OBJECTIVES: To use an automated Classification of Hospital Acquired Diagnoses (CHADx) reporting system to report the incidence of hospital-acquired complications in inpatients and investigate the association between hospital-acquired complications and hospital length of stay (LOS) in multiday-stay patients. DESIGN: Retrospective cross-sectional study for calendar years 2010 and 2011. SETTING: South Metropolitan Health Service in Western Australia, which consists of two teaching and three non-teaching hospitals. MAIN OUTCOME MEASURES: Incidence of hospital-acquired complications and mean LOS for multiday-stay patients. RESULTS: Of 436 841 inpatient separations, 29 172 (6.68%) had at least one hospital-acquired complication code assigned in the administrative data, and there were a total of 56 326 complication codes. The three most common complications were postprocedural complications; cardiovascular complications; and labour, delivery and postpartum complications. In the subset of data on multiday-stay patients, crude mean LOS was longer in separations for patients with hospital-acquired complications than in separations for those without such complications (17.4 days v 5.4 days). After adjusting for potential confounders, separations for patients with hospital-acquired complications had almost four times the mean LOS of separations for those without such complications (incident rate ratio, 3.84; 95% CI, 3.73-3.96; P < 0.001). CONCLUSIONS: An automated CHADx reporting system can be used to collect data on patients with hospital-acquired complications. Such data can be used to increase emphasis on patient safety and quality of care and identify potential opportunities to reduce LOS.
OBJECTIVES: To use an automated Classification of Hospital Acquired Diagnoses (CHADx) reporting system to report the incidence of hospital-acquired complications in inpatients and investigate the association between hospital-acquired complications and hospital length of stay (LOS) in multiday-stay patients. DESIGN: Retrospective cross-sectional study for calendar years 2010 and 2011. SETTING: South Metropolitan Health Service in Western Australia, which consists of two teaching and three non-teaching hospitals. MAIN OUTCOME MEASURES: Incidence of hospital-acquired complications and mean LOS for multiday-stay patients. RESULTS: Of 436 841 inpatient separations, 29 172 (6.68%) had at least one hospital-acquired complication code assigned in the administrative data, and there were a total of 56 326 complication codes. The three most common complications were postprocedural complications; cardiovascular complications; and labour, delivery and postpartum complications. In the subset of data on multiday-stay patients, crude mean LOS was longer in separations for patients with hospital-acquired complications than in separations for those without such complications (17.4 days v 5.4 days). After adjusting for potential confounders, separations for patients with hospital-acquired complications had almost four times the mean LOS of separations for those without such complications (incident rate ratio, 3.84; 95% CI, 3.73-3.96; P < 0.001). CONCLUSIONS: An automated CHADx reporting system can be used to collect data on patients with hospital-acquired complications. Such data can be used to increase emphasis on patient safety and quality of care and identify potential opportunities to reduce LOS.
Authors: Andreas Sandø; Martin Schultz; Jesper Eugen-Olsen; Lars Simon Rasmussen; Lars Køber; Erik Kjøller; Birgitte Nybo Jensen; Lisbet Ravn; Theis Lange; Kasper Iversen Journal: Scand J Trauma Resusc Emerg Med Date: 2016-08-05 Impact factor: 2.953
Authors: Louis Lind Plesner; Anne Kristine Servais Iversen; Sandra Langkjær; Ture Lange Nielsen; Rebecca Østervig; Peder Emil Warming; Idrees Ahmad Salam; Michael Kristensen; Morten Schou; Jesper Eugen-Olsen; Jakob Lundager Forberg; Lars Køber; Lars S Rasmussen; György Sölétormos; Bente Klarlund Pedersen; Kasper Iversen Journal: Scand J Trauma Resusc Emerg Med Date: 2015-12-01 Impact factor: 2.953
Authors: José Pablo Suárez-Llanos; Néstor Benítez-Brito; Laura Vallejo-Torres; Irina Delgado-Brito; Adriá Rosat-Rodrigo; Carolina Hernández-Carballo; Yolanda Ramallo-Fariña; Francisca Pereyra-García-Castro; Juan Carlos-Romero; Nieves Felipe-Pérez; Jennifer García-Niebla; Eduardo Mauricio Calderón-Ledezma; Teresa de Jesús González-Melián; Ignacio Llorente-Gómez de Segura; Manuel Ángel Barrera-Gómez Journal: BMC Health Serv Res Date: 2017-04-20 Impact factor: 2.655