ENTRIES TAGGED "medical"

Combining personal data with ratings for targeted medical information

HealthTap refines the answers returned to specific health queries

HealthTap is a community of doctors and clients seeking answers to health questions. Its central service provides immediate access to doctors and their knowledge either by doctors answering client questions in real time, or through a large database of previously answered questions and answers from doctors that are peer reviewed and tagged with recommendations by other doctors. By combining the doctors’ recommendations with data provided by each client on himself or herself, HealthTap provides customized results to queries. In this video, HealthTap CEO Ron Gutman explains unexpected lessons they’ve learned from offering the intelligent search service.

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Ginger.io: Putting the Patient-Provider connection at the center

A tool for outreach to patients produces unexpected benefits

This posting was written by guest author Julia Bernstein of Ginger.io. Ginger.io’s CEO Anmol Madan will be speaking on this topic at Strata Rx.

The traditional, office-based model for health care is episodic. The provider-patient relationship exists almost completely within the walls of the exam room, with little or no follow-up between visits. Data is primarily episodic as well, based on blood pressure reading done at a specific time or surveys administered there and then, with little collected out of the office. And even the existing data collection tools—paper diaries or clunky meters—are focused more on storing data that on connecting the patient and provider through that data in real time.

There is no way to get in touch when, for instance, a patient’s blood sugar starts varying wildly or pain levels change. The provider often depends on the patient reaching out to them. And even when a provider does put into place an outreach protocol, it is usually very crude, based on a general approach to managing a population as opposed to an understanding of a patient. The end result is a system that, while doing its best within a difficult setting, is by default reactive instead of proactive.

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The Role of Big Data in Personalizing the Healthcare Experience: Mobile

Sensors, games, and social networking all create change in health and fitness

This article was written with Ellen M. Martin and Tobi Skotnes. Dr. Feldman will deliver a webinar on this topic on September 18 and will speak about it at the Strata Rx conference.

Cheaper, faster, better technology is enabling nearly one in four people around the world to connect with each other anytime, anywhere, as online social networks have changed the way we live, work and play. In healthcare, the data generated by mobile phones and sensors can give us new information about ourselves, extend the reach of our healers and help to accelerate a societal shift towards greater personal engagement in healthcare.

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Cancer and Clinical Trials: The Role of Big Data In Personalizing the Health Experience

Big Data and analytics are the foundation of personalized medicine

This article was written with Ellen M. Martin and Tobi Skotnes. Dr. Feldman will deliver a webinar on this topic on September 18 and will speak about it at the Strata Rx conference.

Despite considerable progress in prevention and treatment, cancer remains the second leading cause of death in the United States. Even with the $50 billion pharmaceutical companies spend on research and development every year, any given cancer drug is ineffective in 75% of the patients receiving it. Typically, oncologists start patients on the cheapest likely chemotherapy (or the one their formulary suggests first) and in the 75% likelihood of non-response, iterate with increasingly expensive drugs until they find one that works, or until the patient dies. This process is inefficient and expensive, and subjects patients to unnecessary side effects, as well as causing them to lose precious time in their fight against a progressive disease. The vision is to enable oncologists to prescribe the right chemical the first time–one that will kill the target cancer cells with the least collateral damage to the patient.

How data can improve cancer treatment

Big data is enabling a new understanding of the molecular biology of cancer. The focus has changed over the last 20 years from the location of the tumor in the body (e.g., breast, colon or blood), to the effect of the individual’s genetics, especially the genetics of that individual’s cancer cells, on her response to treatment and sensitivity to side effects. For example, researchers have to date identified four distinct cell genotypes of breast cancer; identifying the cancer genotype allows the oncologist to prescribe the most effective available drug first.

Herceptin, the first drug developed to target a particular cancer genotype (HER2), rapidly demonstrated both the promise and the limitations of this approach. (Among the limitations, HER2 is only one of four known and many unknown breast cancer genotypes, and treatment selects for populations of resistant cancer cells, so the cancer can return in a more virulent form.)

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Clinical discovery in the age of “Big Data”

Modern data processing tools, many of them open source, allow more clinical studies at lower costs

This guest posting was written by Yadid Ayzenberg (@YadidAyzenberg on Twitter). Yadid is a PhD student in the Affective Computing Group at the MIT Media Lab. He has designed and implemented cloud platforms for the aggregation, processing and visualization of bio-physiological sensor data. Yadid will speak on this topic at the Strata Rx conference.

A few weeks ago, I learned that the Framingham Heart Study would lose $4 million (a full 40 percent of its funding) from the federal government due to automatic spending cuts. This seminal study, begun in 1948, set out to identify the contributing factors to Cardiovascular Disease (CVD) by following a group of 5,209 men and woman and tracking their life style habits, performing regular physical examinations and lab tests. This study was responsible for finding the major risk factors for CVD, such as high blood pressure and lack of exercise. The costs associated with such large-scale clinical studies are prohibitive, making them accessible only to organizations with sufficient financial resources or through government funding.
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Genomics and the Role of Big Data in Personalizing the Healthcare Experience

Increasingly available data spurs organizations to make analysis easier

This article was written with Ellen M. Martin and Tobi Skotnes. Dr. Feldman will deliver a webinar on this topic on September 18 and will speak about it at the Strata Rx conference.

Genomics is making headlines in both academia and the celebrity world. With intense media coverage of Angelina Jolie’s recent double mastectomy after genetic tests revealed that she was predisposed to breast cancer, genetic testing and genomics have been propelled to the front of many more minds.

In this new data field, companies are approaching the collection, analysis, and turning of data into usable information from a variety of angles.
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The Next “Top 5%”: Identifying patients for additional care through micro-segmentation

Health data can go beyond the averages and first order patient characteristics to find long-term trends

This article was written with Arijit Sengupta, CEO of BeyondCore. Tim and Arijit will speak at Strata Rx 2013 on the topic of this post.

Current healthcare cost prevention efforts focus on the top 1% of highest risk patients. As care coordination efforts expand to a larger set of the patient population, the critical question is: If you’re a care manager, which patients should you offer additional care to at any given point in time? Our research shows that focusing on patients with the highest risk scores or highest current costs create suboptimal roadmaps. In this article we share an approach to predict patients whose costs are about to skyrocket, using a hypothesis-free micro-segmentation analysis. From there, working with physicians and care managers, we can formulate appropriate interventions.

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One-click analysis: Detecting and visualizing insights automatically

Arijit Sengupta of BeyondCore uncovers hidden relationships in public health data

The importance of visualizing data is universally recognized. But, usually the data is passive input to some visualization tool and the users have to specify the precise graph they want to visualize. BeyondCore simplifies this process by automatically evaluating millions of variable combinations to determine which graphs are the most interesting, and then highlights these to users. In essence, BeyondCore automatically tells us the right questions to ask of our data.

In this video, Arijit Sengupta, CEO of BeyondCore, describes how public health data can be analyzed in real-time to discover anomalies and other intriguing relationships, making them readily accessible even to viewers without a statistical background. Arijit will be speaking at Strata Rx 2013 with Tim Darling of Objective Health, a McKinsey Solution for Healthcare Providers, on the topic of this post.

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Donald Berwick discusses health care improvement: goals, exemplary organizations,and being at a turning point

A video interview with entrepreneur Colin Hill

Last week, a wide-ranging interview on data in health care took place between Dr. Donald Berwick and Colin Hill of GNS Healthcare. Dr. Berwick and Hill got together in the Cambridge, Mass. office of the Institute for Healthcare Improvement, a health care reform organization founded by Dr. Berwick, to discuss data issues related to O’Reilly’s upcoming Strata Rx conference.

Berwick returned to IHI after his year as administrator of Centers for Medicare & Medicaid Services. Throughout these changes he has maintained his stalwart advocacy for better patient care, a campaign that has always been based on a society’s and a profession’s moral responsibility. Even an IHI course for the “Patient Safety Executive” program puts “Building a just culture” on its agenda.

Among the topics Berwick and and Hill look at in these videos are the importance of transparency or “turning on the lights,” ways of learning from the health provider system itself as well as from clinical trials, types of personalized medicine, the impediments to collecting useful data that can improve care, exemplary organizations that deliver better healthcare, and how long change will take.

The full video appears below.

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Open source software creeps in to health care through clinical research

Report from OpenClinica conference

Although open source has not conquered the lucrative market for electronic health records (EHRs) used by hospital systems and increasingly by doctors, it is making strides in many other important areas of health care. One example is clinical research, as evidenced by OpenClinica in field of Electronic Data Capture (EDC) and LabKey for data integration. Last week I attended a conference for people who use OpenClinica in their research or want to make their software work with it.

At any one time, hundreds of thousands of clinical trials are going on around the world, many listed on an FDA site. Many are low-budget and would be reduced to using Excel spreadsheets to store data if they didn’t have the Community edition of OpenClinica. Like most companies with open-source products, OpenClinica uses the “open core” model of an open Community edition and proprietary enhancements in an Enterprise edition. There are about 1200 OpenClinica installations around the world, although estimation is always hard to do with open source projects.

What is Electronic Data Capture? As the technologically archaic name indicates, the concept goes back to the 1970s and refers simply to the storage of data about patients and their clinical trials in a database. It has traditionally been useful for reporting results to funders, audit trails, printing in various formats, and similar tasks in data tracking.

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