GeoHAI App for Healthcare-Associated Infections

Overseen By Ohio State University Office of Responsible Research Practices

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Ohio State University

Disqualifiers: Not infection preventionist, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 1

25 Participants Needed

Trial Summary

Do I need to stop my current medications for this trial?

The trial protocol does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment GeoHAI for healthcare-associated infections?

The research suggests that using electronic systems, like apps, can help detect and reduce healthcare-associated infections by improving efficiency and accuracy in monitoring these infections. ^{1 2 3 4 5}

How does the GeoHAI App treatment for healthcare-associated infections differ from other treatments?

The GeoHAI App is unique because it uses GeoAI, which combines artificial intelligence with geographic information systems, to monitor and control healthcare-associated infections by analyzing spatial and temporal data. This approach is different from traditional treatments as it focuses on improving surveillance and decision-making through advanced technology rather than direct medical intervention. ^{6 7 8 9 10}

What is the purpose of this trial?

Geographic Information Systems (GIS) and spatial analysis have become important tools in public health informatics but have rarely been applied to the hospital setting. In this study we apply these tools to address the challenge of Hospital Acquired Infections (HAIs) by building, implementing, and evaluating a new computer application which incorporates mapping and geographic data to assist hospital epidemiologists in identifying HAI clusters and assessing transmission risk. We expect that incorporation of geographic information into the workflow of hospital epidemiologists will have a profound effect on our understanding of disease transmission and HAI risk factors in the hospital setting, radically altering the workflow and speed of response of infection preventionists and improving their ability to prevent HAIs.

Research Team

Courtney Hebert, MD

Principal Investigator

Ohio State University

Eligibility Criteria

This trial is for infection preventionists and physicians who are involved in infection control at the participating health system. It's not open to those who aren't in this role or don't work within the specified healthcare setting.

Inclusion Criteria

Infection preventionist or physician involved in infection prevention at participating health system

Exclusion Criteria

Not an infection preventionist nor a physician involved in infection prevention

Does not work at the participating health system

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Training

Participants are trained on how to use the GeoHAI tool

Immediately post-training

1 visit (in-person)

Implementation

Participants use the GeoHAI tool to identify HAI clusters and assess transmission risk

6 months

Follow-up

Participants are monitored for changes in HAI investigation processes and tool usability

6 months

Treatment Details

Interventions

• GeoHAI

Trial Overview The study is testing GeoHAI, a new computer application that uses mapping and geographic data to help hospital epidemiologists identify clusters of Hospital Acquired Infections (HAIs) and assess transmission risks.

Participant Groups

Group I: GeoHAI Use Experimental Treatment 1 Intervention

Participants will use the GeoHAI tool

Who Is Running the Clinical Trial?

Ohio State University

Lead Sponsor

Trials

891

Recruited

2,659,000+

University of Florida

Collaborator

Trials

1,428

Recruited

987,000+

Agency for Healthcare Research and Quality (AHRQ)

Collaborator

Trials

415

Recruited

6,777,000+

References

1. United States pubmed.ncbi.nlm.nih.gov

Identifying critically ill patients at risk for inappropriate antibiotic therapy: a pilot study of a point-of-care decision support alert. [2014]

2. England pubmed.ncbi.nlm.nih.gov

eHealth for the prevention of healthcare-associated infections: a scoping review. [2021]

3. United States pubmed.ncbi.nlm.nih.gov

Incidence and pathogen distribution of healthcare-associated infections in pilot hospitals in Egypt. [2022]

4. Sweden pubmed.ncbi.nlm.nih.gov

Electronically assisted surveillance systems of healthcare-associated infections: a systematic review. [2022]

5. United States pubmed.ncbi.nlm.nih.gov

The impact of healthcare-associated infection on mortality: failure in clinical recognition is related with inadequate antibiotic therapy. [2021]

6. Canada pubmed.ncbi.nlm.nih.gov

Mobile technologies and geographic information systems to improve health care systems: a literature review. [2021]

7. England pubmed.ncbi.nlm.nih.gov

An overview of GeoAI applications in health and healthcare. [2023]

8. England pubmed.ncbi.nlm.nih.gov

Geographical information system and spatial-temporal statistics for monitoring infectious agents in hospital: a model using Klebsiella pneumoniae complex. [2022]

9. United States pubmed.ncbi.nlm.nih.gov

Development and user testing study of MozzHub: a bipartite network-based dengue hotspot detector. [2023]

10. Netherlands pubmed.ncbi.nlm.nih.gov

POLESAT an Innovative e-Geoplatform in Health Management. [2018]