DURHAM, NC — Even though HMG-CoA reductase inhibitors (statins) lower cholesterol and prevent cardiovascular disease, nearly half of patients stop taking statin medications one year after they are prescribed.
A study published by PLoS One noted that discontinuation of the medication leads to higher cholesterol levels, increased cardiovascular risk and costs due to excess hospitalizations. One way to individualize therapy and improve adherence, according to the research, is to identify patients at highest risk for not following their long-term statin regimen.1
A study team from Duke University and the Air Force Medical Operations Agency at Joint Base Lackland-Kelly, TX, focused on electronic health records (EHR) as an increasingly common source of data that are challenging to analyze but have potential for generating more accurate predictions of disease risk.
Their study sought to create an EHR based model for statin adherence and link it to biologic and clinical outcomes in patients receiving statin therapy. To do that, researchers gathered EHR data from the MHS, which maintains administrative data for active duty, retirees and dependents of the U.S. military who receive health care benefits.
With data collected from patients prescribed their first statin prescription in 2005 and 2006, baseline billing, laboratory, and pharmacy claims data were pulled together from the two years leading up to the first statin prescription. Follow-up statin prescription refill data was used to define the adherence outcome, defined as more than 80% days covered. The study team also looked at overall disease risk and statin adherence. Overall, the analytical dataset included about 139,000 patients.
Predicted statin adherence for each patient was subsequently used to correlate with cholesterol lowering and hospitalizations for cardiovascular disease during the five year follow-up.
Results indicated that the predicted statin adherence was independently associated with greater cholesterol lowering (correlation = 0.14, p < 1e-20) and lower hospitalization for myocardial infarction, coronary artery disease, and stroke (hazard ratio = 0.84, p = 1.87E-06).
“Electronic health records data can be used to build a predictive model of statin adherence that also correlates with statins’ cardiovascular benefits,” the study team concluded.
- Lucas JE, Bazemore TC, Alo C, Monahan PB, Voora D. An electronic health record based model predicts statin adherence, LDL cholesterol, and cardiovascular disease in the United States Military Health System. PLoS One. 2017 Nov 20;12(11):e0187809. doi: 10.1371/journal.pone.0187809. eCollection 2017. PubMed PMID: 29155848; PubMed Central PMCID: MC5695792.
Welcome news indeed! Our facility did a recent study in response to PCP request. My November 2017 count, as a primary care physician, was 3538. Divided by the 20 business days for Nov equals 177/day. By the above reported time burden per alert, assuming maximum efficiency following a busy day of patient care, this adds minimum 2 1/2 to 3 hours to a clinical day and does not include additional time yet for processing patient outside records, reading EKGs, or mandatory TMS training. A certain recipe for physician burn out.
I didn’t understand the relationship between the EMR in the title of this article and the content of the article itself.
Welcome news indeed! Our facility did a recent study in response to PCP request. My November 2017 count, as a primary care physician, was 3538. Divided by the 20 business days for Nov equals 177/day. By the above reported time burden per alert, assuming maximum efficiency following a busy day of patient care, this adds minimum 2 1/2 to 3 hours to a clinical day and does not include additional time yet for processing patient outside records, reading EKGs, or mandatory TMS training. A certain recipe for physician burn out.
I didn’t understand the relationship between the EMR in the title of this article and the content of the article itself.