In a previous blog I discussed the need for a uniformed data structure in healthcare. The concept got me thinking about how to accomplish such a monumental task, and make no mistake, it would be a monumental task. There aren’t many “people” out there that could develop the hardware and software infrastructure solid enough to handle the needs of the complex data stream coming out of the healthcare industry.
Then I noticed a trend at a lot of the web sites that I frequent: Microsoft has slowly, and quietly, been positioning itself to jump into the healthcare market.
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CMIO: “In the past, major barriers to EHR adoption included high upfront costs and lack of IT resources to implement and maintain the technology,” the report stated. “A SaaS model solves both of these issues and Ovum believes it is the best approach for physician offices and small hospitals. With a predictable, monthly expense, a subscription-based SaaS EHR is a much easier cost for providers to swallow.” Speech recognition tools have helped increase EHR adoption among clinicians by increasing the accuracy of the patient health record—providers don’t need to make as many corrections. Speech recognition should feed directly into the PHR without the lag time of transcription, according to the report.” – It makes sense that Software-as-a-Service (SaaS) and speech recognition could be used to increase EHR adoption rates. Together they offer several potential benefits as well as creating a better user experience. In fact, I’m a fan of both and have blogged about how I think they could be used in pharmacy; here and here. However, in regards to speech recognition, an educational session at the 95th Annual Meeting of the Radiological Society of North America (RSNA) reports that “a study by Zoltani and colleagues conducted at their facility found that 68 percent of more than 17,000 finalized reports contained errors, 15 percent of which could potentially change the meaning of the report. A radiologist’s experience, sex and caseload were not associated with significant differences in error rates.”
Over the weekend I spent a little time looking at trends in pharmacy and technology. As expected the healthcare technology market is expanding rapidly and this expansion is creating a need for pharmacists with technology know-how. To prove my point I created a job trends graph from indeed.com using the following search criteria: “pharmacy informatics”, “clinical pharmacist” and “director of pharmacy”. As expected the search trends for “clinical pharmacist” and “director of pharmacy” are relatively flat, but the trend line for “pharmacy informatics” is striking. It looks like a new pharmacy career path is born.
Our facility is running a trial of DynaMed, “an evidence based medicine point-of-care” database. It reminds me of UpToDate.
From the DynaMed site:
• According to the National Academy Press (2001) 44-98,000 American deaths per year occur due to preventable medical errors; medical errors are estimated to cost the U.S. $17 to $29 billion annually
• Using the “best available evidence” for clinical decision-making improves health outcomes and reduces health care costs
• Busy clinicians use “fast and easy” resources expected to answer most of their questions instead of resources designed to provide the best current evidence
• Clinicians sometimes turn to textbooks and online resources with substantial breadth, but these resources do not use the best available evidence
• Physicians and other health care professionals need a resource where they can reliably answer most questions quickly and accurately (i.e., with the best available evidence)
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A friend from Talyst stopped by the pharmacy and spent the greater part of Monday afternoon and Tuesday morning taking a look at what it means to work in an acute care hospital pharmacy. We have several pieces of Talyst automation and technology in our pharmacy and he was interested in how we used it and how it fit into the general scheme of things. As we roamed the pharmacy, I began describing our Pyxis system, how we handle our replenishment, how we put our order away, how we package bulk medications, how we barcode syringes, how we handle an IV batch, how we handle infusions for our smart pumps, and so on and so forth ad infinitum. It was a good exercise for me as it often improves my understanding of something when I try to explain it to someone else.
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The National Library of Medicine has a website know as Pillbox beta that allows anyone to use various identifiers on a tablet or capsule, i.e. imprint, shape, color, size and/or scoring, to quickly identify a medication. I’ve used systems like this many times for the emergency department when a patient would roll in the door with ten different medications all thrown together in a plastic baggie. The nurse would bring them to the pharmacy and say “I need you to tell me what these are”. I tried holding the baggie to my head like the Great Carnac on Carson, but most of the time I had to use other references to help me out.
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The most recent issue of Hospital Pharmacy (Vol 45, No 1, 2010) has an article by Fox and Felkey that discusses the demand that the ARRA will place on the current and future HIT workforce. According to the article “the workforce to shepherd implementation, training, and support [for the modernization of heath care delivery] simply does not exist today; consequently, we could face a situation where health systems and clinics are financially ready to adopt HIT but do not have the personnel to carry it out.” I believe this is absolutely true and have alluded to it in the past (here and here).
More importantly, the shortage of HIT personnel will be further exacerbated by the need for clinicians to enter the technology field. The article supports this thinking by saying that “some experts have suggested that clinically-trained individuals are more suited to the design, selection, implementation, and management of HIT because they have a fundamental understanding of the processes of health care delivery. Alternatively, individuals trained in IT are more technically inclined, but lack firsthand experience with health care delivery systems” Another truism and a problem that is certainly not unique to the HIT field. Companies like Microsoft, Google, GE, Siemens, etc hire pharmacists and other clinician for their unique experience in the health care industry.
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Every pharmacist that has worked in an acute care environment is familiar with documenting interventions. Information from captured interventions is often assigned a dollar value and used by pharmacy and hospital administration to justify pharmacy services or additional pharmacist FTEs.
Interventions captured can range from secondary issues like illegible handwriting and incomplete orders, to pharmacokinetic consults, renal dosage adjustment and prevention of adverse drug events caused by allergies, drug-drug interactions, disease-drug interactions, etc.
Several methods have been used over the years to capture pharmacist initiated interventions, and no two have been the same. I’ve worked at several facilities over the years, and the systems used have included a paper method, a Microsoft Access database, a PDA system built with Pendragon Forms for the Palm Pilot, a third party software system and of course the pharmacy information system (PhIS) itself. Each had advantages as well as disadvantages. The two things they had in common were that they cumbersome and lacked standardization.
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The practice of informatics: Application of information technology: MedEx: a medication information extraction system for clinical narratives
Hua Xu, Shane P Stenner, Son Doan, Kevin B Johnson, Lemuel R Waitman, Joshua C Denny
Abstract
Medication information is one of the most important types of clinical data in electronic medical records. It is critical for healthcare safety and quality, as well as for clinical research that uses electronic medical record data. However, medication data are often recorded in clinical notes as free-text. As such, they are not accessible to other computerized applications that rely on coded data. We describe a new natural language processing system (MedEx), which extracts medication information from clinical notes. MedEx was initially developed using discharge summaries. An evaluation using a data set of 50 discharge summaries showed it performed well on identifying not only drug names (F-measure 93.2%), but also signature information, such as strength, route, and frequency, with F-measures of 94.5%, 93.9%, and 96.0% respectively. We then applied MedEx unchanged to outpatient clinic visit notes. It performed similarly with F-measures over 90% on a set of 25 clinic visit notes.
Xu H, Stenner SP, Doan S, et al. MedEx: a medication information extraction system for clinical narratives. Journal of the American Medical Informatics Association. 2010;17(1):19-24.
2009 brought many new and exciting changes not only in my personal life, but in the world of pharmacy and technology as well. I’ve learned many new things, gained some skills previously absent from my armamentarium, met some great new people, discovered the “real” internet for the first time, traveled more than ever before, discovered I don’t know diddly squat about a great many things, and am more excited about the next year than I can remember in recent history.
Below is a list of opinions about a great many things that I have seen and done over the past year. Some are pharmacy related, some are technology related, some are personal, and some are just random thoughts.
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