Diseases, Conditions, Syndromes

Research look at the definition of “multimorbidity” and how much it costs us.

Depending on how it is defined precisely, multimorbidity, or the co-existence of two or more chronic conditions, has varying prevalence. Additionally, many disease combinations have higher total health care costs than the total cost of each disease alone. These are the findings of two recent studies that examine multimorbidity in general and its costs. The studies were released on April 4 in the open-access journal PLOS Medicine.

Due to improved chronic disease survival rates and population aging, multimorbidity is becoming more common and now presents significant challenges to healthcare systems around the world. The prevalence of multimorbidity and the rising costs of healthcare in many developed nations are related, but the nature of their connection is unclear.

In the initial study, Clare MacRae of the University of Edinburgh in Scotland and associates examined English primary care data on nearly 1 and 2 million individuals registered with 149 general medical practices. They demonstrated, using nine lists of medical conditions that have been published, that changing the specific conditions that are thought to contribute to multimorbidity results in significant differences when calculating multimorbidity prevalence.

“With global health expenditure on the rise, particularly in the United States, identifying high-prevalence, high-spending illnesses and super-additive disease combinations should aid policymakers in designing initiatives to increase treatment efficacy and minimize cost,”

Angela Chang of the University of Southern Denmark, Copenhagen,

When only the two most prevalent conditions were taken into account, the prevalence of multimorbidity was 4 point 6 percent; however, when the ten most prevalent conditions were taken into account, it increased to 29 point 5 percent, the twenty most prevalent conditions to 35 point 2, and all 80 conditions to 40 point 5 percent. To achieve a multimorbidity prevalence of >99.9% across the entire population, 52 of the 80 possible conditions must exist or would need to. According to age, this varies. To obtain accurate measurements of multimorbidity, more conditions must be taken into account in younger populations (71 conditions for children under the age of 10) compared to older populations (29 conditions for people over the age of 80).

The authors state that “there is a need for standardization when measuring multimorbidity prevalence so that results across studies are comparable and population subgroups are accurately represented.”

Data from private health insurance claims of more than 16 million distinct enrollees in the United States, aged 18 to 64, were used in the second study by Angela Chang of the University of Southern Denmark, Copenhagen, and colleagues. According to the team’s analysis of 63 chronic conditions, 56.2% of the population had at least two chronic conditions.

They examined all possible two- and three-disease combinations and found that 60.1% of them had superadditive spending, meaning that the combined spending was higher than the sum of the spending for the individual diseases. The illnesses with both the highest cost per case and the highest contribution to multimorbidity spending were ischemic heart disease, inflammatory bowel disease, chronic kidney disease, and liver cirrhosis.

Finding high prevalence, high spending conditions, and super-additive disease combinations could assist policymakers in designing interventions to improve treatment effectiveness and lower costs, the authors write, at a time when health spending is on the rise everywhere, but particularly in the United States.

The papers’ combined findings highlight the need for novel approaches to research the prevalence and expenses of multimorbidity. To better inform policymakers and better allocate resources for its management and prevention, more research is required to replicate and generalize estimates of multimorbidity prevalence and spending using standardized methods for these calculations.

More information: C. MacRae et al, The impact of varying the number and selection of conditions on estimated multimorbidity prevalence: A cross-sectional study using a large, primary care population dataset. PLOS Medicine (2023). DOI: 10.1371/journal.pmed.1004208

A Y Chang et al, Estimating health spending associated with chronic multimorbidity in 2018: An observational study among adults in the United States, PLOS Medicine (2023). DOI: 10.1371/journal.pmed.1004205

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