Literature DB >> 26975757

USING CLAIMS DATA FOR EVIDENCE GENERATION IN MANAGED ENTRY AGREEMENTS.

Alina Brandes1, Larissa Schwarzkopf1, Wolf H Rogowski2.   

Abstract

OBJECTIVES: This study assesses the use of routinely collected claims data for managed entry agreements (MEA) in the illustrative context of German statutory health insurance (SHI) funds.
METHODS: Based on a nonsystematic literature review, the data needs of different MEA were identified. A value-based typology to classify MEA on the basis of these data needs was developed. The typology is oriented toward health outcomes and utilization and costs, key components of a new technology's value. For each MEA type, the suitability of claims data in establishing evidence of the novel technology's value in routine care was systematically assessed. Assessment criteria were data availability, completeness, timeliness, confidentiality, reliability, and validity.
RESULTS: Claims data are better suited to MEA addressing uncertainty regarding the utilization and costs of a novel technology in routine care. In schemes where safety aspects or clinical effectiveness are assessed, the role of claims data is limited because clinical information is not included in sufficient detail.
CONCLUSIONS: The suitability of claims data depends on the source of uncertainty and, in consequence, the outcome measures chosen in the agreements. In all schemes, the validity of claims data should be judged with caution as data are collected for billing purposes. This framework may support manufacturers and payers in selecting the most suitable contract type and agreeing on contract conditions. More research is necessary to validate these results and to address remaining medical, economic, legal, and ethical questions of using claims data for MEA.

Keywords:  Data collection/methods; Decision making; Insurance; Risk sharing; Technological innovation; financial/economics; health; reimbursement

Mesh:

Year:  2016        PMID: 26975757     DOI: 10.1017/S0266462316000131

Source DB:  PubMed          Journal:  Int J Technol Assess Health Care        ISSN: 0266-4623            Impact factor:   2.188


  3 in total

1.  Rules Based Data Quality Assessment on Claims Database.

Authors:  Mary A Gadde; Zhan Wang; Meredith Zozus; John B Talburt; Melody L Greer
Journal:  Stud Health Technol Inform       Date:  2020-06-26

2.  Usability of German hospital administrative claims data for healthcare research: General assessment and use case of multiple myeloma in Munich university hospital in 2015-2017.

Authors:  Amal AlZahmi; Irena Cenzer; Ulrich Mansmann; Helmut Ostermann; Sebastian Theurich; Tobias Schleinkofer; Karin Berger
Journal:  PLoS One       Date:  2022-07-28       Impact factor: 3.752

Review 3.  Health economic evaluations based on routine data in Germany: a systematic review.

Authors:  Fabia Mareike Gansen
Journal:  BMC Health Serv Res       Date:  2018-04-10       Impact factor: 2.655

  3 in total

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