JAIDS Journal of Acquired Immune Deficiency Syndromes:
Epidemiology and Prevention
Cost Effectiveness of the National HIV/AIDS Strategy Goal of Increasing Linkage to Care for HIV-Infected Persons
Gopalappa, Chaitra PhD; Farnham, Paul G. PhD; Hutchinson, Angela B. PhD; Sansom, Stephanie L. PhD
Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA.
Correspondence to: Chaitra Gopalappa, PhD, Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, 1600 Clifton Rd, NE, MS E-48, Atlanta, GA 30333 (e-mail: email@example.com).
No direct funding was received for this study. The authors were personally salaried by their institutions during the period of writing (although no specific salary was set aside or given for the writing of this article). No funding bodies had any role in the study design, data collection, analysis, decision to publish, or preparation of the manuscript.
Presented at the National HIV Prevention Conference, August 2011, Atlanta, GA and Institute for Operations Research and Management Science Annual Meeting, November 13–16, 2011, Charlotte, NC.
The authors have no conflicts of interest to disclose.
The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.
Supplemental digital content is available for this article. Direct URL citations seen in the printed text and are provided in the HTML and PDF versions of this article on the Web site of the journal (www.jaids.com).
Received December 21, 2011
Accepted April 19, 2012
Background: One of the goals of the National HIV/AIDS Strategy (NHAS) is to increase the proportion of HIV-infected individuals linked to care within 3 months of diagnosis (early linkage) from 65% to 85%. Earlier access to care, and eventually, to treatment, increases life expectancy and quality of life for HIV-infected persons. However, longer treatment is also associated with higher costs, especially for antiretroviral drugs. We evaluated the cost effectiveness of achieving the NHAS goal and estimated the maximum cost that HIV programs could spend on linkage to care and remain cost effective.
Methods: We used the Progression and Transmission of HIV/AIDS model to estimate the effects on life measures and costs associated with increasing early linkage to care from 65% to 85%. We estimated an incremental cost-effectiveness ratio as the additional cost required to reach the target divided by the quality-adjusted life years (QALYs) gained and assumed that programs costing $100,000 or less per QALY gained are cost effective.
Results: Achieving the NHAS linkage-to-care goal increased life expectancy by 0.4 years and delayed the onset of AIDS by 1.2 years on average for every HIV-diagnosed person. Increasing early linkage to care cost an extra $62,200 per QALY gained, considering only benefits to index persons. The maximum that could be cost effectively spent on early linkage-to-care interventions was approximately $5100 per HIV-diagnosed person.
Conclusions: Considerable investment can be cost effectively made to achieve the NHAS goal on early linkage to care.
Antiretroviral therapy (ART) for treatment of HIV infection halved the number of years of life lost to infection between 1996 and 1999 and 2003 and 2005 from approximately 20 to 10 years.1 In addition, approximately 80% of persons on ART are estimated to achieve viral load suppression.2–4 Studies among serodiscordant couples have documented a 90% to 96% reduction in heterosexual transmission when the HIV-infected partner is on ART.5,6 However, only an estimated 65% of individuals are linked to care within 3 months of diagnosis, while the rest delay care and treatment until the disease has further advanced.7–9 Thus, the benefits of treatment in improving life expectancy, quality of life, and HIV prevention cannot be fully realized without increasing linkage to care.10
One of the goals of the National HIV/AIDS Strategy (NHAS),11 is to increase the proportion of people linked to care early, that is, within 3 months of diagnosis, from the current 65% to 85%. In this article, we defined being in care as timely monitoring of CD4 counts and viral load, with the opportunity to start ART at the appropriate CD4 count. We analyzed the cost effectiveness of achieving the NHAS goal of linking 85% of individuals to care within 3 months of diagnosis (early care) using the linkage intervention from the Antiretroviral Treatment Access Study (ARTAS).12 We also estimated the maximum cost that could be spent to achieve 85% linkage and remain within cost-effectiveness thresholds.
We used a model developed by the Division of HIV/AIDS Prevention in the US Centers for Disease Control and Prevention to estimate the lifetime measures and costs for HIV-infected individuals under different linkage-to-care scenarios. The Progression and Transmission of HIV/AIDS (PATH) model13 is a Monte Carlo simulation health state transition model that individually tracks a first generation of HIV-infected persons (index persons) and the partners they infect from the time of infection to death. During the simulation, the model generates events such as testing, initiation of treatment, and change of ART regimen. The model updates HIV-specific parameters, including CD4 cell count, viral load, opportunistic infection (OI) incidence, onset of AIDS and HIV transmission to sexual or needle-sharing partners during every calendar quarter of a year based on disease stage and treatment status. The model also estimates costs incurred during the quarter, such as those for HIV diagnosis, treatment, follow-up CD4 cell count and RNA tests, health care utilization, and OI treatment, and assigns quality-adjusted life-year (QALY) estimates based on the CD4 count during the quarter. All costs are reported in year 2009 $US and a discount rate of 3% was applied when estimating lifetime costs. The lifetime costs were estimated by applying drug and utilization costs and a linkage-to-care intervention cost. We also included QALY gained, thereby generating a societal perspective, although we did not capture costs for linkage-to-care program participation for the newly diagnosed. Further details of the model along with the parameter values used in the simulations are presented in Supplemental Digital Content 1 (http://links.lww.com/QAI/A331).
Linkage-To-Care Scenarios (Base Case Analysis)
We ran the PATH model for 10,000 individuals newly infected with HIV (index persons) under each of 2 linkage-to-care scenarios that we will refer to as current practice and NHAS goal scenarios. Before outlining the difference between the 2 scenarios, we note below the assumptions common to both scenarios.
Linkage to care is only one component of the HIV-treatment cascade of care.2,14 Two other main components are diagnosis and retention in care. Individuals are diagnosed at different CD4 counts, and some individuals in care dropout and reenter care after different periods in time. We assumed the following cumulative distribution for CD4 count at diagnosis: minimum of 4 cells/μL, the 25th, 50th, and 75th percentile values as 185, 356, and 535 cells/μL, respectively, and a maximum of 900 cells/μL.15,16 For retention in care, we assumed that of those linked to care only 25% were retained until death, 40% dropped out of treatment after 2 years, and the remaining 35% dropped out after 4 years.8 We also assumed that after dropping out of care on average, 45% of individuals would reenter within 1–2 years, 45% would reenter when their CD4 count decreased to 200 cells/μL, and 10% when their CD4 count decreased to 40 cells/μL.2 Because of the lack of data on disease progression for individuals between dropping out and reentering care, we assumed that the viral load level and rate of CD4 count decline were the same as in the period before initiating treatment. We also assumed that dropping out of treatment would create resistance to the regimen and hence, upon reentry to care, the individual would start with the next line of therapy.
In addition, we assigned normal distributions to input variables associated with disease progression, such as age at infection, CD4 count at infection, viral load set point, the viral load values associated with suppression when on ART, with rebound when ART fails, and when on salvage therapy, and the rate of decline in CD4 count in specific viral load strata (for the list of values, see Table, Supplemental Digital Content 1, http://links.lww.com/QAI/A331).
We assumed that for the current practice (and NHAS goal) scenario, 65% (and 85%) of those newly diagnosed were linked to care early, that is, within 3 months of diagnosis,7,8,17–19 and began treatment at a CD4 count of 350 cells/μL or less.20 For the rest of the 35% (and 20%) who did not link to care early, we assumed that they would link to care and start treatment when their CD4 count decreased to the AIDS-defining stage of 200 cells/μL if they were diagnosed above a CD4 count of 200 cells/μL, or when their CD4 count decreased to 40 cells/μL if they were diagnosed below a CD4 count of 200 cells/μL. We also ran the simulation model under a second case where, for those linking to care early, we changed the decision rule for treatment initiation from a CD4 count of 350–500 cells/μL, consistent with the US Department of Health and Human Services HIV-treatment recommendations.20 To achieve the NHAS goal of increasing the proportion of persons linked to care early, we assumed a case-management–type intervention based on ARTAS.12
ARTAS Intervention Program
ARTAS was a brief case-management intervention trial for increasing linkage to care for recently diagnosed HIV-infected persons in the United States.12,21 The intervention included up to 5 sessions with a case manager over a 90-day period. Approximately 78% of people who received the intervention visited a HIV clinic at least once within 6 months compared with 60% of the control group (standard care) participants, who received informational pamphlets and passive referral to HIV care providers. Although the efficacy of the intervention when averaged over all implementation sites was only 78%, which is less than the NHAS goal of 85%, the efficacy was 87% when averaged over only those sites that had an HIV primary care facility.22 Therefore, we assumed that an ARTAS-type intervention could provide the targeted goal of 85% linkage at HIV primary care facilities at an estimated cost of $790 per newly diagnosed client (US 2009 $).12 We added this cost for each index person in the NHAS goal scenario.
We simulated the PATH model for 10,000 index (newly infected with HIV) persons under the current practice and NHAS goal scenarios. To analyze the cost effectiveness of achieving the NHAS goal, we estimated the following lifetime measures and costs averaged over the 10,000 index persons in each scenario: undiscounted life expectancy from time of infection, undiscounted time to onset of AIDS from time of infection, undiscounted and discounted QALYs lost to infection, and discounted lifetime program and treatment costs of HIV. We further estimated an incremental cost-effectiveness ratio (ICER) as the difference in the average discounted lifetime costs between the 2 scenarios divided by the difference in the average discounted QALYs lost to infection between the 2 scenarios. We also obtained a threshold estimate for a linkage-to-care program cost below which the intervention would be cost effective, that is, the maximum cost that could be added to the average discounted lifetime cost in the NHAS goal scenario to generate an ICER of $100,000 or less per QALY gained.23–25 Under each linkage-to-care scenario, we also simulated a second generation of HIV-infected individuals arising from transmissions from the index persons, and we estimated their corresponding HIV-related costs and QALYs.
Variability Measure in Cost Effectiveness
We ran the above simulation 100 times each with 10,000 individuals, estimating a threshold intervention program cost and ICER in each run, and used those 100 values to determine the variability in the threshold cost and ICER values, that is, we estimated the average, median, and 95% confidence interval values over the 100 runs. We also obtained a cost-effectiveness acceptability curve on the ICER values.
To further explore the individual effects of the CD4 count at diagnosis and retention in care assumptions on the variability in the model results, we performed the following sensitivity analyses:
1. CD4 count at diagnosis: We assumed that individuals would be diagnosed at a CD4 count based on the distribution described in the base case analysis, but we kept all other variables at their constant mean values (for the list of values, see Table, Supplemental Digital Content 1, http://links.lww.com/QAI/A331). To eliminate the effect of dropping out of care, we assumed 100% retention. The current and NHAS goal scenarios were assumed to be the same as in the base case analysis, and we continued to use the 2 treatment initiation decision rules of ART initiation at a CD4 count of 350 cells/μL or less and 500 cells/μL or less.
2. Retention in care: We assumed individuals would drop out of care and reenter care based on the step function described in the base case analysis, but we kept all other parameters at their constant mean values (see Table, Supplemental Digital Content 1, http://links.lww.com/QAI/A331). The CD4 count at diagnosis was kept constant at 350 cells/μL for all persons in the model. For the current practice (and NHAS goal) scenario, we assumed that of those newly diagnosed: 65% (and 85%) were linked to care within 3 months of diagnosis and hence would start treatment at the time of diagnosis, that is, at a CD4 count of 350 cells/μL; 15% (and 10%) would delay care and start treatment when their CD4 count dropped to an AIDS-defining value of 200 cells/μL; and the remaining 20% (and 5%) would delay care until they were very sick and start treatment when their CD4 count dropped to 40 cells/μL.
Base Case Analysis
We present results as the median value over the 100 runs, where in each run the value was estimated as the average per index person. Under the NHAS goal scenario, where 85% of individuals newly diagnosed with HIV were linked to care early compared with 65% in current practice, life expectancy increased to 30.7 from 30.3 (to 30.8 from 30.3) years per index person, when the decision rule for ART initiation was set at a CD4 count of 350 cells/mL (500 cells/mL) (Table 1). The onset of AIDS was delayed to approximately 14 from 12.8 years per index person under both decision rules for ART initiation. The discounted values of total lifetime costs of HIV for an index person increased by $13,300 ($18,600) and those of QALY increased by 0.2 (0.3) when the decision rule for ART initiation was set at a CD4 count of 350 cells/μL (500 cells/μL) (Table 1). Thus, the cost per QALY gained of linking 85% of individuals to care early, compared with 65%, was approximately $62,200 ($80,500). Our threshold analysis indicated that up to $8900 ($5100) could be spent to link each newly diagnosed person to care and still be cost effective when the decision rule for ART initiation was set at a CD4 count of 350 cells/μL (500 cells/μL) (Table 1).
In the base case, under both ART initiation decision rules, health care utilization, ART drugs, and costs of OI constituted approximately 25%, 73%, and 2% of the total lifetime costs. The NHAS goal scenario incurred about $2400 more per person for utilization costs and $400 less per person for the OIs cost compared with the current practice scenario under both ART initiation rules. The cost of ART drugs increased by $10,000 ($15,000) per person in the NHAS goal compared with current practice under an ART initiation rule of ≤350 (≤500) cells/μL (data not shown).
We estimated the lifetime number of HIV transmissions averted per index person under the NHAS goal linkage scenario compared with the current practice scenario to be 0.01 under both decision rules of ART initiation. This difference was not statistically significant (data not shown). Consequently, our results, including those described here and presented in Table 1 and Figures 1 and 2, reflect benefits of early linkage to care to index persons only.
When we allowed only the CD4 count at diagnosis of HIV-infected persons to vary widely in the current practice and NHAS goal scenarios, kept all other variables at constant levels, and assumed 100% retention in care, the incremental cost per QALY gained by achieving the NHAS goal was $69,200 ($84,800) when the decision rule for treatment initiation was set at a CD4 count of ≤350 cells/μL (≤500 cells/μL) (Table 1). When the assumption about retention and reentry to case was kept at base case levels, but all other variables were held constant, including a constant CD4 count at diagnosis of 350 cells/μL, the incremental cost per QALY gained by achieving the NHAS goal was $50,400.
Variability in Cost Effectiveness
The likelihood that achieving the NHAS goal will have an incremental cost per QALY gained of $100,000 or less was approximately 93% when the decision rule for treatment initiation was set at a CD4 count ≤350 cells/μL and 75% when the decision rule for treatment initiation was set at a CD4 count ≤500 cells/μL under the base case analysis (Fig. 1). The major source of variability in the incremental cost per QALY values resulted from the variation in the CD4 count at diagnosis as can be seen in the variability measures plotted in Figure 2 (ART initiation was set at CD4 350 cells/μL).
The results of our study quantify the cost effectiveness of the NHAS goal with respect to early linkage to care. With guidelines moving toward starting treatment at early stages in the infection,26 linkage to care, in addition to early diagnosis, may become an important component in starting individuals on treatment early. In this study, we provide program planners with an estimate of the maximum cost that can be spent on linkage-to-care programs and still be cost effective.
In the base case, we showed that expanding the proportion of HIV-infected individuals linked to care within 3 months of diagnosis from 65% to 85% resulted in an average gain of 0.4 years of life in a cohort of HIV-infected individuals and an average delay in the onset of AIDS of 1.2 years. These results occurred under the decision rules for initiating ART at both 350 and 500 cells/μL. The expansion in early linkage to care was cost effective at $62,200 per QALY (ART initiation at 350 cells/μL) and $80,500 per QALY (ART initiation at 500 cells/μL). The cost effectiveness acceptability curve showed that there was a high probability that the intervention was cost effective at the $100,000 per QALY threshold. Our results also indicated that communities or organizations could spend up to $8900 ($5100) to link each diagnosed person and remain within the cost-effectiveness threshold. When only the CD4 count at diagnosis was varied based on a distribution and all other variables were kept at constant levels, the resulting cost-effectiveness values had a large variability. When only retention and reentry to care varied according to a step function and all other variables were kept at constant levels, the resulting cost-effectiveness values had almost no variability. This indicates that the main source of variation in the cost-effectiveness values in the base case resulted from the variation in CD4 count at diagnosis. However, when only retention and reentry to care varied, the ICER was less than that in the base case because of the assumption of the constant and early CD4 count at diagnosis value of 350 cells/μL.
Although the threshold program cost that could be spent on the linkage-to-care intervention is higher than the ARTAS program cost, population-specific programs, or programs that vary in the number and type of counseling sessions, might incur higher costs.27–30 In addition, the cost of an intervention might not be linearly related to the increase in the proportion of people linked to care early. That is, while it might cost a certain amount to get the first 5-percentage point increase in the proportion, the cost to get the next 5-percentage point increase might be higher. On the other hand, our threshold program costs were estimated assuming that an intervention would apply to all who are diagnosed. However, as observed in the ARTAS trial, 60% of individuals in the control arm linked to care within 6 months of diagnosis without the ARTAS intervention, and hence, linkage interventions could be designed to target only those who delay entry into care. In such a case, a higher cost per person could be spent without exceeding the cost-effectiveness threshold. Overall, there are few published studies on efficacious linkage-to-care programs and their costs. More work is needed to determine population-specific efficacy and costs of these programs.
An increase in early linkage to care did not significantly decrease the average number of lifetime transmissions per HIV-diagnosed index person. This is largely because the percent linked to care at diagnosis in the current practice scenario was already fairly high (65% of diagnosed index persons), the percentage in the NHAS goal scenario was increased by only 20 percentage points, and we measured only first level transmissions. However, other analyses have indicated that an increase in early linkage reduces new cases of HIV over a longer period of time and more so when combined with increased efficacies in improving the other components on the cascade of care.13,31
The cost effectiveness of using an ARTAS-type intervention to achieve the NHAS linkage-to-care goal is similar to that of other interventions. For example, interventions promoting adherence to ART varied from $1300 per QALY gained to $90,000 per QALY gained32–35; evidence-based behavioral interventions for HIV-negative persons at highest risk for acquiring HIV ranged from cost saving to $176,619 per QALY gained36–39; newborn and adult male circumcision varied from cost saving to $90,83840,41; and routine HIV testing or screening varied from $34,000 per QALY gained to $144,130 per QALY gained.42–45 With the change in guidelines toward earlier initiation of ART, interventions for linking people into care early may become more essential especially if individuals resist treatment because they feel healthy.
Although several studies identify barriers to HIV medical care and some describe linkage-to-care interventions,7,29,30,46 the ARTAS is the only study currently available that provides the costs and efficacy results of a linkage-to-care intervention. Also, efficacy in ARTAS was measured as the proportion of HIV-infected persons linking to care within 6 months from the time of intervention. We assumed that similar levels of effectiveness could be obtained in linking diagnosed individuals to care within 3 months as defined in our scenarios. In our analysis, we projected only one level of transmission, thus underestimating transmissions averted from infected partners to subsequent rounds of partners. Although guidelines recommend initiating treatment at a CD4 count of 500 cells/μL or higher, there is uncertainty regarding the magnitude of the health benefits to index patients of starting treatment higher than at a CD4 count of 350 cells/μL. Hence, we used similar disease progression and treatment efficacy assumptions while setting the decision rule for treatment initiation at ≤500 cells/μL and ≤350 cells/μL.
Our analysis showed that intervention programs to increase (by 20 percentage points) the proportion of HIV-infected people linked to care within 3 months of diagnosis are cost effective, and a considerable amount can be spent on a linkage-to-care intervention per HIV-diagnosed person. Although the ARTAS intervention cost is well below the estimated threshold cost, intervention programs targeting specific populations might be more expensive. Our analysis also indicated a high likelihood that the cost per QALYs gained would be less than or at $100,000, and the CD4 count at diagnosis appeared to be the most sensitive variable in the cost effectiveness of linkage to care. Early linkage-to-care and treatment initiation provides significantly improved life expectancy for HIV-infected persons and is likely to play an important role in HIV prevention and care services.
We would like to thank Dr James D. Heffelfinger, Dr Paul Weidle, and Dr John T. Brooks from Centers for Disease Control and Prevention, Atlanta, GA and Dr David Rimland from Veterans Affair Medical Center, Decatur, GA, for their contribution on input parameters to the PATH model. We also thank Dr Ya-Lin Huang for extracting the cost-effectiveness estimates of other interventions in the literature.
1. Hogg R, Lima V, Sterne JAC, et al.. Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies. Lancet. 2008;372:293–299.
2. Gardner EM, McLees MP, Steiner JF, et al.. The spectrum of engagement in HIV care and its relevance to test-and-treat strategies for prevention of HIV infection. Clin Infect Dis. 2011;52:793–800.
3. Das M, Chu PL, Santos GM, et al.. Decreases in community viral load are accompanied by reductions in new HIV infections in San Francisco. PLoS One. 2010;5:e11068.
4. Gill VS, Lima VD, Zhang W, et al.. Improved virological outcomes in British Columbia concomitant with decreasing incidence of HIV type 1 drug resistance detection. Clin Infect Dis. 2010;50:98–105.
5. Attia S, Egger M, Muller M, et al.. Sexual transmission of HIV according to viral load and antiretroviral therapy: systematic review and meta-analysis. AIDS. 2009;23:1397–1404.
6. Cohen MS, Chen YQ, McCauley M, et al.. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365:493–505.
7. Torian LV, Wiewel EW, Liu KL, et al.. Risk factors for delayed initiation of medical care after diagnosis of human immunodeficiency virus. Arch Intern Med. 2008;168:1181–1187.
8. Marks G, Gardner LI, Craw J, et al.. Entry and retention in medical care among HIV-diagnosed persons: a meta-analysis. AIDS. 2010;24:2665–2678.
9. Torian LV, Wiewel EW. Continuity of HIV-related medical care, New York City, 2005-2009: do patients who initiate care stay in care? AIDS Patient Care STDS. 2011;25:79–88.
10. Mugavero MJ, Amico KR, Westfall AO, et al.. Early retention in HIV care and viral load suppression: implications for a test and treat approach to HIV prevention. J Acquir Immune Defic Syndr. 2012;59:86–93.
12. Gardner LI, Metsch LR, Anderson-Mahoney P, et al.. Efficacy of a brief case management intervention to link recently diagnosed HIV-infected persons to care. AIDS. 2005;19:423–431.
13. Prabhu VS, Farnham PG, Hutchinson AB, et al.. Cost-effectiveness of HIV screening in STD clinics, emergency departments, and inpatient units: a model-based analysis. PLoS One. 2011;6:e19936.
14. Vital signs: HIV prevention through care and treatment—United States. Morb Mortal Wkly Rep. 2011;60:1618–1623.
15. White DA, Scribner AN, Schulden JD, et al.. Results of a rapid HIV screening and diagnostic testing program in an urban emergency department. Ann Emerg Med. 2009;54:56–64.
16. Buchacz K, Armon C, Palella FJ, et al.. CD4 cell counts at HIV diagnosis among HIV outpatient study participants, 2000-2009. AIDS Res Treat. 2012;2012:869841.
17. Zetola NM, Bernstein K, Ahrens K, et al.. Using surveillance data to monitor entry into care of newly diagnosed HIV-infected persons: San Francisco, 2006-2007. BMC Public Health. 2009;17:9.
18. Reed JB, Hanson D, McNaghten AD, et al.. HIV testing factors associated with delayed entry into HIV medical care among HIV-infected persons from eighteen states, United States, 2000-2004. AIDS Patient Care STDS. 2009;23:765–773.
19. Jean-Jacques M, Walensky RP, Aaronson WH, et al.. Late diagnosis of HIV infection at two academic medical centers: 1994-2004. AIDS Care. 2008;20:977–983.
21. Craw JA, Gardner LI, Marks G, et al.. Brief strengths-based case management promotes entry into HIV medical care—results of the antiretroviral treatment access study-II. J Acquir Immune Defic Syndr. 2008;47:597–606.
22. Craw J, Gardner L, Rossman A, et al.. Structural factors and best practices in implementing a linkage to HIV care program using the ARTAS model. BMC Health Serv Res. 2010;10:246.
23. Ubel PA, Hirth RA, Chernew ME, et al.. What is the price of life and why doesn't it increase at the rate of inflation? Arch Intern Med. 2003;163:1637–1641.
24. Braithwaite RS, Meltzer DO, King JT Jr, et al.. What does the value of modern medicine say about the $50,000 per quality-adjusted life-year decision rule? Med Care. 2008;46:349–356.
25. Weinstein MC. How much are Americans willing to pay for a quality-adjusted life year? Med Care. 2008;46:343–345.
27. Messeri PA, Abramson DM, Aidala AA, et al.. The impact of ancillary HIV services on engagement in medical care in New York City. AIDS Care. 2002;14:S15–S29.
28. Conover CJ, Whetten-Goldstein K. The impact of ancillary services on primary care use and outcomes for HIV/AIDS patients with public insurance coverage. AIDS Care. 2002;14:S59–S71.
29. Gruber D, Campos P, Dutcher M, et al.. Linking recently diagnosed HIV-positive persons to medical care: perspectives of referring providers. AIDS Care. 2011;23:16–24.
30. Molitor F, Waltermeyer J, Mendoza M, et al.. Locating and linking to medical care HIV-positive persons without a history of care: findings from the California Bridge Project. AIDS Care. 2006;18:456–459.
31. Sorensen SW, Sansom SL, Brooks JT, et al.. A mathematical model of comprehensive test-and-treat services and HIV incidence among men who have sex with men in the United States. PLoS One. 2012;7:e29098.
32. Munakata J, Benner JS, Becker S, et al.. Clinical and economic outcomes of nonadherence to highly active antiretroviral therapy in patients with human immunodeficiency virus. Med Care. 2006;44:893–899.
33. Goldie SJ, Paltiel AD, Weinstein MC, et al.. Projecting the cost-effectiveness of adherence interventions in persons with human immunodeficiency virus infection. Am J Med. 2003;115:632–641.
34. Freedberg KA, Hirschhorn LR, Schackman BR, et al.. Cost-effectiveness of an intervention to improve adherence to antiretroviral therapy in HIV-infected patients. J Acquir Immune Defic Syndr. 2006;43(suppl 1):S113–S118.
35. Zaric GS, Bayoumi AM, Brandeau ML, et al.. The cost-effectiveness of counseling strategies to improve adherence to highly active antiretroviral therapy among men who have sex with men. Med Decis Making. 2008;28:359–376.
36. Tao G, Remafedi G. Economic evaluation of an HIV prevention intervention for gay and bisexual male adolescents. J Acquir Immune Defic Syndr Hum Retrovirol. 1998;17:83–90.
37. Johnson-Masotti AP, Laud PW, Hoffmann RG, et al.. A Bayesian approach to net health benefits: an illustration and application to modeling HIV prevention. Med Decis Making. 2004;24:634–653.
38. Johnson-Masotti AP, Pinkerton SD, Kelly JA, et al.. Cost-effectiveness of an HIV risk reduction intervention for adults with severe mental illness. AIDS Care. 2000;12:321–332.
39. Pinkerton SD, Johnson-Masotti AP, Otto-Salaj LL, et al.. Cost-effectiveness of an HIV prevention intervention for mentally ill adults. Ment Health Serv Res. 2001;3:45–55.
40. Anderson J, Wilson D, Templeton DJ, et al.. Cost-effectiveness of adult circumcision in a resource-rich setting for HIV prevention among men who have sex with men. J Infect Dis. 2009;200:1803–1812.
41. Sansom SL, Prabhu VS, Hutchinson AB, et al.. Cost-effectiveness of newborn circumcision in reducing lifetime HIV risk among U.S. males. PLoS One. 2010;5:e8723.
42. Phillips KA, Fernyak S. The cost-effectiveness of expanded HIV counselling and testing in primary care settings: a first look. AIDS. 2000;14:2159–2169.
43. Sanders GD, Bayoumi AM, Sundaram V, et al.. Cost-effectiveness of screening for HIV in the era of highly active antiretroviral therapy. N Engl J Med. 2005;352:570–585.
44. Paltiel AD, Weinstein MC, Kimmel AD, et al.. Expanded screening for HIV in the United States—an analysis of cost-effectiveness. New Engl J Med. 2005;352:586–595.
45. Paltiel AD, Walensky RP, Schackman BR, et al.. Expanded HIV screening in the United States: effect on clinical outcomes, HIV transmission, and costs. Ann Intern Med. 2006;145:797–806.
46. Mutchler MG, Wagner G, Cowgill BO, et al.. Improving HIV/AIDS care through treatment advocacy: going beyond client education to empowerment by facilitating client-provider relationships. AIDS Care. 2011;23:79–90.
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