Dataset Information

Validity and reliability of a medical record review method identifying transitional patient safety incidents in merged primary and secondary care patients' records.

ABSTRACT:

Objective

Inadequate information transfer during transitions in healthcare is a major patient safety issue. Aim of this study was to pilot a review of medical records to identify transitional safety incidents (TSIs) for use in a large intervention study and assess its reliability and validity.

Design

A retrospective medical record review study.

Settings and participants

Combined primary and secondary care medical records of 301 patients who had visited their general practitioner and the University Medical Center Utrecht, the Netherlands, in 2013 were randomly selected. Six trained reviewers assessed these medical records for presence of TSIs.

Outcomes

To assess inter-rater reliability, 10% of medical records were independently reviewed twice. To assess validity, the identified TSIs were compared with a reference standard of three objectively identifiable TSIs.

Results

The reviewers identified TSIs in 52 (17.3%) of all transitional medical records. Variation between reviewers was high (range: 3-28 per 50 medical records). Positive agreement for finding a TSI between reviewers was 0%, negative agreement 80% and the Cohen's kappa -0.15. The reviewers identified 43 (22%) of 194 objectively identifiable TSIs.

Conclusion

The reliability of our measurement tool for identifying TSIs in transitional medical record performed by clinicians was low. Although the TSIs that were identified by clinicians were valid, they missed 80% of them. Restructuring the record review procedure is necessary.

SUBMITTER: van Melle MA

PROVIDER: S-EPMC6091899 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Publications

Validity and reliability of a medical record review method identifying transitional patient safety incidents in merged primary and secondary care patients' records.

van Melle Marije A MA Zwart Dorien L M DLM Poldervaart Judith M JM Verkerk Otto Jan OJ Langelaan Maaike M van Stel Henk F HF de Wit Niek J NJ

BMJ open 20180813 8

<h4>Objective</h4>Inadequate information transfer during transitions in healthcare is a major patient safety issue. Aim of this study was to pilot a review of medical records to identify transitional safety incidents (TSIs) for use in a large intervention study and assess its reliability and validity.<h4>Design</h4>A retrospective medical record review study.<h4>Settings and participants</h4>Combined primary and secondary care medical records of 301 patients who had visited their general practit ...[more]

PMID: 30104308

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Project description:BackgroundIt is unlikely that applications of artificial intelligence (AI) will completely replace physicians. However, it is very likely that AI applications will acquire many of their roles and generate new tasks in medical care. To be ready for new roles and tasks, medical students and physicians will need to understand the fundamentals of AI and data science, mathematical concepts, and related ethical and medico-legal issues in addition with the standard medical principles. Nevertheless, there is no valid and reliable instrument available in the literature to measure medical AI readiness. In this study, we have described the development of a valid and reliable psychometric measurement tool for the assessment of the perceived readiness of medical students on AI technologies and its applications in medicine.MethodsTo define medical students' required competencies on AI, a diverse set of experts' opinions were obtained by a qualitative method and were used as a theoretical framework, while creating the item pool of the scale. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were applied.ResultsA total of 568 medical students during the EFA phase and 329 medical students during the CFA phase, enrolled in two different public universities in Turkey participated in this study. The initial 27-items finalized with a 22-items scale in a four-factor structure (cognition, ability, vision, and ethics), which explains 50.9% cumulative variance that resulted from the EFA. Cronbach's alpha reliability coefficient was 0.87. CFA indicated appropriate fit of the four-factor model (χ2/df = 3.81, RMSEA = 0.094, SRMR = 0.057, CFI = 0.938, and NNFI (TLI) = 0.928). These values showed that the four-factor model has construct validity.ConclusionsThe newly developed Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS) was found to be valid and reliable tool for evaluation and monitoring of perceived readiness levels of medical students on AI technologies and applications. Medical schools may follow 'a physician training perspective that is compatible with AI in medicine' to their curricula by using MAIRS-MS. This scale could be benefitted by medical and health science education institutions as a valuable curriculum development tool with its learner needs assessment and participants' end-course perceived readiness opportunities.

Dataset Information

Validity and reliability of a medical record review method identifying transitional patient safety incidents in merged primary and secondary care patients' records.

Objective

Design

Settings and participants

Outcomes

Results

Conclusion

Publications

Validity and reliability of a medical record review method identifying transitional patient safety incidents in merged primary and secondary care patients' records.

Similar Datasets

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