Identifying Adverse Events Using International Classification of Diseases, Tenth Revision Y Codes in Korea: A Cross-sectional Study

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.

Development of the Korean Patient Safety Incidents Code Classification System

OBJECTIVES

Attempts to understand patient safety using administrative data in Korea have been rare. This study develops a Korean patient safety incident code classification system and identifies its characteristics to boost diagnosis code usage for assessing patient safety.

METHODS

Based on existing literature, we selected Korean Standard Classification of Diseases 7 codes for characterizing patient safety incidents using diagnosis codes. We conducted 2 rounds of review to evaluate the codes applicability to different patient safety incidents using the Delphi method. The verified diagnosis codes were then classified by incident type.

RESULTS

Of the 54,259 Korean Standard Classification of Diseases 7 codes, 4509 were applicable for Korean patients, which were divided into 2435 code groups and 2074 candidate groups. The codes were classified into 6 categories (diagnosis, medication, patient care, operation or procedure, infection related, and other) and then further classified into 35 subcategories. The major categories of patient safety incidents, in the order of frequency, involved medication, fluid and blood related (1719, 38.1%), operation and procedure related (1339, 29.7%), and patient care related (991, 22.0%). Meanwhile, there were only 2 codes related to diagnosis.

CONCLUSIONS

Our study provides a basis for estimating patient safety incidents using diagnosis codes. We suggest that gradually increasing the utilization and accuracy of the patient safety incident codes will help develop effective patient safety indicators in Korea similar to other countries. Moreover, clinicians are also needed to be aware of using the developed code classification system.

Evaluation of Factors Associated with Adverse Drug Events in South Korea Using a Population-Based Database

This retrospective study aims to investigate the factors associated with the occurrence of ADEs using nationally representative claims data. All patients with at least one claim with diagnosis codes denoting potential ADE between 1 July 2015 and 31 December 2015 were included. Potential ADE was defined as ADE identified in the claims data, because it was not verified. The index date was defined as the date of the first claim with potential ADEs. Demographic data were collected at the index date, while data on comorbidities and number of medications used were collected six months before the index date. Multivariate logistic regression was used to explore the association between potential ADEs and several factors, including sex, age group, insurance type, comorbidities, and number of prescribed medications. Patients with potential ADEs were older, had more chronic diseases, and used more medications than those without potential ADEs. In the multivariate analysis, occurrence of potential ADEs was associated with age (≥65 years, odds ratio [OR] 1.15, 95% confidence interval [CI] 1.08–1.21), Medical Aid program (OR 1.37, 95% CI 1.27–1.47), Charlson Comorbidity Index scores (≥5, OR 2.87, 95% CI 2.56–3.20), and use of six or more medications (6–10 medications, OR 1.89, 95% CI 1.79–1.99). Age, Medical Aid program, comorbidities, and number of medications were associated with occurrence of potential ADEs.

The Korea National Patient Safety Incidents Inquiry Survey: Characteristics of Adverse Events Identified Through Medical Records Review in Regional Public Hospitals

OBJECTIVES

In 2019, the Korean National Patient Safety Incidents Inquiry was conducted in the Republic of Korea to identify the national-level incidence of adverse events. This study determined the incidence and detailed the characteristics of adverse events at 15 regional public hospitals in the Republic of Korea.

METHODS

Medical records data of 500 randomly selected patients (discharged in 2016) were extracted from each of the 15 studied hospitals and reviewed in 3 stages. First, for each hospital, 2 nurses independently reviewed the medical records, using 41 screening criteria. Second, 2 physicians independently reviewed the records of those patients with at least 1 screening criterion from the first stage for adverse events occurrence and their characteristics. Third, a 9-member committee conducted a final review and compiled the final adverse event report.

RESULTS

Among 7500 patients, 4159 (55.5%) had at least 1 screening criterion; 745 (9.9%) experienced 901 adverse events (incidence, 12.0%). By type of institution, adverse event incidence varied widely from 1.2% to 45.6%. In 1032 adverse events, the majority (33.5%) were "patient care-related." By severity, the majority (638; 70.8%) were temporary, requiring intervention, whereas 38 (4.2%) resulted in death. The preventability score was high for "patient care-related" and "diagnosis-related" adverse events. Duration of hospitalization was extended for 463 (44.9%) adverse events, with "diagnosis-related" (30.8%) and "surgery/procedural-related" (30.1%) types extended by at least 21 days.

CONCLUSIONS

A review of medical records aids in identifying adverse events in medical institutions with varying characteristics, thus helping prioritize interventions to reduce their incidence.

Feasibility of Capturing Adverse Events From Insurance Claims Data Using International Classification of Diseases, Tenth Revision, Codes Coupled to Present on Admission Indicators

OBJECTIVE

The aim of the study was to investigate the feasibility of using administrative data to screen adverse events in Korea.

METHODS

We used a diagnosis-related groups claims data set and the information of the checklist of healthcare quality improvement (a part of the value incentive program) to verify adverse events in fiscal year 2018. Adverse events were identified using patient safety indicator (PSI) clusters and a present on admission indicator (POA). The PSIs consisted of 19 clusters representing subcategories of adverse events, such as hospital-acquired infection. Among the adverse events identified using PSI clusters, "POA = N," which means not present at the time of admission, was only deemed as the case in the final stage. We compared the agreement on the occurrence of adverse events from claims data with a reference standard data set (i.e., checklist of healthcare quality improvement) and presented them by PSI cluster and institution.

RESULTS

The cases of global PSI for any adverse event numbered 27,320 (2.32%) among all diagnostic codes in 2018. In terms of institutional distribution, considerable variation was observed throughout the clusters. For example, only 13.2% of institutions (n = 387) reported any global PSI for any adverse event throughout the whole year. The agreement between the reference standard and the claims data was poor, in the range of 2.2% to 10.8%, in 3 types of adverse events. The current claims data system (i.e., diagnostic codes coupled to POA indicators) failed to capture a large majority of adverse events identified using the reference standard.

CONCLUSIONS

Our results imply that the coding status of International Classification of Diseases, Tenth Revision, codes and POA indicators should be refined before using them as quality indicators.

Use of a hospital administrative database to identify and characterize community-acquired, hospital-acquired and drug-induced acute kidney injury

BACKGROUND

Acute kidney injury (AKI) has serious short- and long-term consequences. The objective of the present study of a cohort of hospitalized patients with AKI was to (i) evaluate the proportion of patients with hospital-acquired (HA) AKI and community-acquired (CA) AKI, the characteristics of these patients and the AKIs, and the short-term outcomes, and (ii) determine the performance of several ICD-10 codes for identifying AKI (both CA and HA) and drug-induced AKI.

METHODS

A cohort of hospitalized patients with AKI was constituted by screening hospital's electronic medical records (EMRs) for cases of AKI. We distinguished between and compared CA-AKI and HA-AKI and evaluated the proportion of AKIs that were drug-induced. The EMR data were merged with hospital billing codes (according to the International Classification of Diseases, 10th Edition (ICD-10)) for each hospital stay. The ability of ICD-10 codes to identify AKIs (depending on the type of injury) was determined by calculating the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Lastly, we sought to validate specific ICD-10 codes for drug-induced AKI.

RESULTS

Of the 2473 patients included, 1557 experienced an AKI (HA-AKI: 59.3%; CA-AKI: 40.7%). Patients with CA-AKI had a better short-term outcome and a lower death rate (7.6%, vs. 20% for HA-AKI). One AKI in three was drug-induced. The combination of AKI codes had a very high specificity (94.8%), a high PPV (94.9%), a moderate NPV (56.7%) and moderate sensitivity (57.4%). The sensitivity was higher for CA-AKI (72.2%, vs. 47.2% for HA-AKI), for more severe AKI (82.8% for grade 3 AKI vs. 43.7% for grade 1 AKI), and for patients with CKD. Use of a specific ICD-10 code for drug-induced AKI (N14x) alone gave a very low sensitivity (1.8%), whereas combining codes for adverse drug reactions with AKI-specific codes increased the sensitivity.

CONCLUSION

Our results show that the combination of an EMR-based analysis with ICD-10-based hospital billing codes gives a comprehensive "real-life" picture of AKI in hospital settings. We expect that this approach will enable researchers to study AKI in more depth.

Use of ICD-10-CM T codes in hospital claims data to identify adverse drug events in Taiwan

WHAT IS KNOWN AND OBJECTIVE

Adverse drug events (ADEs) are a major public health concern worldwide and may prolong hospital stays, causing a burden on the healthcare system and increasing the associated costs. Therefore, optimizing medication use and reducing ADEs are priorities for public health. Medication safety can be monitored and improved by identifying ADEs. The utilization of diagnoses coded according to the International Statistical Classification of Diseases and Related Health Problems (ICD) system for the identification of ADEs has been firmly established. In Taiwan, however, the validity of recording ADEs on the basis of inpatient ICD-10-CM T codes has not been evaluated. Therefore, this study investigated the potential usefulness of ICD-10-CM T codes in routine hospital data for the identification of ADEs and for increasing the rate of reporting.

METHODS

We use hospital claims data of hospitalized patients from one medical centre in northern Taiwan between 1 July 2016 and 30 June 2018. We defined an ADE to have taken place if an ICD-10-CM T code was present among the primary or secondary diagnosis codes. The inpatients who were discharged with T codes in a primary or secondary diagnosis were identified by the computerized T code information platform, and the retrospective review of the medical charts was performed by pharmacists to confirm the ADEs.

RESULTS AND DISCUSSION

1384 inpatients who were discharged with the relevant T codes in a primary or secondary diagnosis were identified during the study period. Code T36 (poisoning by, adverse effect of or underdosing of systemic antibiotics) was the most common code, accounting for 56.6%, followed by T42 (17.7%; poisoning by, adverse effect of or underdosing of antiepileptic, sedative-hypnotic or antiparkinsonism drug). Overall, 789 clinically significant ADEs were identified after medical chart review. The dermatologic system was the most commonly involved. The overall positive predictive value for a flagged code representing an ADE was 57%. Furthermore, the use of T codes to confirm the number of ADE cases increased the ADE reporting rate by 9.17%.

WHAT IS NEW AND CONCLUSION

The PPV of ICD-10-CM T codes analysed in our study was insufficient for identifying ADEs during hospitalization. The sensitivity and specificity of this were inadequate. However, the T code system can be used as an auxiliary resource for pharmacists to identify potential ADEs and report the information as prompts on the physician order entry system. When a physician prescribes a drug that may cause an ADE in a patient, an alert is issued to ensure medication safety. In conclusion, the T codes did not perform well in our study and caution should be exercised in their use to identify ADEs on their own.

Variation between hospitals and reviewers in detection of adverse events identified through medical record review in Korea

OBJECTIVES

This study utilized the method of medical record review to determine characteristics of adverse events that occurred in the inpatient units of hospitals in Korea as well as the variations in adverse events between institutions.

DESIGN

A two-stage retrospective medical record review was conducted. The first stage was a nurse review, where two nurses reviewed medical records of discharged patients to determine if screening criteria had been met. In the second stage, two physicians independently reviewed medical records of patients identified in the first stage, to determine whether an adverse event had occurred.

SETTING

Inpatient units of six hospitals.

PARTICIPANTS

Medical records of 2 596 patients randomly selected were reviewed in the first stage review.

INTERVENTION(S)

N/A.

MAIN OUTCOME MEASURE(S)

Adverse events.

RESULTS

A total of 277 patients (10.7%) were confirmed to have had one or more adverse event(s), and a total of 336 adverse events were identified. Physician reviewers agreed about whether an adverse event had occurred for 141 patients (5.4%). The incidence rate of adverse events was at least 1.3% and a maximum of 19.4% for each hospital. Most preventability scores were less than four points (non-preventable), and there were large variations between reviewers and institutions.

CONCLUSIONS

Given the level of variation in the identified adverse events, further studies that include more medical institutions in their investigations are needed, and a third-party committee should be involved to address the reliability issues regarding the occurrence and characteristics of the adverse events.