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Ervin, Keondae

Mayo Clinic

National Evaluation System for Health Technology Coordinating Center, Medical Device Innovation Consortium, Arlington, Virginia

Citations 4

Safety and Effectiveness of a Catheter With Contact Force and 6-Hole Irrigation for Ablation of Persistent Atrial Fibrillation in Routine Clinical Practice
Dhruva, Sanket S. , Zhang, Shumin , Chen, Jiajing , Doshi, Amit, Agboola, Kolade M. , Jiang, Guoqian , Yu, Yue , Cafri, Guy , Farr, Kimberly Collison, Ervin, Keondae, Noseworthy, Peter A. , Herrin, Jeph , Ross, Joseph S. , COPLAN, PAUL M. , Drozda, Joseph P.

JAMA Network Open | August 19, 2022 | Volume: 5 | Issue: 8 | Pages: e2227134

10.1001/jamanetworkopen.2022.27134 Get It

Pre S cription Digita L Th E rap E utic for P
Dreyer, Rachel P. , Berkowitz, Alyssa, Schneeberg, Lynelle, Shah, Nilay D. , Emanuel, Lindsay, Kolla, Bhanuprakash , Jeffery, Molly M. , Deeg, Mark A. , Ervin, Keondae, Thorndike, Frances P. , Jeffery, Molly Moore , Yaggi, Henry Klar , Kolla, Bhanu Prakash , Ross, Joseph S.

BMJ Open | August 8, 2022 | Volume: 12 | Issue: 8 | Pages: e062041

10.1136/bmjopen-2022-062041 Get It

Introduction Cognitive behavioural therapy for insomnia (CBT-I) is effective at treating chronic insomnia, yet in-person CBT-I can often be challenging to access. Prior studies have used technology to bridge barriers but have been unable to extensively assess the impact of the digital therapeutic on real-world patient experience and multidimensional outcomes. Among patients with insomnia, our aim is to determine the impact of a prescription digital therapeutic (PDT) (PEAR-003b, FDA-authorised as Somryst; herein called PDT) that provides mobile-delivered CBT-I on patient-reported outcomes (PROs) and healthcare utilisation. Methods and analysis We are conducting a pragmatically designed, prospective, multicentre randomised controlled trial that leverages Hugo, a unique patient-centred health data-aggregating platform for data collection and patient follow-up from Hugo Health. A total of 100 participants with insomnia from two health centres will be enrolled onto the Hugo Health platform, provided with a linked Fitbit (Inspire 2) to track activity and then randomised 1:1 to receive (or not) the PDT for mobile-delivered CBT-I (Somryst). The primary outcome is a change in the insomnia severity index score from baseline to 9-week postrandomisation. Secondary outcomes include healthcare utilisation, health utility scores and clinical outcomes; change in sleep outcomes as measured with sleep diaries and a change in individual PROs including depressive symptoms, daytime sleepiness, health status, stress and anxiety. For those allocated to the PDT, we will also assess engagement with the PDT. Ethics and dissemination The Institutional Review Boards at Yale University and the Mayo Clinic have approved the trial protocol. This trial will provide important data to patients, clinicians and policymakers about the impact of the PDT device delivering CBT-I on PROs, clinical outcomes and healthcare utilisation. Findings will be disseminated to participants, presented at professional meetings and published in peer-reviewed journals. Trial registration number NCT04909229 .
Heart Watch Study: protocol for a pragmatic randomised controlled trial
Dhruva, Sanket S. , Shah, Nilay D. , Vemulapalli, Sreekanth , Deshmukh, Abhishek , Gamble, Ginger , Hummel, James P. , Piccini, Jonathan P. , Akar, Joseph G. , Ervin, Keondae, Arges, Kristine, Emanuel, Lindsay, Hu, Tiffany , Bartlett, Victoria , Gamble, Ginger M , Piccini, Jonathan P , Beatty, Alexis L. , Freeman, James V. , Noseworthy, Peter A. , Hu, Tiffany, Ross, Joseph S.

BMJ Open | December 30, 2021 | Volume: 11 | Issue: 12 | Pages: e054550

10.1136/bmjopen-2021-054550 Get It

Introduction Personal digital devices that provide health information, such as the Apple Watch, have developed an increasing array of cardiopulmonary tracking features which have received regulatory clearance and are directly marketed to consumers. Despite their widespread and increasing use, data about the impact of personal digital device use on patient-reported outcomes and healthcare utilisation are sparse. Among a population of patients with atrial fibrillation and/or atrial flutter undergoing cardioversion, our primary aim is to determine the impact of the heart rate measurement, irregular rhythm notification, and ECG features of the Apple Watch on quality of life and healthcare utilisation. Methods and analysis We are conducting a prospective, open-label multicentre pragmatic randomised clinical trial, leveraging a unique patient-centred health data sharing platform for enrolment and follow-up. A total of 150 patients undergoing cardioversion for atrial fibrillation or atrial flutter will be randomised 1:1 to receive the Apple Watch Series 6 or Withings Move at the time of cardioversion. The primary outcome is the difference in the Atrial Fibrillation Effect on QualiTy-of-life global score at 6 months postcardioversion. Secondary outcomes include inpatient and outpatient healthcare utilisation. Additional secondary outcomes include a comparison of the Apple Watch ECG and pulse oximeter features with gold-standard data obtained in routine clinical care settings. Ethics and dissemination The Institutional Review Boards at Yale University, Mayo Clinic, and Duke University Health System have approved the trial protocol. This trial will provide important data to policymakers, clinicians and patients about the impact of the heart rate, irregular rhythm notification, and ECG features of widely used personal digital devices on patient quality of life and healthcare utilisation. Findings will be disseminated to study participants, at professional society meetings and in peer-reviewed journals. Trial registration number NCT04468321
Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report
Jiang, Guoqian , Dhruva, Sanket S. , Chen, Jiajing , Doshi, Amit, Zhang, Shumin , Young, H. P. , Ervin, Keondae, Shah, Nilay D. , Patrick Young, H , Drozda, Joseph P. , Schulz, Wade L. , Noseworthy, Peter A. , Yu, Yue , Brandt, Eric, Ross, Joseph S. , COPLAN, PAUL M.

Journal of the American Medical Informatics Association | May 29, 2021 | Volume: 28 | Issue: 10 | Pages: 2241-2250

10.1093/jamia/ocab117 Get It

Abstract Objective The study sought to conduct an informatics analysis on the National Evaluation System for Health Technology Coordinating Center test case of cardiac ablation catheters and to demonstrate the role of informatics approaches in the feasibility assessment of capturing real-world data using unique device identifiers (UDIs) that are fit for purpose for label extensions for 2 cardiac ablation catheters from the electronic health records and other health information technology systems in a multicenter evaluation. Materials and Methods We focused on data capture and transformation and data quality maturity model specified in the National Evaluation System for Health Technology Coordinating Center data quality framework. The informatics analysis included 4 elements: the use of UDIs for identifying device exposure data, the use of standardized codes for defining computable phenotypes, the use of natural language processing for capturing unstructured data elements from clinical data systems, and the use of common data models for standardizing data collection and analyses. Results We found that, with the UDI implementation at 3 health systems, the target device exposure data could be effectively identified, particularly for brand-specific devices. Computable phenotypes for study outcomes could be defined using codes; however, ablation registries, natural language processing tools, and chart reviews were required for validating data quality of the phenotypes. The common data model implementation status varied across sites. The maturity level of the key informatics technologies was highly aligned with the data quality maturity model. Conclusions We demonstrated that the informatics approaches can be feasibly used to capture safety and effectiveness outcomes in real-world data for use in medical device studies supporting label extensions.