A Shared Decision-making Tool for Drug Interactions Between Warfarin and Nonsteroidal Anti-inflammatory Drugs: Design and Usability Study.

BACKGROUND: Exposure to life-threatening drug-drug interactions (DDIs) occurs despite the widespread use of clinical decision support. The DDI between warfarin and nonsteroidal anti-inflammatory drugs is common and potentially life-threatening. Patients can play a substantial role in preventing harm from DDIs; however, the current model for DDI decision-making is clinician centric. OBJECTIVE: This study aims to design and study the usability of DDInteract, a tool to support shared decision-making (SDM) between a patient and provider for the DDI between warfarin and nonsteroidal anti-inflammatory drugs. METHODS: We used an SDM framework and user-centered design methods to guide the design and usability of DDInteract-an SDM electronic health record app to prevent harm from clinically significant DDIs. The design involved iterative prototypes, qualitative feedback from stakeholders, and a heuristic evaluation. The usability evaluation included patients and clinicians. Patients participated in a simulated SDM discussion using clinical vignettes. Clinicians were asked to complete eight tasks using DDInteract and to assess the tool using a survey adapted from the System Usability Scale. RESULTS: The designed DDInteract prototype includes the following features: a patient-specific risk profile, dynamic risk icon array, patient education section, and treatment decision tree. A total of 4 patients and 11 clinicians participated in the usability study. After an SDM session where patients and clinicians review the tool concurrently, patients generally favored pain treatments with less risk of gastrointestinal bleeding. Clinicians successfully completed the tasks with a mean of 144 (SD 74) seconds and rated the usability of DDInteract as 4.32 (SD 0.52) of 5. CONCLUSIONS: This study expands the use of SDM to DDIs. The next steps are to determine if DDInteract can improve shared decision-making quality and to implement it across health systems using interoperable technology.

Consensus recommendations for systematic evaluation of drug-drug interaction evidence for clinical decision support.

BACKGROUND: Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. OBJECTIVE: The aim of this study was to provide recommendations for systematic evaluation of evidence for DDIs from the scientific literature, drug product labeling, and regulatory documents. METHODS: A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 18 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar 12 times from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. RESULTS: We developed expert consensus answers to the following three key questions. (i) What is the best approach to evaluate DDI evidence? (ii) What evidence is required for a DDI to be applicable to an entire class of drugs? (iii) How should a structured evaluation process be vetted and validated? CONCLUSION: Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug compendia and clinical decision support systems in which these recommendations are implemented should be able to provide higher-quality information about DDIs.

Proposed methods and endpoints for defining and assessing adverse environmental impact (AEI) on fish communities/populations in Tennessee River reservoirs.

Two multimetric indices have been developed to help address fish community (reservoir fish assemblage index [RFAI]) and individual population quality (sport fishing index [SFI]) in Tennessee River reservoirs. The RFAI, with characteristics similar to the index of biotic integrity (IBI) used in stream fish community determinations, was developed to monitor the existing condition of resident fish communities. The index, which incorporates standardized electrofishing of littoral areas and experimental gill netting for limnetic bottom-dwelling species, has been used to determine residential fish community response to various anthropogenic impacts in southeastern reservoirs. The SFI is a multimetric index designed to address the quality of the fishery for individual resident sport fish species in a particular lake or reservoir[4]. The SFI incorporates measures of fish population aspects and angler catch and pressure estimates. This paper proposes 70% of the maximum RFAI score and 10% above the average SFI score for individual species as "screening" endpoints for balanced indigenous populations (BIP) or adverse environmental impact (AEI). Endpoints for these indices indicate: (1) communities/populations are obviously balanced indigenous populations (BIP) indicating no adverse environmental impact (AEI), or are "screened out"; (2) communities/populations are considered to be potentially impacted; and (3) where the resident fish community/population should be considered adversely impacted. Suggestions are also made concerning how examination of individual metric scores can help determine the source or cause of the impact.

Interpretation of digital mammograms: comparison of speed and accuracy of soft-copy versus printed-film display.

PURPOSE: To compare the speed and accuracy of the interpretations of digital mammograms by radiologists by using printed-film versus soft-copy display. MATERIALS AND METHODS: After being trained in interpretation of digital mammograms, eight radiologists interpreted 63 digital mammograms, all with old studies for comparison. All studies were interpreted by all readers in soft-copy and printed-film display, with interpretations of images in the same cases at least 1 month apart. Mammograms were interpreted in cases that included six biopsy-proved cancers and 20 biopsy-proved benign lesions, 20 cases of probably benign findings in patients who underwent 6-month follow-up, and 17 cases without apparent findings. Area under the receiver operating characteristic curve (A(z)), sensitivity, and specificity were calculated for soft-copy and printed-film display. RESULTS: There was no significant difference in the speed of interpretation, but interpretations with soft-copy display were slightly faster. The differences in A(z), sensitivity, and specificity were not significantly different; A(z) and sensitivity were slightly better for interpretations with printed film, and specificity was slightly better for interpretations with soft copy. CONCLUSION: Interpretation with soft-copy display is likely to be useful with digital mammography and is unlikely to significantly change accuracy or speed.