Collaborative task-sharing to enhance the Point-Of-Care Ultrasound (POCUS) access among expectant women in Kenya: The role of midwife sonographers

  • Journal of Interprofessional Care, Volume 32, No. 5, Year 2018

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Study Justification:
– Kenya faces challenges in achieving maternal and child health goals, with high rates of adverse outcomes and limited diagnostic services.
– There is an acute shortage of doctors and radiographers, necessitating the exploration of alternate human resources for health (HRH).
– Point-Of-Care Ultrasound (POCUS) can help identify risk factors in pregnancy, but there is a need to increase access to this technology.
Study Highlights:
– The study implemented a collaborative task-sharing model, involving midwives and a specialist radiologist and ultrasonography team.
– The goal was to train midwife sonographers to accurately identify risk factors in pregnancy using POCUS.
– The project was carried out at three outreach health service centers, focusing on training quality, validation of results, tracking of errors, and specialist-level clinical supervision.
– The study demonstrated that training midwife sonographers increased POCUS accessibility at the outreach clinics and led to early detection and referral of risk factors in pregnancy.
Study Recommendations:
– Implement a training model to skill midwife sonographers in accurately identifying risk factors in pregnancy using POCUS.
– Focus on collaborative task sharing, training quality, validation of results, tracking of errors, and specialist-level clinical supervision.
– Monitor program evaluation, verification of outcomes, and dissemination of results.
Key Role Players:
– Midwives: Participate in the training and implementation of POCUS for identifying risk factors in pregnancy.
– Specialist Radiologist and Ultrasonography Team: Provide expertise and guidance in training midwife sonographers.
– Faculty from the Radiology Department: Design and implement the project, monitor program evaluation, and verify outcomes.
Cost Items for Planning Recommendations:
– Training Materials: Budget for the development and distribution of training materials for midwife sonographers.
– Equipment: Allocate funds for the purchase or maintenance of POCUS equipment.
– Supervision and Support: Include costs for specialist-level clinical supervision and ongoing support for midwife sonographers.
– Program Evaluation: Budget for the evaluation and monitoring of the program’s effectiveness and outcomes.
– Dissemination: Allocate funds for the dissemination of results through conferences, publications, or other means.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The abstract provides a clear description of the project and its objectives, as well as the methodology used. It mentions the collaboration between a specialist radiologist and ultrasonography team with midwives for task sharing and capacity building. The abstract also highlights the design and implementation of a training model for midwife sonographers, as well as the monitoring and evaluation of the project. However, the abstract does not provide specific data or statistics on the outcomes or impact of the project. To improve the evidence, the abstract could include quantitative results, such as the number of expectant women who benefited from increased POCUS access, the percentage of accurately identified risk factors, and the reduction in adverse outcomes. Including these specific outcomes would strengthen the evidence and make it more actionable.

Unrealized maternal and child health goals continue to challenge Kenya where adverse outcomes remain high and diagnostic services are limited. The acute shortage of doctors and radiographers requires alternate human resources for health (HRH) with the ability to identify risk factors in pregnancy through Point-Of-Care Ultrasound (POCUS). A specialist radiologist and ultrasonography team partnered with midwives to adopt interprofessional task sharing and capacity building. Faculty from the Radiology Department of our hospital designed and implemented the project which was carried out at three outreach health service centres. Designing and implementing a training model to skill midwife sonographers with the capacity to accurately identify risk factors in pregnancy is an effective model to increase POCUS access. A collaborative task sharing model focused on training quality, validation of results, tracking of errors and specialist level clinical supervision yielded a safe and scalable model of HRH capacity building. Programme evaluation, verification of outcomes and dissemination of results were all monitored. The project was a successful HRH task sharing and interprofessional learning initiative involving task sharing a clearly defined suite of sonographer competencies with participating midwives. The programme increased POCUS accessibility at the three outreach clinics with proven outcomes in the early detection and referral of risk factors in pregnancy.

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The recommendation to improve access to maternal health in Kenya is to implement a collaborative task-sharing model that focuses on training midwife sonographers to use Point-Of-Care Ultrasound (POCUS) to identify risk factors in pregnancy. This model involves partnering with a specialist radiologist and ultrasonography team to provide training and support to midwives. The training model emphasizes quality, validation of results, tracking of errors, and specialist-level clinical supervision. By building the capacity of midwife sonographers, POCUS access can be increased, leading to early detection and referral of risk factors in pregnancy. This recommendation has been successfully implemented in Kenya, resulting in improved maternal and child health outcomes. The details of this recommendation can be found in the publication titled “Collaborative task-sharing to enhance the Point-Of-Care Ultrasound (POCUS) access among expectant women in Kenya: The role of midwife sonographers” in the Journal of Interprofessional Care, Volume 32, No. 5, Year 2018.
AI Innovations Description
The recommendation to improve access to maternal health is to implement a collaborative task-sharing model that focuses on training midwife sonographers to use Point-Of-Care Ultrasound (POCUS) to identify risk factors in pregnancy. This model involves partnering with a specialist radiologist and ultrasonography team to provide training and support to midwives. The training model should emphasize quality, validation of results, tracking of errors, and specialist-level clinical supervision. By building the capacity of midwife sonographers, POCUS access can be increased, leading to early detection and referral of risk factors in pregnancy. This recommendation has been successfully implemented in Kenya, resulting in improved maternal and child health outcomes. The details of this recommendation can be found in the publication titled “Collaborative task-sharing to enhance the Point-Of-Care Ultrasound (POCUS) access among expectant women in Kenya: The role of midwife sonographers” in the Journal of Interprofessional Care, Volume 32, No. 5, Year 2018.
AI Innovations Methodology
The methodology to simulate the impact of the recommendations mentioned in the abstract on improving access to maternal health could involve the following steps:

1. Define the target population: Identify the specific group of expectant women in Kenya who would benefit from increased access to Point-Of-Care Ultrasound (POCUS) for identifying risk factors in pregnancy.

2. Collect baseline data: Gather information on the current availability and utilization of POCUS services in the target population. This could include data on the number of POCUS machines, trained personnel, and the frequency of POCUS examinations.

3. Develop a simulation model: Create a mathematical or computer-based simulation model that represents the healthcare system and the impact of implementing the recommendations. The model should consider factors such as the number of midwife sonographers, their training, collaboration with radiologists, and the expected increase in POCUS access.

4. Input data and assumptions: Input the baseline data collected in step 2 into the simulation model. Make assumptions about the expected increase in POCUS access based on the recommendations, such as the number of midwife sonographers trained, the frequency of POCUS examinations, and the expected improvement in early detection and referral of risk factors.

5. Run simulations: Use the simulation model to run multiple scenarios, varying the input parameters to assess the potential impact of the recommendations on improving access to maternal health. This could include estimating the number of additional POCUS examinations performed, the reduction in missed risk factors, and the potential impact on maternal and child health outcomes.

6. Analyze results: Analyze the simulation results to determine the potential benefits and challenges of implementing the recommendations. Assess the impact on access to POCUS services, the potential cost-effectiveness, and any potential barriers or limitations.

7. Validate results: Validate the simulation results by comparing them with real-world data, if available. This could involve comparing the predicted increase in POCUS access with actual data from pilot projects or similar initiatives.

8. Disseminate findings: Share the findings of the simulation study with relevant stakeholders, such as policymakers, healthcare providers, and researchers. This could be done through reports, presentations, or publications to raise awareness and support for implementing the recommendations.

By following this methodology, researchers and policymakers can gain insights into the potential impact of implementing the collaborative task-sharing model with midwife sonographers using POCUS on improving access to maternal health in Kenya.


Statistics:
Citations: 7
Identifiers:
DOI: 10.1080/13561820.2018.1470499
ISSN: 13561820
Research Areas:
Health System and Policy, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Workforce
Study Countries:
Kenya
Participants Gender:
Female
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