform the range we tested. In other cases, we assumed an increase or decrease of 15 percent from the base case parameter value. For input parameters expressed in matrix form (eg, service needs by demographic and risk group), we varied all values concurrently by the same percentage. Parameter values were varied the same for the RWHAP and counterfactual scenarios.

TABLE 2. - Ranges of Parameter Values of Inputs Used in Sensitivity Analysis
Parameter Current Value Low High Variance/Source
Proportion of all people with HIV who need ancillary services Based on input matrix* ±15%
Proportion of RWHAP clients who need ancillary services Based on input matrix* ±15%
Proportion of RWHAP clients who receive ancillary services Based on input matrix* ±15%
 MCM only Based on input matrix* ±15%
 MH/SA only Based on input matrix* ±15%
 SS only Based on input matrix* ±15%
Proportion of discordant partners
 MSM 0.6 0.51 0.69 ±15%
 IDU 0.04 0.03 0.05 ±15%
 Heterosexual contact 0.5 0.43 0.58 ±15%
Probability of transmitting HIV through MSM contact (x heterosexual contact rate) 3 times ±15%
Monthly probabilities
 HIV-Positive but undiagnosed (stage 2) to diagnosed (stage 3) Based on input matrix* ±15%
 Diagnosed (stage 3) to care and treatment (stage 4) 0.237 0.069 0.413 Medland et al (2014)
 Care and treatment (stage 4) to viral suppression (stage 5) 0.259 0.220 0.300 ±15%
 Care and treatment (stage 4) or viral suppression (stage 5) to left care (stage 6) 0.00625 0.00530 0.00710 ±15%
 Viral suppression (stage 5) to care and treatment (stage 4) 0.0065 0.00633 0.00667 O'Conner et al (2017)
 Left care (stage 6) to care and treatment (stage 4) 0.0141 0.0120 0.0162 15%
 Stages 1–6 to death (stage 7) Based on input matrix* ±15%
Impact of ancillary services on:
 Retention in care and treatment (transition from stages 4 and 5 to stage 6) Based on input matrix* ±15%
 Viral suppression (transition from stage 4 to stage 5) Based on input matrix* ±15%
 Quality of life weights Based on input matrix* Tengs and Lin26
Monthly costs
 ART $1374 $1168 $1580 ±15%
 OAHS $120 $102 $138 ±15%
 MCM $224 $190 $258 ±15%
 MH/SA $385 $327 $443 ±15%
 SS $98 $83 $113 ±15%
*Sensitivity tests are based on input matrices presented in technical supplement to Goyal et al19.

Both the percentages of people with HIV who need an ancillary service and those who receive the services they need are critical inputs in the model. Because we assume that service need is the same for RWHAP and non-RWHAP populations, we varied the proportion who need a service in both populations (by demographic and risk group) by 15 percent. When examining the receipt of ancillary services, we also varied the percentage of people who receive the services they need in both RWHAP and non-RWHAP populations. We examined the sensitivity of the model results to the receipt of all 3 ancillary services jointly and individually.

RESULTS

Results of Primary Analysis

The RWHAP is predicted to generate an additional $165 billion (25 percent) in health care-related costs over 50 years compared with the non-RWHAP scenario because of there being more people with HIV living longer and healthier lives under the program (Fig. 1). The cumulative cost of outpatient services are 35 percent higher under the RWHAP scenario, reflecting the larger number of people who are in care and treatment and receiving the services they need under the RWHAP scenario. In contrast, cumulative costs associated with hospitalizations and ED visits are 14 percent lower under the RWHAP, as health outcomes improve and people have fewer acute care episodes. Under both scenarios, ART constitutes the largest share of costs (63 percent under the RWHAP scenario versus 59 percent in the non-RWHAP scenario), followed by inpatient care (16 percent under the RWHAP scenario versus 23 percent under the non-RWHAP scenario).

F1
FIGURE 1.:
Comparison of lifetime costs between RWHAP and non-RWHAP scenarios, measured over a 50-year time horizon.

The proportion of people with HIV who are ever engaged in care and treatment is 24.5 percentage points higher (88.3 percent versus 63.8 percent) in the presence of the RWHAP (Table 3), reflecting the gain in access to care and treatment for uninsured people with HIV. Similarly, the proportion of people with HIV who are ever virally suppressed is 25.2 percentage points higher (82.6 percent with the RWHAP with versus 57.4 percent without the RWHAP). In contrast, the proportion of people with HIV who are ever lost to care is 11.3 percentage points lower in the presence of the RWHAP (3.4 percent versus 14.7 percent).

TABLE 3. - Comparison of Cost-Effectiveness Results Between RWHAP and Non-RWHAP Scenarios, Measured Over a 50-Year Time Horizon
Outcome RWHAP Scenario Non-RWHAP Scenario Difference
Percentage of people with HIV who were ever:
 In care and treatment (%) 88.3 63.8 24.5
 Lost to care and treatment (%) 3.4 14.7 −11.3
 Virally suppressed (%) 82.6 57.4 25.2
Health outcomes
 No. of new HIV infections 844,550 1,034,747 −190,197
 No. of deaths among people with HIV 600,865 868,752 −267,886
 No. of life yr (in millions) 217.0 211.6 5.4
 No. of QALYs (in millions) 211.2 205.6 5.6
Total costs (in millions) $825,963 $660,815 $165,148
Cost per QALY $2147 $1769 $378
ICER $29,573 n.a n.a
The ICER is based on incremental costs divided by incremental QALYs. Due to rounding, the ICER may not equal the ratio of incremental costs to incremental QALYs as reported in the table.

People with HIV who are virally suppressed have a significantly reduced risk of transmitting HIV to others. As a result of improved access to care and treatment, the number of new HIV infections is predicted to fall by 190,197 over 50 years under the RWHAP, a reduction of 18 percent compared with the number of new infections without the RWHAP. In addition, the RWHAP will reduce the number of all-cause deaths among people with HIV by 267,886 (31 percent) and increase the total number of life years by 5.4 million (2.6 percent) and QALYs by 5.6 million (2.7 percent) over the 50-year simulation relative to the non-RWHAP scenario.

Based on results of the model, the RWHAP is estimated to have an ICER of $29,573 per QALY gained compared with the non-RWHAP scenario (Table 3). Using the guidelines of the World Health Organization (WHO) for assessing cost-effectiveness, the RWHAP would be considered very cost-effective because it is less than the per capita gross domestic product in the United States of $57,467 in 2016.30

Results of Sensitivity Analysis

Figure 2 shows the change in the ICER for the most influential model parameters. The probability of transmitting HIV via male-to-male (MSM) sexual contact has the largest effect on the ICER, ranging from $23,717 to $38,082 per QALY gained as we varied the original value by 15 percent. The cost of ART was the second most influential parameter, followed by the proportion of discordant partners among MSM, and the receipt of ancillary services. Among ancillary services, the receipt of noncore medical and support services has the largest effect on the cost-effectiveness of the program. The remainder of the parameters we tested did not have a substantial effect on the ICER. In all cases, the RWHAP would still be considered very cost-effective using WHO guidelines. The consistently favorable results are primarily because of the fact that the RWHAP provides a large number of people with HIV without alternative sources of coverage access to care and treatment and thereby achieve viral suppression. The increased availability of ancillary services to keep people in care and virally suppressed also contributes to the overall cost-effectiveness of the program. Given the efficacy of treatment to mitigate transmission, the only situation in which the RWHAP may not be cost-effective is if prescription medications become extremely costly.

F2
FIGURE 2.:
Change in ICER based on varying the value of key model parameters. Note. The value ranges used for the sensitivity analysis are presented in Table 2. Stage 1 = HIV negative, stage 2 = undiagnosed, stage 3 = diagnosed, stage 4 = care and treatment, stage 5 = viral suppression, stage 6 = Left care, stage 7 = death.

DISCUSSION

Our model demonstrates that, over a 50-year horizon, the RWHAP increases the proportion of people with HIV who are in care and treatment by 38 percent and virally suppressed by 44 percent, relative to the counterfactual. In addition, the RWHAP reduces the number of new HIV infections by 18 percent (267,886), increases the number of QALYs by 2.7 percent (5.6 million), and reduces the number of deaths among people with HIV by 31 percent (267,886). The model also shows that the RWHAP produces an ICER of $29,573 per QALY gained, and the result is robust to the model's input values.

The model results are based on 3 key assumptions. First, we assumed that in the absence of the RWHAP, only uninsured clients lose access to outpatient medical and support services. It is likely that, without the RWHAP, many insured clients would also lose access to some services, particularly ancillary services critical for helping people with HIV stay in care and adherent to treatment and reach viral suppression. RWHAP also pays for health care coverage for many people with HIV, and therefore some clients would lose access to full health care coverage benefits in the absence of the program. Second, we assumed that people eligible for the RWHAP have the same chance of entering care and treatment as those who are not. However, the RWHAP also funds early intervention services to facilitate linkage to care and treatment after diagnosis. If these services increase the rate of transition to care and treatment among newly diagnosed clients, the model will likely underestimate the cost-effectiveness of the program. Third, we assumed that the need for services (conditional on a person's demographic and risk profile) is the same in both systems of care. If people who access care and treatment through the RWHAP face greater needs than those who access services outside the RWHAP system (controlling for differences in their demographic and risk group characteristics), the model will likely underestimate the cost-effectiveness of the program.

Although the RWHAP represents a complex system of care and cannot be compared directly to single HIV treatment interventions, its ICER compares favorably to other U.S.-based HIV care and treatment initiatives. Freedberg et al31 evaluated the cost-effectiveness of three-drug ART regimens (compared to no therapy) and reported an ICER of $23,000 per QALY. Weinstein et al estimated an ICER of $17,900 for genotypic resistance testing at treatment failure, and Sax et al reported an ICER of $20,200 for genotypic resistance testing among treatment-naïve patients.32,33 In contrast, Bernard et al14 found that a three-pronged intervention for adults who use inject drugs based on pre-exposure prophylaxis with frequent screening and enhanced provision of ART for those who become infected was not cost-effective, even at the $100,000 threshold.

Three recent studies on the cost-effectiveness of care coordination programs for people with HIV are particularly useful points of comparison. Flash et al12 examined the cost-effectiveness of a two-year HIV care coordination program in Los Angeles County and produced an overall ICER of $27,400, but the favorable results disappear when estimated over a lower acuity population. Stevens et al13 estimated the cost-effectiveness of a local HIV care coordination program if it were expanded to all people with HIV in New York City. The authors concluded that broad scale-up of the care coordination program in New York City was not likely to be cost-effective at current costs and observed levels of effectiveness, but may become so in cities with lower baseline viral suppression rates. Both studies focused on people at risk of poor health outcomes, and thus the results are not directly comparable to our study which is based on the overall HIV population in the United States. Finally, Krebs et al11 conducted a cost-effectiveness analysis of 16 HIV interventions—including 7 related to engagement and re-engagement in care and treatment—in 6 cities with varying degrees of unmet need. The authors found that several of the interventions were cost-effective at the $100,000 threshold, but only in cities where people had access to high-quality HIV care and treatment services.

Our study is subject to several limitations. First, the model captures outcomes over a 50-year period, but some individuals will remain alive at the end of the simulation. Thus, we cannot assess the impact of the RWHAP on life expectancy because there will be model agents still alive at the end of the simulation. Second, most estimates stem from values derived from published data, such as the proportion of people with HIV who need and receive services and the probability of transmitting HIV through MSM contact.5,22,34–37 These values were derived from a review of current literature, but the settings from which the estimates were derived may not be generalizable to our model setting. Lack of available data required us to estimate the values of several parameters using calibration techniques. However, we validated key model outputs by comparing them against external benchmarks.19 Furthermore, we assessed the sensitivity of the ICER results and found that the program remained cost-effective in all cases. Third, the model results are based on HIV cost estimates that may not reflect current care and treatment patterns for people with HIV. Nor do they reflect differences in outpatient medical or ancillary service costs across disease states. Higher cost prescription medications would likely reduce the cost-effectiveness of the program. Finally, as mentioned earlier, this study treats the RWHAP as a single, comprehensive, integrated system of care and treatment, rather than a collection of distinct interventions or services. The RWHAP legislation specifies these individual service categories; RWHAP recipients to make their own service delivery decisions based on the needs of the communities they serve. Therefore, in this analysis, we focused on the cost-effectiveness of the entire RWHAP system of care rather than the cost-effectiveness of individual services.

Our results suggest that the RWHAP plays a critical role in the U.S. public health response to the HIV epidemic and, based on WHO evaluation guidelines, it represents a cost-effective use of public resources. Without the RWHAP, a significant proportion of people with HIV would lose access to care and treatment and the ancillary services that help them become and remain virally suppressed. By improving access to care and treatment among low-income people with limited or no health care coverage, the RWHAP serves as an important source of access to medications for people with HIV that can improve their quality of life and prevent the spread of the disease. In future work, we will use the model to investigate additional scenarios—including the goals of the Ending the HIV Epidemic initiative—that further examine the role of the RWHAP in the evolving HIV care system.38

ACKNOWLEDGMENTS

This paper was made possible by the contributions of the Ryan White HIV/AIDS Program grant recipients and subrecipients that provided data to HRSA.

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Keywords:

HIV/AIDS; health care cost; HRSA; RWHAP; cost-effectiveness; mathematical modeling

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