scholarly journals Effectiveness of Evidence-based Pneumonia CPOE Order Sets Measured by Health Outcomes

2015 ◽  
Vol 7 (2) ◽  
Author(s):  
Jacob Krive ◽  
Joel S. Shoolin ◽  
Steven D. Zink
Keyword(s):  
Health Outcomes ◽  
Patient Care ◽  
Cost Of Care ◽  
Patient Treatment ◽  
Computerized Physician Order Entry ◽  
Evidence Based ◽  
Order Entry ◽  
Order Sets ◽  
Physician Order Entry ◽  
Order Set

ObjectiveEvidence-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.MethodsIn 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.ResultsThe 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)].ConclusionEvidence-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.Keywords: evidence-based medicine, medication order sets, health outcomes research, pneumonia, computerized physician order entry (CPOE).

Evidence-based red cell transfusion in the critically ill: Quality improvement using computerized physician order entry*

2006 ◽  
Vol 34 (7) ◽  
pp. 1892-1897 ◽  
Author(s):  
Rimki Rana ◽  
Bekele Afessa ◽  
Mark T. Keegan ◽  
Francis X. Whalen ◽  
Gregory A. Nuttall ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Critically Ill ◽  
Computerized Physician Order Entry ◽  
Evidence Based ◽  
Red Cell ◽  
Order Entry ◽  
Red Cell Transfusion ◽  
Physician Order Entry

Systematic Update of Computerized Physician Order Entry Order Sets to Improve Quality of Care: A Case Study

PEDIATRICS ◽  
2013 ◽  
Vol 131 (Supplement 1) ◽  
pp. S60-S67 ◽  
Author(s):  
Michael G. Leu ◽  
Sheryl A. Morelli ◽  
Oi-Yan Chung ◽  
Shanon Radford
Keyword(s):  
Quality Of Care ◽  
Computerized Physician Order Entry ◽  
Improve Quality ◽  
Order Entry ◽  
Order Sets ◽  
Physician Order Entry

scholarly journals Default settings of computerized physician order entry system order sets drive ordering habits

2015 ◽  
Vol 6 (1) ◽  
pp. 16 ◽  
Author(s):  
Jordan Olson ◽  
Thomas Abendroth ◽  
William Castellani ◽  
Keri Donaldson ◽  
Christopher Hollenbeak
Keyword(s):  
Computerized Physician Order Entry ◽  
Order Entry ◽  
Order Sets ◽  
Physician Order Entry ◽  
System Order

scholarly journals Duplicate Orders: An Unintended Consequence of Computerized provider/physician order entry (CPOE) Implementation

2012 ◽  
Vol 03 (04) ◽  
pp. 377-391 ◽  
Author(s):  
C. Forrer ◽  
S. Shaha ◽  
S. Magid
Keyword(s):  
Time Series ◽  
Improve Patient Safety ◽  
Clinical Decision ◽  
Unintended Consequences ◽  
Unintended Consequence ◽  
Mitigation Strategies ◽  
Order Entry ◽  
Order Sets ◽  
Physician Order Entry ◽  
Order Set

SummaryObjective: Computerized provider/physician order entry (CPOE) with clinical decision support (CDS) is designed to improve patient safety. However, a number of unintended consequences which include duplicate ordering have been reported. The objective of this time-series study was to characterize duplicate orders and devise strategies to minimize them.Methods: Time series design with systematic weekly sampling for 84 weeks. Each week we queried the CPOE database, downloaded all active orders onto a spreadsheet, and highlighted duplicate orders. We noted the following details for each duplicate order: time, order details (e.g. drug, dose, route and frequency), ordering prescriber, including position and role, and whether the orders originated from a single order or from an order set (and the name of the order set). This analysis led to a number of interventions, including changes in: order sets, workflow, prescriber training, pharmacy procedures, and duplicate alerts.Results: Duplicates were more likely to originate from different prescribers than from same prescribers; and from order sets than from single orders. After interventions, there was an 84.8% decrease in the duplication rate from weeks 1 to 84 and a 94.6% decrease from the highest (1) to the lowest week (75). Currently, we have negligible duplicate orders.Conclusions: Duplicate orders can be a significant unintended consequence of CPOE. By analyzing these orders, we were able to devise and implement generalizable strategies that significantly reduced them. The incidence of duplicate orders before CPOE implementation is unknown, and our data originate from a weekly snapshot of active orders, which serves as a sample of total active orders. Thus, it should be noted that this methodology likely under-reports duplicate orders.Citation: Magid S, Forrer C, Shaha S. Duplicate Orders: An unintended consequence of computerized provider/physician order entry (CPOE) implementation. Analysis and mitigation strategies. Appl Clin Inf 2012; 3: 377–391http://dx.doi.org/10.4338/ACI-2012-01-RA-0002

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