The Health System and Population Health Implications of Large-Scale Diabetes Screening in India: A Microsimulation Model of Alternative Approaches

Derek Bell,Sanjay Basu,Sandeep Vijan,John S Yudkin,Christopher Millett,Rodney A Hayward,Rahoul Ahuja,Sanjay Kinra

doi:10.1371/journal.pmed.1001827

Abstract

BackgroundLike a growing number of rapidly developing countries, India has begun to develop a system for large-scale community-based screening for diabetes. We sought to identify the implications of using alternative screening instruments to detect people with undiagnosed type 2 diabetes among diverse populations across India.Methods and FindingsWe developed and validated a microsimulation model that incorporated data from 58 studies from across the country into a nationally representative sample of Indians aged 25–65 y old. We estimated the diagnostic and health system implications of three major survey-based screening instruments and random glucometer-based screening. Of the 567 million Indians eligible for screening, depending on which of four screening approaches is utilized, between 158 and 306 million would be expected to screen as “high risk” for type 2 diabetes, and be referred for confirmatory testing. Between 26 million and 37 million of these people would be expected to meet international diagnostic criteria for diabetes, but between 126 million and 273 million would be “false positives.” The ratio of false positives to true positives varied from 3.9 (when using random glucose screening) to 8.2 (when using a survey-based screening instrument) in our model. The cost per case found would be expected to be from US$5.28 (when using random glucose screening) to US$17.06 (when using a survey-based screening instrument), presenting a total cost of between US$169 and US$567 million. The major limitation of our analysis is its dependence on published cohort studies that are unlikely fully to capture the poorest and most rural areas of the country. Because these areas are thought to have the lowest diabetes prevalence, this may result in overestimation of the efficacy and health benefits of screening.ConclusionsLarge-scale community-based screening is anticipated to produce a large number of false-positive results, particularly if using currently available survey-based screening instruments. Resource allocators should consider the health system burden of screening and confirmatory testing when instituting large-scale community-based screening for diabetes.

Highlights

Type 2 diabetes has increased in prevalence at an alarming rate in rapidly developing countries such as India and China [1,2,3,4]
Ethics committee approval for the Indian Migration Study (IMS) that was used to inform the model was obtained from the All India Institute of Medical Sciences Ethics Committee, reference number A-60/4/8/2004; for the overall modeling research, ethics committee approval was obtained from the Stanford University Institutional Review Board, reference number eP28811
Among the 586 million people anticipated to be aged 25–65 y old in India in the year 2015, the mean diabetes prevalence rate was estimated as 12.0% in our model, such that an estimated 70 million people in this age group are thought to have diabetes

Summary

Introduction

Type 2 diabetes has increased in prevalence at an alarming rate in rapidly developing countries such as India and China [1,2,3,4]. Most people with diabetes in these countries are undiagnosed; community-based screening of adults for diabetes has been suggested [5,6,7,8]. In India, for example, a recently initiated program has already screened as many as 53 million adults in both urban and rural communities, using either survey-based instruments (i.e., risk-scoring questionnaires) or random (i.e., not necessarily fasting) blood glucose testing [9]. Like a growing number of rapidly developing countries, India has begun to develop a system for large-scale community-based screening for diabetes. Long-term complications of diabetes, which include an increased risk of heart disease and stroke, reduce the life expectancy of people with diabetes by about 10 years compared to people without diabetes

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Conclusion