Abstract
BackgroundEasy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world. Current measurement is restricted by limitations in existing measurement systems in the developing world and the lack of biometry tests for non-communicable diseases. Diagnosis based on self-reported signs and symptoms (“Symptomatic Diagnosis,” or SD) analyzed with computer-based algorithms may be a promising method for collecting timely and reliable information on non-communicable disease prevalence. The objective of this study was to develop and assess the performance of a symptom-based questionnaire to estimate prevalence of non-communicable diseases in low-resource areas.MethodsAs part of the Population Health Metrics Research Consortium study, we collected 1,379 questionnaires in Mexico from individuals who suffered from a non-communicable disease that had been diagnosed with gold standard diagnostic criteria or individuals who did not suffer from any of the 10 target conditions. To make the diagnosis of non-communicable diseases, we selected the Tariff method, a technique developed for verbal autopsy cause of death calculation. We assessed the performance of this instrument and analytical techniques at the individual and population levels.ResultsThe questionnaire revealed that the information on health care experience retrieved achieved 66.1% (95% uncertainty interval [UI], 65.6–66.5%) chance corrected concordance with true diagnosis of non-communicable diseases using health care experience and 0.826 (95% UI, 0.818–0.834) accuracy in its ability to calculate fractions of different causes. SD is also capable of outperforming the current estimation techniques for conditions estimated by questionnaire-based methods.ConclusionsSD is a viable method for producing estimates of the prevalence of non-communicable diseases in areas with low health information infrastructure. This technology can provide higher-resolution prevalence data, more flexible data collection, and potentially individual diagnoses for certain conditions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-014-0245-8) contains supplementary material, which is available to authorized users.
Highlights
Easy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world
Questionnaires were analyzed using all of the different methods mentioned above, this section presents only the results derived from the Tariff method
We further simulated the application of Tariff in the field by testing the performance with the inclusion/exclusion of Health care experience (HCE) information, which allowed us to determine the viability of using Tariff in areas with no health care, and by testing performance in samples of test data with random cause compositions
Summary
Easy-to-collect epidemiological information is critical for the more accurate estimation of the prevalence and burden of different non-communicable diseases around the world. Despite the substantial burden of NCDs around the world, it continues to be difficult to collect accurate information on their prevalence, in areas that lack consistent or accessible health care. In part, this is due to inherent limitations in diagnosing these conditions. While information on some infectious diseases, such as HIV, malaria, and tuberculosis, can be collected through biological assays or cultures, such an equivalent does not exist for certain NCDs. The diagnostic criteria for a condition such as chronic obstructive pulmonary disease (COPD), for example, require medical resources such as spirometry or medical knowledge to interpret FEV1/ FVC ratios and differentiate COPD from asthma based on subtle differences in clinical signs and symptoms. Medical diagnostic tests for NCDs, when existent, are frequently more expensive than for infectious diseases, so surveys tend not to include them; for example, a rapid diagnostic test for malaria costs less than $1 USD in most countries [2], whereas the costs to obtain and measure liver function tests or conduct a 12-lead electrocardiogram are much higher
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