Adverse events related to hospital care: a retrospective medical records review in a Swiss hospital

Halfon, Patricia; Staines, Anthony; Burnand, Bernard

doi:10.1093/intqhc/mzx061

Cited by 45 publications

(48 citation statements)

References 28 publications

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“…Of the remaining 307 studies, 241 were excluded after reviewing the full article. A total of 66 studies reporting 70 independent samples were included in the review 1732333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798Figure 1. shows the study flow for the selection process.…”

Section: Resultsmentioning

confidence: 99%

Prevalence, severity, and nature of preventable patient harm across medical care settings: systematic review and meta-analysis

Panagioti

Khan

Keers

et al. 2019

BMJ

447

337

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ObjectiveTo systematically quantify the prevalence, severity, and nature of preventable patient harm across a range of medical settings globally.DesignSystematic review and meta-analysis.Data sourcesMedline, PubMed, PsycINFO, Cinahl and Embase, WHOLIS, Google Scholar, and SIGLE from January 2000 to January 2019. The reference lists of eligible studies and other relevant systematic reviews were also searched.Review methodsObservational studies reporting preventable patient harm in medical care. The core outcomes were the prevalence, severity, and types of preventable patient harm reported as percentages and their 95% confidence intervals. Data extraction and critical appraisal were undertaken by two reviewers working independently. Random effects meta-analysis was employed followed by univariable and multivariable meta regression. Heterogeneity was quantified by using the I2 statistic, and publication bias was evaluated.ResultsOf the 7313 records identified, 70 studies involving 337 025 patients were included in the meta-analysis. The pooled prevalence for preventable patient harm was 6% (95% confidence interval 5% to 7%). A pooled proportion of 12% (9% to 15%) of preventable patient harm was severe or led to death. Incidents related to drugs (25%, 95% confidence interval 16% to 34%) and other treatments (24%, 21% to 30%) accounted for the largest proportion of preventable patient harm. Compared with general hospitals (where most evidence originated), preventable patient harm was more prevalent in advanced specialties (intensive care or surgery; regression coefficient b=0.07, 95% confidence interval 0.04 to 0.10).ConclusionsAround one in 20 patients are exposed to preventable harm in medical care. Although a focus on preventable patient harm has been encouraged by the international patient safety policy agenda, there are limited quality improvement practices specifically targeting incidents of preventable patient harm rather than overall patient harm (preventable and non-preventable). Developing and implementing evidence-based mitigation strategies specifically targeting preventable patient harm could lead to major service quality improvements in medical care which could also be more cost effective.

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Section: Resultsmentioning

confidence: 99%

Prevalence, severity, and nature of preventable patient harm across medical care settings: systematic review and meta-analysis

Panagioti

Khan

Keers

et al. 2019

BMJ

447

337

View full text Add to dashboard Cite

show abstract

“…As data sources, electronic health records are rich but often somewhat chaotic, adding to the complexity of adverse event detection. Terms used to report fall events vary between settings, which could limit an algorithm’s performance [ 29 ]. However, in our validation study, the same unmodified version of our algorithm returned excellent results in 3 clinical departments on 2 sites (using 2 electronic health record systems) [ 30 - 32 ].…”

Section: Discussionmentioning

confidence: 99%

“…This study is subject to several notable limitations. First, the quality of any algorithm’s results cannot surpass that of the documentation upon which it is based, that is, the quality and the completeness of the documentation define the limits of the algorithm’s performance [ 17 , 29 ]. Therefore, heavy workloads, which influence documentation quality, also influence our algorithm’s capacity to detect falls.…”

Section: Discussionmentioning

confidence: 99%

Automated Fall Detection Algorithm With Global Trigger Tool, Incident Reports, Manual Chart Review, and Patient-Reported Falls: Algorithm Development and Validation With a Retrospective Diagnostic Accuracy Study

Dolci¹,

Schärer²,

Grossmann³

et al. 2020

J Med Internet Res

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Background Falls are common adverse events in hospitals, frequently leading to additional health costs due to prolonged stays and extra care. Therefore, reliable fall detection is vital to develop and test fall prevention strategies. However, conventional methods—voluntary incident reports and manual chart reviews—are error-prone and time consuming, respectively. Using a search algorithm to examine patients’ electronic health record data and flag fall indicators offers an inexpensive, sensitive, cost-effective alternative. Objective This study’s purpose was to develop a fall detection algorithm for use with electronic health record data, then to evaluate it alongside the Global Trigger Tool, incident reports, a manual chart review, and patient-reported falls. Methods Conducted on 2 campuses of a large hospital system in Switzerland, this retrospective diagnostic accuracy study consisted of 2 substudies: the first, targeting 240 patients, for algorithm development and the second, targeting 298 patients, for validation. In the development study, we compared the new algorithm’s in-hospital fall rates with those indicated by the Global Trigger Tool and incident reports; in the validation study, we compared the algorithm’s in-hospital fall rates with those from patient-reported falls and manual chart review. We compared the various methods by calculating sensitivity, specificity, and predictive values. Results Twenty in-hospital falls were discovered in the development study sample. Of these, the algorithm detected 19 (sensitivity 95%), the Global Trigger Tool detected 18 (90%), and incident reports detected 14 (67%). Of the 15 falls found in the validation sample, the algorithm identified all 15 (100%), the manual chart review identified 14 (93%), and the patient-reported fall measure identified 5 (33%). Owing to relatively high numbers of false positives based on falls present on admission, the algorithm’s positive predictive values were 50% (development sample) and 47% (validation sample). Instead of requiring 10 minutes per case for a full manual review or 20 minutes to apply the Global Trigger Tool, the algorithm requires only a few seconds, after which only the positive results (roughly 11% of the full case number) require review. Conclusions The newly developed electronic health record algorithm demonstrated very high sensitivity for fall detection. Applied in near real time, the algorithm can record in-hospital falls events effectively and help to develop and test fall prevention measures.

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“…Since then, the actual amount of avoidable patient harm has been controversially discussed [ 17 ], [ 18 ], [ 19 ], [ 20 ], [ 21 ], [ 22 ], [ 23 ], [ 24 ], [ 25 ], [ 26 ], [ 27 ], [ 28 ], [ 29 ], [ 30 ], [ 31 ], [ 32 ]. However, a current review about the results of all studies that have been conducted based on retrospective file analyses revealed that avoidable harm occurs in at least 5% of all hospital stays ([ 33 ], here figure 2). Furthermore, a current systematic review mentions an average of 2-3 critical events per 100 outpatient medical consultations and/or patient files of the included studies.…”

Section: Introductionmentioning

confidence: 99%

Concept and contents of a voluntary course for medical students' achievement of a basic qualification in patient safety during the practical year of medical studies

Opitz

Heinis

Jerrentrup

2019

GMS Journal for Medical Education; 36(2):Doc20

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Adverse events related to hospital care: a retrospective medical records review in a Swiss hospital

Abstract: The incidence of preventable AE in patients hospitalized in one Swiss hospital is comparable to previously reported rates. Further, patient safety improvement is needed, especially among older patients, and for surgical procedures.

Cited by 45 publications

References 28 publications

Prevalence, severity, and nature of preventable patient harm across medical care settings: systematic review and meta-analysis

Prevalence, severity, and nature of preventable patient harm across medical care settings: systematic review and meta-analysis

Automated Fall Detection Algorithm With Global Trigger Tool, Incident Reports, Manual Chart Review, and Patient-Reported Falls: Algorithm Development and Validation With a Retrospective Diagnostic Accuracy Study

Concept and contents of a voluntary course for medical students' achievement of a basic qualification in patient safety during the practical year of medical studies

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