Doganer, Yusuf C

AbstractRationale, aims and objectivesAchieving control over elevated lipid parameters, particularly low‐density lipoprotein (LDL)‐cholesterol, is an acknowledged quality indicator in primary care. The Centers for Disease Control and Prevention (CDC)'s model for investigation of outbreaks (person–place–time) can be applied to the analysis of quality indicators.MethodsA sample of 322 family medicine patients for whom lipid levels were ordered was extracted. LDL > 100 mg/dL was cross‐tabulated by personal characteristics [age group, gender, body mass index (BMI), diagnoses], month (time) and ordering department (place).ResultsAge (except one age category), gender, time and location were not related to LDL > 100 mg/dL after adjustment for covariates. All levels of BMI above normal elevated the risk of LDL > 100 mg/dL [BMI 25–29.9: odds ratio (OR) = 3.41, confidence interval (CI) = 1.61–7.23, P = 0.0014; BMI 30–34.9: OR = 2.93, CI = 1.28–6.70, P = 0.0109; BMI ≥ 35: OR = 2.75, CI = 1.19–6.37, P = 0.0181]. Patients with coronary artery disease (CAD) and diabetes mellitus (DM) were at reduced risk for LDL > 100 mg/dL (CAD: OR = 0.47, CI = 0.24–0.91, P = 0.0254; DM: OR = 0.28, CI = 0.14–0.55, P = 0.0002).ConclusionAn outbreak investigation model is useful for analysing variations in this quality indicator. Patients with higher BMI and those not diagnosed with CAD or DM type I/II may be considered for intensified lipid lowering using quality improvement efforts. These might include counselling for lifestyle changes or medication therapy depending upon their calculated cardiac risk.

AbstractBackgroundThe collaborative care model (CCM) has been consistently shown to achieve effectiveness in depression management compared to usual care. In the present study, we aimed to determine the impact of age on cost metrics in patients who were treated with CCM for 6 months after a diagnosis of depression.MethodsThe upper quartile of age was 50 years and older (n = 56), and the comparison group was composed of patients in the three younger quartiles, aged 18–49 years (n = 163).ResultsPatients in the older age group had an elevated median Current Procedure Terminology cost rank of 255.5 compared to 168.0 for the younger patients (P < 0.001). Multiple logistic regression analysis revealed that being in the upper quartile of age (≥50 years) (odds ratio = 2.272, 95% confidence interval: 1.064–4.851; P = 0.034) and having higher numbers of clinical visits 6 months prior to index (odds ratio = 1.209, 95% confidence interval: 1.118–1.307; P < 0.001) were significant predictor variables of being cost rank outliers (>80th percentile) in patients with CCM.ConclusionMedical cost utilization in the 6 months after diagnosis of depression was significantly higher in patients in the upper age quartile (≥50 years) enrolled in CCM than those in the lower quartiles (age <50).

AbstractRationale, aims and objectivesThis study was undertaken to assess the frequency of lipid screening in comparison with the United States Preventive Services Task Force guideline in a sample of family medicine patients. In addition, we sought to determine the association between testing frequency and achievement of lipid targets.MethodsA random sample was extracted from 271 patients from among all patients cared for in our Department of Family Medicine for whom lipid screening was ordered from March to September 2012 and who had ≥2 well‐defined cardiovascular risk factors. Lipid testing frequency was classified in three ways: semi‐annual or less often (0–12 tests over 6 years), annual or less often (0–6 tests), or biennial (0–3 tests).ResultsMultiple logistic regression analysis revealed that the predictors of lipid screening more often than semi‐annually were age ≥60 years [odds ratio (OR) = 3.7] and diabetes mellitus (DM) (OR = 30.6). Predictors of screening more often than annually were DM (OR = 4.3), hypertension (OR = 2.1), family history of premature coronary artery disease (OR = 5.6) and statin treatment (OR = 3.5). Lipid goal attainment was not associated with testing frequency except with regard to low‐density lipoprotein levels (P = 0.043, P < 0.001, P = 0.005, by semi‐annual, annual and biennial, respectively) and total cholesterol levels (P = 0.015, P = 0.025 by semi‐annual and annual, respectively).ConclusionsQuestionable high frequency of lipid testing was detected even when the more conservative approach of annual monitoring was assumed. Frequency of testing was not associated with goal attainment for most parameters. Physicians should request the lipid testing based on overall risk assessment and person variability in accordance with published guidelines.

AbstractRationale, aims and objectivesThe impact of seasonal variation on clinical remission in patients with depression has not been well studied. The hypothesis for this study was that the clinical remission rate would be lower in the winter comparing to the other seasons, specifically evaluated by gender.MethodsThe study cohort comprised 2873 primary care patients with depression as a longitudinal retrospective chart review analysis. The sample was limited to patients who were continuing in care; dropouts were excluded from the analysis.ResultsMultivariate logistic regression analysis of the independent variables for those participants who achieved clinical remission demonstrated that for the male patients, the season of diagnosis did not impact the rate of remission at 6 months while controlling for all other independent variables. For female patients, those that were diagnosed with depression in the fall had increased likelihood of 6‐month remission compared with those patients diagnosed in the winter months (OR 1.300, CI 1.006–1.680, P = 0.045) and the spring and summer patients were not significantly different in their outcome rates. When both genders were combined, the odds of remission at 6 months were not statistically significant for any season of diagnosis.ConclusionsThis study demonstrates that in patients who were continuing care, women who were diagnosed with major depression or dysthymia in the fall season have improved 6‐month clinical outcome of remission compared with those women diagnosed in the winter, when controlling for demographic and clinical characteristics. This effect was not seen in men or when the genders were combined into a single cohort. The assessment of the seasonality effect on depression outcomes requires further long‐term follow‐up studies.