Comparative effectiveness and cost-effectiveness of treat-to-target versus benefit-based tailored treatment of type 2 diabetes in low-income and middle-income countries: a modelling analysis

Reducing non-communicable diseases among Palestinian populations in Gaza: A participatory comparative and cost-effectiveness modeling assessment

We sought to assess the effectiveness and cost-effectiveness of potential new public health and healthcare NCD risk reduction efforts among Palestinians in Gaza. We created a microsimulation model using: (i) a cross-sectional household survey of NCD risk factors among 4,576 Palestinian adults aged ≥40 years old in Gaza; (ii) a modified Delphi process among local public health experts to identify potentially feasible new interventions; and (iii) reviews of intervention cost and effectiveness, modified to the Gazan and refugee contexts. The survey revealed 28.6% tobacco smoking, a 40.4% prevalence of hypertension diagnosis (with a 95.6% medication treatment rate), a 25.6% prevalence of diabetes diagnosis (with 95.3% on treatment), a 21.9% prevalence of dyslipidemia (with 79.6% on a statin), and a 9.8% prevalence of asthma or chronic obstructive pulmonary disease (without known treatment). A calibrated model estimated a loss of 9,516 DALYs per 10,000 population over the 10-year policy horizon. The interventions having an incremental cost-effectiveness ratio (ICER) less than three times the GDP per capita of Palestine per DALY averted (<$10,992 per DALY averted)(<$10,992 per DALY averted) included bans on tobacco smoking in indoor and public places [$34 per incremental DALY averted (95% CI: $17, $50)], treatment of asthma using low dose inhaled beclometasone and short-acting beta-agonists [$140 per DALY averted (95% CI: $77, $207)], treatment of breast cancer stages I and II [$730 per DALY averted (95% CI: $372, $1,100)], implementing a mass media campaign for healthier nutrition [$737 per DALY averted (95% CI: $403, $1,100)], treatment of colorectal cancer stages I and II [$7,657 per DALY averted (95% CI: $3,721, $11,639)], and (screening with mammography [$17,054 per DALY averted (95% CI: $8,693, $25,359)]). Despite high levels of NCD risk factors among Palestinians in Gaza, we estimated that several interventions would be expected to reduce the loss of DALYs within common cost-effectiveness thresholds.

Economic evaluations of non-communicable diseases conducted in Sub-Saharan Africa: a critical review of data sources

BACKGROUND

Policymakers in sub-Saharan Africa (SSA) face challenging decisions regarding the allocation of health resources. Economic evaluations can help decision makers to determine which health interventions should be funded and or included in their benefits package. A major problem is whether the evaluations incorporated data from sources that are reliable and relevant to the country of interest. We aimed to review the quality of the data sources used in all published economic evaluations for cardiovascular disease and diabetes in SSA.

METHODS

We systematically searched selected databases for all published economic evaluations for CVD and diabetes in SSA. We modified a hierarchy of data sources and used a reference case to measure the adherence to reporting and methodological characteristics, and descriptively analysed author statements.

RESULTS

From 7,297 articles retrieved from the search, we selected 35 for study inclusion. Most were modelled evaluations and almost all focused on pharmacological interventions. The studies adhered to the reporting standards but were less adherent to the methodological standards. The quality of data sources varied. The quality level of evidence in the data domains of resource use and costs were generally considered of high quality, with studies often sourcing information from reliable databases within the same jurisdiction. The authors of most studies referred to data sources in the discussion section of the publications highlighting the challenges of obtaining good quality and locally relevant data.

CONCLUSIONS

The data sources in some domains are considered high quality but there remains a need to make substantial improvements in the methodological adherence and overall quality of data sources to provide evidence that is sufficiently robust to support decision making in SSA within the context of UHC and health benefits plans. Many SSA governments will need to strengthen and build their capacity to conduct economic evaluations of interventions and health technology assessment for improved priority setting. This capacity building includes enhancing local infrastructures for routine data production and management. If many of the policy makers are using economic evaluations to guide resource allocation, it is imperative that the evidence used is of the feasibly highest quality.

Exploring cost drivers to improve disease management: the case of type 2 diabetes at a tertiary hospital in Burundi, Africa

Background

In Burundi, the International Diabetes Federation estimated the prevalence of diabetes mellitus (DM) as high as 2.4% in adults aged between 20 and 79 years old. Thus, the healthcare expenditure for the treatment of diabetic patients is considerably high.

Objective

This study explores the economic burden of type 2 DM and its cost drivers at a tertiary hospital in 2018. It included adult type 2 DM patients who received treatment from a tertiary hospital (Hospital Prince Regent Charles) in 2018. In this study, 81 patients were included.

Methods

Data on illness treatment and complications were collected through patient interviews and by reviewing patients' medical and financial records. A stepwise multiple linear regression model was used to explore factors affecting the cost of type 2 diabetes mellitus.

Results

The average total cost per patient per year was estimated at $2621.06. The fitted cost model had an adjusted R² of 0.427, which explained up to 43% of the variation in the total cost. The results suggest primary cost drivers such as treatment regimen, duration of the disease, payment method, and number of complications.

Conclusion

The findings confirm the profound economic burden of type 2 DM and the need to improve patient care and prevent disease progression. The establishment of a special clinic for patients with diabetes is recommended, as is financial support for underprivileged patients. A specific focus on cost drivers could help establish appropriate disease management programs to control the costs for type 2 diabetes patients.

Application of decision analytical models to diabetes in low- and middle-income countries: a systematic review

BACKGROUND

Decision analytical models (DAMs) are used to develop an evidence base for impact and health economic evaluations, including evaluating interventions to improve diabetes care and health services-an increasingly important area in low- and middle-income countries (LMICs), where the disease burden is high, health systems are weak, and resources are constrained. This study examines how DAMs-in particular, Markov, system dynamic, agent-based, discrete event simulation, and hybrid models-have been applied to investigate non-pharmacological population-based (NP) interventions and how to advance their adoption in diabetes research in LMICs.

METHODS

We systematically searched peer-reviewed articles published in English from inception to 8th August 2022 in PubMed, Cochrane, and the reference list of reviewed articles. Articles were summarised and appraised based on publication details, model design and processes, modelled interventions, and model limitations using the Health Economic Evaluation Reporting Standards (CHEERs) checklist.

RESULTS

Twenty-three articles were fully screened, and 17 met the inclusion criteria of this qualitative review. The majority of the included studies were Markov cohort (7, 41%) and microsimulation models (7, 41%) simulating non-pharmacological population-based diabetes interventions among Asian sub-populations (9, 53%). Eleven (65%) of the reviewed studies evaluated the cost-effectiveness of interventions, reporting the evaluation perspective and the time horizon used to track cost and effect. Few studies (6,35%) reported how they validated models against local data.

CONCLUSIONS

Although DAMs have been increasingly applied in LMICs to evaluate interventions to control diabetes, there is a need to advance the use of DAMs to evaluate NP diabetes policy interventions in LMICs, particularly DAMs that use local research data. Moreover, the reporting of input data, calibration and validation that underlies DAMs of diabetes in LMICs needs to be more transparent and credible.

[Integrating hypertension and diabetes management in primary health care settings: HEARTS as a toolIntegrando o manejo da hipertensão e do diabetes na atenção primária à saúde: uso do HEARTS como instrumento]

Hypertension and diabetes are modifiable cardiovascular disease (CVD) risk factors that contribute to nearly one-third of all deaths in the Americas Region each year (2.3 million deaths). Despite advances in the detection and clinical management of hypertension and diabetes, there are substantial gaps in their implementation globally and in the Region. The considerable overlap in risk factors, prognosis, and treatment of hypertension and diabetes creates a unique opportunity for a unified implementation model for management at the population level. This report highlights one such high-profile effort, the Pan American Health Organization's "HEARTS in the Americas" program, based on the World Health Organization's HEARTS Technical Package for Cardiovascular Disease Management in Primary Health Care. The HEARTS program aims to improve the implementation of preventive CVD care in primary health systems using six evidence-based, pragmatic components: Healthy-lifestyle counseling, Evidence-based protocols, Access to essential medicines and technology, Risk-based CVD management, Team-based care, and Systems for monitoring. To date, HEARTS implementation projects have focused primarily on hypertension given that it is the leading modifiable CVD risk factor and can be treated cost-effectively. The objective of this report is to describe opportunities for integration of diabetes clinical care and policy within the HEARTS hypertension framework. A substantial global burden of disease could be averted with integrated primary care management of these conditions. Thus, there is an urgency in applying lessons from HEARTS to close these implementation gaps and improve the integrated detection, treatment, and control of diabetes and hypertension.

Comprehensive league table of cost-utility ratios: A systematic review of cost-effectiveness evidence for health policy decisions in India

Background and objectives

Although a relatively recent concept for developing countries, the developed world has been using League Tables as a policy guiding tool for a comprehensive assessment of health expenditures; country-specific "League tables" can be a very useful tool for national healthcare planning and budgeting. Presented herewith is a comprehensive league table of cost per Quality Adjusted Life Years (QALY) or Disability Adjusted Life Years (DALY) ratios derived from Health Technology Assessment (HTA) or economic evaluation studies reported from India through a systematic review.

Methods

Economic evaluations and HTAs published from January 2003 to October 2019 were searched from various databases. We only included the studies reporting common outcomes (QALY/DALY) and methodology to increase the generalizability of league table findings. To opt for a uniform criterion, a reference case approach developed by Health Technology Assessment in India (HTAIn) was used for the reporting of the incremental cost-effectiveness ratio. However, as, most of the articles expressed the outcome as DALY, both (QALY and DALY) were used as outcome indicators for this review.

Results

After the initial screening of 9,823 articles, 79 articles meeting the inclusion criteria were selected for the League table preparation. The spectrum of intervention was dominated by innovations for infectious diseases (33%), closely followed by maternal and child health (29%), and non-communicable diseases (20%). The remaining 18% of the interventions were on other groups of health issues, such as injuries, snake bites, and epilepsy. Most of the interventions (70%) reported DALY as an outcome indicator, and the rest (30%) reported QALY. Outcome and cost were discounted at the rate of 3 by 73% of the studies, at 5 by 4% of the studies, whereas 23% of the studies did not discount it. Budget impact and sensitivity analysis were reported by 18 and 73% of the studies, respectively.

Interpretation and conclusions

The present review offers a reasonably coherent league table that reflects ICER values of a range of health conditions in India. It presents an update for decision-makers for making decisions about resource allocation.

Integrating hypertension and diabetes management in primary health care settings: HEARTS as a tool

Hypertension and diabetes are modifiable cardiovascular disease (CVD) risk factors that contribute to nearly one-third of all deaths in the Americas Region each year (2.3 million deaths). Despite advances in the detection and clinical management of hypertension and diabetes, there are substantial gaps in their implementation globally and in the Region. The considerable overlap in risk factors, prognosis, and treatment of hypertension and diabetes creates a unique opportunity for a unified implementation model for management at the population level. This report highlights one such high-profile effort, the Pan American Health Organization's "HEARTS in the Americas" program, based on the World Health Organization's HEARTS Technical Package for Cardiovascular Disease Management in Primary Health Care. The HEARTS program aims to improve the implementation of preventive CVD care in primary health systems using six evidence-based, pragmatic components: Healthy-lifestyle counseling, Evidence-based protocols, Access to essential medicines and technology, Risk-based CVD management, Team-based care, and Systems for monitoring. To date, HEARTS implementation projects have focused primarily on hypertension given that it is the leading modifiable CVD risk factor and can be treated cost-effectively. The objective of this report is to describe opportunities for integration of diabetes clinical care and policy within the HEARTS hypertension framework. A substantial global burden of disease could be averted with integrated primary care management of these conditions. Thus, there is an urgency in applying lessons from HEARTS to close these implementation gaps and improve the integrated detection, treatment, and control of diabetes and hypertension.

Estimated effect of increased diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among low-income and middle-income countries: a microsimulation model

BACKGROUND

Given the increasing prevalence of diabetes in low-income and middle-income countries (LMICs), we aimed to estimate the health and cost implications of achieving different targets for diagnosis, treatment, and control of diabetes and its associated cardiovascular risk factors among LMICs.

METHODS

We constructed a microsimulation model to estimate disability-adjusted life-years (DALYs) lost and health-care costs of diagnosis, treatment, and control of blood pressure, dyslipidaemia, and glycaemia among people with diabetes in LMICs. We used individual participant data-specifically from the subset of people who were defined as having any type of diabetes by WHO standards-from nationally representative, cross-sectional surveys (2006-18) spanning 15 world regions to estimate the baseline 10-year risk of atherosclerotic cardiovascular disease (defined as fatal and non-fatal myocardial infarction and stroke), heart failure (ejection fraction of <40%, with New York Heart Association class III or IV functional limitations), end-stage renal disease (defined as an estimated glomerular filtration rate <15 mL/min per 1·73 m2 or needing dialysis or transplant), retinopathy with severe vision loss (<20/200 visual acuity as measured by the Snellen chart), and neuropathy with pressure sensation loss (assessed by the Semmes-Weinstein 5·07/10 g monofilament exam). We then used data from meta-analyses of randomised controlled trials to estimate the reduction in risk and the WHO OneHealth tool to estimate costs in reaching either 60% or 80% of diagnosis, treatment initiation, and control targets for blood pressure, dyslipidaemia, and glycaemia recommended by WHO guidelines. Costs were updated to 2020 International Dollars, and both costs and DALYs were computed over a 10-year policy planning time horizon at a 3% annual discount rate.

FINDINGS

We obtained data from 23 678 people with diabetes from 67 countries. The median estimated 10-year risk was 10·0% (IQR 4·0-18·0) for cardiovascular events, 7·8% (5·1-11·8) for neuropathy with pressure sensation loss, 7·2% (5·6-9·4) for end-stage renal disease, 6·0% (4·2-8·6) for retinopathy with severe vision loss, and 2·6% (1·2-5·3) for congestive heart failure. A target of 80% diagnosis, 80% treatment, and 80% control would be expected to reduce DALYs lost from diabetes complications from a median population-weighted loss to 1097 DALYs per 1000 population over 10 years (IQR 1051-1155), relative to a baseline of 1161 DALYs, primarily from reduced cardiovascular events (down from a median of 143 to 117 DALYs per 1000 population) due to blood pressure and statin treatment, with comparatively little effect from glycaemic control. The target of 80% diagnosis, 80% treatment, and 80% control would be expected to produce an overall incremental cost-effectiveness ratio of US$1362 per DALY averted (IQR 1304-1409), with the majority of decreased costs from reduced cardiovascular event management, counterbalanced by increased costs for blood pressure and statin treatment, producing an overall incremental cost-effectiveness ratio of $1362 per DALY averted (IQR 1304-1409).

INTERPRETATION

Reducing complications from diabetes in LMICs is likely to require a focus on scaling up blood pressure and statin medication treatment initiation and blood pressure medication titration rather than focusing on increasing screening to increase diabetes diagnosis, or a glycaemic treatment and control among people with diabetes.

FUNDING

None.

Estimating risk factor progression equations for the UKPDS Outcomes Model 2 (UKPDS 90)

OBJECTIVES

To estimate 13 equations that predict clinically plausible risk factor time paths to inform the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model version 2 (UKPDS-OM2).

METHODS

Data from 5102 UKPDS participants from the 20-year trial, and the 4031 survivors with 10 years further post-trial follow-up, were used to derive equations for the time paths of 13 clinical risk factors: HbA_1c , systolic blood pressure, LDL-cholesterol, HDL-cholesterol, BMI, micro- or macro-albuminuria, creatinine, heart rate, white blood cell count, haemoglobin, estimated glomerular filter rate, atrial fibrillation and peripheral vascular disease (PVD). The incidence of events and death predicted by the UKPDS-OM2 when informed by the new risk factor equations was compared with the observed cumulative rates up to 25 years.

RESULTS

The new equations were based on 24 years of follow-up and up to 65,252 person-years of data. Women were associated with higher values of all continuous risk factors except for haemoglobin. Older age and higher BMI at diagnosis were associated with higher rates of PVD (HR 1.06 and 1.02), atrial fibrillation (HR 1.10 and 1.08) and micro- or macro-albuminuria (HR 1.01 and 1.18). Smoking was associated with higher rates of developing PVD (HR 2.38) and micro- and macro-albuminuria (HR 1.39). The UKPDS-OM2, informed by the new risk factor equations, predicted event rates for complications and death consistent with those observed.

CONCLUSIONS

The new equations allow risk factor time paths beyond observed data, which should improve modelling of long-term health outcomes for people with type 2 diabetes when using the UKPDS-OM2 or other models.

Assessing the capacity of Ghana to introduce health technology assessment: a systematic review of economic evaluations conducted in Ghana

OBJECTIVES

Ghana is in the process of formally introducing health technology assessment (HTA) for health decision making. Similar to other low- and middle-income countries, evidence suggests that the lack of data and human capacity is a major barrier to the conduct and use of HTA. This study assessed the current human and data capacity available in Ghana to undertake HTA.

METHODS

As economic evaluation (EE) forms an integral part of HTA, a systematic review of EE studies undertaken in Ghana was conducted to identify the quality and number of studies available, methods and source of data used, and local persons involved. The literature search was undertaken in EMBASE (including MEDLINE), PUBMED, and Google Scholar. The quality of studies was evaluated using the Consolidated Health Economics Evaluation Reporting Standards. The number of local Ghanaians who contributed to authorship were used as a proxy for assessing human capacity for HTA.

RESULTS

Thirty-one studies were included in the final review. Overall, studies were of good quality. Studies derived their effectiveness, resource utilization and cost data mainly from Ghana. The most common source of cost data was from the National Health Insurance Scheme pricing list for medicines and tariffs. Effectiveness data were mostly derived from either single study or intervention programs. Sixty out of 199 authors were Ghanaians (30 percent); these authors were mostly involved in data collection and study conceptualization.

CONCLUSIONS

Human capacity for HTA in Ghana is limited. To introduce HTA successfully in Ghana, policy makers would need to develop more local capacity to undertake Ghanaian-specific HTA.

Population-level mortality benefits of improved blood pressure control in Indonesia: a modelling study

BACKGROUND

There are few estimates of the potential gains in adult mortality from population-level improvements in systolic blood pressure (SBP) in a major low-and-middle income country (LMIC). Using nationally representative cohort data from Indonesia-the third most populous LMIC- I estimated the gains in adult life expectancy from improving SBP control among adults ages 40 and above and assessed the benefits among richer and poorer subpopulations.

METHODS

I used longitudinal data from 10 085 adults ages 40 and above (75 288 person-age observations) enrolled in the 2007 and 2014/15 waves of the Indonesian Family Life Survey. Next, I used Poisson-regression parametric g-formulas to directly estimate age-specific mortality rates under different blood pressure control strategies and constructed period life expectancies using the observed and counterfactual mortality rates.

RESULTS

Fully controlling SBP to a population mean of under 125 mmHg was associated with a life expectancy gain at age 40 of 5.3 years [95% confidence interval (CI): 3.2, 7.4] for men and 6.0 years (95% CI: 3.6, 8.4) for women. The gains associated with blood pressure control were similar for both rich and poor subpopulations. The life expectancy gains under scenarios with imperfect blood pressure control and coverage were more modest in size and ranged between 1 and 2.5 years for a large fraction of the scenarios.

CONCLUSIONS

In Indonesia, elevated SBP carries a large mortality burden, though the results suggest that realistic efforts to address hypertension will likely produce more modest gains in life expectancy. Comparing improvements from different strategies and identifying the most cost-effective ways to introduce and scale up hypertension interventions is a critical focus for both research and policy.

Outcomes and Strategies to Support a Treat-to-target Approach in Inflammatory Bowel Disease: A Systematic Review

BACKGROUND AND AIMS

Management of Crohn's disease and ulcerative colitis has typically relied upon treatment intensification driven by symptoms alone. However, a 'treat-to-target' management approach may help to address underlying inflammation, minimise disease activity at early stages of inflammatory bowel disease, limit progression, and improve long-term outcomes.

METHODS

A systematic literature review was conducted to identify data relevant to a treat-to-target approach in inflammatory bowel disease, published between January 1, 2007 and May 15, 2017.

RESULTS

Consistent with recommendations of the Selecting Therapeutic Targets in Inflammatory Bowel Disease [STRIDE] working group, studies have investigated factors influencing the achievement of both endoscopic and histological mucosal healing and patient-level outcomes in inflammatory bowel disease [IBD]. Histological healing and biomarker levels have also been shown to be modifiable outcomes. Although there is a lack of prospectively derived evidence validating mucosal healing as a treatment target, data are emerging to suggest that targeting mucosal healing or inflammation rather than symptoms may be cost-effective in some settings. The review highlighted several strategies that may support the implementation of a treat-to-target approach in IBD. The prospective randomised CALM study demonstrated how tight control [whereby treatment decisions are based on close monitoring of inflammatory biomarkers] leads to improvements in endoscopic and clinical outcomes. The review also considered the influence of coordinated care from a multidisciplinary team and patient engagement with improved adherence, as well as the role of therapeutic drug monitoring in inflammatory bowel disease management.

CONCLUSIONS

A treat-to-target strategy may impact on disease progression and improve outcomes in inflammatory bowel disease. Prospective studies including long-term data are required to ensure that the most appropriate targets and strategies are identified.

Economic effects of the double burden of malnutrition

Observations from many countries indicate that multiple forms of malnutrition might coexist in a country, a household, and an individual. In this Series, the double burden of malnutrition (DBM) encompasses undernutrition in the form of stunting, and overweight and obesity. Health effects of the DBM include those associated with both undernutrition, such as impaired childhood development and greater susceptibility to infectious diseases, and overweight, especially in terms of increased risk of added visceral fat and increased risk of non-communicable diseases. These health effects have not been translated into economic costs for individuals and economies in the form of lost wages and productivity, as well as higher medical expenses. We summarise the existing approaches to modelling the economic effects of malnutrition and point out the weaknesses of these approaches for measuring economic losses from the DBM. Where population needs suggest that nutrition interventions take into account the DBM, economic evaluation can guide the choice of so-called double-duty interventions as an alternative to separate programming for stunting and overweight. We address the evidence gap with an economic analysis of the costs and benefits of an illustrative double-duty intervention that addresses both stunting and overweight in children aged 4 years and older by providing school meals with improved quality of diet. We assess the plausibility of our method and discuss how improved data and models can generate better estimates. Double-duty interventions could save money and be more efficient than single-duty interventions.

A Prediction Model for Uncontrolled Type 2 Diabetes Mellitus Incorporating Area-level Social Determinants of Health

BACKGROUND

Social determinants of health (SDH) at the area level are understood to influence the likelihood of having poor glycemic control for patients with type 2 diabetes mellitus (T2DM).

OBJECTIVES

To develop a model for predicting whether a person with T2DM has uncontrolled diabetes (hemoglobin A1c ≥9%), incorporating individual and area-level (census tract) covariates.

RESEARCH DESIGN

Development and validation of machine learning models.

SUBJECTS

Total of N=1,015,808 privately insured persons in claims data with T2DM.

MEASURES

C-statistic, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy.

RESULTS

A standard logistic regression model selecting among the available individual-level covariates and area-level SDH covariates (at the census tract level) performed poorly, with a C-statistic of 0.685, sensitivity of 25.6%, specificity of 90.1%, positive predictive value of 56.9%, negative predictive value of 70.4%, and accuracy of 68.4% on a 25% held-out validation subset of the data. By contrast, machine learning models improved upon risk prediction, with the highest performance from a random forest algorithm with a C-statistic of 0.928, sensitivity of 68.5%, specificity of 94.6%, positive predictive value of 69.8%, negative predictive value of 94.3%, and accuracy of 90.6%. SDH variables alone explained 16.9% of variation in uncontrolled diabetes.

CONCLUSIONS

A predictive model developed through a machine learning approach may assist health care organizations to identify which area-level SDH data to monitor for prediction of diabetes control, for potential use in risk-adjustment and targeting.

Incidence, socio-economic inequalities and determinants of catastrophic health expenditure and impoverishment for diabetes care in South Africa: a study at two public hospitals in Tshwane

BACKGROUND

Direct out of pocket (OOP) payments for healthcare may cause financial hardship. For diabetic patients who require frequent visits to health centres, this is of concern as OOP payments may limit access to healthcare. This study assesses the incidence, socio-economic inequalities and determinants of catastrophic health expenditure and impoverishment amongst diabetic patients in South Africa.

METHODS

Data were taken from a cross-sectional survey conducted in 2017 at two public hospitals in Tshwane, South Africa (N = 396). Healthcare costs and transport costs related to diabetes care were classified as catastrophic if they exceeded the 10% threshold of household's capacity to pay (WHO standard method) or if they exceeded a variable threshold of total household expenditure (Ataguba method). Erreygers concentration indices (CIs) were used to assess socio-economic inequalities. A multivariate logistic regression was applied to identify the determinants of catastrophic health expenditure and impoverishment.

RESULTS

Transport costs contributed to over 50% of total healthcare costs. The incidence of catastrophic health expenditure was 25% when measured at a 10% threshold of capacity to pay and 13% when measured at a variable threshold of total household expenditure. Depending on the method used, the incidence of impoverishment varied from 2 to 4% and the concentration index for catastrophic health expenditure varied from - 0.2299 to - 0.1026. When measured at a 10% threshold of capacity to pay factors associated with catastrophic health expenditure were being female (Odds Ratio 1.73; Standard Error 0.51), being within the 3rd (0.49; 0.20), 4th (0.31; 0.15) and 5th wealth quintile (0.30; 0.17). When measured using a variable threshold of total household expenditure factors associated with catastrophic health expenditure were not having children (3.35; 1.82) and the 4th wealth quintile (0.32; 0.21).

CONCLUSION

Financial protection of diabetic patients in public hospitals is limited. This observation suggests that health financing interventions amongst diabetic patients should target the poor and poor women in particular. There is also a need for targeted interventions to improve access to healthcare facilities for diabetic patients and to reduce the financial impact of transport costs when seeking healthcare. This is particularly important for the achievement of universal health coverage in South Africa.

Economic Impact of Diabetes in South Asia: the Magnitude of the Problem

PURPOSE OF REVIEW

To critically assess and identify gaps in the current literature on the economic impact of diabetes in South Asia.

RECENT FINDINGS

The total annual (direct medical and non-medical and indirect) costs for diabetes care in South Asia range from $483-$2637 per patient, and on an average 5.8% of patients with diabetes suffer catastrophic spending i.e. when households reduce basic expenditure by 40% to cope with healthcare costs. The mean direct costs per patient are positively associated with a country's gross domestic product (GDP) per capita, although there is wide heterogeneity across South Asian countries. With an estimated 84 million people suffering from diabetes in South Asia, diabetes imposes a substantial economic burden on individuals, families, and society. Since the disease burden increasingly occurs in the most productive midlife period, it adversely affects workforce productivity and macroeconomic development. Diabetes-related complications lead to markedly higher treatment costs, causing catastrophic medical spending for many households, thus underscoring the importance of preventing diabetes-related complications.

Estimation of global insulin use for type 2 diabetes, 2018-30: a microsimulation analysis

BACKGROUND

The amount of insulin needed to effectively treat type 2 diabetes worldwide is unknown. It also remains unclear how alternative treatment algorithms would affect insulin use and disability-adjusted life-years (DALYs) averted by insulin use, given that current access to insulin (availability and affordability) in many areas is low. The aim of this study was to compare alternative projections for and consequences of insulin use worldwide under varying treatment algorithms and degrees of insulin access.

METHODS

We developed a microsimulation of type 2 diabetes burden from 2018 to 2030 across 221 countries using data from the International Diabetes Federation for prevalence projections and from 14 cohort studies representing more than 60% of the global type 2 diabetes population for HbA_1c, treatment, and bodyweight data. We estimated the number of people with type 2 diabetes expected to use insulin, international units (IU) required, and DALYs averted per year under alternative treatment algorithms targeting HbA_1c from 6·5% to 8%, lower microvascular risk, or higher HbA_1c for those aged 75 years and older.

FINDINGS

The number of people with type 2 diabetes worldwide was estimated to increase from 405·6 million (95% CI 315·3 million-533·7 million) in 2018 to 510·8 million (395·9 million-674·3 million) in 2030. On this basis, insulin use is estimated to increase from 516·1 million 1000 IU vials (95% CI 409·0 million-658·6 million) per year in 2018 to 633·7 million (500·5 million-806·7 million) per year in 2030. Without improved insulin access, 7·4% (95% CI 5·8-9·4) of people with type 2 diabetes in 2030 would use insulin, increasing to 15·5% (12·0-20·3) if insulin were widely accessible and prescribed to achieve an HbA_1c of 7% (53 mmol/mol) or lower. If HbA_1c of 7% or lower was universally achieved, insulin would avert 331 101 DALYs per year by 2030 (95% CI 256 601-437 053). DALYs averted would increase by 14·9% with access to newer oral antihyperglycaemic drugs. DALYs averted would increase by 44·2% if an HbA_1c of 8% (64 mmol/mol) were used as a target among people aged 75 years and older because of reduced hypoglycaemia.

INTERPRETATION

The insulin required to treat type 2 diabetes is expected to increase by more than 20% from 2018 to 2030. More DALYs might be averted if HbA_1c targets are higher for older adults.

FUNDING

The Leona M and Harry B Helmsley Charitable Trust.

Matching Microsimulation Risk Factor Correlations to Cross-sectional Data: The Shortest Distance Method

BACKGROUND

Microsimulation models often compute the distribution of a simulated cohort's risk factors and medical outcomes over time using repeated waves of cross-sectional data. We sought to develop a strategy to simulate how risk factor values remain correlated over time within individuals, and compare it to available alternative methods.

METHODS

We developed a method using shortest-distance matching for modeling changes in risk factors in individuals over time, which preserves both the cohort distribution of each risk factor as well as the cross-sectional correlation between risk factors observed in repeated cross-sectional data. We compared the performance of the method with rank stability and regression methods, using both synthetic data and data from the Framingham Offspring Heart Study (FOHS) to simulate a cohort's atherosclerotic cardiovascular disease (ASCVD) risk.

RESULTS

The correlation between risk factors was better preserved using the shortest distance method than with rank stability or regression (root mean squared difference = 0.077 with shortest distance, v. 0.126 with rank stability and 0.146 with regression in FOHS, and 0.052, 0.426 and 0.352, respectively, in the synthetic data). The shortest distance method generated population ASCVD risk estimate distributions indistinguishable from the true distribution in over 99.8% of cases (Kolmogorov-Smirnov, P > 0.05), outperforming some existing regression methods, which produced ASCVD distributions statistically distinguishable from the true one at the 5% level around 15% of the time.

LIMITATIONS

None of the methods considered could predict individual longitudinal trends without error. The shortest-distance method was not statistically inferior to rank stability or regression methods for predicting individual risk factor values over time in the FOHS.

CONCLUSIONS

A shortest distance method may assist in preserving risk factor correlations in microsimulations informed by cross-sectional data.

Validation of Risk Equations for Complications of Type 2 Diabetes (RECODe) Using Individual Participant Data From Diverse Longitudinal Cohorts in the U.S

OBJECTIVE

We sought to validate Risk Equations for Complications of Type 2 Diabetes (RECODe) among diverse populations.

RESEARCH DESIGN AND METHODS

We compared risk predictions from RECODe equations and from two alternative risk models (UK Prospective Diabetes Study Outcomes Model 2 [UKPDS OM2] and American College of Cardiology/American Heart Association Pooled Cohort Equations) to observed outcomes in two studies: the Multi-Ethnic Study of Atherosclerosis (MESA, n = 1,555 adults with type 2 diabetes, median follow-up 9.1 years) and the Jackson Heart Study (JHS, n = 1,746 adults with type 2 diabetes, median follow-up 8.0 years). Outcomes included nephropathy by multiple measures (microalbuminuria, macroalbuminuria, renal failure, end-stage renal disease, and reduction in glomerular filtration rate), moderate to severe diabetic retinopathy by Airlie House classification, fatal or nonfatal myocardial infarction, fatal or nonfatal stroke, congestive heart failure, and all-cause mortality.

RESULTS

RECODe equations for microvascular and cardiovascular outcomes had C-statistics for discrimination ranging from 0.71 to 0.85 in MESA and 0.64 to 0.91 in JHS for alternative outcomes. Calibration slopes in MESA ranged from 0.62 for a composite nephropathy outcome, 0.83-1.04 for individual nephropathy outcomes, 1.07 for retinopathy, 1.00-1.05 for cardiovascular outcomes, and 1.03 for all-cause mortality. Slopes in JHS ranged from 0.47 for retinopathy, 0.97-1.16 for nephropathy, 0.72-1.05 for cardiovascular outcomes, and 1.01 for all-cause mortality. The alternative models had C-statistics 0.50-0.72 and calibration slopes 0.07-0.60.

CONCLUSIONS

RECODe equations improved risk estimation for diverse patients with type 2 diabetes, as compared with two commonly used alternatives.

Individualized Glycemic Control for U.S. Adults With Type 2 Diabetes: A Cost-Effectiveness Analysis

BACKGROUND

Intensive glycemic control in type 2 diabetes (glycated hemoglobin [HbA1c] level <7%) is an established, cost-effective standard of care. However, guidelines recommend individualizing goals on the basis of age, comorbidity, diabetes duration, and complications.

OBJECTIVE

To estimate the cost-effectiveness of individualized control versus uniform intensive control (HbA1c level <7%) for the U.S. population with type 2 diabetes.

DESIGN

Patient-level Monte Carlo-based Markov model.

DATA SOURCES

National Health and Nutrition Examination Survey 2011-2012.

TARGET POPULATION

The approximately 17.3 million persons in the United States with diabetes diagnosed at age 30 years or older.

TIME HORIZON

Lifetime.

PERSPECTIVE

Health care sector.

INTERVENTION

Individualized versus uniform intensive glycemic control.

OUTCOME MEASURES

Average lifetime costs, life-years, and quality-adjusted life-years (QALYs).

RESULTS OF BASE-CASE ANALYSIS

Individualized control saved $13 547 per patient compared with uniform intensive control ($105 307 vs. $118 854), primarily due to lower medication costs ($34 521 vs. $48 763). Individualized control decreased life expectancy (20.63 vs. 20.73 years) due to an increase in complications but produced more QALYs (16.68 vs. 16.58) due to fewer hypoglycemic events and fewer medications.

RESULTS OF SENSITIVITY ANALYSIS

Individualized control was cost-saving and generated more QALYs compared with uniform intensive control, except in analyses where the disutility associated with receiving diabetes medications was decreased by at least 60%.

LIMITATION

The model did not account for effects of early versus later intensive glycemic control.

CONCLUSION

Health policies and clinical programs that encourage an individualized approach to glycemic control for U.S. adults with type 2 diabetes reduce costs and increase quality of life compared with uniform intensive control. Additional research is needed to confirm the risks and benefits of this strategy.

PRIMARY FUNDING SOURCE

National Institute of Diabetes and Digestive and Kidney Diseases.

Cost of diabetes mellitus in Africa: a systematic review of existing literature

Background

There is an increasing recognition that non communicable diseases impose large economic costs on households, societies and nations. However, not much is known about the magnitude of diabetes expenditure in African countries and to the best of our knowledge no systematic assessment of the literature on diabetes costs in Africa has been conducted. The aim of this paper is to capture the evidence on the cost of diabetes in Africa, review the methods used to calculate costs and identify areas for future research.

Methods

A desk search was conducted in Pubmed, Medline, Embase, and Science direct as well as through other databases, namely Google Scholar. The following eligibility criteria were used: peer reviewed English articles published between 2006 and 2016, articles that reported original research findings on the cost of illness in diabetes, and studies that covered at least one African country. Information was extracted using two data extraction sheets and results organized in tables. Costs presented in the studies under review are converted to 2015 international dollars prices (I$).

Results

Twenty six articles are included in this review. Annual national direct costs of diabetes differed between countries and ranged from I$3.5 billion to I$4.5 billion per annum. Indirect costs per patient were generally higher than the direct costs per patient of diabetes. Outpatient costs varied by study design, data source, perspective and healthcare cost categories included in the total costs calculation. The most commonly included healthcare items were drug costs, followed by diagnostic costs, medical supply or disposable costs and consultation costs. In studies that reported both drug costs and total costs, drug costs took a significant portion of the total costs per patient. The highest burden due to the costs associated with diabetes was reported in individuals within the low income group.

Conclusion

Estimation of the costs associated with diabetes is crucial to make progress towards meeting the targets laid out in Sustainable Development Goal 3 set for 2030. The studies included in this review show that the presence of diabetes leads to elevated costs of treatment which further increase in the presence of complications. The cost of drugs generally contributed the most to total direct costs of treatment. Various methods are used in the estimation of diabetes healthcare costs and the costs estimated between countries differ significantly. There is room to improve transparency and make the methodologies used standard in order to allow for cost comparisons across studies.

Electronic supplementary material

The online version of this article (10.1186/s12992-017-0318-5) contains supplementary material, which is available to authorized users.

Development and validation of Risk Equations for Complications Of type 2 Diabetes (RECODe) using individual participant data from randomised trials

BACKGROUND

In view of substantial mis-estimation of risks of diabetes complications using existing equations, we sought to develop updated Risk Equations for Complications Of type 2 Diabetes (RECODe).

METHODS

To develop and validate these risk equations, we used data from the Action to Control Cardiovascular Risk in Diabetes study (ACCORD, n=9635; 2001-09) and validated the equations for microvascular events using data from the Diabetes Prevention Program Outcomes Study (DPPOS, n=1018; 1996-2001), and for cardiovascular events using data from the Action for Health in Diabetes (Look AHEAD, n=4760; 2001-12). Microvascular outcomes were nephropathy, retinopathy, and neuropathy. Cardiovascular outcomes were myocardial infarction, stroke, congestive heart failure, and cardiovascular mortality. We also included all-cause mortality as an outcome. We used a cross-validating machine learning method to select predictor variables from demographic characteristics, clinical variables, comorbidities, medications, and biomarkers into Cox proportional hazards models for each outcome. The new equations were compared to older risk equations by assessing model discrimination, calibration, and the net reclassification index.

FINDINGS

All equations had moderate internal and external discrimination (C-statistics 0·55-0·84 internally, 0·57-0·79 externally) and high internal and external calibration (slopes 0·71-1·31 between observed and estimated risk). Our equations had better discrimination and calibration than the UK Prospective Diabetes Study Outcomes Model 2 (for microvascular and cardiovascular outcomes, C-statistics 0·54-0·62, slopes 0·06-1·12) and the American College of Cardiology/American Heart Association Pooled Cohort Equations (for fatal or non-fatal myocardial infarction or stroke, C-statistics 0·61-0·66, slopes 0·30-0·39).

INTERPRETATION

RECODe might improve estimation of risk of complications for patients with type 2 diabetes.

FUNDING

National Institute for Diabetes and Digestive and Kidney Disease, National Heart, Lung and Blood Institute, and National Institute on Minority Health and Health Disparities, National Institutes of Health, and US Department of Veterans Affairs.