Assessment of a Medication Reconciliation Program on Transitional Care

Overview

The purpose of this study is to assess and compare the effectiveness of the Kaiser Permanente Colorado's (KPCO) Call Center's Medication Reconciliation Program and standard care in regards to their impacts on emergency department (ED) and urgent care visits, inpatient rehospitalizations, and adherence to preferred, formulary medications.

This study will be a health services evaluation. This study will be a pilot study utilizing a randomized controlled trial design. This study will utilize secondary data collected from existing KPCO databases to assess outcomes. Interventions will occur over a one-month period. The study will take approximately twelve months to conduct including the data collection and analysis, results interpretation, and manuscript and report preparation. The duration of intervention group subject participation will be limited to the length of the medication reconciliation counseling phone call and the 3-month follow-up period while the duration of control group subject participation will be limited to the 3-month follow-up period. KPCO internists discharging patients on medications to ambulatory care from either the Good Samaritan or St. Joseph hospitals over a four-week period will send discharge orders to the CPCC via Health Connect. Project-dedicated CPCC pharmacists will utilize the inclusion and exclusion criteria to determine patient eligibility. Project-dedicated CPCC staff will make several attempts at varying times during the 24 hours following reception of the discharge note in Health Connect to conduct the telephonic consent process among eligible patients. If a patient can not be contacted after several attempts, the staff member will leave a HIPAA-compliant message, if possible, to request either the patient or his/her caregiver call the CPCC. If the subject doesn't not contact the CPCC after being left such a message, the staff member will make two attempts the following day to contact the subject and/or his/her caregiver. Patients consenting to participate will be categorized by hospital and, based on category, randomly assigned to the intervention or control group. Project-dedicated pharmacists will review intervention group subjects' discharge medication orders, identify discrepancies between their primary care regimen and the hospital discharge orders, and collaborate with the patient's primary care physician or discharging provider to reconcile any discrepancies. Project-dedicated pharmacists will make several telephonic attempts at varying times during the 24 hours post-assignment to contact an intervention group subject and/or his/her caregiver to execute the medication review counseling after performing the medication review. If the subject can not be contacted after several attempts, the pharmacist will leave a HIPAA-compliant message, if possible, to request either the subject or his/her caregiver call the CPCC. If the subject doesn't not contact the CPCC in the day after being left such a message, the pharmacist will make two attempts per day for two more days to contact the subject and/or his/her caregiver. Assignment dates will be used as an index dates from which rolling baseline and follow-up periods will be determined. Data will be analyzed on an intention-to-treat basis. Baseline subject characteristics and study outcomes for each of the cohorts will be reported as means, medians, and standard deviations for interval- and ratio-level variables (e.g., age) and proportions for nominal- and ordinal-level data (e.g., gender, hospital discharge diagnoses, post-discharge ED and urgent care visits, IP readmission). Interval-and ratio-level variables will be assessed for normality of their distributions. Appropriate parametric (e.g., independent samples t-test) or non-parametric (e.g., Wilcoxon rank-sum test) statistical tests will then be performed to assess differences in mean or median values. Ordinal-level and nominal-level will be assessed with the Pearson's chi-square statistical test. Logistic regression modeling will be used to assess the relationships between the group and binary data (e.g., ED and urgent care visits, receiving a non-preferred formulary agent) while adjusting for potential confounders (e.g., age, hospital discharge diagnosis, gender, CDS).

Conditions

Interventions

Eligibility

Locations (1)

Outcomes