Quality improvement methodology can reduce hospitalisation for abscess management

BackgroundAbscesses are a common reason for ED visits. While many are drained in the ED, some require drainage in the operating room (OR). We observed that a higher percentage of patients at our institution in Columbus, Ohio, were admitted to the hospital with abscesses for incision and drainage (I&D) in the OR than other institutions, including paediatric institutions. Our aim was to decrease hospitalisations for abscess management.MethodsA multidisciplinary team convened to decrease hospitalisation for patients with abscesses and completed multiple ‘Plan-Do-Study-Act’ cycles, including increasing I&Ds performed in the ED. Other interventions included implementation of a clinical pathway, training of procedure technicians (PT), updating the electronic medical record (EMR), credentialing advanced practice nurses in sedation and individual follow-up with providers for admitted patients. Data were analysed using statistical process control charts. Gross average charges were assessed.ResultsAdmissions for I&D decreased from 26.3% to 13.7%. Abscess drainage in the ED improved from 79.3% to 96.5%. Mean length of stay decreased from 19.5 to 11.5 hours for all patients. Patients sedated increased from 3.3% to 18.2%. The number of repeat I&Ds within 30 days decreased from 4.3% to 1.7%.ConclusionWe decreased hospitalisations for abscess I&D by using quality improvement methodology. The most influential intervention was an initiative to increase I&Ds performed in the ED. Additional interventions included expanded training of PTs, implementation of a clinical pathway, updating the EMR, improving interdepartmental communication and increasing sedation providers.

Deviation Detection in Clinical Pathways Based on Business Alignment

Several unexpected behaviors may occur during actual treatment of clinical pathways, which will have negative impact on the implementation and the future work. To increase the performance of current deviation detection algorithms, a method is presented according to business alignment, which can effectively detect the anomaly in the implementation of the clinical pathways, provide judgment basis for the intervention in the process of the clinical pathway implementation, and play a crucial role in improving the clinical pathways. Firstly, the noise in diagnosis and treatment logs of clinical pathways will be removed. Then, the synchronous composition model is constructed to embody the deviations between the actual process and the theoretical model. Finally, A ∗ algorithm is selected to search for optimal alignment. A clinical pathway for ST-Elevation Myocardial Infarction (STEMI) under COVID-19 is used as a case study, and the superiority and effectiveness of this method in deviation detection are illustrated in the result of experiments.