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The importance of non-communicable diseases (NCD) for the health status of Samoa's population cannot be overstated - NCD causes are responsible for 7 of 10 pre-mature deaths with 3 of 10 due to cardiovascular causes alone1. Many adults are hypertensive while rates of type diabetes and obesity are among the highest in the world and on an increasing trend. The 2013 Stepwise Approach to Surveillance (STEPS) survey found that 28.9 percent of the Samoa population are hypertensive, and 24.8 percent have diabetes. In response, the Government of Samoa has made NCD control and people, centered health services a priority in its Strategy for the Development of Samoa 2016/17-2019/20 and issued the National NCD Policy 2019-2023. In 2015, it contextualized and piloted WHO's Package of Essential Non-communicable diseases (PEN) interventions and collected implementation experiences. The PEN Fa'a Samoa is oriented toward community participation and outreach services. It places emphasis on early detection of NCDs, effective referral and increasing population awareness of NCD risk factors. However four years after initiating PEN Fa'a Samoa program, it had only been rolled out to 17 out of total 431 villages in the country indicating the stagnant status of the screening. A World Bank study of NCD cost analysis in 2017 flagged low hypertension (HTN) treatment levels in Samoa as an issue of concern. The widespread HTN and the significant cardiovascular disease burden and high premature deaths suggest that the continuum of HTN care is sub-optimal in Samoa. To support the Government in improving NCD care, the World Bank joined the Ministry of Health (MOH) in 2018 to conduct a study on HTN and chronic care. The primary aim was to identify breakpoints and gaps in the continuum of HTN care and determine issues in chronic care and propose potential solutions. The study findings inform Samoa's policy formulation, intervention implementation and the World Bank's Samoa NCD control project. As the first in the Pacific Region to do an implementation cascade study, other Pacific Island Countries (PICs) may also draw on the findings of the study.

AbstractIntroductionSouth Africa's National Department of Health launched the National Adherence Guidelines for Chronic Diseases in 2015. These guidelines include adherence clubs (AC) and decentralized medication delivery (DMD) as two differentiated models of care for stable HIV patients on antiretroviral therapy. While the adherence guidelines do not suggest that provider costs (costs to the healthcare system for medications, laboratory tests and visits to clinics or alternative locations) for stable patients in these differentiated models of care will be lower than conventional, clinic‐based care, recent modelling exercises suggest that such differentiated models could substantially reduce provider costs. In the context of continued implementation of the guidelines, we discuss the conditions under which provider costs of care for stable HIV patients could fall, or rise, with AC and DMD models of care in South Africa.DiscussionIn prior studies of HIV care and treatment costs, three main cost categories are antiretroviral medications, laboratory tests and general interaction costs based on encounters with health workers. Stable patients are likely to be on the national first‐line regimen (Tenofovir/Entricitabine/Efavarinz (TDF/FTC/EFV)), so no difference in the costs of medications is expected. Laboratory testing guidelines for stable patients are the same regardless of the model of care, so no difference in laboratory costs is expected as well. Based on existing information regarding the costs of clinic visits, AC visits and DMD drug pickups, we expect that for some clinics, visit costs for DMD or AC models of care could be less, but modestly so, than for conventional, clinic‐based care. For other clinics, however, DMD or AC models could have higher visit costs (see Table 2).ConclusionsThe standard of care for stable patients has already been "differentiated" for years in South Africa, prior to the roll out of the new adherence guidelines. AC and DMD models of care, when implemented as envisioned in the guidelines, are unlikely to generate substantive reductions or increases in provider costs of care.

AbstractIntroductionIn response to suboptimal adherence and retention, South Africa's National Department of Health developed and implemented National Adherence Guidelines for Chronic Diseases. We evaluated the effect of a package of adherence interventions beginning in January 2016 and report on the impact of Fast‐Track Treatment Initiation Counselling (FTIC) on ART initiation, adherence and retention.MethodsWe conducted a cluster‐randomized mixed‐methods evaluation in 4 provinces at 12 intervention sites which implemented FTIC and 12 control facilities providing standard of care. Follow‐up was by passive surveillance using clinical records. We included data on subjects eligible for FTIC between 08 Jan 2016 and 07 December 2016. We adjusted for pre‐intervention differences using difference‐in‐differences (DiD) analyses controlling for site‐level clustering.ResultsWe enrolled 362 intervention and 368 control arm patients. Thirty‐day ART initiation was 83% in the intervention and 82% in the control arm (RD 0.5%; 95% CI: −5.0% to 6.0%). After adjusting for baseline ART initiation differences and covariates using DiD we found a 6% increase in ART initiation associated with FTIC (RD 6.3%; 95% CI: −0.6% to 13.3%). We found a small decrease in viral suppression within 18 months (RD −2.8%; 95% CI: −9.8% to 4.2%) with no difference after adjustment (RD: −1.9%; 95% CI: −9.1% to 5.4%) or when considering only those with a viral load recorded (84% intervention vs. 86% control). We found reduced crude 6‐month retention in intervention sites (RD −7.2%; 95% CI: −14.0% to −0.4%). However, differences attenuated by 12 months (RD: −3.6%; 95% CI: −11.1% to 3.9%). Qualitative data showed FTIC counselling was perceived as beneficial by patients and providers.ConclusionsWe saw a short‐term ART‐initiation benefit to FTIC (particularly in districts where initiation prior to intervention was lower), with no reductions but also no improvement in longer‐term retention and viral suppression. This may be due to lack of fidelity to implementation and delivery of those components that support retention and adherence. FTIC must continue to be implemented alongside other interventions to achieve the 90‐90‐90 cascade and fidelity to post‐initiation counselling sessions must be monitored to determine impact on longer‐term outcomes. Understanding the cost‐benefit and role of FTIC may then be warranted.

AbstractIntroductionIn 2014, city leaders from around the world endorsed the Paris Declaration on Fast‐Track Cities, pledging to achieve the 2020 and 2030 HIV targets championed by UNAIDS. The City of Johannesburg – one of South Africa's metropolitan municipalities and also a health district – has over 600,000 people living with HIV (PLHIV), more than any other city worldwide. We estimate what it would take in terms of programmatic targets and costs for the City of Johannesburg to meet the Fast‐Track targets, and demonstrate the impact that this would have.MethodsWe applied the Optima HIV epidemic and resource allocation model to demographic, epidemiological and behavioural data on 26 sub‐populations in Johannesburg. We used data on programme costs and coverage to produce baseline projections. We calculated how many people must be diagnosed, put onto treatment and maintained with viral suppression to achieve the 2020 and 2030 targets. We also estimated how treatment needs – and therefore fiscal commitments – could be reduced if the treatment targets are combined with primary HIV prevention interventions (voluntary medical male circumcision (VMMC), an expanded condom programme, and comprehensive packages for female sex workers (FSW) and young females).ResultsIf current programmatic coverage were maintained, Johannesburg could expect 303,000 new infections and 96,000 AIDS‐related deaths between 2017 and 2030 and 769,000 PLHIV by 2030. Achieving the Fast‐Track targets would require an additional 135,000 diagnoses and 232,000 people on treatment by 2020 (an increase in around 80% over 2016 treatment numbers), but would avert 176,000 infections and 56,500 deaths by 2030. Assuming stable ART unit costs, this would require ZAR 29 billion (USD 2.15 billion) in cumulative treatment investments over the 14 years to 2030. Plausible scale‐ups of other proven interventions (VMMC, condom distribution and FSW strategies) could yield additional reductions in new infections (between 4 and 15%), and in overall treatment investment needs. Scaling up VMMC in line with national targets is found to be cost‐effective in the medium term.ConclusionsThe scale‐up in testing and treatment programmes over this decade has been rapid, but these efforts must be doubled to reach 2020 targets. Strategic investments in proven interventions will help Johannesburg achieve the treatment targets and be on track to end AIDS by 2030.

Background: Diabetes is one of the leading causes of poor health and high care costs in Ukraine. To prevent diabetes complications and alleviate the financial burden of diabetes care on patients, the Ukrainian government reimburses diabetes medication and provides glucose monitoring, but there are significant gaps in the care continuum. We estimate the costs of providing diabetes care and the most cost-effective ways to address these gaps in the Poltava region of Ukraine. Methods: We gathered data on the unit costs of diabetes interventions in Poltava and estimated expenditure on diabetes care. We estimated the optimal combination of facility-based and outreach screening and investigated how additional funding could best be allocated to improve glucose control outcomes. Results: Of the ~ 40,000 adults in diabetes care, only ~ 25% achieved sustained glucose control. Monitoring costs were higher for those who did not: by 10% for patients receiving non-pharmacological treatment, by 61% for insulin patients, and twice as high for patients prescribed oral treatment. Initiatives to improve treatment adherence (e.g. medication copayment schemes, enhanced adherence counseling) would address barriers along the care continuum and we estimate such expenditures may be recouped by reductions in patient monitoring costs. Improvements in case detection are also needed, with only around two-thirds of estimated cases having been diagnosed. Outreach screening campaigns could play a significant role: depending on how well-targeted and scalable such campaigns are, we estimate that 10-46% of all screening could be conducted via outreach, at a cost per positive patient identified of US$7.12-9.63. Conclusions: Investments to improve case detection and treatment adherence are the most efficient interventions for improved diabetes control in Poltava. Quantitative tools provide essential decision support for targeting investment to close the gaps in care.

BACKGROUND: Diabetes is one of the leading causes of poor health and high care costs in Ukraine. To prevent diabetes complications and alleviate the financial burden of diabetes care on patients, the Ukrainian government reimburses diabetes medication and provides glucose monitoring, but there are significant gaps in the care continuum. We estimate the costs of providing diabetes care and the most cost-effective ways to address these gaps in the Poltava region of Ukraine. METHODS: We gathered data on the unit costs of diabetes interventions in Poltava and estimated expenditure on diabetes care. We estimated the optimal combination of facility-based and outreach screening and investigated how additional funding could best be allocated to improve glucose control outcomes. RESULTS: Of the ~ 40,000 adults in diabetes care, only ~ 25% achieved sustained glucose control. Monitoring costs were higher for those who did not: by 10% for patients receiving non-pharmacological treatment, by 61% for insulin patients, and twice as high for patients prescribed oral treatment. Initiatives to improve treatment adherence (e.g. medication copayment schemes, enhanced adherence counseling) would address barriers along the care continuum and we estimate such expenditures may be recouped by reductions in patient monitoring costs. Improvements in case detection are also needed, with only around two-thirds of estimated cases having been diagnosed. Outreach screening campaigns could play a significant role: depending on how well-targeted and scalable such campaigns are, we estimate that 10–46% of all screening could be conducted via outreach, at a cost per positive patient identified of US$7.12–9.63. CONCLUSIONS: Investments to improve case detection and treatment adherence are the most efficient interventions for improved diabetes control in Poltava. Quantitative tools provide essential decision support for targeting investment to close the gaps in care.

AbstractIntroductionIn 2014, the South African government adopted a differentiated service delivery (DSD) model in its "National Adherence Guidelines for Chronic Diseases (HIV, TB and NCDs)" (AGL) to strengthen the HIV care cascade. We describe the barriers and facilitators of the AGL implementation as experienced by various stakeholders in eight intervention and control sites across four districts.MethodsEmbedded within a cluster‐randomized evaluation of the AGL, we conducted 48 in‐depth interviews (IDIs) with healthcare providers, 16 IDIs with Department of Health and implementing partners and 24 focus group discussions (FGDs) with three HIV patient groups: new, stable and those not stable on treatment or not adhering to care. IDIs were conducted from August 2016 to August 2017; FGDs were conducted in January to February 2017. Content analysis was guided by the Consolidated Framework for Implementation Research. Findings were triangulated among respondent types to elicit barriers and facilitators to implementation.ResultsNew HIV patients found counselling helpful but intervention respondents reported sub‐optimal counselling and privacy concerns as barriers to initiation. Providers felt insufficiently trained for this intervention and were confused by the simultaneous rollout of the Universal Test and Treat strategy. For stable patients, repeat prescription collection strategies (RPCS) were generally well received. Patients and providers concurred that RPCS reduced congestion and waiting times at clinics. There was confusion though, among providers and implementers, around implementation of RPCS interventions. For patients not stable on treatment, enhanced counselling and tracing patients lost‐to‐follow‐up were perceived as beneficial to adherence behaviours but faced logistical challenges. All providers faced difficulties accessing data and identifying patients in need of tracing. Congestion at clinics and staff attitude were perceived as barriers preventing patients returning to care.ConclusionsImplementation of DSD models at scale is complex but this evaluation identified several positive aspects of AGL implementation. The positive perception of RPCS interventions and challenges managing patients not stable on treatment aligned with results from the larger evaluation. While some implementation challenges may resolve with experience, ensuring providers and implementers have the necessary training, tools and resources to operationalize AGL effectively is critical to the overall success of South Africa's HIV control strategy.

INTRODUCTION: In 2014, the South African government adopted a differentiated service delivery (DSD) model in its "National Adherence Guidelines for Chronic Diseases (HIV, TB and NCDs)" (AGL) to strengthen the HIV care cascade. We describe the barriers and facilitators of the AGL implementation as experienced by various stakeholders in eight intervention and control sites across four districts. METHODS: Embedded within a cluster‐randomized evaluation of the AGL, we conducted 48 in‐depth interviews (IDIs) with healthcare providers, 16 IDIs with Department of Health and implementing partners and 24 focus group discussions (FGDs) with three HIV patient groups: new, stable and those not stable on treatment or not adhering to care. IDIs were conducted from August 2016 to August 2017; FGDs were conducted in January to February 2017. Content analysis was guided by the Consolidated Framework for Implementation Research. Findings were triangulated among respondent types to elicit barriers and facilitators to implementation. RESULTS: New HIV patients found counselling helpful but intervention respondents reported sub‐optimal counselling and privacy concerns as barriers to initiation. Providers felt insufficiently trained for this intervention and were confused by the simultaneous rollout of the Universal Test and Treat strategy. For stable patients, repeat prescription collection strategies (RPCS) were generally well received. Patients and providers concurred that RPCS reduced congestion and waiting times at clinics. There was confusion though, among providers and implementers, around implementation of RPCS interventions. For patients not stable on treatment, enhanced counselling and tracing patients lost‐to‐follow‐up were perceived as beneficial to adherence behaviours but faced logistical challenges. All providers faced difficulties accessing data and identifying patients in need of tracing. Congestion at clinics and staff attitude were perceived as barriers preventing patients returning to care. CONCLUSIONS: ...

AbstractIntroductionWith limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources.MethodsEach study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts.Results and discussionThe optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required.ConclusionsGreater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

INTRODUCTION: With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS: Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION: The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS: Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

INTRODUCTION With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.

INTRODUCTION: With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS: Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION: The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS: Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process.