Enhanced Cluster Detection Methods for Outbreak Control

(CLUSTER Trial)

No longer recruiting at 83 trial locations

Overseen By Micaela Coady, MS

Age: Any Age

Sex: Any

Trial Phase: Academic

Sponsor: Harvard Pilgrim Health Care

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

Compensation: Varies

Number of Visits: Unknown

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to enhance hospitals' ability to detect and control disease outbreaks. It tests a new automatic tool, Enhanced Cluster Detection, which uses statistics to identify outbreaks faster than regular methods. The goal is to determine if this tool can help contain outbreaks more quickly, reducing their size and duration. Hospitals within the HCA Healthcare system that provide inpatient care and report data regularly can join the trial. As an unphased trial, this study offers a unique opportunity to advance public health safety and outbreak management.

Will I have to stop taking my current medications?

The trial information does not specify whether participants need to stop taking their current medications.

What prior data suggests that this method is safe for outbreak control?

Research has shown that automated tools for detecting infection clusters in hospitals hold promise. Studies have found that these systems can identify groups of germs early, which is crucial for controlling infections. Although these tools did not always reduce the size of outbreaks, they provided valuable insights into how outbreaks spread.

This method is not a drug or medical procedure but a tool that helps hospitals identify infection patterns faster than manual methods. Since it is not used directly on people, it does not carry the same safety concerns as treatments or medications. It focuses on enhancing the hospital's ability to respond to outbreaks quickly and effectively. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores the potential of enhanced cluster detection methods to improve outbreak control in hospitals. Unlike routine cluster detection practices, this approach uses an automated statistical tool to identify clusters more quickly and accurately. This could lead to faster response times and more effective containment of outbreaks, ultimately improving patient safety and hospital efficiency. By integrating advanced technology into traditional practices, this trial aims to revolutionize how hospitals detect and respond to potential outbreaks.

What evidence suggests that this trial's methods could be effective for outbreak control?

Research has shown that improved methods for identifying case clusters can significantly enhance outbreak detection in hospitals. This trial will compare two approaches: Enhanced cluster detection, which uses an automated statistical cluster detection tool alongside routine practices, and Routine cluster detection, which relies solely on standard practices. A study developed a tool combining statistics and microbiology data, which showed promise in identifying hospital outbreaks faster than older methods. Experiences with detecting clusters in HIV outbreaks demonstrated that automated systems can lead to quicker responses and better control of disease spread. This method uses computer programs to connect cases during an outbreak, helping to identify patterns and clusters early. By detecting outbreaks more quickly, hospitals can respond faster, potentially reducing the size and duration of outbreaks. ^{2 6 7 8 9}

Who Is on the Research Team?

Richard Platt, MD, MSc

Principal Investigator

Harvard Pilgrim Health Care Institute

Susan Huang, MD, MPH

Principal Investigator

University of California, Irvine

Meghan Baker, MD, ScD

Principal Investigator

Brigham and Women's Hospital

Are You a Good Fit for This Trial?

The CLUSTER Trial is for U.S. HCA Healthcare hospitals providing inpatient care and reporting to a centralized data warehouse during the study period. It's not specified which facilities can't participate, suggesting all eligible ones can join.

Inclusion Criteria

The clinical trial may only be conducted at certain medical facilities.

The study includes all HCA Healthcare hospitals in the United States that admit patients for hospital care.

The healthcare facility where you receive treatment must be able to share data with a central database during the study.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Cluster Detection and Response

Hospitals implement either enhanced or routine cluster detection methods with a structured response protocol

30 months

Follow-up

Participants are monitored for outcomes such as cluster size and duration

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Enhanced cluster detection
• Routine cluster detection

Trial Overview This trial tests an automated statistical method for detecting hospital-associated outbreaks against routine methods. The goal is to see if this new approach helps contain outbreaks faster by reducing their size and duration.

How Is the Trial Designed?

Group I: Enhanced cluster detection Active Control 1 Intervention

Hospitals will use an automated statistical cluster detection tool in addition to routine practices for cluster detection with a structured cluster response protocol when a cluster is detected.

Group II: Routine cluster detection Active Control 1 Intervention

Hospitals will use routine practices for cluster detection with a structured cluster response protocol when a cluster is detected.

Who Is Running the Clinical Trial?

Harvard Pilgrim Health Care

Lead Sponsor

Trials

61

Recruited

27,990,000+

Hospital Corporation of America

Industry Sponsor

Trials

8

Recruited

3,433,000+

Centers for Disease Control and Prevention

Collaborator

Trials

902

Recruited

25,020,000+

Harvard School of Public Health (HSPH)

Collaborator

Trials

283

Recruited

17,030,000+

Hospital Corporation of America (HCA) Healthcare

Collaborator

Trials

1

Recruited

2,905,000+

University of Massachusetts, Amherst

Collaborator

Trials

83

Recruited

3,474,000+

Cook County Health & Hospitals System

Collaborator

Trials

7

Recruited

2,910,000+

Duke University

Collaborator

Trials

2,495

Recruited

5,912,000+

Rush University

Collaborator

Trials

46

Recruited

3,294,000+

University of California, San Francisco

Collaborator

Trials

2,636

Recruited

19,080,000+

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10067150/

Automatic case cluster detection using hospital electronic ... We propose an algorithm to identify case clusters within a community during an infectious disease outbreak using Bayesian probabilistic case linking.

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC6454359/

Outbreak science: recent progress in the detection and ... Outbreak response continues to follow nine basic principles: establish the presence of an outbreak, verify the diagnosis, make a case definition, find cases and ...

3. sciencedirect.com sciencedirect.com/science/article/pii/S0749379721003639

HIV Cluster and Outbreak Detection and Response This article reviews the experience gained through 30 HIV cluster and outbreak responses in North America during 2000–2020

4. evidence.nejm.org evidence.nejm.org/doi/full/10.1056/EVIDoa2300342

A Trial of Automated Outbreak Detection to Reduce Hospital ... We developed a statistically based outbreak detection tool by integrating WHONET, an analytics software program for microbiology data, and ...

5. cdc.gov cdc.gov/hivpartners/php/cdr/index.html

HIV Cluster Detection and Response | HIV Partners HIV cluster detection and response (CDR) identifies communities affected by rapid HIV transmission. CDR helps public health agencies and communities identify ...

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC8522860/

Implementation of an automated cluster alert system into ... Early detection of clusters of pathogens is crucial for infection prevention and control (IPC) in hospitals. Conventional manual cluster ...

7. cdc.gov cdc.gov/hivpartners/php/cdr/science-brief.html

Science Brief: Evidence That HIV Cluster and Outbreak ... HIV cluster detection and response (CDR) is an important strategy to identify and close gaps in prevention and care services for communities experiencing rapid ...

8. journals.plos.org journals.plos.org/plosone/article?id=10.1371/journal.pone.0312477

Enhanced automated detection of outbreaks of a rare ... We developed a framework for automatic detection of clusters of AMR bacteria using SaTScan, a free cluster detection tool integrated into WHONET.

9. corha.org corha.org/tools/cluster-toolkit

CLUSTER Detection: Outbreak Response Protocol - CORHA The Outbreak Response Protocol standardizes hospital outbreak management with tiered interventions based on infection prevention assessments. Unassigned.