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Multicenter Study
. 2023 Jan;18(1):5-14.
doi: 10.1002/jhm.12979. Epub 2022 Nov 3.

Implementation of the I-PASS handoff program in diverse clinical environments: A multicenter prospective effectiveness implementation study

Collaborators, Affiliations
Multicenter Study

Implementation of the I-PASS handoff program in diverse clinical environments: A multicenter prospective effectiveness implementation study

Amy J Starmer et al. J Hosp Med. 2023 Jan.

Abstract

Background: Handoff miscommunications are a leading source of medical errors. Harmful medical errors decreased in pediatric academic hospitals following implementation of the I-PASS handoff improvement program. However, implementation across specialties has not been assessed.

Objective: To determine if I-PASS implementation across diverse settings would be associated with improvements in patient safety and communication.

Design: Prospective Type 2 Hybrid effectiveness implementation study.

Settings and participants: Residents from diverse specialties across 32 hospitals (12 community, 20 academic).

Intervention: External teams provided longitudinal coaching over 18 months to facilitate implementation of an enhanced I-PASS program and monthly metric reviews.

Main outcome and measures: Systematic surveillance surveys assessed rates of resident-reported adverse events. Validated direct observation tools measured verbal and written handoff quality.

Results: 2735 resident physicians and 760 faculty champions from multiple specialties (16 internal medicine, 13 pediatric, 3 other) participated. 1942 error surveillance reports were collected. Major and minor handoff-related reported adverse events decreased 47% following implementation, from 1.7 to 0.9 major events/person-year (p < .05) and 17.5 to 9.3 minor events/person-year (p < .001). Implementation was associated with increased inclusion of all five key handoff data elements in verbal (20% vs. 66%, p < .001, n = 4812) and written (10% vs. 74%, p < .001, n = 1787) handoffs, as well as increased frequency of handoffs with high quality verbal (39% vs. 81% p < .001) and written (29% vs. 78%, p < .001) patient summaries, verbal (29% vs. 78%, p < .001) and written (24% vs. 73%, p < .001) contingency plans, and verbal receiver syntheses (31% vs. 83%, p < .001). Improvement was similar across provider types (adult vs. pediatric) and settings (community vs. academic).

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Conflict of interest statement

CONFLICT OF INTEREST

All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: all authors had financial support from the Agency for Healthcare Research and Quality for the submitted work. CPL, SJP, TCS, NDS, AJS, and DCW hold equity in the I-PASS Patient Safety Institute. RS works for Intermountain Healthcare, which holds equity in the I-PASS Patient Safety Institute. SC, JKO’T, and SJP hold stock options in the I-PASS Patient Safety Institute. SC, NK, CPL, JKO’T, SJP, GR, TCS, NDS, AJS, and DCW have consulted with the I-PASS Patient Safety Institute. The I-PASS Patient Safety Institute is a company that seeks to train institutions in best handoff practices and aid in their implementation. The current study was designed before the I-PASS Patient Safety Institute was conceived of as an entity and the I-PASS Patient Safety Institute was in no way involved in this study. Moreover, to ensure objectivity, all data were analyzed via a statistical team who do not have any involvement with the I-PASS Patient Safety Institute. All analyses were conducted by this statistical team. TCS, NDS, AJS, and DCW have received monetary awards, honoraria, and travel reimbursement from multiple academic and professional organizations for teaching and consulting on physician performance and handoffs. CPL and RS are supported in part by the Children’s Hospital Association for their work as executive council members of the Pediatric Research in Inpatient Settings (PRIS) network. RS has received monetary awards, honorariums, and travel reimbursement from multiple academic and professional organizations for talks about pediatric hospitalist research networks and quality of care. CPL has received monetary awards, honoraria, and travel reimbursement from multiple academic and professional organizations for teaching and consulting on sleep deprivation, physician performance, handoffs, and safety, and has served as an expert witness in cases regarding patient safety and sleep deprivation. JLS was the recipient of a grant from Mallinckrodt Pharmaceuticals to conduct an investigator-initiated study of opioid-related adverse drug events in surgical patients. All other authors have no conflict of interest to disclose at this time.

Figures

FIGURE 1
FIGURE 1
Adherence to (a) all 5 verbal I-PASS elements and (b) all five written I-PASS elements. For both figures, to account for clustering by site, proportions estimated from mixed effects models. Vertical lines represent 95% confidence intervals. Horizontal lines reflect peri-intervention and postintervention overall adherence rates.
FIGURE 2
FIGURE 2
Quality of verbal and written handoff communication. To account for clustering by site, proportions estimated from mixed effects models. Vertical lines represent 95% confidence intervals. Improvement from baseline to postintervention for all comparisons (p < .001).
FIGURE 3
FIGURE 3
Verbal adherence to I-PASS by hospital and resident characteristics of (a) wave, (b) hospital type, (c) specialty, and (d) post graduateyear. For all figures, to account for clustering by site, proportions estimated from mixed effects models. Vertical lines represent 95% confidence intervals. Improvement from baseline to postintervention for all comparisons (p < .001). *Difference at baseline across wave (p < .001) and postgraduate year (p < .05). The test of interaction between time (baseline to postintervention) and hospital characteristic was significant for wave (p < .001) and postgraduate year (0.011) but not for hospital type (p = .325) or specialty (p = .070). There were no significant differences in adherence in the postintervention period by wave, hospital type, specialty, or PGY year.
FIGURE 4
FIGURE 4
Written adherence to I-PASS by hospital characteristics of (a) wave of participation, (b) hospital type, and (c) specialty. For all figures, to account for clustering by site, proportions estimated from mixed effects models. Vertical lines represent 95% confidence intervals. Improvement from baseline to postintervention for all comparisons (p < .001). *p < .05 across wave, hospital type, and specialty at baseline. The test of interaction between time (baseline to postintervention) and hospital characteristic was significant for wave (p < .001), hospital type (p < .001), and specialty (p = .018), reflecting significant differences atbaseline. There were no signicant differences in adherence in the postintervention period by wave, hospital type, or specialty.

References

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