scholarly journals MP011: Using GRADE-based recommendations for analgesia and antiemetics in electronic order sets to influence physician behaviour towards best practice and cost-savings

CJEM ◽  
2016 ◽  
Vol 18 (S1) ◽  
pp. S69-S70
Author(s):  
R.J. Hartmann ◽  
E. Lang ◽  
T. Rich ◽  
B. Ford ◽  
K. Lonergan ◽  
...  
Keyword(s):  
Best Practices ◽  
Working Group ◽  
Cost Savings ◽  
Sufficient Evidence ◽  
New Order ◽  
Order Entry ◽  
Physician Behaviour ◽  
Order Sets ◽  
Electronic Order ◽  
Order Set

Introduction: The addition of computerized physician order entry (CPOE) to Emergency Departments in recent years has led to speculation over potential benefits and pitfalls. Recent studies have shown benefits to CPOE, though there lacks sufficient evidence on how it could change physician behaviour. Physician practices are known to be difficult to change, with getting evidence into daily practice being the main challenge of knowledge translation. Our study aims were to determine if well-designed electronic order sets for CPOE improved MD practices. Methods: The Calgary Zone Pain Management in the Emergency Department Working Group relied on a GRADE-based literature review for identifying best practices for analgesia and antiemetics, resulting in soft changes to the dedicated analgesia and antiemetic electronic order set noting working group preference, and emphasizing hydromorphone over morphine, as well as 4 mg ondansetron over 8 mg. The new electronic order set was started in the only Calgary Region order entry system on December 11th, 2014. Data was collected from July 2014 - May 2015. A Yates chi-squared analysis was completed on all orders in a category, as well as the subgroups of ED staff and residents, and orders placed using the new order set. Results: A total of 100460 orders were analyzed. The use of hydromorphone increased significantly across all 4 EDs. IV hydromorphone use increased (5.82% of all opioid orders up to 26.93%, P<0.0001) with a reciprocal decline in IV morphine (67.81% of all opioid orders down to 46.56%, P<0.0001). Similar effects were observed with ondansetron 4 mg IV orders increasing (1.37% of all ondansetron orders to 18.64%, P<0.0001) with a decrease in 8 mg dosing (15.75% of all ondansetron orders to 7.23%, P<0.0001). These results were replicated to a lesser degree in the non-ED staff and non-order set subgroups. Implementation of the new order set resulted in an increase of its use (37.64% of all opioid orders up to 49.29%, P<0.0001). Finally, a cost-savings analysis was completed showing a projected annual savings of $185,676.52 on medications alone. Conclusion: This data supports the manipulation of electronic order sets to help shape physician behaviour towards best practices. This provides another strong argument towards the benefits of CPOE, and can help maintain best practices in Emergency Medicine.

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).

scholarly journals Developing and maintaining clinical decision support using clinical knowledge and machine learning: the case of order sets

2018 ◽  
Vol 25 (11) ◽  
pp. 1547-1551 ◽  
Author(s):  
Yiye Zhang ◽  
Richard Trepp ◽  
Weiguang Wang ◽  
Jorge Luna ◽  
David K Vawdrey ◽  
...  
Keyword(s):  
Machine Learning ◽  
Best Practices ◽  
Clinical Decision ◽  
Machine Learning Algorithms ◽  
Clinical Knowledge ◽  
Order Sets ◽  
Knowledge Intensive ◽  
Individualized Prediction ◽  
Effective Development ◽  
Order Set

Abstract Development and maintenance of order sets is a knowledge-intensive task for off-the-shelf machine-learning algorithms alone. We hypothesize that integrating clinical knowledge with machine learning can facilitate effective development and maintenance of order sets while promoting best practices in ordering. To this end, we simulated the revision of an “AM Lab Order Set” under 6 revision approaches. Revisions included changes in the order set content or default settings through 1) population statistics, 2) individualized prediction using machine learning, and 3) clinical knowledge. Revision criteria were determined using electronic health record (EHR) data from 2014 to 2015. Each revision’s clinical appropriateness, workload from using the order set, and generalizability across time were evaluated using EHR data from 2016 and 2017. Our results suggest a potential order set revision approach that jointly leverages clinical knowledge and machine learning to improve usability while updating contents based on latest clinical knowledge and best practices.

scholarly journals Implementation of disease-based standard order sets in emergency department of tertiary care hospital, Pakistan- a novel approach for enhancing patient care

2020 ◽  
pp. 1-13
Author(s):  
Feroza Parveen ◽  
Asif Khaliq ◽  
Nadeem Ullah Khan ◽  
Zainab Mazhar ◽  
Aisha Akram ◽  
...  
Keyword(s):  
Emergency Department ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Care Hospital ◽  
Order Entry ◽  
Post Intervention ◽  
Order Processing ◽  
Standard Order ◽  
Order Sets ◽  
Order Set

Abstract Objectives: To evaluate the efficacy of disease-based standard order sets in reducing time of order entry, order processing and medication dispensation in emergency department of a tertiary care hospital. Methods: The pilot study was conducted as part of a retrospective clinical audit using pre- and post-intervention design comprising data from July to September 2013 of the emergency department of a tertiary care hospital in Karachi. Data collected related to the reduction in medicine order entry, processing and dispensing time of eight common emergency conditions with standard order set.  Subsequently, standard medication orders for the selected medical conditions were developed together with physicians of emergency and other specialties. Post-intervention data was collected and the two data sets were compared using SPSS version 23.0. Results: Mean medication order entry and processing time from the physician end improved from 67.7±22.7 seconds to 20.5±7.1 seconds.  Mean order processing and medication processing and dispensing time at pharmacist end reduced from 70.0±22.4 to 20.6±8.8 seconds. The difference between pre- and post-intervention values was significant (p<0.001). Conclusion: Implementation of disease-based standard order set significantly improved efficiency. Key Words: Standard, Order sets, Emergency department, Disease, Time management. Continuous...

scholarly journals P019: The path of least resistance: how computerized provider order entry can lead to (and reduce) wasteful practices

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S63-S63
Author(s):  
J. Choi
Keyword(s):  
Complete Blood Count ◽  
Clinical Care ◽  
Cost Savings ◽  
Quality Improvement Initiative ◽  
Order Entry ◽  
Clinical Value ◽  
Post Intervention ◽  
Computerized Provider Order Entry ◽  
Order Sets ◽  
Before And After

Introduction: Background Computerized provider order entry (CPOE) is rapidly becoming the mainstay in clinical care and has the potential to improve provider efficiency and accuracy. However, this hinges on careful planning and implementation. Poorly planned CPOE order sets can lead to undetected errors and waste. In our emergency department (ED), lactate dehydrogenase (LDH) was bundled into various blood work panels, but had little clinical value. Aim Statement This quality improvement initiative aimed to reduce unnecessary LDH testing in the ED. Methods: Methods A group of ED physicians reviewed CPOE blood work panels and uncoupled LDH in conditions where it was deemed not to provide any clinically useful information. We measured the daily number of LDH tests performed before and after its removal. We tracked the frequency of other serum tests as controls. We also analyzed the number of add-on LDH (i.e. to add LDH to samples already sent to the lab) as a balancing measure, since this can disrupt work flow and delay care. Results: Results Through this intervention, we reduced the number of LDH tests performed by 69%, from an average of 75.1 tests per day to 23.2 (p<0.0005). The baseline controls did not differ after the intervention (e.g. a complete blood count was performed 197.7 and 196.1 times per day pre- and post-intervention, respectively [p=0.7663]). There was less than 1 add-on LDH per day on average. This translates to a cost savings of $33,340.65 at our institution. Conclusion: Conclusions CPOE care templates can be powerful in shaping behaviours and reducing variability. However, close oversight of these panels is necessary to prevent errors and waste.

scholarly journals 236. Incorporating Clinical Guidance into Computerized Prescriber Order Entry May Reduce Fluoroquinolone Utilization for the Treatment of Diverticulitis at a Rural Community Health System

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S118-S119
Author(s):  
Raghavendra Tirupathi ◽  
Benton Miller ◽  
Jarett Logsdon
Keyword(s):  
Time Frame ◽  
Secondary Outcome ◽  
Control Group ◽  
Order Entry ◽  
Clinical Guidance ◽  
Clostridioides Difficile ◽  
Days Of Therapy ◽  
Order Sets ◽  
Computerized Prescriber Order Entry ◽  
Order Set

Abstract Background Fluoroquinolones are associated with many adverse effects. As a result, many hospitals are investigating methods to reduce fluoroquinolone use. Computerized prescriber order entry (CPOE) provides an opportunity to develop and implement clinically guided order sets that discourage the use of fluoroquinolones. To date, there are few studies investigating the effect of clinically guided order sets on medication utilization. This study aims to investigate the hypothesis that incorporating clinical guidance and leveraging antimicrobial stewardship into a CPOE diverticulitis order set would reduce fluoroquinolone use in the treatment of diverticulitis. Methods A diverticulitis order set was revised to provide guided antibiotic selection based on a patient’s penicillin allergy. Patients were split into two groups based on admission date relative to the implementation date of the revised order set. Fluoroquinolone use was compared between both groups. The primary outcome was the percentage of patients who were ordered a fluoroquinolone-containing regimen during their stay. The secondary outcome was the percentage of regimens that contained a fluoroquinolone. A subgroup analysis was conducted exclusively on patients whose antibiotics were ordered with the diverticulitis order set. Results 494 patients were included in the study. 316 patients in the pre-order set group, 178 patients in the post-order set group. 56% of patients in the pre-group received a fluoroquinolone in their regimen versus 46% of patients in the post-group (RR=0.82; 95% CI 0.68–0.99, p = 0.028). 49% of regimens in the control group contained a fluoroquinolone versus 39% of regimens in the experimental group (RR=0.78; 95% CI 0.64–0.95; p = 0.012). 77.5% of patients in the control subgroup received a fluoroquinolone in their regimen versus 42.4% of patients in the experimental subgroup (RR=0.55; 95% CI 0.36–0.84, p = 0.0062). Fluoroquinolone days of therapy decreased from 90.6 to 58.6 from 2018–2019. Clostridioides difficile infections also decreased during this time frame. Table 1: Average fluoroquinolone days of therapy per 1000 patient days Figure 1: Percentage of Diverticulitis Orders by Antibiotic Regimen: Pre- and Post-Order Set Change. CFP=cefepime, Metro=metronidazole, PIP-TZ=piperacillin-tazobactam, AM-SB=ampicillin-sulbactam, CIP=ciprofloxacin, Levo=levofloxacin, FQ=fluoroquinolone Figure 2: Fluoroquinolone days of therapy per 1000 patient days from 2016–2020. Conclusion Our findings support the hypothesis that incorporating clinical guidance into a CPOE order set would reduce fluoroquinolone use for the treatment of diverticulitis. Figure 3: Indicence of Clostridioides difficile infection per 1000 patient days Disclosures All Authors: No reported disclosures

A Statistical Approach for the Learning Curve of Physicians in Utilization of Electronic Order Sets

2019 ◽  
Vol 58 (04/05) ◽  
pp. 160-166
Author(s):  
Jaehoon Lee ◽  
Nathan C. Hulse
Keyword(s):  
Learning Curve ◽  
Utilization Rate ◽  
New Order ◽  
Inpatient Setting ◽  
Standard Order ◽  
Order Sets ◽  
Initial Hypothesis ◽  
Localized Patterns ◽  
Physician Order Entry ◽  
Order Set

Abstract Background Understanding a physician's behavior toward learning order sets is important as it is a key information to design order sets with optimized contents. Objective The objective of this article is to test a hypothesis: for a physician using a new order set repeatedly, the utilization rate of order set contents has a pattern of either increase or decrease. Methods To test the hypothesis, we retrieved empirical data of order set usage in local hospitals that adopted a new computerized physician order entry (CPOE) system and enterprise wide standard order sets. We extracted 4-year data including 63,583 orders made by 600 physicians in the inpatient setting and analyzed patterns of the learning curve at several aggregation levels. Result The analysis results demonstrated that content modification rates over time were relatively flat except for a few localized patterns. Conclusion Based on our finding, we reject our initial hypothesis.

scholarly journals Impact of order set design on urine culturing practices at an academic medical centre emergency department

2018 ◽  
Vol 27 (8) ◽  
pp. 587-592 ◽  
Author(s):  
Satish Munigala ◽  
Ronald R Jackups ◽  
Robert F Poirier ◽  
Stephen Y Liang ◽  
Helen Wood ◽  
...  
Keyword(s):  
Emergency Department ◽  
Urine Culture ◽  
Temporal Trends ◽  
Urine Test ◽  
Post Intervention ◽  
Order Sets ◽  
Ed Visits ◽  
Urine Testing ◽  
Electronic Order ◽  
Order Set

BackgroundUrinalysis and urine culture are commonly ordered tests in the emergency department (ED). We evaluated the impact of removal of order sets from the ‘frequently ordered test’ in the computerised physician order entry system (CPOE) on urine testing practices.MethodsWe conducted a before (1 September to 20 October 2015) and after (21 October to 30 November 2015) study of ED patients. The intervention consisted of retaining ‘urinalysis with reflex to microscopy’ as the only urine test in a highly accessible list of frequently ordered tests in the CPOE system. All other urine tests required use of additional order screens via additional mouse clicks. The frequency of urine testing before and after the intervention was compared, adjusting for temporal trends.ResultsDuring the study period, 6499 (28.2%) of 22 948 ED patients had ≥1 urine test ordered. Urine testing rates for all ED patients decreased in the post intervention period for urinalysis (291.5 pre intervention vs 278.4 per 1000 ED visits post intervention, P=0.03), urine microscopy (196.5vs179.5, P=0.001) and urine culture (54.3vs29.7, P<0.001). When adjusted for temporal trends, the daily culture rate per 1000 ED visits decreased by 46.6% (−46.6%, 95% CI −66.2% to –15.6%), but urinalysis (0.4%, 95% CI −30.1 to 44.4%), microscopy (−6.5%, 95% CI −36.0% to 36.6%) and catheterised urine culture rates (17.9%, 95% CI −16.9 to 67.4) were unchanged.ConclusionsA simple intervention of retaining only ‘urinalysis with reflex to microscopy’ and removing all other urine tests from the ‘frequently ordered’ window of the ED electronic order set decreased urine cultures ordered by 46.6% after accounting for temporal trends. Given the injudicious use of antimicrobial therapy for asymptomatic bacteriuria, findings from our study suggest that proper design of electronic order sets plays a vital role in reducing excessive ordering of urine cultures.

Evaluating Adherence to Guideline-Directed C Difficile Infection Management Pre- and Postimplementation of an Electronic Order Set

2020 ◽  
pp. 089719002090385
Author(s):  
Aamer Attaar ◽  
Juanqin Wei ◽  
Luigi Brunetti
Keyword(s):  
Infectious Disease ◽  
Primary Outcome ◽  
Secondary Outcome ◽  
Single Center ◽  
Clostridioides Difficile ◽  
Order Sets ◽  
Before And After ◽  
Clostridioides Difficile Infection ◽  
Electronic Order ◽  
Order Set

Background: After publication of the Clostridioides difficile infection (CDI) guidelines by the Infectious Disease Society of America (IDSA) in early 2018, we identified that many prescribers at our institution continued to practice using the older guidelines. Objective: This study aimed to determine whether the implementation of an electronic order set for CDI would increase prescriber compliance to current IDSA recommendations for CDI management. Methods: This was a single-center, prospective cohort study of adult inpatients with a confirmed CDI. The study was conducted between March 1, 2018, and April 1, 2019. Patients were stratified into a preintervention and postintervention group before and after order set implementation. The primary outcome was a composite of appropriate CDI therapy selection and discontinuation of nonessential antimicrobials and acid-suppressive agents. The secondary outcome evaluated appropriate CDI therapy medications prescribed at hospital discharge. Results: Of the 149 patients included in this study, 96 were included in a preintervention group and 53 included in a postintervention group. The primary outcome was met in 45% of patients in the preintervention group and 66% of patients in the postintervention group ( P = .01). The secondary outcome occurred in 86% of patients in the preintervention group and 100% of patients in the postintervention group ( P = .02). Conclusion: Implementation of a CDI electronic order set and alert bundle was associated with enhanced prescriber adherence to guideline-directed therapy. Our results suggest that order sets not only improve inpatient compliance to guidelines but may also improve medication-related adherence to guideline recommendations upon discharge.

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

Sign in / Sign up

Export Citation Format

Share Document