Schlaud M, Brenner M H, Hoopmann M, Schwartz F W
Department of Epidemiology and Social Medicine, Hannover Medical School, Germany.
J Epidemiol Community Health. 1998 Apr;52 Suppl 1:13S-19S.
An accurate knowledge of the population at risk is a fundamental requirement for determining rates and making comparisons in epidemiological research. The major obstacle of studying the epidemiology of sentinel practice networks is the determination of population at risk, in this case, the reference population of medical practices. This article is intended to give a brief overview of major denominator approaches used in practice based epidemiology today, to discuss their underlying assumptions, their strengths and limitations.
The literature used in this paper was searched from Medline databases of 1970-1997 using the logical expression "denominator and practice". More literature was identified from the references cited in those articles and from research reports that were available to the authors.
There are various approaches to the denominator at different levels of complexity, which were presented akin to the well known "iceberg phenomenon": with only a small portion of the iceberg visible above the surface, inference as to the size of the invisible part may still be made under certain assumptions. Crude numbers of cases may still reflect trends in the true epidemiology of disease and may be useful for time-series analyses. Differences in the number of network participants over time and across region may be controlled for by using the number of sentinel practices as a denominator. The number of consultations is a first step towards a population-based denominator, reflecting characteristics of both patients and the network. The yearly or quarterly contact group is a true person-based denominator, yet disregarding the population not consulting. The population in practices' catchment areas can be either determined from patient lists or estimated using mathematical models. The ideal denominator is the total population in a geographically defined area, though this information can be directly related to medical practices only in very few countries.
Although a person, or ideally a population-based denominator is desirable, even "lower-level" denominators may be suitable for certain research topics. In countries without patient registration, the estimation of incidences and prevalences has many methodological uncertainties that limit the use of sentinel practice systems. Assuming representativeness, valid analytical or time-series studies, however, can still be carried out even if there is very little information on the population at risk covered by particular medical practices.
准确了解高危人群是流行病学研究中确定发病率和进行比较的基本要求。研究哨点执业网络流行病学的主要障碍是确定高危人群，在这种情况下，即医疗执业的参考人群。本文旨在简要概述当今基于实践的流行病学中使用的主要分母方法，讨论其潜在假设、优点和局限性。
本文使用的文献是通过使用逻辑表达式“分母和实践”从1970 - 1997年的Medline数据库中检索的。从这些文章引用的参考文献以及作者可获得的研究报告中识别出了更多文献。
分母有不同复杂程度的各种方法，这些方法类似于著名的“冰山现象”呈现：冰山只有一小部分露出水面，在某些假设下仍可推断不可见部分的大小。病例的粗略数字可能仍能反映疾病真实流行病学的趋势，并且可能对时间序列分析有用。通过使用哨点执业数量作为分母，可以控制网络参与者数量随时间和地区的差异。会诊次数是迈向基于人群的分母的第一步，反映了患者和网络的特征。年度或季度接触组是真正基于人的分母，但忽略了未就诊的人群。执业覆盖区域内的人口可以从患者名单中确定，也可以使用数学模型进行估计。理想的分母是地理定义区域内的总人口，不过只有在极少数国家，此信息才能直接与医疗执业相关。
尽管理想情况下希望使用基于个人或人群的分母，但即使是“较低层次”的分母也可能适用于某些研究主题。在没有患者登记的国家，发病率和患病率的估计存在许多方法上的不确定性，这限制了哨点执业系统的使用。然而，即使关于特定医疗执业所覆盖的高危人群的信息很少，假设具有代表性，仍然可以进行有效的分析性或时间序列研究。
