Dr. Glissmeyer, informaticist, Utah, notes that emergency department visits plummeted in March and are much slower to rebound. Why?
During many winter seasons, pediatric hospitals are bursting at the seams. RSV, Human Metapneumovirus, and other respiratory viruses like non-SARS CoV-2 Coronavirus cause significant disease burden sending pediatric specialists scrambling to find space to admit children with bronchiolitis who need supplemental oxygen and other forms of respiratory support. Patients with the same viruses will “double bunk” in single rooms to receive life-saving care.
2020 has been very different. COVID-19 was announced to have arrived in Utah March 6, 2020. March 13 2020 Utah schools announced that beginning March 16 online home learning would begin and Saturday March 14 the first case community spread of COVID-19 was confirmed. March 16 the Utah Department of Health issued a public health emergency limiting some services and businesses and Intermountain Healthcare and University of Utah Health announced elective and non-emergent surgeries and many non-urgent ambulatory services would be canceled. March 27 the Governor issued a “Stay Safe, Stay Home” directive. Social distancing during these months, via economic and public gathering restriction, was the only public directive. Mask wearing in Utah did not become widely encouraged until July 2020.
As a result of these social distancing measures, we have witnessed a dramatic decrease in infectious diseases. The following data are from germwatch.org and contain data of common infectious disease prevalence in Utah, as identified by testing performed at and sent to Intermountain Healthcare labs, clinics, and hospitals.
We have seen a drop in Emergency Department census that is unprecedented. We attribute this change to the decrease in circulating viruses, commonly spread bacterial pathogens and different healthcare consumer choices. In over 15 years, we have not seen ED volumes in the low ranges we are consistently seeing them now.
Even as many economic restrictions have lifted in recent months, ED census remains lower than previous. At this point, we are uncertain which of the following influencers are playing roles, if all, or others?
Health care consumer choices (avoiding health care)
Social distancing reducing disease transmission
Mask wearing reducing disease transmission as social distancing/economic restriction has begun to lift
Emergency departments are a clinical service entirely dependent upon what is referred or self-referred to them. Yet they are a critical part of the healthcare system for unexpected, emergent care and as a venue for coordinating complex care.
We are seeing an apparent, but slow, increase in ED census over the past 3 months. Much slower than the stock market rebound 😉
July 2020 Daily Census Range: 57-92 July 2019 Daily Census Range: 79-120
Our hospital and others around the country have been bursting at the seams with seasonally variable infectious diseases like RSV and influenza. We now know that social distancing behaviors that decrease disease transmission can have a significantly decrease disease transmission. Data from the Southern hemisphere indicate that influenza season may be better than previous years, perhaps because of societal behavioral changes.
-Eric Glissmeyer, MD Associate Professor, Department of Pediatrics, University of Utah Division of Pediatric Emergency Medicine, University of Utah Medical Director, Care Transformation Information Services, Intermountain Healthcare
The Covid-19 pandemic is still quite uncontrolled in the US.
In this post, we’re going to walk through an analysis that was conducted by the UCHealth data science team looking at “leading indicators” that could help us to plan for a coming spike in COVID-19 inpatient hospitalizations before we actually see an influx of bed demand.
Perhaps, if we start to see more patients reporting a cough, fever, chills, and other flu symptoms, we would expect that this may indicate a growing spread of COVID-19. However, can we actually use the prevalence of these symptoms to predict how many ICU beds will be needed for COVID-19? What about less common symptoms of COVID-19, such as loss of smell or taste, that have been shown to be more predictive of COVID-19 infection?
While this may sound like a relatively straightforward question, there are a number of confounding effects that make it difficult. The above graphic shows the number of patients making an outpatient or virtual office visit due to a fever. As expected, there is a general downward trend as the seasonal influenza season subsides. However, there also appears to be a “spike” in reports of fever in early March in our Northern Colorado geography (orange line). Could this spike be quantified for future predictions?
Defining a “symptom” in our Epic electronic health system is complex. For example, symptoms can be documented as the “reason for visit”, but a medical assistant may or may not choose to report all symptoms as the visit reason. Besides “reason for visit”, our Epic team has developed a COVID-19 symptoms checklist that screens patients at check-in (completed by front desk staff). This list was expanded substantially in the midst of the epidemic based on new evidence (for example, loss of smell). The consequence is that we saw an increase in reporting of these symptoms in April, due to the new data fields, while our actual number of COVID-19 inpatient cases was declining. In short, there is a significant amount of noise to parse through before arriving at a prediction we can trust.
How did we go about identifying the signal from the noise? Knowing that there was no “right” answer, we tested different approaches. I’m going to focus here on the most recent modeling attempt that we have found to be most insightful. We started with the premise that the correlations between our independent variables (reported reason for visit, reported COVID-19 symptoms, and documentation of ICD-10 billing codes indicative of confirmed or potential COVID-19 infection) and our dependent variable (number of COVID-19 inpatient hospitalizations) would change over time due to trends in seasonal influenza and introduction of new codes/data elements in our EMR system. We therefore constructed separate linear regression models for the months of March (when the epidemic hit and we did not yet have IT system capabilities for tracking many symptoms), April (when COVID-19 cases hit their peak and then declined, accompanying a ramp-up in new IT system capabilities), and May (something of a “steady state” when seasonal influenza had passed and no major IT updates were made regarding COVID-19 symptoms or billing codes).
We wanted to test a large number of independent variables, and therefore chose to use a linear regression method known as LASSO regression instead of the traditional OLS modeling technique. LASSO regression introduces a regularization parameter that penalizes large coefficients in the model. Instead of optimizing to minimize prediction error, the model minimizes the below cost function:
Y: Dependent variable
X: Independent variable
β: Regression coefficient
λ: Regularization parameter
n: Number of observations
p: Number of independent variables in the model
In plain English: we reduced the complexity of the model and thus reduced the chance of spurious correlation or the influence of random “noise” in the data.
Our independent variables were reported outpatient symptoms and diagnoses in the seven days prior to the index date, and our dependent variable was the number of COVID-19 hospitalizations in the seven days after the index date. For example, on May 1 we fit the numbers of reported symptoms and documented ICD-10 codes from the prior 7 days (4/24-4/30) to the number of hospitalizations in the next 7 days (5/1 – 5/7). An astute reader will note that our modeling approach violates one of the tenets of linear regression modeling in that the observations are not mutually independent, but rather a time series. To mitigate this issue, as well as the small number of observations in a given month, we used a procedure drawing bootstrapped samples from each month 100 times, and for each sample, using a 5-fold cross validation process to determine the optimal regularization parameter, fit a LASSO regression model. A bootstrap sample is a random sample of the same size as your original data drawn at random with replacement from the original data, so in some samples data points for 5/1, 5/2, and 5/3 will all be included, some may only include 5/1, and some may include none of those data points.
Once again giving a simple English translation for those less interested in the modeling approach: we introduced some randomness to our data to give ourselves better confidence in our estimates of the linear correlation between each variable and our outcome of number of future COVID-19 hospitalizations.
The below table summarizes, by month, the average correlation coefficient from all of the LASSO regression models fit to bootstrapped samples of data from that month, sorted in decreasing order by the value in May. Please interpret the nomenclature as follows:
reason_visit: Indicates the variable is the reported reason for visit in an outpatient or virtual encounter
symptom: Indicates the variable is one of the COVID-19 symptoms selected from a checklist by clinicians at the beginning of outpatient/virtual encounters
icd: Indicates the variable is documentation of an ICD-10 code referencing confirmed or suspected cases of COVID-19
reason_visit_SHORTNESS OF BREATH
symptom_Shortness of breath
symptom_Loss of smell
symptom_Bruising or bleeding
symptom_Loss of taste
The strongest positive correlation with future COVID-19 hospitalizations in the month of May was “cough” as the reason for visit. At first, the trend in this correlation over time seems counterintuitive. Why would we see such a strong negative correlation in the month of March but a strong positive correlation in the month of May? Well, a reasonable hypothesis has to do with the ramp-up in COVID-19 testing coinciding with the end of the 2019-2020 seasonal flu. In March, we saw an overall decline in patients seeking outpatient care for a cough, likely due to both the end of seasonal flu and social distancing keeping patients from seeking treatment at medical facilities, while we simultaneously initiated widespread COVID-19 testing at our inpatient facilities and saw a rapid rise in confirmed cases. In May, by comparison, there was no noise from the seasonal flu influenza and no significant backlog in testing to ramp up.
We can also look at the distribution of the regression coefficient for the cough variable in our bootstrapped samples to better establish our confidence in the value. The below histogram shows the distribution of the coefficient across all 100 bootstrapped samples for the months of March (blue), April (orange), and May (green). Notice that for a large number of samples from March and April, the coefficient is near 0, while for the month of May it ranges consistently between 5-10. What does this mean? It means that a few data points in March and April are likely having a disproportional impact on the estimate of the linear correlation, while the correlation in May is more consistent regardless of which dates are sampled.
Examining the scatterplot for the month of May, we see that this linear correlation does appear quite consistent across the time period.
After all of this analysis, what are our big takeaways? Can we take our regression model for the month of May and start using it to predict bed demand? Unfortunately, this would be unwise. One month of data is too limited a timeframe for us to be confident in our model. While we see a significant correlation between patients seeking treatment for a cough and inpatient COVID-19 hospitalizations in the month of May, both variables declined over the majority of the timeframe. We would feel significantly more confident in our model if we observed a spike in inpatient hospitalizations preceded by a large number of patients reporting in outpatient settings with a cough, as opposed to the continuous decline. Hopefully, this never happens, but we believe a second wave of COVID-19 infections is very probable by at least next Fall or Winter. Our plan is to continue to update our model with new data, potentially including new data sources such as patient engagement with our Patient Line call center resources or Livi chatbot feature, through the next wave of infections and observe performance before deploying to assist in the management of hospital resources.
I forgot about my father’s memory and neurology clinic visit even though I had promised to go down to Denver with both of my parents to help them navigate the complex world of healthcare four months before. A lot changed in those four months, most notably COVID-19 swept across the world and made its way into the US. The pandemic placed my aging parents at a greater risk if they contracted the virus while traveling from Fraser, Colorado to Denver and my work schedule was beyond capacity as I added Federal and State COVID-19 reporting coordination to an already full project portfolio. How could a take a day and a half off work? How could my parents stay safe?
Telehealth and Rural (Mountain) Living
I decided to move on from my first health care job in neurophysiological monitoring to acute care in 2011. I also wanted to move to the mountains of Colorado. My parents already moved from Colorado Springs to Fraser, just outside of Winter Park, Colorado. Yampa Valley Medical Center brought me on as a quality analyst before they were part of the UCHealth system. After moving to Steamboat, I realized how remote and isolated Steamboat Springs, Colorado was from Denver and the other “Front Range” cities in Colorado. Here are some fun facts about driving from Steamboat for medical care:
Steamboat Springs to University of Colorado Hospital and the Anschutz Campus
3 Hours and 10 minutes if traffic is good
One major mountain pass (or two if Eisenhower Tunnel is closed)
Steamboat to Poudre Valley Hospital
3 Hours and 21 minutes if traffic is good
Two major mountain passes or the choice to leave Colorado, go to Wyoming and drive back into Colorado so you only have to deal with one major mountain pass (adding on 30 more miles)
Many specialists come up to mountain communities on a rotational basis. However, this may be once a month and possibly less frequent. Telehealth is the obvious stop-gap for patients in rural and mountain communities that need specialized care. A barrier to telehealth visits as Dr. Lin has mentioned in his blog has mostly been the providers. However, with social distancing and with CMS lifting restrictions on reimbursement for telehealth, providers quickly adopted telehealth to keep revenue streams flowing for their practices.
Telehealth and Telemedicine Expansion and Deregulation
Telehealth and telemedicine rules and regulations relaxed at the start of the COVID-19 pandemic. Now is the time to figure out how else to utilize technology to improve healthcare delivery. Now is the time for innovation and policy reform. So, how can telehealth help patient advocates and family members? Could it be the answer for me and my dad’s visit? Will it work for others in an urban setting or family members that are geographically separated?
Being a Patient Advocate Remotely
Before the pandemic, I had planned on taking a day off of work to drive down to Denver to accompany my father to an appointment at a neurology clinic. This appointment transitioned to a telehealth visit following the outbreak. I considered making the two-hour drive from Steamboat Springs to Fraser to be with him for the appointment. After all, I would generate a net gain of two and a half hours from not having to drive all the way to Denver. In a moment of clairvoyance, however, I decided to find out if I could join remotely. After working with a few key stakeholders at UCHealth, we discovered that if my father gave me access to his My Health Connection account, I could join the same way he would for the remote visit. This access also allowed me to review my father’s medications as the provider discussed them with my mom and dad and access the summary notes from the visit, so I could discuss treatment options with him and my mother at a later time.
The Visit (that’s me at the bottom, by the menu bar)
It was strange to know that I would be on a video call with my parents, but to be on the phone with them as well, ensuring that they could log on. My wife and I have discussed the shift in caring for both sets of aging parents, but this was the first time I needed to support them on multiple fronts. First working with them on technology and second being a health advocate. The visits felt distant, yet at the same time normal. The medical assistant greeted us virtually and started the intake process. Dr. Zachary Macchi jumped onto the call about five minutes in and reviewed history and started the evaluation. About twenty minutes into the call, Dr. Samantha Holden was able to join as well. In the span of twenty minutes a total of six people (including my father) were working together. Had we all gone down to Denver together, this may have been the same outcome. However, Dr. Macchi joined the call first to help Dr. Holden. He stated right away that she would be able to join us, but had other commitments. My guess is that if we were in a traditional setting, we would have waited an extra 20 minutes but telehealth gave the flexibility for coverage. Telehealth has its limitations. My father had difficulty following the motor skills test. We were unsure if it is his motor function or his ability to follow a two dimensional image in the three dimensional world. For this and other reasons, everyone agreed on an in person visit three months following the virtual visit.
Just the first step… what are the next.
This visit made me realize the opportunity for telehealth in the patient advocacy realm. While telehealth offers a convenience for the patient, it certainly helps with obstacles that patient advocates face. I am lucky to live just a few hours drive from my parents. If I lived outside of Colorado, I doubt I would be as involved in their care. However, we now have the tools to improve care coordination between family members. Our first step needs to be promoting the technology to allow for remote patient advocacy. However, we could take it even further. What if we could have an MA set up a camera during an in-clinic visit so the advocate (or family member) could join the visit if they lived too far away to join in person? What are the other ways to utilize telehealth for family members and patient advocates? Will CMS go back to restricting reimbursement for telehealth? Time will tell for these questions, but we need the health care community to (dare I say) advocate for telehealth and the access it can bring for patient advocates.
My name is Guy Ristoff. I work for the EPIC IT Team at UCHealth (Colorado) as an Analyst. I also have a 3D printer. A few weeks ago, I started seeing a bunch of people posting in 3D printer Facebook groups about ear guards to use with surgical masks. I thought it was a great idea for me to explore here at UCHealth.
I contacted a unit I have done some EPIC build for and asked if they would want some. I created my first 10, delivered them to the hospital, and hoped they liked them. I then contacted Gwen Martinez from the Clinical Informatics team and she sent an email blast to a group of people about the ear guards. Within 20 minutes, we started to get responses. It was amazing! The first few “orders” were coming from the Northern Region. My brother lives in Wellington and has 3D printer as well. I called and asked him if he would be interested in donating ear guards to the Poudre Valley and MCR. He was excited to help! His kiddos even got in on the fun by making thank you cards for the staff.
As for production, I can make 17 of them per batch, which takes about 4 hours. It is not a super-fast process, but it is a lot of fun making something that helps people be more comfortable. My brother has made and dropped off 80 of them. I have created 122 of them for the AMC and MHC campus so far. I am dropping those in the mail and at the hospital today! I will keep up production, so keep the orders coming. I am just happy to be able to help!
CMIO’s take? Thanks to all our creative Epic/IT team members like Guy, to step up and help in every way that they can. –CT Lin MD
Covid-19 threatens to hospitalize an exponentially increasing number of patients in the coming weeks. In addition to building more physical space and finding more equipment, what happens when we run out of hospitalists to manage their care? What if, instead of our usual 10 teams of hospitalists, we need 20 teams? Thirty simultaneous teams?
Thanks to CT for the guest-blogging spot. I’m a physician / programmer working at the University of Colorado and UCHealth, helping our system prepare for the Covid-19 crisis.
Seeing the the massive surges in patient volume related to the Covid-19 pandemic that befell our colleagues in China, Europe and New York, we knew that we would have to find “surge capacity” among providers in our area.
We guessed that outpatient docs (like CT and me) would be needed to support the inpatient service, where neither of us have been for a long time.
I for one, was relatively panicked by the thought of serving on the inpatient service. Not only is it a different branch of medicine at this point, more than a decade from my training years, but from an informatics perspective, the workflow is completely different. I figured that if someone with my (relatively high-level) of comfort with the Epic EHR was feeling stress, others would be as well.
So roughly four weeks ago, I reached out to my informatics colleague on the inpatient service and suggested that we leverage our existing training videos to quickly produce a comprehensive written and video guide to the inpatient service, targeted at these likely recruits.
He and I, together with three other hospitalists, another outpatient internist and an informatics neurologist, quickly compiled a comprehensive document of workflow and tips.
We are so grateful that our cross-specialty relationships and shared technical expertise that are unique to informatics allowed us to create and present this material in a matter of days. Our wish:
That our surge of hospital patients is manageable
That our hospitalists stay safe and healthy
That any outpatient providers who are called to duty stay safe and healthy
We are grateful for the role we’ve played, and will continue to play
I hope that you can benefit from these documents. However, the longer view and greater message is the value of a strong informatics team which is uniquely positioned to rapidly mobilize and meet unforeseen needs.
Is the integration of an individual’s narrative into the Electronic Health Record FEASIBLE to Improve Person-Centered Care? (CT Lin: I’m excited to welcome Guest Blogger: Heather Coats PhD)
Person-Centered Care, a buzz word to refocus our Western
(US) healthcare system on the user of the system, the person who has a health
need. We as clinicians, use the word
“patient” but they are a human, just like us the clinician. We all have past,
present and future stories that make up “who we are” However, this whole self
sometimes is seen as parts in our western medicine culture…the cancer patient in room 202, instead of Jon, the person…who is a
grandpa, a dad, and businessman whose illness is impacting his ability to be
all of these things.
In recent years, the shift in Western Medicine to
incorporate the person’s experience has been moving upstream. The IHI (Institute
for Health Improvement) “Person- and Family-Centered Care” domain–Putting
the patient and the family at the heart of every decision and empowering them
to be genuine partners in their care,
goal is to develop “partnerships
between clinicians and individuals where the values, needs, and preferences of
the individual are honored; the best evidence is applied; and the shared goal is
optimal functional health and quality of life”
Since 2015, the IHI helped share the practice of asking the individual receiving health care: a simple question…“What matters to you?” in addition to “What’s the matter?” This reframing of the clinician-person interaction orients the care being provided more to the whole person, to give a much different light to a plan of care that opens the door for opportunities to involve the person’s whole self. http://www.ihi.org/about/Documents/IHI_Timeline_2018.pdf.
Now, I do not want to diminish the physiological as an important component in the delivery of care. As clinicians, our expertise (life experiences, training) are grounded in knowledge of the physiological, but I would dare to ask, we are not the experts in the whole person who is sitting across from us. Second, when a person is facing an illness…cure of the illness may not be a reality, but healing of the self is still possible.
A recent NPR Morning Edition aired on their Morning Edition program (June 8, 2019): “Storytelling Helps Hospital Staff Discover the person within the Patient aired on June 8, 2019 on Morning Edition on National Public Radio.
Person-centered narratives are one proposed way to have dedicated tools to shift to more person-centered care.
An exemplar of this narrative shift, is the MyLife/MyStory program at the William S. Middleton Memorial Veterans Hospital in Madison, WI. https://www.youtube.com/watch?v=_Wy1aMXQCTk. This program has included over 2,000 person centered co-created narratives into the electronic health record since 2013. Their program has trained an additional 50 sites to implement programs similar to theirs.
This is where my “story” comes in, I had the pleasure to attend MyLife/MyStory training back in 2015, which allowed me to think about this type of program could be implemented outside the VA, and have a program of research that tested person centered narratives interventions to improve communication between clinician and persons receiving healthcare. My NIH/NINR funded research focuses on the implementation of a person centered narrative intervention that co-creates a first person narrative that is approved by the person, then uploaded into the person’s electronic health record for their healthcare team to learn more about “What matters to them?” The first phase of the program did prove to be feasible and acceptable by the individual- the person hospitalized for serious illness, their family, and their clinicians. Through this work, perhaps, there is just one more way to help shift Western healthcare to “truly” be person and family centered.
—Heather Coats, PhD, APRN-BC Assistant Professor of Research Office of Research and Scholarship University of Colorado, College of Nursing Nurse Practitioner, University of Colorado Hospital Palliative Care Consult Service (PCCS), Department of Medicine, Division of General Internal Medicine, University of Colorado, School of Medicine
UCHealth, like many other health systems, are extending their EHR network to affiliate hospitals and facilities. Whether a hospital is coming from a paper charting system or from a different EHR, there is dramatic culture change for independent physicians as they get ready to adopt the system-wide EHR. Here are some challenges presented by physicians working at these hospitals joining the system:
Independent physicians were loosely affiliated with the hospital previously. Some surgeons were used to handwriting their H&P or faxing in a preoperative H&P they dictated via their office chart. They did the same with paper preoperative orders. Will they be allowed to continue?
Independent hospitals have had paper-based or electronic order sets developed over decades of tradition which are often customized for each of the providers even though they address the same clinical condition. Will they be allowed to keep the many physician-specific versions of these local, non-standardized order sets in the system EHR? How about if they have no-longer-standard-of-care medications and care instructions?
Independent hospitals have medical staff committees, often with committee attendance paid by hospital. When assembling leadership committees, will the system pay for physician attendance at EHR committee meetings preparing for go-live?
Inevitably, some services and specialties are more engaged than others. In the worst case, physicians will ignore the calls to attend mandatory training and readiness evaluations. As a result, these same physicians and specialties will disproportionately think that “your EHR is a piece of #(&$.” How will you work with these physicians?
Similarly, some services will need more support after go live than others. These are typically the least-engaged physicians in the hospital. How will you develop relationships with these physicians to help them be successful?
Our solution (after several trial-and-error experiences…) is to create ONE Physician Champion for that hospital, and to pay for 0.2 FTE (20% of a full time equivalent, or about 8 hours a week) to serve as THE Physician Champion for that hospital for 6 months prior, 2 weeks intensively during go live, and about 3-4 months after.
We anticipate this Champion would spend less than 8 hours a week in months leading up, and spend quite a bit MORE than 8 hours a week just before and during go live, as long as the total engagement over the 9 months, averages out.
Here are the relationships that will make this Champion successful (see graphic):
Senior (system-level) Physician Informaticist with hospital go-live experience to be a partner and coach (model of “see one, do one, teach one” from residency training)
Project Manager who represents the IT analyst team that builds the EHR tools and infrastructure and tracks deliverables and deadlines, and Nurse Informaticist who represents clinical staff roles and shared workflows.
Physician Readiness Leaders working group to create consensus and disseminate knowledge back to front-line clinicians
To extend the reach and influence of the Champion, we establish a working group of pre-go-live Physician Readiness Leaders. The specialties represent a majority of patients admitted to that hospital. We emphasize the inclusion of particular specialties like surgery, obgyn, emergency medicine, hospitalists, AND infrequent consultants and primary care referring physicians.
This committee is co-chaired by the senior Physician Informaticist and the hospital Physician Champion, comprises about 6-9 Physician Readiness Leaders. The nurse informaticist and project manager also are crucial (see above). This whole group meets monthly in the 6 months prior to Go Live, then twice a month in 2 months after Go Live.
Physician Readiness Leads are required to: attendearly EHR training, and attendextra EHR training sessions to reinforce collegial discussions and problem-solving during training, and make rounds in the hospital in the first couple weeks of go live to commiserate chat with colleagues. Depending on the hospital and local culture, these Leaders may continue to meet sporadically after go live for ongoing maintenance concerns and EHR updates. The hospital Physician Champion is contracted for about a year, and is expected to step down several months after the go live is completed. In some cases, that person or an alternate Physician Champion is selected for ongoing participation in the system-level Large PIG to help with ongoing EHR improvements and be the bi-directional relationship for that region/hospital with the larger informatics and physician community.
HERE IS OUR INTERNAL DOCUMENT FOR Benefits and Responsibilities of Physician Champion
IMPORTANT: Strong Physician Relationships are directly proportional to effective clinical care and the successful implementation of electronic health records. It is even more important than the configuration of the actual EHR technology.
Benefits of the role:
Develop a global perspective of the IT provider plan and how the unified integrated EHR system (Epic) can benefit your group.
Hit the ground running in regards to workflow efficiency at go-live and staying ahead of the curve after go live
Opportunity to be operational and clinical leaders in the hospital configuration decisions
Decrease patient safety risk when providers’ groups are involved in order set build, training engagement and attendance at pre-flight sessions
In the absence of provider participation in EHR meetings, nursing and administrator decisions may have unintended impact on provider workflow.
Help to shape physician go-live support which can be focused for your providers that will have their first shifts and procedures after go-live
Attend meetings where your feedback is highly valued and affects change rather than informational only meetings
Start to develop partnerships, communication lines, and understanding of workflows that affect your day-to-day job
Nurses want to know that the providers are on board with the change. Participating in the decisions of this committee allows you are to be seen as the leaders.
Opportunities to visit and collaborate with same-specialty providers at other system Epic hospitals
Develop relationships with colleagues to help improve the system prior to and after go-live
Responsibilities of the role:
Attend 1 hour monthly physician readiness meetings for the 6 months prior to Epic go-live
Review specialty-specific order sets to assure appropriate content is available for go-live
Communicate with colleagues in your specialty at your hospital and inform the working group about your colleague’s readiness or participation in training, order set review, and pre-flight readiness.
Bring specialty-specific concerns to the readiness group, particularly around multi-disciplinary workflows (e.g. is faxing/scanning of paper H/P’s allowed? Who will enter order set orders if/when verbal orders are permitted?)
Communicate concerns to the Physician Champion
Communicate information discussed during readiness meetings to your respective specialty colleagues
Participate in early Epic training and at least one additional training session with specialty colleagues
Participate in Clinical Informatics Journal Club as part of monthly physician readiness meetings
Some sample books included in our Journal Club:
Leading Change (Kotter)
Managing Transitions (Bridges)
Design of Everyday Things (Norman)
Crucial Conversations (Grenny)
Getting To Yes (Ury)
Jonathan Pell MD
CMIO’s (and guest’s) take? Create a clear set of expectations and responsibilities and a small multi-disciplinary team with STRONG relationships. Success in informatics is about relationships. (Thanks, Jon!)
A little over a year ago, CT Lin, CMIO at UCHealth asked “How might we reduce physician burnout associated with the use of the electronic health record?” as part of an initiative he coined EHR2.0. Through collaboration with Physician Informatics, Epic Certified Analysts, and Trainers, the optimization sprint pilot was quickly out of the starting blocks. Would the experience be the 100 meter sprint or the 110 meter hurdles?
The team accelerated quickly generating ideas. They sent out surveys, evaluated provider efficiency profiles, created checklists, investigated prior optimization requests, and observed providers interacting with the system. The team included Ambulatory Analysts, Trainers, a Scrum Master, a Nurse Informaticist, and a Physician Informaticist. They had two weeks to accomplish as much as possible through interaction in the provider’s clinic establishing a medium for collaboration in real time.
The hurdles could be anticipated; “everything is critical!”, governance, change control, communication, capacity constraints, time, trust, and differing opinions. Next, too much work in progress could create a residue effect as the analysts bounce between ideas instead of focusing on immediate next steps towards completion. Finally, how do we identify and address assumptions, inferences, and facts?
The team leveraged agile methodologies in running the sprint to help address some of these obstacles. They used a Kanban board (Backlog, To Do, Doing, Done) as a way to visualize their work and agree to the work in progress, a Burn Up chart to show their accomplishments, and a Daily Scrum (Huddle) to discuss challenges, priorities, next steps, and context for the upcoming work.
The key to the sprint became the stakeholder participation in prioritizing what was important to them and assisting with trade-offs. Instead of ideas having a static prioritization of critical, they float relative to other ideas. There was also simultaneous exploration of the problem and solution domains as the immersion provided immediate feedback loops. The focus quickly shifted from linear/more is better to high value deliverables.
The team was thinking through doing expressed best by the Chinese proverb,
“What I hear, I forget; What I see, I remember;
What I do, I understand.”
Early results across the finish line demonstrate high impact to Epic flow sheets, SmartLinks, note templates, In Basket efficiency, Synopsis, and Med Rec along with positive net promotor scores.
The experience was neither a 100 meter sprint nor a 110 meter hurdle, it was a Tough Mudder!
The fastest way to the finish line was to lower hurdles through collaboration and provide performance enhancing features that minimized mundane clerical activities, streamlined charting time, and stimulated the cognitive clinical art of practicing medicine.
Brian Redig, MBA, SCPM
Lean Six Sigma Black Belt
Board Certified Nuclear Pharmacist