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Klinik - Intelligent Patient Flow Management

NCT04577079 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 273

Last updated 2022-11-21

No results posted yet for this study

Summary

Digital health technologies (DHT) are increasingly developed to support healthcare systems around the world. However, they are frequently lacking evidence-based medicine and medical validation. There is considerable need in the western countries to allocate healthcare resources accurately and give the population detailed and reliable health information enabling to take greater responsibility for their health. Intelligent patient flow management system (IPFM, product name Klinik Frontline) is developed to meet these needs. In practice, IPFM is used for decision support in the triaging and diagnostic processes as well as automatizing the management of inflow of the patients. The core of the IPFM is a clinical artificial intelligence (AI), which utilizes a comprehensive medical database of clinical correlations generated by medical doctors.

The study population of this research consists of patients from the Emergency Department of Kuopio University Hospital (KUH). Data will be gathered during 2 weeks of piloting, after which the results will be analysed. Anticipated number of patients to the study is minimum of 246 patients, with objective to be several hundreds. When attending to the hospital, patients will report their demographics, background information and symptoms using structured IPFM online form. Patients entering the unit in an ambulance or with need of immediate care of healthcare professionals due to severe and acute conditions are referred similar to normal process to ensure the patient safety. Results obtained from IPFM are blinded from the healthcare professional and IPFM does not affect professional's clinical decision making in any way. The data obtained from IPFM online form and clinical data from the emergency department and KUH will be analysed after the data collection.

The main aim of the research is to validate the use of IPFM by evaluating the association of IPFM output with 1) urgency and severity of the conditions (using Emergency Severity Index \[ESI\], an international triaging protocol for emergency units, and an assessment by triage nurse); and 2) actual diagnoses diagnosed by medical doctors. The main hypotheses of the research are that 1) IPFM is safe and sensitive in evaluating the urgency of the conditions of arriving patients at the emergency department and that 2) IPFM has sufficient correlation of differential diagnosis with actual diagnosis made by medical doctor.

Conditions

  • Emergency Medical Services

Interventions

DEVICE

Evaluation of the need of emergency medical services

The main aim of this study is to validate the use of IPFM in a hospital setting by evaluating the association of IPFM output with 1) clinical urgency and severity of the conditions (using Emergency Severity Index \[ESI\], an international triaging protocol for emergency units, and an assessment by triage nurse); and 2) actual diagnoses made by the hospital doctors. The objective is also to assess the correlation of IPFM output with redirection or referral to various specialties

Sponsors & Collaborators

  • Kuopio University Hospital

    lead OTHER

Principal Investigators

  • Tero J Martikainen, MD. PhD · Kuopion University Hospital, Emergency medicine

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2020-09-01
Primary Completion
2020-10-31
Completion
2022-11-18

Countries

  • Finland

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04577079 on ClinicalTrials.gov