Purpose

To perform a systematic review of the validity of algorithms for identifying cerebrovascular accidents (CVAs) or transient ischemic attacks (TIAs) using administrative and claims data.

Methods

PubMed and Iowa Drug Information Service (IDIS) searches of the English language literature were performed to identify studies published between 1990 and 2010 that evaluated the validity of algorithms for identifying CVAs (ischemic and hemorrhagic strokes, intracranial hemorrhage and subarachnoid hemorrhage) and/or TIAs in administrative data. Two study investigators independently reviewed the abstracts and articles to determine relevant studies according to pre-specified criteria.

Results

A total of 35 articles met the criteria for evaluation. Of these, 26 articles provided data to evaluate the validity of stroke, 7 reported the validity of TIA, 5 reported the validity of intracranial bleeds (intracerebral hemorrhage and subarachnoid hemorrhage), and 10 studies reported the validity of algorithms to identify the composite endpoints of stroke/TIA or cerebrovascular disease. Positive predictive values (PPVs) varied depending on the specific outcomes and algorithms evaluated. Specific algorithms to evaluate the presence of stroke and intracranial bleeds were found to have high PPVs (80% or greater). Algorithms to evaluate TIAs in adult populations were generally found to have PPVs of 70% or greater.

Conclusions

The algorithms and definitions to identify CVAs and TIAs using administrative and claims data differ greatly in the published literature. The choice of the algorithm employed should be determined by the stroke subtype of interest.

Objective

The prevalence of coronary heart disease increases with advancing age. However, there is evidence that older patients and women were underrepresented in coronary heart disease clinical trials prior to the year 2000. To determine whether the participation of the elderly and women in published clinical trials has increased during recent years, we conducted a review of recent clinical trials of acute coronary syndromes (ACS).

Design and Measurements

We conducted a search of MEDLINE and the Cochrane Central Register of Controlled Trials to identify clinical trials of ACS published from May, 2007 to May, 2009. Trials were excluded if they enrolled <50 patients, were sub-studies of previously published trials, or initiated treatment more than 3 weeks after the acute cardiac event.

Results

Eighty trials, enrolling a total of 68,016 subjects, met our pre-established criteria. Nearly 30% (n= 23) had explicit exclusion criteria based on age. Only 13.8% of study participants were ≥75 years and 27.7% of subjects were women. These percentages remain below the representation of all U.S. adults experiencing an ACS in recent years who were ≥75 years of age (41.9%) or women (41.5%). The average age of all study participants was 61.6 years (SD=3.8). There was a significant association between the mean age of a study participant and the proportion of women enrolled in the trial.

Conclusion

Older adults and women remain underrepresented in recent clinical trials of patients hospitalized with an ACS. These exclusions may hinder efforts to inform evidence-based clinical decision-making in these high-risk patient populations.

Background

An estimated 20–50% of patients do not take medications as recommended. Accepting a doctor’s recommendation is the first step in medication adherence, yet little is known about patients’ beliefs and preferences about how medications are prescribed.

Objective

To explore patients’ beliefs and preferences about medication prescribing to understand factors that might affect medication adherence.

Methods

Fifty members from 2 health plans in Massachusetts participated in in-depth telephone interviews. Participants listened to an audio-vignette of a doctor prescribing a medication to a patient and were asked a series of questions related to the vignette. Responses were reviewed in an iterative process to identify themes related to participants’ beliefs and preferences about medication prescribing.

Results

Participants’ beliefs and preferences about medication prescribing encompassed 3 major areas: patient–doctor relationships, outside influences, and professional expertise. Important findings included participants’ concerns about the pharmaceutical industry’s influence on doctors’ prescribing practices and beliefs that there is a clear “best” medication for most health problems.

Conclusions

Patients’ beliefs and preferences about medication prescribing may affect medication adherence. Additional empiric studies that explore whether doctors’ relationships with pharmaceutical representatives impact medication adherence by affecting trust are indicated. In addition, it would be worthwhile to explore whether discussions between patients and doctors regarding equipoise (no clear scientific evidence for 1 treatment choice over another) affect medication adherence.