Background: To effectively deliver on proposed objectives, it is vital that practitioners, policymakers, and other stakeholders are able to clearly understand how strongly their large-scale program is being implemented. This study sought to test the feasibility, cost-effectiveness, and validity of a phone-based method as an innovative and cost-efficient approach to assessing program implementation strength (through an Implementation Strength Assessment-ISA), alternative to the traditional in-person field methods. Methods: We conducted 701 mobile phone and 356 in-person interviews with facility in-Charges and two types of community health workers who provide family planning services in the Dowa and Ntcheu districts in Malawi. Responses received via the phone interview were validated through in-person review of records and inspections. Sensitivity and specificity were calculated to determine validity. Results: Most indicators at the health facility and community health worker levels were above a 70% threshold for sensitivity. However, there were fewer indicators that met this threshold for specificity. The primary reason for lower specificity was due to poor recordkeeping. Collecting data via mobile phone was found to be feasible and twice as cost-efficient as collecting the same data via in-person inspections. Conclusions: The rapid increase in mobile phone ownership and network availability in lower income countries could offer an alternative, cost-effective avenue to collect data for a better understanding of program implementation. Through rigorous assessment, this study found that using mobile phones could be a low-cost alternative to collect data on health system delivery of services, especially in places where routine data quality is poor and traditional, in-person methods are costly.
How strong are Malawi's family planning programs for adolescent and adult women? Results of a national assessment of implementation strength conducted by Malawi's National Evaluation Platform Background To assess the strength of implementation of family planning programs targeting youth (15-24) in Malawi with a specific focus on youth and the Youth-Friendly Health Services program Methods We conducted 9781 mobile phone interviews with facility in-Charge Nurses and health workers (health facility workers, health surveillance assistants [HSAs] and community-based distribution agent [CBDAs]) who provide family planning (FP) services across the 28 districts. Responses were entered in tablet using Open Data Kit. They were summarized and presented using R, Stata (College Station, TX, USA), StatsReport (JHU, Baltimore, MD, USA) and ArcView GIS (ESRI, Redlands, CA, USA). Results Availability of key products was a challenge across all health worker types as only 39% of health facilities, 29% of HSAs and 45% of CBDAs had all the FP methods they are supposed to provide on the day of the interview. About 50% of health workers were supervised within past 90 days preceding the study. Despite most facilities saying that they provide youth friendly health services, youth-specific FP guidelines or protocols were not available in 43% of facilities that provide these services and only 33% of facilities had special rooms and 58% have special days for youth. Conclusions The commodity supply system needs to ensure that all facilities and workers have a consistent supply of all contraceptive methods. Government and program implementers should ensure availability of all FP guidelines and information, education, communication materials at all service delivery points and facilitate creation of special rooms or days for youth.
While Indonesia introduced a national health insurance scheme (JKN) in 2014 and coverage has grown to over 80% of the population, Indonesians still spend significant sums out-of-pocket (OOP) for their healthcare–over 30% of current health expenditure (CHE). This study aims to better understand how JKN is influencing OOP payments, especially among the poor and rural, at the range of health facilities. This study uses data from the National Socio-Economic Survey (SUSENAS) in 2018 and 2019, as these surveys started including a question on how much OOP spending a household incurs on health. The results show that households with JKN membership are far less likely than the uninsured to pay OOP for healthcare, and that if they do incur a cost, the magnitude of this cost is much lower among JKN households than uninsured ones. The results also show that JKN households in the two poorest quintiles have a higher probability to not incur any OOP (37% and 35%, respectively) compared to those in the wealthier quintiles 4 (32%) and 5 (30%). Poorer JKN households living in the eastern part of Indonesia–the less urbanized and developed regions–experienced the most cost-savings, though largely due to supply-side constraints. In fact, JKN members save more at public primary health care facilities vs. private ones (who often do not contract with JKN) and also save significantly more (over 50%) than uninsured households at both public and private hospitals. The study demonstrates the positive influence JKN has on OOP payments, especially among the poor and rural, but also highlights how the scheme needs to better engage with the growing private sector and invest in infrastructure in rural areas to help secure financial protection for its entire population.
Quantitative analysis and modeling of public health QI activities are feasible and desirable. It may provide critical information leading to incremental improvement in QI performance within public health practice. This work can inform the nascent national accreditation program and the developing QI in Public Health Practice Exchange.
Background: Data that capture implementation strength can be combined in multiple ways across content and health system levels to create a summary measure that can help us to explore and compare program implementation across facility catchment areas. Summary indices can make it easier for national policymakers to understand and address variation in strength of program implementation across jurisdictions. In this paper we describe development of an index that we used to describe the district level strength of implementation of the Malawi national family planning program. Methods: To develop the index, we used data collected during a 2017 national, health facility and community health worker Implementation Strength Assessment survey in Malawi to test different methods to combine indicators within and then across domains (4 methods: simple additive, weighted additive, principal components analysis, exploratory factor analysis) and combine scores across health facility and community health worker levels (2 methods: simple average and mixed effects model) to create a catchment area-level summary score for each health facility in Malawi. We explored how well each model captures variation and predicts couple years protection and how feasible it is to conduct each type of analysis and the resulting interpretability. Results: We found little difference in how the four methods combined indicator data at the individual and combined levels of the health system. However, there were major differences when combining scores across health system levels to obtain a score at the health facility catchment area level. The scores resulting from the mixed effects model were able to better discriminate differences between catchment area scores compared to the simple average method. The scores using the mixed effects combination method also demonstrated more of a dose and response relationship with couple years protection. Conclusions: The summary measure that was calculated from the mixed effects combination method captured the variation of strength of implementation of the Malawi national family planning program at the health facility catchment area level. However, the best method for creating an index should be based on pros and cons listed, not least, analyst capacity and ease of interpretability of findings. Ultimately, the resulting summary measure can aid decisionmakers in understanding the combined effect of multiple aspects of programs being implemented in their health system and comparing strengths of programs across geographies.
To explore the association between the strength of implementation of family planning (FP) programs on the use of modern contraceptives. Specifically, how strongly these programs are being implemented across a health facility’s catchment area in Malawi and the odds of a woman in that catchment area is using modern contraceptives. This information can be used to assess whether the combined impact of multiple large-scale FP programs is leading to change in the health outcomes they aim to improve. We used data from the 2017 Implementation Strength Assessment (ISA) that quantified how much of family planning programs at the health facility and community health worker levels were being implemented across every district of Malawi. We used a summary measure developed in a previous study that employs quantitative methods to combine data across FP domains and health system levels. We tested the association of this summary measure for implementation strength with household data from the 2015 Malawi Demographic Health Survey (DHS). We found that areas with stronger implementation of FP programs had higher odds of women using modern contraceptives compared with areas with weaker implementation. The association of ISA with use of modern contraception was different by education, marital status, and geography. After controlling for these factors, we found that the adjusted odds of using a modern contraceptive was three times higher in catchment areas with high implementation strength compared to those with lower strength. Metrics that summarize how strongly FP programs are being implemented were used to show a statistically significantly positive relationship between increasing implementation strength and higher rates of modern contraceptive use. Decisionmakers at the various levels of health authority can use this type of summary measure to better understand the combined impact of their diverse FP programming and inform future programmatic and policy decisions. The findings also reinforce the idea that having a well-supported and supplied cadre of community health workers supplementing FP provision at the health facility can be an important health systems mechanism, especially in rural settings and to target youth populations.
Background Data that capture implementation strength can be combined in multiple ways across content and health system levels to create a summary measure that can help us to explore and compare program implementation across facility catchment areas. Summary indices can make it easier for national policymakers to understand and address variation in strength of program implementation across jurisdictions. In this paper, we describe the development of an index that we used to describe the district-level strength of implementation of Malawi’s national family planning program. Methods To develop the index, we used data collected during a 2017 national, health facility and community health worker Implementation Strength Assessment survey in Malawi to test different methods to combine indicators within and then across domains (4 methods—simple additive, weighted additive, principal components analysis, exploratory factor analysis) and combine scores across health facility and community health worker levels (2 methods—simple average and mixed effects model) to create a catchment area-level summary score for each health facility in Malawi. We explored how well each model captures variation and predicts couple-years protection and how feasible it is to conduct each type of analysis and the resulting interpretability. Results We found little difference in how the four methods combined indicator data at the individual and combined levels of the health system. However, there were major differences when combining scores across health system levels to obtain a score at the health facility catchment area level. The scores resulting from the mixed effects model were able to better discriminate differences between catchment area scores compared to the simple average method. The scores using the mixed effects combination method also demonstrated more of a dose–response relationship with couple-years protection. Conclusions The summary measure that was calculated from the mixed effects combination method captured the variation of strength of implementation of Malawi’s national family planning program at the health facility catchment area level. However, the best method for creating an index should be based on the pros and cons listed, not least, analyst capacity and ease of interpretability of findings. Ultimately, the resulting summary measure can aid decision-makers in understanding the combined effect of multiple aspects of programs being implemented in their health system and comparing the strengths of programs across geographies.
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