Using modeling and scenario analysis to support evidence-based health workforce strategic planning in Malawi.

BACKGROUND: A well-trained and equitably distributed workforce is critical to a functioning health system. As workforce interventions are costly and time-intensive, investing appropriately in strengthening the health workforce requires an evidence-based approach to target efforts to increase the number of health workers, deploy health workers where they are most needed, and optimize the use of existing health workers. This paper describes the Malawi Ministry of Health (MoH) and collaborators' data-driven approach to designing strategies in the Human Resources for Health Strategic Plan (HRH SP) 2018-2022. METHODS: Three modelling exercises were completed using available data in Malawi. Staff data from districts, central hospitals, and headquarters, and enrollment data from all health training institutions were collected between October 2017 and February 2018. A vacancy analysis was conducted to compare current staffing levels against established posts (the targeted number of positions to be filled, by cadre and work location). A training pipeline model was developed to project the future available workforce, and a demand-based Workforce Optimization Model was used to estimate optimal staffing to meet current levels of service utilization. RESULTS: As of 2017, 55% of established posts were filled, with an average of 1.49 health professional staff per 1000 population, and with substantial variation in the number of staff per population by district. With current levels of health worker training, Malawi is projected to meet its establishment targets in 2030 but will not meet the WHO standard of 4.45 health workers per 1000 population by 2040. A combined intervention reducing attrition, increasing absorption, and doubling training enrollments would allow the establishment to be met by 2023 and the WHO target to be met by 2036. The Workforce Optimization Model shows a gap of 7374 health workers to optimally deliver services at current utilization rates, with the largest gaps among nursing and midwifery officers and pharmacists. CONCLUSIONS: Given the time and significant financial investment required to train and deploy health workers, evidence needs to be carefully considered in designing a national HRH SP. The results of these analyses directly informed Malawi's HRH SP 2018-2022 and have subsequently been used in numerous planning processes and investment cases in Malawi. This paper provides a practical methodology for evidence-based HRH strategic planning and highlights the importance of strengthening HRH data systems for improved workforce decision-making.

Understanding job satisfaction and motivation among nurses in public health facilities of Ethiopia: a cross-sectional study.

BACKGROUND: Poor job conditions and limited resources are reducing job satisfaction and motivation among nurses in low-income countries, which may affect the quality of services and attrition rates. The objective of this study was to examine job satisfaction, motivation and associated factors among nurses working in the public health facilities of Ethiopia, with the aim of improving performance and productivity in the health care system. METHODS: The study employed a cross-sectional two-stage cluster sampling design. From a random sample of 125 health facilities, 424 nurses were randomly selected for face-to-face interviews in all regions of Ethiopia. Nurses responded to questions about their overall job satisfaction and job conditions, including items related to intrinsic and extrinsic motivation, using a 5-point Likert scale. Multilevel analysis was performed to adjust for different clustering effects. Satisfaction levels (percent of respondents who were satisfied) were calculated for individual items, and composite mean scores (range: 1-5) were calculated for motivational factors. Adjusted odds ratios were computed to examine the association of these factors with overall job satisfaction. RESULTS: Overall, 60.8% of nurses expressed satisfaction with their job. Composite mean scores for intrinsic and extrinsic motivational factors were 3.5 and 3.0, respectively. Job satisfaction levels were significantly higher for female nurses (65.6%, p = 0.04), those older than 29 years (67.8%, p = 0.048) and had over 10 years work experiences (68.8%, p = 0.007). Satisfaction with remuneration (AOR = 2.04, 95% CI = 1.36, 3.06), recognition (AOR = 2.21; 95% CI = 1.38, 3.53), professional advancement (AOR = 1.54; 95% CI = 1.06, 2.29), features of the work itself (AOR = 1.65; 95% CI = 1.20, 2.91) and nurses' work experiences from 5 to 10 years (AOR = 0.37, 95% CI = 0.17, 0.79) were significantly associated with overall job satisfaction after controlling for other predictors. CONCLUSIONS: The study findings are signals for the Ministry of Health to strengthen the human resource management system and practices to improve nurses' overall job satisfaction and motivation, especially among nurses with 5 to 10 years of experience on the job. Expanded recognition systems and opportunities for advancement are required to increase nurses' job satisfaction and motivation. Equitable salary and fringe benefits are also needed to reduce their dissatisfaction with the job.