Introducing AI for clinical text interpretation in the 3terra platform
(For a brief overview of clinical text AI and how it will change hospital analytics, please first watch this .) Over the past three years, the advancement of natural language processing (NLP) within healthcare has been remarkable to watch. In that time, a new service model has emerged where the top technology giants (Microsoft, Amazon, IBM, and Google) have released world class medical NLP Application Programming Interfaces (APIs) that enable new opportunities to use unstructured medical text to solve a wide variety of analytical and research problems. We recently completed the integration of Microsoft’s Cognitive Services into our platform to assist in …
How to introduce Machine Learning into your hospital
Machine learning (ML) and Artificial Intelligence (AI) have consistently been the topic of healthcare articles citing advanced applications such as identifying malignant tumors from radiology images or automatically diagnosing patients. There is a very wide spectrum of uses for machine learning, many of which can be applied towards less captivating hospital operational purposes. In this article, I hope to illustrate that there are many hospital Decision Support (DS) problems that can be best solved using ML and that you do not require an advanced degree in mathematics to take advantage of the technology. We use Machine Learning extensively in our …
A guide to successful CDI software initiatives for Ontario hospitals
Over the past decade, Clinical Documentation Improvement (CDI) has become increasingly important as Ontario has moved into data-driven funding mechanisms. With the new focus on financially incentivizing performance across the health system, data quality will continue to be a critical factor as it has been in similar models in other countries. We’ve had the opportunity to work with over 40 hospitals in Ontario to help improve their clinical documentation through the implementation of our Data Quality Assist (DQA) CDI platform. We’ve published this with the hope that it provides insight into common areas that should be considered by Ontario hospitals …
How custom software is hurting your hospital
Through the work that we do, we get to talk to a lot of hospitals about their IT and Decision Support initiatives, and their successes and failures. We’ve seen a pattern where hospitals are facing increasing problems with custom-developed software (internally created or by consultants) whether they are small data management applications or large data warehouses. NOTE: Any custom application code, script, database, report, Excel macro, or analytical view that needs to be developed and maintained by the hospital is considered “software” within the context of this article. SYMPTOMS OF THE PROBLEM The majority of work being assigned to technical …
How to work with physicians to improve data quality and funding
Physicians learn many things during their years of training. Unfortunately for the people who work in hospital Health Records and Decision Support departments, clinical documentation is generally not one of them. HIGH QUALITY PHYSICIAN DOCUMENTATION MATTERS MORE THAN EVER Since the launch of Health System Funding Reform (HSFR) in 2012, up to 70% of a hospital’s annual funding is based on their performance relative to other hospitals in Ontario. Efficiency is measured in terms of cost per weighted case, with the denominator directly coming from the output of Health Information Management (HIM) professionals coding and abstracting from physician documentation of discharged …
The revenue impact of unrecorded emergency department procedures
A central area of expertise at 3terra is helping hospitals improve data quality which can lead to improved funding, as outlined in this article. This year, we expanded our focus and started to analyze the effect of poor data quality on outpatient cases, including Emergency Department (ED) visits. This article provides an overview of those findings. THE METHODOLOGY The case weight (a measure of patient complexity that is used to determine hospital funding) for an ED visit is straightforward compared to inpatient stays. Generally speaking, patients are in the ED for a limited amount of time, so fewer interventions and procedures …
Using data to reduce preventable harm
We’ve recently released our new hospital harm module and have begun working with hospitals to refine the tool and get feedback to guide future functionality. Here is some background and insight into our initial findings. BACKGROUND According to the Canadian Patient Safety Institute (CPSI), approximately 1 in every 18 hospital stays in Canada involve at least one occurrence of preventable harm, resulting in an average of four extra patient days per occurrence. The World Health Organization estimates between 20% to 40% of all health spending is wasted due to poor-quality care. This topic has received increased interest of late because of media attention and the fact that patient …
How data quality affects funding for Ontario hospitals
In 2012, the Ontario government introduced Health System Funding Reform (HSFR) which moved hospitals from global budgets to a form of activity-based funding. Up to 70% of hospital funding in Ontario will eventually be from activity-based allocations. In order for this funding model to work, the Ministry of Health and Long Term Care (MOHLTC) needs an accurate clinical representation of all patients treated by hospitals in the province. They get this information through the submission of patient encounter data files (patient abstracts) by each hospital. After a patient is discharged, coders in health records departments create an abstract designed to tell the story …
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