Leveraging multi-tier healthcare facility network simulations for capacity planning in a pandemic.

The COVID-19 pandemic has placed severe demands on healthcare facilities across the world, and in several countries, makeshift COVID-19 centres have been operationalised to handle patient overflow. In developing countries such as India, the public healthcare system (PHS) is organised as a hierarchical network with patient flows from lower-tier primary health centres (PHC) to mid-tier community health centres (CHC) and downstream to district hospitals (DH). In this study, we demonstrate how a network-based modelling and simulation approach utilising generic modelling principles can (a) quantify the extent to which the existing facilities in the PHS can effectively cope with the forecasted COVID-19 caseload; and (b) inform decisions on capacity at makeshift COVID-19 Care Centres (CCC) to handle patient overflows.

Healthcare seeking behavior among patients visiting public primary and secondary healthcare facilities in an urban Indian district: A cross-sectional quantitative analysis.

In this work, we examined healthcare seeking behavior (HSB) of patients visiting public healthcare facilities in an urban context. We conducted a cross-sectional survey across twenty-two primary and secondary public healthcare facilities in the South-west Delhi district in India. The quantitative survey was designed to ascertain from patients at these facilities their HSB-i.

Prevalence of highly actionable mutations among Indian patients with advanced non-small cell lung cancer: A systematic review and meta-analysis.

Background: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality in India. To clarify rates of actionable mutations, and thereby identify opportunities to improve the delivery of best available care for a large volume of patients, a comprehensive review of available data is warranted.

Methods: Studies that reported prevalence of any actionable gene variant among adult Indian patients with advanced NSCLC were selected from three databases (PubMed, EMBASE, and Cochrane Library).

A discrete-event simulation model of the kidney transplantation system in Rajasthan, India.

We present a discrete-event simulation model of the kidney transplantation system in an Indian state, Rajasthan. Organs are generated across the state based on the organ donation rate among the general population, and are allocated to patients on the kidney transplantation waitlist. The organ allocation algorithm is developed using official guidelines published for kidney transplantation, and model parameters were estimated using publicly available data to the extent possible.

A model-based investigation into urban-rural disparities in tuberculosis treatment outcomes under the Revised National Tuberculosis Control Programme in India.

In this study, we investigate differences in tuberculosis (TB) treatment outcomes between urban and rural India and estimate their impact on epidemiological outcomes such as TB incidence, prevalence and mortality using a mathematical model of TB transmission dynamics. Publicly available district-level treatment outcomes data for new and previously treated TB cases was analyzed in conjunction with census data providing the proportion of urban population in each district to determine the effect of urbanity/rurality on treatment outcomes. Districts were grouped in clusters based on the proportion of urban population in each district, wherein the clusters were identified by applying machine learning methods.

An economic analysis of tolvaptan compared with fluid restriction among hospitalized patients with hyponatremia.

Objective: The vasopressin-receptor antagonist tolvaptan is used for the treatment of hyponatremia (HN) in hospitalized patients with congestive heart failure (CHF) or syndrome of inappropriate antidiuretic hormone secretion (SIADH). The objective of this economic modeling study was to assess the potential cost and health outcomes associated with tolvaptan in comparison with fluid restriction (FR).

Methods: A decision-analytic model was developed to estimate potential cost and health outcomes associated with tolvaptan compared with FR among hospitalized CHF and SIADH patients with severe HN (serum sodium [SS] levels < 125 mEq/L).

Cost-effectiveness analysis of universal noninvasive testing for post-treatment confirmation of Helicobacter pylori eradication and the impact of patient adherence.

Background: The treatment failure rate for Helicobacter pylori eradication therapy is ~20% due to poor patient compliance and increased antibiotic resistance. This analysis assessed the cost-effectiveness of universal post-treatment testing to confirm eradication of H. pylori infection in adults.

Impact of patient adherence on the cost-effectiveness of noninvasive tests for the initial diagnosis of Helicobacter pylori infection in the United States.

Objective: Previous US-based economic models of noninvasive tests for diagnosis of Helicobacter pylori infection did not consider patient adherence or downstream costs of continuing infection. This analysis evaluated the long-term cost-effectiveness of the urea breath test (UBT), fecal antigen test (FAT), and serology for diagnosis of H. pylori infection after incorporating information regarding test adherence.

Category-specific uncertainty modeling in clinical laboratory measurement processes.

Background: A statement of measurement uncertainty describes the quality of a clinical assay analysis result, and uncertainty models of clinical assays can be used to evaluate and optimize laboratory protocols designed to minimize the measurement uncertainty associated with an assay. In this study, we propose a methodology to lend systematic structure to the uncertainty modeling process.

Methods: Clinical laboratory assays are typically classified based on the chemical reaction involved, and therefore, based on the assay analysis methodology.

Application of mathematical models of system uncertainty to evaluate the utility of assay calibration protocols.

Background: Laboratory protocols used to calibrate commercial clinical chemistry systems affect test result quality. Mathematical models of system uncertainty can be developed using performance parameters provided by the manufacturer for various subsystems. These models can be used to evaluate protocols for specific laboratory operations.