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表里記錄的內(nèi)容，是定義數(shù)據(jù)源中居民所涉及到的臨床事件的時(shí)間段（去重），即使居民事實(shí)上沒有任何臨床事件記錄（無醫(yī)保核保記錄的健康居民）
| Field | Required | Type | Description |
|---|---|---|---|
| observation_period_id | Yes | integer | A unique identifier for each observation period. |
| 觀察期-時(shí)段-ID | 每個(gè)觀察期的唯一標(biāo)識(shí)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 | 外鍵，指向該觀察期對(duì)象（居民）的標(biāo)識(shí)符。而該居民的人口統(tǒng)計(jì)學(xué)信息存儲(chǔ)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. |
| 觀察-期間-開始-日期 | 某數(shù)據(jù)可從數(shù)據(jù)源獲得的最早日期，即為觀察期的開始日期。 | ||
| observation_period_end_date | Yes | date | The end date of the observation period for which data are available from the data source. |
| 觀察-期間-結(jié)束-日期 | 某數(shù)據(jù)可從數(shù)據(jù)源獲得的最晚日期，即為觀察期的開始日期。 | ||
| 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 |
| 觀察期-類型-概念-ID | 外鍵，標(biāo)準(zhǔn)詞匯表中預(yù)置概念的標(biāo)識(shí)符，反映觀察期信息的來源，屬于“Obs Period Type”詞匯表 |
共識(shí)
| No. | Convention Description | 共識(shí) |
|---|---|---|
| 1 | Each Person has to have at least one observation period. | 每個(gè)居民必須至少有一個(gè)觀察期。 |
| 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 | 在一個(gè)人群定義查詢中，可能存在一個(gè)居民在查詢條件中有一個(gè)或多個(gè)間斷的觀察期 |
| 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. | 每個(gè)居民可以有多個(gè)有效的OBSERVATION_PERIOD記錄，但沒有兩個(gè)觀察期可以在時(shí)間上重疊。 |
| 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. | 作為一般假設(shè)，在觀察期間，發(fā)生在居民身上的任何臨床事件都會(huì)被記錄。相反，如果某臨床事件未被記錄，表明該居民沒有發(fā)生該臨床事件。 |
| 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. | 臨床事件的_START_DATE和_END_DATE都必須在observation_period_start_date和observation_period_end_date之間。 |
| 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 | 臨床事件可能不在觀察期內(nèi)，則可涵蓋至保險(xiǎn)計(jì)劃時(shí)間范圍內(nèi)，例如Medicare Part D（也稱為Medicare處方藥福利，是一項(xiàng)可選的美國(guó)聯(lián)邦政府計(jì)劃，旨在幫助Medicare受益人通過處方藥保險(xiǎn)費(fèi)支付自我管理的處方藥），這可能會(huì)與觀察期重疊。但為確保研究質(zhì)量，不能通過觀察期之外的事件去抓取居民數(shù)據(jù)，也不能用于分析。 |
| 7 | For claims data, observation periods are inferred from the enrollment periods to a health benefit plan. | 對(duì)于索賠數(shù)據(jù)，應(yīng)從登記期間到健康福利計(jì)劃的期間來推斷觀察期。 |
| 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. | 對(duì)于EHR數(shù)據(jù)，無法明確確定觀察期，因?yàn)榫用裢ǔ２粫?huì)宣布他們什么時(shí)候離開具體哪個(gè)醫(yī)療機(jī)構(gòu)。所以ETL的時(shí)候必須應(yīng)用一些啟發(fā)式思維方法來合理的猜測(cè)Observation_period應(yīng)該是多少。有關(guān)詳細(xì)信息，請(qǐng)參閱ETL文檔。 |
本系列在介紹目前世界上最適用于臨床科研+衛(wèi)生經(jīng)濟(jì)學(xué)的標(biāo)準(zhǔn)醫(yī)療大數(shù)據(jù)格式（未經(jīng)嚴(yán)謹(jǐn)考證，但有相關(guān)研究發(fā)表在專業(yè)期刊上），儼然是真實(shí)世界研究方案里面最接進(jìn)成熟的基礎(chǔ)建設(shè)方案。感興趣的介紹請(qǐng)移步B站觀看視頻。
OHDSI——觀察性健康醫(yī)療數(shù)據(jù)科學(xué)與信息學(xué)，是一個(gè)世界性的公益型非盈利研究聯(lián)盟，主要研究全方位醫(yī)學(xué)大數(shù)據(jù)分析的開源解決方案，旨在通過大規(guī)模數(shù)據(jù)分析和挖掘來提升臨床醫(yī)學(xué)數(shù)據(jù)價(jià)值，實(shí)現(xiàn)跨學(xué)科、跨行業(yè)的多方合作。目前，目前，已有來自美國(guó)、加拿大、澳大利亞、英國(guó)等幾十個(gè)國(guó)家地區(qū)的上百個(gè)組織機(jī)構(gòu)，高校，醫(yī)院和公司企業(yè)參與了OHDSI全球協(xié)作網(wǎng)絡(luò)，如斯坦福、哈佛、杜克大學(xué)醫(yī)學(xué)院，強(qiáng)生、諾華、甲骨文、IBM公司，擁有超過6億人口的臨床數(shù)據(jù)規(guī)模，累計(jì)協(xié)作研究發(fā)表了上百篇論文。
我們?cè)谶@里邀請(qǐng)國(guó)內(nèi)對(duì)相關(guān)工作感興趣、愿共同學(xué)習(xí)的好學(xué)人士參與到中文興趣小組，互通有無，一起彌補(bǔ)跨行業(yè)、跨學(xué)科的知識(shí)積累。前期主要以對(duì)OHDSI在github上的開源工作進(jìn)行翻譯、交流、學(xué)習(xí)為主，并會(huì)對(duì)醫(yī)療大數(shù)據(jù)、醫(yī)學(xué)統(tǒng)計(jì)學(xué)、生物信息學(xué)等學(xué)科知識(shí)建立學(xué)習(xí)互助、互督的機(jī)制。有興趣的請(qǐng)看文檔，微信群二維碼在內(nèi)：OHDSI中文興趣小組共識(shí)&OHDSI介紹
OHDSI秉持開源、開放的宗旨，加快全球醫(yī)學(xué)數(shù)據(jù)研究的步伐，本文內(nèi)容原創(chuàng)來自Github（https://github.com/OHDSI/CommonDataModel/wiki），若有利益沖突，請(qǐng)?jiān)诒卷撁媪粞裕?侵刪。
