The AMIA 2013 conference just wrapped up in Washington, DC. I had the honor of giving two talks on topics I often discuss on this blog – medication safety screening and clinical decision support (CDS) standards. Read further >
Vice President, Medical Informatics
Wolters Kluwer Health – Clinical Solutions
As the VP of Medical Informatics for Wolters Kluwer Health – Clinical Solutions, Howard focuses on building products that answer clinical questions and integrate knowledge with electronic medical record (EMR) and computerized physician order entry (CPOE) systems. He is also actively involved in standards development as a co-chair of the Health Level Seven (HL7) Clinical Decision Support (CDS) Technical Committee, which develops CDS standards in areas such as Infobuttons, order sets, and decision support services.
Prior to joining Wolters Kluwer Health in 2003, he was CEO of Skolar, Inc., an online provider of clinical information and "in context" continuing medical education (CME) for medical professionals.
Howard received his MD degree from the University of Western Ontario and his MS degree in Medical Information Sciences from Stanford University. He is board certified in Family Medicine. As a hobby, he enjoys following the airline industry, especially with regards to the latest schedules, routes, fares and frequent flyer programs.
Posts by Howard Strasberg
One of the most important benefits of implementing an electronic medical record (EMR) system is the ability to provide clinical decision support (CDS). CDS can come in many forms, such as order sets, alerts, reminders, documentation templates, relevant data display, and filtered reference information. Evaluation of CDS systems is required to make sure that they are providing the right advice. While the impact of CDS systems is often evaluated after the system has been in use for a period of time, evaluations should also occur before these systems have been deployed – i.e. as a condition of deployment. Read further >
Medication safety screening, as I have written about at length previously, has the potential to reduce prescribing errors and therefore to improve patient safety. I have also previously described alert fatigue, which occurs when the signal:noise ratio is so low that providers start to ignore the alerts. Design of clinical decision support (CDS) systems is therefore a critical factor in order to optimize the impact of these systems on patient care. Read further >
The Health eDecisions (HeD) Use Case 1 pilot program wrapped up this week. This federal (US) initiative is working on identifying, defining and harmonizing standards for shareable clinical decision support (CDS). Please see my previous blog post on this topic for additional background on the initiative. Use Case 1 deals with standards to structure medical knowledge in a shareable and executable format. In particular, it defines a harmonized XML schema for rules, order sets and documentation templates. This schema was piloted over the last few months by a variety of content and electronic health record vendors. For example, Wolters Kluwer participated by providing a clinical documentation template for urinary tract infections in the HeD format, which was then successfully converted to a format that could be used by the Veterans Health Administration (VA). Read further >
Last month I attended a drug-drug interaction (DDI) clinical decision support (CDS) conference funded by the Agency for Healthcare Research & Quality (AHRQ) and organized by the University of Arizona College of Pharmacy. The conference brought together various stakeholders and experts in the field to try to answer some key DDI questions. The work began by conference calls before the conference and will continue through additional conference calls after the conference. The work is divided into three workgroups: Read further >
In medication safety screening, alert fatigue occurs when the signal:noise ratio is so low that clinicians develop a habit of ignoring alerts, thereby potentially missing important alerts when they occur. One idea for reducing alert fatigue is to display relevant and recent lab results alongside the alert, thereby allowing physicians to make a more informed decision of the risk of a particular drug-drug interaction in a given patient. For example, if a drug-drug interaction may cause an increase in serum potassium (hyperkalemia), and if a patient’s serum potassium is already on the high side of normal, a physician may determine that it’s too risky to continue with the prescribed drug combination in this particular patient. Read further >
In a typical electronic health record (EHR), patient data are entered and stored using some combination of structured data (e.g. diagnosis codes) and free text. In general, analyses of EHR data focus on the structured data portion, which can be leveraged more easily by standard query tools, and which avoids some of the problems with free text, such as ambiguous terms and negation. Still, there’s a lot of useful information buried in the free text portions of these records. If there were some way to mine the free text, gold might well be discovered. Read further >
In the current issue of JAMIA, I along with my co-authors Guilherme Del Fiol and Jim Cimino describe various terminology challenges surrounding Infobutton implementations. I have frequently written about Infobuttons on this blog. In essence they are context-sensitive links from electronic health records (EHRs) to knowledge resources. Read further >
I have written several posts about how to address the problem of alert fatigue in medication safety screening. Alert fatigue occurs when the signal:noise ratio is so low that clinicians develop a habit of ignoring alerts, thereby potentially missing important alerts when they occur. Read further >
Regular readers of this blog will know that I frequently comment on the Health Level Seven International (HL7) Infobutton standard. Infobuttons are context-sensitive links from electronic health records (EHRs) to knowledge resources. Infobuttons were included in the 2014 EHR certification criteria (United States) under both clinical decision support (CDS) and patient education. Read further >