JMIR Publications

ABSTRACT

Background:

Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate through the EHR. These data can be used to better understand provider responses to EHR-based clinical decision support (CDS), shedding light on why CDS is (and is not) effective.

Objective:

To determine the feasibility of using EHR access and audit logs to track primary care physician (PCP) opening of and response to non-interruptive alerts delivered to EHR InBaskets.

Methods:

We conducted a descriptive study to assess use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 non-interruptive alerts sent to 75 PCPs’ InBaskets as part of a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients post-hospital discharge: information-only (593), medication recommendations (37), and test recommendations (169). We sought log data to identify timing of alert opening and timing and type of PCPs’ subsequent EHR actions (immediate actions and those taken by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use.

Results:

We successfully identified the required data in EHR access and audit logs. Our descriptive study found that one-third (33.8%) of alerts opened by the addressed PCP (208/616) were followed by immediate EHR action by the PCP. Two-thirds (67.3%) of all alerts (538/799) had evidence of action by the end of the following day. Compared to information-only alerts, the odds ratios (OR) of immediate action for medication recommendation were 4.03 [95% confidence interval (CI) 1.67- 9.72]; the OR for test recommendation alerts was 2.14 [95% CI 1.38-3.32]. Compared to information-only alerts, OR of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59 [95% CI 2.42-12.94]) and test recommendations (1.71 [95% CI 1.09-2.68]); we found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges. (1) Capturing a historical snapshot of EHR status (e.g. number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior along with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team, taking action within the EHR then examining the audit log to identify the corresponding documentation.

Conclusions:

EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned in advance of implementing an EHR-based study.