Anticoagulation clinics (ACCs) are specialty clinics that manage patients with blood clotting problems. Since labor costs usually account for a substantial portion of a healthcare organization's budget, optimizing the number and types of staff required was often the focus, especially for ACCs, where labor-intensive staff-patient interactions occur. A significant portion of tasks performed by clinical pharmacists might be completed by clinical pharmacist technicians, which are lessexpensive resources. While nurse staffing models for a hospital inpatient unit are well established, these models are not readily applicable to staffing ACCs. Therefore, the objective of this paper is to develop a framework for determining the right staff mix of clinical pharmacists and clinical pharmacy technicians that increases the efficiency of care delivery process and improves the productivity of ACC staff. A framework is developed and applied to build a semi-automated fulltime equivalent (FTE) calculator and compare various staffing scenarios using a simulation model. The FTE calculator provides the right staff mix for a given staff utilization target. Data collected from the ACCs at VA Boston Healthcare System is used to illustrate the FTE calculator and the simulation model. The result of the simulation model can be used by ACC managers to easily determine the number of FTEs of clinical pharmacists and clinical pharmacy technicians required to reach the target utilization and the corresponding staffing cost.

The Centers for Medicare and Medicaid Services (CMS) Innovation Center offers two alternative payment models for joint replacement: the voluntary Bundled Payment for Care Improvement (BPCI) model and the mandatory Comprehensive Care for Joint Replacement (CJR) model. As CMS considers methods for cost reduction, research is needed to understand patient-level outcomes and organizational-level success factors. A retrospective cross-sectional study of hospitals was performed, using regression models to evaluate an aggregate patient satisfaction score, complication rates, and operational differences among BPCI, CJR, and nonparticipating hospitals. Results show that BPCI hospitals received significantly better patient satisfaction scores (88.6) than CJR hospitals (86.0), but complication rates were not significantly different between CJR and BPCI hospitals (2.83 and 2.77, respectively). Factors associated with BPCI participation include academic affiliation, a Northeast region locale, and having a higher CMS efficiency score. Thus, requiring more hospitals to participate in CMS-bundled payment programs as a federal policy may not be the optimal way to improve patient satisfaction and outcomes. Rather, the CJR and BPCI programs should be further studied, and the results generalized for use by nonparticipating hospitals to encourage preparation and participation in CMS value-based initiatives.