All Automation Isn’t Good: CPOE and Order Sets

HIT or Miss ◽  
2019 ◽  
pp. 137-142
Keyword(s):  
Order Sets

scholarly journals Scalable Model for Delivery of Inpatient Palliative Care During a Pandemic

2021 ◽  
pp. 104990912110057
Author(s):  
Ebru Kaya ◽  
Warren Lewin ◽  
David Frost ◽  
Breffni Hannon ◽  
Camilla Zimmermann
Keyword(s):  
Palliative Care ◽  
High Quality ◽  
Consultation Service ◽  
General Internal ◽  
Virtual Care ◽  
Palliative Care Teams ◽  
Order Sets ◽  
Embedded Model ◽  
Advance Care ◽  
Care Capacity

Background: During the COVID-19 pandemic, hospitals worldwide have reported large volumes of patients with refractory symptoms and a large number of deaths attributable to COVID-19. This has led to an increase in the demand for palliative care beyond what can be provided by most existing programs. We developed a scalable model to enable continued provision of high-quality palliative care during a pandemic for hospitals without a palliative care unit or existing dedicated palliative care beds. Methods: A COVID-19 consultation service working group (CWG) was convened with stakeholders from palliative care, emergency medicine, critical care, and general internal medicine. The CWG connected with local palliative care teams to ensure a coordinated response, and developed a model to ensure high-quality palliative care provision. Results: Our 3-step scalable model included: (1) consultant model enhanced by virtual care; (2) embedded model; and (3) cohorted end-of-life unit for COVID-19 positive patients. This approach was enabled through tools and resources to ensure specialist palliative care capacity and rapid upskilling of all clinicians to deliver basic palliative care. Enabling tools and resources included a triage tool for in-person versus virtual care, new medication order sets and guidelines to facilitate prescribing for common symptoms, and lead advance care planning and goals of care discussions. A redeployment plan of generalist physicians and psychiatrists was created to ensure seamless provision of serious illness care. Conclusion: This 3-step, scalable approach enables rapid upscaling of palliative care in collaboration with generalist physicians, and may be adapted for future pandemics or natural disasters.

scholarly journals Best Paper Selection

2018 ◽  
Vol 27 (01) ◽  
pp. 127-128
Keyword(s):  
Decision Support ◽  
Postoperative Delirium ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Knowledge Bases ◽  
Free Text ◽  
Health Records ◽  
Support Tool ◽  
Team Selection ◽  
Order Sets

Chen JH, Alagappan M, Goldstein MK, Asch SM, Altman RB. Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets. Int J Med Inform 2017 Jun;102:71-9 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/28495350/ Ebadi A, Tighe PJ, Zhang L, Rashidi P. DisTeam: A decision support tool for surgical team selection. Artif Intell Med 2017 Feb;76:16-26 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/28363285/ Fung KW, Kapusnik-Uner J, Cunningham J, Higby-Baker S, Bodenreider O. Comparison of three commercial knowledge bases for detection of drug-drug interactions in clinical decision support. J Am Med Inform Assoc 2017 Jul 1;24(4):806-12 https://academic.oup.com/jamia/article-lookup/doi/10.1093/jamia/ocx010 Mikalsen KØ, Soguero-Ruiz C, Jensen K, Hindberg K, Gran M, Revhaug A, Lindsetmo RO, Skrøvseth SO, Godtliebsen F, Jenssen R. Using anchors from free text in electronic health records to diagnose postoperative delirium. Comput Methods Programs Biomed 2017 Dec;152:105-14 https://linkinghub.elsevier.com/retrieve/pii/S0169-2607(17)31154-9

Understanding Opioid Prescribing Practices of Resident Physicians

2021 ◽  
pp. 000313482110604
Author(s):  
Julia M. Coughlin ◽  
Samantha L. Terranella ◽  
Ethan M. Ritz ◽  
Thomas Q. Xu ◽  
John F. Tierney ◽  
...  
Keyword(s):  
Best Practice ◽  
Monitoring Program ◽  
Resident Training ◽  
Prescribing Practices ◽  
Exact Test ◽  
Opioid Prescribing ◽  
Resident Physicians ◽  
Order Sets ◽  
Patient’S History ◽  
Safe Opioid Prescribing

Background To compare opioid prescribing practices of resident physicians across a variety of surgical and nonsurgical specialties; to identify factors which influence prescribing practices; and to examine resident utilization of best practice supplemental resources. Methods An anonymous survey which assessed prescribing practices was completed by residents from one of several different subspecialties, including internal medicine, obstetrics and gynecology, general surgery, neurosurgery, orthopedic surgery, and urology. Fisher’s exact test assessed differences in prescribing practices between specialties. Results Only 35% of residents reported receiving formal training in safe opioid prescribing. Overall, the most frequently reported influences on prescribing practices were the use of standardized order sets for specific procedures, attending preference, and patient’s history of prescribed opioids. Resident physicians significantly underutilize best practice supplemental resources, such as counseling patients on pain expectations prior to prescribing opioid medication; contacting established pain specialists; screening patients for opioid abuse; referring to the Prescription Monitoring Program; and counseling patients on safe disposal of unused pills ( P < .001). Discussion The incorporation of comprehensive prescribing education into resident training and the utilization of standardized order sets can promote safe opioid prescribing.

Implementation of Global Strategies to Prevent Hospital-Onset Clostridium difficile Infection: Targeting Proton Pump Inhibitors and Probiotics

2017 ◽  
Vol 51 (10) ◽  
pp. 848-854 ◽  
Author(s):  
Paul O. Lewis ◽  
Timothy S. Lundberg ◽  
Jennifer L. Tharp ◽  
Clay W. Runnels
Keyword(s):  
Cohort Study ◽  
Clostridium Difficile ◽  
Proton Pump Inhibitors ◽  
Proton Pump ◽  
Clostridium Difficile Infection ◽  
Retrospective Cohort ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
Order Sets ◽  
Global Strategies

Background: Proton pump inhibitors (PPIs) have been identified as a significant risk factor for the development of Clostridium difficile infection (CDI). Probiotics given concurrently with antibiotics have been shown to have a moderate impact on preventing CDI. Objective: To evaluate the effectiveness of hospital-wide interventions designed to reduce PPI use and increase probiotics and whether these interventions were associated with a change in the incidence of hospital onset (HO)-CDI. Methods: This retrospective cohort study compared 2 fiscal years: July 2013 to June 2014 (FY14) and July 2014 to June 2015 (FY15). In July of FY15, global educational initiatives were launched targeting PPIs. Additionally, a HO-CDI prevention bundle was added to antibiotic-containing order sets targeting probiotics. Overall PPI use, probiotic use, and incidence of HO-CDI were recorded and compared for each cohort. Charts were also reviewed for patients who developed HO-CDI for the presence and appropriateness of a PPI and presence of probiotics. Results: The interventions resulted in a decrease in PPI use by 14% or 96 doses/1000 patient days (TPD; P = 0.0002) and a reduction in IV PPI use by 31% or 71 doses/TPD ( P = 0.0008). Probiotic use increased by 130% or 126 doses/TPD ( P = 0.0006). The incidence of HO-CDI decreased by 20% or 0.1 cases/TPD ( P = 0.04). Conclusions: A collaborative, multifaceted educational initiative directed at highlighting the risks associated with PPI use was effective in reducing PPI prescribing. The implementation of a probiotic bundle added to antibiotic order sets was effective in increasing probiotic use. These interventions were associated with a decrease in incidence of HO-CDI.

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 An Examination of a Canada-wide Collaboration Platform for Order Sets: A First Report (Preprint)

10.2196/26123 ◽  
2020 ◽  
Author(s):  
Arshia Javidan ◽  
Allan Brand ◽  
Andrew Cameron ◽  
Tommaso D'Ovidio ◽  
Martin Persaud ◽  
...  
Keyword(s):  
First Report ◽  
Order Sets

scholarly journals Path of least resistance: how computerised provider order entry can lead to (and reduce) wasteful practices

2018 ◽  
Vol 7 (2) ◽  
pp. e000345 ◽  
Author(s):  
Joseph Choi ◽  
Cori Rebecca Atlin
Keyword(s):  
Blood Count ◽  
Complete Blood Count ◽  
Clinical Care ◽  
Work Flow ◽  
Quality Improvement Initiative ◽  
Order Entry ◽  
Clinical Value ◽  
Careful Planning ◽  
Order Sets ◽  
Before And After

BackgroundComputerised 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.ObjectivesThis quality improvement initiative aimed to reduce unnecessary LDH testing in the ED.MethodsA 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 analysed the number of add-on LDH (ie, to add LDH to samples already sent to the lab) as a balancing measure, since this can disrupt work flow and delay care.ResultsThrough 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 (eg, a complete blood count was performed 197.7 and 196.1 times per day preintervention and postintervention, respectively (P=0.7663)). There was less than one add-on LDH per day on average.ConclusionsCPOE care templates can be powerful in shaping behaviours and reducing variability. However, close oversight of these panels is necessary to prevent errors and waste.

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