Celine Hollombe

Description and pilot results from a novel method for evaluating return of incidental findings from next-generation sequencing technologies

Purpose:The aim of this study was to develop, operationalize, and pilot test a transparent, reproducible, and evidence-informed method to determine when to report incidental findings from next-generation sequencing technologies.Methods:Using evidence-based principles, we proposed a three-stage process. Stage I “rules out” incidental findings below a minimal threshold of evidence and is evaluated using inter-rater agreement and comparison with an expert-based approach. Stage II documents criteria for clinical actionability using a standardized approach to allow experts to consistently consider and recommend whether results should be routinely reported (stage III). We used expert opinion to determine the face validity of stages II and III using three case studies. We evaluated the time and effort for stages I and II.Results:For stage I, we assessed 99 conditions and found high inter-rater agreement (89%), and strong agreement with a separate expert-based method. Case studies for familial adenomatous polyposis, hereditary hemochromatosis, and α1-antitrypsin deficiency were all recommended for routine reporting as incidental findings. The method requires <3 days per topic.Conclusion:We establish an operational definition of clinically actionable incidental findings and provide documentation and pilot testing of a feasible method that is scalable to the whole genome.Genet Med 15 9, 721–728.Genetics in Medicine (2013); 15 9, 721–728. doi:10.1038/gim.2013.37

Approaches to integrating germline and tumor genomic data in cancer research

Cancer is characterized by a diversity of genetic and epigenetic alterations occurring in both the germline and somatic (tumor) genomes. Hundreds of germline variants associated with cancer risk have been identified, and large amounts of data identifying mutations in the tumor genome that participate in tumorigenesis have been generated. Increasingly, these two genomes are being explored jointly to better understand how cancer risk alleles contribute to carcinogenesis and whether they influence development of specific tumor types or mutation profiles. To understand how data from germline risk studies and tumor genome profiling is being integrated, we reviewed 160 articles describing research that incorporated data from both genomes, published between January 2009 and December 2012, and summarized the current state of the field. We identified three principle types of research questions being addressed using these data: (i) use of tumor data to determine the putative function of germline risk variants; (ii) identification and analysis of relationships between host genetic background and particular tumor mutations or types; and (iii) use of tumor molecular profiling data to reduce genetic heterogeneity or refine phenotypes for germline association studies. We also found descriptive studies that compared germline and tumor genomic variation in a gene or gene family, and papers describing research methods, data sources, or analytical tools. We identified a large set of tools and data resources that can be used to analyze and integrate data from both genomes. Finally, we discuss opportunities and challenges for cancer research that integrates germline and tumor genomics data.

Study protocol for “Study of Practices Enabling Implementation and Adaptation in the Safety Net (SPREAD-NET)”: a pragmatic trial comparing implementation strategies

BackgroundLittle research has directly compared the effectiveness of implementation strategies in any setting, and we know of no prior trials directly comparing how effectively different combinations of strategies support implementation in community health centers. This paper outlines the protocol of the Study of Practices Enabling Implementation and Adaptation in the Safety Net (SPREAD-NET), a trial designed to compare the effectiveness of several common strategies for supporting implementation of an intervention and explore contextual factors that impact the strategies’ effectiveness in the community health center setting.Methods/designThis cluster-randomized trial compares how three increasingly hands-on implementation strategies support adoption of an evidence-based diabetes quality improvement intervention in 29 community health centers, managed by 12 healthcare organizations. The strategies are as follows: (arm 1) a toolkit, presented in paper and electronic form, which includes a training webinar; (arm 2) toolkit plus in-person training with a focus on practice change and change management strategies; and (arm 3) toolkit, in-person training, plus practice facilitation with on-site visits. We use a mixed methods approach to data collection and analysis: (i) baseline surveys on study clinic characteristics, to explore how these characteristics impact the clinics’ ability to implement the tools and the effectiveness of each implementation strategy; (ii) quantitative data on change in rates of guideline-concordant prescribing; and (iii) qualitative data on the “how” and “why” underlying the quantitative results. The outcomes of interest are clinic-level results, categorized using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework, within an interrupted time-series design with segmented regression models. This pragmatic trial will compare how well each implementation strategy works in “real-world” practices.DiscussionHaving a better understanding of how different strategies support implementation efforts could positively impact the field of implementation science, by comparing practical, generalizable methods for implementing clinical innovations in community health centers. Bridging this gap in the literature is a critical step towards the national long-term goal of effectively disseminating and implementing effective interventions into community health centers.Trial registrationClinicalTrials.gov, NCT02325531

Cardiovascular care guideline implementation in community health centers in Oregon: a mixed-methods analysis of real-world barriers and challenges

BackgroundSpreading effective, guideline-based cardioprotective care quality improvement strategies between healthcare settings could yield great benefits, particularly in under-resourced contexts. Understanding the diverse factors facilitating or impeding such guideline implementation could improve cardiovascular care quality and outcomes for vulnerable patients.MethodsWe sought to identify multi-level factors affecting uptake of cardioprotective care guidelines in community health centers (CHCs), within a successful trial of cross-setting implementation of an effective intervention. Quantitative analyses used multivariable logistic regression to examine in-person patient encounters at 10 CHCs from June 2011-May 2014. At these encounters, a point-of-care alert flagged adults with diabetes who were clinically indicated for, but not currently prescribed, cardioprotective medications. The main outcome measure was the rate of relevant prescriptions issued within two days of encounters. Qualitative analyses focused on CHC providers and staff, and, guided by the constant comparative method, were used to enhance understanding of the factors that influenced this prescribing.ResultsRecommended prescribing occurred at 13–16% of encounters with patients who were indicated for such prescribing. The odds of this prescribing were higher when the patient was male, had HbA1c ≥7, was previously prescribed a similar medication, gave diabetes as the chief complaint, saw a mid-level practitioner, or saw their primary care provider. The odds were lower when the patient was insured, had ≥1 clinic visits in the past year, had kidney disease, or was prescribed certain other medications. Additional factors were associated with prescribing of each medication class. Qualitative results both supported and challenged the quantitative findings, illustrating important tensions involved in guideline-based prescribing. Clinic staff stressed the importance of the provider-patient relationship in guiding prescribing decisions in the face of competing priorities and care needs, and the impact of rapidly changing guidelines.ConclusionsDiverse factors associated with guideline-concordant prescribing illuminate the complexity of delivering evidence-based care in CHCs. We present possible strategies for addressing barriers to guideline-based prescribing.Clinical trials registrationThis trial was registered retrospectively.Currently Controlled Trials NCT02299791. Retrospectively registered 10 November 2014.

Adoption of Social Determinants of Health EHR Tools by Community Health Centers

PURPOSE This pilot study assessed the feasibility of implementing electronic health record (EHR) tools for collecting, reviewing, and acting on patient-reported social determinants of health (SDH) data in community health centers (CHCs). We believe it is the first such US study. METHODS We implemented a suite of SDH data tools in 3 Pacific Northwest CHCs in June 2016, and used mixed methods to assess their adoption through July 2017. We modified the tools at clinic request; for example, we added questions that ask if the patient wanted assistance with SDH needs. RESULTS Social determinants of health data were collected on 1,130 patients during the study period; 97% to 99% of screened patients (n = 1,098) had ≥1 SDH need documented in the EHR, of whom 211 (19%) had an EHR-documented SDH referral. Only 15% to 21% of patients with a documented SDH need indicated wanting help. Examples of lessons learned on adoption of EHR SDH tools indicate that clinics should: consider how to best integrate tools into existing workflow processes; ensure that staff tasked with SDH efforts receive adequate tool training and access; and consider that timing of data entry impacts how and when SDH data can be used. CONCLUSIONS Our results indicate that adoption of systematic EHR-based SDH documentation may be feasible, but substantial barriers to adoption exist. Lessons from this study may inform primary care providers seeking to implement SDH-related efforts, and related health policies. Far more research is needed to address implementation barriers related to SDH documentation in EHRs.