OBJECTIVE: To assess whether the Belgian Hospital Discharge Dataset (B-HDDS) is a valid source for the detection of adverse events in acute hospitals. DESIGN, SETTING AND PARTICIPANTS: Retrospective review of 1515 patient records in eight acute Belgian hospitals for the year 2005. MAIN OUTCOME MEASURES: Predictive value of the B-HDDS and medical record reviews and degree of correspondence between the B-HDDS and medical record reviews for five indicators: pressure ulcer, postoperative pulmonary embolism or deep vein thrombosis, postoperative sepsis, ventilator-associated pneumonia and postoperative wound infection. RESULTS: Postoperative wound infection received the highest positive predictive value (62.3%), whereas postoperative sepsis and ventilator-associated pneumonia were rated as only 44.2% and 29.9% respectively. Excluding present on admission from the screening substantially decreased the positive predictive value of pressure ulcer from 74.5% to 54.3%, as pressure ulcers present on admission were responsible for more B-HDDS-medical record mismatches than any other indicator. Over half (56.8%) of false-positive cases for postoperative sepsis were due to a lack of specificity of the ICD-9-CM code, whereas in 58.6% of false-positive cases for ventilator-associated pneumonia, clinical criteria appeared to be too stringent. CONCLUSIONS: The B-HDDS has the potential to accurately detect some but not all adverse events. Adding a code 'present on admission' and improving the ICD-9-CM codes might already partially improve the correspondence between the B-HDDS and the medical record review.
OBJECTIVE: To assess whether the Belgian Hospital Discharge Dataset (B-HDDS) is a valid source for the detection of adverse events in acute hospitals. DESIGN, SETTING AND PARTICIPANTS: Retrospective review of 1515 patient records in eight acute Belgian hospitals for the year 2005. MAIN OUTCOME MEASURES: Predictive value of the B-HDDS and medical record reviews and degree of correspondence between the B-HDDS and medical record reviews for five indicators: pressure ulcer, postoperative pulmonary embolism or deep vein thrombosis, postoperative sepsis, ventilator-associated pneumonia and postoperative wound infection. RESULTS: Postoperative wound infection received the highest positive predictive value (62.3%), whereas postoperative sepsis and ventilator-associated pneumonia were rated as only 44.2% and 29.9% respectively. Excluding present on admission from the screening substantially decreased the positive predictive value of pressure ulcer from 74.5% to 54.3%, as pressure ulcers present on admission were responsible for more B-HDDS-medical record mismatches than any other indicator. Over half (56.8%) of false-positive cases for postoperative sepsis were due to a lack of specificity of the ICD-9-CM code, whereas in 58.6% of false-positive cases for ventilator-associated pneumonia, clinical criteria appeared to be too stringent. CONCLUSIONS: The B-HDDS has the potential to accurately detect some but not all adverse events. Adding a code 'present on admission' and improving the ICD-9-CM codes might already partially improve the correspondence between the B-HDDS and the medical record review.
Authors: Maaike S M van Mourik; Pleun Joppe van Duijn; Karel G M Moons; Marc J M Bonten; Grace M Lee Journal: BMJ Open Date: 2015-08-27 Impact factor: 2.692
Authors: Stephanie A Woo; Amber Cragg; Maeve E Wickham; David Peddie; Ellen Balka; Frank Scheuermeyer; Diane Villanyi; Corinne M Hohl Journal: BMC Med Res Methodol Date: 2018-12-04 Impact factor: 4.615
Authors: Corinne M Hohl; Lisa Kuramoto; Eugenia Yu; Basia Rogula; Jürgen Stausberg; Boris Sobolev Journal: BMC Health Serv Res Date: 2013-11-12 Impact factor: 2.655