How we are different from other HCIT tools

Based on client data

** Indications for Use: DECISIO’s InsightIQ (DECISIO Health Patient Dashboard) is a decision support device indicated for aggregating, displaying, and managing physiologic and other patient information. This information is generated by third party medical devices and patient information systems. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities.

47%    Morgan CK, et.al. Continuous Cloud-Based Early Warning Score Surveillance to Improve the Safety of Acutely Ill Hospitalized Patients; J Healthc Qual. 2021

4.7 Days  Based on actual client data

** Indications for Use: DECISIO’s InsightIQ (DECISIO Health Patient Dashboard) is a decision support device indicated for aggregating, displaying, and managing physiologic and other patient information. This information is generated by third party medical devices and patient information systems. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities.

13%       https://pubmed.ncbi.nlm.nih.gov/28697109/

11%        https://www.cmqcc.org/resources-tool-kits/toolkits/ob-hemorrhage-toolkit

1 in 7      https://www.cdc.gov/media/releases/2022/p0428-pregnancy-hypertension.html

21%        https://www.medpagetoday.com/meetingcoverage/acog/98676

** Indications for Use: DECISIO’s InsightIQ (DECISIO Health Patient Dashboard) is a decision support device indicated for aggregating, displaying, and managing physiologic and other patient information. This information is generated by third party medical devices and patient information systems. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities.

Client Published Papers:

P1.  Morgan CK et.al. Continuous Cloud-Based Early Warning Score Surveillance to Improve the Safety of Acutely Ill Hospitalized Patients; J Healthc Qual. 2021.

P2.  Howard C, et. al. Implementation of automated early warning decision support to detect acute decompensation in the emergency department improves hospital mortality. BMJ Open Qual. 2022.

P3.  Jung AD, et al. Sooner is better: use of a real-time automated bedside dashboard improves sepsis care. Journal of Surgical Research. 2018.

Client Published Abstracts:

A1.  Computerized Clinical Decision Support System Improves Door-To-Needle Time for Acute Ischemic Stroke.

A2.  Howard C et. al. Improving Compliance with Low Tidal Volume/Lung Protective Ventilation with Utilization of a Real-Time, Bedside Surveillance and Early Warning Decision Support System; Abstract CHEST. San Antonio, TX 2018.

A3.  Baker J et.al. Acute Kidney Injury Reduction after Implementation of an ICU Visual Clinical Decision Support Tool. Poster American Surgical Association; Napa Valley, CA 2018.

Other Sources:

1.  Jones D et. al. U of Melbourne, ISRRS. 2019

2. Brown A et. al. Recognition of the critically ill patient and escalation of therapy. Anesthesia & Intensive Care Medicine 2019.

3. AHA, ACLS Provider Handbook, 2015

5. Shafi S, et. al. Compliance with Recommended Care at Trauma Centers: Association with Patient Outcomes. J Am Coll Surg 2014.

6. Duclos G, et. al. Implementation of an electronic checklist in the ICU: Association with improved outcomes. Anaesth Crit Care Pain Med 2018.

15. Modern Healthcare, Sepsis treatment costs shoot up $1.5 billion for hospitals over three years, March 2019

17. Key 2008 CMQCC Hemorrhage Task Force Survey Findings

18. Creanga A A, Syverson C, Seed K, Callaghan W M. Pregnancy-related mortality in the United States, 2011-2013. Obstet Gynecol. 2017;130(02):366–373

**Indications for Use: DECISIO’s InsightIQ (DECISIO Health Patient Dashboard) is a decision support device indicated for aggregating, displaying, and managing physiologic and other patient information. This information is generated by third party medical devices and patient information systems. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities.

<51%      Bellaini G, et. al. Epidemiology, patterns of care, and mortality for patients with Acute Respiratory Distress Syndrome in Intensive Care Units in 50 countries. JAMA Feb 2016

20-30%   Uchino S. The epidemiology of acute renal failure in the world. Curr Opin Crit Care. 2006

12%         Seymour CW, Gesten F, Prescott HC, Friedrich ME, Iwashyna TJ, Phillips GS, et al. Time to treatment and mortality during mandated emergency Care for Sepsis. N Engl J Med. 2017;376(23):2235–44.

** Indications for Use: DECISIO’s InsightIQ (DECISIO Health Patient Dashboard) is a decision support device indicated for aggregating, displaying, and managing physiologic and other patient information. This information is generated by third party medical devices and patient information systems. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities.

The Decisio Health Patient Dashboard (Decisio Insight) is a decision support device indicated for aggregating, displaying, and managing physiologic and other patient information. This information is generated by third party medical devices and patient information systems. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities. The Decisio Health Patient Dashboard (Decisio Insight) is intended for use by clinicians in healthcare facilities.

The Decisio Health Patient Dashboard (“Patient Dashboard”) is a data aggregation and visualization software device. The Patient Dashboard is designed to display patient information, facility specific care protocols, and visual cues to care providers on a single display device. The Patient Dashboard is configured to receive patient data through the facility’s Electronic Medical Record system and display information to the user on a patient monitor, computer, or a mobile device. Data received through the EMR includes input from various sources within the hospital, including manually entered data into the EMR (e.g., laboratory data), vital signs monitors, ventilators, IV pumps, and Foley catheter devices. The data the Patient Dashboard receives are then stored, filtered, and displayed through the Patient Dashboard web browser application. The Patient Dashboard is customized to individual facility’s care as it is programmed with the facility’s treatment protocols, which dictate the information that is displayed relative to those protocols. The device performs automated calculations on patient data collected by third party devices based on approved clinical protocols at patient care facilities.