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ItemThe "cost" of treating to target: cross-sectional analysis of patients with poorly controlled type 2 diabetes in Australian general practiceFurler, J ; Hii, JWS ; Liew, D ; Blackberry, I ; Best, J ; Segal, L ; Young, D (BMC, 2013-03-08)BACKGROUND: To describe the current treatment gap in management of cardiovascular risk factors in patients with poorly controlled type 2 diabetes in general practice as well as the associated financial and therapeutic burden of pharmacological treatment. METHODS: Cross-sectional analysis of data from the Patient Engagement and Coaching for Health trial. This totalled 473 patients from 59 general practices with participants eligible if they had HbA1c > 7.5%. Main outcome measures included proportions of patients not within target risk factor levels and weighted average mean annual cost for cardiometabolic medications and factors associated with costs. Medication costs were derived from the Australian Pharmaceutical Benefits Schedule. RESULTS: Average age was 63 (range 27-89). Average HbA1c was 8.1% and average duration of diabetes was 10 years. 35% of patients had at least one micro or macrovascular complication and patients were taking a mean of 4 cardio-metabolic medications. The majority of participants on treatment for cardiovascular risk factors were not achieving clinical targets, with 74% and 75% of patients out of target range for blood pressure and lipids respectively. A significant proportion of those not meeting clinical targets were not on treatment at all. The weighted mean annual cost for cardiometabolic medications was AUD$1384.20 per patient (2006-07). Independent factors associated with cost included age, duration of diabetes, history of acute myocardial infarction, proteinuria, increased waist circumference and depression. CONCLUSIONS: Treatment rates for cardiovascular risk factors in patients with type 2 diabetes in our participants are higher than those identified in earlier studies. However, rates of achieving target levels remain low despite the large 'pill burden' and substantial associated fiscal costs to individuals and the community. The complexities of balancing the overall benefits of treatment intensification against potential disadvantages for patients and health care systems in primary care warrants further investigation.
ItemNo Preview AvailableSelf-Rated Health and Long-Term Prognosis of DepressionAmbresin, G ; Chondros, P ; Dowrick, C ; Herrman, H ; Gunn, JM (ANNALS FAMILY MEDICINE, 2014-01-01)PURPOSE: Indicators of prognosis should be considered to fully inform clinical decision making in the treatment of depression. This study examines whether self-rated health predicts long-term depression outcomes in primary care. METHODS: Our analysis was based on the first 5 years of a prospective 10-year cohort study underway since January 2005 conducted in 30 randomly selected Australian primary care practices. Participants were 789 adult patients with a history of depressive symptoms. Main outcome measures include risks, risk differences, and risk ratios of major depressive syndrome (MDS) on the Patient Health Questionnaire. RESULTS: Retention rates during the 5 years were 660 (84%), 586 (74%), 560 (71%), 533 (68%), and 517 (66%). At baseline, MDS was present in 27% (95% CI, 23%-30%). Cross-sectional analysis of baseline data showed participants reporting poor or fair self-rated health had greater odds of chronic illness, MDS, and lower socioeconomic status than those reporting good to excellent self-rated health. For participants rating their health as poor to fair compared with those rating it good to excellent, risk ratios of MDS were 2.10 (95% CI, 1.60-2.76), 2.38 (95% CI, 1.77-3.20), 2.22 (95% CI, 1.70-2.89), 1.73 (95% CI, 1.30-2.28), and 2.15 (95% CI, 1.59-2.90) at 1, 2, 3, 4, and 5 years, after accounting for missing data using multiple imputation. After adjusting for age, sex, multimorbidity, and depression status and severity, self-rated health remained a predictor of MDS up to 5 years. CONCLUSIONS: Self-rated health offers family physicians an efficient and simple way to identify patients at risk of poor long-term depression outcomes and to inform therapeutic decision making.