Rapid Clinical Snapshots from the EMR among Pneumonia Patients

描述(由申请人提供)：目前对住院患者的研究主要集中在重症监护病房(ICU)的患者，这些患者已经成为电子病历(EMR)的早期采用者。由于人工提取生理数据，特别是生命体征的高成本，对普通内外科病房患者的研究一直受到限制。鉴于此类数据的缺乏，临床医生缺乏量化工具来衡量不同时间点的医院护理过程，更不用说给定患者在住院过程中的不同时间点可能具有的恶化风险水平。本项目使用住院患者电子病历来提供这样的工具。它侧重于发病率和死亡率极高的特定患者群体：患有社区获得性肺炎(CAP)的住院成年人，他们经历了意外转移到更高级别的护理(例如，从普通内科外科病房转移到ICU)。大约70%的转院发生在医院的前72小时，这些患者的死亡率从10%到40%不等，经严重程度调整后的观察死亡率与预期死亡率高达16%。我们的长期目标是利用住院EMR的力量进行质量监测、质量改进，并确定旨在防止医院内恶化的有效做法和干预措施。为了达到这一目标，我们有两个具体目标：(1)采用病例队列方法，我们将开发适合嵌入EMR的模型，以预测最初未进入ICU的慢性阻塞性肺病患者在入院72小时内发生危重疾病的情况。使用20家北加州Kaiser Permanente医院的综合住院和门诊EMR数据，我们将确定符合以下标准的大约13,700名住院患者：年龄=18岁，入院诊断为CAP；并且不只是为了缓解或舒适护理而入院。危重疾病的定义是：(A)休克，(B)需要辅助呼吸的呼吸衰竭，和/或(C)心脏骤停。我们将使用大约8,800名患者的住院记录(我们估计其中485人，或5.5%将在72小时内发展为危重疾病)来开发预测模型，并在大约4,900名患者记录上验证它们(其中270人在72小时内发展为危重疾病)。(2)使用特定目标1的结果，我们将生成时间限定的CAP患者的特征快照，这些患者发生了危重疾病，而没有发展为危重疾病。“快照”将描述CAP患者入院时以及入院后12、24和48小时的特征：(A)他们的人口统计、临床和生理特征(包括生命体征、实验室检查结果和病情严重程度评分)；(B)护理的关键过程，例如是否以及何时进行特定测试(例如，胸片、脉搏血氧仪、乳酸)和干预措施(例如，补充氧气、全身抗生素治疗、静脉滴注液体)；以及(C)他们的住院结果，包括病情恶化、死亡、住院时间(LOS)和幸存者的出院处置。

DESCRIPTION (PROVIDED BY APPLICANT): Current research on hospitalized patients has focused on patients in intensive care units (ICUs), which have been early adopters of electronic medical records (EMRs). Research on general medical-surgical ward patients has been limited due to the high cost of manual abstraction of physiologic data, particularly vital signs. Given the paucity of such data, clinicians lack quantitative tools to gauge the process of hospital care at different points in time, let alone the level of risk of deterioration a given patient may have at different points in the course of a hospital stay. This project employs the inpatient EMR to provide such tools. It focuses on a specific patient population that has extremely high morbidity and mortality: hospitalized adults with community-acquired pneumonia (CAP) who experience an unplanned transfer to a higher level of care (e.g., from a general medical surgical ward to the ICU). Approximately 70% of these transfers occur in the first 72 hours in the hospital, and death rates among these patients range from 10 to 40%, with severity-adjusted observed to expected mortality ratios as high as 16. Our long term goal is to harness the power of the inpatient EMR for quality monitoring, quality improvement, and the identification of effective practices and interventions designed to prevent in-hospital deterioration. To achieve this goal, we have two specific aims: (1) Using a case-cohort methodology, we will develop models, suitable for embedding in the EMR, to predict the occurrence of critical illness within 72 hours of hospital admission among CAP patients who were not initially admitted to the ICU. Using comprehensive inpatient and outpatient EMR data from 20 Northern California Kaiser Permanente hospitals, we will identify a cohort of approximately 13,700 hospitalized patients meeting the following criteria: age =18 years, admission diagnosis of CAP; and not admitted only for palliative or comfort care. Critical illness is defined as (a) shock, (b) respiratory failure requiring assisted ventilation, and/or (c) cardiac arrest. We will develop predictive models using approximately 8,800 patient hospitalization records (of which we estimate 485, or 5.5%, will develop critical illness within 72 hours) and validate them on approximately 4,900 patient records (with 270 developing critical illness within 72 hours). (2) Using the results of Specific Aim 1, we will generate time-delimited "snapshots" of the characteristics of CAP patients who did and who did not develop critical illness. The "snapshots" will characterize CAP patients on admission and at 12, 24, and 48 hours into their hospital stay with respect to (a) their demographic, clinical, and physiologic characteristics (including vital signs, laboratory test results, and severity of illness scores); (b) key processes of care, such as whether and when specific tests (e.g., chest roentgenograms, pulse oximetry, lactates) and interventions (e.g., provision of supplemental oxygen, treatment with systemic antibiotics, intravenous fluid boluses) were performed; and (c) their hospital outcomes, including deterioration, death, length of stay (LOS), and discharge disposition for survivors.