Introduction: Outcome research (OR) and clinical decision support systems (CDSS) are established mechanisms to assess and improve patient care. While the focus of OR is on the end results of medical care, CDSS is intended to guide the clinician through proven pathways of medical care utilizing patient characteristics and best evidence based practices. A reliable electronic medical record system (EMR) is essential for streamlined implementation of such mechanisms; however variation in compatibility of EMRs may lead to fragmentation of data necessary for implementation of algorithms.
Methods: A comprehensive application that assembles the most reliable sources of patient information was developed by a multidisciplinary team prospectively collecting information on all neurosurgical procedures consecutively. Information was stratified by the primary neurosurgical procedure performed: major- craniotomy, spinal, cerebrospinal fluid (CSF) diversion, peripheral nerve and other, and minor procedures . All procedures were assessed for outcome including hospital length of stay (LOS), infection, CSF leak, new neurological deficit, 30 and 90 day re-admission, re-operation within 30 and 90 days and survival.
Results: A total of 687 neurosurgical procedures were performed in 2012; 546 were major and 141 minor operations. Five of the most common procedures were selected for initial modeling: shunt placement or revision (n = 90), craniosynostosis repair (n = 62), craniotomy for tumor resection (n = 48), Chiari decompression (n = 40) and tethered cord release (n = 37). Trends in all measured outcomes, demonstrated variability amongst providers, but our results did not reach statistical significance due to the low number of each procedure.
Conclusions: OR and CDSS are dependent upon the acquisition of reliable clinical information. Continuous assessment of data and clear definition of quality metrics are necessary for the identification of the most clinically efficacious and cost effective pathways for care and their subsequent implementation as CDSS.
Patient Care: Clinical decision support systems and outcomes research can be utilized to create real-time analysis of patient characteristics and available treatment options to improve outcomes in patient populations. The ability to consolidate various electronic medical record systems improved data collection and can be used to develop real-time analysis of patients during their plan of care to offer and alter treatment when necessary.
Learning Objectives: 1) Consolidation of multiple electronic medical records as a source for prospective data collection in quality analysis.
2) Application of real-time outcomes data analysis in clinical decision making.
References: Kawamoto K, Houlihan CA, Balas EA, Lobach DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005 Apr 2;330(7494):765. Epub 2005 Mar 14.