A stepped wedge, cluster controlled trial of an intervention to improve safety and quality on medical wards: the HEADS-UP study protocol

Samuel Pannick, Iain Beveridge, Hutan Ashrafian, Susannah J Long, Thanos Athanasiou, Nick Sevdalis

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

INTRODUCTION: The majority of preventable deaths in healthcare are due to errors on general wards. Staff perceptions of safety correlate with patient survival, but effectively translating ward teams' concerns into tangibly improved care remains problematic. The Hospital Event Analysis Describing Significant Unanticipated Problems (HEADS-UP) trial evaluates a structured, multidisciplinary team briefing, capturing safety threats and adverse events, with rapid feedback to clinicians and service managers. This is the first study to rigorously assess a simpler intervention for general medical units, alongside an implementation model applicable to routine clinical practice.

METHODS/ANALYSIS: 7 wards from 2 hospitals will progressively incorporate the intervention into daily practice over 14 months. Wards will adopt HEADS-UP in a pragmatic sequence, guided by local clinical enthusiasm. Initial implementation will be facilitated by a research lead, but rapidly delegated to clinical teams. The primary outcome is excess length of stay (a surplus stay of 24 h or more, compared to peer institutions' Healthcare Resource Groups-predicted length of stay). Secondary outcomes are 30-day readmission or excess length of stay; in-hospital death or death/readmission within 30 days; healthcare-acquired infections; processes of escalation of care; use of traditional incident-reporting systems; and patient safety and teamwork climates. HEADS-UP will be analysed as a stepped wedge cluster controlled trial. With 7840 patients, using best and worst case predictions, the study would achieve between 75% and 100% power to detect a 2-14% absolute risk reduction in excess length of stay (two-sided p<0.05). Regression analysis will use generalised linear mixed models or generalised estimating equations, and a time-to-event regression model. A qualitative analysis will evaluate facilitators and barriers to HEADS-UP implementation and impact.

ETHICS AND DISSEMINATION: Participating institutions' Research and Governance departments approved the study. Results will be published in peer-reviewed journals and at conference presentations.

TRIAL REGISTRATION NUMBER: ISRCTN34806867.

Original languageEnglish
Article numbere007510
Number of pages9
JournalBMJ open
Volume5
Issue number6
DOIs
Publication statusPublished - 22 Jun 2015

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