Skip to main content

Blog

In the current competitive marketplace for healthcare, pharmaceutical and medical technology companies must be able to demonstrate clinical and economic evidence of benefit to providers, healthcare decision-makers and payers.

Now more than ever, pricing pressure and regulatory restrictions are generating increased demand for this kind of outcomes evidence.

Health Economics and Outcomes Research (HEOR) aims to assess the direct and indirect health care costs associated with a disease or a therapeutic area, and associated interventions in real-world clinical practice.

These costs include:

  • Direct economic loss
  • Economic loss through hospitalization
  • Indirect costs from loss of wider societal productivity

The availability of increasing amount of data on patients, prescriptions, markets, and scientific literature combined with the wider use of comparative effectiveness make traditional keyword based search techniques ineffectual. I2E can provide the starting point for efficiently performing evidence based systematic reviews over very large sets of scientific literature, enabling researchers to answer questions such as:

• What is the economic burden of disease within the healthcare system? Across states, and globally?

• Does XYZ new intervention merit funding? What are the economic implications of its use?

• How do the incremental costs compare with the anticipated benefits for specific patient groups?

• How does treatment XYZ affect quality of life? Activities of daily living? Health status indicators? Patient satisfaction?


Last year Georgetown University Medical Center launched the Center for Innovation in Leadership and Education (CENTILE).

In June I presented a poster at the first CENTILE  Colloquium for GUMC Educators in the Health Professions.

My poster Using iPads to Enhance Teaching and Learning on Patient Rounds explained how I have used iPads over the last four years on patient rounds to improve the education of medical students and residents at GUMC. I plan to continue to be involved with CENTILE in the future as I explore further innovative uses of technology in education.

View the original post.


Part of the I2E Enterprise installation is the Sample Web GUI — a Smart Query interface written as a web application that allows users to run smart queries using only their browser.

The Smart Query interface

A neat trick that it performs is on-the-fly class matching: start typing in a word and the server starts to suggest terms in your dictionary that would match. So a search for “psor” will suggest Psoriasis, Psoriatic Arthritis, etc.

Accepting the suggestion will then populate the search with that class rather than the word. The autosuggestion, dropdowns and tooltips are very nice from the user experience perspective, but today’s post will concentrate on the class match itself – how can a search for “psoriasis” retrieve a class match?

There is a two-part answer to that question – the first part is quite easy to answer and the second part is (only slightly) more complicated. So, let’s start with the first part.

Using the query parameters “search”, “pt” or “synonym”

Class matching is a synchronous operation in I2E that uses a query parameter to specify the input and returns the matches as a list/array of classes. Because of this, it’s something that you can try very simply with your web browser. The general form of the URL is (omitting the protocol, servername and port information for brevity):

/api;type=class/pathto/myindex/?search=psoriasis


It’s funny, isn’t it? Search at home just works. You’re looking for a holiday, train times, a particular recipe or the answer to your kid’s homework.

You sit down and type your keyword/s into your search engine. Milliseconds later, results appear – the one you’re looking for is usually one of the first ones – you click on it and voila! You have what you were looking for.

But search at work doesn’t seem to be as effective. Maybe you are looking for information internally. You know it exists but you’re not quite sure where. The information lies across silos and it’s a mix of structured and unstructured.

As a scientist it’s important for you to easily find information hidden in memos, project plans, meeting minutes, study reports, literature etc. You type a keyword search in your enterprise search engine.

A list of documents comes back but none of them look like the one you want. You feel like you’re wasting your time. Sound familiar?

You’re not alone. At least that is what recent surveys and conferences on enterprise search have revealed. According to a recent report from Findwise 64% of organizations say it’s difficult to find information within their organization. Why?

  • Poor search functionality
  • Inconsistencies in how information is tagged
  • People don’t know where to look or what to look for

So how can we address this? Well, there’s already been talk of using text analytics to improve enterprise search.