# Optimal Medication Dispensing for People Living with HIV with and without Other Chronic Diseases in Zambia: A Mathematical Model

> **NIH NIH F32** · BOSTON MEDICAL CENTER · 2022 · $76,839

## Abstract

PROJECT SUMMARY
In the current era of universal antiretroviral treatment (ART), health systems have the challenge of optimizing
care for a growing number of diverse groups of people living with HIV and on ART who are also on chronic,
life-long treatment for non-communicable diseases (NCDs). Differentiated service delivery (DSD) was
developed as a means to combat suboptimal long-term retention on ART and increase the efficiency of
resource utilization by simplifying and adapting care along the cascade, guided by patient preferences and
needs, while reducing unnecessary burdens on individuals and the health system. Much remains to be
understood, however, about whether DSD models will work for integrated service delivery for multiple
conditions and how to find the optimal DSD model for specific populations and health systems. Using a large
patient dataset of routinely collected medical records in Zambia, I propose to create a dynamic microsimulation
model of disease and service delivery – focusing on HIV with and without other chronic diseases such as
diabetes – to identify the potential benefits and costs of an optimal medication dispensing strategy. I expect
that the cost-effectiveness of alternative drug dispensing strategies will be a function of service volume, patient
outcomes, unit costs, and probability of congestion within clinics. This research will directly inform policy
questions relating to how DSD models should be implemented to improve population health outcomes and
program cost-effectiveness. Aims 1 and 2 will construct HIV service delivery indices of intensity, capacity,
density, and frequency, assess distributions by patient/facility groups, and evaluate economies of scale of drug
dispensing strategies for HIV with and without other chronic diseases such as diabetes. I will build a model to
quantify the extent of service capacity and utilization increase using an integrated and multi-month drug
dispensing strategy for HIV and diabetes, based on the proportion of stable/comorbid patients, unit time/cost
per service, and clinic capacity. Aim 3 will project the long-term impact and cost-effectiveness of an integrated
drug dispensing strategy for HIV with and without other chronic diseases. My model will estimate whether and
to what extent service integration and multi-month drug dispensing can change total treatment initiation and
retention in a clinic and how that may in turn change the probability of clinic congestion, unit costs, treatment
retention/service quality, and cost effectiveness. The primary research environment, Boston University Medical
Campus, will contribute to the success of the proposed project, as it provides rich, multidisciplinary institutional
resources, including a strong commitment to research and training and ample departmental facilities and
resources. I have access to the necessary resources and data to complete the proposed research. Through
this mentored research training award, I will gain expertise in i...

## Key facts

- **NIH application ID:** 10448273
- **Project number:** 5F32MH128120-02
- **Recipient organization:** BOSTON MEDICAL CENTER
- **Principal Investigator:** Youngji Jo
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $76,839
- **Award type:** 5
- **Project period:** 2021-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10448273

## Citation

> US National Institutes of Health, RePORTER application 10448273, Optimal Medication Dispensing for People Living with HIV with and without Other Chronic Diseases in Zambia: A Mathematical Model (5F32MH128120-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10448273. Licensed CC0.

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