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Effect of Synapse Medicine Decision Support on Inpatient Pharmacist Efficacy and Efficiency

Not Applicable
Not yet recruiting
Conditions
Liver Diseases
Gastrointestinal Diseases
Lung Diseases
Infections
Kidney Diseases
Heart Diseases
Interventions
Other: Synapse medicine platform
Registration Number
NCT05459155
Lead Sponsor
Brigham and Women's Hospital
Brief Summary

Adverse drug events (ADE) are common and dangerous in the hospital and following discharge to the ambulatory setting. One cause of ADEs in both settings is medication regimen inappropriateness, including polypharmacy, drug-drug interactions, and medications that are inappropriate or inappropriately dosed given patients' age, renal, and hepatic function. Hospitalization provides a good opportunity to investigate medication appropriateness given new or worsening conditions and available expertise. Inpatient pharmacists are medication experts and often round with medical teams, but they may not always have all the information available at their fingertips to make optimal recommendations regarding medication appropriateness for each patient. Clinical decision support to pharmacists at the point of care has potential to improve the speed, quantity, and quality of medication recommendations to inpatient teams; any subsequent improvements to medication regimen appropriateness have the potential to reduce ADEs in the hospital and after discharge.

Specific Aims and Objectives

Aim 1: Implement real-time decision support regarding medication regimen appropriateness among pharmacists who round with inpatient medical teams.

Aim 2: Determine the effects of this intervention on the number of medication regimen recommendations and time spent per recommendation

Aim 3: Evaluate the use and usability of the decision support tool and develop strategies to mitigate barriers and promote facilitators of implementation using mixed methods implementation science approaches.

Detailed Description

This will be a prospective pre-post mixed methods hybrid type 2 effectiveness-implementation study. The study will take place at BWH and at Vanderbilt University Medical Center (VUMC). The direct subjects will be the inpatient pharmacists (4 at each site) who round with general medicine teams. Patients will be indirect subjects as pharmacists provide medication recommendations regarding these patients to the clinicians on each team with or without the Synapse software. We estimate this number of patients to be 3 new admitted patients per day per team x 56 days x 8 teams = 1344 patients (672 at MGB sites). Patients can be any patients admitted to these general medicine service teams at BWH and VUMC. The pharmacists are trained hospital pharmacists who round with general medicine service teams and approve inpatient medication orders. There are no local site restrictions. VUMC will cede IRB approval to the MGB IRB.

Recruitment & Eligibility

Status
NOT_YET_RECRUITING
Sex
All
Target Recruitment
672
Inclusion Criteria
  • any patient that the inpatient pharmacists care for on the inpatient medical team they round with
Exclusion Criteria
  • N/A

Study & Design

Study Type
INTERVENTIONAL
Study Design
CROSSOVER
Arm && Interventions
GroupInterventionDescription
Pharmacist team post-interventionSynapse medicine platformThe direct subjects will be the inpatient pharmacists who round with general medicine teams and approve inpatient medication orders. They will be given full access to the Synapse Medicine medication decision support platform.
Primary Outcome Measures
NameTimeMethod
Change in the number of medication recommendations made per patientpre- and post-intervention periods: 4 weeks each per pharmacist

Change from pre- to post-intervention in the number of recommendations regarding medication changes made by pharmacists per patient

Secondary Outcome Measures
NameTimeMethod
Change in the time spent per recommendation per patientpre- and post-intervention periods: 4 weeks each per pharmacist

Change from pre- to post-intervention in time spent per patient evaluating regimen appropriateness divided by the number of recommendations for that patient

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