Basu Sanjay, Landon Bruce E, Song Zirui, Bitton Asaf, Phillips Russell S
*Prevention Research Center; Centers for Health Policy, Primary Care and Outcomes Research, and Center on Poverty and Inequality, Stanford University, Stanford, CA †Department of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK ‡Department of Health Care Policy, Harvard Medical School §Division of General Internal Medicine and Primary Care, Beth Israel Deaconess Medical Center ∥Center for Primary Care, Harvard Medical School, Boston, MA.
Med Care. 2015 Feb;53(2):125-32. doi: 10.1097/MLR.0000000000000278.
Primary care practice transformations require tools for policymakers and practice managers to understand the financial implications of workforce and reimbursement changes.
To create a simulation model to understand how practice utilization, revenues, and expenses may change in the context of workforce and financing changes.
We created a simulation model estimating clinic-level utilization, revenues, and expenses using user-specified or public input data detailing practice staffing levels, salaries and overhead expenditures, patient characteristics, clinic workload, and reimbursements. We assessed whether the model could accurately estimate clinic utilization, revenues, and expenses across the nation using labor compensation, medical expenditure, and reimbursements databases, as well as cost and revenue data from independent practices of varying size. We demonstrated the model's utility in a simulation of how utilization, revenue, and expenses would change after hiring a nurse practitioner (NP) compared with hiring a part-time physician.
Modeled practice utilization and revenue closely matched independent national utilization and reimbursement data, disaggregated by patient age, sex, race/ethnicity, insurance status, and ICD diagnostic group; the model was able to estimate independent revenue and cost estimates, with highest accuracy among larger practices. A demonstration analysis revealed that hiring an NP to work independently with a subset of patients diagnosed with diabetes or hypertension could increase net revenues, if NP visits involve limited MD consultation or if NP reimbursement rates increase.
A model of utilization, revenue, and expenses in primary care practices may help policymakers and managers understand the implications of workforce and financing changes.
基层医疗实践转型需要工具,以便政策制定者和实践管理者了解劳动力和报销变化的财务影响。
创建一个模拟模型,以了解在劳动力和融资变化的背景下,实践利用率、收入和费用可能如何变化。
我们创建了一个模拟模型,使用用户指定的或公开的输入数据来估计诊所层面的利用率、收入和费用,这些数据详细说明了实践人员配备水平、薪资和间接费用支出、患者特征、诊所工作量和报销情况。我们使用劳动报酬、医疗支出和报销数据库,以及来自不同规模独立诊所的成本和收入数据,评估该模型是否能够准确估计全国范围内诊所的利用率、收入和费用。我们通过模拟与雇佣兼职医生相比,雇佣一名执业护士(NP)后利用率、收入和费用将如何变化,展示了该模型的实用性。
模拟的实践利用率和收入与独立的全国利用率和报销数据密切匹配,这些数据按患者年龄、性别、种族/族裔、保险状况和国际疾病分类(ICD)诊断组进行了分类;该模型能够估计独立的收入和成本,在较大规模的实践中准确性最高。一项示范分析表明,如果NP的就诊涉及有限的医生会诊,或者NP的报销率提高,雇佣一名NP独立治疗一部分被诊断患有糖尿病或高血压的患者可能会增加净收入。
基层医疗实践中的利用率、收入和费用模型可能有助于政策制定者和管理者理解劳动力和融资变化的影响。