Using All-Payer Claims Databases to Study Insurance and Health Care Utilization Dynamics

Dworsky, Michael

doi:10.1007/s11606-017-4128-5

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…To fulfill these aims, we used an all-payer claims database (APCD) that covered 99.9% of the Dutch population. This enabled analysis of the services used and expenditures of the total type 2 diabetes population across the entire health system and over time [ 27 , 28 ].…”

Section: Introductionmentioning

confidence: 99%

Delineating the Type 2 Diabetes Population in the Netherlands Using an All-Payer Claims Database: Specialist Care, Medication Utilization and Expenditures 2016–2018

Geurten

Struijs

Elissen

et al. 2021

PharmacoEconomics Open

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Objectives The aim of this study was to describe the healthcare utilization and expenditures related to medical specialist care and medication of the entire type 2 diabetes population in the Netherlands in detail. Methods For this retrospective, observational study, we used an all-payer claims database. Comprehensive data on specialist care and medication utilization and expenditures of the type 2 diabetes population (n = 900,522 in 2018) were obtained and analyzed descriptively. Data were analyzed across medical specialties and for various types of diabetes medication (or glucose-lowering drugs [GLDs]) and other medication. Results Specialist care utilization was diverse: different medical specialties were visited by a considerable fraction of the type 2 diabetes population. Total expenditures on specialist care were €2498 million in 2018 (i.e., 10.6% of the national specialist care expenditures). In total, 97.8% of patients used other medication (not GLDs) and 81.8% used GLDs; 25.6% of medication expenditures were for GLDs. For both specialist care and medication, mean expenditures per treated patient were higher than median expenditures, indicating a skewed distribution of spending. Conclusion Use of and expenditures on specialist care and medication of the type 2 diabetes population is diverse. These heterogeneous healthcare use patterns are likely caused by the presence of comorbidities. Additionally, we found that a small fraction of the population is responsible for a large share of the expenditures. A shift towards more patient-centered care could lead to health improvements and a reduction in overall costs, subsequently promoting the sustainability of healthcare systems.

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Section: Introductionmentioning

confidence: 99%

Delineating the Type 2 Diabetes Population in the Netherlands Using an All-Payer Claims Database: Specialist Care, Medication Utilization and Expenditures 2016–2018

Geurten

Struijs

Elissen

et al. 2021

PharmacoEconomics Open

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“…A key challenge the All-Payer Claims Database (APCD) addressed upon its inception was the linking of key information to allow for tracking patients as they change commercial insurers. 3 Because each commercial payer uses a different identification system, there is no standard patient identifier across insurers. The MA APCD overcame this barrier by creating a member enterprise ID that was used as a master patient identifier.…”

Section: Cohort Data Sourcementioning

confidence: 99%

Hematopoietic Stem-Cell Transplant Utilization in Relapsed/Refractory Hodgkin Lymphoma: A Population-Level Analysis of Statewide Claims Data

Waheed

Rodday

Kumar

et al. 2022

JCO Clinical Cancer Informatics

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PURPOSE Although hematologic malignancies affect adults of all ages, few data exist on the real-world patterns of care for patients younger than 65 years in the United States. Understanding patterns of care from diagnosis through relapsed disease may provide insight about care across community and academic centers. We used a large statewide claims database to describe the path of Hodgkin lymphoma (HL) treatment among adults age < 65 years at diagnosis. METHODS We defined a cohort of commercially insured patients with HL who underwent hematopoietic stem-cell transplantation (HSCT) from 2009 to 2013 in the Massachusetts All-Payer Claims Database (APCD). The primary goals of our study were to accurately identify patients and their treatment patterns who had relapsed/refractory HL and underwent HSCT. We also characterized time to treatment failure and overall survival. RESULTS A total of 7,613 patients had International Classification of Diseases, Ninth Revision, diagnostic codes for HL. From our algorithm, we identified 117 patients as part of the final cohort who underwent autologous and/or allogeneic HSCT. Median age was 39.0 years and 50.4% were female. Initial therapy was identified for 68 of the 117 patients (58.1%). Most (> 74.4%) of the identified transplants were autologous, and 19 patients (16.2%) underwent allogeneic transplant, with or without prior autologous transplant. Of the 68 patients with initial therapy data, the median time to HSCT after completion of initial treatment was 223.5 days (Q1 = 151.5, Q3 = 414.5). CONCLUSION We used the Massachusetts APCD to create a cohort of patients age < 65 years with relapsed/refractory HL. Our findings support the use of APCD for the large-scale analysis of patient characteristics, treatment patterns, and outcomes for young adult patients with hematologic malignancies.

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“…In the ACA Medicaid expansion and the federal and state health insurance exchanges, health plans compete for enrollees under age 65 who are ineligible for Medicaid and not covered by employer-sponsored insurance. 60 On one hand, market competition is a key approach for improving value through lower prices and higher quality. 61 On the other hand, market competition and the exchanges may increase plan switching and instability among private plans in exchanges, including among those private managed care plans competing to enroll Medicaid beneficiaries, and can contribute to individuals churning between Medicaid and private exchange plans due to different eligibility criteria, cost-sharing and premiums, and other factors.…”

Section: Conceptual Model Of Health Insurance Stabilitymentioning

confidence: 99%

A conceptual model of health insurance stability in the United States health care system

Grembowski

Leibbrand

2022

Health Serv Manage Res

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In the U.S. health care system, people under age 65 are at risk of losing and regaining health insurance coverage over their lifetimes, which has important consequences for their physical and mental health. Despite the importance of insurance stability, we have an incomplete understanding about the complex factors influencing whether people lose and regain coverage. To advance our understanding of the dynamics of health insurance coverage and guide future research, our purpose is to present a new conceptual model of health insurance stability, where instability is defined as a person’s loss or change of coverage, which can occur more than once in a lifetime. Drawing from theory and evidence in the literature, we posit that personal and plan characteristics, the health system, and the environmental context – economic, social/cultural, political/judicial, and geographic – drive health insurance stability over the life course and are understudied. Studies are needed to identify the populations most at risk of experiencing insurance instability and vulnerability in health outcomes that results from such insecurity, which may suggest reforms and health policies at the individual, health system, or environment levels to reduce those risks.

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Using All-Payer Claims Databases to Study Insurance and Health Care Utilization Dynamics

Cited by 5 publications

References 9 publications

Delineating the Type 2 Diabetes Population in the Netherlands Using an All-Payer Claims Database: Specialist Care, Medication Utilization and Expenditures 2016–2018

Delineating the Type 2 Diabetes Population in the Netherlands Using an All-Payer Claims Database: Specialist Care, Medication Utilization and Expenditures 2016–2018

Hematopoietic Stem-Cell Transplant Utilization in Relapsed/Refractory Hodgkin Lymphoma: A Population-Level Analysis of Statewide Claims Data

A conceptual model of health insurance stability in the United States health care system

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