Citations

Abstract Electronic health record (EHR) algorithms for defining patient cohorts are commonly shared as free-text descriptions that require human intervention both to interpret and implement. We developed the Phenotype Execution and Modeling Architecture (PhEMA, http://projectphema.org) to author and execute standardized computable phenotype algorithms. With PhEMA, we converted an algorithm for benign prostatic hyperplasia, developed for the electronic Medical Records and Genomics network (eMERGE), into a standards-based computable format. Eight sites (7 within eMERGE) received the computable algorithm, and 6 successfully executed it against local data warehouses and/or i2b2 instances. Blinded random chart review of cases selected by the computable algorithm shows PPV ≥90%, and 3 out of 5 sites had >90% overlap of selected cases when comparing the computable algorithm to their original eMERGE implementation. This case study demonstrates potential use of PhEMA computable representations to automate phenotyping across different EHR systems, but also highlights some ongoing challenges.

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Background: Coronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown. Methods: We performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus. Results: The meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35–1.86; P =2.6×10 − 10 ). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14–2.57; P =0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17–2.24; P =0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18–4.75; P =0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes. Conclusions: Genetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them.

With advancements in surgical techniques, patients have experienced improvements in health and recovery outcomes. However, about 87% of laparoscopic surgeons [1] and an increasing number of surveyed allied health professionals [2, 3] report musculoskeletal symptoms. Medical practitioners and human factors engineers have highlighted the “hostile” and “dangerous” operating room (OR) environment [1, 4, 5]. With increasing technology and surgical case complexity, physical demands for surgical team members will continue to increase due to circumstances such as technology restricting posture, taking up working space and more team members working around smaller surgical incisions [6]. There is widespread concern that these medical professionals’ work is unsustainable for safe and healthy patients and surgical team members. Surgical team members can benefit from posture improvement during surgery; however, direct postural feedback may be difficult during their work due to the high visual and auditory stimuli during surgery. The tactile modality has been recently explored as a method to provide additional information without interfering with cognitive resources dedicated to visual and auditory pathways [7]. Tactile devices have successfully been implemented in high-stress environments, e.g., military, healthcare, and rehabilitation with a resulting improvement in performance [8–11]. Vibrotactile feedback has been specifically implemented in the healthcare field for improved performance by 31–75% anesthesiologists during simulated tasks [10]. Additionally, it has contributed to improved postural control in rehabilitation patients[11]. Despite success in other application areas, the potential of tactile devices for improving healthcare workers’ safety and performance remains unexplored. This study is a part of a larger project to design a wearable device that provides realtime vibrotactile feedback for preventing fatigue and musculoskeletal disorders for healthcare workers in the workplace. This specific aim of this study is to measure distraction, frustration, and performance during a surgical simulation task performed with and without vibrotactile feedback. This is a test of initial feasibility of vibrotactile feedback for use in training proper ergonomics for surgical team members. The researchers hypothesize that there will be some distraction with the vibrotactile feedback wearable but no frustration or performance degradation during the basic simulation task.

Genome-wide association studies have identified >50 common variants associated with kidney function, but these variants do not fully explain the variation in eGFR. We performed a two-stage meta-analysis of associations between genotypes from the Illumina exome array and eGFR on the basis of serum creatinine (eGFRcrea) among participants of European ancestry from the CKDGen Consortium ( n Stage1 : 111,666; n Stage2 : 48,343). In single-variant analyses, we identified single nucleotide polymorphisms at seven new loci associated with eGFRcrea ( PPM1J , EDEM3, ACP1, SPEG, EYA4, CYP1A1 , and ATXN2L ; P Stage1 <3.7×10 −7 ), of which most were common and annotated as nonsynonymous variants. Gene-based analysis identified associations of functional rare variants in three genes with eGFRcrea, including a novel association with the SOS Ras/Rho guanine nucleotide exchange factor 2 gene, SOS2 ( P =5.4×10 −8 by sequence kernel association test). Experimental follow-up in zebrafish embryos revealed changes in glomerular gene expression and renal tubule morphology in the embryonic kidney of acp1- and sos2 -knockdowns. These developmental abnormalities associated with altered blood clearance rate and heightened prevalence of edema. This study expands the number of loci associated with kidney function and identifies novel genes with potential roles in kidney formation.

Introduction: Racial and ethnic groups are under-represented among research subjects who assent to brain donation in Alzheimer disease research studies. There has been little research on this important topic. Although there are some studies that have investigated the barriers to brain donation among African American study volunteers, there is no known research on the factors that influence whether or not Asians or Latinos are willing to donate their brains for research. Methods: African American, Caucasian, Asian, and Latino research volunteers were surveyed at 15 Alzheimer Disease Centers to identify predictors of willingness to assent to brain donation. Results: Positive predictors included older age, Latino ethnicity, understanding of how the brain is used by researchers, and understanding of what participants need to do to ensure that their brain will be donated. Negative predictors included African/African American race, belief that the body should remain whole at burial, and concern that researchers might not be respectful of the body during autopsy. Discussion: The predictive factors identified in this study may be useful for researchers seeking to increase participation of diverse ethnic groups in brain donation.

Medical care providers recognize nonadjustable examination tables in clinics as a barrier to comprehensively and safely providing routine healthcare for disabled, elderly and obese patients. The aim of this study was to understand how the availability of the adjustable examination table may affect the medical care provider’s perception of the quality of care provided to patients who need physical assistance. Fifty providers answered questionnaires to report their perceptions of two different examination tables’ usability. The first one is a mid-century industrial designed table and the other adjustable and ADA compliant, as used in a community health clinic. Before implementation of the new adjustable examination table, 34 medical care providers provided feedback on their experiences with nonadjustable examination tables. A second survey was administered approximately six months after implementation of the new adjustable examination tables to 16 medical care providers (with 2 indicating participation in the prior-to-implementation survey) for their feedback on experiences with the new adjustable examination tables. Providers reported significantly (p<0.05) more comfort in getting typical patients (27%), bariatric patients (50%), and geriatric patients (30%) into a sitting position when they used the adjustable examination table compared to the nonadjustable examination table. Providers considered the adjustable examination tables to have a more ideal width (60%) and length (64%) to accommodate a wider variety of patients than the nonadjustable examination tables. Providers also considered the adjustable table (33%) easier to use and preferable to the nonadjustable table. This research showed how the adjustable examination table improves healthcare provider experience to provide access to healthcare for patients with disabilities with better ergonomics and greater safety for both patients and providers.

Abstract Objective Health care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine phenotype algorithms to achieve high positive predictive values (PPVs) or sensitivity, thereby identifying valid cases and controls. These algorithms achieve the greatest utility when validated and shared by multiple health care systems. Materials and Methods We report the current status and impact of the Phenotype KnowledgeBase (PheKB, http://phekb.org ), an online environment supporting the workflow of building, sharing, and validating electronic phenotype algorithms. We analyze the most frequent components used in algorithms and their performance at authoring institutions and secondary implementation sites. Results As of June 2015, PheKB contained 30 finalized phenotype algorithms and 62 algorithms in development spanning a range of traits and diseases. Phenotypes have had over 3500 unique views in a 6-month period and have been reused by other institutions. International Classification of Disease codes were the most frequently used component, followed by medications and natural language processing. Among algorithms with published performance data, the median PPV was nearly identical when evaluated at the authoring institutions (n = 44; case 96.0%, control 100%) compared to implementation sites (n = 40; case 97.5%, control 100%). Discussion These results demonstrate that a broad range of algorithms to mine electronic health record data from different health systems can be developed with high PPV, and algorithms developed at one site are generally transportable to others. Conclusion By providing a central repository, PheKB enables improved development, transportability, and validity of algorithms for research-grade phenotypes using health care generated data.