A STATISTICAL METHOD FOR MONITORING NON-ACCEPTABLE DIAGN

联邦医疗保险制度下的政府、私营保险公司和一些管理型医疗保健 各组织已采用(诊断相关组)DRG系统作为 医院住院费用报销的依据。的DRG代码 住院是基于一种使用患者的复杂算法 用于确定医疗费用报销的医疗记录。最近 对医疗保险系统的审计估计，数十亿不必要的 由于供应商不正确的编码，可能已经花费了美元。 目前，发现不正确的DRG代码是由于昂贵 对病人病历样本的审核。因为审计依赖于 人力资本，需要充足的工作人员，并与 医院财务调整从审计开始会滞后于时间 住院时间的记录。此外，只有所有医疗记录的样本是 仔细检查，大多数记录都不是。 该项目将使用已从一家保险公司获得的数据来设计 并测试模型以预测索赔是否编码错误。 统计模型的估计值将用作 统计监测，以确定进程是否(百分比 错误的DRG代码)已更改。关于应用的策略 型号和显示器将确定。新政策的有效性 系统将通过检查与当前使用的系统进行比较 DRG代码不正确的比率和不必要的付款金额。 一种廉价的统计控制系统来监控错误的DRG 对所有索赔进行编码将减少管理成本，并 提高对不必要支付的监测精确度。一个 建立在电子信息基础上的统计模型可以 加快审核过程，并更及时地提供调整 时尚。所有索赔都可以包括在这样的系统中，而这些索赔 有更高的机会是错误的，可以进一步检查。这个 然后可以使用分析的结果来改进预测 原始模型的准确性。型号和监视器将不会 专利和研究结果将发表在 开放科学文献。

The government under Medicare, private insurers, and some managed care organizations have adopted the (Diagnosis Related Group) DRG system as a basis for reimbursing hospitals for inpatient stays. The DRG code for a hospital stay is based on a complicated algorithm that uses patient medical records for determining health care reimbursement. A recent audit of the Medicare system estimates that billions of unnecessary dollars may have been spent due to incorrect coding by providers. Currently, a finding of incorrect DRG codes results from expensive audits of samples of patient medical records. As the audit relies on human capital which requires adequate staffing and coordination with the hospital, financial adjustments from the audit will lag from the time of the hospital stay. Also, only a sample of all medical records are examined, most records are not. This project will use data already available from one insurer to design and test a model to predict whether a claim is coded incorrectly. Estimates from the statistical model will be used as input to the statistical monitor to determine whether the process (percent of incorrect DRG codes) has changed. Strategies for application of the model and monitor will be determined. The effectiveness of the new system will be compared to that which is currently in use by examining the rate of incorrect DRG codes and the dollars of unnecessary payments. An inexpensive statistical control system to monitor the incorrect DRG coding for all claims would decrease the administrative costs and increase the precision of monitoring for unnecessary payments. A statistical model built on electronically available information could expedite the auditing process and provide adjustments in a more timely fashion. All claims could be included in such a system and those claims with a higher chance of being incorrect could be further examined. The results of the analysis could then be used to improve the predictive accuracy of the original model. The model and monitor will not be proprietary and the results of the research will be published in the open scientific literature.