Background 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. Methods 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. Results 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. Conclusions 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.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• There are presently no published data on tramadol transfer into breast milk or on its effects in the breastfed infant. WHAT THIS STUDY ADDS• We have provided quantitative data on the absolute and relative infant doses of rac-tramadol and it rac-O-desmethyl metabolite for the breastfed infant.• We have also demonstrated a novel sparse sampling data collection method for investigating infant exposure via milk. AIMSTo investigate the transfer of rac-tramadol and its rac-O-desmethyl metabolite into transitional milk, and assess unwanted effects in the breastfed infant. METHODSTramadol HCl (100 mg six hourly) was administered to 75 breastfeeding mothers for postoperative analgesia on days 2-4 after Caesarian section. Milk and plasma samples were collected after administration of four or more doses. Rac-tramadol and rac-O-desmethyltramadol were measured by high performance liquid chromatography. Milk : plasma ratio (M : P) and infant doses were calculated by standard methods. The behavioural characteristics of the exposed breastfed infants and a matched control group of infants not exposed to tramadol were also studied. RESULTSAt steady-state, mean (95% CI) M : P was 2.2 (2.0, 2.4) for rac-tramadol and 2.8 (2.5, 3.1) for rac-O-desmethyltramadol. The estimated absolute and relative infant doses were 112 (102, 122) mg kg -1 day -1 and 30 (28, 32) mg kg -1 day -1, and 2.24% (2.04, 2.44)% and 0.64% (0.59, 0.69)% for rac-tramadol and rac-O-desmethyltramadol, respectively. The exposed infants and control breastfed infants had similar characteristics, including Apgar scores at birth and Neurologic and Adaptive Capacity Scores. CONCLUSIONSThe combined relative infant dose of 2.88% at steady-state was low. The similarity of NACS in exposed infants and controls suggests that there were no significant behavioural adverse effects. We conclude that short-term maternal use of tramadol during establishment of lactation is compatible with breastfeeding.

A commercial rule base (Cerner Multum) was used to identify medication orders exceeding recommended dosage limits at five hospitals within BJC HealthCare, an integrated health care system. During initial testing, clinical pharmacists determined that there was an excessive number of nuisance and clinically insignificant alerts, with an overall alert rate of 9.2%. A method for customizing the commercial rule base was implemented to increase rule specificity for problematic rules. The system was subsequently deployed at two facilities and achieved alert rates of less than 1%. Pharmacists screened these alerts and contacted ordering physicians in 21% of cases. Physicians made therapeutic changes in response to 38% of alerts presented to them. By applying simple techniques to customize rules, commercial rule bases can be used to rapidly deploy a safety net to screen drug orders for excessive dosages, while preserving the rule architecture for later implementations of more finely tuned clinical decision support.