The OBSERVATION_PERIOD table contains records which uniquely define the spans of time for which a Person is at-risk to have clinical events recorded within the source systems, even if no events in fact are recorded (healthy patient with no healthcare interactions)
OBSERVATION_PERIOD表里记录的内容，是定义数据源中居民所涉及到的临床事件的时间段（去重），即使居民事实上没有任何临床事件记录（无医保核保记录的健康居民）
| Field | Required | Type | Description |
|---|---|---|---|
| observation_period_id | Yes | integer | A unique identifier for each observation period. |
| 观察期-时段-ID | 每个观察期的唯一标识符。 | ||
| person_id | Yes | integer | A foreign key identifier to the person for whom the observation period is defined. The demographic details of that person are stored in the person table. |
| 居民-ID | 外键，指向该观察期对象（居民）的标识符。而该居民的人口统计学信息存储在person表中。 | ||
| observation_period_start_date | Yes | date | The start date of the observation period for which data are available from the data source. |
| 观察-期间-开始-日期 | 某数据可从数据源获得的最早日期，即为观察期的开始日期。 | ||
| observation_period_end_date | Yes | date | The end date of the observation period for which data are available from the data source. |
| 观察-期间-结束-日期 | 某数据可从数据源获得的最晚日期，即为观察期的开始日期。 | ||
| period_type_concept_id | Yes | Integer | A foreign key identifier to the predefined concept in the Standardized Vocabularies reflecting the source of the observation period information, belonging to the 'Obs Period Type' vocabulary |
| 观察期-类型-概念-ID | 外键，标准词汇表中预置概念的标识符，反映观察期信息的来源，属于“Obs Period Type”词汇表 |
共识
| No. | Convention Description | 共识 |
|---|---|---|
| 1 | Each Person has to have at least one observation period. | 每个居民必须至少有一个观察期。 |
| 2 | One Person may have one or more disjoint observation periods, during which times analyses may assume that clinical events would be captured if observed | 在一个人群定义查询中，可能存在一个居民在查询条件中有一个或多个间断的观察期 |
| 3 | Each Person can have more than one valid OBSERVATION_PERIOD record, but no two observation periods can overlap in time for a given person. | 每个居民可以有多个有效的OBSERVATION_PERIOD记录，但没有两个观察期可以在时间上重叠。 |
| 4 | As a general assumption, during an Observation Period any clinical event that happens to the patient is expected to be recorded. Conversely, the absence of data indicates that no clinical events occurred to the patient. | 作为一般假设，在观察期间，发生在居民身上的任何临床事件都会被记录。相反，如果某临床事件未被记录，表明该居民没有发生该临床事件。 |
| 5 | Both the _START_DATE and the _END_DATE of the clinical event has to be between observation_period_start_date and observation_period_end_date. | 临床事件的_START_DATE和_END_DATE都必须在observation_period_start_date和observation_period_end_date之间。 |
| 6 | Events CAN fall outside of an observation period and payer plan period should be used to capture coverage, such as Medicare Part D, which can overlap an observation period. However, time outside of an observation period cannot be used to identify people. To ensure quality, events outside of an observation period should not be used for analysis. THEMIS issue #23 | 临床事件可能不在观察期内，则可涵盖至保险计划时间范围内，例如Medicare Part D（也称为Medicare处方药福利，是一项可选的美国联邦政府计划，旨在帮助Medicare受益人通过处方药保险费支付自我管理的处方药），这可能会与观察期重叠。但为确保研究质量，不能通过观察期之外的事件去抓取居民数据，也不能用于分析。 |
| 7 | For claims data, observation periods are inferred from the enrollment periods to a health benefit plan. | 对于索赔数据，应从登记期间到健康福利计划的期间来推断观察期。 |
| 8 | For EHR data, the observation period cannot be determined explicitly, because patients usually do not announce their departure from a certain healthcare provider. The ETL will have to apply some heuristic to make a reasonable guess on what the observation_period should be. Refer to the ETL documentation for details. | 对于EHR数据，无法明确确定观察期，因为居民通常不会宣布他们什么时候离开具体哪个医疗机构。所以ETL的时候必须应用一些启发式思维方法来合理的猜测Observation_period应该是多少。有关详细信息，请参阅ETL文档。 |
本系列在介绍目前世界上最适用于临床科研+卫生经济学的标准医疗大数据格式（未经严谨考证，但有相关研究发表在专业期刊上），俨然是真实世界研究方案里面最接进成熟的基础建设方案。感兴趣的介绍请移步B站观看视频。
OHDSI——观察性健康医疗数据科学与信息学，是一个世界性的公益型非盈利研究联盟，主要研究全方位医学大数据分析的开源解决方案，旨在通过大规模数据分析和挖掘来提升临床医学数据价值，实现跨学科、跨行业的多方合作。目前，目前，已有来自美国、加拿大、澳大利亚、英国等几十个国家地区的上百个组织机构，高校，医院和公司企业参与了OHDSI全球协作网络，如斯坦福、哈佛、杜克大学医学院，强生、诺华、甲骨文、IBM公司，拥有超过6亿人口的临床数据规模，累计协作研究发表了上百篇论文。
我们在这里邀请国内对相关工作感兴趣、愿共同学习的好学人士参与到中文兴趣小组，互通有无，一起弥补跨行业、跨学科的知识积累。前期主要以对OHDSI在github上的开源工作进行翻译、交流、学习为主，并会对医疗大数据、医学统计学、生物信息学等学科知识建立学习互助、互督的机制。有兴趣的请看文档，微信群二维码在内：OHDSI中文兴趣小组共识&OHDSI介绍
OHDSI秉持开源、开放的宗旨，加快全球医学数据研究的步伐，本文内容原创来自Github（https://github.com/OHDSI/CommonDataModel/wiki），若有利益冲突，请在本页面留言，真-侵删。
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