Here is the “burr in my sock” or “pebble in my shoe” that bad EHR design can become. In another context, this is can be beautiful.
Found this in my sock in the middle of my hike.
The only way to hike in Tucson in the fall is starting at 630am and being done before 9am.
CMIO’s take? Be present, get outside, take a breath.
How do you fit a curve to your theories? Come along as CT tries to convince you that he’s right…
Over the past 2 years, our lives have been topsy-turvy. Here’s my previous post from April 2020 on the percent of patients using our My Health Connection portal at the beginning of the pandemic.
To be clear, the graphs I’ll be showing today indicates the percent of patients being seen each month at UCHealth, across all of our hospitals and clinics, who have an active My Health Connection (our brand of MyChart) patient portal account.
The tail end of the curve in March 2020 showed a dramatic uptick. So, what happened since then? In that 2020 post, I showed the March uptick in Patient Portal signups, anticipating an ongoing bump in patients. We believe this was mainly (back then) about connecting with the doctor, learning about and using Video (Virtual) Visits to see the doctor/provider since we were in the process of shutting down in-person clinics due to the pandemic.
Of course we know what happened next: an explosion of video visits (see previous post), then the availability of COVID testing, and later the availability of COVID vaccines, all of which were easier to request and obtain via the Portal.
In the graph below, we extend our original graph and add the months following March of 2020. I think we can agree that there was a steeper increase in patient portal signups below. Specifically the months between April 2020 to April to 2021, the curve looks different. And then, following April 2021, the curve appears to change again. How do we make sense of this?
One way to think about this to apply a logistic regression. I’m both too unskilled and also too lazy to attempt that. Here is my powerpoint-low-tech version, where I’ve simply pasted a line on top of the graph. Are you convinced? Do you agree that April 2020 to April 2021 shows a divergent signup rate, and that after April, the signup rate has returned to some sort of “inevitable baseline growth rate”?
As an aside, the curve above actually looks like that brilliant drawing by The Little Prince of an elephant swallowed by a boa constructor. Thus, the pachyderm.
Okay, back to our pseudo-analysis. Here is an alternate set of lines: maybe we just accelerated our patient portal signup for a year, and then hit our theoretical maximum at 86% of the population in our region being on the portal and there is no one else coming in, after April 2021?
Sure! That looks like a better fit, right?
OR, could it be that BOTH are the case, an immediate acceleration of patient portal signups in March/April 2020, sustained increase for the year that encompasses: video visits, COVID testing, COVID vaccines, THEN a leveling off of portal signups since then?
Another side observation: In the headlong rush for patients signing up for our online portal service, I’m personally finding more patients who “have an active portal account” who have not seen messages I’ve sent to them. I believe there is a growing fundamental problem here with several possible causes:
Three stories, three sets of arbitrarily drawn lines. I also know that our data scientists are skilled enough to be able to do the math to justify any of these power-point-line drawings.
CMIO’s take: Now that we are seeing a dramatic drop in cases from our Omicron surge, and our hospitals are down below 100% census for the first time in TWO YEARS, we can now sit back and do some armchair theorizing. And then plan for our next chapter. Which do YOU think it is? Let me know.
(okay and fingers on a keyboard)
Is this a universal condition or what? It is nearly 2 years since I set up my basement command center and accepted the 10-12 hour days of zooming and teaming my way through meetings, collaborations and seeing patients.
I just want to acknowledge that visionaries like Gene Roddenberry (Star Trek and the big brain people, above) and Matt Groening and Futurama saw clearly from decades ago, our present condition.
I’ve heard that there is a thing called “outside” that I’m going to go up the stairs and find out, if it exists.
For 4000 patients, we now have data and reminder tools to notify clinicians of important drug-gene interactions at the time of prescribing.
by GUEST BLOGGERS: Christina Aquilante PharmD and David Kao MD
The morning of Wednesday, December 1, 2021, members from the Colorado Center for Personalized Medicine (CCPM), UCHealth IT, and BC Platforms teams surrounded their home computers, fixated on a Microsoft Teams channel. It had all the feels of a space shuttle launch. The teams had been working for five months to upgrade the CCPM Biobank pharmacogenetic (PGx) return of results pipeline. Today was the big day – CYP2C19 and SLCO1B1 PGx results were about to be returned to the UCHealth Epic electronic health record (EHR) for Biobank participants.
8:22 am. “Good morning! Happy go-live! Kristy Crooks, Biobank Laboratory Director, will be signing off the first plate at 8:30 am.” typed UCHealth Project Leader, Emily Hearst.
8:30 am. “Please post in the Teams chat when you sign off on the first plate. We know there will be a delay as the plate is being processed,” typed Emily Hearst.
8:32am. “Plate signed off. Not seeing a result in Epic yet,” typed Kristy Crooks.
8:36 am. “PGX molecular was resulted!” typed Kristy Crooks. A flurry of emojis followed.
8:37 am. “Yesssss!!! Strong work all!” typed CCPM Medical Director, Dave Kao.
The teams worked for the next few hours troubleshooting minor technical glitches and testing more plates.
12:21 pm. “We have success!” typed UCHealth Systems Architect, Katie Hess.
The success of December 1st’s go-live was a culmination of years of hard work from many different teams. In 2015, CCPM partnered with UCHealth to establish the Biobank Research Study. As part of the study, UCHealth patients are asked to provide a blood or saliva sample for genetic research. There is also the potential to have clinically actionable results (e.g., PGx) returned to them and their EHR. Prior to 2021, PGx results had been returned for some Biobank participants but the return process was put on hold to upgrade some of the IT infrastructure. After an incredible team effort, the revised IT pipeline launched on December 1, 2021 and
almost 4000 Biobank participants have now had CYP2C19 and SLCO1B1 results returned to their UCHealth EHR and patient portal.
Christina Aquilante, PharmD
CYP2C19 is an enzyme that metabolizes medications such as citalopram, escitalopram, clopidogrel, proton pump inhibitors, and voriconazole. Due to genetics, approximately 60% of patients are not CYP2C19 normal metabolizers, which can influence medication efficacy and safety. SLCO1B1 is a protein that transports statins into the liver. Approximately, 28% of patients have decreased or poor SLCO1B1 transporter function. This can lead to an increased risk for statin-associated musculoskeletal symptoms.
Given that > 30 million Americans take statins annually, this seemingly small risk [genetic variant] can ultimately affect a lot of people.
Christina Aquilante, PharmD
The questions that get asked most often by clinicians are – How will I know if my patient is a Biobank participant? How will I know if they have CYP2C19 or SLCO1B1 results? What do I do with this information clinically? How often are these alerts going to interrupt what I’m doing?
The good news is that the CCPM and UCHealth teams have built clinical decision support tools to notify clinicians of important drug-gene interactions for Biobank participants at the time of prescribing. In other words – clinicians don’t need to look for it – the tools will tell them when it is important. Currently, PGx CDS tools are live across the UCHealth system for 17 medications affected by either CYP2C19 or SLCO1B1. These tools contain guidance for how to modify drug therapy based on the patient’s PGx results.
In the cable TV industry, this used to be called the “Last Mile” problem, where a cable company could build a terrific network of cable channels, underground cables and signal transmitters, and yet that “last mile” to the customer’s home, determines if the customer gets any benefit.
Importantly, the teams took great care when designing the CDS tools, and most of the tools are highly visible and yet non-interruptive in nature, i.e., they will not stop a clinician’s workflow. As of February 14, 2022,
301 drug-gene interaction alerts have fired in clinical practice for 268 Biobank participants.
David Kao MD
The most common alerts are for proton-pump inhibitors (PPIs), followed by es/citalopram, and then statins. The work to date is just the tip of the iceberg for the CCPM Biobank PGx return of results initiative at UCHealth. The team is in the process of preparing for another gene launch in early summer – this one for DPYD, which affects the chemotherapeutic agents 5-fluorouracil and capecitabine. Simultaneously, the teams are planning for the deployment of a Genomics Module in Epic and testing out new genotyping platforms with more extensive PGx variant coverage. When these pieces are in place, the sky’s the limit for PGx at UCHealth.
Christina Aquilante, PharmD, Professor
Director of Pharmacogenomics, Colorado Center for Personalized Medicine
David Kao, MD, Associate Professor
Medical Director, Colorado Center for Personalized Medicine
I don’t know where I land in this debate. Certainly, I agree that open-office cubicles are not helpful. I also agree that zoom meetings leave something out of in-person discussions and side-bar conversations before and after our meetings. This article made me think.
Here’s this month’s prompt, how to submit, and an illustrated archive of past favorites.
— Read on www.wired.com/story/six-word-sci-fi/
