In January, a brilliant OpEd ran in the New York Times in response to an MIT Technology Review piece that warned about the lack of transparency in the decision-making process for AI systems. In addition to likening AI systems to “black boxes”, they culminated with a warning that “no one really knows how the most advanced algorithms do what they do”. Talk to any data scientist who works with NLP and AI systems and they’ll fundamentally disagree with this stance (and likely side with our champion at the New York Times).
Natural language processing (NLP) is an important aspect of artificial intelligence that allows machines to process large amounts of data in human (natural) language - for instance, open-text fields or speech-to-text data. With NLP, just as with human language, it is critical that the machine is able to distinguish three things: content, concept and context.
Pieces Technologies has implemented its decision support software solutions - Pieces Decision Support (DS) and Pieces Iris - throughout health systems and community-based organizations nationwide. When we began, we knew we needed a hosting partner that would allow us to scale quickly and provide unparalleled security. We chose Amazon Web Services (AWS) due to their remarkable experience: the largest cloud provider, highest ranked by Gartner among competitors, and deep healthcare client base.
The delivery of high performance clinical care – care that is reliable, efficient, and timely – is difficult. Even under the best marriage of clinical workflow and algorithmic modeling, unpredictable adverse outcomes can occur in the modern clinical practice. Many analytics vendors address this through human oversight of their artificial intelligence (AI) algorithms.
“Writing in English is like throwing mud at a wall.”
― Joseph Conrad
I recently watched the 2016 movie “Arrival.” The film explores the idea that what you think and how you think may actually be closely intertwined. “Arrival” is a story about humanity’s first contact with aliens and how a pair of scientist find ways to communicate without a common language. As they spend more and more time with the octopus-like creatures, they get increasingly frustrated with their lack of progress and must get creative in order to effectively communicate with these new visitors to Earth. I won’t spoil it for you, but this film beautifully illustrates how powerful and difficult the use of language can be, whether it’s between a linguist and a 10-foot-tall mollusk or with each other.
CMS Dollars Part 1: IPPS Made Simple Protecting Your Hospital Nest Egg
Nadia Christensen, MD
Hospital margins are narrower than ever, and hospitals dedicate many resources to understanding and capturing their reimbursement dollars. Medicare is the single largest purchaser of healthcare in the US – spending $610B in 2014, which is almost a quarter of all spending on medical goods and services. With inpatient hospital reimbursement being one of the largest pieces of the pie, accounting for 23% of all Medicare spending, sharing how Medicare regulations affect your hospital reimbursement with your staff is paramount in protecting your nest egg of reimbursement dollars. This is the first in a series of blogs simplifying complex CMS reimbursement programs.
The Boomerang Effect
CMS Dollars Part II: HRRP Made Simple The Boomerang Effect
Nadia Christensen, MD
Hospital readmissions account for a huge portion of US healthcare costs. As clinicians we are always trying to understand the root cause of why one of our patients might bounce back. In some circles, we refer to this as the boomerang effect.
Over the years, in an effort to stem the rising costs of healthcare dollars spent on readmissions, CMS has created many programs to encourage hospitals to address this problem. One of these programs is the Hospital Readmission Reduction Program (HRRP). HRRP was established by the Affordable Care Act in 2012 and required CMS to reduce payments to hospitals with excess readmissions.
The Unwanted Visitor
Nadia Christensen, MD
Unfortunately, it happens all the time. You take your elderly father into the hospital for a routine surgery such as a total hip replacement, and while being treated for the hip, he ends up with a Hospital-Acquired Condition (HAC). Think of an HAC as your bothersome Aunt Ethel, an unwanted house guest who shows up when you least expect her, bringing in suitcases full of complications, and leaving a trail of havoc in her wake. Simply stated, an HAC is a potentially avoidable infection or complication that occurs while a patient is hospitalized for an unrelated condition. Years ago, people referred to these conditions as Healthcare-Associated Infections (HAIs) or nosocomial infections. However, today many preventable conditions, which are not infections such as pressure ulcers or DVTs, have been added to the list and term broadened to HACs.