842例工人、农民和战士最大呼气流量-容积曲线的测定

作者用“点值法”对成都市内和郊区842例从事轻、中、重劳动的健康工人、农民和战士作了MEFV曲线和常规肺功能测定,发现工人和农民在低肺容积时流量增加,在高、中肺容积时流量下降,并以农民最明显,重劳动工人次之,轻、中劳动工人较不明显,战士则相反。揭示不同的体力活动方式及生活条件可导致不同肺容积时的流量改变,以适应其代谢增强时的耗氧需求。     

三维及多平面重建CT技术在鼻部整形中的应用价值分析

目的:分析在鼻部整形中三维及多平面重建CT技术的应用价值。方法:选择2018年2月~2019年7月本院收治的60例行鼻部整形的患者进行分析,所有患者均开展三维及多平面重建CT技术检测,结合检查结果,开展相应的隆鼻手术。分析术后不良反应、患者满意度。术后6个月,在CT测量下,检测前后鼻部解剖数据。结果:在鼻部整形中,三维及多平面重建CT技术的应用,可以准确了解鼻部结构,如观察侧鼻骨、鼻部皮肤、鼻根等情况。术后评价,患者对鼻部整形满意度较高,术后6个月,患者对鼻部整形满意度较高,术后与术后6个月患者鼻部满意度相比,无统计学意义,P>0.05。术后60例患者没有出现出血、切口感染等反应,同时也没有出现肋软骨外漏与倾斜等现象。经随访术后6个月发现1例患者的鼻背软骨出现轻度弯曲,但无明显表现,没有做特殊处理;其余患者,鼻部外形均表现为鼻尖挺拔、鼻背曲线流畅。结论:在鼻部整形中,应用三维及多平面重建CT技术,可以辅助提高隆鼻手术准确度,并在CT技术的引导下,准确植入自体肋软骨,可以为手术成功奠定基础,促使鼻唇与周围器官形态的协调性,进一步提高患者满意度。     

Assessing the Economic Value of Clinical Artificial Intelligence: Challenges and Opportunities

ObjectivesClinical artificial intelligence (AI) is a novel technology, and few economic evaluations have focused on it to date. Before its wider implementation, it is important to highlight the aspects of AI that challenge traditional health technology assessment methods.MethodsWe used an existing broad value framework to assess potential ways AI can provide good value for money. We also developed a rubric of how economic evaluations of AI should vary depending on the case of its use.ResultsWe found that the measurement of core elements of value—health outcomes and cost—are complicated by AI because its generalizability across different populations is often unclear and because its use may necessitate reconfigured clinical processes. Clinicians’ productivity may improve when AI is used. If poorly implemented though, AI may also cause clinicians’ workload to increase. Some AI has been found to exacerbate health disparities. Nevertheless, AI may promote equity by expanding access to medical care and, when properly trained, providing unbiased diagnoses and prognoses. The approach to assessment of AI should vary based on its use case: AI that creates new clinical possibilities can improve outcomes, but regulation and evidence collection may be difficult; AI that extends clinical expertise can reduce disparities and lower costs but may result in overuse; and AI that automates clinicians’ work can improve productivity but may reduce skills.ConclusionsThe potential uses of clinical AI create challenges for health technology assessment methods originally developed for pharmaceuticals and medical devices. Health economists should be prepared to examine data collection and methods used to train AI, as these may impact its future value.     

The History and Future of the “ISPOR Value Flower”: Addressing Limitations of Conventional Cost-Effectiveness Analysis

ObjectivesSince its publication as part of the 2018 ISPOR Special Task Force (STF) on US Value Assessments, the “ISPOR value flower,” with its petals highlighting elements that may be overlooked or underappreciated in conventional drug value assessments, has been discussed and debated. We review the history of the value flower, describe recent developments, and consider implications for future value assessments.MethodsWe discuss various antecedents to the value flower, as well as conceptual and empirical articles published in the past 4 years.ResultsSince the publication of the ISPOR STF report, researchers have provided more rigorous theoretical and mathematical foundations for certain novel value elements (eg, severity of illness, value of insurance, value of hope) through “generalized risk-adjusted cost-effectiveness analysis,” which incorporates risk aversion in people’s preferences and uncertainty in treatment outcomes. Empirical estimates are also emerging to support key elements, such as insurance value, real option value, value of hope, and value of knowing. Although health technology assessment bodies have applied or are considering certain elements (eg, severity modifiers to cost-effectiveness thresholds), other elements have yet to gain traction.ConclusionsFive years after the STF began its work, the development of novel value measures continues to evolve. Although it is encouraging to see supporting empirical studies emerging, more are needed. Additional efforts are also needed to illustrate how the estimates can be used in the deliberative processes that are integral to health technology assessments.     

Development of an EQ-5D Value Set for India Using an Extended Design (DEVINE) Study: The Indian 5-Level Version EQ-5D Value Set

ObjectivesThis study aimed to develop the Indian 5-level version EQ-5D (EQ-5D-5L) value set, which is a key input in health technology assessment for resource allocation in healthcare.MethodsA cross-sectional survey using the EuroQol Group’s Valuation Technology was undertaken in a representative sample of 3548 adult respondents, selected from 5 different states of India using a multistage stratified random sampling technique. The participants were interviewed using a computer-assisted personal interviewing technique. This study adopted a novel extended EuroQol Group’s Valuation Technology design that included 18 blocks of 10 composite time trade-off (c-TTO) tasks, comprising 150 unique health states, and 36 blocks of 7 discrete choice experiment (DCE) tasks, comprising 252 DCE pairs. Different models were explored for their predictive performance. Hybrid modeling approach using both c-TTO and DCE data was used to estimate the value set.ResultsA total of 2409 interviews were included in the analysis. The hybrid heteroscedastic model with censoring at ?1 combining c-TTO and DCE data yielded the most consistent results and was used for the generation of the value set. The predicted values for all 3125 health states ranged from ?0.923 to 1. The preference values were most affected by the pain/discomfort dimension.ConclusionsThis is the largest EQ-5D-5L valuation study conducted so far in the world. The Indian EQ-5D-5L value set will promote the effective conduct of health technology assessment studies in India, thereby generating credible evidence for efficient resource use in healthcare.     

补肾生血方联合西药治疗再生障碍性贫血早期疗效预测指标

目的：探讨补肾生血方联合西药治疗再生障碍性贫血（AA）早期疗效的预测指标,为中医补肾治法联合西药治疗AA提供预后参考指标。方法：本研究为回顾性研究,选取2018年9月至2021年3月于中国中医科学院西苑医院等19家医院就诊并采用补肾生血方联合西药治疗6个月有效的126例患者,评价其治疗4个月时的疗效,根据治疗4个月时的疗效评价结果将其分为4个月有效组和4个月无效组,分析比较两组患者治疗前在年龄、性别、疾病分型[包括重型AA(SAA)、非重型AA(NSAA)]、病程、骨髓有核细胞增生程度及基线血象水平[包括白细胞（WBC）、中性粒细胞（ANC）、血红蛋白（HGB）、血小板（PLT）、网织红细胞（RET）]、T淋巴细胞及亚群、T-box转录因子（T-bet）、GATA家族转录因子-3(GATA-3)表达水平指标上的差异。结果：4个月有效组在20岁≤年龄<40岁及60岁≤年龄<80岁患者占比较高（P<0.05）;两组患者在性别、疾病分型（SAA/NSAA）、病程、有无合并症等方面均差异无统计学意义。4个月有效患者治疗前HGB、WBC、ANC、PLT基线水平明显高于治疗4个月...     

政策反馈理论视域：中国医疗卫生政策钟摆式变迁及其逻辑

新中国成立以来,党和国家不断强化医疗卫生建设,70余年来医疗卫生政策演进呈钟摆式变迁的特征,即从公益导向的福利性医疗卫生政策摆向效率导向的市场化政策,再摆向公益为主兼顾效率的民生导向政策,在公益与效率间发生三次摆动。本文借助政策反馈理论分析医疗卫生政策钟摆式变迁的内在逻辑,发现政策变迁过程中原有政策通过资源效应、解释效应、演化效应和学习效应影响新政策的制定,使得新政策留有原政策的烙印,呈现出摆动式变迁而非剧烈或范式变迁。政策反馈理论为医疗卫生政策制定提供新视角,制定医疗卫生政策需注重原政策的历史影响力,以公共价值引领医疗医保医药政策,从多重政策反馈效应视角出发优化卫生政策的制定。     

雌孕激素序贯用药治疗流产术后宫腔残留患者的临床价值分析

目的分析雌孕激素序贯用药治疗流产术后宫腔残留患者的临床价值。方法选取2017年1月至2019年12月我站收治的人工流产患者60例,按治疗方式不同分为对照组(28例)和观察组(32例)。对照组采用刮宫治疗,观察组于人工流产术后第7 d行B超检查,观察宫腔残留情况后采用药物治疗。比较两组的临床疗效、并发症。结果两组的总有效率比较无统计学差异(P>0.05)。观察组的腹痛发生率低于对照组,出血时间短于对照组(P <0.05)。结论雌孕激素序贯用药治疗能够有效清除宫腔残留,缩短出血时间,减轻腹痛,有利于重新建立正常的月经周期,促进子宫功能修复,避免再次刮宫对子宫内膜的损伤及手术对患者造成的不良身心应激,具有较高的临床推广价值。     

肿瘤M2型丙酮酸激酶检测在结肠癌诊断中的临床价值

目的探究肿瘤M2型丙酮酸激酶检测在结肠癌诊断中的临床价值。方法选取本院经病理诊断确诊为结肠癌的50例患者与结肠腺瘤的60例患者分别设为结肠癌组与结肠腺瘤组,选择90例健康人设为正常组,分别使用ELISA、化学发光法(CL)检测血浆M2-PK数值及癌胚抗原(CEA)水平。结果结肠癌组及Dukes C、D期肿瘤M2-PK水平与结肠腺瘤组、正常组及Dukes A、B期相比更高(P<0.05),肿瘤M2-PK结肠癌诊断敏感性与CEA相比更高。结论肿瘤M2型丙酮酸激酶检测在结肠癌诊断中具有较高的临床价值,且肿瘤M2-PK的敏感性高于CEA,与肿瘤分期之间具有十分密切的联系,能够有效应用于结肠癌的筛查与诊断工作当中。     

医疗绩效管理中实施PDCA循环的效果分析

目的对比分析实施PDCA循环前后医疗绩效管理的效果。方法医院每季度进行一次绩效管理考核,分为核心制度、病历质量、用药情况、耗材情况和医疗效率5个维度。2019年第一季度绩效管理开始引入PDCA循环,以第一季度各维度得分作为基础值,对比分析引入PDCA循环前后各维度得分,以手术科室为例,进行统计分析。结果核心制度、病历质量、耗材情况维度得分比较,均P<0.05,差异具有统计学意义;用药情况、医疗效率维度得分比较,均P>0.05,但各季度得分相比基础值均逐渐升高,第四季度与基础值比较差异具有统计学意义(P<0.05)。结论医疗绩效管理中实施PDCA循环,能有效提升管理水平,促进医疗质量螺旋上升。