Heterogeneity in the costs of medical care among people living with HIV/AIDS in the United States

What are the drivers of high-cost HIV patients?

We aimed to identify "high-cost" patients with HIV (PWH) and determine drivers behind higher costs. All PWH at the Southern Alberta HIV Clinic, Canada, and active in 2017 were included. Sociodemographic, clinical, and healthcare utilization data were collected. The direct care costs from the payers' perspective including antiretroviral drugs (ARV), outpatient visits, and hospital admissions were determined for 2017. Patients' annual total costs were grouped into top 5% (i.e., high-cost), top 20%, middle 60%, and bottom 20%. High-cost patients were older, Caucasian or indigenous Canadian, and more likely acquired HIV from intravenous drug use (all p < 0.05). High-cost patients had lower nadir CD4, more comorbidities, missed more clinic appointments, had more ARV interruptions, and developed more ARV resistance (p < 0.01). The overall median cost of HIV care was US$14,064 [IQR US$13,121-US$17,883] (2017 Cdn$). High-cost patients had a median cost of US$29,902 [IQR US$27,229-US$37,891] and accounted for 14% of total costs and 84% of all inpatient costs. Hospitalizations constituted 58% of costs for high-cost patients. Although heterogeneous, high-cost patients have distinct sociodemographic and clinical characteristics driving their healthcare utilization. Addressing these social determinants of health and using novel ARV administration approaches may preserve health and save costs.

Cost-Effectiveness Analysis Combining Medical and Mental Health Services for Older Adults with HIV in New York City

Older adults with the human immunodeficiency virus or HIV (OAWH), people 50 years and older, are aging with the disease and experience low quality of life. Mental health disorders trigger and worsen health inequalities with larger impacts on the quality of life of OAWH. This paper evaluated two rival health interventions using a standard decision-analytic model and quantified the cost per quality-adjusted life-years (QALY) to understand the differential in cost and effectiveness of an additional unit of perfect health. HIV medical care was compared with a combined strategy that includes both HIV medical and behavioral care. Primary data from a convenience sample (n=139) collected in New York City and outcomes for healthy older adults from the literature were used in this study. The incremental cost-effectiveness ratio (ICER) evaluating the economic cost and health benefits of the new intervention was $36,166 per QALY, which is less than the willingness to pay ($75,000). The ICER for Hispanics was $35,325 and for White/Caucasians was $40,499. Integrated medical plus behavioral care is cost-effective and improves quality of life among OAWH. Given the high rates of mental health disorders along with an underutilization of behavioral care among OAWH, timely and effective mental health programs are paramount to increase quality of life.

Developing a dynamic HIV transmission model for 6 U.S. cities: An evidence synthesis

BACKGROUND

Dynamic HIV transmission models can provide evidence-based guidance on optimal combination implementation strategies to treat and prevent HIV/AIDS. However, these models can be extremely data intensive, and the availability of good-quality data characterizing regional microepidemics varies substantially within and across countries. We aim to provide a comprehensive and transparent description of an evidence synthesis process and reporting framework employed to populate and calibrate a dynamic, compartmental HIV transmission model for six US cities.

METHODS

We executed a mixed-method evidence synthesis strategy to populate model parameters in six categories: (i) initial HIV-negative and HIV-infected populations; (ii) parameters used to calculate the probability of HIV transmission; (iii) screening, diagnosis, treatment and HIV disease progression; (iv) HIV prevention programs; (v) the costs of medical care; and (vi) health utility weights for each stage of HIV disease progression. We identified parameters that required city-specific data and stratification by gender, risk group and race/ethnicity a priori and sought out databases for primary analysis to augment our evidence synthesis. We ranked the quality of each parameter using context- and domain-specific criteria and verified sources and assumptions with our scientific advisory committee.

FINDINGS

To inform the 1,667 parameters needed to populate our model, we synthesized evidence from 59 peer-reviewed publications and 24 public health and surveillance reports and executed primary analyses using 11 data sets. Of these 1,667 parameters, 1,517 (91%) were city-specific and 150 (9%) were common for all cities. Notably, 1,074 (64%), 201 (12%) and 312 (19%) parameters corresponded to categories (i), (ii) and (iii), respectively. Parameters ranked as best- to moderate-quality evidence comprised 39% of the common parameters and ranged from 56%-60% across cities for the city-specific parameters. We identified variation in parameter values across cities as well as within cities across risk and race/ethnic groups.

CONCLUSIONS

Better integration of modelling in decision making can be achieved by systematically reporting on the evidence synthesis process that is used to populate models, and by explicitly assessing the quality of data entered into the model. The effective communication of this process can help prioritize data collection of the most informative components of local HIV prevention and care services in order to reduce decision uncertainty and strengthen model conclusions.