B1050
Title: Estimating length of stay in a multi-state model conditional on the pathway, with application to patients with Covid-19
Authors: Ruth Keogh - London School of Hygiene and Tropical Medicine (United Kingdom) [presenting]
Abstract: Multi-state models are used to describe how individuals transition through different states over time. The distribution of the time spent in different states, referred to as `length of stay', is often of interest. Methods for estimating expected length of stay in a given state are well established. The focus will be on estimating the distribution of the time spent in different states conditional on the complete pathway taken through the states, which we call `conditional length of stay'. The motivation comes from questions about the length of stay in hospital wards and intensive care units among patients hospitalised due to Covid-19. Conditional length of stay estimates are useful as a way of summarising individuals' transitions through the multi-state model, and also as inputs to mathematical models used in planning hospital capacity requirements. We will outline describe non-parametric methods for estimating the conditional length of stay distributions in a multi-state model in the presence of censoring. The methods will be illustrated using data on 42980 individuals hospitalised due to Covid-19 in the UK from March to July 2020, from the COVID19 Clinical Information Network.
