Healthcare organizations are learning many lessons during the COVID-19 crisis. Whether still in thick of it or coming up for air, data and technology are key tools in the fight against this pandemic. Data and analytics help with capacity planning, modeling PPE needs, and testing protocols. With new efforts to move employees to remote work, staff needs access to business and clinical applications. Working apart requires new workflows and productivity tools. In light of this, healthcare systems moved to telehealth faster than previously thought possible. With changes in telehealth reimbursement, increased provider and patient demand, and loosening of privacy and security restrictions, many healthcare systems are now all-in to continue offering telehealth as the country slowly opens back up.
Many healthcare systems had to adapt quickly and add new technology capabilities to keep up with these massive COVID-19 systemic changes. Some of the IT additions will carry forward with adaptation, to create a more robust and secure IT environment. Healthcare systems still have differing amounts of technology work to do to ensure positive and secure changes. The new normal is under construction.
Long-term healthcare IT needs
Long term, healthcare systems will need continued (and new) analytics abilities. That can create electronic health records (EHR) data challenges, in accessing data, sharing abilities, and quality inputs and outputs. We already have the data, but accessing it can be difficult. That access has to be relatively quick, as insights into treating this fast-moving disease are best when they can be applied before patients suffer major or even fatal damage. Clinical guidelines will continue evolving as we collect and analyze the data, to ensure clinicians are making the best treatment decisions, as we’ve seen happen with ventilator recommendations.
Reopening society and moving forward means testing and tracking COVID-19 symptoms and contacts. Available therapeutics are also being tested for effectiveness, while vaccines are being developed and entering human trials faster than at any other time in history. The need for collaboration is also great, with data set sharing, including a public data set program offered by Google.
Long-term healthcare will also rely on monitoring patient flow and intake, whether at hospitals, ambulatory surgery centers or doctors’ offices. Lab capabilities and throughput will enter the analytics mix for modeling, data visualization, and workflow, as both current disease and antibody testing are new categories that promise to be around a long time, at high volumes.
How COVID-19 is changing data assessment
The pandemic is increasing transformative collaboration, requiring conversations and data sharing among healthcare groups typically competitive with each other. This collaboration ensures that clinical guidelines are followed across organizations and at different care levels. This includes nursing homes, which have been an infection hot spot with a vulnerable population. Gathering and using the data in a timely manner to inform decisions across the healthcare spectrum is vital.
Those with existing health disparities are more heavily impacted by COVID-19, resulting in a population health issue. We need to set up processes to collect the needed data and systems to address these populations to ensure those most at risk not only have access to care but are receiving the care itself. This means being more strategic about how to collect, analyze, and use the data. Perfect is the enemy of the good here. The concept of “good enough” data is gaining prominence, rather than waiting for “perfect” data which will only delay results and worsen clinical outcomes.
With COVID-19, we’ve gone from predictable to unpredictable in patient flow and scheduling. The 2019 healthcare system models optimized efficiency, working to perfect the remaining small percentages of efficiency. These models are now moot. The efficient assembly-line approach to patient flow gave way to the need for flexibility and agility. We’re now in an environment of rapid change. Instead of focusing on efficiency and existing processes, we need to step back and determine how to respond. Taking a centralized command control approach, we need to look at categories like regulatory and legal issues, supplies and treatment changes, and understand how to change these actions based on data.
The old school approach is heavy on process. Organizational changes traditionally were made after months of meetings and project planning. That can’t happen now. Like with other disruptive industries, decisions need to happen quickly, but still, be driven by data. Understandably, this approach will make many uncomfortable. Once the data is shown to be valid and trustworthy, people will need to learn to trust the new process, to become more agile in decision-making.
Even before COVID-19, we saw a move toward a data agility approach. Changes are not made based on data alone, but with data as a tool. Data provides the ability to look back and explore answers to our questions.
To learn more about how Maven Wave is working with health systems to create a platform to visualize and analyze COVID-19 data to give front-line healthcare workers a real-time feed of information, stream our on-demand webinar here.
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