Thursday, September 17, 2020

Teaching Example : The Ice Cream Order Set

Hi fellow #ClinicalInformatics, #Informatics, #HealthIT, #CMIO, #CNIO, #CPOE, #workflow, and other #design thinking friends, 

Order sets - If you work in Clinical Informatics, you probably have a lot of experience with them

Order sets offer great opportunity, and can really help streamline clinical processes and create predictable outcomes. Since they are a part of the medical record that every doctor uses (like Larry Weed, MD once said), they can help guide and teach. In my 13 years of designing them, I've seen remarkable standardization in processes, reduction in variation, and improved outcomes when they are designed well

For those who design and build them, however, here are the five most common challenges : 

  1. People without solid order set experience often don't budget properly from them, from a time or resources perspective. (They often take more work than most people would initially imagine.)
  2. Doing them well often requires a great deal of effort and coordination between multiple clinical stakeholders (Physicians, Nurses, Pharmacists, and often other ancillary services, operational leaders, finance, legal/compliance, etc.)
  3. It's not just the effort to create them - It's also the effort to maintain them.
  4. People often disagree about the best way to create, review, test, approve, and publish them. 
  5. Managing expectations can take time, especially when people try to use them to solve complex training/education or utilization problems. 
There are actually best-practices for developing them, but they're often not well-understood. It often takes time to build them in a collaborative manner, to help ensure the best outcomes: Order sets that physicians will actually *use*, predictably, to achieve predictable outcomes. 
So recently on Twitter, my CMIO colleague Paul Fu, MD from UCLA shared a tweet about an EMR order for 'birthday cake', presumably from a pediatric hospital that had actually had built an order for pediatric patients who could tolerate a piece of birthday cake on their birthday.

While several Clinical Informatics friends chimed in to comment, I took the opportunity to create a tongue-in-cheek, general-purpose Ice Cream Order Set that could actually be used for teaching and discussion purposes : 

Ice Cream Order Set

This [DRAFT] order set example above basically lets you prepare ice cream for your TV binge-watching purposes. Remember, It's not a real order set, but it's a decent teaching example to show just how complicated and workflow-dependent order set design can be. 

You'll notice that it's a general-purpose ice-cream order set, addressing some common scenarios : 

  • It's fairly flexible, allowing you to eat as little as a single scoop in a bowl or cup, or as much as multiple pints.
  • It does a decent job addressing common allergies (lactose, peanut, dairy, etc.)
  • It uses fairly standardized units of measurement, which are reasonable for most ice-cream consumption purposes. 
  • It lets you select a number of toppings - and even finishes with a cherry on top. 
You'll also notice that it has some limitations : 
  • It only offers three flavors - Chocolate, strawberry, and vanilla. (Imagine trying to index an order set to offer more complex flavor combinations?)
  • While it has decision-support built in to help guide an ordering provider to the right choices, it does require a doctor to order the ice cream differently, depending on the utensils and container (cup/bowl versus the ice-cream container)
  • Some Clinical Informatics friends have suggested it should have some alerts and hard-stops for people with certain food allergies (e.g. should you be able to order peanuts if you have a peanut allergy?)
Of course, it's just ice-cream, but the order set is still fairly complex, and required the development of a new term ('unique container') to address the ordering workflow related to eating from bowls/cups versus the ice-cream container - Imagine creating order sets for complex or high-risk clinical workflows.

Feel free to share this teaching example for your own discussion or education purposes - If you don't use an EMR or don't use order sets, it's a friendly way of showing people the promise and complexity that order sets can present, both in development and use.

Remember this blog is for discussion and education purposes only - Your mileage may vary. What would you do to make this order set easier or offer more flavors? Do you have any tips or feedback about order set development or maintenance? Feel free to leave them in the comments section below!

Friday, September 11, 2020

How to Untangle a Complex Clinical Workflow

Hi to my fellow #CMIO, #CNIO, #ClinicalInformatics, #Design, #Designthinking, #workflow, and #HealthIT friends,

For today, I thought I'd share an easy trick for untangling even the most complicated clinical workflows. 

Let's say you're asked to help troubleshoot a particularly complicated workflow, where the end-users tell you things like 'It's so complicated, I can't even describe it!', or 'It's very non-linear'. You want to help, but aren't sure where to start. 

Here's my tip : Start by just writing procedures

While many people in the industry commonly write their workflows as 'swimlane' workflow diagrams, I find that these can sometimes quietly have room for error. In the wrong hands, with an untrained eye, it's possible to draw up a swimlane diagram with 'hidden gaps' that are hard-to-spot until you talk through each step in the process, usually with a group of end-users.

Indeed, swimlanes are the usual industry standard for planning or troubleshooting complex workflows, but writing good procedures can be equally as effective, with some added benefits : 

  • Procedures can usually be edited dynamically, on-the-fly, with a group of people (e.g. in a video conference), as an easy way of quickly collecting their understanding of their workflow/process. 
  • Procedures also make it easier to spot missing pieces - If you use my format above, you'll always know when the WHO (stakeholder) is missing, when it's not clear what's a REQUIRED (will) task or an OPTIONAL (may) task, or what exactly the task is. 
  • Procedures can also usually be easily converted into policies or education, for those times when you want a policy to help back up and reinforce your important procedure, or educate it out to the people who need to follow your new workflow/procedure.
  • Procedures are also generally 'naturally lean'. Missing pieces, redundancies, or design problems usually become obvious as you write out the procedure, allowing you to address those questions before you build your new process. 
If you use the procedure outline above, with the optional modifiers - you can even estimate the time it takes to do each task, allowing you to estimate the total time, people, and resources you will need to achieve your desired outcome. This can even be helpful in developing a Total Cost of Ownership (TCO) and Return-on-Investment (ROI) for your workflow.

And it's generally easier to stitch procedures together than it is to try to stitch swimlane workflows, which can take some time to move objects around, edit text, and reformat the diagram. 

Finally - For extra clarity, you can even name your procedures exactly what they are, e.g. : 
  • DRAFT - CURRENT STATE - How to cook good food
  • FINAL - CURRENT STATE - How to cook good food
  • DRAFT - FUTURE STATE - How to cook even better food
  • FINAL - FUTURE STATE - How to cook even better food

If you have any tips you'd like to share for documenting or troubleshooting workflows, feel free to leave them in the comments section below!

Remember, this blog is for educational and discussion purposes only - Your mileage may vary! Please check with your Clinical Informatics, Legal/Compliance, or Clinical Operational leadership before documenting any of your own workflows. If you have any feedback, tips, or tricks you'd like to share - Feel free to leave them in the comments section below!

Thursday, August 13, 2020

Why Terminology Matters

 Hi fellow Clinical Informaticists, CMIOs, CNIOs, and other HealthIT friends,

A short post this time - Just sharing how terminology management can impact EMR usability

Managing an enterprise EMR is a lot like owning a closet. Information is stored in certain virtual 'drawers', where people (users) get used to storing and finding the information they need to do their jobs.

The problem is, just like closets - Exactly where and how people like to store this information is an intensely personal, cognitively-driven process. If you have ever had to share a closet, you probably know how challenging it can be to share a closet with another person. 

Now, imagine having to share a closet with 500 people. The first step would be getting all 500 people together for a meeting, and discussing/reviewing : 

  • Where should we keep the socks?
  • Where should we keep the pants?
  • Where should we keep the shirts?
Some people may have different opinions about where and how to keep things, but ultimately, you will need to make some final, group-based decisions

Still, some people may start working for your company after those group discussions/decisions are made, so it's helpful if you :
  • ... have an easily-identifable pattern associated with your information storage and retrieval, and...
  • ... if you label things correctly
Today's post is really about labeling things correctly. For teaching purposes, I sometimes simplify it as this : 
"Call it what it is."
It can sometimes be difficult to spot terminology issues, so I'll start with a simple hierarchy that helps explain the confusion that can create frustration for end-users :


Keep in mind that these are simple, real-world examples that we are using as proxies for more complicated, real-world clinical scenarios.

In any case - when labeling a button, folder, or other item in an EMR, it's important to have the appropriate level of granularity and accurate clinical terminology, or else you can lead to confusion for end-users : 

Suppose a user is looking for an apple. 

  • In scenario #1 above, if we just refer to apples and oranges as "fruit" - users will need to spend time clicking through both boxes, looking for the apple. It might be in the left box, or the right box - They are both labeled "Box of Fruit", and fruit is not a granular enough term to identify the exact tool the user is looking for (an apple).

  • In scenario #2 above, it's easy to find an apple. The first box is labeled, "Box of Apples".

So it's always very helpful to :

  • understand and anticipate what the user will be looking for, and...
  • understand the clinical terminology and associated hierarchies, and...
  • call it what it is.
Some people might argue "Well, if both apples and oranges are fruit, why not keep them in the same 'fruit' folder?" For sure, there are some scenarios where this may make sense, especially if there are not many items to look for under a folder. 

However, keeping too many items in a folder can also lead to unnecessary time spent looking for things. 

So ideally, especially when storing a large number of items - It's helpful to understand the clinical role, the clinical context, the clinical terminology, and the higher/lower level concepts, to help identify the right term to label buttons in your EMR, for maximum efficiency and less clicks.

Hope this helps shed some light on common terminology issues that every organization has to manage as they configure their EMRs. If you're not sure about a term, reach out to your local Clinical Informaticist for guidance, tips on how to reduce clicks, and other common clinical workflow design issues.

Remember, this blog is for educational/discussion purposes only, and your mileage may vary. If you have any terminology tips or suggestions, please leave them in the comments box below!

Tuesday, June 23, 2020

Determining COVID-19 Status in an EMR

Hi to my fellow CMIOs, CNIOs, #HealthIT friends, and other Clinical Informatics professionals,

For most of us, the last few months have been very busy. At no point during my medical education did I ever think we would all be working one day in the middle of a global, 1918-style pandemic.  And yet, here we are. For my fellow healthcare workers, I hope you and your families are all safe and healthy.

While there continues to be national debate about how best to manage our global crisis, there seems to be one thing most experts agree on - Having good data is key to planning and public health decision-making. 


So as a Clinical Informaticist with a background in public health and epidemiology, I'm always especially interested in the national (public) discussion about total numbers
  • How many people have been infected with the SARS-2-Novel Coronavirus?
  • How many people have active infections with the SARS-2-Novel Coronavirus? 
  • Of those infected - how many display symptoms of COVID-19? How long after infection with the SARS-2-Novel Coronavirus, and for what duration?
  • Of those infected - how many have COVID-19 illness that progresses to severe illness and/or death (case fatality rate)? How long after infection?
And yet, with all of these questions, here's one I find the most puzzling

"Q : How do you know if a patient has COVID?"

While this might seem like an easy question (A: read the chart!), in reality - it's anything but simple

FIRST - AN IMPORTANT POINT:
It's tempting to just look in a chart for "COVID" or "COVID-19", but it's important to consider that the virus is actually called the "Novel SARS-Covariant-2 RNA virus".
  • "Novel SARS-Covariant-2 RNA virus" = The new coronavirus that actually infects people, reproduces inside their cells, and may/may not cause symptomatic disease.
  • "COVID-19" = The constellation of symptoms that are caused by the Novel SARS-Covariant-2 RNA virus
So it's entirely possible to :
  • be infected with the Novel SARS-Covariant-2 RNA Virus, with NO SYMPTOMS OR
  • be infected with the Novel SARS-Covariant-2 RNA Virus, with symptoms of COVID-19 disease. 
  • assume that patients with symptoms of COVID-19 disease should be tested for the Novel SARS-Covariant-2 RNA Virus, to determine if that is the cause of their disease symptoms.
And so when someone asks, "Q : How do you know if a patient has COVID?", it's first important to distinguish : 
  • "Did you mean how many people are CURRENTLY Infected with the Novel SARS-Covariant-2 RNA Virus?" OR
  • "Did you mean how many people total have been Infected with the Novel SARS-Covariant-2 RNA Virus, since the beginning of the outbreak?" OR
  • "Did you mean how many people infected with the Novel SARS-Covariant-2 RNA Virus have developed symptoms of COVID-19 disease?"
Always remember, when reporting data, especially to researchers or regulatory agencies - it's very important to first make sure you know exactly what is being asked

WHERE IN A CHART CAN YOU LOOK?
To help answer the question, "Q: Does this patient have COVID?", there are a surprising number of different places you might look in a medical record : 
  1. The Chief Complaint, (e.g. "cc: COVID symptoms" or "cc: Fever, Respiratory Symptoms" or "cc: Suspected COVID" or "cc: Suspected Pneumonia") - This gives you some insight about what type of symptoms the patient might have had on arrival. 
  2. The History of Present Illness (e.g. "75M with recent travel to country with high COVID activity and recent exposure to known COVID patient (8d ago), who now presents with home temp of 103 and worsening shortness of breath x1 day.") - This helps further establish the likelihood of COVID-19 disease, but may not always be conclusive.
  3. The Review of Systems (e.g. "+Fever, +Chills, +Cough, +Worsening exertional dyspnea, +Weakness") - Again, like the History of Present Illness, this is suggestive, but not conclusive of disease.
  4. The Vital Signs (e.g. "HR=120, BP=100/60, O2sat=75% on RA") - This also helps build the case that the patient has COVID-19 disease symptoms, especially the low O2 sat, which has been a hallmark of disease in patients with severe symptoms. But keep in mind : Normal vitals do not exclude disease
  5. The Radiology (e.g. Chest X-ray or CT Scan showing bilateral ground glass opacities, CT Angio showing pulmonary embolism, or ultrasounds showing DVT/VTE) - This further helps establish clinical suspicion of COVID-19 disease and SARS-CoV-2 RNA Virus Infection - But is not confirmatory
  6. The Routine Labwork (e.g. Lymphopenia, elevated Ferritin, elevated D-Dimer, Renal Insufficiency, Transaminitis) - This pattern helps establish suspicion of SARS-CoV-2 Infection and possibly COVID-19 disease, but is not confirmatory.
  7. The Diagnostic Labwork - Nasal Swabs (e.g. Positive SARS-CoV-2 RNA PCR Nasal Swab) - This is helpful and confirmatory, to determine if your patient has COVID-19 disease symptoms caused by the Novel SARS-2-CoV RNA Virus - But remember that most nasal testing, as of this post, is only about 90% sensitive. So about 1 in 10 people with a negative result may in fact actually have the disease. (As of this writing, I'm not entirely sure if this refers to testing patients WITH symptoms, or testing patients WITHOUT symptoms - If you have a good answer to this, please feel free to comment below!)
  8. The Diagnostic Labwork - Antibody Serologies (e.g. Positive IgG antibodies to the SARS-CoV-2 RNA virus) - This can help determine a prior infection, provided the patient has enough time and immune response to develop antibodies. (I'm not sure if anyone has good data on timeframes for developing antibodies - If you have a good answer to this, please feel free to comment below!Presuming the test is a reliable one, having antibodies suggests that the patient was at least exposed to the virus. Not having antibodies is not as helpful diagnostically. 
  9. The Admission Diagnosis (e.g. "Respiratory Symptoms" or "Pneumonia" or possibly "COVID-19") - This can be very helpful, and it is a required data field in most hospital admissions. If the clinical suspicion from the initial workup is high enough, and there is maybe even laboratory confirmation of SARS-2-CoV RNA Virus infection, it's possible this might list "COVID-19disease as an admission diagnosis. Keep in mind that during most hospitalizations, often because of the incomplete information on admission, the admission diagnosis is not as accurate as the discharge diagnosis. (E.g. Some doctors might not be willing to call it "COVID-19 disease" until the laboratory confirmation has returned.)
  10. The Discharge Diagnosis (e.g. "COVID-19" or "Suspected COVID-19" or "Suspected SARS CoV-2") - This can also be very helpful, and is also a required data field in most hospital discharges. Remember that because of the additional data obtained during a hospitalization, the discharge diagnosis is usually more accurate than the admission diagnosis
  11. The Active Problem List (e.g. "COVID-19" or "Suspected COVID-19" or "Confirmed COVID-19") - This can be very helpful, since doctors usually have to manually add it to the list - So if it's there, it usually means a doctor had enough clinical suspicion and laboratory confirmation to label the patient as having COVID-19 disease. Keep in mind that some doctors might not put it in the active problem list, and instead put it in their progress notes. 
  12. The ASSESSMENT/PLAN on the Admission H&P, Daily Progress Notes, and Discharge Summary (e.g. "Assessment : Patient with COVID-19 disease, hospital day #2, improving steadily." or "Plan : COVID-19 - Continue current therapy") - This can also be very helpful, since the Admission H&P, Daily Progress Notes, and Discharge Summary are usually the most intimate notes that doctors write in a chart. Depending on the clinical information available when they were were written, they might not confirm COVID-19 disease until later in the hospitalization.
  13. The Death Certificate (e.g. "Primary Cause of Death = Cardiopulmonary arrest, Secondary Cause of Death = COVID-19 Disease, Tertiary Cause of Death = Novel SARS-CoV-2 Infection) - This would be an ideal source of data and mortality, but this can be dependent on the time of death - Death immediately on arrival may not have the symptoms/laboratory confirmation/clinical information available as a death after several days of hospitalization and data gathering. (It may also be dependent on what exactly a doctor writes on the death certificate, e.g. "COVID-19 disease" or "Suspected COVID-19 disease" or "Confirmed COVID-19 disease" or "Novel SARS-CoV-2 Pneumonia"
What does this analysis suggest? That determining a patient's Novel SARS-CoV-2 Infection status or COVID-19 disease status in a medical record (electronic or paper) is not as easy and straightforward as one might imagine. And so, writing data reports for local or national reporting purposes is not easy

SOME FINAL THOUGHTS : 
If that's true, then how do you develop accurate reports for local and federal reporting purposes? It takes work, but here are a few suggestions I wanted to share : 
  • Before you develop any reports, make sure you familiarize yourself with the different elements of a medical record, and work closely with clinical staff to develop those reports.
  • Try to avoid using a single data point as your source-of-truth.
  • Work closely with your clinical staff to help regularly review and validate your reports.
  • Maintain open discussions about these issues with your report writers, your clinical staff, your legal/compliance team, and your HIM team. 
  • In the absence of manual chart reviews - it would be helpful if software vendors could look at algorithms and artificial intelligence to help review all of these data sources and make a predictive analysis that could be used for reporting purposes.
I hope this helps you better understand the complexities of reporting on both Novel SARS-CoV-2 RNA Virus infections and COVID-19 disease. If you have any tips or tricks you'd like to share, please feel free to leave in the comments section below!

Remember, the information in this blog above is for educational purposes only - Your mileage may vary. If you have any reporting tips or tricks you'd like to share, feel free to leave in the comments section below!

Sunday, February 23, 2020

Developing Communication and Education Strategy for Providers

Hi fellow CMIOs, CNIOs, #ClinicalInformatics, and other #HealthIT friends,

A short blog post this month

Provider burnout (including physicians, nurses, residents/housestaff, and APPs) is a real issue, and having both good communication and training strategies can be a real help in making things easier for everyone - both sender and recipient of your many important messages.

So to help reinforce my message about the importance of good workflow design, I took the liberty of adapting my recent post on Signal-to-Noise, Provider Communication, and Provider Education, into this 11-minute video below : 


The animated discussion about signal-to-video is intended only to stimulate discussion about the importance of managing both signal and noise across your clinical spectrum, for front-line providers and other clinical staff who are both on-and-off duty. 

I hope this helps stimulate strategic discussions in your own settings! If you have any helpful communications or education tips, feel free to leave them in the comments section below. 

Remember, the above is for educational discussion only - Your mileage may vary. Always check with your Senior Leadership, Clinical Leadership, Legal/Compliance, and Clinical Informatics teams before considering any kind of strategic changes in your own organization.

Have any helpful tips, suggestions, or feedback? Feel free to leave in the comments section below! 

Friday, January 3, 2020

Signal-to-Noise, Provider Communication, and Provider Education

Hi fellow CMIOs, CNIOs, Clinical Informatics, HealthIT friends, (and other Clinical Jedi!),

Happy 2020! May this year bring us all peace, happiness, and good clinical workflows.


Speaking of good clinical workflows, thought I'd introduce today's piece by sharing some recent #HealthIT Tweets - One I was connected with on January 1st came from the great Janae Sharp (@CoherenceMed), via her @SharpIndex account: 

(For those of you who don't know the Sharp Index
it's a 501c 3 non-profit dedicated to improving awareness and tools to combat physician burnout.)

In any case, it's an honor being mentioned in this group with other fantastic people who are working on the same or similar issues - So I figured I'd simply respond with: 

So with this 2020 goal in mind, let's get to today's post. 


Communication with your clinical providers is vitally important. Often when discussing provider communication, I get the question, "Why is it so hard to communicate with providers?", sometimes followed by some kind of joke, usually about providers not being able to read their email in a timely basis. 


At that point, I usually have to explain exactly why provider communication is particularly challenging. To help explain the unique challenges providers face, there's a little concept that's fairly well-known in engineering circles, that is not as well-known in clinical circles - So with this blog post, I thought I'd bridge the gap


It's called a signal-to-noise ratio, sometimes written in engineering circles as "S/N". And it's super-helpful concept in a lot of situations - from everything including tuning your car radio, to developing communication strategy in emergencies, to clinical workflow design, to provider communication and education strategies.


You can read more about the engineering principles behind a signal-to-noise ratio on the Wikipedia page ( https://en.wikipedia.org/wiki/Signal-to-noise_ratio ), where on this day I retrieved it (1/3/2020) it defines the signal-to-noise ratio as : 

Signal-to-noise ratio is defined as the ratio of the power of a signal (meaningful information) to the power of background noise (unwanted signal).
The Wikipedia article then has a lot of complex math and descriptions of modulation and decibels, but you don't need to understand any of that math to appreciate the concepts behind a signal-to-noise ratio: 

Slide 1 - Introduction slide showing signal-to-noise ratio

In any environment, as humans, we always seek meaningful information (signal). Sometimes, finding that meaningful information (signal) is easy, provided the surrounding noise is fairly low. And sometimes, finding the signal can be a challenge, especially when the noise is high.

You can experiment with signal-to-noise ratios by visiting a restaurant with a friend before routine dinner hours - and trying to have a conversation


Before dinner hours - your conversation may start with a relatively normal signal, where you can both hear each other fairly well, with only a limited amount of ambient noise in the background; perhaps from waitstaff speaking or preparing for the dinner rush

Slide 2 - Signal-to-noise ratio before dinner crowd arrives 
in restaurant

But as more people come into the restaurant, it starts the race-to-the-top. Gradually more people arrive, the noise in the restaurant goes up, and pretty soon you can't hear each other as well
Slide 3 - Signal-to-noise ratio as more people arrive
and it gets harder to hear conversation

At this point, it starts to become a little uncomfortable - So to compensate, you will both need to speak louder (increase your signal), to continue your conversation in the setting of increasing noise:  
Slide 4 - Both people start speaking louder, to hear 
signal above noise and continue conversation

But then eventually everyone in the restaurant starts speaking louder to hear each other, and the noise goes up again - So it starts to get more uncomfortable: 
Slide 5 - Everyone in restaurant is speaking louder, 
noise goes up, conversation is harder to hear.

And perhaps, just a few times, you can't actually hear what the other person is saying: 
Slide 6 - Noise in restaurant is higher than 
your friend's voice (signal)Conversation fails.

So to keep talking to your friend, you will need to increase your signal, and raise your voice again
Slide 7 - To maintain conversation, you have to raise your 
voice again (increase signal).

... at which point you will start to shout, get a sore throat, or speak only in short sentences (because you can't get enough air to increase your signal above the noise). 

If you've ever experienced this, you probably know it can make for a fairly unpleasant dining experience. Eventually, you'll leave the restaurant, and the first thing you might experience is this: 
Slide 8 - First reaction on leaving the noisy restaurant, 
when everyone seems to be 'speaking loudly'

... after which your friend may say "You don't need to shout anymore!". Soon after, the dinner crowd will empty out, and the restaurant will go back to a more normal signal-to-noise ratio again: 

Slide 9 - The restaurant goes back to a normal signal-to-noise ratio - 
but may wonder why the diners report an unpleasant experience. 

This same principle applies to provider communication and email boxes, which often have an unusual signal-to-noise ratio when compared with other clinical and administrative roles. Whether it's by email, page/text, phone call, or other communications means, here's roughly what most providers and nurses have to contend with: 
Operationally, the above table looks something like this (in no particular order, and Nurses have a very similar-looking communications map) : 
... where you can imagine, being the operator/orchestrator at the center of this communications chain - It's easy for the signal-to-noise ratio to get out-of-hand. This is why, nationally, provider communications and education strategies are particularly challenging.

This is also why, when there are critical safety issues, and patient-care is on the line - The most reliable mechanism you can use to ensure proper communication (and confirm receipt of that information) is a direct telephone call. Other methods (pages, texts, emails, etc.) are all valid forms of communication, but they are asynchronous, and may be prone to delays, or worse yet, they may get lost in the signal-to-noise ratio the provider is currently experiencing. Telephone calls are synchronous, and if it fails - You know immediately that it has failed, so you can try another provider or try another mechanism.

This is also why a good provider communication/education strategy does not just rely on just one mechanism :

[ DRAFT ] LIST - Sample modes of provider communication/education
  1. Telephone Calls - Directly to the provider
  2. Pages - Requesting a call-back from a provider
  3. Texts - Directly to the provider
  4. Emails - To the provider's email inbox
  5. EMR Inbox/Inbasket messages - To the provider's EMR inbox/inbasket
  6. Posters - On the walls of the hospital, office, nursing unit, or staff bathrooms
  7. Department Meetings - Scheduled meetings with the department members
  8. Workgroup Meetings - Scheduled meetings with a select set of clinical staff
  9. Committee Meetings - Regular meetings with selected committees
  10. Face-to-face communication - Meeting in a common location (e.g. cafeteria, staff lounge)
  11. Intranet - Creating a high-value communication/learning ecosystem for providers (containing high-value blogs, videos, and links to training and solutions)
  12. Social Media - Creating easy links to high-value communication/learning (e.g. videos, blogs, and links to training)
  13. Classroom Training / Web Instruction Creating a defined curriculum and assessment tool, for use in a classroom or virtual web environment
  14. Configuration / Clinical Decision Support - Embedding EMR alerts, order set templates, and other tools inside the common EMR workflows, to help guide staff to desired outcomes
  15. Policies/Procedures - Tools used to define organizational standards and how to achieve them
  16. Guidelines - Tools used to educate staff about how to achieve desired outcomes
  17. Onboarding / Credentialing - Tools used to educate staff when they join your organization
  18. Recredentialing - Tools used to educate staff at regular intervals (e.g. recredentialing)
  19. Screen Savers - Tools on the computers in clinical and non-clinical areas that display important messages during periods of non-use
  20. And more...
Each of these tools has it's own costs, risks, and benefits - And so which tools you use, and who you direct them to, requires thoughtful analysis and consideration of things like : 
  • What exactly is the purpose of the communication?
  • Who (exactly) is the desired recipient/audience for the communication? (Careful not to confuse provider service with provider specialty!)
  • What is the criticality of the communication? (What if the communication fails to reach the desired recipient/audience?)
  • What details need to be included in the communication? 
  • When and how often does the communication need to be delivered? (Once? Before a project go-live? Or a series of emails leading up to the go-live?)
  • Which of the above tools are likely to be most effective with the desired recipient/audience?
  • How often will the communication need to be updated? (Is it a one-time communicaiton based on a particular project? Or trying to communicate a TJC standard that may be updated next year? Or trying to communicate a long-standing HR standard that is unlikely to change?)
  • How often will the communication need to be delivered? (Once? In a sequence leading up to an event? Only during credentialing/onboarding? Yearly? Bi-yearly with recredentialing?)
And why I'd like to leave off with a few take-home points
  • It's helpful to understand the concept of signal-to-noise ratios, when analyzing your clinical workflows and provider communication and education strategies.
  • Some ways to help minimize noise include fully building out workflows (to minimize communications related to clarifications), changing the supervision model (to help off-load some communications to other members of the care team, e.g. APPs), or changing communications modes and timing (to better target communications and minimize disruptions during patient care hours.)
  • Good provider communication and education strategies do not rely on a single tool - They are a toolbox of tools.
  • The tool(s) you use for communications and education should depend on a thoughtful analysis of the exact message, the desired recipient(s), the timing, the criticality, the frequency, and the anticipated need to update the message(s) in the future.
  • Every role will have a different communication map - You can streamline your workflows for any role by making a map and then working to streamline your communications.
Hope this is helpful in guiding your clinical workflow analysis and your provider communications and education strategies! If you have any thoughts or feedback, feel free to leave in the comments section below!

Remember, this blog is for educational discussion only - Your mileage may vary. Always discuss with your Clinical Leadership, Administrative Leadership, Legal/Compliance Team, and Senior Leadership before making any strategic changes to your clinical workflows or communications or training strategies.

Have any thoughts or feedback? Or other communications or educational secrets to share? Feel free to leave them in the comments section below!

Sunday, December 29, 2019

Clinical Informatics Memes

Hi fellow #ClinicalInformatics, #CMIO, #CNIO, #HealthIT, and other friends,

Explaining the term "Clinical Informatics" to laypeople is not easy. After first trying to describe the role, the discussion can get easily lost in the current sea-of-terminology surrounding the current use of the word "Informatics" - See the current Wikipedia entries on :

Shortly after I created this post, the famous Informatics teacher and guru Dr. Bill Hersh (from OHSU!) reviewed my diagram above, and offered his famous diagram from "A stimulus to define informatics and health information technology", published May 2009 in BMC Medical Information Decision Making, for comparison. 

So, from Hersh, W. A stimulus to define informatics and health information technology. BMC Med Inform Decis Mak 9, 24 (2009) doi:10.1186/1472-6947-9-24, the following diagram is being used with permission for educational purposes : 


Used with permission, from Hersh W. A stimulus to define informatics and health information technology, BMC Med Inform Decis Mak 9, 24 (2009)
(Side note : What an honor to get feedback from the great Dr. Hersh!)

Dr. Hersh correctly points out (paraphrasing) that all 'informaticists' need to care about standards, and both data in and data out - So drawing a distinction between people who focus on data in and others who focus on data out is not helpful. 

Still, my own personal observation is that some 'Informaticists' and 'Health Informaticists' seem to focus more on data in (Clinical Informatics), and others focus on data out (Analytics, Data Scientists, Research Informatics, Population Health, Public Health Informatics). Should we all work together? Absolutely, yes. Do we need to draw lines between roles? Ideally, no, but from a practical standpoint - It seems some people prefer to create data, and others prefer to analyze and study it. (Hopefully both types can work together for the betterment of individual and population health.)

Either way, while the common use of the term "Health Informatics" might lead some people to refer to themselves as "Informaticists" (Informaticians?) or maybe "Clinical Informaticists" (Clinical Informaticians?), there is often confusion about who is responsible for the difficult task of usability, configuration, testing, education, implementation, and support

After all, when it comes to data, garbage in, garbage out - so while analyzing data may be a powerful tool for analytics, research, and population health, the quality of that data is only as good as the usability of the software, the function of the configuration during patient care, the predictability of the clinical workflows, and the training support for the users.

Since none of this complex terminology and role discussion really helps laypeople to better understand the role of Clinical Informatics, or to engage physicians in the important role of configuration and adoption - I've decided to start assembling some Clinical Informatics memes, only for friendly discussion and educational purposes. 

They are attached below - Feel free to click each image to expand.

[ DRAFT ] LIBRARY - Sample Clinical Informatics Memes (click each image to enlarge) : 
 
 



I hope these images help you educate and engage with your own teams!

Remember, these images and this blog are for educational purposes only - Your mileage may vary. Always consult with your own clinical informatics team, legal/compliance team, and Clinical and Senior Leadership teams before engaging in any strategic planning or process changes.

Have any links to other educational graphics, or feedback you'd care to share? Feel free to leave them in the comments section below!