Improving health worker efficiency

The introduction of digital health interventions requires re-examining existing workflows and operations in health facilities in order to ensure that interventions are used efficiently. Finding the optimal integration of an intervention into a facility workflow requires that an intervention is designed with existing workflows taken into account, but also with consideration for how existing workflows can be modified. This optimization helps to improve the efficiency and quality of work completed by healthcare workers when a digital intervention is in use. We studied the effects of modifying workflows within immunization clinics where an electronic immunization registry (EIR) had been introduced, in order to achieve efficient use of the EIR in collecting and reporting immunization data. Using time-motion study techniques, we studied immunization clinic workflow patterns at public health facilities in Kenya. By assessing immunization clinic workflows among facilities using the EIR, we identified bottlenecks, potential solutions, and tested strategies for redesigning an immunization session to increase time efficiencies when healthcare workers perform dual data entry (paper and electronic). We used an iterative approach to test different workflows, assessing how time use changed for each activity, and documenting needed EIR software updates to support healthcare workers using an improved workflow. Workflows were assessed across different sizes and types of facilities. We tested three workflow modifications: preparing records the day before, full paperless data entry, and the use of two tablets (versus one) in a single facility. This study quantified the improved accessibility of immunization information for healthcare workers, allowing them to perform new tasks that can help increase their facility’s vaccination coverage.

As in many resource constrained settings, the ratio of client populations to community health workers is large. Further inflating this ratio are issues of chronic absenteeism and inadequate staffing. A direct result of this overburdened health workforce is the limited time then available for quality service provision by the health worker that is on staff. The limited time available results in the most vulnerable populations being habitually “missed”, as they often live the furthest away from urban centers and due to affordability of land, in the most difficult-to-reach parts of communities. As part of the mCARE-II trial being implemented in rural Bangladesh, investigators sought to quantify the true gaps in coverage and service provision that exist for these populations. This session will demonstrate the use of digital health strategies to answer critical questions, such as, how many clients actual live in each government worker’s catchment area? What happens to clients living in areas where there is confusion of catchment area boundaries? How can geofencing and vector-overlap (concave hull) tools be used to identify missed clients or overlapping areas ? Are clients who are visited by their community health workers different than those who are missed, and if they are, how so? Data to answer these questions is available from the independent JiVitA Project research workforce, tasked with prospectively establishing a true denominator of all eligible women, pregnancies, and birth outcomes that occur within a 450 sq km area, as well as assessing the care that these individuals receive. This analysis will help define the workforce gap using digital tools -- a major barrier to achieving high coverage of essential public health interventions.

PSI Zimbabwe needed a way to fully integrate client records for increased client management that is effective across health areas. While PSI/Z clinics are integrated in the service delivery offered, there is currently a separate medical record tool for each intervention. The system is vertical across health areas. For example, a woman can access SRHR at a New Start Clinic, yet the SRHR counsellor won’t know with certainty the last visit a client had with SRHR or even when her last HTS was conducted beyond client-self reporting. Data collection across the health areas was not streamlined resulting data like risk assessment data being collected multiple time. To resolve this problem PSI/Zimbabwe created Bahmni. Bahmni, is an easy to use, open source Electronic Medical Record [EMR] system. It is bundled with three existing open source products and enhanced to be a single application. Bahmni, was designed with the aim to cater to the needs of a hospital for improved healthcare delivery through efficient information management at rural and resource-constrained areas. It is currently deployed and used in more than 40 countries for various clinical needs & missions. This session will be discussing how Bahmni works and how it’s integration to DHIS2 was achieved.