Part 3 in our five week blog series: The New Normal: Covid-19’s Impact on Population Health Information Technology. What we know to be true about this healthcare space has been reinforced and accelerated. We’ll help you to discern the noise from the NOW.



Introduction

As many organizations found during the first wave of COVID-19 infections (and others are now finding as a second wave begins to take hold), online symptom checkers are only as good as the discipline and accuracy of the patients who are completing them.  While chat bots and text surveys may increase patient adoption of tools to streamline critical healthcare resources during times of infection surge, lack of accuracy continues to impede health systems’ ability to engage the highest risk patients most efficiently.  We can all do better.

Integration with Devices

If you’ve been following along with the blog series, your organization may already be prioritizing risk scores and risk trends as key to its outcome improvement efforts.  Whether done to stem the negative outcomes associated with unchecked chronic illness, widespread infectious disease, and/or racially systemic social determinants of health, no matter.  You have taken a great first step! 

In time, you’ll find development of real-time data integrations with patient devices – think data-impacts to your pivotal risk and trend scoring paradigms – can improve resource efficiency at the margins even more.  In fact, doing so will likely assist in at least 2 of the 3 observed areas for improvement alluded to by a recent major-metropolitan academic medical center, based on their recent COVID-19 monitoring program experiences, detailed here.

Patient Engagement

Technology-forward patients are likely to welcome the integrations that your system can facilitate with their at-home, WiFi-enabled, and/or blue-tooth scales, apple-watches and thermometers.  They probably bought them with improved health in mind! 

In another vein, patients who present to urgent cares and clinics not severe enough for admission but open to at-home monitoring, with a shiny new device and a set of straight-forward setup instructions in hand on discharge, will certainly be more “engaged” than others sent home with portal login instructions and timetables for data-entry.

Timely Data

Regardless of aptitude or willingness to improve, continual data integration can take the discipline of regular data-reporting by patients out of the equation.  Depending on the program goals and thereby the devices accounted for by your integration efforts, it’s easy to see how scales stepped on, temperatures taken, and walks strolled early in the am, if integrated via devices, would benefit program prioritization and outreach efforts that begin at the open of business hours.

Beyond improved engagement and data timeliness?  Integration takes the guesswork of how to properly enter data off of patients’ plates and assures its inherently ready for the algorithmic consideration necessary to make stratification and trend-based clinician outreach straight-forward. Data standardization assures EMR and analytics databases can do the technical jobs that inspired you to deploy them in the first place.

High Touch to Automated Transitions:  Effecting Rapid Change

The monitoring and outreach programs your system deployed during peak Covid-19 periods were pivotal to organizational morale and community growth.  But let’s face it, they are not sustainable for the long-term. We need better systems and methodologies for surges and/or future events to come, we need to get into the habit of going from high touch to efficient stabilization for this and future efforts, and we need to learn from this crisis period to effect rapid change in healthcare on an ongoing basis moving forward.  As if this weren’t enough, we need to weave patient device integration into all of these imperatives.

Familiarize staff with these imperatives by leveraging projects that fall under chief system goals and initiatives.  Socialize them as just as important to the current crisis as efforts currently wrapping-up, and even more so given their importance to the preparedness for future crises.  We don’t want to be caught flat-footed!

1. FIRST: Identify the core areas in which you’d like to move towards standardization and to automate outreach.

2. Parallel Work Stream A:

   • Engage your internal, local, and state leadership to assist with deployment of data integration tools crucial to future symptom and monitoring programs.

   • Integrate data sources: build, test, validate, deploy

3. Parallel Work Stream B:

   • Rapidly stand up your processes that make use of manual data capture and intervention strategies

   • Refine based on real-time experiences as you build for automation

4. Parallel Work Streams A & B Converge:

   • Integrate data feeds into manual capture and intervention processes

   • Begin to automate outreach stratification based on patient device-integrated risk-scores and trends

   • Transition high touch outreach efforts to only those cases trending most negatively, use alternative automated mediums for other population segments

Engaging Governments: Effecting Change as Rapidly as Possible

Local, state, and federal infection forecasting more highly intertwined with personal device data is ripe for discussion right now. While we can assume this is going to take more time, there’s no excuse not to have the conversations and to plan for future full-scale interoperability as alluded to in the convergent work stream above.  Where do you start? 

1. With the discussions.  Use your organizational priorities and information already on hand to make educated best-guesses on device types, volumes, and funds you and/or your governments can begin to set aside.

2. Develop and test the integration necessary for a variety of scales, thermometers, watches, pulse oximeters and the like such that your recommendations to partners can be informed by experience.  NOTE: even learnings from early stages of testing and validation can be telling.

3. Engage hardware partners on successes and failures.

4. Keep your government and community partners abreast of what’s working now.

   • Get sophisticated, not just general numbers and names.  Be specific to models showing long-term integration promise.

5. Repeat.

Summary:

Whether your programs are designed to care for chronic illness populations during normal or pandemic times, to get ahead of peak resource utilization during the next surge, or to right the wrongs of decades of resource misappropriation, when scaling of efforts is met with resource limitations, every data point at the margins matters.  Patients have devices capable of integration, governments and non-profit organizations can get them to those who don’t, and health systems who are out-front on monitoring and outreach programs are telling us what can be improved about these integrated monitoring and outreach processes.

It’s time to integrate the data beyond health systems’ walls with the data-forward approaches inside them.

If it were possible to begin to stockpile devices capable of at-home integration and your organization believed they could be critical to keeping the next curve flat, your government, community, and device partners should know.  Start your discussions, and your efforts, now.

Thank you for reading. If this content speaks to you, please follow CJ on Twitter or LinkedIn to be made aware of future blog content when it’s hot off the presses.