Water, Water, Everywhere, and Not a Drop to Drink

In themovie Life of Pi, the protagonist and his tiger companion facea slowdeath fromthirstwhile surroundedbyanocean of water. The ubiquity of the desired and vital substance, though inunacceptable form, supplies rich irony to theprotagonist’s struggle, andso it is with the informationneedsof clinicians. It is no great revelation to say we live in a society that carries auniverse of possibilities in its pocket: global telecommunicationandvideoconferencing, instantaneousknowledge at our fingertips, business transactions viamobile applications, and libraries of books,music, andvideos ondemand. Even so, the informationneeds of clinicianswhoprovide care in the office or at the bedside are not so easily met. The systematic reviewbyDelFiol et al1 highlights the continued need for information by clinicians despite the explosion ofmedical literature. It has been estimated that approximately 10 million articles were published between 1865 and 2006, with a steady annual increase in numbers.2 Despite the staggering availability of information,Del Fiol et al found that on average a clinicianwill have 1 question for every 2 patients seen but will seek answers to only 50% of questions and find answers for 80%of questions pursued.How is it that approximately 50% of clinical questions are not acted on?What does it tell us thatwhenquestions are pursued, the clinician is able to find an answer 80% of the time? The answers to these questions probably lie in the barriers summarized byDel Fiol et al.1 The lack of time at the point of care and subsequent forgetting of questions could explain whymany clinicians do not attempt to answer questions that arise from patient care, and the demands of caring for a high volume of patients and the attendant after-hours work could explainwhymany clinicians defer searching for answers. It is possible, however, that questions disregarded as insignificant could changepatient care if information that includedanswerswasprovided seamlessly. Fortunately, several developments in recent years helppromotemore seamless delivery of information at the point of care. In 2011, phase 1 of Meaningful Use, a product of the Health Information Technology for Economic and Clinical Health Act, incentivized and mandated the adoption of certified electronic health records (EHRs). This certification requires EHRs to use established medical terminology coding standards for medications, laboratories, and diagnoses (eg, RxNorm, LOINC [Logical Observation Identifiers Names and Codes], and SNOMED CT [Systematized Nomenclature of Medicine–Clinical Terms]), which is key to fostering interoperability between clinical information systems and, eventually, health information sharing. As noted by Del Fiol et al,1 the standard used to send messages from one system to another (Health Level Seven) has included a contextaware knowledge retrieval “Infobutton” as part of its standard, which has also been included among the requirements of EHR certification.3 Unfortunately, this process is only part of the equation. Used alone, it would be as if the protagonist Pi developed an apparatus that could extract water from the ocean but not convert salt water into fresh water; the result is still no potable water. The knowledge resources (eg, PubMed,Medline Plus,National ClearinghouseGuidelines, andUpToDate) are the other half of the equation. Once a clinical topic is identified via one of the common standards found in the EHR, the topic then needs tobemapped to the semantic taxonomyusedbyknowledge resource developers. In most cases, knowledge resourcedevelopersuseMeSH(MedicalSubjectHeadings) terms, Unified Medical Language System, or nonstandardized textbased classifications,which arenot necessarily goodmatches to the standard codes from theEHR.4 The ability tomatch the information needed depends on the quality and detail of the metadata surrounding the information resources aswell as the level of specificity requiredby thequestion. This presents the challenge of knowing howmuch information to provide and howtoprovide it. Thehuman-computer interactionwithin information-seeking behaviors needs to be better understood if information is to be provided unobtrusively, and this consideration could affect future adoption. Fortunately, the Clinical Decision Support Consortium is working to promote an Enterprise Clinical Decision Support Framework, which would ideally support information services in the formof clinical guideline alerts in theEHR.5Moreover, the Clinical Decision Support Work Group’s effort with Infobuttons seems uniquely poised for the provision of “context-aware” general information.3 However, these efforts do not seem to encompass the unique patient-specific information required formore complexquestions. Interestingwork is being done on the use of natural language processing to rank key sentences from primary literature abstracts that apply to a specific question asked.6,7 Although this use falls short of an automatedcontext-specificquestion-answer system, it is a significant start toward that end. Imagine the clinical impact if your patient’s EHR provided summary information tohelp youdetermine the risk of startingwarfarin therapy in an octogenarianwith a history of strokeandnew-onset atrial fibrillation, alongwith links to specific articles in the primary literature. Again, this level of detail will require use ofmore robustmetadata or semantic taxonomy on the knowledge resource side to match patient demographics and clinical details, but this approach couldultimately improve the application of study results by matching population characteristics to individual patients, thereby ensuring external validity. The realmessage of the reviewbyDel Fiol et al1 is not that clinicians have questions but that many of our questions remainunanswereddespite theoceanof informationaroundus. Related article page 710 Questions Raised by Clinicians at Point of Care Original Investigation Research