Decomposition of outpatient health care spending by disease - a novel approach using insurance claims data

Abstract

Background Decomposing health care spending by disease, type of care, age, and sex can lead to a better understanding of the drivers of health care spending. But the lack of diagnostic coding in outpatient care often precludes a decomposition by disease. Yet, health insurance claims data hold a variety of diagnostic clues that may be used to identify diseases. Methods In this study, we decompose total outpatient care spending in Switzerland by age, sex, service type, and 42 exhaustive and mutually exclusive diseases according to the Global Burden of Disease classification. Using data of a large health insurance provider, we identify diseases based on diagnostic clues. These clues include type of medication, inpatient treatment, physician specialization, and disease specific outpatient treatments and examinations. We determine disease-specific spending by direct (clues-based) and indirect (regression-based) spending assignment. Results Our results suggest a high precision of disease identification for many diseases. Overall, 81% of outpatient spending can be assigned to diseases, mostly based on indirect assignment using regression. Outpatient spending is highest for musculoskeletal disorders (19.2%), followed by mental and substance use disorders (12.0%), sense organ diseases (8.7%) and cardiovascular diseases (8.6%). Neoplasms account for 7.3% of outpatient spending. Conclusions Our study shows the potential of health insurance claims data in identifying diseases when no diagnostic coding is available. These disease-specific spending estimates may inform Swiss health policies in cost containment and priority setting.

Burden of seasonal influenza in the Swiss adult population during the 2016/2017–2018/2019 influenza seasons

“…Total medical expenditures varied considerably across seasons and accounted for 0.04% to 0.09% of total Swiss healthcare expenditures 43 or 0.47% to 1.07% of medical expenditures for communicable diseases 44 . The largest proportion of medical expenditures was observed among residents aged 65+ who exhibited much higher hospitalization rates than younger patients.…”

What drives health care spending in Switzerland? Findings from a decomposition by disease, health service, sex, and age

“…The results of this decomposition were then used to assess the contribution of four spending drivers on the overall and disease-specific spending increase from 2012 to 2017. Parts of this approach have been previously described [ 13 , 14 ].

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“…Spending was assigned to diseases using direct assignment and regression-based methods. The methodology is described in Stucki et al [ 14 ].…”

“…We contribute to the existing literature in multiple ways. First , we improve on previous studies decomposing Swiss health care spending by diseases [ 14 , 15 ] by substantially increasing the granularity of the decomposition. Second , we apply a comprehensive approach by using an exhaustive and mutually exclusive list of medical conditions, including diseases, injuries, and well care.…”

Preferences for innovations in healthcare delivery models in the Swiss elderly population: a latent class, choice modelling study

“…In Switzerland, chronic conditions account for more than 80% of total outpatient healthcare expenditures. 1 Moreover, with continuously increasing healthcare expenditures (>12% of GDP spent on healthcare), the country is facing increasing burden on households due to high out-of-pocket payments and community-rated premiums, 2–4 while healthcare resources are not always allocated efficiently. 1 , 2 Therefore, a recurring topic of political discussions is the enhancement of equity in financing and the development of alternative models of healthcare delivery (e.g.…”