Howard R. Strasberg

Recommendations to Improve the Usability of Drug-Drug Interaction Clinical Decision Support Alerts

OBJECTIVE To establish preferred strategies for presenting drug-drug interaction (DDI) clinical decision support alerts. MATERIALS AND METHODS A DDI Clinical Decision Support Conference Series included a workgroup consisting of 24 clinical, usability, and informatics experts representing academia, health information technology (IT) vendors, healthcare organizations, and the Office of the National Coordinator for Health IT. Workgroup members met via web-based meetings 12 times from January 2013 to February 2014, and two in-person meetings to reach consensus on recommendations to improve decision support for DDIs. We addressed three key questions: (1) what, how, where, and when do we display DDI decision support? (2) should presentation of DDI decision support vary by clinicians? and (3) how should effectiveness of DDI decision support be measured? RESULTS Our recommendations include the consistent use of terminology, visual cues, minimal text, formatting, content, and reporting standards to facilitate usability. All clinicians involved in the medication use process should be able to view DDI alerts and actions by other clinicians. Override rates are common but may not be a good measure of effectiveness. DISCUSSION Seven core elements should be included with DDI decision support. DDI information should be presented to all clinicians. Finally, in their current form, override rates have limited capability to evaluate alert effectiveness. CONCLUSION DDI clinical decision support alerts need major improvements. We provide recommendations for healthcare organizations and IT vendors to improve the clinician interface of DDI alerts, with the aim of reducing alert fatigue and improving patient safety.

Health data use, stewardship, and governance: ongoing gaps and challenges: a report from AMIA's 2012 Health Policy Meeting

Large amounts of personal health data are being collected and made available through existing and emerging technological media and tools. While use of these data has significant potential to facilitate research, improve quality of care for individuals and populations, and reduce healthcare costs, many policy-related issues must be addressed before their full value can be realized. These include the need for widely agreed-on data stewardship principles and effective approaches to reduce or eliminate data silos and protect patient privacy. AMIAs 2012 Health Policy Meeting brought together healthcare academics, policy makers, and system stakeholders (including representatives of patient groups) to consider these topics and formulate recommendations. A review of a set of Proposed Principles of Health Data Use led to a set of findings and recommendations, including the assertions that the use of health data should be viewed as a public good and that achieving the broad benefits of this use will require understanding and support from patients.

Analyzing Information Seeking and Drug-Safety Alert Response by Health Care Professionals as New Methods for Surveillance

Background Patterns in general consumer online search logs have been used to monitor health conditions and to predict health-related activities, but the multiple contexts within which consumers perform online searches make significant associations difficult to interpret. Physician information-seeking behavior has typically been analyzed through survey-based approaches and literature reviews. Activity logs from health care professionals using online medical information resources are thus a valuable yet relatively untapped resource for large-scale medical surveillance. Objective To analyze health care professionals’ information-seeking behavior and assess the feasibility of measuring drug-safety alert response from the usage logs of an online medical information resource. Methods Using two years (2011-2012) of usage logs from UpToDate, we measured the volume of searches related to medical conditions with significant burden in the United States, as well as the seasonal distribution of those searches. We quantified the relationship between searches and resulting page views. Using a large collection of online mainstream media articles and Web log posts we also characterized the uptake of a Food and Drug Administration (FDA) alert via changes in UpToDate search activity compared with general online media activity related to the subject of the alert. Results Diseases and symptoms dominate UpToDate searches. Some searches result in page views of only short duration, while others consistently result in longer-than-average page views. The response to an FDA alert for Celexa, characterized by a change in UpToDate search activity, differed considerably from general online media activity. Changes in search activity appeared later and persisted longer in UpToDate logs. The volume of searches and page view durations related to Celexa before the alert also differed from those after the alert. Conclusions Understanding the information-seeking behavior associated with online evidence sources can offer insight into the information needs of health professionals and enable large-scale medical surveillance. Our Web log mining approach has the potential to monitor responses to FDA alerts at a national level. Our findings can also inform the design and content of evidence-based medical information resources such as UpToDate.

Terminology challenges implementing the HL7 context-aware knowledge retrieval (‘Infobutton’) standard

Point-of-care information needs are common and frequently unmet. One solution to this problem is the use of Infobuttons, which are context-sensitive links from electronic health records (EHR) to knowledge resources, sometimes involving an intermediate broker known as an Infobutton Manager. Health Level Seven (HL7) has developed the Context-Aware Knowledge Retrieval (Infobutton) standard to standardize the integration between EHR systems and knowledge resources. While the standard specifies a set of context attributes and standard terminologies, it leaves to knowledge resources the flexibility to decide how to use these attributes and terminologies to retrieve the most relevant content. This paper describes some of the challenges faced by knowledge resources in trying to locate the most relevant content based on the attribute values for a given Infobutton request. Various approaches to content retrieval are discussed, including the role of indexing with standardized codes, the role of text-based search engines together with their ranking algorithms, and the role of hybrid approaches. Knowledge resource developers must carefully consider business rules, heuristics, and precision/recall tradeoffs when implementing the HL7 Infobutton standard.