Operating Room Scheduling
Conditions
Keywords
Operating room utilization
Brief summary
This study compares two different methodologies of scheduling cases in the operating room.
Detailed description
The goal of the proposed study is to address the efficacy of a scheduling methodology that uses a regression-based predictive modeling system (PMS) to calculate operative and anesthetic time length. The investigators hypothesize that compared to the traditional scheduling system (TSS) that calculate operative length using historic means, case allocation in an operating room using the PMS will improve scheduling precision, increase operative volume and increase Operative Suite (OS) personnel satisfaction, without having adverse impact on patient outcomes. The investigators will evaluate this hypothesis using a randomized block design in two operating rooms of a single surgical specialty for a total of 100 operative days per arm.
Interventions
OTHERScheduling using historical means
Scheduling will be performed taking into account historical means only for anesthetic, operative, and turn around time
OTHERScheduling using regression modeling system
A regression model that uses predictor of operative length will be used to predict operative, anesthetic, and turn around time length
Sponsors
VA Office of Research and Development
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
QUADRUPLE (Subject, Caregiver, Investigator, Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* The only requirement for including a day in the study will be that all the procedures performed in that specific day have been previously performed in our hospital at least 5 times a year for each of the last three years. This rule will encompass the vast majority of the performed vascular procedures in our facility. Setting the threshold at a minimum of 5 cases per year is essential to assure that some data will be available to calculate the expected length of the case with either the traditional or the predictive modeling system. If a case is performed in a day when the scheduling imprecision is supposed to be calculated using the PMS but modeling data do not exist, then the anticipated length of this case will be calculated using the historic means. * Surgery cancellation after the first case will not disqualify that day from inclusion in the study. If the cancellation occurs in the last case of the sequence for the specific day then no particular intervention will be taken. The anticipated end of the surgical day will reset to the end of the last case that took place, and all the imprecision calculations will be performed as described below. If the cancellation occurs in one of the intermediate cases, then the end of the operative day will reset to reflect the removal of the cancelled case.
Exclusion criteria
A day will be excluded from the study when any of the following occur (based on historical data the investigators anticipate 10-15% of the operative days to meet the
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Difference Between the Actual and Predicted Length of Operative Day (in Minutes) | Three years | The scheduling imprecision between the two scheduling approaches will be compared. Scheduling imprecision is defined as the difference between the actual and predicted length of operative day. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Difference in Throughput | Three years | Difference in total number of cases scheduled per unit of time analyzed between the two study arms |
| Operative Suite Personnel Job Satisfaction | Three years | Comparison of job satisfaction between study arms using three domains of the Maslach Burnout Inventory: Depersonalization (range 0-17, score of 17 indicates worse depersonalization). Emotional Exhaustion (range: 0-36, score of 36 is the worse). Personal accomplishment (range 1-60, score of 60 is best). |
| Complications: A Composite Endpoint of Death, Myocardial Infarction, Bleeding, Amputation | Three years | Comparison of the perioperative (30-day postoperative) composite endpoint of death, myocardial infarction, bleeding, amputation between the two study groups |
Countries
United States
Participant flow
Recruitment details
Calendar days during which vascular surgery operations were performed were randomly scheduled using either the Historical Means or the Predictive Modeling System methodologies. Please, note that unit of randomization was operative days, not patients
Pre-assignment details
Operative days that were on holidays, or when staff surgeons were out of town were excluded. Similarly, did not schedule any cases during the re-calibration of the predictive models
Participants by arm
| Arm | Count |
|---|---|
| Historical Means Method Scheduling using historical means: Scheduling will be performed taking into account historical means only for anesthetic, operative, and turn around time | 356 |
| Historical Means Method Scheduling using historical means: Scheduling will be performed taking into account historical means only for anesthetic, operative, and turn around time | 107 |
| Predictive Modeling System (PMS) Scheduling using regression modeling system: A regression model that uses predictor of operative length will be used to predict operative, anesthetic, and turn around time length | 379 |
| Predictive Modeling System (PMS) Scheduling using regression modeling system: A regression model that uses predictor of operative length will be used to predict operative, anesthetic, and turn around time length | 100 |
| Total | 942 |
Baseline characteristics
| Characteristic | Historical Means Method | Predictive Modeling System (PMS) | Total |
|---|---|---|---|
| Age, Customized | 62 Years STANDARD_DEVIATION 8 | 62.5 Years STANDARD_DEVIATION 10 | 62.5 Years STANDARD_DEVIATION 10 |
| Available operative days for randomization | 107 Operative Days | 100 Operative Days | 207 Operative Days |
| Sex/Gender, Customized Sex Females | 5 Participants | 6 Participants | 11 Participants |
| Sex/Gender, Customized Sex Males | 351 Participants | 373 Participants | 724 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk |
|---|---|---|
| deaths Total, all-cause mortality | — / — | — / — |
| other Total, other adverse events | 0 / 0 | 0 / 0 |
| serious Total, serious adverse events | 0 / 0 | 0 / 0 |
Outcome results
Primary
Difference Between the Actual and Predicted Length of Operative Day (in Minutes)
The scheduling imprecision between the two scheduling approaches will be compared. Scheduling imprecision is defined as the difference between the actual and predicted length of operative day.
Time frame: Three years
Population: We analyzed data from 107 operative days in the HM arm, and 100 days in the PMS arm
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Historical Means Method | Difference Between the Actual and Predicted Length of Operative Day (in Minutes) | 30.8 Minutes | Standard Deviation 99 |
| Predictive Modeling System (PMS) | Difference Between the Actual and Predicted Length of Operative Day (in Minutes) | 7.2 Minutes | Standard Deviation 67 |
Comparison: The null hypothesis was that there would be no difference in predictive imprecision for the end of the operative day between the two armsp-value: 0.02495% CI: [3.15, 44]t-test, 2 sided
Comparison: Null hypothesis: There would be no difference in throughput between the two armsp-value: 0.0495% CI: [1.01, 1.34]Poisson regression
Secondary
Complications: A Composite Endpoint of Death, Myocardial Infarction, Bleeding, Amputation
Comparison of the perioperative (30-day postoperative) composite endpoint of death, myocardial infarction, bleeding, amputation between the two study groups
Time frame: Three years
Population: Patients
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Historical Means Method | Complications: A Composite Endpoint of Death, Myocardial Infarction, Bleeding, Amputation | 8 Participants |
| Predictive Modeling System (PMS) | Complications: A Composite Endpoint of Death, Myocardial Infarction, Bleeding, Amputation | 12 Participants |
Comparison: Null hypothesis was that there would be no difference in the adverse event rates between the two scheduling methodologiesp-value: 0.44Chi-squared
Secondary
Difference in Throughput
Difference in total number of cases scheduled per unit of time analyzed between the two study arms
Time frame: Three years
Population: Operative days
| Arm | Measure | Value (NUMBER) |
|---|---|---|
| Historical Means Method | Difference in Throughput | 3.33 Operations/day analyzed |
| Predictive Modeling System (PMS) | Difference in Throughput | 3.79 Operations/day analyzed |
Comparison: Null hypothesis was that there was no difference in throughput between the two scheduling methodsp-value: 0.0495% CI: [1.01, 1.34]Poisson Regression
Secondary
Operative Suite Personnel Job Satisfaction
Comparison of job satisfaction between study arms using three domains of the Maslach Burnout Inventory: Depersonalization (range 0-17, score of 17 indicates worse depersonalization). Emotional Exhaustion (range: 0-36, score of 36 is the worse). Personal accomplishment (range 1-60, score of 60 is best).
Time frame: Three years
Population: Health care providers
| Arm | Measure | Group | Value (MEAN) |
|---|---|---|---|
| Historical Means Method | Operative Suite Personnel Job Satisfaction | Depersonalization | 3.23 units on a scale |
| Historical Means Method | Operative Suite Personnel Job Satisfaction | Emotional Exhaustion | 11.82 units on a scale |
| Historical Means Method | Operative Suite Personnel Job Satisfaction | Personal Accomplishment | 37.51 units on a scale |
| Predictive Modeling System (PMS) | Operative Suite Personnel Job Satisfaction | Depersonalization | 2.04 units on a scale |
| Predictive Modeling System (PMS) | Operative Suite Personnel Job Satisfaction | Emotional Exhaustion | 10.03 units on a scale |
| Predictive Modeling System (PMS) | Operative Suite Personnel Job Satisfaction | Personal Accomplishment | 40.47 units on a scale |
Comparison: Null hypothesis: There would be no difference in personnel satisfaction between the groupsp-value: 0.04t-test, 2 sided