Using neighborhood-level census data to predict diabetes progression in patients with laboratory-defined prediabetes

Context Research on predictors of clinical outcomes usually focuses on the impact of individual patient factors, despite known relationships between neighborhood environment and health. Objective To determine whether US census information on where a patient resides is associated with diabetes development among patients with prediabetes. Design Retrospective cohort study of all 157,752 patients aged 18 years or older from Kaiser Permanente Northern California with laboratory-defined prediabetes (fasting plasma glucose, 100 mg/dL-125 mg/dL, and/or glycated hemoglobin, 5.7%-6.4%). We assessed whether census data on education, income, and percentage of households receiving benefits through the US Department of Agriculture’s Supplemental Nutrition Assistance Program (SNAP) was associated with diabetes development using logistic regression controlling for age, sex, race/ethnicity, blood glucose levels, and body mass index. Main Outcome Measure: Progression to diabetes within 36 months. Results Patients were more likely to progress to diabetes if they lived in an area where less than 16% of adults had obtained a bachelor’s degree or higher (odds ratio [OR] =1.22, 95% confidence interval [CI] = 1.09-1.36), where median annual income was below $79,999 (OR = 1.16 95% CI = 1.03-1.31), or where SNAP benefits were received by 10% or more of households (OR = 1.24, 95% CI = 1.1-1.4). Conclusion Area-level socioeconomic and food assistance data predict the development of diabetes, even after adjusting for traditional individual demographic and clinical factors. Clinical interventions should take these factors into account, and health care systems should consider addressing social needs and community resources as a path to improving health outcomes

Exploiting non‐systematic covariate monitoring to broaden the scope of evidence about the causal effects of adaptive treatment strategies

In studies based on electronic health records (EHR), the frequency of covariate monitoring can vary by covariate type, across patients, and over time, which can limit the generalizability of inferences about the effects of adaptive treatment strategies. In addition, monitoring is a health intervention in itself with costs and benefits, and stakeholders may be interested in the effect of monitoring when adopting adaptive treatment strategies. This paper demonstrates how to exploit non‐systematic covariate monitoring in EHR‐based studies to both improve the generalizability of causal inferences and to evaluate the health impact of monitoring when evaluating adaptive treatment strategies. Using a real world, EHR‐based, comparative effectiveness research (CER) study of patients with type II diabetes mellitus, we illustrate how the evaluation of joint dynamic treatment and static monitoring interventions can improve CER evidence and describe two alternate estimation approaches based on inverse probability weighting (IPW). First, we demonstrate the poor performance of the standard estimator of the effects of joint treatment‐monitoring interventions, due to a large decrease in data support and concerns over finite‐sample bias from near‐violations of the positivity assumption (PA) for the monitoring process. Second, we detail an alternate IPW estimator using a no direct effect (NDE) assumption. We demonstrate that this estimator can improve efficiency but at the potential cost of increase in bias from violations of the PA for the treatment process

Improving Treatment Intensification to Reduce Cardiovascular Disease Risk: A Cluster Randomized Trial

Background: Blood pressure, lipid, and glycemic control are essential for reducing cardiovascular disease (CVD) risk. Many health care systems have successfully shifted aspects of chronic disease management, including population-based outreach programs designed to address CVD risk factor control, to non-physicians. The purpose of this study is to evaluate provision of new information to non-physician outreach teams on need for treatment intensification in patients with increased CVD risk. Methods Cluster randomized trial (July 1-December 31, 2008) in Kaiser Permanente Northern California registry of members with diabetes mellitus, prior CVD diagnoses and/or chronic kidney disease who were high-priority for treatment intensification: blood pressure ≥ 140 mmHg systolic, LDL-cholesterol ≥ 130 mg/dl, or hemoglobin A1c ≥ 9%; adherent to current medications; no recent treatment intensification). Randomization units were medical center-based outreach teams (4 intervention; 4 control). For intervention teams, priority flags for intensification were added monthly to the registry database with recommended next pharmacotherapeutic steps for each eligible patient. Control teams used the same database without this information. Outcomes included 3-month rates of treatment intensification and risk factor levels during follow-up. Results: Baseline risk factor control rates were high (82-90%). In eligible patients, the intervention was associated with significantly greater 3-month intensification rates for blood pressure (34.1 vs. 30.6%) and LDL-cholesterol (28.0 vs 22.7%), but not A1c. No effects on risk factors were observed at 3 months or 12 months follow-up. Intervention teams initiated outreach for only 45-47% of high-priority patients, but also for 27-30% of lower-priority patients. Teams reported difficulties adapting prior outreach strategies to incorporate the new information. Conclusions: Information enhancement did not improve risk factor control compared to existing outreach strategies at control centers. Familiarity with prior, relatively successful strategies likely reduced uptake of the innovation and its potential for success at intervention centers. Trial registration ClinicalTrials.gov Identifier NCT0051768

Improving treatment intensification to reduce cardiovascular disease risk: a cluster randomized trial

Abstract Background Blood pressure, lipid, and glycemic control are essential for reducing cardiovascular disease (CVD) risk. Many health care systems have successfully shifted aspects of chronic disease management, including population-based outreach programs designed to address CVD risk factor control, to non-physicians. The purpose of this study is to evaluate provision of new information to non-physician outreach teams on need for treatment intensification in patients with increased CVD risk. Methods Cluster randomized trial (July 1-December 31, 2008) in Kaiser Permanente Northern California registry of members with diabetes mellitus, prior CVD diagnoses and/or chronic kidney disease who were high-priority for treatment intensification: blood pressure ≥ 140 mmHg systolic, LDL-cholesterol ≥ 130 mg/dl, or hemoglobin A1c ≥ 9%; adherent to current medications; no recent treatment intensification). Randomization units were medical center-based outreach teams (4 intervention; 4 control). For intervention teams, priority flags for intensification were added monthly to the registry database with recommended next pharmacotherapeutic steps for each eligible patient. Control teams used the same database without this information. Outcomes included 3-month rates of treatment intensification and risk factor levels during follow-up. Results Baseline risk factor control rates were high (82-90%). In eligible patients, the intervention was associated with significantly greater 3-month intensification rates for blood pressure (34.1 vs. 30.6%) and LDL-cholesterol (28.0 vs 22.7%), but not A1c. No effects on risk factors were observed at 3 months or 12 months follow-up. Intervention teams initiated outreach for only 45-47% of high-priority patients, but also for 27-30% of lower-priority patients. Teams reported difficulties adapting prior outreach strategies to incorporate the new information. Conclusions Information enhancement did not improve risk factor control compared to existing outreach strategies at control centers. Familiarity with prior, relatively successful strategies likely reduced uptake of the innovation and its potential for success at intervention centers. Trial registration ClinicalTrials.gov Identifier NCT00517686http://deepblue.lib.umich.edu/bitstream/2027.42/112310/1/12913_2012_Article_2076.pd

Impact of a Pharmacy Benefit Change on New Use of Mail Order Pharmacy among Diabetes Patients: The Diabetes Study of Northern California (DISTANCE)

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110855/1/hesr12223-sup-0001-AuthorMatrix.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110855/2/hesr12223.pd

Patient Race/Ethnicity and Patient-Physician Race/Ethnicity Concordance in the Management of Cardiovascular Disease Risk Factors for Patients With Diabetes

OBJECTIVE Patient-physician race/ethnicity concordance can improve care for minority patients. However, its effect on cardiovascular disease (CVD) care and prevention is unknown. We examined associations of patient race/ethnicity and patient-physician race/ethnicity concordance on CVD risk factor levels and appropriate modification of treatment in response to high risk factor values (treatment intensification) in a large cohort of diabetic patients. RESEARCH DESIGN AND METHODS The study population included 108,555 adult diabetic patients in Kaiser Permanente Northern California in 2005. Probit models assessed the effect of patient race/ethnicity on risk factor control and treatment intensification after adjusting for patient and physician-level characteristics. RESULTS African American patients were less likely than whites to have A1C <8.0% (64 vs. 69%, P < 0.0001), LDL cholesterol <100 mg/dl (40 vs. 47%, P < 0.0001), and systolic blood pressure (SBP) <140 mmHg (70 vs. 78%, P < 0.0001). Hispanic patients were less likely than whites to have A1C <8% (62 vs. 69%, P < 0.0001). African American patients were less likely than whites to have A1C treatment intensification (73 vs. 77%, P < 0.0001; odds ratio [OR] 0.8 [95% CI 0.7-0.9]) but more likely to receive treatment intensification for SBP (78 vs. 71%, P < 0.0001; 1.5 [1.3-1.7]). Hispanic patients were more likely to have LDL cholesterol treatment intensification (47 vs. 45%, P < 0.05; 1.1 [1.0-1.2]). Patient-physician race/ethnicity concordance was not significantly associated with risk factor control or treatment intensification. CONCLUSIONS Patient race/ethnicity is associated with risk factor control and treatment intensification, but patient-physician race/ethnicity concordance was not. Further research should investigate other potential drivers of disparities in CVD care

Patient-provider communication regarding drug costsin Medicare Part D beneficiaries with diabetes: a TRIAD Study

<p>Abstract</p> <p>Background</p> <p>Little is known about drug cost communications of Medicare Part D beneficiaries with chronic conditions such as diabetes. The purpose of this study is to assess Medicare Part D beneficiaries with diabetes' levels of communication with physicians regarding prescription drug costs; the perceived importance of these communications; levels of prescription drug switching due to cost; and self-reported cost-related medication non-adherence.</p> <p>Methods</p> <p>Data were obtained from a cross-sectional survey (58% response rate) of 1,458 Medicare beneficiaries with diabetes who entered the coverage gap in 2006; adjusted percentages of patients with communication issues were obtained from multivariate regression analyses adjusting for patient demographics and clinical characteristics.</p> <p>Results</p> <p>Fewer than half of patients reported discussing the cost of medications with their physicians, while over 75% reported that such communications were important. Forty-eight percent reported their physician had switched to a less expensive medication due to costs. Minorities, females, and older adults had significantly lower levels of communication with their physicians regarding drug costs than white, male, and younger patients respectively. Patients with < $25 K annual household income were more likely than higher income patients to have talked about prescription drug costs with doctors, and to report cost-related non-adherence (27% vs. 17%, p < .001).</p> <p>Conclusions</p> <p>Medicare Part D beneficiaries with diabetes who entered the coverage gap have low levels of communication with physicians about drug costs, despite the high perceived importance of such communication. Understanding patient and plan-level characteristics differences in communication and use of cost-cutting strategies can inform interventions to help patients manage prescription drug costs.</p