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Thinkwell

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Dodoma
Jakarta
Hanoi
Amman
Nairobi
Port-au-Prince
Monrovia
Cairo
Lusaka
Maputo
Dar Es Salaam
Antananarivo
Karachi
Dhaka
Manila

Summary

With funding from the U.S. Department of Health & Human Services (HRSA), ThinkWell aims to improve the performance and productivity of health facility professionals. Leveraging ThinkWell’s human resources for health (HRH) and health systems expertise, we support the Ministry of Health (MoH) to improve health workers’ performance by (i) testing new approaches and models for health worker allocation, (ii) contributing to the design of a strategy to improve performance, motivation, and management through a performance based financing mechanism appropriate to the national context and MoH objectives, and (iii) through a comprehensive site management approach, strengthen primary health care facility management to more efficiently and effectively meet changing service demands.

Breaking New Ground

In a three-pronged approach, the project:

  1. Developed and assisted the MoH to integrate a tool that calculates health facility HRH needs, based on service provision history and current staffing levels, into the annual district planning process
  2. Advocated for and supports the MoH to develop a strategy to improve performance through a MoH-led national performance-based financing mechanism
  3. Assists the MoH to develop a management and administrative procedures manual, develop staffing structure for high-volume primary care facilities in order to maximize efficiency, and enable them to more effectively meet changing demands

Challenges

In Mozambique, severe resource constraints in the health sector are exacerbated by misallocation of resources, poor management, and poor health worker motivation. Health worker production and allocation in Mozambique has historically been guided by health worker to population ratios at national, provincial, and district-levels and by standard health-team structures. Since similar sized populations may have different healthcare demands and health facilities may attend vastly different numbers of patients, this has led to staff allocations that don’t correspond to needs.

In addition, a combination of insufficient resources, remuneration, management structures that do not reward performance, highly centralized decision making, and poor HR management have resulted in highly demotivated and disempowered frontline health providers.

Finally, the health care demands placed on primary care facilities have dramatically increased and changed over the last 30 years due to the HIV pandemic and an ongoing decentralization process. Yet management structures, systems, and procedures have not kept pace. This has resulted in inefficiencies, poor quality of care, and long waiting times.

Approach

ThinkWell developed a human resource allocation tool that allows planners at all levels to manage the allocation of key health professionals at primary care facilities based on historical service provision and current staffing data. To ensure institutionalization and empower district-level decisionmakers, the project trained district human resource managers and chief medical officers from all provincial directorates and districts.

With the National Institute of Health, we convened a workshop for implementing partners to discuss and compare their approaches improve primary healthcare facility management. We are currently conducting a deep dive assessment of high-volume primary care facilities that will inform a management and administration procedures manual for primary healthcare facilities.

Results

The National Directorate of Human Resources (DRH) of the Ministry of Health adopted the HRH allocation tool and integrated it into the annual planning process (PESS) at the district-level to allow district health directorates to better recruit, allocate, reallocate, and plan HRH priorities. The MoH requested ThinkWell to provide technical support for the tool’s implementation. District-level staff who normally only input data for national health and human resource information systems now use data from these systems to make staff allocation decisions.

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