Research Studies

Peer-reviewed publications

Peer-reviewed research is essential for improving the quality, accuracy, and safety of healthcare technology. Here we present research papers that showcase the value and impact of Infermedica’s AI-powered solutions for healthcare professionals and decision-makers.

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Peer Reviewed

Impact of integrated virtual and live nurse triage on patient care seeking and health care delivery effectiveness and efficiency

Gellert et al. (2024)

Highlights
  • Infermedica’s virtual triage altered member care-seeking behavior in 83.9% of interactions

  • 22.8% of members changed the level of care they intended to seek after using VT-informed nurse triage implemented by Infermedica and Médis

  • 62.2% of those who changed intent de-escalated to lower-acuity care (telemedicine or self-care)

  • 20% of interactions took place outside of regular operating hours, Infermedica’s virtual triage directed 48.4% of these cases to lower acuity care


Peer Reviewed

An analysis of virtual triage utilization by pregnant women prior to and during the COVID-19 pandemic

Jaszczak et al. (2024)

Highlights
  • COVID-19 pandemic significantly influenced the use of VT by pregnant women

  • In the first six months of 2020, there was an increase in pregnant users of 213%

  • The percentage of pregnant users grew from 0.32% in the first half of 2019 to 0.85% in late 2021


Peer Reviewed

Virtual triage early detection of inappropriate care-seeking intent among patients with life-threatening cardiac symptoms

Gellert et al. (2024)

Highlights
  • 76.4% of users with symptoms of a heart attack didn't know the right level of care or planned to seek inappropriate care

  • This was observed across all age groups

  • By gender, there was a slightly higher percentage among female users


Peer Reviewed

Using AI-based virtual triage to improve acuity-level alignment of patient care seeking in an ambulatory care setting

Gellert et al. (2024)

Highlights
  • 35% of patients changed their care-seeking behavior

  • 12.5% decrease in video and in-person consultations

  • 19.1% increase in patient engagement through virtual care


Peer Reviewed

The potential of virtual triage AI to improve early detection, care acuity alignment, and emergent care referral of life-threatening conditions

Gellert et al. (2024)

Highlights
  • 76% of users with symptoms of a heart attack didn't plan urgent care help

  • 33.5% of users with symptoms of investigated acute conditions hadn’t planned medical consultation before completing virtual triage

  • 2 in every 1000 virtual triages performed could lead to life-saving decisions


Peer Reviewed

A comparative performance analysis of live clinical triage using rules-based triage protocols versus artificial intelligence-based automated virtual triage

Gellert et al. (2023)

Highlights
  • Infermedica and Schmitt-Thompson produced zero critical mis-triage situations — cases where an “emergency” is identified as “self-care”

  • Infermedica provides triage advice as safe as Schmitt-Thompson

  • Infermedica collects 4x more patient initial symptoms than Schmitt-Thompson for more data-driven assistance

  • Infermedica provides reliable and accurate results and increases triage levels in case of risk factors (especially for children)


Peer Reviewed

How virtual triage can improve patient experience and satisfaction: a narrative review and look forward

Gellert et al. (2023)

Highlights
  • Delivery of earlier and faster, more acuity-level-appropriate care

  • Digital triage as a front door to reduce a patient’s need to visit a medical facility for low-acuity conditions

  • The use of VT to enhance clinical effectiveness through early detection and referral

  • VT as an opportunity for providers to make patient health care experiences more personalized


Peer Reviewed

The role of virtual triage in improving clinician experience and satisfaction: a narrative review

Gellert et al. (2023)

Highlights
  • Importance of clinician experience and satisfaction to organizational performance

  • Contributors to poor clinician satisfaction

  • Current and potential role of virtual triage in delivering positive clinician experiences and streamlining communication with patients

  • Benefits of using virtual triage technology for healthcare delivery organizations in general and with respect specifically to improving clinician experience and satisfaction


Peer Reviewed

Cardiovascular disease prevention recommendations from an online chat-based AI model

Gellert, G. A., & Jaszczak, J. (2023)

Highlights
  • Generative AI vs. Symbolic AI in healthcare applications

  • Potential and limitations of large language models (LLMs)

  • Investment and research into healthcare AI


Peer Reviewed

A multinational survey of patient utilization of and value conveyed through virtual symptom triage and healthcare referral

Gellert et al. (2023)

Highlights
  • 80.1% of patients indicated substantial overall satisfaction with the experience and value delivered

  • 80% of users indicated that they will use triage recurrently in the future

  • 25.4% decrease in post-triage patients who remained uncertain of their care path


Peer Reviewed

The quality of diagnosis and triage advice provided by free online symptom checkers and apps in Australia

Highlights

Symptomate has the highest accuracy results:

  • 77% correct possible conditions listed in the top 3 results

  • 61% correct possible conditions listed as first

  • 81% correct possible conditions listed in the top 10 results


Peer Reviewed

Diagnostic accuracy of web-based COVID-19 symptom checkers: comparison study

Highlights
  • A good balance between sensitivity and specificity achieved only by two symptom checkers – COVID-RA by Infermedica and Symptoma

  • Infermedica and Symptoma were ranked at the top in terms of the accuracy for COVID-19 evaluations


Peer Reviewed

Virtual care to increase military medical centre capacity in the primary health care setting: a prospective self-controlled pilot study of symptoms collection and telemedicine

Highlights
  • 85.8% of patients were satisfied with the virtual care experience

  • 85.7% of patients agreed that the symptom checker was easy to use

  • Both patients and physicians felt that the symptom checker allowed for clearer and faster consultations


Peer Reviewed

Heuristic evaluation of COVID-19 chatbots

Highlights
  • Infermedica ranked in the top 3 best scoring chatbots

  • Infermedica as one of the web chat bots with the most attractive graphical user interface


Peer Reviewed

Application of a web-based self-assessment triage tool during the COVID-19 pandemic: descriptive study

Highlights
  • The CRA tool screened a vast audience—248,862 people with potentially worrisome symptoms indicating COVID-19

  • Getting results and next-step recommendations provided reassurance and evidence-based information

  • The CRA tool served as a preclinical triage for individuals with worrisome symptoms

How we develop, maintain, and test our technologies

A carefully curated medical information database lies at the very heart of the Infermedica platform. Get a better understanding of the processes used to build, maintain, and test our technologies.

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Content Development Process

The creation, validation, and maintenance of the medical knowledge base follow rigorous and well-established procedures.

Acceptance Test Cases

Learn how we test the quality of our inference engine by carrying out assessments on thousands of well-documented clinical cases.

Certifications
Class I Medical Device

Selected modules marked as class I medical device

GDPR compliant

Compliant with the General Data Protection Regulation

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LEI Code: 984500NIA7B8AFF75805

Quality Management System logo

Quality Management System compliant with PN-EN ISO 13485:2016

Processes and Development Procedures certified with ISO 27001:2017

HIPAA compliant

Compliant with standards for patient data protection

The proof of trust

The excellence of Infermedica’s technology is confirmed by real-life implementations in ecosystems of leading healthcare service providers.

0%

of patients who intended to go to the emergency room changed their mind

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0.4%

of all reported clients’ symptoms are covered by the tool

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