The preliminary development and testing of a global trigger tool to detect error and patient harm in primary-care records

Abstract

Background: A multi-method strategy has been proposed to understand and improve the safety of primary care. The trigger tool is a relatively new method that has shown promise in American and secondary healthcare settings. It involves the focused review of a random sample of patient records using a series of ''triggers'' that alert reviewers to potential errors and previously undetected adverse events. Aim: To develop and test a global trigger tool to detect errors and adverse events in primary-care records. Method: Trigger tool development was informed by previous research and content validated by expert opinion. The tool was applied by trained reviewers who worked in pairs to conduct focused audits of 100 randomly selected electronic patient records in each of five urban general practices in central Scotland. Results: Review of 500 records revealed 2251 consultations and 730 triggers. An adverse event was found in 47 records (9.4%), indicating that harm occurred at a rate of one event per 48 consultations. Of these, 27 were judged to be preventable (42%). A further 17 records (3.4%) contained evidence of a potential adverse event. Harm severity was low to moderate for most patients (82.9%). Error and harm rates were higher in those aged >60 years, and most were medication-related (59%). Conclusions: The trigger tool was successful in identifying undetected patient harm in primary-care records and may be the most reliable method for achieving this. However, the feasibility of its routine application is open to question. The tool may have greater utility as a research rather than an audit technique. Further testing in larger, representative study samples is required.Error and harm in healthcare are common, costly and often preventable.

The Accuracy of Trigger Tools to Detect Preventable Adverse Events in Primary Care: A Systematic Review

“…Therefore, 15 studies with a total of 278,212 patients and 126,197 incidents of positive triggers were included in this review. 17,20,31,[33][34][35][36][37][38][39][40][41][42][43][44][45] Of the 15 included studies, 9 were conducted in the United States, 3 in Scotland, and 1 each in Brazil, France, and Australia (Table 2). Eight studies were published since 2010 and 2 were published before 2000.…”

“…42,43,45 Three studies looked at any type of pAE identified in the chart. 20,31,34,35,37 The most commonly used method to identify pAEs was chart review. 20,31,[33][34][35][36][37][38][39][40][41][42][43][44] Four studies used physicians only as reviewers 35,37,38,40 , 3 used a combination of physicians and pharmacists.…”

“…20,31,34,35,37 The most commonly used method to identify pAEs was chart review. 20,31,[33][34][35][36][37][38][39][40][41][42][43][44] Four studies used physicians only as reviewers 35,37,38,40 , 3 used a combination of physicians and pharmacists. 33,36,41 1 used nurses 34 , 1 used pharmacists 44 , and 1 used a combination of physicians and nurses 20 , 5 studies used more than 1 reviewer and all these used at least 2 independent reviewers.…”

“…This tool was chosen because it has been previously described as particularly relevant to the outpatient and primary care setting and it represents an established list of predefined triggers. 20 The tool developed by the IHI has been reportedly validated in outpatients to detect any AEs, preventable or not. 19 Although there are reasons why assessing preventability can be problematic 21 , pAEs and medical errors are opportunities for many safety interventions 22 and are often the most easily accepted improvement opportunities by providers due to their intuitive appeal as targets for improvement.…”

Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism

“…Thus, trigger tools can be used to alert clinicians about possible delays and other adverse events. [19][20][21][22] Triggers consist of an algorithm applied to an EHR database to identify, or Btrigger,^all patient records that match a predefined pattern of care (e.g., a patient with a test result flagged as Babnormal^but with no provider follow-up within 30 days of the result). We had previously developed and validated a trigger that scanned large repositories of clinical data to identify patients with potentially delayed diagnostic clues that warranted an evaluation for prostate, colorectal, or lung cancer.…”