Marc Carreras, Pere Ibern, José María Inoriza
Abstract
The progressive incorporation of quality of life indicators in health planning meets a critical need: The evaluation of the performance of health services, which are under stress by multiple causes, but in particular by an ageing population. In general, national health plans rely on health expectancies obtained using the Sullivan method.
Introduction
The progressive incorporation of quality of life indicators in health planning meets a critical need: The evaluation of the performance of health services, which are under stress by multiple causes, but in particular by an ageing population. There is a growing interest in measuring not only the number of years lived, but also the quality, adding concepts such as chronic disease burden or self-perceived health status.
Materials and Methods
Individual data of the population of the county of Baix Empordà (Catalonia) was collected ex-post for the consecutive years 2016 and 2017. The resident population, covered by the public insurance scheme, was composed of 91,130 individuals, of whom we had complete follow-up in the health system of N = 87,850.
Result
The output of the multistate micro simulation model is a random sample of individual lifetime trajectories. A numerical approach of the global Life Expectancy function can be obtained from the sample just applying the standard demographic formulas. Moreover, the individual health status changes, along the lifespan.
Discussion
A first aspect to discuss is the different concept of health embedded in the two approaches compared in the article. The significant difference in the results is simply a reflection of such different conception of health status.
Conclusion
According to the results, health indicators such as HLE can be efficiently obtained from multistate models based on mortality and morbidity information, without the use of health surveys. The major implication is that health indicators could be more easily obtained and extensively used for monitoring sub-national populations according to their health status.
Citation: Carreras M, Ibern P, Inoriza JM (2024) Measuring population health using health expectancy estimates from morbidity and mortality databases. PLoS ONE 19(5): e0302174. https://doi.org/10.1371/journal.pone.0302174
Editor: Kofi Awuviry-Newton, Victoria University, AUSTRALIA
Received: June 16, 2023; Accepted: March 27, 2024; Published: May 21, 2024
Copyright: © 2024 Carreras et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: This study was partially funded in the context of the project: PI15/02188, Obtaining life expectancy and decomposition by health states from clinical information, funded by the Carlos III Institute of Health, in the 2015 call for grants of the Health Research Projects Subprogram, co-funded by the European Regional Development Fund (FEDER) of the European Union. All the authors benefited equally from funding. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Source: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302174#sec001
