Can the US minimum data set be used for predicting admissions to acute care facilities?

Patricia Ann Abbott, Stephen Quirolgico, Roopak Manchand, Kip Canfield, Monica Adya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper is intended to give an overview of Knowledge Discovery in Large Datasets (KDD) and data mining applications in healthcare particularly as related to the Minimum Data Set, a resident assessment tool which is used in US long-term care facilities. The US Health Care Finance Administration, which mandates the use of this tool, has accumulated massive warehouses of MDS data. The pressure in healthcare to increase efficiency and effectiveness while improving patient outcomes requires that we find new ways to harness these vast resources. The intent of this preliminary study design paper is to discuss the development of an approach which utilizes the MDS, in conjunction with KDD and classification algorithms, in an attempt to predict admission from a long-term care facility to an acute care facility. The use of acute care services by long term care residents is a negative outcome, potentially avoidable, and expensive. The value of the MDS warehouse can be realized by the use of the stored data in ways that can improve patient outcomes and avoid the use of expensive acute care services. This study, when completed, will test whether the MDS warehouse can be used to describe patient outcomes and possibly be of predictive value.

Original languageEnglish (US)
Title of host publicationStudies in Health Technology and Informatics
Pages1318-1321
Number of pages4
Volume52
DOIs
StatePublished - 1998
Externally publishedYes
Event9th World Congress on Medical Informatics, MedInfo 1998 - Seoul, Korea, Republic of
Duration: Aug 18 1998Aug 22 1998

Other

Other9th World Congress on Medical Informatics, MedInfo 1998
CountryKorea, Republic of
CitySeoul
Period8/18/988/22/98

Fingerprint

Warehouses
Long-Term Care
Data mining
Delivery of Health Care
Data Mining
Finance
Health care
Pressure
Datasets

Keywords

  • Classification
  • Knowledge Discovery in Large Databases
  • Minimum Data Set
  • Nursing Informatics

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Abbott, P. A., Quirolgico, S., Manchand, R., Canfield, K., & Adya, M. (1998). Can the US minimum data set be used for predicting admissions to acute care facilities? In Studies in Health Technology and Informatics (Vol. 52, pp. 1318-1321) https://doi.org/10.3233/978-1-60750-896-0-1318

Can the US minimum data set be used for predicting admissions to acute care facilities? / Abbott, Patricia Ann; Quirolgico, Stephen; Manchand, Roopak; Canfield, Kip; Adya, Monica.

Studies in Health Technology and Informatics. Vol. 52 1998. p. 1318-1321.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abbott, PA, Quirolgico, S, Manchand, R, Canfield, K & Adya, M 1998, Can the US minimum data set be used for predicting admissions to acute care facilities? in Studies in Health Technology and Informatics. vol. 52, pp. 1318-1321, 9th World Congress on Medical Informatics, MedInfo 1998, Seoul, Korea, Republic of, 8/18/98. https://doi.org/10.3233/978-1-60750-896-0-1318
Abbott PA, Quirolgico S, Manchand R, Canfield K, Adya M. Can the US minimum data set be used for predicting admissions to acute care facilities? In Studies in Health Technology and Informatics. Vol. 52. 1998. p. 1318-1321 https://doi.org/10.3233/978-1-60750-896-0-1318
Abbott, Patricia Ann ; Quirolgico, Stephen ; Manchand, Roopak ; Canfield, Kip ; Adya, Monica. / Can the US minimum data set be used for predicting admissions to acute care facilities?. Studies in Health Technology and Informatics. Vol. 52 1998. pp. 1318-1321
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