Clinerion Patent for Technology Underpinning Patient Network Explorer is Published

ClinerionThe new Clinerion patent underpins any medical EHR database infrastructure that incorporates a hybrid model of cloud-and-local server node installations at individual hospitals, as well as any method for search of patient cohort care metrics across such a platform. This allows real-time search at each individual hospital across the entire network at once, returning aggregate metrics from the entire network. This technology forms the basis of Clinerion's Patient Network Explorer.

System: The patent covers a federated network connecting separate healthcare databases with patient records extracted from hospital information systems. Records containing patient treatment metrics such as diagnoses, medications, treatments, procedures, lab results and vital signs, can be searched disparately to return aggregate cohort results per database. In particular, the patent details the set-up of local hospital servers and de-identification modules that transfer local data into anonymized data servers within the hospital environment, separated from identifiable personal data by a firewall.

Method: The patent includes a methodology for selection and identification of de-identified subjects for clinical study, thereby accelerating cohort search and reducing costs. The patent's claims include all cases where a patient cohort is selected based on inclusion/exclusion criteria applied to electronic health records (EHRs) at partner hospitals.

The patent builds in data protection, as it incorporates restrictions to data transfer from the local server to outbound connections, while having no inbound ports, thereby preventing hacking of the local server. The patent also describes a firewall, encryption, and/or additional protective components, as well as the use of an anonymization module on patient data before a request may be initiated. The patent further introduces a reverse identification process crucial to clinical research outreach processes, such as patient engagement. Note that ANID, Clinerion’s state-of-the-art technology for unlinked de-identification of patient records, as well as a process for re-identification, is described in a follow-up patent.

In the instance of Clinerion’s Patient Network Explorer, real-time patient searches are enabled across disparate hospital sites, countries, and languages. De-identified EHRs at the partner hospitals may be queried from the Clinerion cloud, returning a cohort count of relevant patients fitting the inclusion/exclusion criteria. This allows:

  • Identification of the patient cohort, as well as extended usages, such as cohort modeling and cohort feasibility, outcomes analysis and chart review feasibility,
  • Analyses of patient reported outcomes, retrospective studies, or any other real-world evidence generation,
  • Diagnostic outreach, fast patient outreach for patient reported outcomes, recruitment to clinical trials based on real-time EHR updates, and secure re-identification routines, and
  • Real-time data metrics across all partner hospitals.

"This patent is the culmination of development work going back many years," says Dr. Andreas Walter, Clinerion Chief Technology Officer. "Our original aim was to provide huge efficiency savings in patient search for clinical trial recruitment, an area which famously requires high costs and time, using cutting-edge Big Data analytics technologies. We are pleased that the results, in the form of Patient Network Explorer, and all its attending services, now offer real benefits throughout the research timeline."

"Clinerion's proprietary technology has always been a solid cornerstone to our business," says Dr. Barış Erdoğan, Clinerion Chief Executive Officer. "The publication of this patent brings our intellectual property strongly into the light. Having spent many years in healthcare data analytics, we are committed to be a pioneer in the field by bringing in secure, scalable, and trustworthy solutions with the sole aim of creating better patient outcomes."

"This patent represents the foundation of our venture to solve the hardest problem of simplifying access to real-world data," says Ulf Claesson, Clinerion Board Member. "How to not only create homogenous views across different geographies, languages, regulations, and coding standards, but also to guarantee full patient privacy. And now we do that across 26 countries around the globe."

The patent, EP 2015/059415, "PATIENT RECRUITMENT SYSTEM AND PATIENT RECRUITMENT METHOD," was published in the European Patent Bulletin 2021/30 on July 28th, 2021. The patent was submitted on March 30th, 2014. The related US patent is expected to be published soon.

About Clinerion

Clinerion accelerates clinical research and medical access to treatments for patients. We generate real-world data from our global network of partner hospitals for Real World Evidence analyses. Clinerion's Patient Network Explorer radically improves the efficiency and effectiveness of clinical trial recruitment by offering data-driven protocol optimization, site feasibility evaluation and real-time patient search and identification to match patients to treatments.

Clinerion facilitates the participation of partner hospitals in leading-edge, industry-sponsored trials and time savings in patient recruitment. Researchers gain access to real-time, longitudinal patient data from electronic health records for analysis. We enable pharmaceutical companies, CROs and SMOs to shorten patient recruitment and save costs by streamlining operations and leveraging strategic intelligence. Clinerion's Patient Network Explorer also provides a platform for integration of diverse patient data sources into real-world data ecosystems. Clinerion’s proprietary technologies comply with international patient privacy and data security regulations. Clinerion is a global data technology service company headquartered in Switzerland.

www.clinerion.com

Most Popular Now

Researchers Invent AI Model to Design Ne…

Researchers at McMaster University and Stanford University have invented a new generative artificial intelligence (AI) model which can design billions of new antibiotic molecules that are inexpensive and easy to...

Two Artificial Intelligences Talk to Eac…

Performing a new task based solely on verbal or written instructions, and then describing it to others so that they can reproduce it, is a cornerstone of human communication that...

Greater Manchester Reaches New Milestone…

Radiologists and radiographers at Northern Care Alliance NHS Foundation Trust have become the first in Greater Manchester to use the Sectra picture archiving and communication system (PACS) to report on...

Alcidion and Novari Health Forge Strateg…

Alcidion Group Limited, a leading provider of FHIR-native patient flow solutions for healthcare, and Novari Health, a market leader in waitlist management and referral management technologies, have joined forces to...

Powerful New AI can Predict People'…

A powerful new tool in artificial intelligence is able to predict whether someone is willing to be vaccinated against COVID-19. The predictive system uses a small set of data from demographics...

AI-Based App can Help Physicians Find Sk…

A mobile app that uses artificial intelligence, AI, to analyse images of suspected skin lesions can diagnose melanoma with very high precision. This is shown in a study led from...

ChatGPT can Produce Medical Record Notes…

The AI model ChatGPT can write administrative medical notes up to ten times faster than doctors without compromising quality. This is according to a new study conducted by researchers at...

Can Language Models Read the Genome? Thi…

The same class of artificial intelligence that made headlines coding software and passing the bar exam has learned to read a different kind of text - the genetic code. That code...

Advancing Drug Discovery with AI: Introd…

A transformative study published in Health Data Science, a Science Partner Journal, introduces a groundbreaking end-to-end deep learning framework, known as Knowledge-Empowered Drug Discovery (KEDD), aimed at revolutionizing the field...

Study Shows Human Medical Professionals …

When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations...

Wanted: Young Talents. DMEA Sparks Bring…

9 - 11 April 2024, Berlin, Germany. The digital health industry urgently needs skilled workers, which is why DMEA sparks focuses on careers, jobs and supporting young people. Against the backdrop of...

Shared Digital NHS Prescribing Record co…

Implementing a single shared digital prescribing record across the NHS in England could avoid nearly 1 million drug errors every year, stopping up to 16,000 fewer patients from being harmed...