학술논문

Predicting the impact of patient and private provider behavior on diagnostic delay for pulmonary tuberculosis patients in India: A simulation modeling study.
Document Type
Article
Source
PLoS Medicine. 5/14/2020, Vol. 17 Issue 5, p1-18. 18p. 1 Diagram, 10 Charts.
Subject
*TUBERCULOSIS
*TUBERCULOSIS patients
*DISCRETE event simulation
*MEMORY bias
*MEDICAL personnel
*DELAYED diagnosis
Language
ISSN
1549-1277
Abstract
Background: Tuberculosis (TB) incidence in India continues to be high due, in large part, to long delays experienced by patients before successful diagnosis and treatment initiation, especially in the private sector. This diagnostic delay is driven by patients' inclination to switch between different types of providers and providers' inclination to delay ordering of accurate diagnostic tests relevant to TB. Our objective is to quantify the impact of changes in these behavioral characteristics of providers and patients on diagnostic delay experienced by pulmonary TB patients. Methods and findings: We developed a discrete event simulation model of patients' diagnostic pathways that captures key behavioral characteristics of providers (time to order a test) and patients (time to switch to another provider). We used an expectation-maximization algorithm to estimate the parameters underlying these behavioral characteristics, with quantitative data encoded from detailed interviews of 76 and 64 pulmonary TB patients in the 2 Indian cities of Mumbai and Patna, respectively, which were conducted between April and August 2014. We employed the estimated model to simulate different counterfactual scenarios of diagnostic pathways under altered behavioral characteristics of providers and patients to predict their potential impact on the diagnostic delay. Private healthcare providers including chemists were the first point of contact for the majority of TB patients in Mumbai (70%) and Patna (94%). In Mumbai, 45% of TB patients first approached less-than-fully-qualified providers (LTFQs), who take 28.71 days on average for diagnosis. About 61% of these patients switched to other providers without a diagnosis. Our model estimates that immediate testing for TB by LTFQs at the first visit (at the current level of diagnostic accuracy) could reduce the average diagnostic delay from 35.53 days (95% CI: 34.60, 36.46) to 18.72 days (95% CI: 18.01, 19.43). In Patna, 61% of TB patients first approached fully qualified providers (FQs), who take 9.74 days on average for diagnosis. Similarly, immediate testing by FQs at the first visit (at the current level of diagnostic accuracy) could reduce the average diagnostic delay from 23.39 days (95% CI: 22.77, 24.02) to 11.16 days (95% CI: 10.52, 11.81). Improving the diagnostic accuracy of providers per se, without reducing the time to testing, was not predicted to lead to any reduction in diagnostic delay. Our study was limited because of its restricted geographic scope, small sample size, and possible recall bias, which are typically associated with studies of patient pathways using patient interviews. Conclusions: In this study, we found that encouraging private providers to order definitive TB diagnostic tests earlier during patient consultation may have substantial impact on reducing diagnostic delay in these urban Indian settings. These results should be combined with disease transmission models to predict the impact of changes in provider behavior on TB incidence. Sarang Deo and co-workers study providers' approaches to tuberculosis diagnosis in India. Author summary: Why was this study done?: India contributes more than a quarter of the 10 million global tuberculosis (TB) cases every year. Several studies capture long, circuitous care pathways followed by TB patients until their diagnosis. However, these studies do not quantify the link between diagnostic delay and underlying patient and provider behavior characteristics. What did the researchers do and find?: We developed a quantitative simulation model to estimate the impact of behavioral characteristics of patients and providers on diagnostic delay and estimated the parameters of this model using data from detailed interviews of 76 patients from Mumbai and 64 patients from Patna. We found that earlier test ordering by providers would yield a much larger reduction in diagnostic delay than increasing their diagnostic accuracy. What do these findings mean?: Policy-makers and implementing agencies should encourage early test ordering behavior by providers to reduce diagnostic delay, and, consequently, to reduce disease transmission. [ABSTRACT FROM AUTHOR]