多元线性回归模型在住院费用测算中的应用

以河北省某市8所医疗机构1184名住院患者的病案首页信息为研究样本，采用多元线性回归分析方法测算每种疾病各组患者的住院费用标准，同时探讨回归方程的优势以及参数设置、应用需注意的问题。     

合肥市某三甲医院新农合重大疾病按病种付费实施效果分析

目的了解合肥市某三甲医院新农合重大疾病按病种付费实施3年来的情况,调查按病种付费实施后,平均住院日、医疗费用和实际补偿比的变化情况。方法对该院实施新农合重大疾病按病种付费前后平均住院日、医疗费用和实际补偿比做统计分析。结果与实施前相比,实施后各病种平均住院日均有所下降,其中3个病种实施前后差异有统计学意义;人均费用明显降低,6个病种前后差异均有统计学意义;实际补偿比大幅上涨,6个病种差异均有统计学意义。结论实施按病种付费对平均住院日控制效果不明显,对控制医疗费用增长效果明显,对提高实际补偿比效果显著,但仍需结合相应的管理办法对其进行补充和完善。     

34家医院病案首页存在问题分析及改进措施

目的：云南省卫生厅为提高各级医院的诊疗及管理水平,组织相关人员以卫计委修订的2012版病案首页项目内容为基础和填写要求,调查了解云南省二、三级综合医院病案首页信息填写水平及缺陷,针对性的整改,尽快规范病案首页的填写。方法对省内34家二、三级医院各抽取20份出院病案,就病案首页内容进行检查。结果检查780份病案,发现缺陷病案首页共512份,达65.6%。发现患者基本信息、诊疗信息、费用信息和编码填写存在诸多缺陷。结论卫生行政部门加强管理和引导,组织有针对性的培训和检查,督促医务人员掌握病案首页填写规范和技能,取得较好的效果。     

不同决策树算法建立DRGs模型的差异

目的 通过分析不同决策树算法的数据差异,探讨最为适合建立DRG模型的算法.方法 择2007年1月-2012年9月病案首页第一诊断为呼吸系统疾病的12984病案,分别采用CART、CHAID和E-CHAID三种决策树算法建立DRGs模型,并比较模型间的差异.结果 CART算法建立的DRGs模型包括12个DRGs组,使用了6个分组因素,最重要的分组因素为疾病严重程度,模型的Risk值为0.449.CHAID算法建立的DRGs模型包括20个DRGs组,只使用了5个分组因素,分组因素中不包括有无输血,最重要的分组因素为有无手术,模型的Risk值为0.448.E-CHAID算法建立的DRGs模型包括15个DRGs组,使用了6个分组因素,最重要的分组因素为疾病严重程度,模型的Risk值为0.445.结论 通过比较后可认为E-CHAID算法要比其他两种算法更适合于建立DRGs模型.     

临床药师参与的处方点评与医保控费及DRGs干预前后我院住院患者质子泵抑制剂应用情况分析

目的：探讨临床药师参与的处方点评与医保控费及DRGs对我院质子泵抑制剂干预效果。方法：对医院干预前（2017年4月至2017年6月）、干预第一阶段（2017年7月至2017年9月）、干预第二阶段（2017年10月至2017年12月）、干预第三阶段（2018年1月至2018年3月）质子泵抑制剂的人均消费金额和用药合理性进行对比和分析。结果：我院外科住院患者人均PPIs费用干预第一阶段平均增长率为-49.86%,干预第二阶段平均增长率为-42.33%,干预第三阶段平均增长率为-69.59%;内科住院患者人均PPIs费用干预第一阶段平均增长率为-12.29%,干预第二阶段平均增长率为-23.28%,干预第三阶段平均增长率为-35.74%。不合理使用率由干预前的47.5%降至第一阶段干预后的21.5%,并进一步降至第二阶段干预后的13.0%,至第三阶段干预后的4.5%。结论：临床药师参与的处方点评与医保控费及DRGs促进了我院质子泵抑制剂的合理使用,降低了我院质子泵抑制剂的使用费用,为患者减轻了经济负担。     

病例组合方法及应用探讨

为了保证卫生资源分配的有效性和公平性,我国社会医疗保险制度中有必要引入病例组合(Casemix)的管理模式,病例组合是迄今为止国际上较为理想的卫生资源管理及疾病组合模式,病例组合的实施还能够帮助卫生管理机构建立医疗服务质量的评判标准及医疗机构和个人医疗服务质量与效率的比较标准,从而促进医疗服务质量与效率以及我国公共卫生管理水平的全面提高。     

Stroke units and general wards in seven Italian regions: the PROSIT Study

Abstract PROSIT (research PROject on Stroke services in ITaly) is a study performed to evaluate number and work organisation of acute in-hospital services (stroke units, SU) and general wards (GW), in seven Italian regions (Liguria, Lombardia, Lazio, Veneto, Friuli-Venezia-Giulia, Emilia Romagna, Toscana), which have a population of 29 169 811 inhabitants and a relative ratio of 225/100 000 hospitalisations for acute stroke. The registers of hospital discharges from January to December 1999 were looked at identify to services recording at least 50 acute stroke discharges (DRG14) per year. A structured questionnaire investigating stroke service characteristics was submitted to the doctors in charge of the identified units and completed in the presence of an external observer between October 2000 and February 2001. SUs were identified as units with dedicated beds (at least 80%) and team (at least 1 physician and 1 nurse) for acute stroke patients. SUs are still uncommon in many Italian regions because only, as 7% of the wards evaluated were found to be a SU and less than 10% of acute stroke patients resulted to be admitted to a SU. Great heterogeneity was found between the different regions surveyed. The most striking differences between SUs and GW were related to the staffing and care organisation, with higher number/patients ratio in SUs as far as physicians and nurses, speech therapists and social workers were concerned.on behalf of PROSIT collaborators**I. Santilli (Milano), F. Chiodograndi (Trieste), M. Stramba Badiale (Milano), G. P. Anzola (Brescia), M. Del Sette (Genova), D. Guidetti (R Emilia), P. Nencini (Firenze), C. Argentino (Roma), V. Toso (Vicenza)     

DRGs in Transfusion Medicine and Hemotherapy in Germany

Patients requiring transfusion medicine and hemotherapy in an inpatient setting are incorporated into the German Diagnosis Related Groups (G-DRG) system in multiple ways. Different DRGs exist in Major Diagnostic Category 16 for patients that have been admitted for the treatment of a condition from the field of transfusion medicine. However, the reimbursement might be not cost covering for many cases, and efforts have to be intensified to find adequate definitions and prices. We believe that this can only be successful if health service research is intensified in this field. For patients requiring hemotherapy and transfusion medicine concomitant to the treatment of an underlying disease such as cancer, multiple systems exist to increase remuneration, among them the Patient Clinical Complexity Level (PCCL) and complex constellations to induce DRG splits. For direct reimbursement of high cost products, additional remuneration fees (Zusatzentgelte, ZE) are the most important. In addition, expensive innovations not reflected within the DRGs can be reimbursed after application and negotiation of the New Diagnostic and Treatment Methods (Neue Untersuchungs-und Behandlungsmethoden, NUB) system. The NUB system guarantees that medical progress is put rapidly into clinical practice and prevents financial issues from becoming a stumbling block for the use of innovative drugs and methods.     

How do Hospitals Respond to Price Changes? Evidence from Norway

Many publicly funded health systems use activity‐based financing to increase hospital production and efficiency. The aim of this study is to investigate whether price changes for different treatments affect the number of patients treated and the mix of activity provided by hospitals. We exploit the variations in prices created by the changes in the national average treatment cost per diagnosis‐related group (DRG) offered to Norwegian hospitals over a period of 5 years (2003–2007). We use the data from Norwegian Patient Register, containing individual‐level information on age, gender, type of treatment, diagnosis, number of co‐morbidities and the national average treatment costs per DRG. We employ fixed‐effect models to examine the changes in the number of patients treated within the DRGs over time. The results suggest that a 10% increase in price leads to about 0.8–1.3% increase in the number of patients treated for DRGs, which are medical (for both emergency and elective patients). In contrast, we find no price effect for DRGs that are surgical (for both emergency and elective patients). Moreover, we find evidence of upcoding. A 10% increase in the ratio of prices between patients with and without complications increases the proportion of patients coded with complications by 0.3–0.4 percentage points. Copyright © 2015 John Wiley & Sons, Ltd.