The pandemic, patient messages and phone calls: Octopus or Starfish?

Here we are 19+ months into the pandemic. Time to look at our (unvalidated) trends within our 12 hospital, 1000 clinic health system in Colorado.

Top (blue) line indicates outpatient visit volume monthly from Sept 2019 through Sept 2021. Over 2 years, we saw that dramatic dip in volume in March. That was followed by a gradual recovery and a 10% sustained increase in volume since then. We have added some clinics to our system in the meantime.

Magenta line indicates online messages. We started at 58,000 monthly messages in September 2019, and have sustained 180,000 messages in the most recent 3 months of 2021, a 3 fold increase in patient messaging. OK to ignore that weird peak in Mar 2021, related to a one time system broadcast. This is a real concern for provider workload.

Orange: Surprisingly, we also see an increase in telephone messages (triage-type phone calls): from 23,000 to 35,000, a 1.5 x increase. This means that online messages have NOT replaced phone calls since the onset of the pandemic. This could be related to the growth in percentage of our patients who now have a portal account (growth from 70% to 85% of our patients enrolled in a portal account, over 1.6 million accounts), as well as existing portal-using patients sending more requests and messages, wanting to avoid in-person visits.

Red: Additionally, Scheduled Phone Calls (non-existent prior to pandemic) are now at 5000 monthly messages, and

Green: video (virtual) visits went from nearly zero, up to a peak of 70,000 a month, then stabilizing at 23,000 monthly.

It is an interesting, evolving picture. We have not formally changed staffing or workflow to accommodate this change in message and visit volume, and it has resulted in a massive increase in inbasket messages for providers and staff, with concerns of an unmanageable burden and real risks of burnout for providers and clinical staff.

We believe that, at its root, patients want care, are more anxious about their health during a pandemic, want to avoid in-person visits, have learned about our online tools, and are unclear as to the best way to interact with us.

We could: improve our “front door” experience “Here is how best to contact and work with us”. We could improve our triaging of incoming messages to find the right location/time/place (online message, eVisit by messaging, online chat, scheduled phone call, virtual visit, urgent care, emergency department, other innovative approach).

We could ensure our teams know the best practice for: handling patient questions, prescription renewals, referral requests, outreach programs, remote monitoring, when to suggest video or phone visits, huddling in-person to replace unending back-and-forth messaging.

OCTOPUS

As a result, we are kicking off a major Inbasket redesign initiative. Although our inbasket settings were carefully considered and modified over the years since 2011 (our original Epic go live) with careful feedback from our physicians and informaticists, we still have opportunities:

Inbasket TECHNICAL changes:

  • Eliminating “messages > 12 months old”
  • Reducing the “FYI” and not-actionable messages
  • Auto-deleting some categories of messages after some period of time
  • Creating smartphrase responses to improve thoughtful responses to team mates and to patients
  • Streamlining the ‘response buttons’

Inbasket WORKFLOW changes:

  • Creating best-practice teamwork for “top of license” work
  • Considering innovation tools to “auto-reply” to common questions
  • Moving complex conversations away from portal messages to scheduled phone calls, virtual visits, in-person visits, urgent care as appropriate
  • Considering billing for complex portal messages with patient consent

Just like with Physician Burnout and Wellness in general, there is plenty of work for everyone in Inbasket improvement: there are at least 8 arms to this octopus. Even if we can just “hack off” some of the arms (hmm, perhaps not the best metaphor for healthcare), we can certainly reshape the octopus into something more manageable (a starfish?).

STARFISH

CMIO’s take? Is your inbasket an octopus or starfish, or some other marine animal entirely? It is time for a wholesale re-imagining of our messaging and communications with patients and with each other. What are you and your teams doing in this area? Let me know.

This video about storytelling will change your life

I have followed Andy Goodman’s work (he teaches storytelling to nonprofit organizations), and have learned so much about how to be effective at my own work.

It is nearly an hour long, and who has an hour? You do, if you know what is good for you.

But, I know you’re busy, so, if nothing else, watch at 10:30 minutes for 7 minutes. It will be the best 7 minutes.

Then, since you’ll be hooked by then, watch the whole thing. You won’t regret it.

No one ever made a decision because of a number. They need a story.

Daniel Kahneman, in Thinking, Fast and Slow

CMIO’s take? Storytelling by masters like this change lives. He did mine.

Canyonlands, the Zen of Sand, and my most embarrassing moment

Canyonlands Utah in the 1990’s was a beautiful getaway for me and my then-fiancée. Having heard of this wonderful mountain-bike mecca, we had come, bikes-on-top of my subcompact, met up with our tour group, a diverse crew of men and women of various ages.

100 miles

It would be 100 miles in 4 days across rugged terrain on mountain bikes with a group of 12, a couple of guides and a required-escort (at that time) park ranger. Check it out for yourself, it is a quintessential southwest wonderland.

https://www.nps.gov/cany/planyourvisit/whiterimroad.htm

We begin with a 1000 foot descent into the canyon along a jeep trail. We had brought our old unsuspended bikes with hand brakes. Although the ride was hard on our bodies, we were pleasantly surprised that our equipment was up to the task.

wildflowers from nps.gov
from nps.gov

Our ride was a blast: wildflowers, spectacular vistas, and good company, with mostly flat single track.

Great Canyonlands photography at traveldigg.com

Our guides drive a 4×4 SAG wagon with our gear and food and set up not only our first lunch, but all our meals for the coming days. We have gallons of water that we don’t have to carry! Our camelback hydration backpacks are fantastic for on-the-bike refreshment. This is the life.

Glamping (glamour camping)

At about 25 miles into the trip, at the end of the first day, we get to camp: our guides have driven ahead, set up our site. Dinner is ready and all we have to do is pitch a tent, grab a plate and a folding chair, sit and eat. So awesome. And after dinner, a campfire (apparently forbidden in recent years in the park) and then the Milky Way. Canyonlands, and other national parks, are famous for the lack of light pollution and the spectacular view of the night sky.

photo by the author on an iPhone (!), but in Gunnison National Forest, not Canyonlands

At the end of our third day of riding, as we set up camp, our guide tells us: the Green River is about 4 miles away for anyone wanting an extra excursion. Only I take up the challenge, others choose to rest at our campsite. At the time, I was training to ride my first (and only) double century later that summer (200 miles in a day: the Davis Double, but that is a story for another day), and I was anxious to get in some additional miles.

The Zen of Sand

Solo, I head out. We had learned from our guides about long patches of deep sand on the trail, and the “zen” trick of sitting back, focusing on being “smooth and circular” on the pedals, having a fingertip light touch on the handlebars, and gazing far down the track to improve balance. If done just right, one could “float” over deep sand on the trail. Turns out, this guy agrees with me (youtube).

I actually had a few moments of success doing the sand-float in the shadow of the Airport Tower formation, entirely alone with the crags and formations of the Southwest landscape. Other times, I did the meditative sand-bike-walk.

Sun God

Arriving at the river, I stash my bike in the shrubbery. I see a flat rock jutting out into the river and I determine that I’m going to skinny dip, be clean for the first time in days, and sun myself dry on the rock. Should be great.

To my parched, sand-and-sunscreen-caked, sun-blasted body, splashing in water is heaven. I soak in the cool, rub off the grime, submerge my head and hair and luxuriate.

Then I climb out into the rock, buck naked and unafraid. It has been days since I’ve seen more than our merry biker band, and they’re all kicking back at camp. I shall air-dry, sensually alive and glorious.

Author sitting on a rock outcropping. But not naked. And not the same rock.

I am a glorious human form.

I am one with nature.

I am a Sun God.

Tinnitus?

In the back of my head, I begin to hear a buzzing. What is that? Do I have tinnitus? Odd.

It gets louder. Hmm. A washing machine? Absurd.

Yet louder. An airplane? I look overhead. No contrails. Nothing. Clear blue to the horizon.

Unmistakably the sound of machinery. Rrrr-rrrr-mmm-mmm.

cdn.getyourguide.com

… and around the bend of the river, a 20-seater tour boat, 20 feet away, a gawk-fest of tourists, with a couple kids pointing out the naked man with a bike-shorts-tan splayed out on a rock in the river.

I believe all parties were mortified.

What was there to do, but wave? And then =plop= back into the river.

author, hidden

I am a bottom-dwelling salamander.
I am a shrinking violet.
I am an overexposed slide.

Predictive Algorithms Save Lives Sepsis @uchealth: A 5-slide talk

This data dilettante (see previous posts: dilettante #1, dilettante #2) has enjoyed armchair theorizing with all of you, my best (online) friends. Today we explore how our super-smart team scrambled our way to improving sepsis care with a predictive algorithm we built.

The old saying goes: the success of any major project in a large organization follows the 80:20 rule. 20% of the work is getting the technology right, and 80% is the socio-political skill of the people doing the work.

We all underappreciate this fact.

It turns out that we spent months building a sepsis alert predictive tool, based on various deterioration metrics, and a deep analysis of years of our EHR data across multiple hospitals. We designed it to alert providers and nurses up to 12 hours BEFORE clinicians would spot deterioration.

We patted ourselves on the back, deployed the predictive score in a flowsheet row, and in the patient lists and monitoring boards, with color coding and filters, and stepped back to revel in our glory.

Right?

Nope.

Turns out that our doctors and nurses were ALREADY FULLY BUSY (even before the pandemic) taking are of critically ill patients. Adding YET ANOTHER alert, even with fancy colors, did NOT result in a major behavior shift to ordering IV fluids, blood cultures, or life-saving antibiotics any quicker.

Hmph.

See the fancy patient-wearable tech on the left (Visi from Sotera, in this case), and one of our hardworking nurses, with ALL of our current technology hanging off her jacket and stethoscope. She should be the visual encyclopedia entry for “alert fatigue.” 😦

(right: one of our overburdened hardworking nurses, image used with authorization)

Back to the drawing board

As result of our failure, we huddled to think about transforming the way we provided care. It was time to disrupt ourselves. We decided to implement a Virtual Health Center, mimicking what we had seen in a couple places around the country: we deployed 2 critical care physicians and about a half-dozen critical care nurses on rotation, off-site at an innovative, award-winning Virtual Health Center.

This second time around, we created a cockpit of EHR data and predictive alerts to the VHC clinicians, who were dedicated to watching for deterioration across ALL our hospitals, and responding quickly. This does several things:

  • Takes the load off busy front line clinicians
  • Creates a calm environment for focused, rapid response
  • Dramatically improves the signal-to-noise ratio coming from predictive alerts

This way, the VHC nurses view all the alerts, investigate the chart, and contact the bedside nurse when the suspicion is high for sepsis, and start the sepsis bundle immediately.

Soon, by tweaking the ways our teams worked together, we were able to reduce the burden on bedside nurses and physicians and simplify handoffs.

See chart above: Before the VHC, bedside nurses were responsible for detecting sepsis (infrequent, subtle signals during a busy shift with lots of loud alarms for other things), with many ‘grey box’ tasks, as well as ‘magenta box’ delays.

After implementing the VHC, the VHC nurses took over the majority of ‘green box’ tasks, reducing the bedside ‘grey box’ work and completely eliminating ‘magenta box’ delays.

As a result, we have dropped our “time to fluids” by over an hour, and “time to antibiotics” by 20 minutes, which we estimate has saved 77 more lives from sepsis each year.

CMIO’s take? Predictive analytics, data science, machine learning, call it what you like. This is a paradigm shift in thinking that requires disrupting “business as usual” and is hard, but rewarding work. I can’t wait to see what we all can achieve with these new tools.

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