This study aims to evaluate the impact of spaced education, delivered via a smartphone application, on provider prescribing patterns.
As part of a medical center educational initiative at Vanderbilt University Medical Center (VUMC), two educational modules will be sent to prescribing providers through either email or short message service (SMS) text messaging. The first educational module consists of a set of multiple choice questions concerning best practices for prescribing intravenous fluids in the inpatient and perioperative setting. This module is based upon recent literature and specifically derived from the results of the Isotonic Solutions and Major Adverse Renal Events Trial (SMART) and Saline Against Lactated Ringer's or Plasma-Lyte in the Emergency Department (SALT-ED) trial, both published in the New England Journal of Medicine in 2018 and led by Vanderbilt investigators. Similarly, a second educational module concerning evidence-based pain management and opioid prescribing practices will be distributed via email or SMS text messaging. Participants will receive one question per day. If the participant does not answer the question correctly, they will receive the opportunity to attempt the question again after reviewing evidence-based education. All questions have been curated and reviewed by a panel of experts and piloted within VUMC for feasibility and acceptability. Key concepts are repeated in each module and questions are strategically ordered throughout each module to accomplish spaced education.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
369
Text Messaging or Email system
Vanderbilt University Medical Center
Nashville, Tennessee, United States
Median morphine milligram equivalents (MME) per opioid prescription
By extracting prescribing data for opioids from the electronic health records
Time frame: 8 months
Percentage of orders for balanced intravenous (IV) fluid solutions (i.e. not normal saline)
By extracting prescribing data for intravenous fluids from the electronic health records
Time frame: 8 months
Chloride levels in patients receiving intravenous fluid orders from a provider enrolled in the study
By extracting chloride level data from the electronic health records
Time frame: 8 months
Potassium levels in patients receiving intravenous fluid orders from a provider enrolled in the study
By extracting potassium level data from the electronic health records
Time frame: 8 months
Major Adverse Kidney Events by 30 days (MAKE 30) in patients receiving intravenous fluid orders from a provider enrolled in the study
By extracting data from the electronic health records
Time frame: 30 days
Length of stay for patients receiving an intravenous fluid order or an opioid prescription from a provider enrolled in the study.
By extracting length of stay data from the electronic health records
Time frame: 8 months
Length of stay in the intensive care unit (ICU) for patients receiving an intravenous fluid order or an opioid prescription from a provider enrolled in the study
By extracting ICU length of stay from the electronic health records
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Time frame: 8 months
Median number of pills per prescription for patients receiving an opioid prescription from a provider enrolled in the study
By extracting medication data from the electronic health records
Time frame: 8 months
Percent of opioid prescriptions (inpatient) that also had a scheduled (not pro re nata (PRN)) non-opioid (APAP, nonsteroidal anti-inflammatory drugs (NSAIDs), gamma-Aminobutyric acid (GABA), muscle relaxant, etc.)
By extracting medication data from the electronic health records
Time frame: 8 months
Percent of opioid prescriptions (discharge) that also had a scheduled (not PRN) non-opioid (APAP, NSAIDs, GABA, muscle relaxant, etc.)
By extracting medication data from the electronic health records
Time frame: 8 months
Number of Rapid Response Team calls (RRT s) indexed to the number of patients cared for per prescriber (evaluated by level of engagement of the learner with QuizTime)
By extracting RRT calls from the electronic health records
Time frame: 8 months