Optimal Pharmacological Treatment of Symptomatic Peripheral Arterial Occlusive Disease and Evidence of Female Patient Disadvantage: An Analysis of Health Insurance Claims Data

Summary: Background: Although epidemiological data suggest an association between periodontitis (PD) and peripheral arterial disease (PAD), it is currently unclear whether treatment of PD influences the severity of PAD. Patients and methods: Whether periodontal treatment is associated with PAD disease severity was examined by analysing health insurance claims data of patients insured by the German health insurance fund, BARMER, between January 1, 2012 and December 31, 2016. The presence of PAD was determined in individuals using International Classification of Diseases (ICD) 10th revision codes for intermittent claudication (IC) or chronic limb threatening ischaemia (CLTI). Treatment of PD was assessed by adequate ambulatory coding for non-surgical and surgical treatment of PD. Multivariate logistic regression analysis was performed to evaluate the association between PAD stages and periodontal treatment, adjusted for diabetes, age and sex. Results: The study cohort included 70,944 hospitalized patients with a diagnosis of symptomatic PAD (54.99 % women, 49.05 % IC). Among these patients, 3,567 (5.03 %) had received prior treatment for PD by supra- or sub-gingival debridement. PAD patients who had received periodontal treatment showed a lower proportion of CLTI (28.76 % among treated vs. 52.12 % among non-treated). Using multivariable regression methods, exhibiting a CLTI (vs. IC) was associated with not being treated for PD (Odds Ratio 1.97, 95 %–CI 1.83–2.13) after adjustment for age, gender, and diabetes. Conclusions: In this large-scale retrospective analysis of health insurance claims data comprising hospitalized symptomatic PAD patients, treatment of PD was associated with PAD disease severity independent of age, gender and diabetes. A potential benefit of periodontal treatment in relation to PAD will have to be determined in further prospective studies.

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The effect of Asian dust on asthma by socioeconomic status using national health insurance claims data in Korea

Inhalation Toxicology ◽

10.3109/08958378.2015.1123331 ◽

2016 ◽

Vol 28 (1) ◽

pp. 1-6 ◽

Cited By ~ 8

Author(s):

Yoon-Sung Park ◽

Jeong-Hee Kim ◽

Hae-Ji Jang ◽

Yoon-Hee Tae ◽

Dae Hyun Lim

Keyword(s):

Socioeconomic Status ◽

Health Insurance ◽

National Health Insurance ◽

National Health ◽

Claims Data ◽

Asian Dust ◽

Insurance Claims ◽

Insurance Claims Data ◽

Health Insurance Claims Data ◽

Health Insurance Claims

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

BMC Health Services Research ◽

10.1186/s12913-021-07262-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Michael Stucki ◽

Janina Nemitz ◽

Maria Trottmann ◽

Simon Wieser

Keyword(s):

Health Care ◽

Health Insurance ◽

Claims Data ◽

Health Care Spending ◽

Insurance Claims ◽

Diagnostic Coding ◽

Insurance Claims Data ◽

Health Insurance Claims Data ◽

Health Insurance Claims ◽

Disease Specific

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.

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