Evaluation of a Preoperative Optimization Protocol for Primary Hip and Knee Arthroplasty Patients.

BACKGROUND

Preoperative optimization of risk factors has been suggested as a strategy to improve the value of total joint arthroplasty (TJA) care. We assessed the implementation of a TJA preoperative optimization protocol and its impact on length of hospital stay, discharge destination, 90-day readmissions, and hospital direct variable costs.

METHODS

This retrospective cohort study included adults undergoing primary elective TJA from 07/2015-09/2016 at an urban tertiary care hospital. Post-implementation patients were preoperatively screened for 19 risk factors; results and recommended interventions were reported to surgeons, who had the option to postpone or continue surgery as scheduled. Metrics from hospital administrative databases were compared between post-implementation (02/2016-09/2016) and pre-implementation cohorts (07/2015-11/2015).

RESULTS

The 314 post-implementation patients were slightly younger compared to the 351 pre-implementation patients (64.2 years vs 65.8 years, P = .02) and a higher percentage of patients had diabetes (18% vs 5.1%, P < .001). Of the 98% of post-implementation patients screened, 74% had at least 1 risk factor identified. Obstructive sleep apnea was the most common risk factor (52%), followed by depression (22%) and obesity (body mass index > 40 kg/m or 35-40 kg/m with comorbidities) (13%). Forty-six patients (20%) did not follow through with the recommended optimization before undergoing elective surgery. The post-implementation cohort had shorter average length of hospital stay (1.9 days vs 2.2 days, P < .001) and lower average total direct variable costs excluding implants ($5409 vs $5852, P < .001). There was no difference in patients discharged home (90% vs 89%, P = .53) or 90-day readmissions (4.1% vs 4.3%, P = .93).

CONCLUSION

In our experience, the majority of elective TJA patients have modifiable risk factors, indicating opportunity for preoperative intervention. Our evidence-based preoperative optimization program resulted in higher value care, demonstrated by similar outcomes with lower resource utilization.