Testing a Cloud-Based Model for Active Surveillance of Medical Devices with Analyses of Coronary Stent Safety Using the Data Extraction and Longitudinal Trend Analysis (DELTA) System.

Objective: To demonstrate the use of the Data Extraction and Longitudinal Trend Analysis (DELTA) system in the National Evaluation System for health Technology's (NEST) medical device surveillance cloud environment by analyzing coronary stent safety using real world clinical data and comparing results to clinical trial findings. Design and Setting: Electronic health record (EHR) data from two health systems, the Social Security Death Master File, and device databases were ingested into the NEST cloud, and safety analyses of two stents were performed using DELTA. Participants and Interventions: This is an observational study of patients receiving zotarolimus drug-eluting coronary stents (ZES) or everolimus eluting coronary stents (EES) between July 1, 2015 and December 31, 2017. Results: After exclusions, 3334 patients receiving EES and 1002 receiving ZES were available for study. Analysis using inverse probability weighting showed no significant difference in one-year mortality or major adverse cardiac events (MACE) for EES compared to ZES [Mortality Odds Ratio 0.94 (95% CI 0.81-1.175); p = 0.780] [MACE Odds Ratio 1.04 (95% CI 0.92-1.16; p = 0.551]). Analysis using propensity matching showed no significant difference in EES one-year mortality (547 of 992 alive and available after censoring) compared to ZES (546 of 992) [Log-Rank statistic 0.3348 (p = 0.563)]. Conclusion: Automated cloud-based medical device safety surveillance using EHR data is feasible and was efficiently performed using DELTA. No statistically significant differences in 1-year safety outcomes between ZES and EES were identified using two statistical approaches, consistent with randomized trial findings.

Using real-world data from health systems to evaluate the safety and effectiveness of a catheter to treat ischemic ventricular tachycardia.

BACKGROUND: The ThermoCool STSF catheter is used for ablation of ischemic ventricular tachycardia (VT) in routine clinical practice, although outcomes have not been studied and the catheter does not have Food and Drug Administration (FDA) approval for this indication. We used real-world health system data to evaluate its safety and effectiveness for this indication. METHODS: Among patients undergoing ischemic VT ablation with the ThermoCool STSF catheter pooled across two health systems (Mercy Health and Mayo Clinic), the primary safety composite outcome of death, thromboembolic events, and procedural complications within 7 days was compared to a performance goal of 15%, which is twice the expected proportion of the primary composite safety outcome based on prior studies. The exploratory effectiveness outcome of rehospitalization for VT or heart failure or repeat VT ablation at up to 1 year was averaged across health systems among patients treated with the ThermoCool STSF vs. ST catheters. RESULTS: Seventy total patients received ablation for ischemic VT using the ThermoCool STSF catheter. The primary safety composite outcome occurred in 3/70 (4.3%; 90% CI, 1.2-10.7%) patients, meeting the pre-specified performance goal, p = 0.0045. At 1 year, the effectiveness outcome risk difference (STSF-ST) at Mercy was - 0.4% (90% CI: - 25.2%, 24.3%) and at Mayo Clinic was 12.6% (90% CI: - 13.0%, 38.4%); the average risk difference across both institutions was 5.8% (90% CI: - 12.0, 23.7). CONCLUSIONS: The ThermoCool STSF catheter was safe and appeared effective for ischemic VT ablation, supporting continued use of the catheter and informing possible FDA label expansion. Health system data hold promise for real-world safety and effectiveness evaluation of cardiovascular devices.

Integrating real-world data to assess cardiac ablation device outcomes in a multicenter study using the OMOP common data model for regulatory decisions: implementation and evaluation.

The objective of this study is to describe application of the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) to support medical device real-world evaluation in a National Evaluation System for health Technology Coordinating Center (NESTcc) Test-Case involving 2 healthcare systems, Mercy Health and Mayo Clinic. CDM implementation was coordinated across 2 healthcare systems with multiple hospitals to aggregate both medical device data from supply chain databases and patient outcomes and covariates from electronic health record data. Several data quality assurance (QA) analyses were implemented on the OMOP CDM to validate the data extraction, transformation, and load (ETL) process. OMOP CDM-based data of relevant patient encounters were successfully established to support studies for FDA regulatory submissions. QA analyses verified that the data transformation was robust between data sources and OMOP CDM. Our efforts provided useful insights in real-world data integration using OMOP CDM for medical device evaluation coordinated across multiple healthcare systems.

Exploring unique device identifier implementation and use for real-world evidence: a mixed-methods study with NESTcc health system network collaborators.

Objectives: To examine the current state of unique device identifier (UDI) implementation, including barriers and facilitators, among eight health systems participating in a research network committed to real-world evidence (RWE) generation for medical devices. Design: Mixed methods, including a structured survey and semistructured interviews. Setting: Eight health systems participating in the National Evaluation System for health Technology research network within the USA. Participants: Individuals identified as being involved in or knowledgeable about UDI implementation or medical device identification from supply chain, information technology and high-volume procedural area(s) in their health system. Main outcomes measures: Interview topics were related to UDI implementation, including barriers and facilitators; UDI use; benefits of UDI adoption; and vision for UDI implementation. Data were analysed using directed content analysis, drawing on prior conceptual models of UDI implementation and the Exploration, Preparation, Implementation, Sustainment framework. A brief survey of health system characteristics and scope of UDI implementation was also conducted. Results: Thirty-five individuals completed interviews. Three of eight health systems reported having implemented UDI. Themes identified about barriers and facilitators to UDI implementation included knowledge of the UDI and its benefits among decision-makers; organisational systems, culture and networks that support technology and workflow changes; and external factors such as policy mandates and technology. A final theme focused on the availability of UDIs for RWE; lack of availability significantly hindered RWE studies on medical devices. Conclusions: UDI adoption within health systems requires knowledge of and impetus to achieve operational and clinical benefits. These are necessary to support UDI availability for medical device safety and effectiveness studies and RWE generation.

Safety and Effectiveness of a Catheter With Contact Force and 6-Hole Irrigation for Ablation of Persistent Atrial Fibrillation in Routine Clinical Practice.

Importance: The ThermoCool SmartTouch catheter (ablation catheter with contact force and 6-hole irrigation [CF-I6]) is approved by the US Food and Drug Administration (FDA) for paroxysmal atrial fibrillation (AF) ablation and used in routine clinical practice for persistent AF ablation, although clinical outcomes for this indication are unknown. There is a need to understand whether data from routine clinical practice can be used to conduct regulatory-grade evaluations and support label expansions. Objective: To use health system data to compare the safety and effectiveness of the CF-I6 catheter for persistent AF ablation with the ThermoCool SmartTouch SurroundFlow catheter (ablation catheter with contact force and 56-hole irrigation [CF-I56]), which is approved by the FDA for this indication. Design, Setting, and Participants: This retrospective, comparative-effectiveness cohort study included patients undergoing catheter ablation for persistent AF at Mercy Health or Mayo Clinic from January 1, 2014, to April 30, 2021, with up to a 1-year follow-up using electronic health record data. Exposures: Use of the CF-I6 or CF-I56 catheter. Main Outcomes and Measures: The primary safety outcome was a composite of death, thromboembolic events, and procedural complications within 7 to 90 days. The exploratory effectiveness outcome was a composite of AF-related hospitalization events after a 90-day blanking period. Propensity score weighting was used to balance baseline covariates. Risk differences were estimated between catheter groups and averaged across the 2 health care systems, testing for noninferiority of the CF-I6 vs the CF-I56 catheter with respect to the safety outcome using 2-sided 90% CIs. Results: Overall, 1450 patients (1034 [71.3%] male; 1397 [96.3%] White) underwent catheter ablation for persistent AF, including 949 at Mercy Health (186 CF-I6 and 763 CF-I56; mean [SD] age, 64.9 [9.2] years) and 501 at Mayo Clinic (337 CF-I6 and 164 CF-I56; mean [SD] age, 63.7 [9.5] years). A total of 798 (55.0%) had been treated with class I or III antiarrhythmic drugs before ablation. The safety outcome (CF-I6 - CF-I56) was similar at both Mercy Health (1.3%; 90% CI, -2.1% to 4.6%) and Mayo Clinic (-3.8%; 90% CI, -11.4% to 3.7%); the mean difference was noninferior, with a mean of 0.5% (90% CI, -2.6% to 3.5%; P < .001). The effectiveness was similar at 12 months between the 2 catheter groups (mean risk difference, -1.8%; 90% CI, -7.3% to 3.7%). Conclusions and Relevance: In this cohort study, the CF-I6 catheter met the prespecified noninferiority safety criterion for persistent AF ablation compared with the CF-I56 catheter, and effectiveness was similar. This study demonstrates the ability of electronic health care system data to enable safety and effectiveness evaluations of medical devices.

Multi-institutional distributed data networks for real-world evidence about medical devices: building unique device identifiers into longitudinal data (BUILD).

Objectives: To support development of a robust postmarket device evaluation system using real-world data (RWD) from electronic health records (EHRs) and other sources, employing unique device identifiers (UDIs) to link to device information. Methods: To create consistent device-related EHR RWD across 3 institutions, we established a distributed data network and created UDI-enriched research databases (UDIRs) employing a common data model comprised of 24 tables and 472 fields. To test the system, patients receiving coronary stents between 2010 and 2019 were loaded into each institution's UDIR to support distributed queries without sharing identifiable patient information. The ability of the system to execute queries was tested with 3 quality assurance checks. To demonstrate face validity of the data, a retrospective survival study of patients receiving zotarolimus or everolimus stents from 2012 to 2017 was performed using distributed analysis. Propensity score matching was used to compare risk of 6 cardiovascular outcomes within 12 months postimplantation. Results: The test queries established network functionality. In the analysis, we identified 9141 patients (Mercy = 4905, Geisinger = 4109, Intermountain = 127); mean age 65 ± 12 years, 69% males, 23% zotarolimus. Separate matched analyses at the 3 institutions showed hazard ratio estimates (zotarolimus vs everolimus) of 0.85-1.59 for subsequent percutaneous coronary intervention (P = .14-.52), 1.06-2.03 for death (P = .16-.78) and 0.94-1.40 for the composite endpoint (P = .16-.62). Discussion: The analysis results are consistent with clinical studies comparing these devices. Conclusion: This project shows that multi-institutional data networks can provide clinically relevant real-world evidence via distributed analysis while maintaining data privacy.

Advancing Patient Safety Surrounding Medical Devices: Barriers, Strategies, and Next Steps in Health System Implementation of Unique Device Identifiers.

Background: The requirement for medical device manufacturers to label their devices with a unique device identifier (UDI) was formalized by the 2013 US Food and Drug Administration Unique Device Identification System Rule. However, parallel regulatory requirement for US health systems to use UDIs, particularly the electronic documentation of UDIs during patient care is lacking. Despite the lack of regulation, some health systems have implemented and are using UDIs. To assess the current state, we studied representative health system UDI implementation experiences, including barriers and the strategies to overcome them, and identified next steps to advance UDI adoption. Methods: Semi-structured interviews were performed with health system personnel involved in UDI implementation in their cardiac catheterization labs or operating rooms. Interviews were transcribed and analyzed using the framework methodology of Ritchie and Spencer. An expert panel evaluated findings and informed barriers, strategies, and next steps. Results: Twenty-four interviews at ten health systems were performed. Identified barriers were internal (lack of organizational support, information technology gaps, clinical resistance) and external (information technology vendor resistance, limitations in manufacturer support, gaps in reference data, lack of an overall UDI system). Identified strategies included relationship building, education, engagement, and communication. Next steps to advance UDI adoption focus on education, research, support, and policy. Conclusions and Implications: Delineation of UDI implementation barriers and strategies provides guidance and support for health systems to adopt the UDI standard and electronically document UDIs during clinical care. Next steps illuminate critical areas for attention to advance UDI adoption and achieve a comprehensive UDI system in health care to strengthen patient care and safety.

Advancing Patient Safety Surrounding Medical Devices: A Health System Roadmap to Implement Unique Device Identification at the Point of Care.

BACKGROUND: The US Food and Drug Administration's Unique Device Identification System Rule of 2013 mandated manufacturers to assign unique device identifiers (UDIs) to their medical devices. Most high-risk (Class III), moderate-risk (Class II) and implantable devices now have UDIs. To achieve the necessary next step for a comprehensive UDI-enabled system for patient safety, UDIs must be electronically documented during patient care, a process not routinely done. The purpose of this research was to study the implementation experiences of diverse health systems in order to develop a roadmap for UDI implementation at the point of care. METHODS: Semi-structured interviews were conducted with personnel at health systems that had implemented UDI for implantable devices in their cardiac catheterization labs or operating rooms. Interviews were audio-recorded, transcribed, and analyzed using the framework methodology of Ritchie and Spencer. Data interpretation involved development of a conceptual model and detailed recommendations for UDI implementation. An expert panel evaluated and provided input on the roadmap. RESULTS: Twenty-four interviews at ten health systems were conducted by phone. Participants described implementation steps, factors and barriers impacting implementation. Findings populated a UDI implementation roadmap, that includes Foundational Themes, Key Components, Key Steps, UDI Use, and Outcomes. CONCLUSIONS AND IMPLICATIONS: The UDI implementation roadmap provides a framework for health systems to address the necessary steps and multilevel factors that underpin UDI implementation at the point of care. It is intended to guide and advance routine electronic documentation of UDIs for devices used during clinical care, the critical next step for a comprehensive UDI-enabled system to enhance medical device safety and effectiveness for patients.

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.

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.

Feasibility of using real-world data in the evaluation of cardiac ablation catheters: a test-case of the National Evaluation System for Health Technology Coordinating Center.

OBJECTIVES: To determine the feasibility of using real-world data to assess the safety and effectiveness of two cardiac ablation catheters for the treatment of persistent atrial fibrillation and ischaemic ventricular tachycardia. DESIGN: Retrospective cohort. SETTING: Three health systems in the USA. PARTICIPANTS: Patients receiving ablation with the two ablation catheters of interest at any of the three health systems. MAIN OUTCOME MEASURES: Feasibility of identifying the medical devices and participant populations of interest as well as the duration of follow-up and positive predictive values (PPVs) for serious safety (ischaemic stroke, acute heart failure and cardiac tamponade) and effectiveness (arrhythmia-related hospitalisation) clinical outcomes of interest compared with manual chart validation by clinicians. RESULTS: Overall, the catheter of interest for treatment of persistent atrial fibrillation was used for 4280 ablations and the catheter of interest for ischaemic ventricular tachycardia was used 1516 times across the data available within the three health systems. The duration of patient follow-up in the three health systems ranged from 91% to 97% at ≥7 days, 89% to 96% at ≥30 days, 77% to 90% at ≥6 months and 66% to 84% at ≥1 year. PPVs were 63.4% for ischaemic stroke, 96.4% for acute heart failure, 100% at one health system for cardiac tamponade and 55.7% for arrhythmia-related hospitalisation. CONCLUSIONS: It is feasible to use real-world health system data to evaluate the safety and effectiveness of cardiac ablation catheters, though evaluations must consider the implications of variation in follow-up and endpoint ascertainment among health systems.

Achieving Data Liquidity: Lessons Learned from Analysis of 38 Clinical Registries (The Duke-Pew Data Interoperability Project.

BACKGROUND: To assess the current state of clinical data interoperability, we evaluated the use of data standards across 38 large professional society registries. METHODS: The analysis included 4 primary components: 1) environmental scan, 2) abstraction and cross-tabulation of clinical concepts and corresponding data elements from registry case report forms, dictionaries, and / or data models, 3) cross-tabulation of same across national common data models, and 4) specifying data element metadata to achieve native data interoperability. RESULTS: The registry analysis identified approximately 50 core clinical concepts. None were captured using the same data representation across all registries, and there was little implementation of data standards. To improve technical implementation, we specified 13 key metadata for each concept to be used to achieve data consistency. CONCLUSION: The registry community has not benefitted from and does not contribute to interoperability efforts. A common, authoritative process to specify and implement common data elements is greatly needed.

Constructing the informatics and information technology foundations of a medical device evaluation system: a report from the FDA unique device identifier demonstration.

Objective: The US Food and Drug Administration (FDA) has recognized the need to improve the tracking of medical device safety and performance, with implementation of Unique Device Identifiers (UDIs) in electronic health information as a key strategy. The FDA funded a demonstration by Mercy Health wherein prototype UDIs were incorporated into its electronic information systems. This report describes the demonstration's informatics architecture. Methods: Prototype UDIs for coronary stents were created and implemented across a series of information systems, resulting in UDI-associated data flow from manufacture through point of use to long-term follow-up, with barcode scanning linking clinical data with UDI-associated device attributes. A reference database containing device attributes and the UDI Research and Surveillance Database (UDIR) containing the linked clinical and device information were created, enabling longitudinal assessment of device performance. The demonstration included many stakeholders: multiple Mercy departments, manufacturers, health system partners, the FDA, professional societies, the National Cardiovascular Data Registry, and information system vendors. Results: The resulting system of systems is described in detail, including entities, functions, linkage between the UDIR and proprietary systems using UDIs as the index key, data flow, roles and responsibilities of actors, and the UDIR data model. Conclusion: The demonstration provided proof of concept that UDIs can be incorporated into provider and enterprise electronic information systems and used as the index key to combine device and clinical data in a database useful for device evaluation. Keys to success and challenges to achieving this goal were identified. Fundamental informatics principles were central to accomplishing the system of systems model.

Heart Failure Readmission Reduction.

Little is known regarding effectiveness of readmission reduction programs over time. The Heart Failure Management Program (HFMP) of St. John's Physician Group Practice (PGP) Demonstration provided an opportunity to assess outcomes over an extended period. Data from an electronic health record, an inpatient database, a disease registry, and the Social Security Death Master File were analyzed for patients admitted with heart failure (HF) for 5 years before (Period 1) and 5 years after (Period 2) inception of PGP. HF admissions decreased (Period 1, 58.3/month; Period 2, 52.4/month, P = .007). Thirty-day all-cause readmission rate dropped from Period 1 (annual average 18.8% [668/3545]) to year 1 of Period 2 (16.9% [136/804], P = .04) and remained stable thereafter (annual average 16.8% [589/3503]). Thirty-day mortality rate was flat throughout. HFMP was associated with decreased readmissions, primarily related to outpatient case management, while mortality remained stable.

Advancing medical device innovation through collaboration and coordination of structured data capture pilots: Report from the Medical Device Epidemiology Network (MDEpiNet) Specific, Measurable, Achievable, Results-Oriented, Time Bound (SMART) Think Tank.

The Medical Device Epidemiology Network (MDEpiNet) is a public private partnership (PPP) that provides a platform for collaboration on medical device evaluation and depth of expertise for supporting pilots to capture, exchange and use device information for improving device safety and protecting public health. The MDEpiNet SMART Think Tank, held in February, 2013, sought to engage expert stakeholders who were committed to improving the capture of device data, including Unique Device Identification (UDI), in key electronic health information. Prior to the Think Tank there was limited collaboration among stakeholders beyond a few single health care organizations engaged in electronic capture and exchange of device data. The Think Tank resulted in what has become two sustainable multi-stakeholder device data capture initiatives, BUILD and VANGUARD. These initiatives continue to mature within the MDEpiNet PPP structure and are well aligned with the goals outlined in recent FDA-initiated National Medical Device Planning Board and Medical Device Registry Task Force white papers as well as the vision for the National Evaluation System for health Technology.%.

The Mercy unique device identifier demonstration project: Implementing point of use product identification in the cardiac catheterization laboratories of a regional health system.

Mercy, a 4 state health system, conducted an FDA-sponsored demonstration whereby prototype unique device identifiers (UDIs) of coronary stents were implemented in its electronic information systems for safety surveillance and research. To accomplish this, a multi-disciplinary team implemented a point of use barcode scanning inventory management system in all 5 Mercy cardiac catheterization laboratories. The system's potential for improving inventory management and tracking Cath Lab supplies was felt to be sufficiently compelling for system deployment outside of the context of the demonstration. Further, it was felt to be useful for all Cath Lab renewable supplies and not just coronary stents. Benefits included preventing procedure delays, lowering costs, and increasing revenue. Finally, the system is extensible to all implanted medical devices and generalizable to most hospitals.

Predictable and SuStainable Implementation of National Cardiovascular Registries (PASSION) infrastructure: A think tank report from Medical Device Epidemiological Network Initiative (MDEpiNet).

The MDEpiNet is a public-private partnership between the US Food and Drug Administration's Center for Devices and Radiological Health and participating partners. The PASSION program is an MDEpiNet-sponsored program that aims to demonstrate the goals of MDEpiNet by using cardiovascular medical device registries to bridge evidence gaps across the medical device total product life cycle. To this end, a PASSION Think Tank meeting took place in October 2014 in Silver Spring, MD, to facilitate discussion between stakeholders about the successes, challenges, and future novel applications of medical device registries, with particular emphasis on identifying pilot projects. Participants spanned a broad range of groups including patients, device manufacturers, regulators, physicians/academicians, professional societies, providers, and payers. The meeting focus included 4 areas of cardiovascular medicine intended to cultivate interest in 4 MDEpiNet disease-specific/device-specific working groups: coronary intervention, electrophysiology, valvular disease, and peripheral vascular disease. In addition, more general issues applying to registry-based infrastructure and analytical methodologies for assessing device benefit/risk were considered to provide context for the working groups as PASSION programs going forward. This article summarizes the discussions at the meeting and the future directions of the PASSION program.