Return to work and productivity loss after surgery: A health economic evaluation.

BACKGROUND: We aimed to identify preoperative psychosocial factors associated with return-to-work (RTW) and the associated cost of productivity loss due to work absenteeism following surgery. Research demonstrates a high economic burden from productivity loss after surgery, but the comparative cost of productivity loss relative to income across different operations has not been examined. MATERIALS AND METHODS: A mixed surgical cohort recruited for a randomized controlled trial were prospectively followed for up to two years following surgery with daily phone assessments to three months, weekly assessments thereafter to six months, then monthly assessments thereafter to determine RTW status, opioid use and pain. RESULTS: 183 of 207 (88.3%) patients in paid employment prior to surgery, who provided at least one day of follow-up, were included in this analysis. The average cost of productivity loss due to work absenteeism was $13 761 (median $9064). Patients who underwent total knee replacement incurred the highest income loss. Medical claims filed before surgery were significantly associated with relative income loss (AOR 5.09; 95% CI 1.73-14.96; p < 0.01) and delayed postoperative RTW. Elevated preoperative PTSD symptoms were associated with delayed RTW (HR 0.78; 95%CI 0.63-0.96; p-value = 0.02) while male gender (HR 1.63; 95%CI 1.11-2.38; p-value = 0.01) was associated with faster postoperative RTW. CONCLUSION: Surgery places a high economic burden on individuals due to postoperative productivity loss. Multidisciplinary approaches, such as pathways, that facilitate the operation and recovery may mitigate the economic consequences for patients, employers, and the healthcare system.

Improving Care With a Portfolio of Physician-Led Cancer Quality Measures at an Academic Center.

PURPOSE: Development and implementation of robust reporting processes to systematically provide quality data to care teams in a timely manner is challenging. National cancer quality measures are useful, but the manual data collection required is resource intensive, and reporting is delayed. We designed a largely automated measurement system with our multidisciplinary cancer care programs (CCPs) to identify, measure, and improve quality metrics that were meaningful to the care teams and their patients. METHODS: Each CCP physician leader collaborated with the cancer quality team to identify metrics, abiding by established guiding principles. Financial incentive was provided to the CCPs if performance at the end of the study period met predetermined targets. Reports were developed and provided to the CCP physician leaders on a monthly or quarterly basis, for dissemination to their CCP teams. RESULTS: A total of 15 distinct quality measures were collected in depth for the first time at this cancer center. Metrics spanned the patient care continuum, from diagnosis through end of life or survivorship care. All metrics improved over the study period, met their targets, and earned a financial incentive for their CCP. CONCLUSION: Our quality program had three essential elements that led to its success: (1) engaging physicians in choosing the quality measures and prespecifying goals, (2) using automated extraction methods for rapid and timely feedback on improvement and progress toward achieving goals, and (3) offering a financial team-based incentive if prespecified goals were met.