EHR systems are now collecting invaluable information that physicians can use to detect disease patterns, clusters of patients exposed to specific toxins, and groups of patients who respond well to various drug regimens. We can't waste this gold mine.
Healthcare providers are being pushed to deliver more cost effective medical care and to improve the health of not just individual patients but large populations. One key to carrying out both mandates is finding more clinically effective treatment options.
Many academic medical thought leaders insist that the best way to find those treatment protocols is to test them in randomized controlled trials. Such RCTs require a large group of control subjects to receive either a placebo or conventional therapy and a large group to receive the experimental treatment in question. The problem is RCTs are outrageously expensive. In today's cost conscious healthcare system, that's a problem.
Enter comparative effectiveness research. CER compares two or more accepted treatments to determine which are most effective. Medical informatics comes into the picture because it's now possible to get these projects off the ground by analyzing huge patient databases. And much of that patient data can now be gleaned from electronic health record systems.
That's not an idea modern society seems to care much about anymore.
So how do health IT professionals, who are busy planning for tomorrow, convey the importance of their activities to individuals and colleagues who are concerned only about what they need today? To bridge that chasm, you first must convey to them why your health IT activities will be important in the future, no small task considering the complexities of HIT architecture and healthcare standards.
And why, exactly, are your health IT activities important? It's simple: patient care.
Last few years have seen acceleration in adoption of health IT systems. Below is a fantastic infographic from OBizMedia showing how information technology is changing the way medical information is gathering, accessed, reported, shared, and analyzed.
Envisioning the Future of Health. The good folks at Fast Company sourced an interesting visualization from futurist Michell Zappa and the Envisioning Tech crew. Lots of science fiction, but it provides an interesting analysis ...
In the Affordable Care Act environment, healthcare providers have a real opportunity to transform the way they treat people. The objective? Delivering a better patient experience, with improved results, at lower costs. The key to this transformation is digital health technology.
2013 has been a big year for health IT and sets the stage for 2014 to be a pivotal time as IT plays an integral part in healthcare transformation.
Paul Aneja - eTrends's insight:
HealtthIT 2013 Year Review. Health information exchange has become more widespread and is showing itself to be a key enabler of both health system transformation and improved care coordination. Patient engagement was a big theme in 2013 and we may have reached a tipping point in empowering patients with health information and truly making them a part of the care team. EHR Adoption is high. #HealthIT
It isn’t often that I come across an article that truly resonates with me, but Next-Generation Phenotyping of Electronic Health Records, by Hripcsak and Albers, did just that. While the authors’ main focus is EHR data quality, they make this intriguing observation/suggestion:
It will require study of the EHR as if it were a natural object worthy of study in itself (emphasis mine), and it may be helpful to employ the general paradigm of physics, which involves modeling and aggregation. It will be helpful to pull in expertise and algorithms from many fields, including non-linear time series analysis from physics, new directions in causality from philosophy, psychology, economics, of course our usual collaborators in computer science and statistics, and even new models of research that engage the public.
I absolutely agree–it is time to start treating EHR systems as more than front ends to data stores. Considering the role that EHR systems are expected to play in improving healthcare quality and safety while lowering or stabilizing costs, the design of clinical systems is rarely discussed in the literature. As I have mentioned in previous posts, most EHR-related standards address the content and features EHR systems should have, but specifically disclaim any concern about how systems should be built. It’s almost as if the prevailing attitude is that EHR design and architecture are straightforward and require little real intellectual input. This raises another issue that I think deserves discussion—the intellectual work of software development.
IBM Research (@IBMResearch) may be best known for its scientists who have created technology breakthroughs from moving atoms to analytics systems like IBM Watson. But what might surprise many is the number of deep subject matter experts now working side-by-side with computer scientists to redefine how industries apply technology to improve the services they offer.
The world's healthcare systems, for example, are aging and increasingly complex. Despite amazing advances in medicine and patient care, the system is still plagued by misdiagnosis, misaligned incentives that increase cost, and lack of access to the latest information on patient medical history and treatment options.
Today, a team of medical doctors with more than a century of combined experience is working inside IBM Research with scientists from a variety of disciplines. They are examining ways to improve the healthcare system from all angles - from using data analytics for better-informed diagnoses to understanding why certain diseases flourish in some regions of the world but not others. Perhaps most importantly, they are helping researchers deepen their understanding of the industry, in order to apply technology more effectively.
In the U.S. alone, it is estimated that up to 20 percent of diagnoses are either incorrect or incomplete. In addition, there are an estimated 1.5 million errors in the way medications are prescribed, delivered and taken in the U.S. every year.
These mistakes could be greatly reduced if doctors had access to the latest relevant medical information. But there is so much medical data in the world that it is impossible to keep track of it all.
The MDs are now working with researchers to apply IBM Watson's capabilities to answer natural language queries - which it first demonstrate by defeating the world's best human contestants on the quiz show Jeopardy! - to search through tremendous amounts of both structured and unstructured medical data, from journals to CAT scans, to provide practitioners with vital information.
"Watson will leverage existing evidence in new ways," said Josko Silobrcic, MD, Senior Medical Scientist at IBM Research, "and with natural language processing and machine learning, it may uncover new patterns that may not have been recognized before."
Martin Kohn, MD, Chief Medical Scientist for Care Delivery Systems at IBM Research, is helping design Watson's capabilities in a manner that best supports the way clinicians work. He said physicians tell him, "I'm looking for something to bring help to me when I need it, in a format that is useful."
This first installment explores how mHealth is enabling a new paradigm where applications use artificial intelligence to simulate the decision-making process, and the challenges developers must overcome to ensure solutions are useful for patients.
As consumers take more and more of their health-care needs into their own hands, developers can profit by helping them take control of their health and wellness through apps and mobile services, Rock Health's CEO told GigaOM's Mobilize conference.
Although the health-care system may not be structured in a way that makes most people care about their health — since they don’t usually have to bear the full costs of illness — there is a growing movement of consumers who want to try and take an active role in maintaining their health, and that can be a profitable market for apps and services, according to Rock Health founder and CEO Halle Tecco.
The New York Times reported recently on the death of an emergency department patient at NYU Langone Medical Center who was discharged before abnormal lab results were received. The patient was told they were suffering from a typical stomach bug, and never told that a lab order was placed. The primary care physician was never made aware of the lab results either.
My objective is to analyze how health IT might have played a role to help in this tragic event. With the formation of HIEs and ACOs along with adherence to Meaningful Use criteria, the goal is that all patients will receive better quality and more efficient healthcare.
Could available health IT standards prevented what happened at NYU? I will attempt to recreate the workflow of healthcare data using the latest standards and communication frameworks available in healthcare.
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