Individualizing HbA1c targets for patients with diabetes: impact of an automated algorithm within a primary care network.

AIMS: To develop glycaemic goal individualization algorithms and assess potential impact on a healthcare system and different segments of the population with diabetes. METHODS: A cross-sectional observational study of patients with diabetes in a primary care network age > 18 years with an HbA1c measured between 1 January and 31 December 2011. We applied diabetes guidelines to create targeted algorithms 1 and 2, which assigned HbA1c goals based on age, duration of diabetes (< 15 years or < 10 years), diabetes complications and Charlson co-morbidity score (< 6 or < 4) [targeted algorithm 2 was designed to assign more patients a goal < 64 mmol/mol (8.0%) than targeted algorithm 1]. Each patient's HbA1c was compared with these targeted goals and to the 'standard' goal < 53 mmol/mol (7.0%). Agreement was tested using McNemar's test. RESULTS: Overall, 55.7% of 12 199 patients would be considered controlled under the 'standard' approach, 61.2% under targeted algorithm 1 and 67.5% under targeted algorithm 2. Targeted algorithm 1 reclassified 1213 (23.6%) patients considered uncontrolled under the standard approach to controlled, P < 0.001. Targeted algorithm 2 reclassified 1844 (35.2%) patients, P < 0.001. Compared with those controlled under the standard goal, there was no significant difference in the proportion of those controlled using targeted goals who had Medicaid, had less than a high school diploma or received primary care in a federally qualified health centre. CONCLUSIONS: Two automated targeted algorithms would reclassify one quarter to one third of patients from uncontrolled to controlled within a primary care network without differentially affecting vulnerable patient subgroups.

Intensification of diabetes medication and risk for 30-day readmission.

AIM: To examine the association of in-hospital diabetes regimen intensification with subsequent 30-day risk for unplanned readmission/emergency department admission. METHODS: We retrospectively studied 1949 adults with Type 2 diabetes receiving primary care within an academic health network admitted to the hospital between January 2007 and December 2009. Glucose therapy intensification was defined as new start of insulin or oral hypoglycaemic agents, or addition of prandial insulin or insulin mixtures. The association of glucose therapy intensification with subsequent 30-day risk for unplanned readmission/emergency department admission was examined, with focus on medicine service patients with poorly controlled glycaemia (baseline HbA(1c) ≥ 64 mmol/mol). RESULTS: One in six patients (324/1949, 17%) had early readmission/emergency department admission. Compared with patients without early readmission, readmitted patients were more often male (58 vs. 52%, P = 0.03), had higher Charlson co-morbidity score [mean (sd) 3.0 (2.0) vs. 2.8 (1.8), P = 0.02], longer length of stay [5 (4.4) vs. 3.9 (3.3) days, P < 0.01] and were more often discharged home with nursing services (38 vs. 32%, P = 0.03). Overall, glucose therapy intensification was not associated with early hospital readmission/emergency department admission (odds ratio 0.94, 95% CI 0.64-1.37, P = 0.74). However, among medicine service patients with baseline HbA(1c) ≥ 64 mmol/mol (8%), glucose therapy intensification was associated with a significantly decreased early readmission risk (adjusted odds ratio 0.33, 95% CI 0.12-0.88, P = 0.03) and lower post-discharge HbA(1c) {mean decrease (sd): 20 (26) mmol/mol [1.8 (2.4)%] vs. 7 (15) mmol/mol [0.6 (1.4)%], P < 0.01}. CONCLUSIONS: Diabetes medical regimen intensification during hospitalization was not associated with early readmission. Among patients with elevated HbA(1c) , glucose therapy intensification was associated with a decreased 30-day readmission/emergency department admission risk and lower outpatient HbA(1c) levels. Our findings support the safety and durable impact of diabetes regimen optimization during hospital admission.

Symptoms of depression prospectively predict poorer self-care in patients with Type 2 diabetes.

AIMS: To examine prospectively the association of depression symptoms with subsequent self-care and medication adherence in patients with Type 2 diabetes mellitus. METHODS: Two hundred and eight primary care patients with Type 2 diabetes completed the Harvard Department of Psychiatry/National Depression Screening Day Scale (HANDS) and the Summary of Diabetes Self-Care Activities (SDSCA) at baseline and at follow-up, an average of 9 months later. They also self-reported medication adherence at baseline and at a follow-up. RESULTS: Baseline HANDS scores ranged from 0 to 27, with a mean score of 5.15 +/- 4.99. In separate linear regression models that adjusted for baseline self-care, patients with higher levels of depressive symptoms at baseline reported significantly lower adherence to general diet recommendations and specific recommendations for consumption of fruits and vegetables and spacing of carbohydrates; less exercise; and poorer foot care at follow-up (beta ranging from -0.12 to -0.23; P < 0.05). Similarly, each one-point increase in baseline HANDS score was associated with a 1.08-fold increase in the odds of non-adherence to prescribed medication at follow-up (95% confidence interval 1.001, 1.158, P = 0.047). Increases in depression scores over time also predicted poorer adherence to aspects of diet and exercise. CONCLUSIONS: Depressive symptoms predict subsequent non-adherence to important aspects of self-care in patients with Type 2 diabetes, even after controlling for baseline self-care. Although the relationship between symptoms of depression and poorer diabetes self-care is consistent, it is not large, and interventions may need to address depression and self-care skills simultaneously in order to maximize effects on diabetes outcomes.

Association of diabetes-related emotional distress with diabetes treatment in primary care patients with Type 2 diabetes.

AIMS: To characterize the determinants of diabetes-related emotional distress by treatment modality (diet only, oral medication only, or insulin). METHODS: A total of 815 primary care patients with Type 2 diabetes completed the Problem Areas in Diabetes (PAID) Scale and other questions. We linked survey data to a diabetes clinical research database and used linear regression models to assess the associations of treatment with PAID score. RESULTS: PAID scores were significantly higher among insulin-treated (24.6) compared with oral-treated (17.8, P < 0.001) or diet-treated patients (14.7, P < 0.001), but not different between oral- vs. diet-treated patients (P = 0.2). Group scores remained similar, but the statistical significance of their differences was reduced and ultimately eliminated after sequential adjustment for diabetes severity, HbA(1c), body mass index, regimen adherence, and self-blood-glucose monitoring. Insulin-treated patients reported significantly higher distress than oral- or diet-treated patients on 16 of 20 PAID items. 'Worrying about the future' and 'guilt/anxiety when ... off track with diabetes' were the top two serious problems (PAID >or= 5) in all treatment groups. Not accepting diabetes diagnosis was a top concern for oral- and diet-treated patients, and unclear management goals distressed diet-treated patients. CONCLUSIONS: Primary care patients treated with insulin reported higher diabetes-related emotional distress compared with oral- or diet-treated patients. Greater distress was largely explained by greater disease severity and self-care burdens. To improve diabetes-specific quality of life, clinicians should address patients' sense of worry and guilt, uncertain acceptance of diabetes diagnosis, and unclear treatment goals.

Correlates of health-related quality of life in type 2 diabetes.

AIMS/HYPOTHESIS: We assessed the impact of medical comorbidities, depression, and treatment intensity on quality of life in a large primary care cohort of patients with type 2 diabetes. METHODS: We used the Health Utilities Index-III, an instrument that measures health-related quality of life based on community preferences in units of health utility (scaled from 0=death to 1.0=perfect health), in 909 primary care patients with type 2 diabetes. Demographic and clinical correlates of health-related quality of life were assessed. RESULTS: The median health utility score for this population was 0.70 (interquartile range 0.39-0.88). In univariate analyses, older age, female sex, low socioeconomic status, cardiovascular disease, microvascular complications, congestive heart failure, peripheral vascular disease, chronic lung disease, depression, insulin use and number of medications correlated with decreased quality of life, while obesity, hypertension and hypercholesterolaemia did not. In multiple regression analyses, microvascular complications, heart failure and depression were most strongly related to decreased health-related quality of life, independently of duration of diabetes; in these models, diabetes patients with depression had a utility of 0.59, while patients without symptomatic comorbidities did not have a significantly reduced quality of life. Treatment intensity remained a significant negative correlate of quality of life in multivariable models. CONCLUSIONS/INTERPRETATION: Patients with type 2 diabetes have a substantially decreased quality of life in association with symptomatic complications. The data suggest that treatment of depression and prevention of complications have the greatest potential to improve health-related quality of life in type 2 diabetes.

Predictors of costs of caring for elderly patients discharged with heart failure.

BACKGROUND: Investments in programs to improve outcomes and reduce readmissions for patients who survive hospitalization with heart failure will be economically most favorable for those who have the highest risk. Little information is available, however, to stratify the risk of these patients incurring costs after discharge. In this study, we sought to determine correlates of costs in a representative sample of patients with heart failure in the 6 months after discharge. METHODS: We reviewed medical records of 2181 patients aged > or = 65 years who were discharged alive from 18 Connecticut hospitals in 1994 and 1995 with a principal discharge diagnosis of heart failure. Outcomes 6 months after discharge, including all-cause readmission and cost, heart failure-related readmission and cost, and death, were obtained from the Medicare administrative database. A 2-stage sample selection model was used to identify the independent correlates of cost. Risk scores were calculated to identify subsets of patients at risk for generating high costs. RESULTS: On average, patients discharged with heart failure incurred costs of $2388 resulting from heart failure-related admissions and $7101 resulting from admissions from any cause during the 6 months after discharge. An average admission for heart failure cost $7174, whereas an admission resulting from any cause cost $8589. The multivariate models explained 7% of the variation in cost, although clinical characteristics such as recent heart failure admissions, kidney failure, and hypertension were significant independent correlates of increased cost. Older age and a history of stroke were independently associated with decreased cost. Patients without any of the risk factors associated with increased costs still incurred $1500 to $5000, on average, in the 6 months after discharge. CONCLUSIONS: Patients with heart failure generate substantial hospital costs in the 6 months after discharge. Given the emerging evidence for effective programs to reduce readmission, investments in interventions that produce even modest reductions in risk would be economically favorable.