Postoperative Morbidity Clinical Trial
Official title:
Investigating Trends in Compliance With Quality Assurance Metrics
Over 40 million major operative procedures are performed in the US annually and comprise
about 40% of healthcare expenditures. Despite decades of research, perioperative mortality
and morbidity remain a major healthcare system cost and detriment to long-term quality of
life. More than ten percent of patients experience a significant event such as surgical site
infection, reoperation, myocardial infarction, pulmonary embolus, or death. Nearly 100,000
patients die after surgery each year. National data demonstrate a 3-fold variation in risk
adjusted surgical morbidity and mortality, suggesting many opportunities for improvement in
perioperative care.
Anesthesiology care demonstrates wide variation in practice. Sometimes, this variation is
appropriate because the anesthesiologist is responding to patient comorbidities or procedure
specific events. However, even after controlling for patient specific factors, there is a
substantial amount of unexplained variation in fundamental elements of anesthesiology care.
The same procedure and patient can be performed using completely different anesthetic
techniques, hemodynamic management strategies, and medications. This variation in care can
lead to a variation in outcome.
The use of electronic health records (EHR) with detailed preoperative and intraoperative
data allows an automated system to be developed to notify clinicians their compliance to
both process of care metrics and outcome metrics. The Multicenter Perioperative Outcomes
Group (MPOG) quality improvement arm is known as Anesthesiology Performance Improvement
Reporting Exchange (ASPIRE). Like other Collaborative Quality Initiatives, the primary goal
of ASPIRE is to provide hospitals with risk-adjusted feedback on outcome and process of care
variation. In addition, ASPIRE creates an active best-practice sharing environment to enable
data to spur action. Recent literature has demonstrated that hospital-level feedback may not
be adequate to improve performance and clinical outcomes. In addition to hospital level data
and feedback, ASPIRE can disseminate provider-specific electronic feedback that may decrease
variation in care known to impact complications and cost.
The primary aim for this research study on ASPIRE's QI program is to determine if the
investigators can change behavior as measured by a provider's compliance to specific
performance metrics. The investigators believe that the start of individual provider
performance feedback reports to ASPIRE members presents a unique opportunity to research the
efficacy of these novel tools. The investigators propose to test the hypothesis that monthly
provider specific feedback emails on ASPIRE quality metrics over a period of 9 months
improves provider compliance as measured by a either a 10% improvement in the Total
Performance Score or by moving from below to above the 90% performance threshold in the
Total Performance Score Index.
Each provider type (faculty, CRNA, resident/fellow) within a hospital participating in
ASPIRE will be individually randomized to either receiving the electronic performance
improvement email or not for a total of nine months. No individual at the participating site
will see the individualized email compliance reports except for the specific provider. Only
an aggregate of the compliance across the entire hospital will be supplied to the
chairperson and the quality assurance directors. After the completion of the nine month
randomization period, all providers will receive monthly ASPIRE performance improvement
emails.
The University of Michigan is the coordinating center but also participating in this
research on QI project. De-identified patient data will be pulled in aggregate for each
provider using the MPOG database. The provider performance for each measure will then be
sent from ASPIRE to the randomized care provider via an email. The chairperson and quality
assurance directors will only see aggregate data on compliance rates and can NOT identify
individual compliance rates. Each participating site will obtain their own institutional IRB
to participate in this study.
Anesthesiology care demonstrates wide variation in practice. Sometimes, this variation is
appropriate because the anesthesiologist is responding to patient comorbidities or procedure
specific events. However, even after controlling for patient specific factors, there is a
substantial amount of unexplained variation in fundamental elements of anesthesiology care.
The same procedure and patient can be performed using completely different anesthetic
techniques, hemodynamic management strategies, and medications. This variation in care can
lead to a variation in outcome.
- Hemodynamic Management: Despite expert opinion that blood pressure should be maintained
within 20% of baseline, several studies have demonstrated that more than 40% of
patients experience profound hypotension in the operating room, defined as systolic
blood pressure of 79 mmHg or below. These blood pressure levels have been demonstrated
to be associated with acute kidney injury, myocardial ischemia, and death.
- Intraoperative ventilation strategies: A recent prospective, randomized trial in major
abdominal surgery demonstrated that the use of low intraoperative tidal volumes
decreases the risk of postoperative pulmonary complications, including pneumonia and
reintubation, by more than 50%, with no additional costs or adverse events. The use of
large tidal volumes and failure to administer intraoperative recruitment maneuvers is
widespread.
- Neuromuscular blockade (paralysis): The use of intraoperative neuromuscular blockade
for many patients undergoing general anesthesia is necessary to optimize surgical
conditions and prevent catastrophic injury due to unintended patient movement. However,
several trials have now demonstrated that most patients suffer from residual
neuromuscular blockade at the conclusion of surgery, resulting in markedly increased
risk of postoperative hypoxia, pneumonia, reintubation, and prolonged recovery room
stay.
- Fluid balance: Although fluid administration strategies have been studied in small
prospective trials extensively, basic consensus regarding the definition of "liberal"
versus "restrictive" intraoperative fluid administration is absent. Prospective
randomized controlled trials of restrictive fluid administration combined with
vasopressor administration in major abdominal cases have demonstrated markedly reduced
complications and length of stay.
- Fluid choice: The use of colloid fluid therapy has been demonstrated to increase costs
without an improvement in outcomes, yet there are no signs that the use of albumin or
synthetic colloids has decreased. In addition, despite overwhelming evidence that
discretionary transfusion of red blood cells above a hemoglobin of 10 mg/dl is rarely
indicated, recent data demonstrate its continued occurrence in many perioperative
patients.
The use of electronic health records (EHR) with detailed preoperative and intraoperative
data allows an automated system to be developed to notify clinicians their compliance to
both process of care metrics and outcome metrics. The primary goal of ASPIRE is to provide
hospitals with confidential risk-adjusted feedback on outcome and process of care variation.
In addition, ASPIRE creates an active best-practice sharing environment to enable data to
spur action.
Recent literature has demonstrated that hospital-level feedback may not be adequate to
improve performance and clinical outcomes. In addition to hospital level data and feedback,
ASPIRE can disseminate provider-specific feedback that may decrease variation in care known
to impact complications and cost. ASPIRE uses the underlying EHR data integration foundation
of the Multicenter Perioperative Outcomes Group to aggregate and analyze process of care and
outcome data.
To date, there is no anesthesia standard for quality improvement practice regarding
provider-specific feedback. The primary aim of this research study on ASPIRE's QI program is
to determine whether provider-specific feedback affects quality improvement performance
metrics. The investigators believe that the start of individual provider performance
feedback reports to ASPIRE members presents a unique opportunity to evaluate the efficacy of
these tools.
The investigators propose to test the hypothesis that monthly provider specific feedback
emails on ASPIRE quality metrics over a period of 9 months improves provider compliance as
measured by a either a 10% improvement in the Total Performance Score or by moving from
below to above the 90% performance threshold in the Total Performance Score Index.
Pre-defined process of care and outcome metrics will be calculated using the Multicenter
Perioperative Outcomes Group (MPOG) database. De-identified patient data will be extracted
from the MPOG database in aggregate for the anesthesia providers to determine their overall
compliance to the process of care and outcome metrics. The compliance metrics for each
provider will be stored in the MPOG/ASPIRE database. Any measure implemented in production
in between July 1, 2015 and July 1, 2016 will be incorporated into the analysis. The quality
improvement system generates a monthly email to the provider stating their performance
compared against the performance of their peers for each measure. Each measure is then
hyperlinked back into ASPIRE web-based dashboard where the provider can review the cases
that they failed on each measure. The visualization removes protected health information but
is the representation of the physiologic monitoring, medication and fluids administered,
laboratory values, and time-based events of the procedure. Provider attribution for each
measure will follow existing ASPIRE specifications (available at
https://www.aspirecqi.org/aspire-measures ). Each provider type (faculty, CRNA,
resident/fellow) within a hospital participating in ASPIRE will be individually randomized
to either receiving the electronic performance improvement email or not for a total of nine
months. After the completion of the nine month randomization period, all providers will
receive monthly ASPIRE performance improvement emails.
At the conclusion of the project, clinical outcomes of interest will be extracted from the
MPOG database via an honest broker using ICD-9 and ICD-10 codes and all-cause 30 day
mortality.
ASPIRE Quality Measures: Measure Description BP 01: Avoiding intraoperative hypotension
(mean arterial pressure less than 55 mmHg) BP 02: Avoiding gaps in systolic or mean arterial
pressure measurement longer than 10 minutes GLU 01: Percentage of cases with intraoperative
glucose > 200 (between anesthesia start and anesthesia end) with administration of an
insulin bolus or infusion or glucose test recheck GLU 02: Percentage of cases with glucose <
60 (between anesthesia start and anesthesia end with a glucose test recheck or
administration of dextrose containing solution (between anesthesia start and anesthesia end
+ 2 hours) NMB 01: Percentage of cases receiving a non-depolarizing neuromuscular blockade
medication that have a Train of Four (TOF) count documented NMB 02: Percentage of cases
receiving a non-depolarizing neuromuscular blockade medication with administration of
reversal agent PUL 01: Percentage of cases with median tidal volumes less than 10 ml/kg of
ideal body weight (IBW) TRAN 01: Hemoglobin or hematrocrit measurements before each
transfusion for patients receiving discretionary intraoperative red blood cell transfusions
TRAN 02: Avoiding post transfusion hematocrit greater than 30%
Statistical Analysis:
All statistical analysis will be completed using a de-identified dataset for which the
analyst will have no link back to each of the individual's unique names. The investigators
will combine several key process of care measures into a process of care bundle for the
analysis. The bundle for each participating site will include the process of care quality
measures included on month 1 of the email feedback program. If there were more than one
instance that a provider could pass or fail for a specific case, if the provider passed or
failed at least once it would pass or fail for the entire case. The primary outcome will be
the proportion of providers that achieve improvement in performance from start to end of the
study period. The investigators will exclude providers that already met all the metric
thresholds for the primary analysis.
Our primary analysis will include all providers. Secondary analysis will include performers
not meeting threshold measures. Improvement in performance will be determined by the
following method:
1. The performance rates for the measures of each site's bundle will be summed. This total
will be known as the Total Performance Score. The Total Performance Score Index will be
the score divided by the number of measures in the bundle.
2. Improvement is defined as greater than or equal to 10% change in the performance index
from beginning to end of study, OR
3. Total Performance Score Index crossing the 90% threshold between study beginning or
end.
The threshold for what will be considered a performer not meeting threshold measures will be
determined by examining the distribution of the bundle compliance. Randomization is
pre-determined at the start of the project and is NOT based on if the provider is classified
as a performer meeting threshold measures or not. Each provider's baseline compliance rate
will be determined by the performance from the first month's feedback email. In addition,
the investigators will do a secondary analysis investigating if the providers that met all
the threshold metrics prior to the project further improved during the study period. A
sub-group analysis excluding the coordinating center is planned.
The primary analysis will only include sites where all provider types are randomized
(attendings/residents/CRNAs). Sites where one provider type (ie attending or CRNA) was
randomized and the other provider type was not will be included in a secondary analysis.
To assess the investigators primary hypothesis of the impact of provider-specific emails on
overall compliance during the nine-month study period, a repeated measures generalized
linear model (GLM) will be used. Between-subjects (randomization to email) and
within-subjects (compliance) analyses will be reported. The primary analysis will be
stratified by provider type (faculty, fellow, resident, and CRNA). A sub-group analysis
excluding the coordinating center is planned.
For the investigators secondary analysis to determine if a provider who already met the
threshold performance metric prior to the study further increased in their compliance a
linear regression will be used.
Outcome analyses will be performed only using data related to inpatient / admit day of
procedure operations. First, to determine if providers receiving an email about the
participants specific bundled compliance affects a patient's overall combined morbidity and
mortality a binary logistic regression model will be used. The dependent variable will be
combined morbidity and mortality as a Boolean concept. The independent variables entered
into the model will be: primary provider AND primary attending both received an email,
primary provider did NOT receive an email but the primary attending did receive an email,
primary provider did receive an email but the primary attending did NOT receive an email,
elixhauser comorbidity score of 2 or more, ASA (binary concept as 1,2 versus 3,4), age
(binned by decade of life), male gender, BMI (defined by the World Health Organization
Classifications). The investigators can then determine whether providers receiving feedback
emails have a risk adjusted improved combined morbidity and mortality rate. If the
investigators find this to be true, a mediation analysis at the provider level will be
performed to determine if our independent variable (email received) influences the mediator
variable (bundle compliance rate) which thereby influences the dependent variable (outcome
of interest). The investigators will report the direct effect for receiving the email on the
provider's outcome rate as well as the indirect effect of the email that passes through the
bundle compliance rate to affect the outcome rate. These values will be reported as the
proportion of total effect that is mediated by compliance. Sensitivity analyses for
residents/fellow and CRNAs will also be performed. A sub-group analysis excluding the
coordinating center is planned.
;
Status | Clinical Trial | Phase | |
---|---|---|---|
Recruiting |
NCT05824260 -
Risk Factors for Postoperative Complications in Major Non-cardiac Surgery: Post-hoc Analysis of the OPHIQUE Multicentre Study
|
||
Completed |
NCT01145820 -
Fruit And Vegetables and OUtcomes After Removal of Impacted TEeth
|
N/A | |
Recruiting |
NCT04969107 -
Abdominal or Transanal TME for Rectal Cancer Therapy
|
N/A | |
Completed |
NCT02502773 -
Fluid Loading in Abdominal Surgery: Saline Versus Hydroxyethyl Starch (FLASH Study)
|
Phase 3 | |
Completed |
NCT01515670 -
Length of Stay and Complications in High-risk Patients Receiving Fast-track Total Hip (THA) or Knee- Alloplasty (TKA)
|
||
Completed |
NCT03987789 -
Intraoperative Protective Mechanical Ventilation in Patients Requiring Emergency Abdominal Surgery
|
N/A | |
Completed |
NCT03420261 -
Hemostasis Evolution During Fluid Loading in Abdominal Surgery. Effects of Fluid Choice: Saline Versus Hydroxyethyl Starch (HAEMO Study)
|
Phase 4 |