Review Complete

Reduction of inappropriate dosing-- testing a real-time prescriber decision support tool

OPG Proposal Status: 

 

1. The Health Outcome (s) include:  Primary:  prevalence of dosing in agreement with FDA package labelling (dose, frequency, with and without food; route, contraindications medication interactions); Secondary: if not in agreement, documentation of reasons for deviation from FDA package labelling; and post study: Exploratory: prescriber satisfaction with point of care decision support.

 

Use of the Electronic Medical Record to Make Care More Patient-Centered: Systematic Measurement and Feedback to Clinicians of Patients’ Symptoms and Quality of Life

OPG Proposal Status: 

Clinicians routinely ask patients “How are you doing?” but this aspect of the clinical encounter may not be optimal.  Patients with chronic conditions may feel unable to respond comprehensively, and clinicians may feel too busy to learn fully about their experiences.  Validated measures of patients’ reports have long been available, but are used mainly for research.

Leveraging APeX to improve antimicrobial stewardship by standardizing beta-lactam allergy evaluation

OPG Proposal Status: 

Leveraging APeX to standardize beta-lactam allergy management has the potential to improve clinical outcomes by decreasing length of hospital stay, decreasing alternative antibiotic use, and decreasing drug-resistant infections.

 

Objective:

To determine if electronic interventions aimed at decreasing barriers in APeX that prevent clinicians from following best clinical practice for beta-lactam allergy management improves antimicrobial stewardship.

 

Learning How to Reduce Clinician Alert Fatigue and Improve Patient Outcomes by Reducing Inappropriate C. difficile Testing and Treatment

Primary Author: Julia Adler-Milstein
OPG Proposal Status: 

Background and Motivation

Agile Prospective Validation and Trial of Real-Time Predictive Analytics

OPG Proposal Status: 

A.        Artificial intelligence and machine learning are enabling technologies for achieving learning healthcare system

A healthcare system with built-in artificial intelligence (AI) possesses a true learning capacity. Among various AI solutions, machine learning (ML) is a powerful tool to enable the learning that depends on abundant healthcare data in enterprise electronic health record (EHR), patient physiologic monitors and other medical device systems.

B. Unclear process to test and deploy UCSF-born innovative machine learning models

No Kidney Left Behind

OPG Proposal Status: 

The overarching goal of this project is to maximize value provided by the outpatient nephrology clinic.  We will use APEX patient data to identify high risk patients who would benefit the most from evaluations at the nephrology clinic.  For existing patients in the outpatient nephrology clinic, we will use APEX registry both to maintain high risk patients in nephrology clinic as well as to repatriate low risk patients to primary care clinic with anticipatory guidance.

Collaborative medical student shelf study guide

Proposal Type

Proposal Status: 
1. PROPOSAL SUMMARY/ABSTRACT 
We aim to develop a 200-300 question vignette-based study guide for neurology clerkship students to use in independent study to supplement their clinical experience. This study guide would aim to fill remaining gaps in the clerkship curriculum and preparedness for the shelf exam.

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