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

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 Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial

2020 ◽  
Author(s):  
Nicolas Delvaux ◽  
Veerle Piessens ◽  
Tine De Burghgraeve ◽  
Pavlos Mamouris ◽  
Bert Vaes ◽  
...  
Keyword(s):  
Decision Support ◽  
Laboratory Test ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Order Entry ◽  
Order Sets ◽  
Cluster Randomized ◽  
Physician Order Entry ◽  
Test Ordering

Abstract BackgroundInappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care.MethodsThis study was a pragmatic, cluster randomized, open label, controlled clinical trial.Setting280 general practitioners (GPs) from 72 primary care practices in Belgium.PatientsPatients aged 18 years with a laboratory test order for at least one of 17 indications; cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication.InterventionsThe CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician.MeasurementsThe primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume and cascade activities.ResultsCDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16 - 0.26, p<.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37 - 10.93, p=.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease - 0.05% increase) in possible diagnostic error.ConclusionsA CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error. Trial RegistrationClinicaltrials.gov Identifier: NCT02950142

scholarly journals Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial

2020 ◽  
Author(s):  
Nicolas Delvaux ◽  
Veerle Piessens ◽  
Tine De Burghgraeve ◽  
Pavlos Mamouris ◽  
Bert Vaes ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Laboratory Test ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Order Sets ◽  
Cluster Randomized ◽  
Physician Order Entry ◽  
Test Ordering

Abstract Background Inappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care.Methods This study was a pragmatic, cluster randomized, open label, controlled clinical trial. Setting 280 general practitioners (GPs) from 72 primary care practices in Belgium. Patients Patients aged ≥18 years with a laboratory test order for at least one of 17 indications; cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication. Interventions The CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician. Measurements The primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume and cascade activities.Results CDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16 - 0.26, p<.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37 - 10.93, p=.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease - 0.05% increase) in possible diagnostic error.Conclusions A CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error. Trial Registration Clinicaltrials.gov Identifier: NCT02950142, registered on October 25, 2016Funding source This study was funded through the Belgian Health Care Knowledge Centre (KCE) Trials Programme agreement KCE16011.

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.

Altering standard admission order sets to promote clinical laboratory stewardship: a cohort quality improvement study

2019 ◽  
Vol 28 (10) ◽  
pp. 846-852 ◽  
Author(s):  
Benjamin Leis ◽  
Andrew Frost ◽  
Rhonda Bryce ◽  
Andrew W Lyon ◽  
Kelly Coverett
Keyword(s):  
Clinical Decision Making ◽  
Clinical Laboratory ◽  
Clinical Decision ◽  
Thyroid Stimulating Hormone ◽  
Clinical Indication ◽  
Medical Overuse ◽  
Order Sets ◽  
Cohort Quality ◽  
Careful Design ◽  
Order Set

BackgroundCareful design of preprinted order sets is needed to prevent medical overuse. Recent work suggests that removing a single checkbox from an order set changes physicians’ clinical decision-making.Local problemDuring a 2-month period, our coronary care unit (CCU) ordered almost eight times as many serum thyroid-stimulating hormone (TSH) tests as our neighbouring intensive care unit, many without a reasonable clinical basis. We postulated that we could reduce inappropriate testing and improve clinical laboratory stewardship by removing the TSH checkbox from the CCU admission order set.MethodsAfter we retrospectively evaluated CCU TSH ordering before intervention, the checkbox was removed from the CCU admission order set. Twelve weeks later, we commenced a prospective 2-month assessment of TSH testing and clinical sequelae of thyroid disease among all CCU admissions. If clinical indications were absent or testing had occurred within 6 weeks, TSH requests were labelled as ‘inappropriate’.ResultsPhysician ordering and, specifically, inappropriate ordering decreased substantially after the intervention. In 2016 among physician-ordered TSH tests, 60.6% (66/109) were inappropriate; in 2017 this decreased to 20% (2/10, p=0.01). Overall, the net effect of checkbox removal saw the decrease in TSH testing without clinical indication outweigh an increase in missed testing where indications appear to exist.ConclusionsProvision of an optional checkbox for a laboratory test in an admission order set can promote overuse of laboratory resources. Simple removal of a checkbox may dramatically change test ordering patterns and promote clinical laboratory stewardship. Given our reliance on order sets, particularly by trainees, changes to order sets must be cautious to assure guideline-directed care is maintained.

scholarly journals Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Nicolas Delvaux ◽  
Veerle Piessens ◽  
Tine De Burghgraeve ◽  
Pavlos Mamouris ◽  
Bert Vaes ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Laboratory Test ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Order Sets ◽  
Cluster Randomized ◽  
Physician Order Entry ◽  
Test Ordering

Abstract Background Inappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care. Methods This study was a pragmatic, cluster randomized, open-label, controlled clinical trial. Setting Two hundred eighty general practitioners (GPs) from 72 primary care practices in Belgium. Patients Patients aged ≥ 18 years with a laboratory test order for at least one of 17 indications: cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication. Interventions The CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician. Measurements The primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume, and cascade activities. Results CDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16–0.26, p < 0.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37–10.93, p = 0.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease–0.05% increase) in possible diagnostic error. Conclusions A CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error. Trial registration ClinicalTrials.gov Identifier: NCT02950142, registered on October 25, 2016

scholarly journals The tradeoffs between safety and alert fatigue: Data from a national evaluation of hospital medication-related clinical decision support

2020 ◽  
Vol 27 (8) ◽  
pp. 1252-1258 ◽  
Author(s):  
Zoe Co ◽  
A Jay Holmgren ◽  
David C Classen ◽  
Lisa Newmark ◽  
Diane L Seger ◽  
...  
Keyword(s):  
Clinical Decision ◽  
Evaluation Tool ◽  
Order Entry ◽  
Percentage Point Increase ◽  
Point Increase ◽  
Fatigue Data ◽  
Overall Performance ◽  
The Mean ◽  
The Cost ◽  
Physician Order Entry

Abstract Objective The study sought to evaluate the overall performance of hospitals that used the Computerized Physician Order Entry Evaluation Tool in both 2017 and 2018, along with their performance against fatal orders and nuisance orders. Materials and Methods We evaluated 1599 hospitals that took the test in both 2017 and 2018 by using their overall percentage scores on the test, along with the percentage of fatal orders appropriately alerted on, and the percentage of nuisance orders incorrectly alerted on. Results Hospitals showed overall improvement; the mean score in 2017 was 58.1%, and this increased to 66.2% in 2018. Fatal order performance improved slightly from 78.8% to 83.0% (P &lt; .001), though there was almost no change in nuisance order performance (89.0% to 89.7%; P = .43). Hospitals alerting on one or more nuisance orders had a 3-percentage-point increase in their overall score. Discussion Despite the improvement of overall scores in 2017 and 2018, there was little improvement in fatal order performance, suggesting that hospitals are not targeting the deadliest orders first. Nuisance order performance showed almost no improvement, and some hospitals may be achieving higher scores by overalerting, suggesting that the thresholds for which alerts are fired from are too low. Conclusions Although hospitals improved overall from 2017 to 2018, there is still important room for improvement for both fatal and nuisance orders. Hospitals that incorrectly alerted on one or more nuisance orders had slightly higher overall performance, suggesting that some hospitals may be achieving higher scores at the cost of overalerting, which has the potential to cause clinician burnout and even worsen safety.

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