Impact of individual, household, and area characteristics on health and social care outcomes for people with multimorbidity: Protocol for a multilevel analysis

Background:
Multimorbidity is associated with additional healthcare use and premature death and is one of the greatest challenges facing health and social care systems globally. Although the importance of individual characteristics (such as age, sex, and lifestyle factors) on health care outcomes is well understood, little is known about broader contextual determinants such as household and area characteristics. This study protocol presents a plan for the examination of associations of characteristics of people stratified by multimorbidity status, at individual, household, and area levels with important health and social care outcomes.

Methods:
This study will use a cross-section of data from the SAIL Databank on date 01/01/2019 to define the cohort which will include all people alive and registered with a Welsh GP. The cohort will be stratified according to the presence of multimorbidity (≥2 long-term conditions). Three-level multilevel models will examine associations between covariates at individual, household, and area levels with important health and social care outcomes over a 12-month period. The intra-class correlation coefficient will be calculated to determine the strength of association at each level of the hierarchy. Frequentist logit multilevel model models will be used. The outcomes will be any emergency department attendance, unplanned hospital or care home admission, or death, within the study follow-up period.

Discussion:
This study protocol presents a comprehensive explanation of the steps that will be taken to perform classical Frequentist analyses. Results of the analyses will contribute to a better understanding of the importance of individual and contextual factors for people with multimorbidity and can be used to guide clinical and policy responses for efficient use of limited resources.