MAY 11, 2020   7 pm

USING WEB TECH and OSCAR EMR TO MANAGE YOUR PRACTICE DURING THE COVID-19 PANDEMIC

Find your  patients (hypercholesterol, hypertension, CAD, diabetes) who are at HIGH RISK for complications of COVID-19

Find your not at target HBA1C patients and LDL patients

Using COCV to find COVID-19 test results
HOW TO FLAG your COVID-19 cases (positive or negative) in OSCAR EMR
Practical templates for COVID management   AND FLAG THESE HIGH RISK PATIENTS

Experience with TELEMEDICINE to treat these patients
PRACTICAL TIPS for WEBCONFERENCING using OTNconnect, Novari Evisit as well as non-certified social media tools Facebook, Zoom, WeChat, What’s App
Demonstration of OPEN-SOURCE  JITSI MEET Webconference software.

OUR EVIDENCE BASE is EVOLVING with the COVID PANDEMIC so this conference promotes discussion, experience and SOLUTIONS.

RSVP to

Dr. Ian PUN  for WEBEX meeting room
ianpun@gmail.com

SYGMA 1 and 2 demonstrate that as-needed treatment with budesonide and formoterol prevented exacerbations and loss of lung function, significantly reduced median daily ICS dose, but was less effective than the other treatments for symptom control. Treatment should aim for symptom control or exacerbation prevention.

Query by Example : Find your patients prescribed Ventolin over the last year.
Please in ADMIN -> Query By Example

select de.last_name, de.first_name, dr.demographic_no, dr.written_date , dr.special from drugs dr, demographic de where (dr.special like “%ventolin%” or dr.special like “%salbut%” or dr.BN like “%ventolin%” or dr.BN like “%salbut%” ) and dr.demographic_no = de.demographic_no and dr.written_date > date_sub(curdate() , interval 1 year) order by dr.demographic_no;

COVID-19 epidemiology

Ontario Public Heatlh cases of COVID-19
https://www.ontario.ca/page/2019-novel-coronavirus-2019-ncov

Map of COVID-19
https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

Realtime COVID-19 Stats
https://www.worldometers.info/coronavirus

Mathematical model of COVID-19 spread
https://art-bd.shinyapps.io/nCov_control/

show how to change parameters
incubation period = 7 days
when the infection started = Nov 15, 2019 (backtracing of curve)
when the control measures started = Jan 24, 2020

The infectivity of the R0 ( patient spread before control) = 2.3
The infectivity of the Re (patients spread after control= 1.5
Actual reports cases fit curve of Re = 1.9

Use my OSCAR RbT “free-text” search for “wuhan” patients.  I found and contacted a patient who is a flight attendant from Wuhan China, she told me about the situation first-hand starting a month ago (this is her latest email shown below with her consent)

Hello Dr pun ,

Thank you for your email . I am in Dubai now . Now we cannot fly to mainland China so we have to find other destinations as alternatives .

My family in Wuhan are all well . My parents have been staying at home since Jan 23rd . My brother buys groceries for them once a week .

I do have friends have lost their family members and one friend got affected herself , as well as her daughter . Hubei is still in serious
shortage of masks and other essential protection gears . My doctor friends told me that she had her coworkers have to stay at
hotel in case they get the virus。

Air Canada tentatively plan to resume China flight the end of March but not confirmed yet . There will be no flights to Hong Kong
in March due to booking reduction.

Hope the situation can get better soon .

L.

Computer Security
Ransomware: a sustainable, profitable business

Phishing Email is now directed to healthcare. Lifelab , Toronto East General hacked last October
After cfpc.ca email hacked on Feb 5, my OSCAR server started to experience have hacking attempts.
Anti-viral software not much use.

Don’t click on suspicious links
Use secure passwords
Review your security policy of your OSP
BACKUP BACKUP BACKUP

AI skin classifier that classifies a skin picture to 7 categories!

My OSCAR app using Google Tensorflow trained on HAM-10000 skin lesion library.

We tested it on one of the attendees! It’s a benign mole on your face!

Exporting charts in bulk you must check with OSP.  Check the ownership of the clinic.

Chart transfer with pdfs or XML

emailing charts to lawyers or insurance with Keke ZIP with password.   Renaming file to .zap as some mail filters it out.

Next meeting April 9, 2020

Don’t miss it…

Here are the take away points:

CV RISKS:

Dr. Raymond Chan , cardiologist, showed randomized trials of statins and now PCSK-9 inhibitors have shown that lowering LDL-C reduces cardiovascular risk, confirming that LDL-C is a cause of atherosclerotic disease so it beneficial to have the patient’s LDL as low as possible especially for secondary prevention.

I, Dr. Ian Pun, showed how to search for high LDL patient using my report by Template lab searching query which searches for the most recent lab value of every patient.

First I had my audience , who mostly were seasoned OSCAR users, try it out with their own OSCARs
Using ADMIN->QUERY by EXAMPLE

select * from measurements where type = “BP” limit 10;

to make sure their OSCARs had the LDL values as part of measurements.

Then they ran my lab searching report by Template (download in my google classroom https://classroom.google.com/o/OTUxNjY5MTE4M1pa , PM me for access code) for LDL > 5. Then these high risk patients could be accessed first.

Furthermore, I showed a search (requires backend SQL) to QUERY PATIENTS who have LDL > 2 and already on Statin and Ezetimide for PCSK-9 inhibitor treatment. Personally, I have found a handful in my own practice.

Artificial Intelligence:

A.I. encompasses rule based systems (like existing SQL queries in OSCAR) to machine and deep learning systems using neural nets, modelled after biological nervous systems. A.I. using deep learning provides a predictive model that is formed from training data, not based on preprogrammed rules. A.I. learns from examples, not programmed. However, a hugh quantity of quality data is needed.

Using google tensorflow , I demonstrated graphically how a simple neural net works, classifying two different populations with 2 dimensions. Simple data clusters that are simple shapes are easy to train. More complex shapes required more nodes and more neuronal layers to figure out.

Classifying my OSCAR measurement data into Hypertension, Diabetes, CV , I will train the neural net model using Googletensor flow. I graphed the relationship of A1C vs BMI vs Diabetes .

Dr. Raymond chan asked, “Patients who are outliers , do not fit the categories and have problems. How will a neural net find these?” Unfortunately, the neural net will not be sensitive enough to detect this. It can only be solved with more data as outliers may have a different unknown variable. He also asked “Is a neural network brute forcing its solution?” I would say it’s not because it doing it algorithmically and recursively to find the optimum solution from by minimizing the feedback error loop. Brute force is the computer’s way of trying every possibility and picking up the optimum solution. Neural Nets don’t try every possibility, only optimal ones.

Taking Photos to OSCAR — USERS are doing it!

I recommended every patient sign a PHOTO CONSENT if you intend to take a picture of any of their medical conditions.

I showed the two device (phone and computer) method of taking a picture to OSCAR.
Log onto to OSCAR on both devices. Go to patient eChart on computer. Go to patient demographic screen on phone.
On phone , add document, select PHOTO type, type PHOTO description and ADD DOCUMENT. The phone will show you to use the CAMERA APP. Take the picture and check on checkmark. Then click on ADD. On the computer refresh the screen and you’ll see the photo document added.

No extra apps are needed for this technique and your phone photo does not go onto the cloud storage as it is stored temporarily before it is uploaded to OSCAR.

A gastroenterologist in the audience said he uploads his gastroscope pictures onto OSCAR using USB and shows patients polyps on the computer to convince the patients to have them removed.

Tracking Labs

I showed my RbT that matches each patient the lab test request on the lab form (e.g. PSA) to the corresponding measurement received (e.g. PSA) and reports the patients whose measurements that were not found.

We talked about using ticklers and messenger to track lab results and recalls but agreed there are many potential points of failure from patient, lab and physician.

The GI doctor is concerned that when he sends specimens for pathology, he has no way of tracking the result as it comes back on the lab HL7. I told him this can be resolved with an histology eform to match with the HL7 result, However, unlike blood labs , there is no LOINC code for a histology result as it is text only and not pushed to measurement.

Vaccine coding

The Ontario government made a law starting July 1, 2018 that every physician must report public vaccines given directly to public health on-line.

I showed the vaccines have to be coded for name, lot number, location , route, dosage in PREVENTIONS. Hopefully this information will be automatically transferred to eHealth with OSCAR updates.

The present ICON system for entering vaccines is very user un-friendly.

Also, in the meantime I suggested to code vaccines as templates with perhaps later code can populate the preventions automatically

MAKE ENCOUNTER TEMPLATES for vaccines prefix with #V #
#V #Gardasil 9 HPV vaccine MERCK , N035952 10NO2019 , L deltoid , 0.5 cc, im

The complete slide presentation will be uploaded to my google classroom https://classroom.google.com/o/OTUxNjY5MTE4M1pa soon.

Ian

Slides can be found here: OSCARconf4_180614