Informatics Research Seminar: Take Two Alerts and Call me in the Morning

October 24 @ 4:00 – 5:00 pm

Speaker: Eric Eisenstein, DBA
Presented from Duke University

Broadcast Link: Seminar 

 

Abstract:

The Institute of Medicine’s (IOM) Quality Chasm report highlighted 20 priority areas in which improvements in care delivery could significantly impact health quality. Although evidence-based pharmacotherapies (EBP) are a principal component of patient care in many of these areas (asthma, diabetes, depression, heart failure, COPD, hypertension, ischemic heart disease and stroke), 30% to 50% of patients do not take their medications as prescribed.

Medication adherence is a result of two processes: (1) clinicians prescribing EBP to their patients, and (2) patients taking their EBP medications as instructed by their clinicians. However, effective approaches for assuring that these processes are completed have not been well integrated into routine clinical care. This lack of effective integration has led to calls for new care models that address appropriate medication use and make it a part of the patient care process. We conducted a randomized trial of two clinical decision support (CDS) interventions to improved adherence in 2219 patients: patient adherence reports to providers (n=744), patient adherence reports to providers + email notices to care managers (n=736), and controls (739). The study design, patient characteristics and preliminary results from this trial will be presented during the seminar.

Biosketch:

Dr. Eisenstein is a member of the Duke Clinical Research Institute’s Outcomes Research and Assessment Group, with a special interest in understanding the relationships between complex interventions in health care systems and the long-term clinical and
economic outcomes of patients. In addition to his work in traditional health technology evaluation, Dr. Eisenstein has an interest in
evaluating information technologies as interventions in health care systems. In this regard, he has collaborated in the design and conduct of large-scale, randomized clinical trials to evaluate clinical decision support systems. The research objective in these studies has been to develop methods for evaluating health information technologies in practice-based settings using a “tool kit” of inexpensive, yet highly scalable methods that make use of data sets created as a byproduct of normal clinical and administrative operations. The use of these evaluation methods has been demonstrated in four clinical trials that include care process, clinical, economic, and quality of life measurements.