Using clinical decision support to improve urine culture diagnostic stewardship, antimicrobial stewardship, and financial cost: A multicenter experience

2020 ◽  
Vol 41 (5) ◽  
pp. 564-570
Author(s):  
Kaitlin J. Watson ◽  
Barbara Trautner ◽  
Hannah Russo ◽  
Kady Phe ◽  
Todd Lasco ◽  
...  
Keyword(s):  
Urinary Tract ◽  
Electronic Health Record ◽  
Urine Culture ◽  
New Order ◽  
Health Record ◽  
Days Of Therapy ◽  
Electronic Health ◽  
Tract Infections ◽  
The Impact ◽  
Order Set

AbstractObjective:Despite evidence to the contrary, many practitioners continue to inappropriately screen for and treat bacteria in the urine of clinically asymptomatic patients. The purpose of this study was to evaluate the impact of a new order set on the number of urine culture performed, antibiotic days of therapy (DOT), catheter-associated urinary tract infections (CAUTI), and associated financial impact.Design:A quasi-experimental before-and-after intervention.Setting:We conducted this study at 5 Catholic Health Initiative (CHI) hospitals in Texas that use the same electronic health record (EHR) system.Patients:The study populations included adult patients who had urine culture performed from June 2017 to June 2019.Intervention:The intervention (implemented June 25, 2018) was the addition of a new order set in the electronic health record that required practitioners to choose an indication for the type of urine study. The primary outcome was number of urine cultures performed adjusted for the number of total patient days.Results:Following implementation of the new order set, the number of urine cultures performed among the 5 sites decreased from 1,175.8 tests per 10,000 patient days before the intervention to 701.4 after the intervention (40.4% reduction; P < .01). Antibiotic DOT for patients with a urinary tract infection indication decreased from 102.5 to 86.9 per 1,000 patient days (15.2% reduction; P < .01). The CAUTI standardized infection ratio was 1.0 before the intervention and 0.8 after the intervention (P = .23). The estimated yearly savings following the intervention was US$535,181.Conclusions:The addition of a new order set resulted in decreases in the number of urine cultures performed and the antibiotic DOT, as well as substantial financial savings.

scholarly journals Identification of urinary tract infections using electronic health record data

2019 ◽  
Vol 47 (4) ◽  
pp. 371-375
Author(s):  
Kathryn L. Colborn ◽  
Michael Bronsert ◽  
Karl Hammermeister ◽  
William G. Henderson ◽  
Abhinav B. Singh ◽  
...  
Keyword(s):  
Urinary Tract ◽  
Electronic Health Record ◽  
Urinary Tract Infections ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Electronic Health ◽  
Tract Infections

scholarly journals Prediction of Antibiotic Susceptibility for Urinary Tract Infection in a Hospital Setting

2020 ◽  
Vol 64 (7) ◽  
Author(s):  
Courtney Hebert ◽  
Yuan Gao ◽  
Protiva Rahman ◽  
Courtney Dewart ◽  
Mark Lustberg ◽  
...  
Keyword(s):  
Urinary Tract ◽  
Electronic Health Record ◽  
Statistical Learning ◽  
Predictive Models ◽  
Retrospective Cohort ◽  
Hospitalized Patients ◽  
Health Record ◽  
Data Set ◽  
Electronic Health ◽  
Tract Infections

ABSTRACT Empiric antibiotic prescribing can be supported by guidelines and/or local antibiograms, but these have limitations. We sought to use data from a comprehensive electronic health record to use statistical learning to develop predictive models for individual antibiotics that incorporate patient- and hospital-specific factors. This paper reports on the development and validation of these models with a large retrospective cohort. This was a retrospective cohort study including hospitalized patients with positive urine cultures in the first 48 h of hospitalization at a 1,500-bed tertiary-care hospital over a 4.5-year period. All first urine cultures with susceptibilities were included. Statistical learning techniques, including penalized logistic regression, were used to create predictive models for cefazolin, ceftriaxone, ciprofloxacin, cefepime, and piperacillin-tazobactam. These were validated on a held-out cohort. The final data set used for analysis included 6,366 patients. Final model covariates included demographics, comorbidity score, recent antibiotic use, recent antimicrobial resistance, and antibiotic allergies. Models had acceptable to good discrimination in the training data set and acceptable performance in the validation data set, with a point estimate for area under the receiver operating characteristic curve (AUC) that ranged from 0.65 for ceftriaxone to 0.69 for cefazolin. All models had excellent calibration. We used electronic health record data to create predictive models to estimate antibiotic susceptibilities for urinary tract infections in hospitalized patients. Our models had acceptable performance in a held-out validation cohort.

scholarly journals Management of a parenteral opioid shortage using ASHP guidelines

2021 ◽  
Vol 78 (5) ◽  
pp. 426-435
Author(s):  
Peter Vo ◽  
Daniel A Sylvia ◽  
Loay Milibari ◽  
John Ryan Stackhouse ◽  
Paul Szumita ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Drug Product ◽  
Health Record ◽  
Large Hospital ◽  
Hospital Administrators ◽  
Utilization Data ◽  
Electronic Health ◽  
Opioid Medications ◽  
American Society ◽  
The Impact

Abstract Purpose Management of an acute shortage of parenteral opioid products at a large hospital through prescribing interventions and other guideline-recommended actions is described. Summary In early 2018, many hospitals were faced with a shortage of parenteral opioids that was predicted to last an entire year. The American Society of Health-System Pharmacists (ASHP) has published guidelines on managing drug product shortages. This article describes the application of these guidelines to manage the parenteral opioid shortage and the impact on opioid dispensing that occurred in 2018. Our approach paralleled that recommended in the ASHP guidelines. Daily dispensing reports generated from automated dispensing cabinets and from the electronic health record were used to capture dispenses of opioid medications. Opioid prescribing and utilization data were converted to morphine milligram equivalents (MME) to allow clinical leaders and hospital administrators to quickly evaluate opioid inventories and consumption. Action steps included utilization of substitute opioid therapies and conversion of opioid patient-controlled analgesia (PCA) and opioid infusions to intravenous bolus dose administration. Parenteral opioid supplies were successfully rationed so that surgical and elective procedures were not canceled or delayed. During the shortage, opioid dispensing decreased in the inpatient care areas from approximately 2.0 million MME to 1.4 million MME and in the operating rooms from 0.56 MME to 0.29 million MME. The combination of electronic health record alerts, increased utilization of intravenous acetaminophen and liposomal bupivacaine, and pharmacist interventions resulted in a 67% decline in PCA use and a 65% decline in opioid infusions. Conclusion A multidisciplinary response is necessary for effective management of drug shortages through implementation of strategies and practices for notifying clinicians of shortages and identifying optimal alternative therapies.

scholarly journals 216. Are Automatic Antimicrobial Stop Orders an Effective Stewardship Tool for Urinary Tract and Intra-Abdominal Infections?

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S110-S110
Author(s):  
Christina Maguire ◽  
Dusten T Rose ◽  
Theresa Jaso
Keyword(s):  
Urinary Tract ◽  
Antimicrobial Therapy ◽  
Source Control ◽  
Clostridioides Difficile ◽  
Days Of Therapy ◽  
Before And After ◽  
The Difference ◽  
Tract Infections ◽  
Length Of Therapy ◽  
The Impact

Abstract Background Automatic antimicrobial stop orders (ASOs) are a stewardship initiative used to decrease days of therapy, prevent resistance, and reduce drug costs. Limited evidence outside of the perioperative setting exists on the effects of ASOs on broad spectrum antimicrobial use, discharge prescription duration, and effects of missed doses. This study aims to evaluate the impact of an ASO policy across a health system of adult academic and community hospitals for treatment of intra-abdominal (IAI) and urinary tract infections (UTI). ASO Outcome Definitions ASO Outcomes Methods This multicenter retrospective cohort study compared patients with IAI and UTI treated before and after implementation of an ASO. Patients over the age of 18 with a diagnosis of UTI or IAI and 48 hours of intravenous (IV) antimicrobial administration were included. Patients unable to achieve IAI source control within 48 hours or those with a concomitant infection were excluded. The primary outcome was the difference in sum length of antimicrobial therapy (LOT). Secondary endpoints include length and days of antimicrobial therapy (DOT) at multiple timepoints, all cause in hospital mortality and readmission, and adverse events such as rates of Clostridioides difficile infection. Outcomes were also evaluated by type of infection, hospital site, and presence of infectious diseases (ID) pharmacist on site. Results This study included 119 patients in the pre-ASO group and 121 patients in the post-ASO group. ASO shortened sum length of therapy (LOT) (12 days vs 11 days respectively; p=0.0364) and sum DOT (15 days vs 12 days respectively; p=0.022). This finding appears to be driven by a decrease in outpatient LOT (p=0.0017) and outpatient DOT (p=0.0034). Conversely, ASO extended empiric IV LOT (p=0.005). All other secondary outcomes were not significant. Ten patients missed doses of antimicrobials due to ASO. Subgroup analyses suggested that one hospital may have influenced outcomes and reduction in LOT was observed primarily in sites without an ID pharmacist on site (p=0.018). Conclusion While implementation of ASO decreases sum length of inpatient and outpatient therapy, it may not influence inpatient length of therapy alone. Moreover, ASOs prolong use of empiric intravenous therapy. Hospitals without an ID pharmacist may benefit most from ASO protocols. Disclosures All Authors: No reported disclosures

scholarly journals The Development and Piloting of the Ambulatory Electronic Health Record Evaluation Tool: Lessons Learned

2021 ◽  
Vol 12 (01) ◽  
pp. 153-163
Author(s):  
Zoe Co ◽  
A. Jay Holmgren ◽  
David C. Classen ◽  
Lisa P. Newmark ◽  
Diane L. Seger ◽  
...  
Keyword(s):  
Decision Support ◽  
Electronic Health Record ◽  
Medication Safety ◽  
Medication Reconciliation ◽  
The United States ◽  
Health Record ◽  
Evaluation Tool ◽  
Safety Test ◽  
Electronic Health ◽  
The Impact

Abstract Background Substantial research has been performed about the impact of computerized physician order entry on medication safety in the inpatient setting; however, relatively little has been done in ambulatory care, where most medications are prescribed. Objective To outline the development and piloting process of the Ambulatory Electronic Health Record (EHR) Evaluation Tool and to report the quantitative and qualitative results from the pilot. Methods The Ambulatory EHR Evaluation Tool closely mirrors the inpatient version of the tool, which is administered by The Leapfrog Group. The tool was piloted with seven clinics in the United States, each using a different EHR. The tool consists of a medication safety test and a medication reconciliation module. For the medication test, clinics entered test patients and associated test orders into their EHR and recorded any decision support they received. An overall percentage score of unsafe orders detected, and order category scores were provided to clinics. For the medication reconciliation module, clinics demonstrated how their EHR electronically detected discrepancies between two medication lists. Results For the medication safety test, the clinics correctly alerted on 54.6% of unsafe medication orders. Clinics scored highest in the drug allergy (100%) and drug–drug interaction (89.3%) categories. Lower scoring categories included drug age (39.3%) and therapeutic duplication (39.3%). None of the clinics alerted for the drug laboratory or drug monitoring orders. In the medication reconciliation module, three (42.8%) clinics had an EHR-based medication reconciliation function; however, only one of those clinics could demonstrate it during the pilot. Conclusion Clinics struggled in areas of advanced decision support such as drug age, drug laboratory, and drub monitoring. Most clinics did not have an EHR-based medication reconciliation function and this process was dependent on accessing patients' medication lists. Wider use of this tool could improve outpatient medication safety and can inform vendors about areas of improvement.

AIRA, an Artificial Intelligence Realistic Assistant that will save your time, a before-and-after study during Pandemic (Preprint)

2021 ◽  
Author(s):  
Kaio Bin ◽  
Adler Araújo Ribeiro Melo ◽  
José Guilherme Franco Da Rocha ◽  
Renata Pivi De Almeida ◽  
Vilson Cobello Junior ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Record ◽  
Medical Care ◽  
Health Screening ◽  
Urgent Care ◽  
Health Record ◽  
Before And After ◽  
Electronic Health ◽  
The Impact ◽  
Before And After Study

BACKGROUND AIRA is an AI designed to reduce the time that doctors dedicate filling out EHR, winner of the first edition of MIT Hacking Medicine held in Brazil in 2020. As a proof of concept, AIRA was implemented in administrative process before its application in a medical process. OBJECTIVE The aim of the study is to determinate the impact of AIRA by eliminating the Medical Care Registration (MCR) on Electronic Health Record (EHR) by Administrative Officer. METHODS This is a comparative before-and-after study following the guidance “Evaluating digital health products” from Public Health England. An Artificial Intelligence named AIRA was created and implemented at CEAC (Employee Attention Center) from HCFMUSP. A total of 25,507 attendances were evaluated along 2020 for determinate AIRA´s impact. Total of MCR, time of health screening and time between the end of the screening and the beginning of medical care, were compared in the pre and post AIRA periods. RESULTS AIRA eliminated the need for Medical Care Registration by Administrative Officer in 92% (p<0.0001). The nurse´s time of health screening increased 16% (p<0.0001) during the implementation, and 13% (p<0.0001) until three months after the implementation, but reduced in 4% three months after implementation (p<0.0001). The mean and median total time to Medical Care after the nurse’ Screening was decreased in 30% (p<0.0001) and 41% (p<0.0001) respectively. CONCLUSIONS The implementation of AIRA reduced the time to medical care in an urgent care after the nurse´ screening, by eliminating non-value-added activity the Medical Care Registration on Electronic Health Record (EHR) by Administrative Officer.

scholarly journals Opinions, perceptions and attitudes toward an electronic health record system among practicing nurses

2017 ◽  
Vol 8 (3) ◽  
pp. 12
Author(s):  
Ahmad H. Abu Raddaha ◽  
Arwa Obeidat ◽  
Huda Al Awaisi ◽  
Jahara Hayudini
Keyword(s):  
Electronic Health Record ◽  
Clinical Information System ◽  
Research Work ◽  
Healthcare Delivery ◽  
Future Research ◽  
Health Record ◽  
Randomized Sampling ◽  
Positive Attitudes ◽  
Electronic Health ◽  
The Impact

Background: Despite worldwide expanding implementation of electronic health record (EHR) systems, healthcare professionals conducted limited number of studies to explore factors that might facilitate or jeopardize using these systems. This study underscores the impact of nurses’ opinions, perceptions, and computer competencies on their attitudes toward using an EHR system.Methods: With randomized sampling, a cross-sectional exploratory design was used. The sample consisted of 169 nurses who worked at a public teaching hospital in Oman. They completed self-administered questionnaire. Several standardized valid and reliable instruments were utilized.Results: Seventy-four percent of our study nurses had high positive attitudes toward the EHR system. The least ranked perception scores (60.4%) were linked to perceiving that suggestions made by nurses about the system would be taken into account. Nurses who reported that the hospital sought for suggestions for customization of the system [OR: 2.54 (95% CI: 1.09, 5.88), p = .03], who found the system as an easy-to-use clinical information system [OR: 6.53 (95% CI: 1.72, 24.75), p = .01], who reported the presence of good relationship with the system’s managing personnel [OR: 3.59 (95% CI: 1.13, 11.36), p = .03] and who reported that the system provided all needed health information [OR: 2.97 (95% CI: 1.16, 7.62), p = .02] were more likely to develop high positive attitudes toward the system.Conclusions: To better develop plans to foster the EHR system’s use facilitators and overcome its usage barriers by nursing professionals, more involvement of nurses in system’s customization endeavors is highly suggested. When the system did not disrupt workflows, it would decrease clinical errors and expand nursing productivity. In order to maximize the utilization of the system in healthcare delivery, future research work to investigate the effect of the system on other healthcare providers and inter-professional communications is pressingly needed.

scholarly journals Beyond Getting Rid of Stupid Stuff in the Electronic Health Record (Beyond-GROSS): Protocol for a User-Centered, Mixed-Method Intervention to Improve the Electronic Health Record System

10.2196/25148 ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. e25148
Author(s):  
Ahmed Umar Otokiti ◽  
Catherine K Craven ◽  
Avniel Shetreat-Klein ◽  
Stacey Cohen ◽  
Bruce Darrow
Keyword(s):  
Health Care ◽  
Data Analysis ◽  
Electronic Health Record ◽  
Health Record ◽  
User Centered Design ◽  
Pilot Phase ◽  
Direct Input ◽  
Electronic Health ◽  
The Impact ◽  
User Centered

Background Up to 60% of health care providers experience one or more symptoms of burnout. Perceived clinician burden resulting in burnout arises from factors such as electronic health record (EHR) usability or lack thereof, perceived loss of autonomy, and documentation burden leading to less clinical time with patients. Burnout can have detrimental effects on health care quality and contributes to increased medical errors, decreased patient satisfaction, substance use, workforce attrition, and suicide. Objective This project aims to improve the user-centered design of the EHR by obtaining direct input from clinicians about deficiencies. Fixing identified deficiencies via user-centered design has the potential to improve usability, thereby increasing satisfaction by reducing EHR-induced burnout. Methods Quantitative and qualitative data will be obtained from clinician EHR users. The input will be received through a form built in a REDCap database via a link embedded in the home page of the EHR. The REDCap data will be analyzed in 2 main dimensions, based on nature of the input, what section of the EHR is affected, and what is required to fix the issue(s). Identified issues will be escalated to relevant stakeholders responsible for rectifying the problems identified. Data analysis, project evaluation, and lessons learned from the evaluation will be incorporated in a Plan-Do-Study-Act (PDSA) manner every 4-6 weeks. Results The pilot phase of the study began in October 2020 in the Gastroenterology Division at Mount Sinai Hospital, New York City, NY, which includes 39 physicians and 15 nurses. The pilot is expected to run over a 4-6–month period. The results of the REDCap data analysis will be reported within 1 month of completing the pilot phase. We will analyze the nature of requests received and the impact of rectified issues on the clinician EHR user. We expect that the results will reveal which sections of the EHR have the highest deficiencies while also highlighting issues about workflow difficulties. Perceived impact of the project on provider engagement, patient safety, and workflow efficiency will also be captured by evaluation survey and other qualitative methods where possible. Conclusions The project aims to improve user-centered design of the EHR by soliciting direct input from clinician EHR users. The ultimate goal is to improve efficiency, reduce EHR inefficiencies with the possibility of improving staff engagement, and lessen EHR-induced clinician burnout. Our project implementation includes using informatics expertise to achieve the desired state of a learning health system as recommended by the National Academy of Medicine as we facilitate feedback loops and rapid cycles of improvement. International Registered Report Identifier (IRRID) PRR1-10.2196/25148

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