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

NCT03075813 | Completed

• 1 other identifier: Pro00081013
• Study Type: interventional
• Target: 29
• Locations: 1 country
• Sites: 1

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.

Conditions

Infection Control; Surgical Site Infection

Outcome Measures

Primary Outcomes (1)

• Differences in rates of SSI.

  SSI 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.

  SSIs can be diagnosed up 30 to 90 days following the procedure, depending on the type of procedure

Secondary Outcomes (9)

• Proportion of SSIs determined to be potentially preventable

  diagnosed up 30 to 90 days following the procedure, depending on the type of procedure

• Description of and difference in number and type of signals

  36 months (entire study period)

• Difference in number of outbreaks identified

  36 months (entire study period)

• Difference in number of investigations of increased rates of SSI

  36 months (entire study period)

• Total number and differences in proportion of signals that led to investigations

  36 months (entire study period)

Study Arms (2)

Intervention Cluster

EXPERIMENTAL

Surgical surveillance data submitted to the DICON Surgical Database will undergo immediate analysis by optimized SPC methods. If a signal is generated, study personnel in DICON will be notified to adjudicate the signal and determine if further action is required. Optimized SPC methods include the application of two SPC charts. The investigator determined that when either chart identifies a signal, the study will have approximately 90% sensitivity and 65% specificity to identify important increases in rates of SSI.

Other: Intervention Cluster

Control Cluster

NO INTERVENTION

Local personnel in clusters randomized to traditional surveillance and feedback will receive bar graph reports and data interpretation per routine DICON surveillance. These reports will be provided every 6 months.

Interventions

Intervention Cluster OTHER

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.

Intervention Cluster

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may not qualify if:

• 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.

Sponsors & Collaborators

• Duke University: lead
• Agency for Healthcare Research and Quality (AHRQ): collaborator

Study Sites (1)

Duke University Health System

Durham, North Carolina, 27705, United States

Location

Related Publications (2)

• Baker AW, Ilies I, Benneyan JC, Lokhnygina Y, Foy KR, Lewis SS, Wood B, Baker E, Crane L, Crawford KL, Cromer AL, Padgette P, Roach L, Adcock L, Nehls N, Salem J, Bratzler D, Dellinger EP, Greene LR, Huang SS, Mantyh CR, Anderson DJ. Early recognition and response to increases in surgical site infections using optimised statistical process control charts-The early 2RIS trial: A multicentre stepped wedge cluster randomised controlled trial. EClinicalMedicine. 2022 Oct 17;54:101698. doi: 10.1016/j.eclinm.2022.101698. eCollection 2022 Dec.

  PMID: 36277312 DERIVED

• Anderson DJ, Ilies I, Foy K, Nehls N, Benneyan JC, Lokhnygina Y, Baker AW. Early recognition and response to increases in surgical site infections using optimized statistical process control charts-the Early 2RIS Trial: a multicenter cluster randomized controlled trial with stepped wedge design. Trials. 2020 Oct 28;21(1):894. doi: 10.1186/s13063-020-04802-4.

  PMID: 33115527 DERIVED

MeSH Terms

Conditions

Surgical Wound Infection

Condition Hierarchy (Ancestors)

Wound Infection; Infections; Postoperative Complications; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Deverick Anderson, MD

  Duke Health

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: INVESTIGATOR
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 6, 2017
• First Posted: March 9, 2017
• Study Start: March 6, 2017
• Primary Completion: February 29, 2020
• Study Completion: February 29, 2020
• Last Updated: April 2, 2020

Record last verified: 2020-03

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)