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One of the primary goals of the patient-centered medical home (PCMH) is to provide higher quality care that leads to better patient outcomes. Currently, there is only limited evidence regarding the ability of PCMHs to achieve this goal. This article demonstrates the effect of PCMHs in improving certain clinical outcomes, as shown by the ProvenHealth Navigator (PHN), an advanced PCMH model developed and implemented by Geisinger Health System. In this study, the authors examined the claims data from Geisinger Health Plan between 2005 and 2009 and estimated the effect of PHN on reducing amputation rates among patients with diabetes, end-stage renal disease, myocardial infarction, and stroke. The results show that, despite its relatively short period of existence, PHN has led to significant improvements in certain outcomes, further illustrating its potential as a care delivery model to be adopted on a wider scale.

AimsExamine the association between weight loss and adherence with glycaemic goal attainment in patients with inadequately controlled T2DM.Materials and methodsPatients ≥ 18 years with T2DM from a US integrated health system starting a new class of diabetes medication between 11/1/10 and 4/30/11 (index date) with baseline HbA1c ≥ 7.0% were included in this cohort study. Target HbA1c and weight change were defined at 6-months as HbA1c < 7.0% and ≥ 3% loss in body weight. Patient-reported medication adherence was assessed per the Medication Adherence Reporting Scale. Structural equation modelling was used to describe simultaneous associations between adherence, weight loss and HbA1c goal attainment.ResultsInclusion criteria were met by 477 patients; mean (SD) age 59.1 (11.6) years; 50.9% were female; 30.4% were treatment naïve; baseline HbA1c 8.6% (1.6); weight 102.0 kg (23.0). Most patients (67.9%) reported being adherent to the index diabetes medication. At 6 months mean weight change was −1.3 (5.1) kg (p = 0.39); 28.1% had weight loss of ≥ 3%. Mean HbA1c change was −1.2% (1.8) (p< 0.001); 42.8% attained HbA1c goal. Adherent patients (OR 1.70; p = 0.02) and diabetes therapies that lead to weight loss (metformin, GLP-1) were associated with weight loss ≥ 3% (OR 2.96; p< 0.001). Weight loss (OR 3.60; p < 0.001) and adherence (OR 1.59; p < 0.001) were associated with HbA1c goal attainment.ConclusionsWeight loss ≥ 3% and medication adherence were associated with HbA1c goal attainment in T2DM; weight loss was a stronger predictor of goal attainment than medication adherence in this study population. It is important to consider weight-effect properties, in addition to patient-centric adherence counselling, when prescribing diabetes therapy.

In Brief Providing diabetes patients all of the care recommended by current guidelines is a clinical challenge. Geisinger Health System has designed a provider-led, team-based system of care to more consistently and reliably meet this challenge. This system of care uses an all-or-none bundle of diabetes measures and electronic health record tools to improve both process measures and intermediate diabetes outcomes.

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over 15,000 children ages 4-8 had at least one height and one weight recorded in the EHR at the same visit with BMI> 85th % for age, sex. 11,276 physician letters were mailed: 9,954 opt in letters over 13-months (Cohorts 1-3) and1,322 opt out letters in 2-months (Cohort 4). Of the 170 families screened, 58/107 (54%) identified opt in letters as recruitment source; 49/63 (78%) families in Cohort 4 reported opt out letters introduced them to the study. Fifty-six families gave written informed consent and/or assent and were randomized to one of two groups -Group Family Behavior Modification (FBM) or Enhanced Information Mailing (EIM) group. Three FBM and two EIM families dropped before treatment started. Conclusions: Physician letters to parents of eligible children identified in the EHR were the most successful recruitment strategies for the primary care obesity prevention study. Opt-out physician letters shortened recruitment time and doubled the number of participants recruited for the final cohort. Background: Rapidly growing numbers of Type 2 Diabetics (T2D) in the US continues to escalate need for evidence-based primary care interventions to reduce complications and costs. Limited time, information, and lack of revenue for chronic disease management create gaps between national guidelines and primary care for diabetes. Methods: Of the over 20,000 diabetics were identified in Geisinger EPIC ® EHR, 3166 T2D with diagnosis on problem list or ICD-9 code had HgA1c>8.0%. Physician letters or emails were sent to invite them to call to Opt OUT if they did not want more information. After a 10 day period, staff called 1932 eligible T2D to invite them to a shared medical primary care visit to participate in a randomized controlled trial comparing a tailored 5-month web-based lifestyle intervention (dLifeG.com) to usual care. 166 Type 2 diabetics gave written informed consent and were randomized 1:2 to control group or intervention group. In <20 minutes with simple computer instructions, T2Ds in intervention group created password protected personalized website to set goals, view weekly lessons, and take interactive quizzes to improve diabetes knowledge and selfmanagement. Weekly emails with lesson topics and links to the dLifeG.com were sent to intervention group participants. At end of study, control group will also have access to website intervention. Results: At midpoint, ~3/4th of the 100 T2 diabetics in intervention group were engaged [defined by the number of site page viewed (0-3090 pages), emails opened (0-100%), and quiz pages consumed (0-578)]. Mid and end of study changes in diabetes knowledge, HgA1c, Blood Pressure, and weight will be discussed. Conclusions: Web-based lifestyle interventions can be employed in primary care to engage a majority of diabetics with HgA1c>8.0 in a self-management lifestyle modification intervention. Importantly, the study also helped identify diabetics who may need additional resources and assistance with chronic disease management.