Rock Health News

 

Featured 3/11/15

The most important API you’ve never heard of

Everything you need to know about new FHIR standards for EHR interoperability.

Featured 3/11/15

The most important API you’ve never heard of

Everything you need to know about new FHIR standards for EHR interoperability.

Other 11/19/14

Lessons in big data: From New York to Pasadena

Dr. Nirav R. Shah serves as Kaiser Permanente Southern California’s senior vice president and chief operating officer for Clinical Operations. He previously served as the New York State Health Commissioner, where he oversaw the implementation of a statewide healthcare technology initiative, the creation of a successful health insurance exchange, and the redesign of the Medicaid program. He is a board-certified Internist, an elected member of the Institute of Medicine of the National Academy of Sciences, and formerly served on the faculty of NYU School of Medicine. 1. During your time as NY State Health Commissioner, New York set up a great model for data sharing—what was the biggest win? One of our most notable achievements was creating a statewide network for health information exchange. What does that mean? It means that if you got into a car accident in Buffalo, the doctor could pull up your electronic medical records from Brooklyn. This network for nearly 20 million New Yorkers is funded by the state—which means it’s each and every citizen’s data—not the insurance company’s data or the hospital’s data. As a New Yorker, you will have full access to your records through a patient portal (or can download the data…

Other 11/19/14

Lessons in big data: From New York to Pasadena

Dr. Nirav R. Shah serves as Kaiser Permanente Southern California’s senior vice president and chief operating officer for Clinical Operations. He previously served as the New York State Health Commissioner, where he oversaw the implementation of a statewide healthcare technology initiative, the creation of a successful health insurance exchange, and the redesign of the Medicaid program. He is a board-certified Internist, an elected member of the Institute of Medicine of the National Academy of Sciences, and formerly served on the faculty of NYU School of Medicine. 1. During your time as NY State Health Commissioner, New York set up a great model for data sharing—what was the biggest win? One of our most notable achievements was creating a statewide network for health information exchange. What does that mean? It means that if you got into a car accident in Buffalo, the doctor could pull up your electronic medical records from Brooklyn. This network for nearly 20 million New Yorkers is funded by the state—which means it’s each and every citizen’s data—not the insurance company’s data or the hospital’s data. As a New Yorker, you will have full access to your records through a patient portal (or can download the data…

Research 10/27/14

Predictive Analytics: The Future of Personalized Health Care

Personalized medicine, a deterministic model that argues medical science, specifically molecular data, will be able to provide tailored, individual care, has yet to deliver on the promise of its powers. In the meantime, its precursor, predictive analytics, which has proven effective in many industries, is now tackling the healthcare industry. Predictive analytics isn’t anything new (think Amazon, Netflix, and Google searches). It’s simply the process of learning from historical data to make predictions about the future or any unknown. And in healthcare, this is what physicians do every day—look at patient symptoms and apply training and experience to diagnose and predict the best treatment. Taking what physicians do and scaling it with technology enables calculated probabilities to deliver more personalized care. Digital health venture funding reflects the interest in finding the best treatment for each patient with $1.9B raised for companies utilizing predictive analytics. (Note: For the purpose of this report, the scope of predictive analytics only includes companies using algorithms to directly impact patient care. We’re focused on solutions such as clinical decision support, readmission prevention, adverse event avoidance, disease management, and patient matching.)

Research 10/27/14

Predictive Analytics: The Future of Personalized Health Care

Personalized medicine, a deterministic model that argues medical science, specifically molecular data, will be able to provide tailored, individual care, has yet to deliver on the promise of its powers. In the meantime, its precursor, predictive analytics, which has proven effective in many industries, is now tackling the healthcare industry. Predictive analytics isn’t anything new (think Amazon, Netflix, and Google searches). It’s simply the process of learning from historical data to make predictions about the future or any unknown. And in healthcare, this is what physicians do every day—look at patient symptoms and apply training and experience to diagnose and predict the best treatment. Taking what physicians do and scaling it with technology enables calculated probabilities to deliver more personalized care. Digital health venture funding reflects the interest in finding the best treatment for each patient with $1.9B raised for companies utilizing predictive analytics. (Note: For the purpose of this report, the scope of predictive analytics only includes companies using algorithms to directly impact patient care. We’re focused on solutions such as clinical decision support, readmission prevention, adverse event avoidance, disease management, and patient matching.)

Top 10 Datasets for Health Hackers

We’ve seen glimpses of what big data can do to help provide solutions in healthcare–and we’re excited. Access to patient and cost data is key to actionable and relevant insight, but the healthcare system today doesn’t make this information readily available. Hopefully, we will soon be in a world with established data standards that allow for the frictionless transfer of valuable data across systems and interested stakeholders. But until then, here are our favorite datasets for health hackers. Real-time data: Insight by Practice Fusion is a real-time healthcare database based upon records of over 250K patients per day. You’ll be able to see information like disease trends over time and by patient, what diseases are being diagnosed, and real-time prescription drug market share. Validic is a technology platform for accessing data from mobile health devices, in-home devices, and patient healthcare apps. Similarly, Human API is providing the data infrastructure to allow for simple integration of health data. For developers who want to be connected to the healthcare system and leverage publicly available datasets, check out AT&T’s mHealth initiative.

Top 10 Datasets for Health Hackers

We’ve seen glimpses of what big data can do to help provide solutions in healthcare–and we’re excited. Access to patient and cost data is key to actionable and relevant insight, but the healthcare system today doesn’t make this information readily available. Hopefully, we will soon be in a world with established data standards that allow for the frictionless transfer of valuable data across systems and interested stakeholders. But until then, here are our favorite datasets for health hackers. Real-time data: Insight by Practice Fusion is a real-time healthcare database based upon records of over 250K patients per day. You’ll be able to see information like disease trends over time and by patient, what diseases are being diagnosed, and real-time prescription drug market share. Validic is a technology platform for accessing data from mobile health devices, in-home devices, and patient healthcare apps. Similarly, Human API is providing the data infrastructure to allow for simple integration of health data. For developers who want to be connected to the healthcare system and leverage publicly available datasets, check out AT&T’s mHealth initiative.

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