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Early Recognition and Response to Increases in Surgical Site Infections Using Optimized Statistical Process Control Charts: The Early 2RIS Study

Early Recognition and Response to Increases in Surgical Site Infections Using Optimized Statistical Process Control Charts

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03075813
Acronym
Early 2RIS
Enrollment
29
Registered
2017-03-09
Start date
2017-03-06
Completion date
2020-02-29
Last updated
2020-04-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Infection Control, Surgical Site Infection

Brief summary

The purpose of this quality improvement study is to measure the effectiveness of surveillance using optimized statistical process control (SPC) methods and feedback on rates of surgical site infection (SSI) compared to traditional surveillance and feedback. The primary objective is to determine if hospital clusters randomized to receive feedback from optimized SPC surveillance methods collectively have lower rates of SSI compared to hospital clusters randomized to receiving feedback from traditional surveillance methods. Secondary objectives are 1) to estimate and compare the number of signals identified using optimized SPC methods and traditional surveillance methods; 2) to estimate and compare the time and effort required to investigate signals generated using optimized SPC methods and traditional surveillance methods; and 3) to estimate the number and proportion of false-positive signals identified using optimized SPC methods and traditional surveillance methods. The Early 2RIS study will be a prospective, multicenter cluster randomized controlled trial using stepped wedge design. The active component of the quality improvement study will be performed in 29 DICON hospitals over three years, from March 2017 through February 2020. Clusters randomized to intervention will receive feedback on increasing rates of SSI identified through optimized SPC methods. This intervention is expected to decrease the subsequent rate of SSIs by closing the feedback loop on SSI outcomes. Participating study hospitals will all be members of DICON, a network of 43 community hospitals in North Carolina, South Carolina, Georgia, Florida, and Virginia that provides community hospitals access to consultative services from infection prevention experts, data analyses and benchmarking, and educational materials designed by faculty from Duke. This study is considered part of routine quality improvement measures and a part of previously established agreements between DICON and the community hospitals. Data flow and communication are outlined in detail in approved protocols determined to be exempt research by the DUHS IRB. Briefly, existing clinical data are extracted from participating hospitals' electronic medical record into discrete files according to DICON specifications. Then a de-identification process removes direct patient identifiers into a limited dataset. The majority of data collection will occur through methods already developed and utilized by study hospitals. In brief, each hospital routinely submits limited datasets to the DICON Surgical Surveillance Database, including the following variables: hospital, type of procedure, patient identifier, date of procedure, age, sex, surgeon identifier, start/stop times, ASA score, wound class, risk index, SSI (Yes/No), date of infection, type of SSI, location at diagnosis and organism. No identifiable patient or surgeon data are transmitted to the DICON Surgical Database. Data definitions and data collection methods are standardized across DICON hospitals. Following signal adjudication, additional data will be collected in a REDCap database to document actions and rationale.

Interventions

Surgical surveillance date will be analyzed by optimized SPC methods. if signal is generated, study personnel in DICON will be notified to adjudicate the signal and determine if further action is needed.

Sponsors

Agency for Healthcare Research and Quality (AHRQ)
CollaboratorFED
Duke University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
SINGLE (Investigator)

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

* All patients who undergo one of 13 targeted procedures in 29 DICON study hospitals will be eligible for inclusion. The 13 targeted procedures include coronary artery bypass graft, cardiac valve replacement, colon surgery, herniorrhapy, knee arthroplasty, hip arthroplasty, Cesarean section, abdominal hysterectomy, vaginal hysterectomy, spinal fusion, laminectomy, carotid endarterectomy, and peripheral venous bypass. These procedures were selected because they are frequently performed in community hospitals and/or are associated with particularly adverse outcomes if complicated by SSI. Eligible procedures will be categorized by procedure type at each hospital using ICD9 codes published by the NHSN, per routine DICON activities. Six clusters were constructed from these procedures to ensure that surgeons who perform similar types of procedures were grouped together to limit potential bias. These clusters are labeled as Spine, GI, OB/GYN, Ortho, Vascular, and Cardiac. These clusters are the units for randomization and analysis.

Exclusion criteria

* DICON hospitals that did not submit a letter of support for participating in the study will be excluded. Patients not undergoing one of these 13 procedure types at the 29 study hospitals will be excluded from the analysis.

Design outcomes

Primary

MeasureTime frameDescription
Differences in rates of SSI.SSIs can be diagnosed up 30 to 90 days following the procedure, depending on the type of procedureSSI rate will be calculated as number of SSI/100 procedures per month SSIs will be defined using standard NHSN definitions DICON personnel train local infection preventionists about how to use and interpret SSI definitions. Thus, standard definitions and methods are used at all study hospitals. Cluster-level risk adjustment will be performed using median surgical volume and median NHSN Risk Index (an operation- and patient-specific risk score that predicts SSI) per cluster.

Secondary

MeasureTime frameDescription
Proportion of SSIs determined to be potentially preventablediagnosed up 30 to 90 days following the procedure, depending on the type of procedureAmong SSIs investigated, each will be provided a preventability score after reviewing if best practices were followed.
Description of and difference in number and type of signals36 months (entire study period)Signals identified using optimized SPC will be compared to signals identified using standard surveillance; Not a patient-specific outcome
Difference in number of outbreaks identified36 months (entire study period)Outbreaks identified using optimized SPC will be compared to outbreaks identified using standard surveillance; Not a patient-specific outcome
Difference in number of investigations of increased rates of SSI36 months (entire study period)Signals may or may not lead to subsequent investigation. Investigators will compare the number of investigations performed following the use of optimized SPC to the number of investigations performed following the use of standard surveillance; signals identified using standard surveillance; Not a patient-specific outcome
Time to completion of investigation36 months (entire study period)Investigators will determine the time required to complete investigations
Time required to investigate signals36 months (entire study period)Investigators will monitor the time required to investigate signals and compare the time required following the use of optimized SPC methods to the time required following the use of standard surveillance; not a patient-specific outcome
Timing of signals36 months (entire study period)Investigators will determine how promptly the different surveillance strategies identify signals and compare average/median time to signal between the two study arms; not a patient-specific outcome
Strength and type of signals36 months (entire study period)Investigators will compare the strength and types of signals generated from each type of surveillance with subsequent adjudication and intervention.
Total number and differences in proportion of signals that led to investigations36 months (entire study period)Signals may or may not lead to subsequent investigation. Investigators will compare the number of investigations performed following the use of optimized SPC to the number of investigations performed following the use of standard surveillance; signals identified using standard surveillance; Not a patient-specific outcome

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 25, 2026