AIDS Day Q&A Part 3: Standardized Use of Site-Level HRH Data for Differentiated Models of ART Delivery

AIDS Day Q&A Part 3: Standardized Use of Site-Level HRH Data for Differentiated Models of ART Delivery

Dr. Samson Kironde is a medical doctor and public health professional with more than 17 years of experience in strengthening health systems in developing countries, in particular to combat communicable diseases, such as HIV/AIDS, tuberculosis, malaria, and childhood infections. His areas of expertise include strategic project planning, management and implementation, operational research, monitoring and evaluation, and provision of technical assistance. He currently serves as director of PEPFAR/Global Fund human resources for health activities for HRH2030, as well as director for program support and monitoring at the University Research Company and Center for Human Services.

What are the implications of HRH for implementation of new HIV service delivery models or differentiated care models?

The adoption of the “Test and Start” strategy to accelerate the achievement of the UNAIDS 90-90-90 targets opens the door for a growing number of people living with HIV to receive antiretroviral therapy (ART) and achieve viral suppression in order to control the epidemic. A rapid increase in the number of clients on ART, however, may result in various health workforce bottlenecks that can hinder the delivery of critical services in high HIV burden countries. These challenges include inadequate number of health workers for the increased patient load resulting in long wait times for clients, increased workload which may cause low motivation and poor performance, and work processes which may be inefficient under a bigger daily case load. Streamlined service delivery approaches are essential to ensure that patients have access to the quality care they need and that countries can meet the 90-90-90 goals.

A solution with potential is the adoption of differentiated ART delivery models. These differentiated models have been developed to allow for a smoother process for patients who don’t need to see a clinician. They include two facility-based models (group and individual) and two community-based models (also group and individual). Differentiated models enable service delivery to respond to the preferences and expectations of ART clients. Differentiated ART delivery models can minimize unnecessary burdens on the health system by accommodating different client schedules; reducing the number of clinical and laboratory follow-up visits; separating clinical visits from drug refills and providing alternative locations for ART refills; and modifying client-flow patterns to reduce waiting times. For example, a stable patient on ART does not need to visit the clinic for a prescription refill each month. If he or she receives enough medication for several months, it provides clinic staff more time for other patients and saves the stable patient from unnecessary clinic visits. Overall, a differentiated ART delivery model will maximize the use of available resources — including the health workforce — to ensure access to quality care and treatment for more patients.

How is HRH2030 helping to address these health workforce challenges and support differentiated ART service delivery?

HRH2030, through support from USAID and PEPFAR, is developing a standardized, user-friendly tool. This tool will help facility managers who are adopting “Test and Start” to maximize the use of their health workforce, while using differentiated ART delivery models. It provides differentiated ART delivery model options, considering the health facility’s characteristics, clinical status of ART clients, special sub or key-populations, and the health worker skills mix, workload, and workflows.

The tool also contains benchmarks to help estimate the type and number of health workers needed for various tasks along the ART service delivery continuum depending upon selected ART delivery models. HRH2030 formulated these HRH estimates based upon extensive data gathered from facilities that offer varying models of differentiated ART delivery in Uganda.

To use the tool, a facility manager would input site-specific characteristics. These include health worker types and numbers at the facility, estimated proportion of time various types of staff allot to HIV service delivery, and differentiated ART models that the facility currently implements or would like to implement. The tool would then use these inputs and the benchmarks to estimate staffing needs for the facility. Based on these estimates and other contextual factors, the facility manager and ART team could then determine the best combination of differentiated ART models for the site. The team would be able to make an informed decision about reconfiguring its staffing options, workflows and task distribution, or requesting additional staff to meet its targets for clients on ART.

HRH2030 is piloting this tool in Uganda and Cameroon. How will HRH2030 promote its adoption at the national and/or local level to ensure that facilities have the right number and kind of health workers in place to deliver critical HIV services according to local population needs?

Having tested and refined the tool at facilities in Uganda and Cameroon, HRH2030 will work with USAID, implementing partners, and national ministries of health to promote the tool’s use at facilities that are just starting to implement differentiated ART delivery models, or who may be facing challenges in implementing ART services, in PEPFAR-supported high HIV burden countries. HRH2030 will work to ensure that the tool is customizable to different country contexts, taking into consideration staffing norms at facilities offering HIV services, the national guidance on task shifting, and country-specific policies and guidelines for the implementation of differentiated ART delivery models.

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Others in this Series

Part 1: Increasing HIV Impact through Human Resources for Health Interventions
Part 2: Optimizing the Role of Community-Based Workers in HIV Service Delivery
Part 3: Standardized Use of Site-Level HRH Data for Differentiated Models of ART Delivery
Part 4: Making the Case for Investing in HRH