ABSTRACT
Clinical decision support (CDS) is a process that provides information to assist the user in decision making for evaluation and treatment. Although many think only of rules and alerts, CDS is much more than that. Order sets, clinical documents, information fields, and medication sentences are just a few other CDS tools to be considered. CDS has been shown to improve care. Forming the third point of the triangle, CDS, along with process redesign and workflow considerations, improves care and helps create successful outcomes. Failure to address all 3 of these elements creates a less-than-perfect and potentially dangerous result. Examples of the application of CDS in the field of physical medicine and rehabilitation remain limited. This field has a huge opportunity to use CDS to enhance patient care, and is an open area for CDS development and research.
Subject(s)
Decision Support Systems, Clinical , Electronic Health Records , Physical and Rehabilitation Medicine , HumansABSTRACT
OBJECTIVE: Evidence-based sets of medical orders for the treatment of patients with common conditions have the potential to induce greater efficiency and convenience across the system, along with more consistent health outcomes. Despite ongoing utilization of order sets, quantitative evidence of their effectiveness is lacking. In this study, conducted at Advocate Health Care in Illinois, we quantitatively analyzed the benefits of community acquired pneumonia order sets as measured by mortality, readmission, and length of stay (LOS) outcomes. METHODS: In this study, we examined five years (2007-2011) of computerized physician order entry (CPOE) data from two city and two suburban community care hospitals. Mortality and readmissions benefits were analyzed by comparing "order set" and "no order set" groups of adult patients using logistic regression, Pearson's chi-squared, and Fisher's exact methods. LOS was calculated by applying one-way ANOVA and the Mann-Whitney U test, supplemented by analysis of comorbidity via the Charlson Comorbidity Index. RESULTS: The results indicate that patient treatment orders placed via electronic sets were effective in reducing mortality [OR=1.787; 95% CF 1.170-2.730; P=.061], readmissions [OR=1.362; 95% CF 1.015-1.827; P=.039], and LOS [F (1,5087)=6.885, P=.009, 4.79 days (no order set group) vs. 4.32 days (order set group)]. CONCLUSION: Evidence-based ordering practices have the potential to improve pneumonia outcomes through reduction of mortality, hospital readmissions, and cost of care. However, the practice must be part of a larger strategic effort to reduce variability in patient care processes. Further experimental and/or observational studies are required to reduce the barriers to retrospective patient care analyses.
ABSTRACT
OBJECTIVE: Evidence-based order sets for treatment of patients with common conditions promise ordering efficiency and more consistent health outcomes. Despite ongoing utilization of order sets, quantitative evidence of their effectiveness is lacking. This study quantitatively analyzed benefits of CHF order sets as measured by mortality, readmission, and length of stay (LOS) outcomes. METHODS: Mortality and readmissions were analyzed by comparing "order set" and "free text" groups of adult patients using logistic regression, Pearson chi-squared, and Fisher's exact methods. LOS was calculated by applying One-Way ANOVA and Mann-Whitney tests, supplemented by comorbidity analysis via Charlson Comorbidity Index. RESULTS: CHF orders placed via sets were effective in reducing mortality [OR=1.818;95% CF 1.039-3.181;p=0.034] and LOS [F(1,10938)=8.352,p=0.013,4.75 days ("free text" group) vs. 5.46 days ("order set" group)], while readmission outcome was not significant [OR=0.913;95% CF 0.734-1.137;p=0.417]. CONCLUSION: Evidence-based medication ordering practices to treat CHF have potential to reduce mortality and LOS, without effect on readmissions.
