中国基层医疗卫生机构运行效率及影响因素研究

背景　基层医疗卫生机构是我国卫生服务体系的网底,承担着基本医疗和基本公共卫生服务的职责,在改善居民健康状况、降低医药费用等方面起着重要作用,目前国内关于全国性基层医疗卫生机构效率的研究较为缺乏。目的　分析我国基层医疗卫生机构运行效率,探讨基层医疗卫生机构效率的影响因素。方法　数据来源于2016年11月—2017年5月“基层医疗服务能力和质量的综合评价”项目,收集322家基层医疗卫生机构的外部特征、内部管理与技术因素、投入-产出指标等资料。采用数据包络分析计算基层医疗卫生机构的效率值,采用多元线性回归分析基层医疗卫生机构效率的影响因素,提出针对性的建议。结果　322家基层医疗卫生机构平均规模效率、纯技术效率、综合技术效率值分别为（0.79±0.23）、（0.52±0.25）、（0.42±0.26）。多元线性回归分析结果显示,地域、财政补助方式、辖区6岁以下儿童人数为基层医疗卫生机构规模效率的影响因素,地域、是否开设外科、是否使用电子病历、绩效工资主要的影响因素是否包括国家公共卫生服务达标率是基层医疗卫生机构纯技术效率的影响因素,地域、辖区6岁以下儿童人数、是否开设外科为基层医疗卫生机构综合效率的影响因素（P<0.05）。结论　财政补贴应逐渐向按服务单元付费的购买模式转变,开设临床外科可能对基层医疗卫生机构效率不利,薪酬制度的改革可提升基层医疗卫生机构效率。     

从有偿服务看公立医疗卫生机构的运作效率

鉴于公立医院的财政投入比重过小,对医院运作效率的影响不典型,所以,该文运用投入产出定量模型,比较全国疾病控制中心的"财政投入模式(计划包干模型)"、"有偿服务模式(市场运作模型)"和"财政投入与有偿服务混合模式(综合效率模型)"的效率,发现三类模式的运作效率比为1∶7.2∶2.8,得出了目前的财政在投入量不足前提下,投入的效率低下,有偿服务虽有待规范,但是,其市场机制下的高运作效率,尤其是提高运作效率的激励机制却是值得借鉴的,疾控中心因为财政投入和有偿服务收入各约占总收入的一半,因而,总体运作效率也是计划包干的2.8倍.因而服务收费占总收入90%以上的医院,目前的运作效率总体并不低下,问题是补偿机制扭曲下,医院的运作效率朝着拓展业务收入、提供能够增收项目方向发展,从而医疗费用过快增长等成为问题.因此,单个医院的高效率并不意味着卫生事业发展的高效率.     

预警管理在压疮管理中的效能分析

目的运用风险预警管理理念,提升护理人员压疮管理意识,降低压疮发生率。方法选取2009年1月-2011年12月通过护理软件上报的压疮高危患者及压疮患者数据进行分析,对存在的薄弱点及时指导并积极制定整改措施,优化压疮管理流程。结果护理人员预防压疮的意识提高,上报压疮高危患者数逐年上升,2009年-2011年极危及高危上报例数占全院出院人数的比率分别为0．76％、1．01％、1．13％;2009年-2011年院内难免压疮发生率分别为0．06％、0．06％、0．02％。结论以伤口小组管理压疮为依托,培养护理人员风险预警管理理念,赋予相应的职责及管理目标有助于压疮的规范管理及学科水平的不断提高。     

昂丹司琼预防麻醉后寒战有效性和安全性的Meta分析

目的评价昂丹司琼预防麻醉后寒战的有效性和安全性。方法计算机检索Cochrane Library、PubMed、Embase、CNKI、万方、维普等数据库,检索时间为建库至2018年8月,纳入以昂丹司琼预防麻醉后寒战为研究目的,研究组为昂丹司琼,对照组为生理盐水或哌替啶或曲马多的随机对照试验,采用RevMan 5.3对数据进行Meta分析,根据不同对照组、不同麻醉方式及不同剂量进行亚组分析。结果共纳入16项研究,1 443例受试者。有效性方面,研究组寒战发生率明显低于生理盐水组(RR=0.42,95%CI 0.35～0.51,P0.001);与哌替啶组(RR=0.68,95%CI 0.44～1.05,P=0.09)及曲马多组(RR=2.07,95%CI 0.90～4.75,P=0.09)差异无统计学意义;在3个不同麻醉方式亚组(RR=0.44,95%CI 0.36～0.54,P0.001),2个不同剂量亚组(RR=0.41,95%CI 0.34～0.49,P0.001)中,研究组寒战发生率明显低于生理盐水组。安全性方面,研究组术后恶心呕吐发生率明显低于生理盐水组(RR=0.27,95%CI 0.16～0.46,P0.001)。结论昂丹司琼可有效预防麻醉后寒战的发生,其效果与哌替啶、曲马多相当,并且可明显减少术后恶心呕吐的发生。     

A liquid-scintillation-based primary standardization of Pb

A new radioactivity solution standard of ²¹⁰Pb has been developed and will be disseminated by the National Institute of Standards and Technology (NIST) as standard reference material (SRM) 4337. This new ²¹⁰Pb solution standard is contained in a 5 mL flame-sealed borosilicate glass ampoule, consists of (5.133±0.002) g of a nominal 1 mol L⁻¹ nitric acid solution, has a density of (1.028±0.002) g mL⁻¹ at 20 °C, has carrier ion concentrations of about 11 μg Pb²⁺ and 21 μg Bi³⁺ per gram of solution, and is certified to contain a massic activity (9.037±0.22) kBq g⁻¹ as of the reference time 1200 EST, 15 June 2006. All of the uncertainties cited above correspond to standard uncertainties multiplied by a coverage factor k=2. The standardization for the ²¹⁰Pb content of the solution was based on 4πβ liquid scintillation (LS) measurements using CIEMAT/NIST ³H-standard efficiency tracing (CNET). Confirmatory determinations were also performed by high-resolution HPGe γ-ray spectrometry, by 2π spectrometry with a Si surface barrier detector of separated ²¹⁰Po, and by 4πβ(LS)–γ(NaI) anticoincidence counting.     

A Web-Based Tool for Finding Optimal Designs for the Michaelis–Menten Model and an Overview

The Michaelis-Menten model has and continues to be one of the most widely used models in many diverse fields. In the biomedical sciences, the model continues to be ubiquitous in biochemistry, enzyme kinetics studies, nutrition science, and in the pharmaceutical sciences. Despite its wide-ranging applications across disciplines, design issues for this model are given short shrift. This article focuses on design issues and provides a variety of optimal designs of this model. In addition, we evaluate robustness properties of the optimal designs under a variation in optimality criteria. To facilitate use of optimal design ideas in practice, we design a web site for generating and comparing different types of tailor-made optimal designs and user-supplied designs for the Michaelis-Menten and related models.     

Horizontal equity and efficiency at primary health care facilities in rural Afghanistan: A seemingly unrelated regression approach

Producing services efficiently and equitably are important goals for health systems. Many countries pursue horizontal equity – providing people with the same illnesses equal access to health services – by locating facilities in remote areas. Staff are often paid incentives to work at such facilities. However, there is little evidence on how many fewer people are treated at remote facilities than facilities in more densely settled areas. This research explores if there is an association between the efficiency of health centers in Afghanistan and the remoteness of their location.Survey teams collected data on facility level inputs and outputs at a stratified random sample of 579 health centers in 2005. Quality of care was measured by observing staff interact with patients and determining if staff completed a set of normative patient care tasks. We used seemingly unrelated regression to determine if facilities in remote areas have fewer outpatient visits than other rural facilities. In this analysis, one equation compares the number of outpatient visits to facility inputs, while another compares quality of care to determinants of quality.The results indicate remote facilities have about 13% fewer outpatient visits than non-remote facilities, holding inputs constant. Our analysis suggests that facilities in remote areas are realizing horizontal equity since their clients are receiving comparable quality of care to those at non-remote facilities. However, we find the average labor cost for a visit at a remote facility is $1.44, but only $0.97 at other rural facilities, indicating that a visit in a remote facility would have to be ‘worth’ 1.49 times a visit at a rural facility for there to be no equity – efficiency trade-off. In determining where to build or staff health centers, this loss of efficiency may be offset by progress toward a social policy objective of providing services to disadvantaged rural populations.     

Diagnostic validity as a theoretical concept and as a measurable quantity

The analytical result of a laboratory examination is a scientific fact and has no medical meaning as such. It must be interpreted to become a medical finding. To explain the very complex cognitive procedure of the interpretation a three-level model is used. In an environment of cost containment in health care systems the quality of medical laboratory findings is very important. Analytical results are monitored by quality control procedures. For measuring the performance of medical findings the concept of the ‘validity’ of a laboratory test is used. Validity means the ‘degree of achieving the objective’. Accordingly, a valid laboratory finding is one which correctly answers the question which the physician at the sick-bed directs to the laboratory. Quantitative measures for the validity of interpretation can be developed by an analysis of the underlying classification processes. Characteristic indices describing the validity quantitatively in terms of conditional probabilities can be derived from decision tables. Examples of ‘validity indices’ are diagnostic (or prognostic) ‘sensitive’ and ‘specificity’. These indices are powerful tools for developing strategies for the clinical use of laboratory examinations in diagnosis, prognosis and therapy management. Moreover, validity indices are appropriate output quantities for the estimation of effectiveness and efficiency of a diagnostic or prognostic examination.     

Efficiency transfer in the calibration of a coaxial p-type HpGe detector using the Monte Carlo method

Monte Carlo simulation was applied to the efficiency transfer exercise described in the EUROMET428 project (Appl. Radiat. Isot. 55 (2001) 493), evaluating the peak efficiencies in the energy range 60–2000 keV for a typical coaxial p-type HpGe detector and several types of source configuration: point sources located at various distances from the detector and a cylindrical box containing three matrices. The efficiency values were derived in two ways: (a) by direct calculation taking into account the physical dimensions of the detector provided by the supplier, and (b) by means of relative computation (efficiency transfer) taking also into consideration the known efficiency values for a reference point source. As expected, some significant discrepancies between the calculated and experimental values were found when a direct computation was made using the data provided by the supplier. On the contrary, the results for the peak efficiency derived by relative calculation by means of an efficiency transfer were in good agreement with the experimental values. The deviations found with this last procedure were generally below 5% for all the geometries considered, which is entirely satisfactory for the purposes of routine measurements.