Study Design, Setting, and Participants
The Partners Human Research Committee approved the study and granted a waiver of consent. We conducted a cluster randomized controlled trial at Brigham and Women’s Hospital, a 793-bed tertiary care hospital in Boston, MA, affiliated with Partners HealthCare, Inc., an integrated healthcare delivery network. Patients discharged from general medicine and cardiology services with at least one TPAD between June 2011 and May 2012 were assigned to intervention or usual care groups based upon the randomization status of their discharging attending and PCP.
Physicians caring for eligible patients included hospitalists, traditional internists, cardiologists, and other subspecialists attending on general medicine services, as well as PCPs. All Partners physicians could access the network EHR and enterprise email securely from a clinical workstation, personal computer, or encrypted mobile device. Non-network PCPs did not have access to Partners clinical information systems, but discharge summaries were faxed or mailed within 48 hours of discharge.
Intervention
The system automatically sent notifications to network clinicians’ institutional email addresses, and was configured to minimize alert fatigue. Each notification was flagged as an “Important Post-Discharge Test Result” in the subject heading, and the discharging attending was assigned responsibility in the body of the email. Network PCPs were carbon copied, thereby allowing the attending to communicate clinical context and transfer responsibility after discharge.16 Non-network PCPs were not notified by email; however, the attending could choose to communicate with non-network PCPs (via phone, letter, etc.) and document these actions in the EHR.
Randomization
The randomization procedures were previously described.17 Briefly, attendings and PCPs (network and non-network) were independently randomized, and patients were assigned to the intervention or usual care group if the attending and PCP were in concordant study arms. Patients of physicians randomized to discordant study arms were excluded to avoid contamination. Non-network patients were included in the intention-to-treat analysis, though non-network PCPs did not receive automated emails.
Identification of Actionable TPAD Results
We adapted an established algorithm to identify actionable TPADs.3,21 All normal, near-normal, and benign results were excluded. Two board-certified, internal medicine physicians (A-reviewers: AS, AD), blinded to randomization status, independently reviewed the discharge summary to determine whether the TPAD was listed, and to categorize the TPAD as definitely actionable, probably actionable, probably not actionable, or definitely not actionable according to a list of actions designated a priori (Box 1). A-reviewers adjudicated all discrepancies until consensus was reached. Thus, patients with TPADs who did not have at least one actionable TPAD identified by independent physician review were excluded.
Box 1 Types of actions taken by responsible providers after acknowledging an actionable TPAD Determination of Documented Acknowledgement and Actions
Two different physicians (B-reviewers: EG, RP), blinded to randomization, independently reviewed the EHR to identify follow-up documentation for each actionable TPAD identified by A-reviewers. We defined follow-up as explicit documentation of acknowledgment or action (independent events) in the EHR’s note repository similarly to El-Kareh.5 B-reviewers used a natural language processing search tool, Queriable Patient Inference Dossier (QPID)—widely used at our institution to identify clinical information at the point-of-care—to retrieve relevant documentation.22 Specifically, B-reviewers queried the EHR for all documentation pertinent to the actionable TPAD (clinic and hospital notes, phone calls, medication lists, etc.) for up to 6 months after discharge. For patients with a high volume of documentation, reviewers used broad but specific search terms (e.g., A1c) to improve sensitivity when conducting queries while ensuring retrieval of the most pertinent subset of documentation related to the actionable TPAD.
After retrieving relevant documentation, B-reviewers determined whether the result was acknowledged; the name and specialty of the individual who acknowledged the result; the format of acknowledgment (phone call, hospital, or clinic note); and whether one or more actions (Box 1) were documented. B-reviewers resolved all discrepancies between themselves. Chart review was limited to our network’s EHR; out-of-network records of enrolled patients were not reviewed.
Outcomes
The primary outcome was the proportion of actionable TPADs with documented action. Secondary outcomes included the proportion of actionable TPADs with documented acknowledgment, patients with actionable TPADs readmitted within 30-days of hospitalization, and median days to documented follow-up. We quantified types of actions (Box 1) documented.
Sample Size
Based on El-Kareh, we expected the proportion of actionable TPADs with documented follow-up to increase from 13 to 28% when responsible physicians were notified.8 We assumed that patients had approximately one actionable TPAD (Roy et al. observed 1.08 actionable TPADs per patient).3 To achieve 80% power with an alpha of 0.05,23 we estimated that we would need to review records of 144 discharged patients with actionable TPADs to detect the effect size noted above (288 in both groups combined), accounting for clustering by attending (intra-class correlation coefficient of 0.03, cluster size of ten patients with an actionable TPAD per physician based on our prior study17) and a 50% reduction in sample size due to exclusion of patients cared for by physicians randomized to discordant study arms. Sample size calculations were conducted using NCSS PASS, version 12 (Kaysville, UT). We identified this cohort by randomly sampling TPADs from all available patient-discharges for up to 1 year after our prior study.17
Covariates
We collected patient demographics including age, gender, ethnicity, socioeconomic, and insurance status, Elixhauser comorbidity score,24 network affiliation, and length of stay. We collected physician demographics including age, gender, post-graduate year, specialty (general internist, hospitalist, cardiologist, other specialist), and number of years employed from hospital administrative databases, publicly available information (American Board of Internal Medicine), and practice managers.
Statistical Analysis
Patient and physician characteristics were described using means with standard deviations, medians with inter-quartile ranges, and proportions as appropriate. We analyzed the primary outcome as the proportion of actionable TPADs with documented action. We analyzed documented acknowledgment similarly. We analyzed hospital readmissions as the proportion of patients discharged with an actionable TPAD who were readmitted to a network-affiliated hospital within 30 days of index hospitalization. The effect of dichotomous variables on all outcomes was first analyzed using Fisher’s exact test. To measure days to documented follow-up, we calculated adjusted medians with 95% CIs using median regression.25 We then used multivariable logistic regression to analyze action, acknowledgment, and readmission adjusted for a priori selected covariates and general estimating equations to cluster by attending. In sub-group analyses, we used multivariable logistic regression with an interaction term (study arm*characteristic-type) to determine effect modification. Two-sided p values < 0.05 were considered significant. Analyses were conducted using SAS v9.4 (Cary, NC).