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Many health systems are working to become learning health systems (LHSs), which aim to improve the value of health care by rapidly, continuously generating evidence to apply to practice. However, challenges remain to advance toward the aspirational goal of becoming a fully mature LHS. While some important challenges have been well described (i.e., building system-level supporting infrastructure and the accessibility of inclusive, integrated, and actionable data), other key challenges are underrecognized, including balancing evaluation rapidity with rigor, applying principles of health equity and classic ethics, focusing on external validity and reproducibility (generalizability), and designing for sustainability. Many LHSs focus on continuous learning cycles, but with limited consideration of issues related to the rapidity of these learning cycles, as well as the sustainability or generalizability of solutions. Some types of data have been consistently underrepresented, including patient-reported outcomes and preferences, social determinants, and behavioral and environmental data, the absence of which can exacerbate health disparities. A promising approach to addressing many challenges that LHSs face may be found in dissemination and implementation (D&I) science. With an emphasis on multilevel dynamic contextual factors, representation of implementation partner engagement, pragmatic research, sustainability, and generalizability, D&I science methods can assist in overcoming many of the challenges facing LHSs. In this article, the authors describe the current state of LHSs and challenges to becoming a mature LHS, propose solutions to current challenges, focusing on the contributions of D&I science with other methods, and propose key components and characteristics of a mature LHS model that others can use to plan and develop their LHSs.

In recent years, the genomics community has witnessed the growth of large research biobanks, which collect DNA samples for research purposes. Depending on how and where the samples are genotyped, biobanks also offer the potential opportunity to return actionable genomic results to the clinical setting. We developed a preemptive clinical pharmacogenomic implementation initiative via a health system-wide research biobank at the University of Colorado. Here, we describe how preemptive return of clinical pharmacogenomic results via a research biobank is feasible, particularly when coupled with strong institutional support to maximize the impact and efficiency of biobank resources, a multidisciplinary implementation team, automated clinical decision support tools, and proactive strategies to engage stakeholders early in the clinical decision support tool development process.

Patients with congestive heart failure (CHF) require complex medical management across the continuum of care. Electronic health records (EHR) are currently used for traditional tasks of documentation, reviewing and managing test results, computerized order entry, and billing. Unfortunately many clinicians view EHR as merely digitized versions of paper charts, which create additional work and cognitive burden without improving quality or efficiency of care. In fact, EHR are revolutionizing the care of chronic diseases such as CHF. This review describes how appropriate use of technologies offered by EHR can help standardize CHF care, promote adherence to evidence-based guidelines, optimize workflow efficiency, improve performance metrics, and facilitate patient engagement. This review discusses a number of tools including documentation templates, telehealth and telemedicine, health information exchange, order sets, clinical decision support, registries, and analytics. Where available, evidence of their potential utility in management of CHF is presented. Together these EHR tools can also be used to enhance quality improvement, patient management, and clinical research as part of a learning health care system model. This review describes how existing EHR tools can support patients, cardiologists, and care teams to deliver consistent, high-quality, coordinated, patient-centered, and guideline-concordant care of CHF.

Clinical pharmacists use population health methods to generate chronic disease management referrals for patients with uncontrolled chronic conditions. The purpose of this study was to compare primary care providers’ (PCPs) referral responses for 4 pharmacist-managed indications and to identify provider and patient characteristics that are predictive of PCP response.

Background: Despite strong recommendations to use metformin as first-line therapy for type 2 diabetes (T2DM), its use has been suboptimal, likely due to concerns of lactic acidosis. This study compared the association of acidosis in patients with T2DM prescribed metformin with those prescribed other antihyperglycemic medications or no medications.Methods: This was a retrospective cohort study of patients with newly diagnosed T2DM utilizing an administrative database, which includes medical and prescription claims. Eligible patients had a diagnosis of T2DM, had continuous health plan enrollment 3 months prior to study enrollment and during the study period, and were at least 18 years of age. Mutually exclusive exposure groups were metformin only, other antihyperglycemic medications, and no medication. Acidosis cases were stratified by exposure group and risk factors for lactic acidosis (chronic obstructive pulmonary disease, hepatic dysfunction, alcohol abuse, heart failure, renal insufficiency, age of 80 years or older, and a history of acidosis). Degree of renal insufficiency was not available. Associations between exposure and acidosis were estimated, and risk factors evaluated.Results: A total of 132,780 patients met inclusion criteria: 24,936 (20%) metformin only group, 15,059 (11%) other antihyperglycemic medication group, and 92,785 (70%) no medication group. Acidosis was observed in 1.45 per 10,000 patient months (0.78 metformin, 1.59 other antihyperglycemic medication, 1.51 no medication). The unadjusted relative risk of acidosis was 0.5 for patients prescribed metformin only compared with the other exposure groups (95% confidence interval = 0.2–1.2). There was no significant difference in risk of acidosis between exposure groups, irrespective of risk factors for lactic acidosis.Conclusions: Risk of acidosis was similar with metformin only compared with those prescribed other antihyperglycemic medications or no medication. These results support expanded use of metformin for T2DM. Additional studies are needed to understand the impact of risk factor severity on risk of lactic acidosis.

Background: The purpose of this study was to identify the reasons why metformin prescribing is suboptimal.Methods: Two semi-structured focus groups with attitudinal questionnaires and a brief educational presentation were held in two US cities. Participants included providers (physicians, pharmacists, midlevel practitioners) caring for patients with type 2 diabetes mellitus (T2DM) in an ambulatory setting. Outcome measures included provider attitudes, behaviors and opinions regarding the use of metformin.Results: Participants identified three main themes influencing the use of metformin, including the appropriate timing of metformin initiation, known risks associated with metformin, and procedures to manage safety concerns and mitigate adverse effects associated with metformin. Participant prescribing behaviors of metformin were not consistent with the best available evidence in the settings of renal insufficiency, heart failure, hepatic dysfunction, alcohol use, and lactic acidosis. With minimal education, provider prescribing behaviors appeared to change by the end of the focus group to align more closely with the best available evidence.Conclusions: Provider attitudes, behaviors and opinions regarding the use of metformin for T2DM reveals the need for further education to improve appropriate use of metformin. Educational interventions should target prescribing behaviors and opinions identified to be inconsistent with the evidence.

OBJECTIVE To review the pharmacology, efficacy, and safety of phentermine/topiramate (PHEN/TPM) in the management of obese patients.DATA SOURCES MEDLINE (1966-July 2012) was searched using the terms weight loss, obesity, phentermine and topiramate, phentermine, topiramate, Qnexa, Qsymia, and VI-0521. Additionally, the new drug application and prescribing information for PHEN/TPM were retrieved.STUDY SELECTION/DATA EXTRACTION All studies considering the pharmacology, efficacy, and safety of PHEN/TPM were reviewed with a focus on efficacy and safety data from Phase 3 trials.DATA SYNTHESIS In 3 Phase 3 trials (EQUIP, CONQUER, and SEQUEL), treatment with PHEN/TPM consistently demonstrated statistically significant weight loss compared with placebo. After 56 weeks of treatment, percent weight loss achieved with PHEN/TPM was 10.6%, 8.4%, and 5.1% with 15/92 mg, 7.5/46 mg, and 3.75/23 mg, respectively (p < 0.0001). The 52-week extension study (SEQUEL) showed maintained weight loss over 2 years with 9.3% and 10.5% weight loss from baseline for 7.5/46 mg and 15/92 mg PHEN/TPM (p < 0.0001). A significantly higher proportion of patients achieved greater than 5%, 10%, or 15% weight loss with PHEN/TPM compared with placebo. Significant reductions in waist circumference, fasting triglycerides, and fasting glucoses were also attributable to PHEN/TPM. The drug was generally well tolerated in clinical trials. Adverse reactions occurring in 5% or more of study subjects included paresthesia, dizziness, dysgeusia, insomnia, constipation, and dry mouth.CONCLUSIONS PHEN/TPM is a new, once-daily, controlled-release, combination weight-loss product approved as an adjunct to diet and exercise for chronic weight management of obese or overweight patients with weight-related comorbidities. PHEN/TPM is modestly effective and a viable option for patients interested in losing weight, although long-term safety data are lacking.