Better prevention through infection risk management in hospitals
By Nosotech | Published on March 14, 2022
Problem and objectives
Problem
- Rapid spread of hospital-acquired infections
- Increase in duration of care
- Difficult to identify origin of infections
- Difficult to analyze all patient and hospital data (ADT, labs, pharmacy, operating rooms, ER)
- Waste of time and inadequate use of clinical infection prevention experts
Objectives
- Detect nosocomial infections in real time
- Identify patients at risk of developing an infection (under development)
- Prevent hospital-acquired infections by isolating infected patients and patients at risk
Proposed solution
Solution
Nosotech is a Québec company whose mission is to provide healthcare workers with innovative information management solutions. Its software provides real-time access to multiple clinical data sources and integrates artificial intelligence (AI) modules to improve organizational efficiency and quality of care.
The company’s key products are:
- Nosokos: Real-time management tool for healthcare-associated infections
- Antibiokos: Tool for the management of antibiotic use and resistance
- Si-Spin: Portal for the management of national nosocomial infection surveillance programs
- Iris: Aggregated management of laboratory test data in real time for COVID-19
Principle
Nosokos is a surveillance and prevention optimization software program for healthcare-related infections that analyzes ADT, laboratory, pharmacy, operating room, ER, etc. data to identify at-risk cases in real time. It enables infection prevention and control teams to prevent, monitor, oversee and manage nosocomial infections.
User experience
Nosokos software is connected to the hospital’s computer system. It analyzes patient data and sends out alerts if an infection outbreak is identified.
The software automatically creates and populates a patient record with all the collected data. It produces epidemic curves to view changes based on several criteria. It generates and transmits reports for national surveillance programs.
Over time, the software will be able to predict whether a patient is at risk of infection upon arriving at the hospital (under development).
Role of AI
Algorithms that are used
- Detection of laboratory events
- Optimization of antibiotic prescriptions
- Search for patient contacts (close or extended)
- Interpretation of screening results
- Standardization of events from external systems, such as patient movement, laboratory, surgery and pharmacy management systems
Statistical calculations
- Production of cumulative antibiograms
- Turnaround time (TAT)
- Production of a multitude of graphs (including epidemic curves)
- Creatinine clearance calculations
- Calculation of defined daily doses (DDDs) and duration of treatment (DOT)
Deep learning (in development)
- Automated risk prediction models (to come)
Impacts
Main outcomes
Experience and patient care:
- Prediction of infection risk at hospital admission
- Better hospital care (isolation of patient if necessary)
Medical team wellbeing:
- Reduction in data collection time by 90%
- Monitoring the distribution of infections in care units
- Efficient management of isolated patients and carriers of antibiotic resistant bacteria
- Optimization of time spent on prevention
Population health:
Automates the production of national surveillance reports
Health costs:
Reduction in costs associated with nosocomial infections through reduced duration of infection (isolation) and hospitalization
Generation and dissemination of new knowledge:
- Scientific papers published by researchers using Nosotech’s technology (including in the American Journal of Epidemiology and the Journal of Antimicrobial Chemotherapy)
- Scientific presentations (including AMMI Canada – CACMID)
Economic development:
Increase in number of employees: +100% in 2 years
Challenges takled
Nosotech faces system interoperability issues. Nosokos connects to systems that collect heterogeneous data to make its detections and predictions. From one hospital to the next, changes can be seen in epidemic monitoring rules, laboratory business rules and semantics. Increasing the homogeneity of data and data collection, across different systems as well as across hospitals, would enable more efficient integration of Nosokos and more reliable results, as well as the potential to develop new, more powerful functionalities.
Conditions for success
Team mobilised
More than 20 full-time employees
Areas of expertise
- Microbiology
- Infectiology
- Clinical semantic interoperability
- IT specialists (80% of the team)
- Digital product expertise
Collaborations
Implementation
Nosotech’s solutions are found in all Québec hospitals. More specifically, Nosokos is in use in around 60% of hospitals and IRIS in 100% of hospitals, including:
- CHUM;
- CHU de Québec – Université Laval;
- CHUSJ;
- CUSM.
Its solutions are also deployed in European hospitals, including:
- Centre hospitalier Sud Francilien (Corbeil-Essonnes);
- CHU Limoges (Limoges);
- Hôpital Érasme Université Libre de Bruxelles (Brussels);
- Institut mutualiste Montsouris (Paris).
Collaboration
The company is collaborating with the Government of Québec on compliance with monitoring rules, in particular with the Institut national de santé publique du Québec.
Funding received
- SaaS revenue: installation costs and support contracts
- R&D programs
- Public funding
- Investors
Project stages
Launch of a new user interface (Fall 2021)
Project stages - to come
Continuous development to improve performance
Introduction of new modules
Development related to predictive monitoring
Tool for large-scale aggregated management of laboratory data
Context of the solution
Use cases
The patient is admitted to the hospital for surgery. While there, he developed an infection. Nosokos detects the infection by analyzing patient and hospital data. It sends an alert to identify, isolate and treat the infected patient. This significantly limits the spread of infection.
Other use case (in development) The patient is admitted to the hospital for surgery. By analyzing the patient’s personal and contextual data, Nosokos predicts that the patient is at risk of developing an infection. Medical personnel then takes the necessary steps to prevent infection, such as preventive isolation for the patient, preventive treatment, etc., in order to not put the patient’s life at risk.
Customers
Business Model – B2B
Hospitals are implementing Nosokos in their system to prevent infections
Business Model – Research centres
Nosotech is currently developing partnerships and participating in research programs so that research institutes and universities can use its data.
Market opportunity
- Market for infection surveillance solutions: US$372m (2020); forecast at US$712m (by 2026): +12.5% per year
- Global market for clinical decision support systems (CDSS): USD$2.5B by 2028: + 8.6% per year
- Global interoperability of health care systems: US$4B in 2029; forecast at US$8B (by 2024): 13.8% per year