PROCEEDING MEDICAL RECORD

Data and Text Mining the Electronic Medical Record to Improve Care and to Lower Costs

Kumpulan	: Jurnal Ilmiah (Non-Kategori) [Inggris]
Edisi/Volume	: ,
Pengarang	: Patricia Cerrito, University of Louisville, Louisville, KY John C. Cerrito, Kroger Pharmacy, Louisville, KY
Klasifikasi/Subjek	: ,
Penerbitan	: University of Louisville, Louisville: 2010.
Bahasa	: Inggris
PENYIMPANAN
Lokasi	: PUSAT-40-A-
Jumlah	: 1

Abstraksi

ABSTRACT This analysis uses data-mining techniques on an electronic medical record in the Emergency Department of a hospital to improve care while lowering costs. All patients' records for a 6-month period were examined, and records of those patients who had an initial complaint of shortness-of-breath were extracted. The data-mining techniques of transactional time series in the HPF procedure and the association rules in SAS® Enterprise Miner™ were used to examine the data. Patients' orders, medications, and complaints were also examined using SAS® Text Miner to investigate relationships among the variable categories. The Association Node in SAS Enterprise Miner is applied to one target variable that uses a patient identifier to link orders, medications, and charges. Unfortunately, the Association Node is inadequate when there are too many choices for each target; it cannot relate different target values to each other. An alternative method is to change the observational unit to the patient by using the TRANSPOSE and CONCAT procedures. In this way, all patients' orders, medications, and changes are linked in text strings that can be examined and compared using SAS Text Miner. It was discovered that patients with similar complaints were treated very differently depending on the attending physician, and those differences can impact both costs and care in a hospital Emergency Department

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