Using Time-Referenced Data to Assess Medication Administration Performance and Quality

OBJECTIVEThis study tests the feasibility of using a large (big) clinical data set to test the ability to extract time-referenced data related to medication administration to identify late doses and as-needed (PRN) administration patterns by RNs in an inpatient setting. METHODSThe study is a seconda...

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Bibliographic Details
Published in:The Journal of nursing administration 2018-02, Vol.48 (2), p.100-106
Main Authors: Welton, John M, Kleiner, Catherine, Valdez, Carolyn, Richardson, Sara, Boyle, Kathy, Lucas, Eric
Format: Article
Language:English
Subjects:
Big Data
Data analysis
Drug administration
Inpatient care
Nursing
Nursing care
Patient safety
Quality of care
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Summary:OBJECTIVEThis study tests the feasibility of using a large (big) clinical data set to test the ability to extract time-referenced data related to medication administration to identify late doses and as-needed (PRN) administration patterns by RNs in an inpatient setting. METHODSThe study is a secondary analysis of a set of data using bar-code medication administration time stamps (n = 3043812) for 50883 patients admitted to a single, urban, 525-bed hospital in 11 inpatient units by 714 nurses between April 1, 2013, and March 31, 2015. RESULTSThe large majority of scheduled medications (43.3%) were administered between 9 to 10 AM and 9 to 10 PM accounting for the most amount of delayed doses. On average, patients received 8.9 medications per day, and nurses administered 19.7 medications per shift. The average full-time nurse administered 3414 medications per year. CONCLUSIONSThe findings support use of time-referenced data to identify clinical processes and performance in administering scheduled and PRN medications.
ISSN:0002-0443
1539-0721
DOI:10.1097/NNA.0000000000000580