Posts from July 2014

Healthcare
Simon Beaulah

IBM Watson gets a lot of attention in the medical field for trying to take capabilities that were demonstrated on the Jeopardy TV show and apply that cognitive reasoning to clinical care.

The complexities of disease combined with the mass of medical literature and clinical guidelines make this high dimensional problem an appropriate challenge for an industrial power house.

However, it should not be underestimated what can be achieved using sophisticated Natural Language Processing (NLP) for information retrieval in clinical decision support.

One of my favourite customer stories in recent years concerns our work with medical librarian Jonathan Hartmann from Dahlgren Memorial Library, the health sciences library at Georgetown University.

Jonathan’s role is to support the teams on the hospital’s paediatrics and internal medicine units on rounds at the Georgetown University Medical Center with access to the latest medical insights and publications relating to the current patient.

For example, should a patient with metastatic renal cell carcinoma be given warfin (an anticoagulant) for stroke prevention? Using his iPad at the bedside, Jonathan was able to quickly find journal articles that indicated cancer treatments and potentially cancer spread can indeed increase the risk of stroke.

You can read more about the story here.

From a technical perspective the use of NLP in this scenario is well hidden, as it should be, and simply ensures that the right information is provided to assist in clinical decision making.

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You can read the article, here.

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Life sciences
Jane Reed

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?

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Healthcare
Jonathan Hartmann

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.

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