An interventional study of Intervention Cluster in Infection Control and Surgical Site Infection, sponsored by Duke University. Completed at 1 site in United States. Per ClinicalTrials.gov, last updated 2020-04-02.
Sponsored by Duke University · Not applicable, Interventional, and Prevention
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.
6,687 studies on the registry are indexed under Infections; 807 are open to participants now.
This study's enrollment of 29 is below the median of 120 across 4,200 interventional studies indexed under Infections.
Browse Infections studies →Duke University is the lead sponsor of 2,025 studies on the registry; 275 are open to participants now.
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Exclusion Criteria:
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
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.
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.
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.
Time frame: SSIs can be diagnosed up 30 to 90 days following the procedure, depending on the type of procedure
Proportion of SSIs determined to be potentially preventable
Among SSIs investigated, each will be provided a "preventability score" after reviewing if best practices were followed.
Time frame: 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
Signals identified using optimized SPC will be compared to signals identified using standard surveillance; Not a patient-specific outcome
Time frame: 36 months (entire study period)
Difference in number of outbreaks identified
Outbreaks identified using optimized SPC will be compared to outbreaks identified using standard surveillance; Not a patient-specific outcome
Time frame: 36 months (entire study period)
Difference in number of investigations of increased rates of SSI
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 frame: 36 months (entire study period)
Total number and differences in proportion of signals that led to investigations
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 frame: 36 months (entire study period)
Time required to investigate signals
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
Time frame: 36 months (entire study period)
Timing of signals
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
Time frame: 36 months (entire study period)
Time to completion of investigation
Investigators will determine the time required to complete investigations
Time frame: 36 months (entire study period)
Strength and type of signals
Investigators will compare the strength and types of signals generated from each type of surveillance with subsequent adjudication and intervention.
Time frame: 36 months (entire study period)
Plan to share: No
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