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临床试验/NCT04606849
NCT04606849招募中不适用

Adaptation and Pilot Implementation of a Validated, Electronic Real-Time Clinical Decision Support Tool for Care of Pneumonia Patients in 10 Utah Urgent Care Centers

Intermountain Health Care, Inc.24 个研究点 分布在 1 个国家目标入组 4,000 人开始时间: 2020年11月12日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
4,000
试验地点
24
主要终点
ePNa utilization and impact on the UCC clinical environment

研究概览

简要总结

We plan to adapt an innovative, validated emergency department (ED) CDS tool based on consensus guidelines for pneumonia care (ePNa) to function in urgent care clinics (Instacares at Intermountain) and combine it seamlessly with Stanford's CheXED artificial intelligence model using an interoperable platform currently under development by Care Transformation Information Services at Intermountain. We will then deploy it to one of two groups of Instacares (randomly selected) using the CFIR framework for Implementation Science best practice.

详细描述

Clinicians' ability to accurately diagnose pneumonia and then choose the most appropriate treatment options is enhanced by well-designed clinical decision support (CDS). Pneumonia CDS has historically been focused on inpatient settings, but ambulatory care settings with high pneumonia patient volumes also might benefit. The investigators propose to adapt an innovative, validated emergency department (ED) CDS tool based on consensus guidelines for pneumonia care (ePNa) and deploy it to urgent care centers (UCC) using the CFIR framework. Electronic tools such as ePNa may become even more useful within UCCs as the COVID-19 pandemic evolves, since recommendations can be readily updated as better methods of diagnosis and effective treatment develop. ePNa within the ED has already been adapted to recommend SARS-coV-2 testing for patients with pneumonia and signs and symptoms characteristic of viral pneumonia.

The proposal supports four aims:

  1. Adapt ePNa for UCC and after in silico testing, pilot it among "super user" clinicians during UCC shifts and assess its usability. ePNa needs adaptation for more limited patient data available in UCCs, calibration of severity measures for lower observed mortality, and a chest imaging prompt in patients with pneumonia signs and symptoms. ePNa for UCC will incorporate Stanford University's artificial intelligence CheXED model to provide electronic classification of chest images in <10 seconds for elements of pneumonia diagnosis and treatment (radiographic pneumonia, single vs multiple lobes, and pleural effusion).
  2. Using the CFIR framework, our prior ED implementation experience, a focus group of UCC clinicians, semi-structured interviews, and direct observations of workflow including ePNa guided transitions of care between clinicians, the investigators will identify barriers and facilitators to adaptation and implementation of ePNa to UCCs.
  3. Test the implementation strategy by deploying ePNa at one of two randomly chosen Intermountain Healthcare UCC clusters each with about 800 annual pneumonia patients - the other a usual care control.
  4. Co-primary outcomes are a) accuracy of pneumonia diagnosis defined by compatible chief complaint plus ≥ 1 pneumonia sign/symptom and radiographic confirmation will be ≥10% higher in the ePNa cluster, and b) the percent of UCC pneumonia patients transferred to an emergency department for further evaluation will decrease by ≥ 3% in the ePNa cluster replaced by more direct hospital admissions or discharge home. Safety measures will be unplanned subsequent 7-day ED visits/hospitalizations and 30-day mortality. Based on this rigorous pilot study, the investigators anticipate a subsequent multi-system cluster-randomized trial.

Our work incorporates the Five Rights of CDS to ensure that the strengths of this technology are optimized in the clinical environment. The investigators will leverage experience in innovative pneumonia research, pioneering CDS, and implementation science available at Intermountain to successfully complete this proposal.

研究设计

研究类型
Interventional
分配方式
Non Randomized
干预模型
Parallel
主要目的
Health Services Research
盲法
Single (Outcomes Assessor)

入排标准

年龄范围
12 Years 至 —(Child, Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • All patients ≥ 12 years of age with pneumonia: defined by the J-18.X pneumonia code or acute respiratory failure or sepsis with secondary pneumonia codes
  • Survey All physicians and advanced practice clinicians who are employed and actively seeing patients in the 4 Utah Valley Instacares

排除标准

  • Patients without radiographic confirmation of pneumonia
  • Subsequent episodes of pneumonia within 12 months (so as not to over-represent patients with recurrent pneumonia caused by recurrent aspiration or structural lung disease).
  • Survey No providers will be excluded from the survey invitation

结局指标

主要结局

ePNa utilization and impact on the UCC clinical environment

时间窗: through study completion, year 3 of the study

Frequency of clinicians' disagreement with different ePNa recommendations will be monitored along with a tally of the structured reasons for disagreement entered by clinicians into ePNa.

次要结局

  • Number of unplanned subsequent ED Visits(within 7 days of initial encounter)
  • Number of unplanned hospitalizations(within 7 days of initial encounter)
  • Accuracy of pneumonia diagnosis given(through study completion, year 3 of the study)
  • The change in the transfer rate of UCC pneumonia patients to an ED(through study completion, year 3 of the study)
  • Use of fewer health care resources(through study completion, year 3 of the study)

研究者

申办方类型
Other
责任方
Sponsor

研究点 (24)

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