Development of trigger tools for surveillance of adverse events in ambulatory surgery
ABSTRACT The trigger tool methodology uses clinical algorithms applied electronically to 'flag' medical records where adverse events (AEs) have most likely occurred. The authors sought to create surgical triggers to detect AEs in the ambulatory care setting.
Four consecutive steps were used to develop ambulatory surgery triggers. First, the authors conducted a comprehensive literature review for surgical triggers. Second, a series of multidisciplinary focus groups (physicians, nurses, pharmacists and information technology specialists) provided user input on trigger selection. Third, a clinical advisory panel designed an initial set of 10 triggers. Finally, a three-phase Delphi process (surgical and trigger tool experts) evaluated and rated the suggested triggers.
The authors designed an initial set of 10 surgical triggers including five global triggers (flagging medical records for the suspicion of any AE) and five AE-specific triggers (flagging medical records for the suspicion of specific AEs). Based on the Delphi rating of the trigger's utility for system-level interventions, the final triggers were: (1) emergency room visit(s) within 21 days from surgery; (2) unscheduled readmission within 30 days from surgery; (3) unscheduled procedure (interventional radiological, urological, dental, cardiac or gastroenterological) or reoperation within 30 days from surgery; (4) unplanned initial hospital length of stay more than 24 h; and (5) lower-extremity Doppler ultrasound order entry and ICD code for deep vein thrombosis or pulmonary embolus within 30 days from surgery.
The authors therefore propose a systematic methodology to develop trigger tools that takes into consideration previously published work, end-user preferences and expert opinion.
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ABSTRACT: Retrospective record review using trigger tools remains the most widely used method for measuring adverse events (AEs) to identify targets for improvement and measure temporal trends. However, medical records often contain limited information about factors contributing to AEs. We implemented an augmented trigger tool that supplemented record review with debriefing front-line staff to obtain details not included in the medical record. We hypothesised that this would foster the identification of factors contributing to AEs that could inform improvement initiatives. A trained observer prospectively identified events in consecutive patients admitted to a general medical ward in a tertiary care academic medical centre (November 2010 to February 2011 inclusive), gathering information from record review and debriefing front-line staff in near real time. An interprofessional team reviewed events to identify preventable and potential AEs and characterised contributing factors using a previously published taxonomy. Among 141 patients, 14 (10%; 95% CI 5% to 15%) experienced at least one preventable AE; 32 patients (23%; 95% CI 16% to 30%) experienced at least one potential AE. The most common contributing factors included policy and procedural problems (eg, routine protocol violations, conflicting policies; 37%), communication and teamwork problems (34%), and medication process problems (23%). However, these broad categories each included distinct subcategories that seemed to require different interventions. For instance, the 32 identified communication and teamwork problems comprised 7 distinct subcategories (eg, ineffective intraprofessional handovers, poor interprofessional communication, lacking a shared patient care, paging problems). Thus, even the major categories of contributing factors consisted of subcategories that individually related to a much smaller subset of AEs. Prospective application of an augmented trigger tool identified a wide range of factors contributing to AEs. However, the majority of contributing factors accounted for a small number of AEs, and more general categories were too heterogeneous to inform specific interventions. Successfully using trigger tools to stimulate quality improvement activities may require development of a framework that better classifies events that share contributing factors amenable to the same intervention. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.BMJ quality & safety 03/2015; DOI:10.1136/bmjqs-2014-003432 · 3.28 Impact Factor
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ABSTRACT: Background: Patient safety in primary care is a developing field with an embryonic but evolving evidence base. This narrative review aims to identify tools that can be used by family practitioners as part of a patient safety toolkit to improve the safety of the care and services provided by their practices. Methods: Searches were performed in 6 healthcare databases in 2011 using 3 search stems; location (primary care), patient safety synonyms and outcome measure synonyms. Two reviewers analysed the results using a numerical and thematic analyses. Extensive grey literature exploration was also conducted. Results: Overall, 114 Tools were identified with 26 accrued from grey literature. Most published literature originated from the USA (41%) and the UK (23%) within the last 10 years. Most of the literature addresses the themes of medication error (55%) followed by safety climate (8%) and adverse event reporting (8%). Minor themes included; informatics (4.5%) patient role (3%) and general measures to correct error (5%). The primary/secondary care interface is well described (5%) but few specific tools for primary care exist. Diagnostic error and results handling appear infrequently (<1% of total literature) despite their relative importance. The remainder of literature (11%) related to referrals, Out-Of-Hours (OOH) care, telephone care, organisational issues, mortality and clerical error. Conclusions: This review identified tools and indicators that are available for use in family practice to measure patient safety, which is crucial to improve safety and design a patient safety toolkit. However, many of the tools have yet to be used in quality improvement strategies and cycles such as plan-do-study-act (PDSA) so there is a dearth of evidence of their utility in improving as opposed to measuring and highlighting safety issues. The lack of focus on diagnostics, systems safety and results handling provide direction and priorities for future research.BMC Family Practice 10/2014; 15(1):166. DOI:10.1186/1471-2296-15-166 · 1.74 Impact Factor
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ABSTRACT: BACKGROUND: Little evidence exists regarding the characteristics of intraoperative adverse events (iAEs). METHODS: Administrative data, the American College of Surgeons - National Surgical Quality Improvement Project, and systematic review of operative reports were used to confirm iAEs in abdominal surgery patients. Standard American College of Surgeons - National Surgical Quality Improvement Project data were supplemented with variables including injury type/organ, phase of operation, adhesions, repair type, and intraoperative consultations. RESULTS: Two hundred twenty-seven iAEs (187 patients) were confirmed in 9,292 patients. Most common injuries were enterotomies during intestinal surgery (68%) and vessel injuries during hepatopancreaticobiliary surgery (61%); 108 iAEs (48%) specifically occurred during adhesiolysis. A third of the iAEs required organ/tissue resection or complex reconstruction. Because of iAEs, 20 intraoperative consults (11%) were requested and 9 of the 66 (16%) laparoscopic cases were converted to open. Thirty-day mortality and morbidity were 6% and 58%, respectively. The complications included perioperative transfusions (36%), surgical site infection (19%), systemic sepsis (13%), and failure to wean off the ventilator (12%). CONCLUSIONS: iAEs commonly occur in reoperative cases requiring lysis of adhesions and possibly lead to increased patient morbidity. Understanding iAEs is essential to prevent their occurrence and mitigate their adverse effects.The American Journal of Surgery 05/2014; 208(4). DOI:10.1016/j.amjsurg.2014.02.014 · 2.41 Impact Factor