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: https://www.facebook.com/groups/clinical.bioinformaticians/


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:

An Agent based model (ABM) offers visual simulations of complex systems that can be displayed on a web browser. Psoriasis disease process can be modelled using psoriasis patients as ‘turtles’ with the known probabilities of auto-remission, exacerbation, response to conventional treatments and response to newer drugs added to the model. The patients and caregivers could interact with the model to understand how the treatment decisions affect the quality of life. ABM could be an innovative and useful web based patient education tool that portrays the reality of psoriasis without giving any false promises. Those in the  patient’s circle of care and the patient would understand the odds of improving quality of life.

Psoriasis: The naked truth
Psoriasis: The naked truth (Photo credit: SomosMedicina)
An android or iPhone app to calculate and log the PASI score of the patient would be a less obtrusive disease monitoring tool. The app may be designed to send the log to patient’s caregiver. I have not checked the apple app store or google play, probably such apps already exist.

A ‘push’ strategy such as email alerts is unlikely to work for psoriatics. An innovative strategy game where the body is modelled as a kingdom and the immunological perturbations as a t-cell mutiny could be a useful engagement tool. Vascular and systemic changes could also be part of the game. The game would be web based and would continue for a long time with the patient required to login periodically to make strategic alterations (treatment choices). Everytime the patient login to the game, medication reminders would be displayed. The game would mimic reality with changes reflecting new clinical studies. New clinical studies that has an impact on the ‘game plan’ would be available under the ‘game resources’ for everyone to read. Reading and understanding these resources would improve the performance in the game.

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Resource Description Framework (RDF) and Population Informatics

English: A PICTURE OF A RDF
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.

The fundamental characteristics of genomic data are:

1. The data format is simple though it can be annotated in different ways.
2. Raw data is collected first without consideration of relevance. Hypothesis formulation and analysis come later.
3. The data is mostly anonymous.
4. The format and analysis protocol remain the same.

The clinical data has different characteristics:

1. The data is often complex and hence it is difficult to have a uniform format.
2. Data is collected to prove or disprove a hypothesis/diagnosis. Hence only relevant data is collected.
3. The data is often tagged to an individual.
4. The analysis protocol and data collection depends on the hypothesis/diagnosis.

RDF framework would allow abstracting population data from normal everyday HIE data for clinical practice, but both operating within the same ecosystem. The framework will also allow clinical data to have the analytics friendly qualities of genomic data. The clinical viewer can push data into the RDF repository without a separate warehousing process thereby reducing overhead and increasing relevance. New generation wearable devices and monitors can push anonymized raw data directly into the RDF repository. The privacy and security concerns of this architecture will be minimal.

There is another hitherto unexplored advantage for such a clinical RDF repository. Temporal data related to climate changes and other events such as natural calamities can also be pushed into the “structureless” RDF repository making it possible to assess the population health impact of such events.

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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.

If you use SUSie, please cite this webpage and the articles below:
  • Brooke, J. (1996). "SUS: a "quick and dirty" usability scale". In P. W. Jordan, B. Thomas, B. A. Weerdmeester, & A. L. McClelland. Usability Evaluation in Industry. London: Taylor and Francis.
  • Wright, Adam et al. "Physician attitudes toward health information exchange: results of a statewide survey." Journal of the American Medical Informatics Association 17.1 (2010): 66-70.
  • Eapen BR (2014). “SUSie: SUS based questionnaire for assessing usability and provider attitude toward health information exchange.” Applied Bimatics - An Informatics & eHealth Blog.[Internet] Accessible from: http://bioblog.gulfdoctor.net/2014/06/susie-hie-usability-physician-attitude.html

Questions:

  1. I think that I would like to use this Health Information Exchange System frequently. 
  2. I found this Health Information Exchange System unnecessarily complex. 
  3. I think this Health Information Exchange System will reduce healthcare costs. 
  4. I think that I would need the support of a technical person to be able to use this Health Information Exchange System. 
  5. I thought this Health Information Exchange System was easy to use. 
  6. I thought there was too much inconsistency in this Health Information Exchange System. 
  7. I think this Health Information Exchange System will improve Quality of Patient Care. 
  8. I found this Health Information Exchange System very cumbersome to use. 
  9. I found the various functions in this Health Information Exchange System were well integrated. 
  10. I am concerned about the privacy and security of healthcare information on this Health Information Exchange System. 
  11. I found this Health Information Exchange System can save me time. 
  12. I needed to learn a lot of things before I could get going with this Health Information Exchange System. 
  13. I would imagine that most people would learn to use this Health Information Exchange System very quickly. 
  14. I found that I had to significantly change my workflow to use this Health Information Exchange System.
  15. I felt very confident using this Health Information Exchange System.

SUSie uses the following response format:



Scoring SUSie
  • For odd items: subtract one from the user response.
  • For even-numbered items: subtract the user responses from 5
  • This scales all values from 0 to 4 (with four being the most positive response).
  • Add up the converted responses for each user and multiply that total by 1.67
  • This converts the range of possible values from 0 to 100 instead of from 0 to 60.

Interpreting SUSie (Based on SUS)

  • The value is not a percentage.
  • Average value is approximately 68.
  • This is not a validated questionnaire.
  • A percentile graph for SUS and other relevant information is available here: http://www.measuringusability.com/sus.php (courtesy: Jeff Sauro )
  • SUSie may be used to compare groups or for comparing pre and post intervention.

I have created a wiki page for updates. Please add any use-cases you can think of to the Wiki page.

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Git for Doctors and healthcare professionals - 2

Read Part 1

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!

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GIT for Doctors & healthcare professionals - I

Type 36 JSDF Arm Suit
Type 36 JSDF Arm Suit (Photo credit: Mechanekton)
GIT for us doctors is an acronym for GastroIntestinal Tract. But the GIT I am going to talk about here has nothing to do with GastroIntestinal tract. Do you have any gut feeling about what it is going to be?

Well, GIT according to wikipedia is a distributed revision control and source code management (SCM) system with an emphasis on speed. What has that got to do with healthcare professionals and doctors? As healthcare is becoming tech savvy, healthcare professionals and some doctors have started to recognize and understand, not just completed software products, but their source code as well.

The rising prominence of open-source movement in healthcare will greatly benefit from this, as doctors start contributing actively to healthcare application design and code. When you contribute code to an open-source project, there should be a mechanism to download what others have done, maintain concurrency as others keep adding things, keep track of what you add along with others who contribute, and finally impress the master with your contribution. This process is much more complex than the conventional version control or keeping track of older version by keeping copies of different stages. So that is where GIT steps in.

My aim is not to teach you the nitty-gritties of GIT, so that you will become a master of versioning systems. GIT can be quite challenging for doctors to understand and use. (Can you believe it: It is generally used as a command line tool). My aim is to make you comfortable enough to understand and use GIT in a user-friendly way so that when open source initiatives like openmrs.org talks about using GIT, you will know what they mean. BTW if you use EMRs but have not heard about openMRS.org, do take a look. Maybe you (like me) will also be enticed by their motto “ Write Code. Save Lives.”
Deutsch: Logo von GitHub
Deutsch: Logo von GitHub (Photo credit: Wikipedia)

I will start with actual steps in the next post. In the meantime, join the facebook of GIT called GitHub. https://github.com. If you feel like following someone checkout this guy ;) https://github.com/dermatologist . Don’t download and install anything as yet. Just register for a new account.

Next, download and install this free ‘windows’ to GIT http://www.sourcetreeapp.com/ from a software company called Atlassian. This (surprisingly not so popular yet!) software will make your first experience with GIT painless, I promise.

Will be back again with more. BTW did I tell you that GIT may be useful for collaborative writing too!? Unfortunately GIT was not around when I wrote this article in a dermatology journal in 2007. http://www.ncbi.nlm.nih.gov/pubmed/18032878

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Electronic Health Records heartbleed

Open Source Media Framework Icon
Open Source Media Framework Icon (Photo credit: Wikipedia)
Finally we presented our ultra small EHR project (TED) on wednesday with the promise of pushing it into GitHub as an open-source project soon. The biggest challenge in small turnkey EHRs is data security and privacy. While we were presenting our project the world was desperately seeking the patch for the Heartbleed bug and CRA Canada shut down its portal to avoid any potential data security breach. We are still not sure about the impact of this bug worldwide. So what exactly is heartbleed and how can it effect the burgeoning open-source revolution in health informatics?

Heartbleed is a bug in a widely used open-source encryption method called openSSL. When two computers are securely connected by this method there is a mechanism for periodic checking of this secure connection. We now know that this process was not secure after all, as there was a flow in this method that made the data in the RAM of the computers potentially visible to intruders. The data in the RAM of the computer at any time is likely to be the most sensitive including information such as passwords. This vulnerability was present for almost 2 years till it was spotted recently. Though the obvious question at this point is, who knew about this vulnerability before, the potential ramifications of heartbleed extends right to the heart of the open-source philosophy in secure software systems such as EHRs.

Though it is unlikely, there is a possibility that heartbleed bug was intentionally introduced into the software by someone in the open-source community. This is an eye-opener to massively open-source EHR products. The people managing such open-source projects must be aware of the possibility of a security breach by malicious code introduced by the contributors. It may not be easy to spot such vulnerabilities.

Many EHR systems employ openSSL encryption making them vulnerable to heartbleed. Though patching may happen fast in active and funded projects, it may be delayed for some projects making them potentially vulnerable to heartbleed for extended time. Since this vulnerability is known, the chances of potential exploitation is quite high. Though healthcare data is probably less interesting to hackers than other data sources (contrary to what most of us in eHealth think), heartbleed could give healthcare CEOs some heartburn if not a bleed for days to come.

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Yosemite Manifesto on RDF as a Universal Healthcare Exchange Language

Layered Semantic Web Technology Stack
Layered Semantic Web Technology Stack (Photo credit: jalbertbowdenii)
The Bring Your Own EMR (#BYOE) pronounced 'bio', as explained in my last post relies on a reliable interoperability platform. I have always believed that RDF is the key to successful interoperability. RDF has successfully been employed in several other fields and has many stable tools such as jena. I was searching the web for information on how to present the advantages of an RDF based interoperability platform for healthcare data. Then I found this website.

Yosemite Manifesto, pretty much summarizes whatever I had in mind and a lot more! They are also trying to raise awareness about the possible advantages of adopting the RDF platform by requesting researchers to sign a form. I have already signed. Have you?

I am starting a wiki page for #BYOE too.

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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.

Address

Bell Raj Eapen
Hamilton, ON
Canada