Mining Federated Data (Mfd) - A Conceptual Framework For Exploration And Evaluation Of Hospital Performance Measures

Keywords

analytics; framework; health IT; hospitals; performance measures

Abstract

This paper proposes an original mining federated data framework (MFDF) which can be used as a conceptual framework to perform exploratory and evaluation analysis of micro and macro level performance measures of hospitals. The framework uses the data mining techniques (statistical tools/machine learning) on enterprise data warehouse (EDW) platform that federates data for hospitals from multiple sources on a continual basis. This scalable and cyclic framework is flexible to test theories and analyze the impact of independent/predictor variables on dependent/response variables by deploying various data/statistical models. The paper presents a brief exploratory analysis performed based on this framework to understand the relationships between patient perceptions of care and hospital performance scores indicate that there is a positive correlation between patient satisfaction and hospital total performance scores; albeit the relationship of patient satisfaction scores with other domain scores such as safety, timeliness, effectiveness etc. cannot be ascertained.

Publication Date

1-1-2017

Publication Title

Journal of Integrated Design and Process Science

Volume

21

Issue

3

Number of Pages

33-45

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.3233/jid-2017-0013

Socpus ID

85035100792 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85035100792

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