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Background: Older adults may be at risk for adverse outcomes after discharge from skilled nursing facilities (SNF), but little research has focused on this transition. Objective: To assess the impact of an alert system on the rates of adverse outcomes among older adults discharged from SNFs to home. Methods: Within a multispecialty group practice, we tracked 30-day re-hospitalizations after SNF discharges during an intervention that provided discharge alerts to primary care physicians. We compared them to discharges from the pre-intervention period matched on age, gender and SNF. For the first 100 intervention discharges and their matches, we performed chart reviews to identify adverse drug events (ADEs). Multivariate analyses controlled for age, gender and intervention status. Results: We matched 313 intervention SNF discharges to 313 previous discharges. There was a slight reduction in the rate of 30-day re-hospitalization (30% vs. 31%) adjusted. Within the ADE study, 30% of the discharges during the intervention period and 30% of matched discharges had ADEs within 45 days. Among the 83 ADEs identified, 28% were deemed preventable; 69% resulted in symptom duration more than one day; 69% occurred within the first 14 days after discharge. This was a highly vulnerable population: mean age 82.5 (standard deviation (SD) 6.7); mean number of prescribed medications 11.9 (SD 8); 17% had Charlson Comorbidity Scores of ≥4. Common clinical conditions included myocardial infarction (24%), heart failure (22%), COPD (23%), and major depression (28%). Patients with scores of ≥4 were more likely to experience an ADE than those with lower scores (adjusted OR 2.5 (CI 1.2, 5.5), RD 0.21). Conclusion: Simply providing alerts when these vulnerable patients are discharged from SNFs is not sufficient to lower rates of adverse outcomes. Further research is required to track trajectories and identify additional points for interventions.

Background: Electronic medical records (EMR) provide opportunities to implement systems of information flow, such as alerts to providers. Methods: Within a group practice with an EMR, we conducted a trial of automated alerts to the in-baskets of primary care physicians and staff when patients were discharged from hospital to home. We generated alerts for new medications or monitoring needs. Staff received alerts to schedule office visits. Using EMR “digital crumbs”, we tracked when alerts were viewed. We analyzed the impact of physician age, gender, department, and employment status (full-time, part-time) as well as patient conditions (age, gender, comorbidity, and number of office visits in the previous year) on timely opening. Results: Of 763 alerts to physicians, 616 (81%) were opened within one day. Characteristics associated with timely opening were age < 50 (OR 1.7, 95% CI 1.1, 2.6) and full-time employment (OR 2.9, 95% CI 1.6, 5.2). Of 1928 alerts to staff, 1173 (61%) were opened within one day. Staff of male physicians were more likely to open the alerts within one day (OR 1.8, 95% CI 1.4, 2.4) as were working for the Family Medicine department (OR 1.9, 95% CI 1.3, 2.6) or a sub-specialty department (OR 16.6, 95% CI 2.3, 122.3). Staff of full-time physicians were less likely to open alerts (OR 0.64, 95% CI 0.47, 0.87). Adjusting for patient characteristics had no impact on results. Conclusion: Special efforts may be required to reach physicians working part-time and older physicians. Characteristics related to staff opening of alerts are specific to this group practice, but the high level of variability across physician types and departments is likely to be an issue in many settings. Design of a system directed at reaching staff quickly may require in-depth assessment of work flow and communication patterns in clinical departments.