The Identification of Medical Errors by Family Physicians During Outpatient Visits

Abstract

BACKGROUND We wanted to describe errors and preventable adverse events identifi ed by family physicians during the offi ce-based clinical encounter and to determine the physicians' perception of patient harm resulting from these events. METHODWe sampled Cincinnati area family physicians representing different practice locations and demographics. After each clinical encounter, physicians completed a form identifying process errors and preventable adverse events. Brief interviews were held with physicians to ascertain their perceptions of harm or potential harm to the patient. RESULTSFifteen physicians in 7 practices completed forms for 351 outpatient visits. Errors and preventable adverse events were identifi ed in 24% of these visits. There was wide variation in how often individual physicians identifi ed errors (3% to 60% of visits). Offi ce administration errors were most frequently noted. Harm was believe to have occurred as a result of 24% of the errors, and was a potential in another 70%. Although most harm was believed to be minor, there was disagreement as to whether to include emotional discomfort and wasted time as patient harm.CONCLUSIONS Family physicians identify errors and preventable adverse events frequently during patient visits, but there is variation in how some error categories are interpreted and how harm is defi ned. INTRODUCTIONT he role of medical errors and adverse events as important factors in the health outcomes of patients is well known, at least for hospitalized patients.1,2 Identifying adverse events and attributing cause to error, however, is diffi cult.3-5 Most of the medical care in the United States occurs not in the hospital but in the outpatient primary care setting, 6 where the role of medical errors is even less clear. Until now outpatient studies have collected retrospective physician-generated reports of errors they have made 7 or noted in their practices. [8][9][10] A few studies have examined specifi c areas of potential error, such as physician-patient communication, 11 specialist-primary care communication, 12 or incident report claims. 13 When combined, these studies begin to document the full breadth of errors recognized primarily by physicians, but they offer minimal information on incidence or severity.14 A more accurate assessment of the incidence and severity of errors and preventable adverse events in primary care is necessary to develop successful interventions to improve patient safety.The purpose of this study was to have physicians identify prospectively those errors and preventable adverse events that occur during offi ce-based clinical encounters and to assess the physicians' perceptions of harm from these errors. This effort is a preliminary step in defi ning the incidence of medical errors and their associated harm in outpatient primary care. METHODS SampleTwo to 4 physicians in each of 9 family practice offi ces in the greater Cincinnati area were approached to take part in a study "of the errors and problems that seem to occur almost daily in...

Reporting and Using Near-miss Events to Improve Patient Safety in Diverse Primary Care Practices: A Collaborative Approach to Learning from Our Mistakes

“…24 All staff members were invited to anonymously report near-miss events using an online form that had been adapted from previous studies and field tested, with an average completion time of 2 minutes per report (See Appendix). 25 The online form did not include any patient identifiers, was available electronically from any Internet-enabled computer, and stored reports on a central computer in an encrypted format. Staff attended a standardized, 1-hour orientation and during the study period received an automated E-mail message every 2 weeks inviting them to report any near-miss event they could recall from the previous 2 weeks.…”

eHealth-as-a-Service: A Service Based Design Approach for Large Scale eHealth Architecture

“…(Batini & Scannapieco, 2016). However, supported by specialist literature (Banfield, et al, 2013;Elder, Meulen, & Cassedy, 2004), quality dimensions used in the evaluation phase of this thesis was informed by findings in Chapter 4 which concluded that accuracy and timeliness may lead to improved continuity of care. (ii) Meaningful but incorrect IS state from Wand and Wang (1996).…”

“…Reliability signifies that the data can be trusted to deliver correct information. Timeliness is defined by the delay between changes in the RW state and (Banfield, et al, 2013;Elder, Meulen, & Cassedy, 2004), quality dimensions used in the evaluation phase of this thesis was informed by findings in Chapter 4 which concluded that accuracy and timeliness may lead to improved continuity of care. …”

“…This risk is brought into sharp focus by a qualitative analysis of error reports made by primary healthcare clinicians in the United States (US) which identified that 30.9% of errors were due to administrative failures (Dovey et al, 2002). Considering this, information intensive processes such as the coordination of care in primary healthcare settings is vulnerable to missing information which has been linked to adverse clinical events in Australia and the US (Elder, et al, 2004;Harrison, Gibberd, Hamilton, & Wilson, 1999;Smith, et al, 2005).…”

“…The CSHIS system actor was used to establish baseline measures in order to compare and contrast the behaviours of MyHR and eHaaS. Using the techniques discussed in Section 6.3, the quality attributes of data outputs (component data items and information products),were systematically monitored and measured to analyse the processing effectiveness of each system actor.Quality dimensions used in the analysis was informed by findings in Chapter 4 which concluded that accuracy and timeliness may lead to improved continuity of care and this was supported by specialist literature (Banfield, et al, 2013;Elder, et al, 2004). Using a functional approach and differential calculus, it was possible to accurately estimate the effect of transformation functions on these quality attributes and they are relatively straightforward to model.…”