Digital Supportive Supervision
Leona Rosenblum, Deputy Director, Center for Digital Health, JSI
Tuesday June 21, 11:15AM
Supportive supervision is the process of mentoring staff to improve their own work performance continuously (WHO). It is undertaken to ensure health workers have the support and resources they need to do their work, to measure and improve quality of care, and to identify gaps to be able to solve problems as they arise. Supportive supervision has been implemented widely across a variety of health areas, but often lacks structure, continuity from prior visits, and fails to be data-driven.
As digital tools in the hands of frontline health workers have proliferated and systems have been developed to share data with supervisors and district managers, an opportunity to develop digital supportive supervision tools has emerged. Supportive supervision is typically based on formal checklists reviewing facilities or teams and may include assessing equipment, infrastructure, quality of care, staffing, and management issues as well as service delivery. Some supportive supervision tools are bringing together data from various sources to use as a tool in reviewing service delivery or data quality to enable supportive supervision to be more data-driven.
As with other digital health interventions, health programs would benefit from standardized guidance on the key components that should be considered when developing digital supportive supervision tools to leverage these efforts and innovations rather than starting from scratch. To address this emerging opportunity, the USAID-funded Country Health Information Systems and Data Use program (CHISU) is developing a guidance document for digital supportive supervision that will be a global good. This guidance will support country stakeholders to identify approaches to use digital tools to strengthen the supportive supervision process, especially at district and facility level. This activity is well aligned with the components of the USAID Vision for Digital Health including supporting country-level capacity in digital health and the development of global goods. The development and utilization of improved supportive supervision tools should improve quality and resource optimization, both key aspects of USAID’s Vision for Health Systems Strengthening 2030.
During this session, we will review the draft guidance and how DHIS2 is uniquely positioned to facilitate data-driven supervision via its two data models. Supervision visit checklists can be built into the tracker model while the aggregate data model contains service delivery and data quality data, which when used alongside supervision checklists can facilitate more data-driven supervision.