A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals
| Autor: | Erin M. Kirley, Bradford D. Winters, John H.M. Austin, Michael A. Rosen |
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| Rok vydání: | 2018 |
| Předmět: |
Adult
Male Safety Management medicine.medical_specialty Computer science media_common.quotation_subject Documentation Patient Harm 03 medical and health sciences Patient safety 0302 clinical medicine Hospital Administration United States Agency for Healthcare Research and Quality Chart International Classification of Diseases Acute care Health care medicine Humans Quality (business) 030212 general & internal medicine Adverse effect Aged media_common Data collection Maryland Patient‐centered Care business.industry 030503 health policy & services Health Policy Middle Aged medicine.disease United States District of Columbia Female Patient Safety Medical emergency 0305 other medical science business Coding (social sciences) |
| Zdroj: | Health Serv Res |
| ISSN: | 1475-6773 0017-9124 |
| DOI: | 10.1111/1475-6773.13090 |
| Popis: | Objective To compare the Agency for Healthcare Research and Quality's Quality and Safety Review System (QSRS) and the proposed triadic structure for the 11th version of the International Classification of Disease (ICD-11) in their ability to capture adverse events in U.S. hospitals. Data sources/study setting One thousand patient admissions between 2014 and 2016 from three general, acute care hospitals located in Maryland and Washington D.C. Study design The admissions chosen for the study were a random sample from all three hospitals. Data collection/extraction methods All 1000 admissions were abstracted through QSRS by one set of Certified Coding Specialists and a different set of coders assigned the draft ICD-11 codes. Previously assigned ICD-10-CM codes for 230 of the admissions were also used. Principal findings We found less than 20 percent agreement between QSRS and ICD-11 in identifying the same adverse event. The likelihood of a mismatch between QSRS and ICD-11 was almost twice that of a match. The findings were similar to the agreement found between QSRS and ICD-10-CM in identifying the same adverse event. When coders were provided with a list of potential adverse events, the sensitivity and negative predictive value of ICD-11 improved. Conclusions While ICD-11 may offer an efficient way of identifying adverse events, our analysis found that in its draft form, it has a limited ability to capture the same types of events as QSRS. Coders may require additional training on identifying adverse events in the chart if ICD-11 is going to prove its maximum benefit. |
| Databáze: | OpenAIRE |
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