Rapid Clinical Snapshots from the EMR among Pneumonia Patients

肺炎患者 EMR 的快速临床快照

• 批准号: 8111670
• 负责人: GABRIEL J. ESCOBAR
• 金额: $ 49.11万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8111670
• 关键词: Rapid; Clinical; Snapshots; EMR; among

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.

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，这些患者是电子病历 (EMR) 的早期采用者。由于手动提取生理数据（尤其是生命体征）的成本高昂，对普通内外科病房患者的研究受到限制。鉴于此类数据的缺乏，临床医生缺乏定量工具来衡量不同时间点的医院护理过程，更不用说特定患者在住院期间的不同时间点可能出现的病情恶化风险水平。该项目利用住院电子病历来提供此类工具。它重点关注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) 的住院成人，他们经历了计划外转移到更高级别的护理（例如，从普通内外科病房转移到 ICU）。这些转运中大约 70% 发生在入院后的前 72 小时内，这些患者的死亡率在 10% 到 40% 之间，观察到的严重程度调整后的预期死亡率高达 16。我们的长期目标是利用住院患者电子病历在质量监测、质量改进以及确定旨在防止院内病情恶化的有效实践和干预措施方面的力量。为了实现这一目标，我们有两个具体目标：（1）使用病例队列方法，我们将开发适合嵌入 EMR 的模型，以预测以下 CAP 患者入院 72 小时内危重疾病的发生情况：最初并未入住 ICU。利用来自北加州 20 家 Kaiser Permanente 医院的综合住院和门诊 EMR 数据，我们将确定大约 13,700 名住院患者组成的队列，满足以下标准：年龄 = 18 岁，入院诊断为 CAP；且不得仅因姑息或舒适护理而入院。危重症定义为 (a) 休克、(b) 需要辅助通气的呼吸衰竭和/或 (c) 心脏骤停。我们将使用大约 8,800 份患者住院记录（我们估计其中 485 份或 5.5% 将在 72 小时内患上危重病）开发预测模型，并在大约 4,900 份患者记录（其中 270 名患者在 72 小时内患上危重病）上验证它们。 (2) 利用具体目标 1 的结果，我们将生成发生和未发生危重疾病的 CAP 患者的特征的时间限定“快照”。这些“快照”将描述 CAP 患者入院时以及住院后 12、24 和 48 小时的特征，包括 (a) 他们的人口统计学、临床和生理特征（包括生命体征、实验室检查结果和疾病严重程度）分数）； (b) 护理的关键过程，例如是否以及何时进行特定测试（例如胸部 X 光检查、脉搏血氧饱和度、乳酸）和干预措施（例如提供补充氧气、全身抗生素治疗、静脉推注液体）； (c) 他们的医院结果，包括病情恶化、死亡、住院时间 (LOS) 和幸存者的出院处理。