Pitfalls of Single Measurement Screening for Diabetes and Hypertension in Community-Based Settings

BACKGROUND: Cross-sectional screening programs are used to detect and refer individuals with non-communicable diseases to healthcare services. We evaluated the positive predictive value of cross-sectional measurements for Diabetes Mellitus (DM) and hypertension (HTN) as part of a community-based disease screening study, ‘Vukuzazi’ in rural South Africa. METHODS: We conducted community-based screening for HTN and DM using the World Health Organization STEPS protocol and glycated haemoglobin A1c (HbA1c) testing, respectively. Nurses conducted follow-up home visits for confirmatory diagnostic testing among individuals with a screening BP above 140/90 mmHg and/or HbA1c above 6.5% at the initial screen, and without a prior diagnosis. We assessed the positive predictive value of the initial screening, compared to the follow up measure. We also sought to identify a screening threshold for HTN and DM with greater than 90% positive predictive value. RESULTS: Of 18,027 participants enrolled, 10.2% (1,831) had a screening BP over 140/90 mmHg. Of those without a prior diagnosis, 871 (47.6%) received follow-up measurements. Only 51.2% (451) of those with completed follow-up measurements had a repeat BP>140/90 mmHg at the home visit and were referred to care. To achieve a 90% correct referral rate, a systolic BP threshold of 192 was needed at first screening. For DM screening, 1,615 (9.0%) individuals had an HbA1c > 6.5%, and of those without a prior diagnosis, 1,151 (71.2%) received a follow-up blood glucose. Of these, only 34.1% (395) met criteria for referral for DM. To ensure a 90% positive predictive value i.e. a screening HbA1c of >16.6% was needed. CONCLUSIONS: A second home-based screening visit to confirm a diagnosis of DM and HTN reduced health system referrals by 48% and 66%, respectively. Two-day screening programmes for DM and HTN screening might save individual and healthcare resources and should be evaluated carefully in future cost effectiveness evaluations.