Dataset Information

Estimating the Health Care Expenditure to Manage and Care for Type 2 Diabetes in Nepal: A Patient Perspective.

ABSTRACT: Background. This study aimed to estimate the health care expenditure for managing type 2 diabetes (T2D) in the community setting of Nepal. Methods. This is a baseline cross-sectional study of a heath behavior intervention that was conducted between September 2021 and February 2022 among patients with T2D (N = 481) in the Kavrepalanchok and Nuwakot districts of Nepal. Bottom-up and micro-costing approaches were used to estimate the health care costs and were stratified according to residential status and the presence of comorbid conditions. A generalized linear model with a log-link and gamma distribution was applied for modeling the continuous right-skewed costs, and 95% confidence intervals were obtained from 10,000 bootstrapping resampling techniques. Results. Over 6 months the mean health care resource cost to manage T2D was US $22.87 per patient: 61% included the direct medical cost (US $14.01), 15% included the direct nonmedical cost (US $3.43), and 24% was associated with productivity losses (US $5.44). The mean health care resource cost per patient living in an urban community (US $24.65) was about US $4.95 higher than patients living in the rural community (US $19.69). The health care costs per patient with comorbid conditions was US $22.93 and was US $22.81 for those without comorbidities. Patients living in rural areas had 16% lower health care expenses compared with their urban counterparts. Conclusion. T2D imposes a substantial financial burden on both the health care system and individuals. There is a need to establish high-value care treatment strategies for the management of T2D to reduce the high health care expenses.

Highlights

More than 60% of health care expenses comprise the direct medical cost, 15% direct nonmedical cost, and 24% patient productivity losses. The costs of diagnosis, hospitalization, and recommended foods were the main drivers of health care costs for managing type 2 diabetes.Health care expenses among patients living in urban communities and patients with comorbid conditions was higher compared with those in rural communities and those with without comorbidities.The results of this study are expected to help integrate diabetes care within the existing primary health care systems, thereby reducing health care expenses and improving the quality of diabetes care in Nepal.

SUBMITTER: Dahal PK

PROVIDER: S-EPMC10725113 | biostudies-literature | 2023 Jul-Dec

REPOSITORIES: biostudies-literature

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Estimating the Health Care Expenditure to Manage and Care for Type 2 Diabetes in Nepal: A Patient Perspective.

Dahal Padam Kanta PK Rawal Lal L Ademi Zanfina Z Mahumud Rashidul Alam RA Paudel Grish G Vandelanotte Corneel C

MDM policy & practice 20230701 2

Background. This study aimed to estimate the health care expenditure for managing type 2 diabetes (T2D) in the community setting of Nepal. Methods. This is a baseline cross-sectional study of a heath behavior intervention that was conducted between September 2021 and February 2022 among patients with T2D (N = 481) in the Kavrepalanchok and Nuwakot districts of Nepal. Bottom-up and micro-costing approaches were used to estimate the health care costs and were stratified accord ...[more]

PMID: 38107033

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Project description:BackgroundLong-term cost-effectiveness analyses of health behaviour interventions to effectively manage type 2 diabetes mellitus (T2DM) in low-income countries are crucial for minimising economic burden and optimising resource allocation. Therefore, this study aimed to estimate the long-term cost-effectiveness of implementing a health behaviour intervention to manage T2DM in Nepal.MethodsA Markov model in combination with a decision tree was developed to compare the costs and outcomes of the health behaviour intervention against usual care among 481 (238-intervention and 243-control) participants from healthcare system and societal perspectives. The model integrates empirical trial data, with published data to inform parameters not collected during the trial. The model estimated costs, quality-adjusted life years (QALYs) and cost-effectiveness over 5 years, 10 years, 20 years, 30 years and a lifetime time horizons with 3% annual discounting. Sub-group, scenarios, both one-way and two-way analyses and probabilistic sensitivity analyses (PSA) were performed to assess the impact of uncertainty in the model under the threshold of 3 times gross domestic product (GDP) per capita (i.e., US $4140) for Nepal.ResultsBase-case analysis with lifetime horizon showed that the health behaviour intervention compared to usual care improved QALYs by 3.88 and increased costs by US $4293 per patient, with an incremental cost-effectiveness ratio (ICER) of US $1106 per QALY gained from a healthcare system perspective. From a societal perspective, QALYs also improved by 3.88 and costs increased by US $4550, with an ICER of US $1173 per QALY gained. Furthermore, the intervention demonstrated ICERs of US $636, US $678, US $637, and US $632 per QALY gained over 5-, 10-, 20-, and 30-year time horizons, respectively, from a healthcare system perspective, and US $719, US $766, US $659, and US $716 per QALY gained from a societal perspective. In the PSA, the probability of the health behaviour intervention being cost-effective was over 57%.ConclusionsThe health behaviour intervention for managing T2DM was cost-effective over a lifetime horizon compared to usual care. To maximise its impact, this intervention should be scaled up nationwide, and future research is warranted to assess the long-term cost-effectiveness across diverse settings in low-income countries.Trial registrationAustralia and New Zealand Clinical Trial Registry (ACTRN12621000531819).

Project description:BackgroundPrevention of type 2 diabetes is becoming an urgent public health concern in low and middle-income countries (LMICs). However, there is currently no evidence of a cost-effective approach of health behaviour interventions from community settings in low-income countries like Nepal. Therefore, this study aimed to assess the within-trial economic evaluation of a health behaviour intervention compared with usual care for managing type 2 diabetes in a community setting in Nepal.MethodsWe randomly assigned 30 clusters comprising 481 patients with type 2 diabetes of which 15 to a health behaviour intervention (n = 238 patients) and 15 to the usual care (n = 243 patients). Patients in the intervention group received community health workers-led intensive training for diabetes self-management along with regular phone calls and ongoing support from peer supporters. Costs, quality-adjusted life years (QALYs) and incremental cost-effectiveness ratio (ICER) as costs per QALYs gained were assessed after 6-month from a healthcare system perspective. Probabilistic sensitivity analysis was conducted using 10,000 Monte Carlo simulations to assess the impact of uncertainty of cost-effectiveness analysis under the threshold of three times gross domestic product (GDP) per capita for Nepal (i.e., US $4,140).ResultsOver the 6-month, the intervention yielded an incremental cost of US $28.55 (95% CI = US $21.26 to US $35.84) per person and an incremental QALYs of 0.0085 (95% CI = -0.0106 to 0.0275) per person. The ICER associated with the health behaviour intervention was US $3,358.82 (95% CI = US $-2005.66 to US $3,974.54) per QALY gained, which was below the estimated threshold, indicating a cost-effective approach with a net monetary benefit of US $6.64 (95% CI = US $-22.62 to US $78.01). Furthermore, the probabilistic sensitivity analysis consisting of 10,000 Monte Carlo simulations indicates that the intervention being cost-effective at the given threshold was 89.63%.ConclusionsHealth behaviour interventions in community settings are a cost-effective approach to manage type 2 diabetes, offering good value for money. However, more studies focused on long-term follow-up across diverse setting of LMICs should be warranted to assess the maximum impact of such interventions.Trial registrationAustralia and New Zealand Clinical Trial Registry (ACTRN12621000531819) Registered on 6th May 2021.

Project description:BackgroundThere is a growing emphasis on the need to engage patients in order to improve the quality of health care and improve health outcomes. However, we are still lacking a comprehensive understanding on how different measures of patient experiences interact with one another or relate to health status. This study takes a network perspective to 1) study the associations between patient characteristics and patient experience in health care and 2) identify factors that could be prioritized to improve health status.MethodsThis study uses data from the two-year panels from the Medical Expenditure Panel Survey (MEPS) initiated between 2004 and 2011 in the United States. The 88 variables regarding patient health and experience with health care were identified through the MEPS documentation. Sex, age, race/ethnicity, and years of education were also included for analysis. The bnlearn package within R (v3.20) was used to 1) identify the structure of the network of variables, 2) assess the model fit of candidate algorithms, 3) cross-validate the network, and 4) fit conditional probabilities with the given structure.ResultsThere were 51,023 MEPS interviewees aged 18 to 85 years (mean = 44, 95% CI = 43.9 to 44.2), with years of education ranging from 1 to 19 (mean = 7.4, 95% CI = 7.40 to 7.46). Among all, 55% and 74% were female and white, respectively. There were nine networks identified and 17 variables not linked to others, including death in the second years, sex, entry years to the MEPS, and relations of proxies. The health status in the second years was directly linked to that in the first years. The health care ratings were associated with how often professionals listened to them and whether professionals' explanation was understandable.ConclusionsIt is feasible to construct Bayesian networks with information on patient characteristics and experiences in health care. Network models help to identify significant predictors of health care quality ratings. With temporal relationships established, the structure of the variables can be meaningful for health policy researchers, who search for one or a few key priorities to initiate interventions or health care quality improvement programs.

Dataset Information

Estimating the Health Care Expenditure to Manage and Care for Type 2 Diabetes in Nepal: A Patient Perspective.

Highlights

Publications

Estimating the Health Care Expenditure to Manage and Care for Type 2 Diabetes in Nepal: A Patient Perspective.

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