Measuring population health using health expectancy estimates from morbidity and mortality databases

Area of Science:

• Public Health
• Biostatistics
• Health Services Research

Background:

• Health planning increasingly requires quality of life indicators, especially with aging populations.
• National health plans often use the Sullivan method for health expectancies, relying on health surveys.
• An alternative estimation using morbidity and mortality data is needed.

Purpose of the Study:

• To investigate an equivalent estimation of health expectancies using available morbidity and mortality datasets.
• To compare results with the traditional Sullivan method.

Main Methods:

• Utilized mortality and morbidity data from 2016-2017 for Baix Empordà county (N=91,130).
• Classified anonymized individual clinical records (diagnoses, procedures, pharmacy consumption) into health states.
• Employed a multistate microsimulation model to derive life expectancies by health state based on observed transitions and mortality.

Main Results:

• Calculated healthy life expectancies at birth and 65 years for females and males (HLE0female=39.94, HLE0male=42.87, HLE65female=2.43, HLE65male=2.17).
• Results showed considerably lower healthy life expectancies than Sullivan method equivalents (e.g., 8.25 years less for HLE65female).
• Point estimates for global life expectancies were LE0female=85.82, LE0male=80.58, LE65female=22.31, LE65male=18.86, consistent with government reports.

Conclusions:

• Health indicators can be efficiently obtained from multistate models using mortality and morbidity data, without health surveys.
• This alternative method provides a valuable tool for population monitoring in health planning.
• Multistate microsimulation yields lower healthy life expectancies due to a data-based health concept versus self-perception in the Sullivan method.