scholarly journals Identifying collaborative care teams through electronic medical record utilization patterns

2016 ◽  
Vol 24 (e1) ◽  
pp. e111-e120 ◽  
Author(s):  
You Chen ◽  
Nancy M Lorenzi ◽  
Warren S Sandberg ◽  
Kelly Wolgast ◽  
Bradley A Malin
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Collaborative Care ◽  
Cluster Coefficient ◽  
Management Practices ◽  
Medical Center ◽  
Academic Medical Center ◽  
Collaborative Teams ◽  
Care Patterns ◽  
Utilization Patterns

Objective: The goal of this investigation was to determine whether automated approaches can learn patient-oriented care teams via utilization of an electronic medical record (EMR) system. Materials and Methods: To perform this investigation, we designed a data-mining framework that relies on a combination of latent topic modeling and network analysis to infer patterns of collaborative teams. We applied the framework to the EMR utilization records of over 10 000 employees and 17 000 inpatients at a large academic medical center during a 4-month window in 2010. Next, we conducted an extrinsic evaluation of the patterns to determine the plausibility of the inferred care teams via surveys with knowledgeable experts. Finally, we conducted an intrinsic evaluation to contextualize each team in terms of collaboration strength (via a cluster coefficient) and clinical credibility (via associations between teams and patient comorbidities). Results: The framework discovered 34 collaborative care teams, 27 (79.4%) of which were confirmed as administratively plausible. Of those, 26 teams depicted strong collaborations, with a cluster coefficient > 0.5. There were 119 diagnostic conditions associated with 34 care teams. Additionally, to provide clarity on how the survey respondents arrived at their determinations, we worked with several oncologists to develop an illustrative example of how a certain team functions in cancer care. Discussion: Inferred collaborative teams are plausible; translating such patterns into optimized collaborative care will require administrative review and integration with management practices. Conclusions: EMR utilization records can be mined for collaborative care patterns in large complex medical centers.

scholarly journals Optimizing Inpatient Urine Culture Ordering Practices Using the Electronic Medical Record: A Pilot Study

2016 ◽  
Vol 38 (4) ◽  
pp. 486-488 ◽  
Author(s):  
Daniel Shirley ◽  
Harry Scholtz ◽  
Kurt Osterby ◽  
Jackson Musuuza ◽  
Barry Fox ◽  
...  
Keyword(s):  
Pilot Study ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Urine Culture ◽  
Medical Center ◽  
Academic Medical Center ◽  
Academic Medical ◽  
Before And After ◽  
Quasi Experimental ◽  
Before And After Study

A prospective quasi-experimental before-and-after study of an electronic medical record–anchored intervention of embedded education on appropriate urine culture indications and indication selection reduced the number of urine cultures ordered for catheterized patients at an academic medical center. This intervention could be a component of CAUTI-reduction bundles.Infect Control Hosp Epidemiol 2017;38:486–488

scholarly journals 2348. Incorporating Electronic Medical Record Hard Stops to Reduce Inappropriate Clostridioides difficile Testing at an Academic Medical Center: A Quality Improvement Study

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S807-S808
Author(s):  
Seetha Lakshmi ◽  
Kimberly Atrubin ◽  
Andrew Myers ◽  
Jonathan Teter ◽  
Ripal Jariwala ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Medical Center ◽  
Academic Medical Center ◽  
Tertiary Care ◽  
Quality Improvement Initiative ◽  
Process Measures ◽  
Clostridioides Difficile ◽  
Phone Calls

Abstract Background Clostridioides difficile is the most common pathogen causing healthcare-associated infections. This study highlights the multi-disciplinary efforts to reduce C. difficile infections (CDI) at a large, tertiary care teaching facility. Methods A quality improvement study was performed between March 2017 and April 2018, using six Plan-Do-Study-Act cycles that included transmission prevention, diagnostic stewardship, education, and antimicrobial stewardship. Process measures included hand hygiene, isolation precautions, low-level disinfection compliance, number of tests ordered, lab cancelation of tests, and compliance with the Electronic Medical Record (EMR) hard stop for patients with laxative use, and negative C.difficile test in the past 7 days. Results A total of 2,046 C. difficile tests were ordered during the initiative. Of the 124 patients with a positive C. difficile LabID event, 50% were male with a median age of 65 years (range: 11–92 years). A 53% reduction in C. difficile LabID events (7.5 to 4 events per 10,000 patient-days, P < 0.001), with a pronounced decrease between cycle 4 and 5 (5.4 to 2.9 events per 10,000 patient-days, P < 0.001) was achieved. The largest decrease in C. difficile lab tests ordered was seen after implementation of the EMR hard-stop (cycle 5), with fewer than 0.5 LabID events per 1,000 patient-days for each subsequent month after EMR hard-stop implementation. Frequent reasons for physician phone calls to Infection prevention department was related to chronic use of lactulose in patients with cirrhosis (30%) and unexplained diarrhea (70%). Based on provider feedback, EMR changes were made to remove lactulose from the hard-stop and offer infectious disease consultation upfront. There was 99% compliance with electronic medical record hard stop. There was a nonsignificant increase in lab cancelations due to inappropriate stool specimens over time (1.9% to 3.1% from cycle 1 to 6, P = 0.28) A 55% reduction in hospital-onset CDI surveillance events (from 6.9 to 3.2 per 10,000 patient-days, P < 0.001) was noted. Conclusion A multi-disciplinary Quality Improvement initiative is a successful strategy in reducing CDI events, with the largest decrease seen with introduction of EMR hard stops. Disclosures All authors: No reported disclosures.

scholarly journals Impact of a Cost Visibility Tool in the Electronic Medical Record on Antibiotic Prescribing in an Academic Medical Center

2015 ◽  
Vol 50 (6) ◽  
pp. 496-504
Author(s):  
Kelly L. Fargo ◽  
Jessica Johnston ◽  
Kurt B. Stevenson ◽  
Meredith Deutscher ◽  
Erica E. Reed
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Medical Center ◽  
Academic Medical Center ◽  
Antibiotic Prescribing ◽  
Academic Medical

scholarly journals Evaluation of an Outpatient Pharmacist Consult Service at a Large Academic Medical Center

2021 ◽  
Vol 12 (2) ◽  
pp. 13
Author(s):  
Melanie Berry ◽  
Amy Gustafson ◽  
Maya Wai ◽  
Alex J. Luli
Keyword(s):  
Medical Record ◽  
Medical Center ◽  
Academic Medical Center ◽  
Cost Savings ◽  
Acceptance Rate ◽  
Demographic Information ◽  
Consult Service ◽  
Descriptive Data ◽  
Academic Medical ◽  
Patient Demographic Information

Objective: To evaluate a novel outpatient pharmacist consult service in a large academic medical center. Setting: Four outpatient pharmacies that are part of a large academic medical center Methods: An outpatient pharmacist consult order was created and embedded in the electronic medical record (EMR). Medical center providers utilized this consult order when identifying patients in need of specific services provided by outpatient pharmacists. Descriptive data about each individual consult was collected including number completed, type of service, and duration. Rate of accepted pharmacy recommendations and patient cost savings were also evaluated. A survey was administered at the completion of the study period to assess provider and pharmacist satisfaction with the service.  Patient demographic information was collected for those who had a documented completed consult. Results: A total of 193 consults were completed: 137 immunizations, 37 care affordability, 15 education, 3 polypharmacy and 1 OTC recommendation. 89% of completed consults took pharmacists 20 minutes or less to complete. Of completed care affordability consults (n=31), 55% of patients saved between $100 - $500 per medication fill. Of providers who completed a survey and utilized the service (n=12), 83.3% were extremely satisfied and 16.7% were satisfied with it. The provider acceptance rate of pharmacist’s recommendations was 74%. Conclusion: Implementation of an outpatient pharmacist consult service provided an alternative method for the utilization of pharmacist provided MTM services in outpatient pharmacies at a large academic medical center. The service was well received by both providers and pharmacists.

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