News

Health Organizations Implore Congress to Fund Public Health Surveillance Systems

HLN Consulting joined more than eighty organizations, institutions, and companies in imploring Congress to fund public health surveillance systems. The appropriations request letters – one to the House and one to the Senate – seek one billion in funding over ten years (and $100 million in FY 2020) for the Centers for Disease Control and Prevention (CDC). This funding would allow CDC, state, local, tribal, and territorial health departments to move from sluggish, manual, paper-based data collection to seamless, automated, interoperable IT systems and to recruit and retain skilled data scientists to use them.

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Machine Learning in Healthcare: Part 3 - Time for a Hands-On Test

Every inpatient and outpatient EHR could theoretically be integrated with a machine learning platform to generate predictions, in order to alert clinicians about important events such as sepsis, pulmonary emboli, etc. This approach may become essential when genetic information is also included in the EHR which would mandate more advanced computation. However, using machine learning and artificial intelligence (AI) in every EHR will be a significant undertaking because not only do subject matter experts and data scientists need to create and validate the models, they must be re-tested over time and tested in a variety of patient populations. Models could change over time and might not work well in every healthcare system. Moreover, the predictive performance must be clinically, and not just statistically significant, otherwise, they will be another source of “alert fatigue.”

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White Paper: Stop the Referral Problem - Building Digital Care Transitions that Reach Your Entire Network

The healthcare industry has crossed a digital chasm-at least in part. Patient records have moved from paper to computer and many transactions, such as e-prescribing and lab orders have been automated, to accelerate workflows, minimize mistakes and reduce costs. But when it comes to sharing patient records, especially beyond the four walls of a hospital, we remain in the dark ages of paper and fax...In this paper, we will discuss our research about how referrals and care transitions are typically conducted; the financial, non-financial, and quality impacts on patient care; and near-term opportunities for leveraging technology to accelerate these processes to benefit provider organizations and to deliver a high-quality, efficient patient experience.

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Is WeWork's Ecosystems Approach a Model for Healthcare Platforms?

Maybe you don't work in a WeWork office setting. Maybe you haven't ever visited one. Maybe you haven't even heard of WeWork. In that case, then you'll probably be surprised that this audacious real estate start-up now has a valuation close to $50b, with over 400,000 "members" in 100 cities across 27 countries (and they claim to "touch" 5 million people worldwide). Or that their plans go well beyond their unique twist towards office sharing. Who in healthcare is thinking about them, and who should be worried...or intrigued?...WeWork was never just about finding people and companies office space: it wanted to "help people work to make a life, not just a living." It focused on building a culture in its spaces, complete with amenities and events to help build a community among its members.

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9 Resources for Data Science Projects

Data science, machine learning, artificial intelligence, and deep neural nets are all hot topics these days (and key terms that might help this post with some SEO, unless the AI sees through my attempts). Below I've shared several of the resources I use regularly while working on data science projects over the last few years. I don't read many books, so that I've shared even one is evidence of how important it is. There are enough resources here to get even the most novice engineer started on a path towards data science mastery in this new age where data science skills will be needed at every level. There is a tool for performing the work, a class taught by a renowned Stanford professor, websites with tutorials to give you real-life experience, and a site dedicated to making the latest research available to all for free so you can learn more if you want.

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GAO Report on Patient Matching: Nothing New Under the Sun

On January 15, 2019 the US Government Accountability Office (GAO) released a new report to Congress, Health Information Technology: Approaches and Challenges to Electronically Matching Patients' Records across Providers. This report is in response to the mandate in the 21st Century Cures Act for the GAO to study patient matching. To develop this report, GAO reviewed available literature and interviewed more than thirty-five stakeholders (who are not identified) over the course of a year. I have written several blogs and a feature article on patient matching developments in the US. Similarly, this new GAO report is an excellent retrospective on industry efforts over the past several years.

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Machine Learning in Healthcare: Part 2 - Tools Available to the Average Healthcare Worker

A variety of machine learning tools are now available that can be part of the armamentarium of many industries, to include healthcare. Users can choose from commercial expensive applications such as Microsoft Azure Machine Learning Studio, SAS Artificial Intelligence Solutions or IBM SPSS Modeler. Academic medical centers and universities commonly have licenses for commercial statistical/machine learning packages so this may be their best choice. The purpose of this article is to discuss several free open source programs that should be of interest to anyone trying to learn more about machine learning, without the need to know a programming language or higher math.

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Lost in the Signal...Is Most Healthcare Spending Being Wasted?

I finally got around to reading Bryan Caplan's The Case Against Education: Why the Education System Is a Waste of Time and Money. In it, Dr. Caplan, an economics professor at George Mason University and self-avowed libertarian, argues that, aside from basic literacy and numeracy, our educational system serves less to educate and more as a way to signal to employers who might make good employees. Oh, boy did this book make me think about our healthcare system.Dr. Caplan's views on economic signaling are by no means out of the mainstream, although his application of it to education may be. Think of it this way:

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ONC Releases New NPRM on Interoperability: How Might it Affect Public Health?

On February 11, 2019, the Office of the National Coordinator for Health Information Technology (ONC) released its latest Notice of Proposed Rulemaking (NPRM) to Improve the Interoperability of Health Information. Referred to by some people as the "Information Blocking NPRM," since this was the primary topic anticipated, the document actually covers a host of other topics related to interoperability driven primarily by requirements of the 21st Century Cures Act. Besides the initial text of the NPRM, ONC also released a set of summary slides and fact sheets to help explain the document.

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Getting started as a GitLab contributor

GitLab's open culture is one of its strongest assets and the main reason I use GitLab in DevOps transformations. The community edition's code is open source and the paid version makes its source code available for contributions. These are valuable factors rooted in the company culture its CEO has diligently maintained over the years. It doesn't hurt that its tools are great, too. I believe GitLab's sales and marketing team is the best of any company out there. They have included me as a user, customer, and friend over the last few years, and they are genuine and caring people. This was underscored last year when I wanted to contribute a feature, and GitLab's team went to extraordinary lengths to help me succeed. Here's the story of making my first contribution to GitLab.

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