Validation of Intelligent Patient Flow Management System in Kuopio University Hospital Emergency Department
Trial ID: NCT04577079
Status: COMPLETED
Study type: OBSERVATIONAL
Start date: 2020-09-01
Completion date: 2022-11-18
Sponsor: Kuopio University Hospital
Conditions: Emergency Medical Services
Interventions: Evaluation of the need of emergency medical services
Locations: Kuopio university hospital
Countries: Finland
Enrollment: 273
Age range: 18 Years - None
Sex: ALL

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.

Eligibility criteria:
Inclusion Criteria:

All adult (\>18 years of age) patients independently (walking) entering emergency care ward with written consent.

Exclusion Criteria:

* Patients arriving with ambulance
* Patients needing immediate care
* Patients under 18 years of age
* Patients with restricted capabilities or developmental disorders.

Outcomes:
Specificity (%) of intelligent patient flow management (IPFM) correlated with the evaluation of trained emergency (triage) nurse.; Sensitivity (%) of intelligent patient flow management (IPFM) correlated with the evaluation of trained emergency (triage) nurse.