1. Journal Club Notes

2. Learning Objectives
Explain what is meant by a historical control study design
Describe limitations of a historical control study design
Identify factors that improve a historical control study design
Discuss limitations of single center trial
Review the NSQIP Surgical Risk Calculator

3. Modesitt SC, et al. “Enhanced recovery implementation in major gynecologic surgeries: Effect of care standardization”, Obstetrics and Gynecology, 2016, 128:

4. Historical control Compare outcomes, costs, patient satisfaction
Before and after study design
Compare group of patients before an intervention or change in protocol with a group of patients after an intervention/change in protocols
Different groups of patients
Pre-ERAS implementation, patients undergoing elective major gynecologic surgery
Post-ERAS implementation, patients undergoing elective major gynecologic surgery
Compare outcomes, costs, patient satisfaction

5. Historical controls
You want to know did the intervention cause the difference in outcomes
Did the pathways improve clinical outcomes, patient satisfaction and reduce costs?
Need to rule out the possibility that the results are not due to differences between the post- ERAS group and pre-ERAS group
Patients were not randomized to the intervention

6. Limitations of Historical Controls
May be biased if there are differences between the two groups of patients in the distribution of risk or protective factors associated with the outcomes
Problem of confounders – factors associated associated with time and the outcomes

7. Why might there be differences over time?
Changes in diagnostic criteria
Differences in population with the disease
Differences in the standards of care
Technological advances
Differences in assessments that measure the results
Missing data, especially pre-intervention
Data quality problems

8. How can these concerns be addressed?
Short time period between historical data and post intervention data
Selection of concrete outcomes that are less subjective
Ascertain outcomes in a systematic manner – use standardized definitions; provide documentation; train chart abstractors; use staff with appropriate level of knowledge to be able to interpret charts (e.g., RNs or NPs in the specialty)
Large data set
Large effect post-intervention

9. What did this study do to address these concerns?
Short time period between pre-ERAS and post-ERAS group
Less likely that there will be changes in other practice styles, technology, or standards of care
Selection of consecutive patients
Often used to reduce selection bias
Use of objective clinical outcomes, e.g. length of stay
Use of surgical clinical nurse chart reviewers
Use of standard definitions

10. Single center trials Logistically easier Cheaper
Simplified data collection – working with the same Electronic Medical Records, or organization of charts
May be less heterogeneity in the types of patients seen, which could imply less confounding

11. Single center trials Single center trials often lack external validity
Hard to generalize to other institutions
There may be “a champion for the cause” at that one institution
Atypical expertise and/or level of commitment
Intervention less likely to work at another institution
These interventions often need additional staff time and other resources.

12. Single center trial
This study conducted in one clinical center because of the “extensive effort necessary to overcome institutional bias for traditional perioperative care”
Would this work at Crouse or Upstate?
This study shows that it is feasible and could work.
But, will it work?
What will it take to make it work?

13. Stats Review Pre-ERAS and Post-ERAS Continuous variables
Normally distributed compared with t-test
Not normally distributed compared using Wilcoxon’s rank sum non-parametric text
Pre-ERAS and Post-ERAS Categorical variables
Compared with Chi-square test
Used Fisher exact test if small number (usually fewer than 6 cases)

14. Surgical Risk Calculator
National Surgical Quality Improvement Program Surgical Risk Calculator
Used to calculate the predicted risk-adjusted length of stay