Transition to Value-based Healthcare: Development, Implementation, and Results of an Optimal Surgical Care Framework at a National Cancer Institute-designated Comprehensive Cancer Center.

BACKGROUND: The continued rise in healthcare expenditures has not produced commensurate improvements in patient outcomes, leading US healthcare stakeholders to emphasize value-based care. Transition to such a model requires all team members to adopt a new strategic and organizational framework. OBJECTIVE: To describe and report a strategy for the implementation of a novel patient-centered value-based "optimal surgical care" (OSC) framework, with validation and cost analysis in kidney surgery. DESIGN, SETTING, AND PARTICIPANTS: An observational study of care episodes at a single institution from 2014 to 2019 was conducted. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Multidisciplinary teams defined OSC by core and procedure-specific metrics using a combination of provider-based ("bottom-up") and "clinical leadership"-based ("top-down") strategies. Baseline OSC rates across were established, while identifying proportions of OSC achieved by coefficient of variation (CV) in total direct costs. Multivariable linear regression comparing cost between OSC and non-OSC encounters was performed, adjusting for patient characteristics. RESULTS AND LIMITATIONS: An analysis of 30 261 perioperative care episodes was performed. Following the implementation of an OSC framework, there was an increase in OSC rates across all procedure buckets using core (25%) and procedure-specific (26%) metrics. Among the tumors tested, kidney cancer surgical episodes held the highest OSC rate improvement (67%) with lowest variability in cost (CV 0.5). OSC was associated with significant total cost savings across all tumor types after adjusting for inflation (p < 0.05). Compared with non-OSC episodes, a significant reduction in the cost ratio of OSC was noted for renal surgery (p < 0.01), with estimated costs savings of $2445.87 per OSC encounter. CONCLUSIONS: Institutional change directing efforts toward optimizing surgical care and emphasizing value rather than focusing solely on expense reduction is associated with improved outcomes, while potentially reducing costs. The strategy for implementation requires serial performance analyses, engaging and educating providers, and continuous ongoing adjustments to achieve durable results. PATIENT SUMMARY: In this study, we report our strategy and outcomes for transitioning to a value-based healthcare model using a novel "optimal surgical care" framework at a National Cancer Institute-designated comprehensive cancer center. We observed an increase in optimal surgical care episodes across all specialties after 5 yr, with a potential associated reduction in cost expenditure. We conclude that the key to a successful and sustained transition is the implementation strategy, focusing on continual review and provider engagement.

Yield and Cost-effectiveness of Computed Tomography Colonography Versus Colonoscopy for Post Colorectal Cancer Surveillance.

Purpose. As part of a clinical trial comparing the utility of computed tomographic colonography (CTC) and optical colonoscopy (OC) for post colorectal cancer resection surveillance, we explored the diagnostic yield and costs of a strategy of CTC followed by OC if a polyp is observed (abbreviated CTC_S), versus OC 1 year following curative bowel resection, using the detection of actionable polyps on OC as the criterion. Methods. Using data from 231 patients who underwent same-day CTC followed by OC, we created a decision tree that outlined the choices and outcomes at 1-year clinical follow-up. Colorectal polyp prevalence, sensitivity, and specificity of CTC were compared with five exemplary studies and meta-analyses. Detection criteria were derived for ≥6 mm or ≥10 mm polyps. OC was the gold standard. Costs were gleaned from cataloging components of the cases at the principal investigator's institution. Analyses included marginal cost of the OC strategy to detect additional actionable polyps and number of polyps missed per 10,000 patients. Results. At our prevalence of 0.156 for ≥6 mm (0.043 ≥10 mm), CTC_S would miss 779 ≥6 mm actionable polyps per 10,000 patients (≥10 mm: 173 per 10,000). Cost to detect an additional ≥6 mm polyp in this cohort is $5,700 (≥10 mm: $28,000). Sensitivity analyses demonstrate that any improvement in performance characteristics would raise the cost of OC to detect more actionable polyps. Similar results were seen using Medicare costs, or when literature values were used for performance characteristics. Conclusion. At an action threshold of ≥6 mm, OC costs at least $5,700 per extra polyp detected relative to CTC_S in patients undergoing surveillance after colorectal cancer surgery, on the order of incremental cost-effectiveness ratios found for other clinical problems involving short-term events.

Establishment and validation of circulating tumor cell-based prognostic nomograms in first-line metastatic breast cancer patients.

PURPOSE: Circulating tumor cells (CTC) represent a new outcome-associated biomarker independent from known prognostic factors in metastatic breast cancer (MBC). The objective here was to develop and validate nomograms that combined baseline CTC counts and the other prognostic factors to assess the outcome of individual patients starting first-line treatment for MBC. EXPERIMENTAL DESIGN: We used a training set of 236 patients with MBCs starting a first-line treatment from the M.D. Anderson Cancer Center (Houston, TX) to establish nomograms that calculated the predicted probability of survival at different time points: 1, 2, and 5 years for overall survival (OS) and 6 months and 1 and 2 years for progression-free survival (PFS).The covariates computed in the model were age, disease subtype, visceral metastases, performance status, and CTC counts by CellSearch. Nomograms were independently validated with 210 patients with MBCs from the Institut Curie (Paris, France) who underwent first-line chemotherapy. The discriminatory ability and accuracy of the models were assessed using Harrell c-statistic and calibration plots at different time points in both training and validation datasets. RESULTS: Median follow-up was of 23 and 29 months in the MD Anderson and Institut Curie cohorts, respectively. Nomograms showed good c-statistics: 0.74 for OS and 0.65 for PFS and discriminated OS prediction at 1, 2, and 5 years, and PFS prediction at 6 months and 1 and 2 years. CONCLUSIONS: Nomograms, which relied on CTC counts as a continuous covariate, easily facilitated the use of a web-based tool for estimating survival, supporting treatment decisions and clinical trial stratification in first-line MBCs.