Health care costs and comorbidities for patients with inclusion body myositis. (2nd September 2018)

• Record Type: Journal Article
• Authors: Keshishian, Allison; Greenberg, Steven A.; Agashivala, Neetu; Baser, Onur; Johnson, Kristen
• Is Part Of: Current medical research and opinion. Volume 34:Number 9(2018)
• Page Start: 1679
• Page End: 1685
• Publication Date: 2018-09-02
• Subjects: Inclusion body myositis -- myopathies -- health care costs -- prevalence -- Medicare; Clinical medicine -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1080/03007995.2018.1486294
• Languages: English
• ISSNs: 0300-7995

Abstract

Abstract: Objective: This study identifies the health care costs and utilization, as well as comorbidities, in a Medicare population of inclusion body myositis (IBM) patients. Methods: Medicare patients aged ≥65 years with a diagnosis claim for IBM were identified and matched to a cohort of non-IBM patients based on age, sex, race, calendar year and census region. Generalized linear models were used to estimate health care costs and utilization during the follow-up period. Results: The prevalence of IBM in this population, aged ≥65 years, was 83.7 cases per 1 million patients. Mean 1 year costs for the IBM cohort ( N = 361) were $44, 838 compared to $10, 182 for the matched non-IBM cohort ( N = 1805), an excess of $34, 656. IBM was significantly associated with multiple unsuspected comorbidities, including hypertension (66% vs. 22%), hyperlipidemia (47% vs. 18%) and myocardial infarction (13% vs. 2%) (all p < .0001). Conclusions: IBM patients utilize more health care resources and incur higher health care costs than patients without IBM. Furthermore, IBM patients were more likely to have multiple comorbidities, including cardiovascular risk factors and events, muscle and joint pain, and pulmonary complications compared to those without IBM. Limitations: The presence of a diagnosis code for a condition on a medical claim does not necessarily indicate the presence of the disease condition because the diagnosis code could be incorrectly entered in the database. Clinical and disease-specific parameters were not available in the claims data. Additionally, due to the observational study design, the analysis may be affected by unobserved differences between patients.