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Sustainability starts with spending: public financial management lessons from Kenya's universal health care pilot.
Get PDFBACKGROUND: Effective public financial management (PFM) is a foundational enabler of sustainable progress toward Universal Health Coverage (UHC). Achieving UHC requires not only increased funding for the health sector but also the efficient, equitable, and accountable use of resources. In 2019, Kenya piloted a UHC initiative across four counties to generate evidence to inform national scale-up. This study examines the PFM processes underpinning the pilot implementation, with a focus on how financial planning, budget execution, and accountability mechanisms influenced the delivery of UHC interventions at the county level. METHODS: This study employed a qualitative research design to explore PFM processes during the implementation of Kenya's UHC pilot in four counties. Data were collected through 51 in-depth interviews and five focus group discussions with key stakeholders, including healthcare workers, patient representatives, and senior members of the County Health Management Teams (CHMTs). An inductive thematic analysis approach was employed to identify patterns and themes that emerged from the data. The analysis was facilitated using Dedoose software (Version 9.0.17), which enabled systematic coding and organization of the qualitative data. RESULTS: The UHC pilot program in Kenya featured a hybrid planning model, combining top-down directives from the national government with bottom-up inputs from county stakeholders. Despite this collaborative approach, county budgeting processes remained governed by the stipulations of the PFM Act. While counties welcomed additional UHC funds, the removal of user fees led to reduced facility-level revenue, increased service demand, and strain on human and material resources. Delays in fund disbursement, rigid budget structures, and limited financial autonomy further constrained implementation. These experiences underscore the need for a more coherent integration of PFM and health financing policies at the subnational level to ensure sustainable and equitable health service delivery. CONCLUSION: The UHC pilot offers critical lessons for future health financing reforms. Addressing PFM bottlenecks-particularly those related to timely disbursement, budget flexibility, and local revenue generation-is essential to ensure the sustainability of UHC in Kenya and similar contexts. The study's limitations necessitate further research before scaling up nationwide
Health Systems in Action (HSiA) Insights – Tajikistan
Get PDFKey points
● Tajikistan’s health system provides a publicly
financed basic benefits package of services, but a
significant number of people fall outside the scope
of eligibility.
● Health spending per capita is the second lowest
in the WHO European Region in absolute terms,
although public spending on health has increased
over the past two decades. Out-of-pocket (OOP)
payments have declined slightly but remain high,
amounting to 63.5% of health spending in 2021.
● Life expectancy has improved, reaching 74.5 years
in 2017. This was higher than in neighbouring
Central Asian countries but still below the average
in the WHO European Region.
● Infant and maternal mortality in Tajikistan remain
relatively high but have seen steady improvements
over the past two decades. Childhood vaccination
coverage rates are high.
● Rates for many communicable diseases have
improved, but access to pharmaceuticals is an
ongoing challenge to further improvement.
● Noncommunicable diseases (NCDs) are a major
driver of mortality, accounting for 24 718 deaths
in 2017, with cardiovascular disease the most
common cause of death.
● Leading risk factors affecting health include high
blood pressure, poor nutrition and high blood sugar.
Overweight and obesity are not a major concern –
although rates are slowly rising – but child and
maternal malnutrition are still a challenge.
● The COVID-19 pandemic is estimated to have
affected overall mortality rates, but to a lesser
degree than in many other countries in the WHO
European Region.
● Ratios of health workers to population are well
below regional averages, and there are major
regional inequalities in the geographic distribution
of health workers. A high rate of migration
exacerbates health workforce gaps, particularly for
skilled workers
Three years into Russia’s full-scale invasion, Ukraine offers a model of health system resilience
Get PDFHealthcare access among people with and without disabilities: a cross-sectional analysis of the National Socioeconomic Survey of Chile.
Get PDFOBJECTIVES: There is a lack of data on health inequities experienced by people with disabilities in Chile. Hence, this study aimed to compare healthcare utilization, coverage, and barriers to accessing health services among people with and without disabilities in Chile. STUDY DESIGN: Secondary cross-sectional study. METHODS: We analysed data of the 2022 National Socioeconomic Survey of Chile. People with disabilities were identified based on the Washington Group Questions. Multivariable logistic regressions were performed to compare the indicators of utilization, coverage, and barriers to accessing healthcare between people with versus without disabilities. Adjusted odds ratios (aOR) were reported with 95 % confidence intervals (95 % CI). RESULTS: A total of 192,666 participants were included in the study; persons with disabilities represented 10 % of the sample (n = 21,769). People with disabilities were more likely to have had a health problem (aOR, 2·22; 95 % CI, 2·12-2·32) and more frequently used any type of health consultation, than those without disabilities. The coverage of adult health check-ups (aOR, 0·88; 95 % CI, 0·81-0·96) and Pap tests among women (aOR, 0·76; 95 % CI, 0·70-0·82), were lower among those with disabilities. Reports of experiencing any barrier to accessing healthcare were more common among people with disabilities. CONCLUSIONS: People with disabilities in Chile continue to experience health inequities, both in terms of higher healthcare needs and lower coverage, and various barriers to accessing healthcare. Thus, a disability lens needs to be mainstreamed in the health system to leave no one behind
Adult brain cancer incidence patterns: A comparative study between Japan and Japanese Americans.
Get PDFAdult primary brain and central nervous system (CNS) cancers, though comprising only about 4% of new cancer diagnoses, significantly impact morbidity and mortality due to their low survival rates. Globally, brain and CNS tumor incidence varies considerably, with the United States exhibiting one of the highest rates and Japan among the lowest worldwide. In the United States, incidence rates differ by race, with higher rates in non-Hispanic whites (NHW) and lower rates in Asian Americans and Pacific Islanders (AAPI). This study examines the incidence of malignant CNS tumors in Japan and Japanese Americans, comparing these groups to NHW and AAPI populations in the United States. We estimated age-standardized incidence rates (ASR) of brain and CNS tumors among adults using data from the Monitoring of Cancer Incidence in Japan (MCIJ) and the U.S. Surveillance, Epidemiology, and End Results (SEER)-9 registries from 2007 to 2014. Incidence rates were stratified by age, sex, and specific CNS tumor subtypes. Incidence rates of CNS tumors among Japanese (ASR: 3.66, 95% CI: 3.56-3.76) and Japanese Americans (ASR: 2.5, 95% CI: 2.13-3.05) were lower than among NHW (9.43, 95% CI, 9.31-9.56) and AAPI populations (ASR: 4.13, 95% CI: 3.94-4.33) in the United States. The same pattern was observed for CNS tumor subtypes and across age groups and sex. This study supports a genetic component in the risk of brain and CNS tumors, a cancer type with largely unknown etiology. By comparing incidence rates across populations, it contributes to understanding the balance of genetic and environmental risk factors in the development of these cancers
Joint modelling of longitudinal data: a scoping review of methodology and applications for non-time to event data.
Get PDFBACKGROUND: Joint models are powerful statistical models that allow us to define a joint likelihood for quantifying the association between two or more outcomes. Joint modelling has been shown to reduce bias in parameter estimates, increase the efficiency of statistical inference by incorporating the correlation between measurements, and allow borrowing of information in cases where data is missing for variables of interest. Most joint modelling methods and applications involve time-to-event data. There is less awareness about the amount of literature available for joint models of non-time-to-event data. Therefore, this review's main objective is to summarise the current state of joint modelling of non-time-to-event longitudinal data. METHODS: We conducted a search in PubMed, Embase, Medline, Scopus, and Web of Science following the PRISMA-ScR guidelines for articles published up to 28 January 2024. Studies were included if they focused on joint modelling of non-time-to-event longitudinal data and published in English. Exclusions were made for time-to-event articles, conference abstracts, book chapters, and studies without full text. We extracted information on statistical methods, association structure, estimation methods, software, etc. RESULTS: We identified 4,681 studies from the search. After removing 2,769 duplicates, 1,912 were reviewed by title and abstract, and 190 underwent full-text review. Ultimately, 74 studies met inclusion criteria and spanned from 2001 to 2024, with the majority (64 studies; 86%) published between 2014 and 2024. Most joint models were based on a frequentist approach (48 studies; 65%) and applied a linear mixed-effects model. The random effect was the most commonly applied association structure for linking two sub-models (63 studies; 85%). Estimation of model parameters was commonly done using Markov Chain Monte Carlo with Gibbs sampler algorithm (10 studies; 38%) for the Bayesian approach, whereas maximum likelihood was the most common (33 studies; 68.75%) for the frequentist approach. Most studies used R statistical software (33 studies; 40%) for analysis. CONCLUSION: A wide range of methods for joint-modelling non-time-to-event longitudinal data exist and have been applied to various areas. An exponential increase in the application of joint modelling of non-time-to-event longitudinal data has been observed in the last decade. There is an opportunity to leverage potential benefits of joint modelling for non-time-to-event longitudinal data for reducing bias in parameter estimates, increasing efficiency of statistical inference by incorporating the correlation between measurements, and allowing borrowing of information in cases with missing data
Guidelines for the content of statistical analysis plans in clinical trials: protocol for an extension to cluster randomized trials.
Get PDFBACKGROUND: Guidance exists to inform the content of statistical analysis plans in clinical trials. Though not explicitly stated, this guidance is generally focused on clinical trials in which the randomization units are individual patients and not groups of patients. There are critical considerations for the analysis of cluster randomized trials, such as accounting for clustering, the risk of imbalances between the arms due to post-randomization recruitment, and the need to use small sample corrections when the number of clusters is small. METHODS: This paper outlines the protocol for the development of a set of reporting guidelines for the content of statistical analysis plans for cluster randomized trials (including variations such as the stepped wedge cluster randomized trial and other cluster cross-over designs) by extending the minimum reporting analysis requirements as previously defined for individually randomized trials to cluster randomized trials. The guideline will be developed using a consensus-based approach, modifying existing reporting items from the guideline for individually randomized trials and extending to include new items. DISCUSSION: The guideline will be developed so it can be used independently of the guideline for individually randomized designs. The consensus guidelines will be published in an open-access journal, including key guidance as well as exploration and elaboration
Effectiveness of COVID-19 vaccine against SARS-CoV-2 infection among symptomatic COVID-19 patients in Uganda.
Get PDFBACKGROUND: COVID-19 vaccines significantly reduce severe disease outcomes, but uncertainty remains about long-term protection. We investigated vaccine effectiveness (VE) against SARS-CoV-2 infection over extended periods in the World Health Organisation AFRO-MoVE network studies in Africa. METHODS: Participants with COVID-19-like symptoms were recruited between 2023 and 2024 for a test-negative case-control study conducted across 19-healthcare centres in Uganda. Cases were symptomatic patients with any three of cough, sore-throat, coryza, among others, and PCR-confirmed SARS-CoV-2, while controls were SARS-CoV-2 PCR-negative. Vaccination was verified from vaccination cards, hospital-records, vaccination registry and self-reporting. VE was assessed through three measures: (a) Annual - patients vaccinated in the past 12-months regardless of dose vs those vaccinated >12-months before symptom onset plus unvaccinated; (b) Absolute - patients vaccinated in the past 12-months vs unvaccinated; and (c) Relative - patients vaccinated in the past 12-months vs those vaccinated >12-months before symptom onset. VE was calculated as 1- adjusted odds ratio for three patient groups based on days since the last dose; (1) <365, (2) 7-269 and (3) 270-364 while adjusting for age, sex, calendar-time and chronic conditions. The sensitivity analysis excluded patients that were previously infected with SARS-CoV-2. FINDINGS: In total, 1371 patients, 56 % female were recruited. Of these, 173 were classified as cases, with 97 (56 %) fully vaccinated compared to 701 (59 %) controls, p = 0.830. The overall adjusted VE was moderate, 45 % to 59 %, and remained consistent across the annual, absolute and relative measures. Sensitivity analysis showed consistently lower VE (32 % to 38 %) across all measures. INTERPRETATION: The results suggest that COVID-19 vaccination provides moderate protection against symptomatic SARS-CoV-2 infection up to 12-months after the last dose and highlight the importance of up-to-date vaccinations for high-risk individuals. The lack of clear COVID-19 seasonality in this and other African settings creates a challenge to selecting the optimal timing for annual vaccination
