K. Brunisholz

Genome-Wide Significance and Replication of the Chromosome 12p11.22 Locus Near the PTHLH Gene for Peripartum Cardiomyopathy

Background— Peripartum (PP) cardiomyopathy (CM) is a rare condition of unknown etiology that occurs in late pregnancy or early postpartum. Initial evidence suggests that genetic factors may influence PPCM. This study evaluated and replicated genome-wide association of single nucleotide polymorphisms with PPCM. Methods and Results— Genome-wide single nucleotide polymorphisms in women with verified PPCM diagnosis (n=41) were compared separately with local control subjects (n=49 postmenopausal age-discordant women with parity ≥1 and no heart failure) and iControls (n=654 women ages 30 to 84 years with unknown phenotypes). A replication study of independent population samples used new cases (PPCM2, n=30) compared with new age-discordant control subjects (local2, n=124) and with younger control subjects (n=89) and obstetric control subjects (n=90). A third case set of pregnancy-associated CM cases not meeting strict PPCM definitions (n=29) was also studied. In the genome-wide association study, 1 single nucleotide polymorphism (rs258415) met genome-wide significance for PPCM versus local control subjects (P=2.06×10−8; odds ratio [OR], 5.96). This was verified versus iControls (P=7.92×10−19; OR, 8.52). In the replication study for PPCM2 cases, rs258415 (ORs are per C allele) replicated at P=0.009 versus local2 control subjects (OR, 2.26). This replication was verified for PPCM2 versus younger control subjects (P=0.029; OR, 2.15) and versus obstetric control subjects (P=0.013; OR, 2.44). In pregnancy-associated cardiomyopathy cases, rs258415 had a similar effect versus local2 control subjects (P=0.06; OR, 1.79), younger control subjects (P=0.14; OR, 1.65), and obstetric control subjects (P=0.038; OR, 1.99). Conclusions— Genome-wide association with PPCM was discovered and replicated for rs258415 at chromosome 12p11.22 near PTHLH. This study indicates a role of genetic factors in PPCM and provides a new locus for further pathophysiological and clinical investigation.

Organizational Culture Associated With Provider Satisfaction

Background: Organizational culture is key to the successful implementation of major improvement strategies. Transformation to a patient-centered medical home (PCHM) is such an improvement strategy, requiring a shift from provider-centric care to team-based care. Because this shift may impact provider satisfaction, it is important to understand the relationship between provider satisfaction and organizational culture, specifically in the context of practices that have transformed to a PCMH model. Methods: This was a cross-sectional study of surveys conducted in 2011 among providers and staff in 10 primary care clinics implementing their version of a PCMH: Care by Design. Measures included the Organizational Culture Assessment Instrument and the American Medical Group Association provider satisfaction survey. Results: Providers were most satisfied with quality of care (mean, 4.14; scale of 1–5) and interactions with patients (mean, 4.12) and were least satisfied with time spent working (mean, 3.47), paperwork (mean, 3.45), and compensation (mean, 3.35). Culture profiles differed across clinics, with family/clan and hierarchical cultures the most common. Significant correlations (P ≤ .05) between provider satisfaction and clinic culture archetypes included family/clan culture negatively correlated with administrative work; entrepreneurial culture positively correlated with the Time Spent Working dimension; market/rational culture positively correlated with how practices were facing economic and strategic challenges; and hierarchical culture negatively correlated with the Relationships with Staff and Resource dimensions. Conclusions: Provider satisfaction is an important metric for assessing experiences with features of a PCMH model. Identification of clinic-specific culture archetypes and archetype associations with provider satisfaction can help inform practice redesign. Attention to effective methods for changing organizational culture is recommended.

Stepping Back to Move Forward: Evaluating the Effectiveness of a Diabetes Prevention Program Within a Large Integrated Healthcare Delivery System

Objective: To evaluate the short-term effectiveness of the Intermountain Healthcare (IH) Diabetes Prevention Program (DPP) for patients with prediabetes (preDM) deployed within primary care clinics. Study Design: A quasi-experimental study design was used to deploy the DPP within the IH system to identify patients with preDM and target a primary goal of a 5% weight loss within 6–12 months of enrollment. Study Population: Adults (aged 18–75 years) who met the American Diabetes Association criteria for preDM were included for study. Patients who attended DPP counseling between August 2013 and July 2014 were considered as the intervention (or DPP) group. The DPP group was matched using propensity scores at a 1:4 ratio with a control group of patients with preDM who did not participate in DPP. Results: Of the 17,142 patients who met the inclusion criteria for preDM, 40% had an in-person office visit with their provider. On average, patients were 58 years old, and greater than 60% were women. Based on multivariate logistic regression, the DPP group was more likely to achieve a 5% weight loss within 6–12 months after enrollment (OR = 1.70; 95% CI = 1.29–2.25; p < .001) when compared with the no-DPP group. Conclusions: Diabetes Prevention Program–based lifestyle interventions demonstrated significant reduction in body weight and incident Type 2 diabetes mellitus when compared with nonenrollees.

Incidental Risk of Type 2 Diabetes Mellitus among Patients with Confirmed and Unconfirmed Prediabetes.

Objective To determine the risk of type 2 diabetes (T2DM) diagnosis among patients with confirmed and unconfirmed prediabetes (preDM) relative to an at-risk group receiving care from primary care physicians over a 5-year period. Study Design Utilizing data from the Intermountain Healthcare (IH) Enterprise Data Warehouse (EDW) from 2006–2013, we performed a prospective analysis using discrete survival analysis to estimate the time to diagnosis of T2DM among groups. Population Studied Adult patients who had at least one outpatient visit with a primary care physician during 2006–2008 at an IH clinic and subsequent visits through 2013. Patients were included for the study if they were (a) at-risk for diabetes (BMI ≥ 25 kg/m2 and one additional risk factor: high risk ethnicity, first degree relative with diabetes, elevated triglycerides or blood pressure, low HDL, diagnosis of gestational diabetes or polycystic ovarian syndrome, or birth of a baby weighing >9 lbs); or (b) confirmed preDM (HbA1c ≥ 5.7–6.49% or fasting blood glucose 100–125 mg/dL); or (c) unconfirmed preDM (documented fasting lipid panel and glucose 100–125 mg/dL on the same day). Principal Findings Of the 33,838 patients who were eligible for study, 57.0% were considered at-risk, 38.4% had unconfirmed preDM, and 4.6% had confirmed preDM. Those with unconfirmed and confirmed preDM tended to be Caucasian and a greater proportion were obese compared to those at-risk for disease. Patients with unconfirmed and confirmed preDM tended to have more prevalent high blood pressure and depression as compared to the at-risk group. Based on the discrete survival analyses, patients with unconfirmed preDM and confirmed preDM were more likely to develop T2DM when compared to at-risk patients. Conclusions Unconfirmed and confirmed preDM are strongly associated with the development of T2DM as compared to patients with only risk factors for disease.

AcademyHealth’s Delivery System Science Fellowship: training embedded researchers to design, implement, and evaluate new models of care

&NA; AcademyHealths Delivery System Science Fellowship (DSSF) provides a paid postdoctoral pragmatic learning experience to build capacity within learning healthcare systems to conduct research in applied settings. The fellowship provides handson training and professional leadership opportunities for researchers. Since its inception in 2012, the program has grown rapidly, with 16 health systems participating in the DSSF to date. In addition to specific projects conducted within health systems (and numerous publications associated with those initiatives), the DSSF has made several broader contributions to the field, including defining delivery system science, identifying a set of training objectives for researchers working in delivery systems, and developing a national collaborative network of care delivery organizations, operational leaders, and trainees. The DSSF is one promising approach to support higher‐value care by promoting continuous learning and improvement in health systems.

A formative evaluation of a diabetes prevention program using the RE-AIM framework in a learning health care system, Utah, 2013-2015

Introduction Evaluation of interventions can help to close the gap between research and practice but seldom takes place during implementation. Using the RE-AIM framework, we conducted a formative evaluation of the first year of the Intermountain Healthcare Diabetes Prevention Program (DPP). Methods Adult patients who met the criteria for prediabetes (HbA1c of 5.70%–6.49% or fasting plasma glucose of 100–125 mg/dL) were attributed to a primary care provider from August 1, 2013, through July 31, 2014. Physicians invited eligible patients to participate in the program during an office visit. We evaluated 1) reach, with data on patient eligibility, participation, and representativeness; 2) effectiveness, with data on attaining a 5% weight loss; 3) adoption, with data on providers and clinics that referred patients to the program; and 4) implementation, with data on patient encounters. We did not measure maintenance. Results Of the 6,862 prediabetes patients who had an in-person office visit with their provider, 8.4% of eligible patients enrolled. Likelihood of participation was higher among patients who were female, aged 70 years or older, or overweight; had depression and higher weight at study enrollment; or were prescribed metformin. DPP participants were more likely than nonparticipants to achieve a 5% weight loss (odds ratio, 1.70; 95% confidence interval, 1.29–2.25; P < .001). Providers from 7 of 8 regions referred patients to the DPP; 174 providers at 53 clinics enrolled patients. The mean number of DPP counseling encounters per patient was 2.3 (range, 1–16). Conclusion The RE-AIM framework was useful for estimating the formative impact (ie, reach, effectiveness, adoption, and implementation fidelity) of a DPP-based lifestyle intervention deployed in a learning health care system.

Reasons for Left Ventricular Assist Device Patient Denial: Insights into Possible Misconceptions about Mechanical Circulatory Support

Purpose Left ventricular assist devices (LVADs) are becoming a more common and effective therapy for patients with advanced heart failure. However, this technology is underutilized, and there is a general sense that many patients are referred too late, resulting in poor outcomes. The aim of this study was to determine why those patients referred for LVAD therapy who did not undergo LVAD implantation were found to be unsuitable candidates. Methods and Materials The UTAH Cardiac Transplant Program mechanical circulatory support databases were queried for all patients referred for an LVAD between 2006 and 2012. The patients were then stratified into those who received an LVAD and those who did not. For the patients who did not receive an LVAD, the reasons for referral rejection were collected and categorized. Results 604 patients were referred for an LVAD between our two centers of whom 338 (56%) did not receive an LVAD. For the rejected referral population, the average age was 59±14 years and 76% were male. The reasons for LVAD rejection are summarized below. Conclusions In our experience, more than half of patients referred for an LVAD did not receive this therapy. A substantial percent of these patients were declined on the basis of being too sick at the time of evaluation, suggesting that many patients are referred too late. More efforts to educate the referral community about the benefits of a timely referral are needed to improve outcomes and cost-efficiency of LVADs. Reason for RejectionPatients (%)Too Sick81 (24.0)- Renal or Liver Disease17 (5.0)- Acute Critical Illness16 (4.7)- Comorbidities14 (4.1)- Pulmonary Disease11 (3.3)- Multi-Organ Dysfunction7 (2.1)- GI Disorders4 (1.2)- Infection4 (1.2)- Cancer4 (1.2)- Old Age3 (0.9)- Ventricular Arrythmias1 (0.3)Medically Managed80 (23.7)Patient Declined64 (18.9)LVAD as Backup Only32 (9.5)Went to Heart Transplant32 (9.5)Lack of Funding22 (6.5)LVAD Not Needed9 (2.7)Lack of Social Support8 (2.4)Non-Compliance5(1.5)Other5 (1.5)

508 Microvessel Density in Cardiac Allograft Biopsies in Patients with Clinically Significant Coronary Allograft Vasculopathy Treated with Sirolimus

ROC Area 0.64 vs 0.75 0.71 vs 0.78 0.93 vs 0.96 0.75 vs 0.78 0.88 vs 0.92 0.86 vs 0.87 Sensitivity 0.56 vs 0.94 0.66 vs 0.62 0.90 vs 1.00 0.65 vs 0.79 0.71 vs 1.00 0.87 vs 0.87 Specificity 0.71 vs 0.54 0.68 vs 0.86 0.82 vs 0.86 0.75 vs 0.68 0.90 vs 0.72 0.74 vs 0.75 PPV 0.31 vs 0.32 0.78 vs 0.88 0.24 vs 0.30 0.56 vs 0.55 0.23 vs 0.13 0.43 vs 0.43 NPV 0.88 vs 0.97 0.54 vs 0.57 0.99 vs 1.00 0.81 vs 0.87 0.99 vs 1.00 0.96 vs 0.96 Prevalence 0.19 0.63 0.06 0.33 0.04 0.18 Cutoff Value 0.13 vs 0.12 0.45 vs 0.70 0.02 vs 0.05 0.35 vs 0.29 0.03 vs 0.02 0.12 vs 0.11 ROC: Receiver Operating Characteristic; PPV: Positive Predictive Value; NPV: Negative Predictive Value