Is quality affordable for community health systems? Costs of integrating quality improvement into close-to-community health programmes in five low-income and middle-income countries.

INTRODUCTION: Countries aspiring to universal health coverage view close-to-community (CTC) providers as a low-cost means of increasing coverage. However, due to lack of coordination and unreliable funding, the quality of large-scale CTC healthcare provision is highly variable and routine data about service quality are not trustworthy. Quality improvement (QI) approaches are a means of addressing these issues, yet neither the costs nor the budget impact of integrating QI approaches into CTC programme costs have been assessed. METHODS: This paper examines the costs and budget impact of integrating QI into existing CTC health programmes in five countries (Ethiopia, Indonesia, Kenya, Malawi, Mozambique) between 2015 and 2017. The intervention involved: (1) QI team formation; (2) Phased training interspersed with supportive supervision; which resulted in (3) QI teams independently collecting and analysing data to conduct QI interventions. Project costs were collected using an ingredients approach from a health systems perspective. Based on project costs, costs of local adoption of the intervention were modelled under three implementation scenarios. RESULTS: Annualised economic unit costs ranged from $62 in Mozambique to$254 in Ethiopia per CTC provider supervised, driven by the context, type of community health model and the intensity of the intervention. The budget impact of Ministry-led QI for community health is estimated at 0.53% or less of the general government expenditure on health in all countries (and below 0.03% in three of the five countries). CONCLUSION: CTC provision is a key component of healthcare delivery in many settings, so QI has huge potential impact. The impact is difficult to establish conclusively, but as a first step we have provided evidence to assess affordability of QI for community health. Further research is needed to assess whether QI can achieve the level of benefits that would justify the required investment

How do decision-makers use evidence in community health policy and financing decisions? A qualitative study and conceptual framework in four African countries.

Various investments could help countries deliver on the universal health coverage (UHC) goals set by the global community; community health is a pillar of many national strategies towards UHC. Yet despite resource mobilization towards this end, little is known about the potential costs and value of these investments, as well as how evidence on the same would be used in related decisions. This qualitative study was conducted to understand the use of evidence in policy and financing decisions for large-scale community health programmes in low- and middle-income countries. Through key informant interviews with 43 respondents in countries with community health embedded in national UHC strategies (Ethiopia, Kenya, Malawi, Mozambique) and at global institutions, we investigated evidence use in community health financing and policy decision-making, as well as evidentiary needs related to community health data for decision-making. We found that evidence use is limited at all levels, in part due to a perceived lack of high-quality, relevant evidence. This perception stems from two main areas: first, desire for local evidence that reflects the context, and second, much existing economic evidence does not deal with what decision-makers value when it comes to community health systems-i.e. coverage and (to a lesser extent) quality. Beyond the evidence gap, there is limited capacity to assess and use the evidence. Elected officials also face political challenges to disinvestment as well as structural obstacles to evidence use, including the outsized influence of donor priorities. Evaluation data must to speak to decision-maker interests and constraints more directly, alongside financiers of community health providing explicit guidance and support on the role of evidence use in decision-making, empowering national decision-makers. Improved data quality, increased relevance of evidence and capacity for evidence use can drive improved efficiency of financing and evidence-based policymaking

Leveraging real-world data to predict cancer cachexia stage, quality of life, and survival in a racially and ethnically diverse multi-institutional cohort of treatment-naïve patients with pancreatic ductal adenocarcinoma

Introduction Cancer-associated cachexia (CC) is a progressive syndrome characterized by unintentional weight loss, muscle atrophy, fatigue, and poor outcomes that affects most patients with pancreatic ductal adenocarcinoma (PDAC). The ability to identify and classify CC stage along its continuum early in the disease process is challenging but critical for management. Objectives The main objective of this study was to determine the prevalence of CC stage overall and by sex and race and ethnicity among treatment-naïve PDAC cases using clinical, nutritional, and functional criteria. Secondary objectives included identifying the prevalence and predictors of higher symptom burden, supportive care needs, and quality of life (QoL), and examining their influence on overall survival (OS). Materials and methods A population-based multi-institutional prospective cohort study of patients with PDAC was conducted between 2018 and 2021 by the Florida Pancreas Collaborative. Leveraging patient-reported data and laboratory values, participants were classified at baseline into four stages [non-cachexia (NCa), pre-cachexia (PCa), cachexia (Ca), and refractory cachexia (RCa)]. Multivariate regression, Kaplan Meier analyses, and Cox regression were conducted to evaluate associations. Results CC stage was estimated for 309 PDAC cases (156 females, 153 males). The overall prevalence of NCa, PCa, Ca, and RCa was 12.9%, 24.6%, 54.1%, and 8.4%, respectively. CC prevalence across all CC stages was highest for males and racial and ethnic minorities. Criteria differentiated NCa cases from other groups, but did not distinguish PCa from Ca. The most frequently reported symptoms included weight loss, fatigue, pain, anxiety, and depression, with pain significantly worsening over time. The greatest supportive care needs included emotional and physical domains. Males, Black people, and those with RCa had the worst OS. Conclusions Using clinical, nutritional, and functional criteria, nearly one-quarter of the PDAC cases in our diverse, multi-institutional cohort had PCa and 62.5% had Ca or RCa at the time of diagnosis. The PCa estimate is higher than that reported in prior studies. We recommend these criteria be used to aid in CC classification, monitoring, and management of all incident PDAC cases. Findings also highlight the recommendation for continued emotional support, assistance in alleviating pain, and supportive care needs throughout the PDAC treatment journey