Relationship Between Nursing Documentation and Patients' Mortality
Male
Vital Signs
Patient Acuity
Documentation
Length of Stay
Middle Aged
Nursing Staff, Hospital
3. Good health
03 medical and health sciences
Data Mining
Electronic Health Records
Humans
Female
Hospital Mortality
0305 other medical science
Aged
Monitoring, Physiologic
DOI:
10.4037/ajcc2013426
Publication Date:
2013-07-01T07:22:47Z
AUTHORS (7)
ABSTRACT
Nurses alter their monitoring behavior as a patient's clinical condition deteriorates, often detecting and documenting subtle changes before physiological trends are apparent. It was hypothesized that a nurse's behavior of recording optional documentation (beyond what is required) reflects concern about a patient's status and that mining data from patients' electronic health records for the presence of these features could help predict patients' mortality.Data-mining methods were used to analyze electronic nursing documentation from a 15-month period at a large, urban academic medical center. Mortality rates and the frequency of vital sign measurements (beyond required) and optional nursing comment documentation were analyzed for a random set of patients and patients who experienced a cardiac arrest during their hospitalization. Patients were stratified by age-adjusted Charlson comorbidity index.A total of 15,000 acute care patients and 145 cardiac arrest patients were studied. Patients who died had a mean of 0.9 to 1.5 more optional comments and 6.1 to 10 more vital signs documented within 48 hours than did patients who survived. A higher frequency of comment and vital sign documentation was also associated with a higher likelihood of cardiac arrest. Of patients who had a cardiac arrest, those with more documented comments were more likely to die.For the first time, nursing documentation patterns have been linked to patients' mortality. Findings were consistent with the hypothesis that some features of nursing documentation within electronic health records can be used to predict mortality. With future work, these associations could be used in real time to establish a threshold of concern indicating a risk for deterioration in a patient's condition.
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