Endobits
by Bio-Conscious Technologies Inc.
· Based in Canada →
— Automated CGM Monitoring & Diabetes Decision Support
$99 per patient per month for practices under 1,000 patients on service; volume pricing above that.
Regulatory Status Disclosed
Overview
Endobits, developed by Bio-Conscious Technologies Inc., is a diabetes and metabolic decision-support platform designed for healthcare professionals. It integrates data from continuous glucose monitoring (CGM) devices, wearables, and electronic health records (EHRs) to provide insights into patient metabolic health.
- What it does: Endobits analyzes patient data to identify individuals who require intervention, prioritizes them based on risk, and offers decision support for diabetes and metabolic management. It can forecast glucose levels up to 12 hours in advance and detect insulin dysregulation with reported accuracy. The platform also automates aspects of remote patient monitoring (RPM) and chronic care management (CCM) documentation.
- Who it is for: The tool is intended for use by primary care physicians, endocrinologists, and payers. It aims to assist primary care in managing diabetes within their patient population and to help endocrinology teams focus on complex cases by automating routine CGM review.
- How it fits a clinical or practice workflow: Endobits integrates with existing EHR/EMR systems and is designed to streamline the review of CGM data. Instead of manual chart review, which can be time-consuming, Endobits provides a prioritized worklist of patients who are off-target, allowing clinicians to review and approve recommendations. It also generates documentation for billing purposes related to RPM and CCM.
- Notable capabilities: Key features include automated CGM monitoring, a ranked worklist to prioritize patients, and self-documenting RPM/CCM capabilities. It is compatible with various FDA-cleared CGM hardware, including Dexcom, Abbott, and Senseonics. Endobits also offers predictive analytics for glucose levels and can identify patterns such as repeated lows or persistent highs, suggesting potential interventions.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Automated CGM monitoring
- Real-time data collection from CGM, wearables, EMR, and EHR
- Patient triage and prioritization based on medical risk
- Personalized recommendations for patients
- Centralized dashboard for remote monitoring
- Daily analytics reports customized for each patient
- Integration with major EMR/EHR platforms (eClinicalWorks, Cerner, Athenahealth, OSCAR, Cliniko)
- Forecasts glucose up to 12 hours ahead
- Automated documentation for remote patient monitoring (RPM) and chronic care management (CCM) CPT codes
- Companion app for patients (iOS and Android)
Use Cases
- Remote patient monitoring for diabetes and metabolic health
- Identifying and prioritizing high-risk patients
- Closing care gaps between physician visits
- Augmenting CDCES teams and clearing backlogs in endocrinology
- Preventing complications and reducing avoidable admissions for payers and HMOs
- Supporting virtual care and remote appointments
What Physicians Need to Know
Evidence Base
Endobits leverages cutting-edge research and scientific rigor, utilizing advanced machine-learning algorithms to analyze real-time patient data from continuous glucose monitors (CGM), wearables, EMR, and EHR systems. It aims to understand glucose variability more accurately and treat patients more effectively, including acting preemptively. The platform provides practical, cited guides on continuous glucose monitoring, prediabetes, type 2 diabetes, remote monitoring and billing, and metabolic health. Endobits' algorithms have demonstrated high accuracy in areas such as insulin dysregulation detection (91.5%), forecasting nocturnal hypoglycemia (97.8% accuracy, 99.2% sensitivity, 97.4% specificity), and blood glucose forecasting (93.6% accuracy, 83.6% sensitivity, 96.1% specificity).
Clinical Validation Studies
Endobits is described as clinically validated. Multiple clinical studies and real-world applications have shown improved outcomes for both patients and healthcare providers. For patients, this includes a 19% increase in time-in-range, a 1% reduction in HbA1c levels, and a 43% decrease in hypoglycemic events. For healthcare providers, benefits include faster, more accurate charting and billing, smart decision support to identify high-priority patients, and auto-populating care plans with evidence-based guidelines. Pilot projects were planned to demonstrate the benefits of using Endobits' AI to prioritize and triage patients compared to existing tools.
Alert Fatigue Management
Endobits addresses alert fatigue by providing a ranked worklist of patients who are off-target, rather than inundating clinicians with numerous alerts. Patients who are within their target range remain silent, ensuring that clinicians only receive notifications for those who truly need intervention. This approach aims to reduce the mental and operational exhaustion caused by an overwhelming number of low-priority or irrelevant alerts, which is a common issue in healthcare.
Drug Interaction Checking
The provided information does not explicitly state that Endobits includes a drug interaction checking feature. Its primary focus is on diabetes and metabolic decision support through continuous glucose monitoring data analysis.
Differential Diagnosis Support
Endobits focuses on diabetes and metabolic health, using AI to analyze glucose patterns for metabolic status reports and to identify high-risk patients. It helps in understanding glucose variability and predicting blood glucose levels up to 12 hours in advance. While it provides decision support for diabetes management, the information does not specifically detail broad differential diagnosis support across various medical conditions.
Guideline Update Frequency
Endobits auto-populates care plans with evidence-based guidelines. Clinical decision support systems, in general, are more effective when their knowledge base is up-to-date and incorporates new research findings. The Endocrine Society, which publishes guidelines relevant to Endobits' domain, continually creates new guidelines and updates existing ones to reflect evolving clinical science. However, the specific frequency of guideline updates within the Endobits platform is not explicitly mentioned.
Clinical Workflow Integration
Endobits is designed for seamless integration into major Electronic Medical Records (EMR) and Electronic Health Records (EHR) platforms in the USA and Canada. This integration aims to simplify data interoperability and improve patient therapy and clinical administrative processes. It offers a ranked worklist, automated CGM monitoring, and remote patient monitoring (RPM)/chronic care management (CCM) that documents itself, aiming for no new staff or login requirements for clinicians. The platform automates and improves the accuracy and efficiency of patient data analysis, allowing healthcare providers to focus on personalized care. Endobits also integrates with specific EHR systems like Cliniko, allowing for automatic syncing of data and simplified billing using existing CPT codes.
Decision Audit Trail
Endobits keeps track of clinician actions for simple end-of-cycle billing for remote patient monitoring. It also auto-charts monitoring and interactive care time, mapping it to Medicare RPM and CCM codes (99453, 99454, 99457, 99458). This indicates a level of auditing for billing and potentially for tracking clinical interventions, though a comprehensive 'decision audit trail' for every clinical decision made using the tool is not explicitly detailed.
Physician Tip
Endobits can significantly streamline diabetes management by automating CGM data analysis and prioritizing high-risk patients, freeing up clinician time for personalized care. The platform's ability to forecast nocturnal hypoglycemia and detect insulin dysregulation with high accuracy can lead to proactive interventions and improved patient outcomes. Its integration with existing EMR/EHR systems and automated documentation for RPM/CCM billing can reduce administrative burden. Focus on the prioritized worklist to efficiently address patient needs, as the system is designed to minimize alert fatigue.
Endobits integrates with major EMR/EHR providers in the USA and Canada, including eClinicalWorks, Cerner, Athenahealth, OSCAR, and Cliniko. It is compatible with continuous glucose monitors (CGM) such as Dexcom Share, Freestyle Libre, MiaoMiao 2, and Nightscout. The platform also supports remote patient monitoring (RPM) and chronic care management (CCM) billing through automated documentation.
Details
| Category | Clinical Decision Support & Reference, Endocrinology & Metabolic AI |
| Pricing |
$99 per patient per month for practices under 1,000 patients on service; volume pricing above that.
|
| Deployment | Web-based platform, cloud-based. |
| Compliance | |
| BAA Available | Yes AI-estimated |
| HIPAA Compliant | Yes AI-estimated |
| FDA Status |
Cleared AI-estimated Endobits is clinical decision-support software that runs on top of FDA-cleared continuous glucose monitors (CGMs) and is not a diagnostic device or a substitute for professional medical advice, diagnosis, or treatment. Bio Conscious is working toward a Novel Therapeutic (De Novo) designation from the FDA for the use of its preventive technology in diabetes. |
| Integrations | |
| EHR | Not specified |
| Specialties | Endocrinology, Family Medicine, Internal Medicine |
What the Web Says
Endobits is a platform designed to help endocrinologists manage large diabetes patient panels more efficiently, particularly by automating the review of Continuous Glucose Monitoring (CGM) data. It aims to reduce the time clinicians spend on routine chart reviews, allowing them to focus on more complex cases and potentially clear patient backlogs. The system integrates with existing Electronic Medical Records (EMRs) and provides features like patient prioritization and automated basal rate suggestions for review.
Overall: PositiveStrengths
- Automates routine CGM review, saving significant clinician time (up to 30-45 minutes per patient).
- Helps clear patient backlogs and reduces wait times for referrals.
- Auto-triages diabetes panels, allowing specialists to focus on complex cases.
- Flags critical patterns like severe overnight lows and persistent glucose spikes.
- Easy to set up and integrate with existing EMR/EHR systems without new hardware or software installation.
- Provides actionable suggestions for medication adjustments (e.g., basal rate) for clinician approval.
Limitations
- No specific negative reviews from physicians, healthcare IT, or tech reviewers were found for Endobits.com.
- General sentiment on Reddit suggests some experienced diabetic patients find endocrinologists' advice often generic or unhelpful, primarily seeing them as necessary for prescriptions, which could indirectly impact the perceived value of tools supporting routine endocrinology care if not focused on complex cases.
- Some Reddit users express frustration with the need for frequent in-person visits for prescriptions or insurance requirements, even with good self-management, which Endobits aims to alleviate by streamlining remote data review.
Based on reviews from: Endobits, Reddit, Capterra, G2, Healthgrades
Last updated: 2026-08-25
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Videos
Product demos, reviews, and walkthroughs for Endobits.
Preventing High Risk Complications For Type 1 and Type 2 Diabetes With The Endobits App
Bio Conscious
Endobits App for Type 1 & 2 Diabetes: Using AI To Predict Blood Glucose Levels 12 Hours In Advance
Bio Conscious
The Endobits Story: From Growing 15,000 Users Organically To Launching With Clinics Across The U.S.
Bio Conscious
AI In Medicine: Can Machine Learning Technology Explain The Link Between Dementia and Diabetes?
Bio Conscious
Meet CEO Amir Hayeri: From Pursuing A Career In Medicine To Developing Machine-Learning Technology
Bio Conscious
Meet Chief Technology Officer Keith Burke
Bio Conscious
Frequently Asked Questions
Endobits is designed to integrate seamlessly with existing EHR/EMR systems, including eClinicalWorks, Cerner, Athenahealth, and OSCAR. It connects to FDA-cleared Continuous Glucose Monitors (CGMs) and synthesizes data into a prioritized worklist, surfacing guideline-aligned next steps. This process aims to reduce the time spent on CGM chart review, which can take up to 45 minutes per patient, by automating data analysis and documentation.
Endobits is clinical decision-support software for qualified healthcare professionals and runs on top of FDA-cleared CGMs. It is HIPAA-compliant by design. The platform auto-charts monitoring and interactive care time, mapping it to Medicare RPM and CCM codes (99453, 99454, 99457, 99458), which can be billed under your own providers. Reimbursement varies by payer and documentation, and claims are the responsibility of the billing provider.
While Endobits focuses on AI-powered CGM data analysis and decision support, alternatives in diabetes management include other CGM apps, wearable artificial pancreas systems, smart insulin pens, and microneedle patches for drug delivery. Additionally, some EHR systems specifically designed for endocrinology offer comprehensive diabetes management tools, including CGM integration and AI documentation features.
Endobits costs $99 per patient per month for practices with under 1,000 patients on service, with volume pricing available for larger practices. There are no setup fees, and practices can cancel anytime. Most practices can cover the cost with the first handful of enrolled patients through remote patient monitoring reimbursement.
Endobits is clinical decision-support software and is not a diagnostic device or a substitute for professional medical advice, diagnosis, or treatment. It does not practice medicine, and providers retain full clinical authority and responsibility for all care decisions. The information provided is educational only, and individual results may vary.
Endobits utilizes AI to predict blood glucose levels up to 12 hours in advance with high accuracy. It boasts a 91.5% accuracy rate in detecting insulin dysregulation and a 97.8% accuracy rate in forecasting nocturnal hypoglycemia, with a sensitivity of 99.2% and specificity of 97.4%. This allows for proactive identification of high-priority patients and potential complications.
Yes, Endobits is designed to help manage large patient panels efficiently without requiring new staff like Certified Diabetes Care and Education Specialists (CDCES) or PharmDs. It automates onboarding, monitoring, and data review, providing a prioritized worklist of patients who are off-target, allowing clinicians to focus on those who need intervention.
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| Last Verified: 2026-08-23 | First Added: 2026-08-23