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| Name | Class |
|---|---|
| Beijing No.6 Hospital | UNKNOWN |
| Beijing Longfu Hospital | UNKNOWN |
| Beijing Puren Hospital | UNKNOWN |
| Beijing Hepingli Hospital |
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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.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Not applicable- observational study | Other | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Adverse event incidence | The proportion of admissions with at least one adverse event. | During the index admission, including review of relevant prior hospitalization records and all available records through 30 days after discharge. |
| Measure | Description | Time Frame |
|---|---|---|
| Types of adverse event | 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. |
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Inclusion Criteria:
Exclusion Criteria:
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The study population consisted of inpatient admissions to 5 participating public general hospitals in Beijing, China, during 2024. Eligible admissions were identified according to predefined inclusion and exclusion criteria. Stratified random sampling was used, with sample sizes allocated in proportion to hospital admission volumes. Within each site, eligible admissions were randomly selected with equal selection probabilities. The final study sample included 2,843 admissions.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College | Beijing | Beijing Municipality | 100730 | China |
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| UNKNOWN |
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| 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. | 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). | 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). | 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). | 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). | After completion of AE screening, adjudication, and re-review of randomly sampled screen-negative admissions |