A 2024 Heart Rhythm Society perspective piece on CIED data workflows described a problem that rarely makes it into vendor marketing: most cardiac device data is still locked in proprietary, often image- or PDF-based formats that don't talk to each other, forcing clinics and research teams alike to cobble together incompatible systems just to manage it. That paper, co-authored by clinicians and engineers across the device and remote-monitoring industry (including contributors from several of the platforms discussed below), points to standardized data interoperability as the long-term fix. That work is ongoing industry-wide.
For a research coordinator trying to build a cohort or prep a dataset for submission, the gap between "standard eventually" and "usable today" decides whether a project ships on time or never gets off the ground. The platforms built for day-to-day clinical triage rarely solve this problem, because it isn't the one they were built to solve.
TL;DR: The best cardiac monitoring software for research needs more than a set of premade dashboards and a large dataset. It needs structured, queryable data that isn't locked behind a request-and-wait process, and, ideally, a vendor that can point to peer-reviewed evidence of its technology's performance.
Key Takeaways
- Research teams need direct, structured access to monitoring data, beyond a clinical review dashboard built for triage
- Ask Atlas™ lets research staff query Octagos's implanted and ambulatory monitoring data in natural language, with no request to a third party
- Multi-site scalability matters for any platform supporting multi-center studies
- Published, peer-reviewed evidence on the underlying technology is worth more than a vendor's own claims
Ask Atlas: Built for This Use Case
Most cardiac remote monitoring platforms treat data access as something you request. You build a hypothesis and wait for someone to build a dashboard that answers your question, or wait on a manual export you'll still need to clean before you can use it.
Ask Atlas takes a different approach: research staff query Octagos's implanted and ambulatory monitoring data in natural language, the same way they'd ask a colleague a question, with no export request or manual pull.
A coordinator building a cohort of patients with a specific arrhythmia burden over a defined window, or pulling transmission compliance rates across a multi-site study, can get there directly instead of reconstructing it from raw exports after the fact.
That matters more than it sounds on paper, because the bottleneck in most research workflows is the time between "we need this dataset" and "this dataset is available to analyze."
Ask Atlas runs on the same data infrastructure as Octagos's remote monitoring platform, which includes Atlas AI™, the triage engine at the center of the Two-Brain Approach™. In that model, Atlas AI™ prioritizes each transmission and a certified device specialist reviews it. Its performance has been published in two peer-reviewed studies: 99.5% accuracy across 690,673 transmissions in JACC: Advances (2025), and a 57% reduction in non-actionable transmissions in Heart Rhythm O2 (2023). That means Ask Atlas is a query tool built on infrastructure with a track record of peer-reviewed, published scrutiny.
For a research team, the actual pitch is direct access to your data without a middleman, on top of a data platform that's already been through peer review, even as we continue building out published evidence for Ask Atlas specifically.
What Each Platform Offers for Research Use
Octagos: the strongest fit for teams that need to query data directly instead of waiting on dashboards or exports. Ask Atlas gives research staff natural-language access to implanted and ambulatory monitoring data, with no manual exports. Atlas AI, the triage engine underneath, has published, peer-reviewed performance data (JACC: Advances, 2025 and Heart Rhythm O2, 2023; see references). Those studies cover transmission triage; published evidence for the natural-language query layer is still being built.
Implicity: a European vendor with a research-oriented feature set, including a dedicated research tool with built-in eCRF and patient consent management, and raw (non-PDF) discrete data across manufacturers. Worth a look for teams running formal multi-site studies with consent and case-report-form requirements and want to do that directly through their remote monitoring software.
PaceMate: offers a large aggregated dataset (device, EHR, and operational data combined) with flexible custom filtering in a range of pre-built dashboards.
Murj: offers pre-built dashboards and exportable reports, explicitly marketed for supporting research and quality-improvement work, though the workflow leans more on structured reporting than open-ended querying.
91 Life: advertises AI-powered patient insights and large-scale data access with patient-specific queries. We haven't independently verified the accuracy claims behind this, and haven't found published clinical validation; worth asking directly before relying on it for a study.
RhythmScience (Rhythm360): the platform's public materials focus on billing capture and alert triage across vendors more than research-specific tooling. Recent hiring for a clinical AI research role suggests population/cohort analytics may be in development, but there's no published research-use case study yet.
Frequently Asked Questions
What makes cardiac monitoring software suitable for research versus everyday clinical use? Clinical use prioritizes triage speed and billing capture. Research use prioritizes structured, queryable data and a dataset large enough to draw conclusions from.
What is Ask Atlas and how is it different from standard data export? Ask Atlas lets research staff query your data in natural language without filing a manual export request and cleaning the result afterward. It's built to answer specific research questions directly, isolating a patient cohort by arrhythmia type, or pulling compliance rates across a multi-site study, instead of handing back a raw file that still needs to be shaped into something usable.
What security certifications should a research institution require? SOC 2 Type II, SOC 3, HITRUST, and HIPAA compliance are standard requirements for any use of patient data.
Can a platform built for single-institution use support a multi-center study? Not typically. This is where legacy, on-prem platforms tend to fall short. Gathering data across institutions is much more labor-intensive without a cloud-based, multi-site architecture. Confirm that the solution you are considering has role and site functionality that supports multicenter structures.
See How Ask Atlas Handles Your Research Data
Most research delays in cardiac monitoring come from the time it takes to turn raw transmission data into something a research team can actually analyze.
If your team is still filing export requests or cleaning up data before you can even start building a cohort, it's worth seeing how a query-first approach changes that timeline.
References
- Slotwiner DJ, Serwer GA, Allred JD, et al. 2024 HRS perspective on advancing workflows for CIED remote monitoring. Heart Rhythm O2. 2024;5(12):845-853. https://doi.org/10.1016/j.hroo.2024.09.012
- Bawa D, Ghazal R, Kabra R, et al. Role of Artificial Intelligence in Reducing Data Deluge From Cardiac Implantable Electronic Devices. JACC: Advances. 2025;4(10_Part_2):102057. https://doi.org/10.1016/j.jacadv.2025.102057
- Bawa D, Kabra R, Ahmed A, et al. Data deluge from remote monitoring of cardiac implantable electronic devices and importance of clinical stratification. Heart Rhythm O2. 2023;4(6):374-381. https://doi.org/10.1016/j.hroo.2023.04.005