Background: Value-based health-care delivery is a framework for restructuring our health-care systems with the goal of providing better outcomes for patients at lower cost. Value is determined by patient health outcomes per dollar spent on health services. We sought to develop a value dashboard that could be used to easily track and improve the value of total hip and knee arthroplasty (THA and TKA). Methods: We created a value dashboard for TKAs and THAs at our institution. Value was defined as quality of outcomes per dollar spent. The dashboard for each procedure displayed the average value by surgeon, compared with institutional averages for physical function scores and cost. Quality metrics were determined by weighted surgeon ranking using a modified Delphi process and included both clinical and patient-reported outcomes, as measured by the mean change in the Patient-Reported Outcomes Measurement Information System Global-10 (PROMIS-10) physical function score, mean change in the Hip disability and Osteoarthritis Outcome Score-Joint Replacement (HOOS-JR) or the Knee injury and Osteoarthritis Outcome Score-Joint Replacement (KOOS-JR), mean change in the modified Single Assessment Numeric Evaluation (SANE) score, complication rate, periprosthetic joint infection (PJI) rate, and 30-day readmission rate. Average direct costs per surgeon were used. Data from January 2017 through April 2018 were included to ensure 1-year follow-up. Results: Six surgeons were included in the value dashboard for TKA, and 5 were included in the THA dashboard. The value for TKA by surgeon ranged from 7% below to 12% above the institutional benchmark. The value for THA by surgeon ranged from 12% below to 7% above the institutional benchmark. Conclusions: The proposed dashboard utilizes value in a health-care framework and could be used for comparing and improving value for THA and TKA. This dashboard successfully combined patient outcome metrics and direct costs of surgical procedures. Future studies should focus on involving patients in this process and using national data to create benchmarks, which could provide a more accurate representation of value than using institutional averages.

Triple-negative breast cancer is a highly aggressive subtype of breast cancer. Frequently, breast cancer cells modulate their calcium signaling pathways to optimize growth. Unique calcium pathways in breast cancer cells could serve as a way to target tumorigenic cells without affecting normal tissue. Resveratrol has previously been shown to activate calcium signaling pathways. We use cell viability, single-cell calcium microscopy, and RT-PCR assays to determine the activity and mechanism of three different 4′-esterified resveratrol derivatives. We demonstrate that two of the derivatives reduce cell viability more effectively than resveratrol in MDA-MB-231 human breast cancer cells. The derivatives also activate similar pro-apoptotic calcium signaling pathways. In particular, the pivalated and butyrated resveratrol derivatives are intriguing putative chemotherapeutics because they are more effective at decreasing cell viability in vitro and inhibiting the plasma membrane Ca2+-ATPase, a protein that is often modulated in breast cancer.

Combining chemotherapeutics to treat malignant tumors has been shown to be effective in preventing drug resistance, tumor recurrence, and reducing tumor size. We modeled combination drug therapy in PC-3 human prostate cancer cells using mixture design response surface methodology (MDRSM), a statistical technique designed to optimize compositions that we applied in a novel manner to design combinations of chemotherapeutics. Conventional chemotherapeutics (mitoxantrone, cabazitaxel, and docetaxel) and natural bioactive compounds (resveratrol, piperlongumine, and flavopiridol) were used in 12 different combinations containing three drugs at varying concentrations. Cell viability and cell cycle data were collected and used to plot response surfaces in MDRSM that identified the most effective concentrations of each drug in combination. MDRSM allows for extrapolation of data from three or more compounds in variable ratio combinations, unlike the Chou-Talalay method. MDRSM combinations were compared with combination index data from the Chou-Talalay method and were found to coincide. We propose MDRSM as an effective tool in devising combination treatments that can improve treatment effectiveness and increase treatment personalization, because MDRSM measures effectiveness rather than synergism, potentiation, or antagonism.