Development of the Korean Patient Safety Incidents Code Classification System

Estimating the Effect of Disclosure of Patient Safety Incidents in Diagnosis-Related Patient Safety Incidents: A Cross-sectional Study Using Hypothetical Cases

BACKGROUND

Disclosure of patient safety incidents (DPSIs) is a strategic measure to reduce the problems of patient safety incidents (PSIs). However, there are currently limited studies on the effects of DPSIs on resolving diagnosis-related PSIs. Therefore, this study aimed to estimate the effects of DPSIs using hypothetical cases, particularly in diagnosis-related PSIs.

METHODS

A survey using 2 hypothetical cases of diagnosis-related PSIs was conducted in 5 districts of Ulsan Metropolitan City, Korea, from March 18 to 21, 2021. The survey used a multistage stratified quota sampling method to recruit participants. Multiple logistic regression and linear regression analyses were performed to determine the effectiveness of DPSIs in hypothetical cases. The outcomes were the judgment of a situation as a medical error, willingness to revisit and recommend the hypothetical physician, intention to file a medical lawsuit and commence criminal proceedings against the physicians, trust score of the involved physicians, and expected amount of compensation.

RESULTS

In total, 620 respondents, recruited based on age, sex, and region, completed the survey. The mean age was 47.6 (standard deviation, ±15.1) years. Multiple logistic regression showed that DPSIs significantly decreased the judgment of a situation as a medical error (odds ratio [OR], 0.44; 95% confidence interval [CI], 0.24-0.79), intention to file a lawsuit (OR, 0.53; 95% CI, 0.42-0.66), and commence criminal proceedings (OR, 0.43; 95% CI, 0.34-0.55). It also increased the willingness to revisit (OR, 3.28; 95% CI, 2.37-4.55) and recommend the physician (OR, 8.21; 95% CI, 4.05-16.66). Meanwhile, the multiple linear regression demonstrated that DPSIs had a significantly positive association with the trust score of the physician (unstandardized coefficient, 1.22; 95% CI, 1.03-1.41) and a significantly negative association with the expected amount of compensation (unstandardized coefficient, -0.18; 95% CI, -0.29 to -0.06).

CONCLUSIONS

DPSIs reduces the possibility of judging the hypothetical case as a medical error, increases the willingness to revisit and recommend the physician involved in the case, and decreases the intent to file a lawsuit and commence a criminal proceeding. Although this study implemented hypothetical cases, the results are expected to serve as empirical evidence to apply DPSIs extensively in the clinical field.

Taxonomy development methods regarding patient safety in health sciences - A systematic review

BACKGROUND

Taxonomies are needed for automated analysis of clinical data in healthcare. Few reviews of the taxonomy development methods used in health sciences are found. This systematic review aimed to describe the scope of the available taxonomies relative to patient safety, the methods used for taxonomy development, and the strengths and limitations of the methods. The purpose of this systematic review is to guide future taxonomy development projects.

METHODS

The CINAHL, PubMed, Scopus, and Web of Science databases were searched for studies from January 2012 to April 25, 2023. Two authors selected the studies using inclusion and exclusion criteria and critical appraisal checklists. The data were analysed inductively, and the results were reported narratively.

RESULTS

The studies (n = 13) across healthcare concerned mainly taxonomies of adverse events and medication safety but little for specialised fields and information technology. Critical appraisal indicated inadequate reporting of the used taxonomy development methods. Ten phases of taxonomy development were identified: (1) defining purpose and (2) the theory base for development, (3) relevant data sources' identification, (4) main terms' identification and definitions, (5) items' coding and pooling, (6) reliability and validity evaluation of coding and/or codes, (7) development of a hierarchical structure, (8) testing the structure, (9) piloting the taxonomy and (10) reporting application and validation of the final taxonomy. Seventeen statistical tests and seven software systems were utilised, but automated data extraction methods were used rarely. Multimethod and multi-stakeholder approach, code- and hierarchy testing and piloting were strengths and time consumption and small samples in testing limitations.

CONCLUSION

New taxonomies are needed on diverse specialities and information technology related to patient safety. Structured method is needed for taxonomy development, reporting and appraisal to strengthen taxonomies' quality. A new guide was proposed for taxonomy development, for which testing is required. Prospero registration number CRD42023411022.

Accuracy assessment of patient safety incident (PSI) codes and present-on-admission (POA) indicators: a cross-sectional analysis using the Patient Safety Incidents Inquiry (PSII) in Korea

BACKGROUND

Among the various methods used, administrative data collected for claims and billing purposes, such as diagnosis codes and present-on-admission (POA) indicators, can easily be employed to assess patient safety status. However, it is crucial that administrative data be accurate to generate valid estimates of adverse event (AE) occurrence. Thus, we aimed to evaluate the accuracy of diagnosis codes and POA indicators in patients with confirmed AEs in the hospital admission setting.

METHODS

We analysed the diagnosis codes of 1,032 confirmed AE cases and 6,754 non-AE cases from the 2019 Patient Safety Incidents Inquiry, which was designed as a cross-sectional study, to determine their alignment with the Korean Patient Safety Incidents (PSIs) Code Classification System. The unit of analysis was the individual case rather than the patient, because two or more AEs may occur in one patient. We examined whether the primary and secondary diagnostic codes had PSIs codes matching the AE type and checked each PSI code for whether the POA indicator had an 'N' tag. We reviewed the presence of PSI codes in patients without identified AEs and calculated the correlation between the AE incidence rate and PSI code and POA indicator accuracy across 15 hospitals.

RESULTS

Ninety (8.7%) of the AE cases had PSI codes with an 'N' tag on the POA indicator compared to 294 (4.4%) of the non-AE cases. Infection- (20.4%) and surgery/procedure-related AEs (13.6%) had relatively higher instances of correctly tagged PSI codes. We did not identify any PSI codes for diagnosis-related incidents. While we noted significant differences in AE incidence rates, PSI code accuracy, and POA indicator accuracy among the hospitals, the correlations between these variables were not statistically significant.

CONCLUSION

Currently, PSI codes and POA indicators in South Korea appear to have low validity. To use administrative data in medical quality improvement activities such as monitoring patient safety levels, improving the accuracy of administrative data should be a priority. Possible strategies include targeted education on PSI codes and POA indicators and introduction of new evaluation indicators regarding the accuracy of administrative data.