Data Privacy Compliant Validation of Health Insurance Claims Data: the IDOMENEO Approach

Christian-Alexander Behrendt, Thea Schwaneberg, Sandra Hischke, Tobias Müller, Tom Petersen, Ursula Marschall, Sebastian Debus, Levente Kriston, Christian-Alexander Behrendt, Thea Schwaneberg, Sandra Hischke, Tobias Müller, Tom Petersen, Ursula Marschall, Sebastian Debus, Levente Kriston

Abstract

Recently, health insurance claims have regained the attention of the scientific community as a source of real-world evidence in health care research and quality improvement. To date, very few studies are available which investigate the validity of health insurance claims; these may be affected by bias from several sources, such as possible upcoding of co-morbidities and complications for reimbursement advantages. The IDOMENEO study investigates the inpatient treatment of peripheral arterial disease (PAD) comprehensively using various data sources with a consortium involving experts from health care research and data privacy, a large health insurance fund, biostatisticians, jurists, and computer scientists. Prospective registry data were collected from 30-40 vascular centres in Germany using the GermanVasc registry. In addition, health insurance claims data were prospectively collected from BARMER, the second largest health insurance fund in Germany. The consortium is currently developing a data privacy compliant method of health insurance claims data validation, the methodological foundations of which are described here.

Conflict of interest statement

The authors declare no conflicts of interest.

Eigentümer und Copyright ©Georg Thieme Verlag KG 2019.

Figures

Fig. 1
Fig. 1
Illustration of the IDOMENEO approaches to validate health insurance claims data (BARMER) with prospectively collected and quality assured registry data (GermanVasc).

References

    1. Quinn K.After the revolution: DRGs at age 30 Ann Intern Med 2014160426–429.doi:10.7326/M13-2115
    1. Choudhry N K.Randomized, Controlled Trials in Health Insurance Systems N Engl J Med 2017377957–964.doi:10.1056/NEJMra1510058
    1. Behrendt C A, Debus E S, Mani K et al.The Strengths and Limitations of Claims Based Research in Countries With Fee for Service Reimbursement. Eur J Vasc Endovasc Surg. 2018 doi: 10.1016/j.ejvs.2018.06.001.
    1. Behrendt C A, Heidemann F, Riess H Cet al.Registry and health insurance claims data in vascular research and quality improvement Vasa 20174611–15.doi:10.1024/0301-1526/a000589
    1. Behrendt C A, Joassart Ir A, Debus E Set al.The Challenge of Data Privacy Compliant Registry Based Research Eur J Vasc Endovasc Surg 201855601–602.doi:10.1016/j.ejvs.2018.02.018
    1. Behrendt C A, Riess H, Harter Met al.Guideline recommendations and quality indicators for invasive treatment of peripheral arterial disease in Germany: The IDOMENEO study for quality improvement and research in vascular medicine Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 201861218–223.doi:10.1007/s00103-017-2676-9
    1. Behrendt C A, Härter M, Kriston Let al.IDOMENEO – Ist die Versorgungsrealität in der Gefäßmedizin Leitlinien- und Versorgungsgerecht? Gefässchirurgie 20172241–47.doi:10.1007/s00772-016-0234-7
    1. DeStatis SB KrankenhausdiagnosestatistikInURL:Statistisches Bundesamt DeStatis: Gesundheitsberichterstattung des Bundes 2014
    1. Riess H C, Debus E S, Schwaneberg T et al.Indicators of outcome quality in peripheral arterial disease revascularisations – a Delphi expert consensus. Vasa. 2018 doi: 10.1024/0301-1526/a000720:1-7..
    1. Debus E S, Kriston L, Schwaneberg Tet al.Rationale and methods of the IDOMENEO health outcomes of the peripheral arterial disease revascularisation study in the GermanVasc registry Vasa 201810.1024/0301-1526/a000730:1-7doi:10.1024/0301-1526/a000730
    1. Behrendt C A, Tsilimparis N, Diener Het al.Einführung des GermanVasc Gefässchirurgie 201419403–411.doi:10.1007/s00772-014-1351-9
    1. Messick S.Standards of Validity and the Validity of Standards in Performance Assessment Educational Measurement: Issues and Practice 2005145–8.doi:10.1111/j.1745-3992.1995.tb00881.x
    1. Farin E.Die Anwendung Hierarchischer Linearer Modelle für Einrichtungsvergleiche in der Qualitätssicherung und Rehabilitationsforschung Die Rehabilitation 200544157–164.doi:10.1055/s-2004-834785
    1. Wirtz M. Die Mehrebenenanalyse als Verfahren zur Analyse rehabilitationswissenschaftlicher Forschungsfragen. Die Rehabilitation. 2018 doi: 10.1055/s-0043-124334.
    1. Steenkamp J, Benedict E M, Baumgartner H.Assessing Measurement Invariance in Cross-National Consumer Research Journal of Consumer Research 19982578–107.doi:10.1086/209528
    1. Sweeney L.k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 200210557–570.doi:10.1142/s0218488502001648
    1. Meyerson A, Williams R. On the complexity of optimal K-anonymity. Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems – PODS '04 2004
    1. Aggarwal C C, Yu P S.A General Survey of Privacy-Preserving Data Mining Models and Algorithms Privacy-Preserving Data Mining 200811–52.doi:10.1007/978-0-387-70992-5_2
    1. Machanavajjhala A, Kifer D, Gehrke Jet al.L-diversity ACM Transactions on Knowledge Discovery from Data 200713–es.doi:10.1145/1217299.1217302
    1. Li N, Li T, Venkatasubramanian S. t-Closeness: Privacy Beyond k-Anonymity and l-Diversity. 2007 IEEE 23rd International Conference on Data Engineering. 2007:106–115.
    1. Behrendt C A, Bertges D, Eldrup Net al.International Consortium of Vascular Registries Consensus Recommendations for Peripheral Revascularisation Registry Data Collection Eur J Vasc Endovasc Surg 201856217–237.doi:10.1016/j.ejvs.2018.04.006
    1. Elixhauser A, Steiner C, Harris D R et al.Comorbidity measures for use with administrative data. Medical care. 1998;36:8–27.
    1. Quan H, Sundararajan V, Halfon P et al.Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Medical care. 2005;43:1130–1139.
    1. Behrendt C A, Pridohl H, Schaar Ket al.Clinical registers in the twenty-first century : Balancing act between data protection and feasibility? Chirurg 201788944–949.doi:10.1007/s00104-017-0542-9
    1. Bjorck M, Mani K.Publication of Vascular Surgical Registry Data: Strengths and Limitations Eur J Vasc Endovasc Surg 201754788doi:10.1016/j.ejvs.2017.09.013
    1. Bergqvist D, Bjorck M, Sawe Jet al.Randomized trials or population-based registries Eur J Vasc Endovasc Surg 200734253–256.doi:10.1016/j.ejvs.2007.06.014
    1. Venermo M, Mani K, Kolh P.The quality of a registry based study depends on the quality of the data – without validation, it is questionable Eur J Vasc Endovasc Surg 201753611–612.doi:10.1016/j.ejvs.2017.03.017

Source: PubMed

3
Abonner