Research featured on this website was conducted in collaboration with Force Therapeutics, utilized data collected through the Force platform, or independently referenced and incorporated the platform into published work. Credit for all research and findings belongs to the original authors and institutions.
Preoperative optimization: Using data & pre-operative tools for patient selection and better outcomes
Preop Steps in TJA
Methods
- Looked at preop steps as a categorical predictor: 0, <25000, <50000, >=50000
- Corresponding LOS was 1.06, 1.04, 0.88, 0.85 respectively (p<.003)
Key Takeaways
- Pre-operative step data of may provide an objective, predictive data point in helping determine LOS than purely physiologic measures
Preop Opioids & TJA Outcomes
Methods
- Reviewed 2,186 TJA cases (1,173 TKA, 1,013 THA)
- Stepwise logistic regression was used to evaluate predictors in the multivariate model
- VR-12 PCS: Female gender (OR=1.9; 1.5-2.3), diabetes (OR=1.4; 1.0-2.2), pain medication usage for >30 days (OR=1.6;1.2-2.3), assistive device usage (OR=1.4; 1.0-1.9), and history of cardiac conditions (OR=1.3; 1.0-1.8).
Key Takeaways
- Opiate usage of >30 days pre-operatively is linked to a 1.6x increased likelihood of a poor outcome after TJA
- Patient selection and optimization are key for a successful recovery
RAPT Score vs. Discharge for TJA
Methods
- Reviewed RAPT score and discharge result of 100 TJA patients
- Of 55 patients with a RAPT >9 (home without services), 34 reported that they actually received Home Health services with an average of 6.5 visits
- Of 40 patients with a RAPT from 6-9 (home with services), 36 received home health with 2 who were discharged to a rehab facility
- Observed/Expected ratio of .61 for d/c without services and should ideally be close to 1.0
Key Takeaways
- Optimizing low-risk patients and setting patient expectations on post-acute services can result in cost-savings of roughly $2800 to the surgical episode
