The goal of this observational study is to learn about the incidence and characteristics of adverse events (AEs) among hospitalized patients in China and to compare 4 commonly used methods for detecting these events. The main questions it aims to answer are: How common are AEs among hospitalized patients, and what are their characteristics (types, severity, and preventability) in China? How do 4 commonly used methods, including the Harvard Medical Practice Study (HMPS), Global Trigger Tool (GTT), Patient Safety Indicators (PSIs), and incident reporting systems (IRSs), compare in detecting AEs? Researchers review randomly selected medical records from 5 hospitals in China to identify AEs, assess their type, severity, and preventability, and evaluate the performance of the 4 detection methods.
Study Type
OBSERVATIONAL
Enrollment
2,807
This is a retrospective cross-sectional study based on medical record review. The study assesses AE incidence and characteristics and compares AE detection methods, with no intervention administered to participants.
Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College
Beijing, Beijing Municipality, China
Adverse event incidence
The proportion of admissions with at least one adverse event.
Time frame: During the index admission, including review of relevant prior hospitalization records and all available records through 30 days after discharge.
Types of adverse event
Time frame: During the index admission, including review of relevant prior hospitalization records and all available records through 30 days after discharge
Preventability of adverse event
Adverse event with 6-point Likert scale scores ≥4 were considered preventable.
Time frame: During the index admission, including review of relevant prior hospitalization records and all available records through 30 days after discharge
Severity of adverse events
Severity was graded using the National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) classification.
Time frame: During the index admission, including review of relevant prior hospitalization records and all available records through 30 days after discharge
Sensitivity of adverse event detection methods
Admission-level sensitivity was calculated for the Harvard Medical Practice Study (HMPS), Global Trigger Tool (GTT), Patient Safety Indicators (PSIs), and incident reporting systems (IRSs).
Time frame: After completion of AE screening, adjudication, and re-review of randomly sampled screen-negative admissions
Specificity of adverse event detection methods
Admission-level specificity was calculated for the Harvard Medical Practice Study (HMPS), Global Trigger Tool (GTT), Patient Safety Indicators (PSIs), and incident reporting systems (IRSs).
Time frame: After completion of AE screening, adjudication, and re-review of randomly sampled screen-negative admissions
Positive predictive value (PPV) of adverse event detection methods
Admission-level positive predictive value (PPV) was calculated for the Harvard Medical Practice Study (HMPS), Global Trigger Tool (GTT), Patient Safety Indicators (PSIs), and incident reporting systems (IRSs).
Time frame: After completion of AE screening, adjudication, and re-review of randomly sampled screen-negative admissions
Negative predictive value (NPV) of adverse event detection methods
Admission-level negative predictive value (NPV) was calculated for the Harvard Medical Practice Study (HMPS), Global Trigger Tool (GTT), Patient Safety Indicators (PSIs), and incident reporting systems (IRSs).
Time frame: After completion of AE screening, adjudication, and re-review of randomly sampled screen-negative admissions
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