Factors influencing the motivation of maternal health workers in conflict setting of Mogadishu, Somalia.

Background: Motivated health workers play an important role in delivering high-quality maternal health services, especially in low-income countries where maternal mortality rates are high, and shortages of human resource for health is prevalent. The aim of this study is to investigate the motivation of maternal health workers in three tertiary hospitals in Mogadishu Somalia. Method: To investigate health worker motivation in Somalia, we used a semi-structured questionnaire that was validated and widely used in Sub-Saharan Africa. Data were collected from 220 health workers across three tertiary hospitals in Mogadishu between February and April 2020. Health worker motivation was measured using seven constructs: general motivation, burnout, job satisfaction, intrinsic job satisfaction, organizational commitment, conscientiousness, timeliness and attendance. A multivariate regression analysis was performed to determine the predictors of health worker motivation. Results: The study found that male health workers have a higher work motivation, with a mean score of 92.75 (SD 21.31) versus 90.43 (SD 21.61) in women. A significant correlation was found between health workers motivation and being an assistant, nurse, physician, pediatric-assistant, midwife, supervisor and pharmacist. Unexpectedly, the gynecologists and midwives were the least motivated groups among the different professions, with mean scores of 83.63, (SD: 27.41) and 86.95 (SD: 21.08), respectively. Of the aforementioned seven motivation constructs, the highest mean motivation scores (from 1-5) were observed in conscientiousness and intrinsic job satisfaction. Conclusion: The results highlight the importance of targeted interventions that increase the motivation of female health workers, particularly gynecologists and midwives in Somalia. This can be done by providing non-financial incentives, in addition to encouraging their participation in the decision-making process. Further research is needed to investigate the effect of a lack of motivation among gynecologists and midwives on maternal health in Somalia.

Systematic review of performance-enhancing health worker supervision approaches in low- and middle-income countries

Background The strength of a health system—and ultimately the health of a population—depends to a large degree on health worker performance. However, insufficient support to build, manage and optimize human resources for health (HRH) in low- and middle-income countries (LMICs) results in inadequate health workforce performance, perpetuating health inequities and low-quality health services. Methods The USAID-funded Human Resources for Health in 2030 Program (HRH2030) conducted a systematic review of studies documenting supervision enhancements and approaches that improved health worker performance to highlight components associated with these interventions’ effectiveness. Structured by a conceptual framework to classify the inputs, processes, and results, the review assessed 57 supervision studies since 2010 in approximately 29 LMICs. Results Of the successful supervision approaches described in the 57 studies reviewed, 44 were externally funded pilots, which is a limitation. Thirty focused on community health worker (CHW) programs. Health worker supervision was informed by health system data for 38 approaches (67%) and 22 approaches used continuous quality improvement (QI) (39%). Many successful approaches integrated digital supervision technologies (e.g., SmartPhones, mHealth applications) to support existing data systems and complement other health system activities. Few studies were adapted, scaled, or sustained, limiting reports of cost-effectiveness or impact. Conclusion Building on results from the review, to increase health worker supervision effectiveness we recommend to: integrate evidence-based, QI tools and processes; integrate digital supervision data into supervision processes; increase use of health system information and performance data when planning supervision visits to prioritize lowest-performing areas; scale and replicate successful models across service delivery areas and geographies; expand and institutionalize supervision to reach, prepare, protect, and support frontline health workers, especially during health emergencies; transition and sustain supervision efforts with domestic human and financial resources, including communities, for holistic workforce support. In conclusion, effective health worker supervision is informed by health system data, uses continuous quality improvement (QI), and employs digital technologies integrated into other health system activities and existing data systems to enable a whole system approach. Effective supervision enhancements and innovations should be better integrated, scaled, and sustained within existing systems to improve access to quality health care.

Evaluating the impact of language concordance on COVID-19 contact tracing outcomes among Spanish-speaking adults in San Francisco between June and November 2020

We evaluated the impact of language concordance—clinician or public health worker fluency in a patient’s primary language—on COVID-19 contact tracing outcomes among 2668 Spanish-speaking adults in San Francisco. Language concordance was associated with 20% greater odds of COVID-19 testing and 53% greater odds of support service referrals.