Applied Bimatics - An Informatics & eHealth Blog

I am a clinician with a passion for informatics. This blog is about my eHealth journey exploring interoperability in Electronic Medical Records (EMR/EHR), Patient Safety, Pharmacovigilance, Data Analytics, Clinical Research and Bioinformatics in a clinical context. Comparing Canadian, Indian and Middle Eastern healthcare systems and services. Join our open facebook group here:

Intelligent Federated Clinical Viewers #IFCV

I have blogged about federated search clinical viewers before. Essentially such viewers query source health information systems in real time and provide the user with a consolidated view. There is no data repository, ensuring data integrity and data privacy. Though the system can be slow because of the real-time search, there are many successful regional implementations of this type.

There is an obvious disadvantage here. Intelligence cannot be built into such viewers. Since there is no server side data storage, there is no scope for server side processing. The data comes together only in the rendered view. Some  mixed systems that have a data-repository provide some crude warning flags that are not-real time. But clinically useful alerts are beyond the capabilities of federated systems. So how do we build intelligent federated clinical viewers?
Intelligent Federated Clinical Viewer #IFCV

As HTML5 specifications mature, intelligence can be built into clinical viewers by client side processing and storage. Though local database storage implemented by Safari is too insecure at this stage for this purpose, it might become viable in the future. Some useful functionality can be built with the Session storage functionality that has been expanded to store up to 4MB of data depending on browser implementations. This is much more than the conventional cookie storage. The Sessions object persist only till the window is active and is reasonably secure. I have listed some typical use cases below.

A typical pharmacy module of a clinical viewer brings together all the medications the patient is on from all source hospitals. A client side script could identify drug interactions by analysing the view. This is beyond the local EHR system as disparate systems do not talk to each other.

If all the active drugs can be stored locally during the pharmacy module view, contraindications such as steroids in hyperglcemia can be alerted when the lab module is accessed. These intelligent alerts could be clinically invaluable.

The utopian dream of cross-communicating EHRs are still a long way in the future. Regional federated clinical viewers are going to rule the roost for some time. So intelligent federated clinical viewers may be worth a consideration. I don't know whether this is already in the pipeline for vendors such as Mulesoft, Medseek or Mirth. If not, a link here (and a mail) will be highly appreciated when they do.

Labels: , , , ,

commentAdd Your Comments/Suggestions/Criticisms! | View Comments | Links to this post

LesionMapper: Pictographic lesion encoder for Dermatology

An electronic medical record example
An electronic medical record example (Photo credit: Wikipedia)
Grading systems and novel methods of symptom coding is becoming more and more important with the growth of telehealth and electronic health records. It is probable that in dermatology too, a significant number of consultations will move online soon.

Visual Analogue Scale (VAS) is a commonly used tool for measuring subjective sensations such as itching. There is evidence showing that visual analogue scales have superior metrical characteristics than discrete scales, thus a wider range of statistical methods can be applied to the measurements.

Couple of months back, I attended a thesis defense in McMaster in which an innovative web based tool called Pain-QuILTTM for visual self-report of pain was presented. The technique of iconography - pictorial material relating to or illustrating a subject - was employed to represent pain using a flash based web-interface. Pain-QuILTTM tracks quality, intensity, location and temporal characteristics of the pain. Quality is represented by different icons, intensity is represented by a visual analogue scale of 1 -10, location by the position of icon on the body image and temporal characteristics by the time stamp. The clinical feasibility of Pain-QuILTTM has been successfully validated and published.
Pain-QuILTTM is a property of McMaster University and is subject to McMaster University's terms of use. It can be accessed here

The iconographic symptom encoding could be applied easily to dermatology as well. Dermatology lesions are primarily visual and dermatological diagnosis to a great extend is based on the type, distribution, intensity and temporal characteristics of the skin lesions. However the representation may be challenging because of the diverse nature of lesions.

Recently I came across fabric.js a javascript library for image manipulation based on HTML5 canvas. Fabric.js was much more versatile and powerful than I expected. I could prototype  LesionMapperTM (that is what I want to call it), in less than 24 hours. The type of lesions are symbolized by representative clinical pictures instead of icons, intensity is represented by the opacity/translucency of the image and the location and distribution by the position and size of the lesion respectively, on the body image. The images can be dragged, enlarged or rotated.

Febrile neutrophilic dermatosis
Febrile neutrophilic dermatosis (Photo credit: Wikipedia)
The icing on the cake is the ability of fabric.js to rasterize the image into a JSON that can be stored easily in a database. LesionMapper allows you to save the LesionMap for 6 months and can be rendered back by providing the ID. If you want to include this as an Electronic Health Record system plugin, do give me a shout by clicking on Contact Me on the menu above.

Take a look at LesionMapper(TM) here!

Labels: ,

commentAdd Your Comments/Suggestions/Criticisms! | View Comments | Links to this post

GIT for doctors (Part 3) - stash, branch, merge, rebase and tag

To continue with our git story: Read the full series on GIT for doctors here

If you think you have made a mistake, you can “stash” the changes. Your file will be returned to the previous state. You have the option of returning to the stash if needed, but this is beyond our scope at present.

Now let us consider another scenario: You have two differential diagnosis for your patient and you want to investigate the patient for both conditions. You may decide to keep two versions of the same case sheet to continue the work up on both differentials. In Git you can create a “branch” for this situation. You can work on branches independently. The main branch or the trunk is called “master” by convention. You can give any name for the other branches.

Embiodea (Photo credit: beapen)
If you decide to consult your colleague, he/she may want to continue working on their copy without changing the “master” file in your possession. So they can work on their “branches” too. Later on if you want to add your differential branch or your colleague’s branch into the master file, you can choose “merge”.

You can create branches of branches. If you want to merge several such branches into the “master”, you have to paste all branches together into a single branch. This is called “rebase”.

If you have to submit a master chart for audit, you can “tag” the chart, so that you can give a name to the current state. “Tagging” for software is generally done when you decide to release a version to the end user.

In the next part, I will discuss how to collaborate with your friends. If you are not on as yet, do register for an account now. If you want to follow someone, let me suggest yours truly:

Read the full series on GIT for doctors here

Labels: ,

commentAdd Your Comments/Suggestions/Criticisms! | View Comments | Links to this post

Psoriasis support : eHealth gaming tools for patient engagement

Psoriasis manum
Psoriasis manum (Photo credit: Wikipedia)

Here is the IFPA  survey to compare 17 different strategies and activities that can be used to advance psoriasis education, advocacy and awareness. Preliminary results of the survey will be presented on World Psoriasis Day and the final results will be announced at the 4th World Psoriasis & Psoriatic Arthritis Conference in Stockholm July 8-11, 2015.

I have listed below some of my random ideas on eHealth tools for patient engagement in psoriasis:

Read more »

Labels: , ,

commentAdd Your Comments/Suggestions/Criticisms! | View Comments | Links to this post

Resource Description Framework (RDF) and Population Informatics

A PICTURE OF A RDF (Photo credit: Wikipedia)
I have been an RDF fan even before I used it for dermbase. I promptly signed the Yosmite Manifesto and blogged about it last year. After gaining more experience in the regional health information exchange initiative(s), I still feel that RDF is important, but in a different way.

Most federated regional clinical viewers query host databases, convert the results into an intermediary format (mostly xml or HL7), apply filters and then provide a consolidated view in the browser and mobile as html embellished with jQuery. Though this seems not-so-scalable technology, it works remarkably well in a regional context. Federated clinical viewers also attempt to create data warehouses on top of the Clinical Viewer. Such data warehouses have enormous potential in population informatics and RDF could be an ideal framework for this purpose.

RDF is a proven technology that is schema agnostic. However in this context the biggest advantage of RDF is its data-atomic nature that enables each data element to be queried, changed, or deleted independent of any other data element. RDF blank nodes can be used to effectively anonymize the data. From a data analytics perspective representation in the RDF format makes data amenable for “reasoning” to discover new knowledge.

Genomic data analytics has revolutionized pre-clinical research. Growing popularity of Health Information Technology (HIT) and Health Information Exchange (HIE) has not yet resulted in a similar impact on population health. There are some fundamental differences between genomic and clinical data.

Read more »

Labels: , , ,

commentAdd Your Comments/Suggestions/Criticisms! | View Comments | Links to this post

SUSie: SUS based questionnaire for assessing usability and physician attitude toward health information exchange

evaluation of eyetracking after an usability test
evaluation of eyetracking after an usability test (Photo credit: Wikipedia)
Health information exchange (HIE) allows healthcare providers and patients to access and securely share medical information electronically. Several organizations are now emerging to provide both form and function for HIE efforts, both on independent and governmental/regional levels. However the biggest challenge is Change Management, as healthcare providers are exposed to one more ICT tool that they need to master for providing quality care.

There are no formal tools to study individual and organizational attitude towards HIE or to measure their usability. Physician attitude towards the impact of HIE on reducing healthcare costs, improving quality of patient care, saving time and their concern about data privacy and security are important in HIE adoption. Usability is also of vital importance in the meaningful use of HIE tools.

SUSie (SUS for HIE) is an attempt at creating a useful tool for measuring the above factors. It is modelled based on System Usability Scale (SUS), one of the most used questionnaire for measuring perceptions of usability. Five additional questions were added to assess factors that are specific for HIE. The scoring is based on a scale of 5 ranging from Strongly disagree(1) to Strongly agree (5). The ratio of positively and negatively worded questions are maintained and the final multiplication factor was changed to 1.67 to represent the final score on a scale of 100. I hope that this would make the interpretation similar to SUS and benefit from the prior experience available for SUS. The questions and details of scoring are explained below.

Read more »

Labels: , , , ,

commentAdd Your Comments/Suggestions/Criticisms! | View Comments | Links to this post

Git for Doctors and healthcare professionals - 2

Read the full series on GIT for doctors here

Imagine that you have a patient's case file in a folder on your computer. The file has many contents such as history sheets, lab reports and discharge summaries.

[Create a folder in your computer with few word files. This folder is your case file.]

Since the case file is precious, you want to take a photocopy before you change/add anything to the file. So you decide to buy a photocopy machine. In 'GIT' instead of the photocopy machine you 'create a repository'

[Click on create repository and choose the folder.]

Now you have to decide what to photocopy. Let us say, you decide to photocopy everything. Deciding what to photocopy is called staging in GIT.

[Select All – and 'Add to Index']

Now go ahead and take the photocopy. In GIT it is called Commit

[Click commit]

Congrats.. You have photocopied the contents. Now you can safely add your comments.

[Add some text to any of the files.]

Now you want to photocopy again so that, what you have added is not lost when you make changes again.

[Go back to sourcetree. It will display the changed file. 'Add to index' & Commit. You will be asked to add a comment, though it is optional.]

Now you have 2 photocopies.

But wait.. You find out that what you added to the file during your last edit was wrong. How do you remove what you added or go back to a previous stage?

Wait for a week to find out!: Read the full series on GIT for doctors here


commentAdd Your Comments/Suggestions/Criticisms! | View Comments | Links to this post

About Me

As a Dermatologist and Informatician my research mainly involves application of bioinformatics techniques and tools in dermatological conditions. However my research interests are varied and I have publications in areas ranging from artificial intelligence, sequence analysis, systems biology, ontology development, microarray analysis, immunology, computational biology and clinical dermatology. I am also interested in eHealth, Health Informatics and Health Policy.


Bell Raj Eapen
Hamilton, ON