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Objectives Hypertension is a modifiable risk factor for numerous comorbidities and treating hypertension can greatly improve health outcomes. We sought to increase the efficiency of a virtual hypertension management program through workflow automation processes. Methods We developed a customer relationship management (CRM) solution at our institution for the purpose of improving processes and workflow for a virtual hypertension management program and describe here the development, implementation, and initial experience of this CRM system. Results Notable system features include task automation, patient data capture, multi-channel communication, integration with our electronic health record (EHR), and device integration (for blood pressure cuffs). In the five stages of our program (intake and eligibility screening, enrollment, device configuration/setup, medication titration, and maintenance), we describe some of the key process improvements and workflow automations that are enabled using our CRM platform, like automatic reminders to capture blood pressure data and present these data to our clinical team when ready for clinical decision making. We also describe key limitations of CRM, like balancing out-of-the-box functionality with development flexibility. Among our first group of referred patients, 76% (39/51) preferred email as their communication method, 26/51 (51%) were able to enroll electronically, and 63% of those enrolled (32/51) were able to transmit blood pressure data without phone support. Conclusion A CRM platform could improve clinical processes through multiple pathways, including workflow automation, multi-channel communication, and device integration. Future work will examine the operational improvements of this health information technology solution as well as assess clinical outcomes.

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

Objectives To understand the impact of GeneInsight Clinic (GIC), a web-based tool designed to manage genetic information and facilitate communication of test results and variant updates from the laboratory to the clinics, we measured the use of GIC and the time it took for new genetic knowledge to be available to clinicians. Methods Usage data were collected across four study sites for the GIC launch and post-GIC implementation time periods. The primary outcome measures were the time (average number of days) between variant change approval and notification of clinic staff, and the time between notification and viewing the patient record. Results Post-GIC, time between a variant change approval and provider notification was shorter than at launch (average days at launch 503.8, compared to 4.1 days post-GIC). After e-mail alerts were sent at launch, providers clicked into the patient record associated with 91% of these alerts. In the post period, clinic providers clicked into the patient record associated with 95% of the alerts, on average 12 days after the e-mail was sent. Discussion We found that GIC greatly increased the likelihood that a provider would receive updated variant information as well as reduced the time associated with distributing that variant information, thus providing a more efficient process for incorporating new genetic knowledge into clinical care. Conclusions Our study results demonstrate that health information technology systems have the potential effectively to assist providers in utilizing genetic information in patient care.

SummaryPartners HealthCare Personalized Medicine developed GeneInsight Clinic (GIC), a tool designed to communicate updated variant information from laboratory geneticists to treating clinicians through automated alerts, categorized by level of variant interpretation change.The study aimed to evaluate feedback from the initial users of the GIC, including the advantages and challenges to receiving this variant information and using this technology at the point of care.Healthcare professionals from two clinics that ordered genetic testing for cardiomyopathy and related disorders were invited to participate in one-hour semi-structured interviews and/ or a one-hour focus group. Using a Grounded Theory approach, transcript concepts were coded and organized into themes.Two genetic counselors and two physicians from two treatment clinics participated in individual interviews. Focus group participants included one genetic counselor and four physicians.Analysis resulted in 8 major themes related to structuring and communicating variant knowledge, GIC’s impact on the clinic, and suggestions for improvements. The interview analysis identified longitudinal patient care, family data, and growth in genetic testing content as potential challenges to optimization of the GIC infrastructure.Participants agreed that GIC implementation increased efficiency and effectiveness of the clinic through increased access to genetic variant information at the point of care.Development of information technology (IT) infrastructure to aid in the organization and management of genetic variant knowledge will be critical as the genetic field moves towards whole exome and whole genome sequencing. Findings from this study could be applied to future development of IT support for genetic variant knowledge management that would serve to improve clinicians’ ability to manage and care for patients.Citation: Klinkenberg-Ramirez S, Neri PM, Volk LA, Samaha SJ, Newmark LP, Pollard S, Varugheese M, Baxter S, Aronson SJ, Rehm HL, Bates DW. Evaluation: A qualitative pilot study of novel information technology infrastructure to communicate genetic variant updates.

Genetic tests often identify variants whose significance cannot be determined at the time they are reported. In many situations, it is critical that clinicians be informed when new information emerges on these variants. It is already extremely challenging for laboratories to provide these updates. These challenges will grow rapidly as an increasing number of clinical genetic tests are ordered and as the amount of patient DNA assayed per test expands; the challenges will need to be addressed before whole-genome sequencing is used on a widespread basis.Information technology infrastructure can be useful in this context. We have deployed an infrastructure enabling clinicians to receive knowledge updates when a laboratory changes the classification of a variant. We have gathered statistics from this deployment regarding the frequency of both variant classification changes and the effects of these classification changes on patients. We report on the system's functionality as well as the statistics derived from its use.Genet Med advance online publication 5 April 2012.

The future of personalized medicine will hinge on effective management of patient genetic profiles. Molecular diagnostic testing laboratories need to track knowledge surrounding an increasingly large number of genetic variants, incorporate this knowledge into interpretative reports, and keep ordering clinicians up to date as this knowledge evolves. Treating clinicians need to track which variants have been identified in each of their patients along with the significance of these variants. The GeneInsight(SM) Suite assists in these areas. The suite also provides a basis for interconnecting laboratories and clinicians in a manner that increases the scalability of personalized medicine processes.

Graphical abstractDisplay Omitted Highlights? We evaluated an innovative application for communicating genetic results. ? Application allows users to access knowledge updates to reported variants. ? Optimizing accessibility and clinical relevance of genetic data is essential. ? Incorporating user focused design can optimize value of application. ? Providers felt the application had high value for delivering clinical care. The complexity and rapid growth of genetic data demand investment in information technology to support effective use of this information. Creating infrastructure to communicate genetic information to healthcare providers and enable them to manage that data can positively affect a patient's care in many ways. However, genetic data are complex and present many challenges. We report on the usability of a novel application designed to assist providers in receiving and managing a patient's genetic profile, including ongoing updated interpretations of the genetic variants in those patients. Because these interpretations are constantly evolving, managing them represents a challenge. We conducted usability tests with potential users of this application and reported findings to the application development team, many of which were addressed in subsequent versions. Clinicians were excited about the value this tool provides in pushing out variant updates to providers and overall gave the application high usability ratings, but had some difficulty interpreting elements of the interface. Many issues identified required relatively little development effort to fix suggesting that consistently incorporating this type of analysis in the development process can be highly beneficial. For genetic decision support applications, our findings suggest the importance of designing a system that can deliver the most current knowledge and highlight the significance of new genetic information for clinical care. Our results demonstrate that using a development and design process that is user focused helped optimize the value of this application for personalized medicine.