Medication nonadherence, inconsistent patient self-monitoring, and inadequate treatment adjustment exacerbate poor disease control. In a collaborative, team-based, care management program for complex patients (TEAMcare), we assessed patient and physician behaviors (medication adherence, self-monitoring, and treatment adjustment) in achieving better outcomes for diabetes, coronary heart disease, and depression.A randomized controlled trial was conducted (2007-2009) in 14 primary care clinics among 214 patients with poorly controlled diabetes (glycated hemoglobin [HbA(1c)] ≥8.5%) or coronary heart disease (blood pressure >140/90 mm Hg or low-density lipoprotein cholesterol >130 mg/dL) with coexisting depression (Patient Health Questionnaire-9 score ≥10). In the TEAMcare program, a nurse care manager collaborated closely with primary care physicians, patients, and consultants to deliver a treat-to-target approach across multiple conditions. Measures included medication initiation, adjustment, adherence, and disease self-monitoring.Pharmacotherapy initiation and adjustment rates were sixfold higher for antidepressants (relative rate [RR] = 6.20; P <.001), threefold higher for insulin (RR = 2.97; P <.001), and nearly twofold higher for antihypertensive medications (RR = 1.86, P <.001) among TEAMcare relative to usual care patients. Medication adherence did not differ between the 2 groups in any of the 5 therapeutic classes examined at 12 months. TEAMcare patients monitored blood pressure (RR = 3.20; P <.001) and glucose more frequently (RR = 1.28; P = .006).Frequent and timely treatment adjustment by primary care physicians, along with increased patient self-monitoring, improved control of diabetes, depression, and heart disease, with no change in medication adherence rates. High baseline adherence rates may have exerted a ceiling effect on potential improvements in medication adherence.
Advanced cytopathology training has finally obtained official recognition in Canada, having recently been assigned the newly developed status of "Area of Focused Competence" by the Royal College of Physicians and Surgeons of Canada.It is hoped that the trainees who
While the 2011 implementation of "meaningful use" legislation for certified electronic health records (EHRs) promises to change quality reporting by overcoming data capture issues affecting quality measurement, the magnitude of this effect is unclear. We compared the measured quality of laboratory monitoring of Healthcare Effectiveness Data and Information Set (HEDIS) medications based on specifications that (1) include and exclude patients hospitalized in the measurement year and (2) use physician test orders and patient test completion.Cross-sectional study.Among patients 18 years and older in a large multispecialty group practice utilizing a fully implemented EHR between January 1, 2008, and July 31, 2008, we measured the prevalence of ordering and completion of laboratory tests monitoring HEDIS medications (cardiovascular drugs [angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, digoxin, and diuretics] and anticonvulsants [carbamazepine, phenobarbital, phenytoin, and valproic acid]).Measures excluding hospitalized patients were not statistically significantly different from measures including hospitalized patients, except for digoxin, but this difference was not clinically significant. The prevalence of appropriate monitoring based on test orders typically captured in the EHR was statistically significantly higher than the prevalence based on claims-based test completions for cardiovascular drugs.HEDIS quality metrics based on data typically collected from claims undermeasured quality of medication monitoring compared to EHR data. The HEDIS optional specification excluding hospitalized patients from the monitoring measure does not have a significant impact on reported quality. Integration of EHR data into quality measurement may significantly change some organizations' reported quality of care.
Correction of echo planar imaging (EPI)-induced distortions (called "unwarping") improves anatomical fidelity for diffusion magnetic resonance imaging (MRI) and functional imaging investigations. Commonly used unwarping methods require the acquisition of supplementary images during the scanning session. Alternatively, distortions can be corrected by nonlinear registration to a non-EPI acquired structural image. In this study, we compared reliability using two methods of unwarping: (1) nonlinear registration to a structural image using symmetric normalization (SyN) implemented in Advanced Normalization Tools (ANTs); and (2) unwarping using an acquired field map. We performed this comparison in two different test-retest data sets acquired at differing sites (N = 39 and N = 32). In both data sets, nonlinear registration provided higher test-retest reliability of the output fractional anisotropy (FA) maps than field map-based unwarping, even when accounting for the effect of interpolation on the smoothness of the images. In general, field map-based unwarping was preferable if and only if the field maps were acquired optimally.
