INFORMED CLINICIANS. IMPROVED OUTCOMES. HEALTH INFORMATICS IN CRITICAL CARE UNITS

Extracting actionable insights from data to improve care

pdf Health Informatics in Critical Care Units (.pdf)

Quickly converting data to actionable insights is key to effective treatment of critically ill patients. Learn how health informatics can help integrate data from multiple devices and systems and transform that data into clinically meaningful information.

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INFORMED CLINICIANS. IMPROVED OUTCOMES.

Woman in hospital bed being treated by nurse

Health informatics and its role in critical care units

Synopsis: Helping clinicians provide better patient care while managing costs becomes particularly challenging when dealing with critical care patients, who require continuous, intensive monitoring. Typically, in the ICU or recovery unit of a hospital, these patients require teams of clinicians to track and treat complex conditions. From patients on invasive mechanical ventilation, to those at risk of unrecognized deterioration, optimal care involves ongoing monitoring and coordinated, timely clinical decisions.


EFFICIENCY CHALLENGES INCREASE RISK AMONG CRITICAL CARE PATIENTS

“When it comes to high-risk patients, our goal is to help clinicians detect, diagnose, and treat early, so as to avoid preventable complications,” explains Medtronic Vice President of Health Informatics, Julia Strandberg. “Today, hospital systems are challenged with individually monitoring these patients in real time to catch early warning signs,” she says.

A recent survey indicated that despite well-intentioned investment in staffing, issues remain. Of the physicians surveyed, nearly 90% reported spending less than 60% of their time on direct patient care.1

In the ICU and recovery unit, that challenge could mean the difference between complication-free care and recovery and adverse, costly outcomes.


PREVENTING THE PREVENTABLE

At Medtronic, we believe data and analytics play a key role in preventing the preventable and facilitating early detection and treatment of critically ill patients. And while the amount of data available to clinicians continues to expand, data alone is not enough. Providing clinicians with the right information, for the right patient, at the right time, is paramount in critical care settings.

Artificial intelligence (AI), advanced algorithms, and predictive analytics, Strandberg explains, can all be used to aggregate discrete data into actionable insights for clinicians. “With today’s technology, we are able to take huge amounts of data — from EHRs, monitoring systems, and therapies — and integrate it into dashboards, alerts, or other reporting mechanisms that aid in making timely clinical decisions,” she says.

And those decisions can have a significant impact on patient outcomes and costs. For mechanically ventilated patients in the ICU, for example, providing clinicians with continuous monitoring and protocol-driven weaning tools can help get a patient off a ventilator more than a day earlier and reduce a patient’s length of stay in the ICU by up to 11%.4

    

Health Informatics Infographic

IT SOLUTIONS FOR COORDINATED CARE

Medtronic offers a portfolio of health informatics and monitoring solutions for hospitals. They are designed to help clinicians collaborate on patient care and work at optimal efficiency. The software platform and clinician decision support tools have been designed to help reduce never events,5 the length of ICU stays, and code blues.6

MEDTRONIC MONITORING AND CLINICAL DECISION SUPPORT TOOLS:
HOW THEY WORK

medtronic-monitoring-and-clinical-decision-support-tools
  1. Data from multiple devices and systems is integrated and transmitted to a clinician's hospital server.
  2. Here, it is transformed to provide near-real-time, clinically meaningful information.
  3. Available where, and when, a clinical needs it — on virtually any device.

COLLABORATING ON THE FUTURE OF HEALTHCARE

The role of data in improving patient outcomes and system efficiencies is widely recognized by IT experts. Implementing tools and solutions that leverage that data to its fullest potential, however, is a journey.

“Dedicated time and resources are required to create a true data science platform,” says Dr. John Chelico, vice president, chief informatics & innovation officer, Northwell Health. “As a healthcare IT leader, you have to paint a picture of what the future will look like to influence stakeholders about the benefits.”

Medtronic strives to be an active partner in the transformation, leveraging its device technology and value-based healthcare (VBHC) offerings. Other elements of strong collaboration in data and analytics, as Strandberg explains, include:

  • A shared vision
  • Focused teams with vast capabilities and competencies
  • A commitment to quality, process, and structure

Through the Medtronic Hospital IT Advisory Board, CIOs and CTOs are joined by Medtronic experts to discuss challenges, share opportunities, and explore potential solutions that could deliver short- and long-term benefits to clinicians and patients alike. Together, they are unlocking the potential of what data can do for the future of healthcare — in critical care settings, and beyond.


1

Paperwork Versus Patient Care: A Nationwide Survey of Residents’ Perceptions of Clinical Documentation Requirements and Patient Care. Christino MA, Matson AP, Fischer SA, Reinert SE, DiGiovanni CW, Fadale PD. J Grad Med Educ. 2013 Dec; 5(4): 600–604. doi: 10.4300/JGME-D-12-00377.1 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886458/

2

Healthcare Cost and Utilization Project (HCUP). National Inpatient Sample Database. 2014: Internal Analysis.

3

Torio CM, Andrews RM. National Inpatient Hospital Costs: The Most Expensive Conditions by Payer, 2013. https://www.hcup-us.ahrq.gov/reports/statbriefs/sb204-Most-Expensive-Hospital-Conditions.pdf Accessed on September 9, 2018.

4

Blackwood B, Burns KE, Cardwell CR, O’Halloran P. Protocolized versus non-protocolized weaning for reducing the duration of mechanical ventilation in critically ill adult patients. Cochrane Database Syst Rev. 2014(11):CD006904.

5

Slight SP, Franz C, Olugbile M, Brown HV, Bates DW, Zimlichman E. The return on investment of implementing a continuous monitoring system in general medical-surgical units. Crit Care Med. 2014;42(8):1862-8.

6

Brown H, Terrence J, Vasquez P, Bates DW, Zimlichman E. Continuous monitoring in an inpatient medical-surgical unit: a controlled clinical trial. Am J Med. 2014;127(3):226-32.