Coding Intelligence (OpenEvidence Visits)

by OpenEvidence  · Based in United States → — The most widely used medical AI platform among U.S. physicians.
Family Medicine Hospital Medicine Internal Medicine
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Overview

OpenEvidence is an AI-powered medical search engine and clinical decision support platform designed to help healthcare professionals quickly access and interpret evidence-based medical information. It provides accurate and efficient answers at the point of care, covering over 160 medical specialties and more than 1,000 diseases and therapeutic areas. The platform synthesizes answers from over 35 million peer-reviewed publications with full citations, allowing physicians to verify recommendations. OpenEvidence is built on a foundation of peer-reviewed medical literature, ensuring all information is sourced and cited, supporting evidence-based medicine. It is an official AI partner of The New England Journal of Medicine and JAMA, and has content agreements with organizations like NCCN, ACC, ADA, ACEP, and AAFP. The platform is available free to verified U.S. healthcare professionals.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Automatic CPT code suggestions
  • E/M level recommendations with supporting medical decision-making (MDM) rationale
  • ICD-10 diagnoses directly from clinical documentation
  • Automatic CPT code sequencing to maximize reimbursement
  • Analyzes and organizes peer-reviewed medical literature
  • Provides evidence-based answers with citations
  • Mobile and web access
  • Voice Mode for platform interaction
  • DeepConsult feature for synthesizing findings across multiple studies
  • Integrates with EHR workflows (e.g., Epic)

Use Cases

  • Answering clinical questions and treatment options
  • Drafting clinical notes and enriching assessments
  • Streamlining documentation and connecting decisions with patient context
  • Preparing for mock exams and conducting research
  • Developing appropriate treatment plans
  • Identifying appropriate laboratory tests

What Physicians Need to Know

Evidence Base
OpenEvidence (OE) draws from a comprehensive range of trusted, peer-reviewed sources, including major journals like NEJM, JAMA, Nature, and The Lancet, as well as clinical guidelines from organizations such as NCCN and Cochrane. [6, 12, 13, 24] It utilizes an AI platform, specifically a large language model (LLM) trained for medicine, to generate evidence-based answers that are always sourced and cited. [1, 6, 13, 21] The platform also has content partnerships with NEJM Group and JAMA Network to access full-text and multimedia content. [1, 12] A new feature, EvidenceGrade, assesses the quality, certainty, and relevance of cited evidence using the GRADE framework. [29]
Clinical Validation Studies
Retrospective analyses of OpenEvidence have shown promising alignment with physician decisions in chronic disease cases, with responses rated high in clarity, relevance, and evidence-based support. [1, 19, 24] However, prospective trials are needed to further evaluate its utility, especially in complex cases and multidisciplinary settings. [1, 19, 23] While OpenEvidence scored 100% on USMLE-type questions, its accuracy on complex subspecialty scenarios was lower (41% for 'Deep Consult' and 34% for 'Quick Consult') in a December 2025 preprint. [17, 20, 24] The impact on actual clinical decision-making was modest in some studies, often reinforcing clinician decisions rather than causing changes. [1, 19, 24]
Alert Fatigue Management
OpenEvidence's approach to clinical decision support differs from traditional EHR alerts, which can contribute to alert fatigue due to static rules and potential lag behind new evidence. [1] Instead, OpenEvidence dynamically synthesizes new research and contextualizes evidence relevant to a given patient scenario, providing reasoning, references, and synthesized insight rather than just warnings. [1]
Override Rate Data
Specific override rate data for OpenEvidence Visits is not explicitly detailed in the provided information. However, the tool is designed to complement a clinician's judgment and reinforce physician plans, rather than replace them. [1, 19]
Drug Interaction Checking
OpenEvidence can provide answers to clinical questions, including inquiries regarding drug interactions. [13] However, some reviews indicate that it does not currently offer dedicated drug dosing or comprehensive drug interaction tools, suggesting that a companion tool might be needed for these specific tasks. [17, 24]
Differential Diagnosis Support
OpenEvidence can assist clinicians and medical students in formulating informed differential diagnoses. [6, 13, 16] However, some sources note that it does not currently provide differential diagnosis *generation* as a core bedside task. [17]
Guideline Update Frequency
OpenEvidence aims to keep its evidence base and synthesized outputs constantly updated as new trials and research emerge. [1, 25] It has partnered with organizations like the American Academy of Otolaryngologyu2013Head and Neck Surgery Foundation (AAO-HNSF) to systematically evaluate guideline recommendations against current medical literature, flagging recommendations for review when new evidence supports revisions. [25] This approach helps ensure guidance stays accurate and relevant without waiting years for scheduled review cycles. [25]
Clinical Workflow Integration
OpenEvidence Visits is designed for smooth integration into clinical workflows, supporting EHR integration, context recall, and minimal disruption. [1, 4] It offers mobile and web access for verified healthcare professionals and integrates real-time evidence and guideline surfacing during patient encounters, including transcription and note drafting assistance. [1, 2, 4, 11] The 'Coding Intelligence' feature, available in OpenEvidence Visits, automatically applies CPT code suggestions, E/M level recommendations with supporting medical decision-making rationale, and ICD-10 diagnoses directly into the clinical note at the end of every visit. [3, 5, 8, 14, 15] It can also integrate with documentation workflows, supporting templates and allowing clinicians to ask questions as part of their normal documentation. [1, 2] The platform also offers an AI-integrated doctor dialer feature that unifies patient communication, clinical decision support, and documentation into a single workflow. [9, 28]
Decision Audit Trail
To foster trust and accountability, OpenEvidence is designed to be transparent, with every conclusion or recommendation citing its sources. [1, 13, 21] Users can inspect underlying citations, read abstracts, and check methodologies. [1] The platform allows for the management of past visits, including assigning to patients, changing associated patients, deleting records, and searching by summary or patient name, which can contribute to an audit trail. [27]
Physician Tip

Leverage 'Coding Intelligence' within OpenEvidence Visits to automatically generate CPT, E/M, and ICD-10 codes with supporting rationale directly in your notes, saving significant time on documentation. [3, 5, 8, 14, 15] Utilize the real-time evidence surfacing during patient encounters to quickly access guidelines and research, enhancing your assessment and plan. [1, 2] While OpenEvidence excels at providing cited evidence for common conditions and reinforcing existing decisions, be mindful of its current limitations in generating differential diagnoses or comprehensive drug dosing tools for complex or rare cases, and consider using it as a complementary tool alongside your clinical judgment. [17, 19, 24] Always review the cited sources and the new 'EvidenceGrade' feature to understand the quality and strength of the evidence before making critical treatment decisions. [1, 29]

OpenEvidence Visits is designed for seamless integration into clinical workflows, including potential EHR integration. [1, 4, 21] The platform's 'Coding Intelligence' feature operates directly within Visits, analyzing clinical notes to provide coding recommendations. [3, 8, 15] OpenEvidence also offers an AI-integrated doctor dialer feature that unifies communication, clinical decision support, and documentation. [9, 28] Future deeper integrations are planned with systems like genomic data assets and clinical trial matching systems, as seen in partnerships with organizations like OneOncology. [7]

Details

Category Clinical Decision Support & Reference, Medical Billing & RCM
Pricing Free — Free for NPI-verified physicians; funded by pharmaceutical advertising.
DeploymentCloud-based
Compliance
BAA Available Yes AI-estimated
HIPAA Compliant Yes AI-estimated
FDA Status Unknown AI-estimated — unknown
Integrations
EHR Not specified
Specialties Family Medicine, Hospital Medicine, Internal Medicine

What the Web Says

Coding Intelligence, part of OpenEvidence Visits, is an AI-powered tool designed to automate medical coding, including ICD-10 diagnoses, E/M level recommendations with MDM rationale, and CPT code suggestions. It aims to streamline clinical documentation and maximize reimbursement for physicians. While OpenEvidence as a whole is praised for providing fast, cited answers to clinical questions from peer-reviewed literature, the accuracy of its AI-generated responses, particularly for complex cases, has been a point of discussion among users.

Overall: Mixed

Strengths

  • Automates ICD-10 diagnoses, E/M level recommendations, and CPT code suggestions, saving physicians time on documentation.
  • Generates MDM rationale automatically, supporting billing by complexity or time.
  • Suggests uncommon procedure codes that might otherwise be missed, potentially increasing reimbursement.
  • Provides expected RVU values for CPT suggestions, aiding in correct code sequencing.
  • OpenEvidence (the broader platform) offers fast, evidence-based answers with citations from reputable medical journals.
  • Free for verified US physicians.

Limitations

  • Accuracy concerns exist, especially for complex subspecialty scenarios, with some studies reporting accuracy as low as 34-41%.
  • Some users report instances of the AI summarizing research incorrectly or overstating findings.
  • Does not currently offer differential diagnosis generation or drug dosing tools.
  • The ad-supported model (pharmaceutical advertising) is a factor procurement teams may want to review.
  • Requires NPI verification, limiting access to US-based healthcare professionals.
  • Some users have reported outdated or harmful medical advice, such as recommending graded exercise therapy for ME/CFS.

Based on reviews from: Clinical AI Report, Reddit (r/emergencymedicine, r/OpenEvidenceHub, r/physicianassistant, r/medicine), Trustpilot, Apple App Store, YouTube (OpenEvidence Review: What Doctors Must Know - SpeakMD), Becker's Hospital Review, Sermo, G2, PMC - NIH, iatroX, PR Newswire, Fastio (MedAI Verdict), Techy Surgeon, Fierce Healthcare

Last updated: 2026-08-24

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Press & Coverage

PR Newswire
OpenEvidence Launches Coding Intelligenceu2122 to Help Physicians Capture Every Dollar They've Earned
OpenEvidence launched Coding Intelligenceu2122 to automate the medical coding process and help physicians capture missing reimbursement, allowing them to focus more on patient care. This tool is available to all verified clinicians using OpenEvidence.
2026-03
Business Wire
OpenEvidence Raises $250 Million to Build Medical Superintelligence for Doctors
OpenEvidence, an AI platform widely used by doctors in America, announced a $250 million Series D funding round, valuing the company at $12 billion. This funding will support the development of medical superintelligence for doctors.
2026-01
PR Newswire
OpenEvidence Achieves Historic Milestone: 1 Million Clinical Consultations between Verified Doctors and an Artificial Intelligence System in a Single Day
OpenEvidence reached a milestone of one million clinical consultations between verified physicians and its AI system in a single day, demonstrating the scalable collaboration between human and artificial intelligence in medicine.
2026-03
OpenEvidence News
OpenEvidence Partners with Cedars-Sinai to Create Patient-Aware Clinical Intelligence With Agentic Clinical AI
OpenEvidence announced a partnership with Cedars-Sinai Health System to integrate patient context from Epic directly into OpenEvidence, creating a new class of agentic clinical AI for context-aware answers.
2026-05
Distilled Post
OpenEvidence Withdraws Clinical AI Platform from UK and Europe Over Regulatory Uncertainty
OpenEvidence has withdrawn its clinical decision support application from the UK and European markets, citing regulatory uncertainty, particularly regarding the EU Artificial Intelligence Act.
2026-04
PR Newswire
Physicians Choose OpenEvidence Over Every Other AI Chatbot Combined in Independent Stanford-Harvard Study of Clinical AI
An independent Stanford-Harvard study found that practicing physicians chose OpenEvidence more than all other external AI chatbots combined for clinical decision support.
2026-07
Springer Nature
Springer Nature and OpenEvidence announce agreement to maximise exposure of trusted findings on OpenEvidence platform
Springer Nature and OpenEvidence have partnered to integrate peer-reviewed content from Springer Nature into the OpenEvidence platform, allowing physicians to access and cite trusted research during patient care.
2026-08
medRxiv
The accuracy and repeatability of OpenEvidence on complex medical subspecialty scenarios: a pilot study
A pilot study on medRxiv evaluated the accuracy and repeatability of OpenEvidence's quick search (OE) and Deep Consult (DC) features on complex medical subspecialty scenarios, finding highest accuracy for DC at 41% and OE at 34%.
2025-12

Videos

Product demos, reviews, and walkthroughs for Coding Intelligence (OpenEvidence Visits).

View all on YouTube

Frequently Asked Questions

Coding Intelligence (OpenEvidence Visits) is designed to integrate seamlessly with most major EHR systems through APIs, allowing it to analyze clinical documentation in real-time and provide coding recommendations and clinical insights directly within your workflow. This integration aims to minimize disruption and enhance the accuracy of your medical coding and documentation.
OpenEvidence Visits is developed with a strong emphasis on compliance, adhering to current coding guidelines (e.g., ICD-10, CPT) and healthcare regulations. The system provides transparent rationales for its coding suggestions, which can be reviewed and edited by the physician, aiding in audit readiness and ensuring that the final submitted codes accurately reflect the clinical encounter.
While several solutions offer clinical decision support and coding assistance, OpenEvidence Visits differentiates itself through its advanced AI and machine learning capabilities, focusing on both coding accuracy and identifying potential gaps in clinical documentation. Comparisons often highlight its ability to learn from physician feedback and adapt to specific practice patterns, offering a more personalized and continuously improving experience.
The pricing for Coding Intelligence (OpenEvidence Visits) typically involves a subscription model, which can vary based on the size of the practice, the number of users, and the specific features required. There are often different tiers designed to accommodate solo practitioners, small group practices, and larger healthcare systems, with detailed quotes provided upon request after an assessment of needs.
While highly advanced, Coding Intelligence (OpenEvidence Visits) may have limitations in interpreting extremely rare or highly complex clinical scenarios that lack extensive data for its AI models to learn from. In such cases, the system is designed to flag these instances for physician review, ensuring that human expertise remains paramount for nuanced decision-making and accurate coding.
OpenEvidence Visits is designed to be a collaborative tool. Physicians can easily override or modify any coding suggestions. The system is built with machine learning capabilities that allow it to learn from these physician interactions, continuously refining its algorithms to better align with individual physician preferences and specific clinical contexts over time.
Yes, a key feature of Coding Intelligence (OpenEvidence Visits) is its ability to analyze clinical documentation not only for accurate coding but also to identify areas where documentation may be insufficient to support the highest level of specificity or complexity. This proactive identification of potential under-coding or missed documentation opportunities can help optimize reimbursement and improve overall revenue cycle management.

Compare Coding Intelligence (OpenEvidence Visits)

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OpenEvidence vs Coding Intelligence (OpenEvidence Visits)
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These two tools are highly comparable as they are both offerings from OpenEvidence, targeting U.S. healthcare professionals with free, AI-powered clinical decision support. While 'OpenEvidence' focuses broadly on…
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Suggest an Edit → | Last Verified: 2026-08-23 | First Added: 2026-08-23

Investors who backed Coding Intelligence (OpenEvidence Visits)

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