CDS, UX, and System Redesign - Promising Techniques and Tools to Bridge the Evidence Gap

INTRODUCTION: In this special issue of eGEMs, we explore the struggles related to bringing evidence into day-to-day practice, what I define as the evidence gap. We are all aware of high quality evidence in the form of guidelines, randomized clinical trials for treatments and diagnostic tests, and clinical prediction rules, which are all readily available online. We also know that electronic health records (EHRs) are now ubiquitous in health care and in most practices across the country. How we marry this high quality evidence and the practice of medicine through effective decision support is a major challenge. ABOUT THE ISSUE: All of the articles in this issue explore, in some fashion, CDS systems and how we can best bring providers and their work environment to the evidence. We are at the very early stages of the science of usability. Much more research and funding is needed in this area if we hope to improve the dissemination and implementation of evidence in practice. While the featured examples, techniques, and tools in the special issue are a promising start to improving usability and CDS, many of the papers highlight current gaps in knowledge and a great need for generalizable approaches. The great promise is for learning approaches to generate new evidence and to integrate this evidence in reliable, patient-centered ways at scale using new technology. Closing the evidence gap is a real possibility, but only if the community works together to innovate and invest in research on the best ways to disseminate, communicate, and implement evidence in practice

THE HIGH COST OF LOW VALUE CARE

The main focus of this study is bridging the evidence gap between frontline decision-making in health care and the actual evidence, with the hope of reducing unnecessary diagnostic testing and treatments. From our work in pulmonary embolism (PE) and over ordering of computed tomography pulmonary angiography, we integrated the highly validated Wells\u27 criteria into the electronic health record at two of our major academic tertiary hospitals. The Wells\u27 clinical decision support tool triggered for patients being evaluated for PE and therefore determined a patients\u27 pretest probability for having a PE. There were 12,759 patient visits representing 11,836 patients, 51% had no D-dimer, 41% had a negative D-dimer, and 9% had a positive D-dimer. Our study gave us an opportunity to determine which patients were very low probabilities for PE, with no need for further testing

Implement Smart Sensors With Wireless Communication Protocols With Embedded Microcontrollers in a Capstone Project Design

Wireless communication has become popular and widely used in our daily lives. Their applications are: Cellular Wireless for telephone systems, data collection, voice communication, and other mobile or extremely remote devices, Bluetooth for low-power applications in short range and moderate date bandwidth, Proprietary ISM (industrial, scientific, medical) protocols used in open frequency bands from 260 to 470 MHz, 902 to 928 MHz, and 2.4GHz, 802.11/WiFi in wireless data communications, 802.15/ZigBee for mesh networks of sensors and controllers, and Z-Wave for low speed wireless protocol of home electronics devices to intercommunicate using reliable protocol that easily travels through walls, floors, and cabinets1. Sensors with embedded intelligence and integrated with cost effective wireless protocols have been recognized as smart sensors in many applications, such as smart home appliances, home automation, green technology in energy conservation and harvesting, and remote data logging etc2. This application project is implemented in the classification between Proprietary ISM, ZigBee, and Z-Wave wireless applications. It is built based on the MRF24J40MA (2.4GHz RF modules) that follows the IEEE 802.15.4TM-2003 rules7, standards, and software protocols designs with SPI (Serial Peripheral Interface)9 interfacing to a PIC16F877A microcontroller. The project uses three 2.4 GHz RF modules (MRF24J40MA), and three PIC16F877A units hosted in three previously developed low cost PIC microcontroller training systems3. The sensor stations are designed as Slave units and responsible for conditioning and reporting temperature, humidity, and atmospheric pressure. The control unit is categorized as a Master station and responsible for interacting with user/host to decide when, where, and how to report the data to the inquiries. In addition to sensors on the Slaves station, there are assistances from real time clock and external serial EEPROM devices to provide time stamped real time data for future inquiry from the Master. All the communications between the Master and multiple Slaves are through wireless RF signals with customized software protocol designs4

Healthcare provider perceptions of clinical prediction rules

Objectives: To examine internal medicine and emergency medicine healthcare provider perceptions of usefulness of specific clinical prediction rules. Setting: The study took place in two academic medical centres. A web-based survey was distributed and completed by participants between 1 January and 31 May 2013. Participants: Medical doctors, doctors of osteopathy or nurse practitioners employed in the internal medicine or emergency medicine departments at either institution. Primary and secondary outcome measures: The primary outcome was to identify the clinical prediction rules perceived as most useful by healthcare providers specialising in internal medicine and emergency medicine. Secondary outcomes included comparing usefulness scores of specific clinical prediction rules based on provider specialty, and evaluating associations between usefulness scores and perceived characteristics of these clinical prediction rules. Results: Of the 401 healthcare providers asked to participate, a total of 263 (66%), completed the survey. The CHADS2 score was chosen by most internal medicine providers (72%), and Pulmonary Embolism Rule-Out Criteria (PERC) score by most emergency medicine providers (45%), as one of the top three most useful from a list of 24 clinical prediction rules. Emergency medicine providers rated their top three significantly more positively, compared with internal medicine providers, as having a better fit into their workflow (p=0.004),helping more with decision-making (p= 0.037), better fitting into their thought process when diagnosing patients (p= 0.001) and overall, on a 10-point scale, more useful (p= 0.009). For all providers, the perceived qualities of useful at point of care, helps with decision making, saves time diagnosing, fits into thought process, and should be the standard of clinical care correlated highly (\u3e= 0.65) with overall 10-point usefulness scores. Conclusions: Healthcare providers describe clear preferences for certain clinical prediction rules, based on medical specialty

Optimal search strategies for identifying sound clinical prediction studies in EMBASE

BACKGROUND: Clinical prediction guides assist clinicians by pointing to specific elements of the patient's clinical presentation that should be considered when forming a diagnosis, prognosis or judgment regarding treatment outcome. The numbers of validated clinical prediction guides are growing in the medical literature, but their retrieval from large biomedical databases remains problematic and this presents a barrier to their uptake in medical practice. We undertook the systematic development of search strategies ("hedges") for retrieval of empirically tested clinical prediction guides from EMBASE. METHODS: An analytic survey was conducted, testing the retrieval performance of search strategies run in EMBASE against the gold standard of hand searching, using a sample of all 27,769 articles identified in 55 journals for the 2000 publishing year. All articles were categorized as original studies, review articles, general papers, or case reports. The original and review articles were then tagged as 'pass' or 'fail' for methodologic rigor in the areas of clinical prediction guides and other clinical topics. Search terms that depicted clinical prediction guides were selected from a pool of index terms and text words gathered in house and through request to clinicians, librarians and professional searchers. A total of 36,232 search strategies composed of single and multiple term phrases were trialed for retrieval of clinical prediction studies. The sensitivity, specificity, precision, and accuracy of search strategies were calculated to identify which were the best. RESULTS: 163 clinical prediction studies were identified, of which 69 (42.3%) passed criteria for scientific merit. A 3-term strategy optimized sensitivity at 91.3% and specificity at 90.2%. Higher sensitivity (97.1%) was reached with a different 3-term strategy, but with a 16% drop in specificity. The best measure of specificity (98.8%) was found in a 2-term strategy, but with a considerable fall in sensitivity to 60.9%. All single term strategies performed less well than 2- and 3-term strategies. CONCLUSION: The retrieval of sound clinical prediction studies from EMBASE is supported by several search strategies

Predictors of Overtesting in Pulmonary Embolism Diagnosis

© 2019 Background: The benefits of computed tomography pulmonary angiography (CTPA) for pulmonary embolism (PE) diagnosis must be weighed against its risks, radiation-induced malignancy, and contrast-induced nephropathy. Appropriate use of CTPA can be assessed by monitoring yield, the percentage of tests positive for PE. We identify factors that are associated low CTPA yield, which may predict overtesting. Methods: This was a retrospective cohort study of six emergency departments between June 2014 and February 2017. The electronic health record was queried for CTPAs ordered for adult patients in the emergency department. We assessed the following patient factors: age, gender, body mass index, number of comorbidities, race, and ethnicity, provider factors: type (resident, fellow, attending, physician assistant) and environment factors: test time of day, season of visit, and crowdedness of the department. Results: A total of 14,782 CTPAs were reviewed, of which 1366 were found to be positive for PE, resulting in an overall CTPA yield of 9.24%. Provider type was not associated with a difference in yield. Testing was less likely to be positive in younger patients, females, those with lower body mass indexes and those identifying as Asian or Hispanic. Testing was also less likely to be positive when ordered during the overnight shift and during the winter and spring seasons. Conclusion: Our study identified several patient and environmental factors associated with low CTPA yield suggesting potential targets for overtesting. Targeting education and clinical decision support to assist providers in these circumstances may meaningfully improve yields

Do actions occur inside the body?

The paper offers a critical examination of Jennifer Hornsby's view that actions are internal to the body. It focuses on three of Hornsby's central claims: (P) many actions are bodily movements (in a special sense of the word “movement”) (Q) all actions are tryings; and (R) all actions occur inside the body. It is argued, contra Hornsby, that we may accept (P) and (Q) without accepting also the implausible (R). Two arguments are first offered in favour of the thesis (Contrary-R): that no actions occur inside the body. Three of Hornsby's arguments in favour of R are then examined. It is argued that we need to make a distinction between the causes and the causings of bodily movements (in the ordinary sense of the word “movement”) and that actions ought to be identified with the latter rather than the former. This distinction is then used to show how Hornsby's arguments for (R) may be resisted

Measures of User experience in a Streptococcal pharyngitis and Pneumonia Clinical Decision Support Tools

Objective: To understand clinician adoption of CDS tools as this may provide important insights for the implementation and dissemination of future CDS tools. Materials and Methods: Clinicians (n=168) at a large academic center were randomized into intervention and control arms to assess the impact of strep and pneumonia CDS tools. Intervention arm data were analyzed to examine provider adoption and clinical workflow. Electronic health record data were collected on trigger location, the use of each component and whether an antibiotic, other medication or test was ordered. Frequencies were tabulated and regression analyses were used to determine the association of tool component use and physician orders. Results: The CDS tool was triggered 586 times over the study period. Diagnosis was the most frequent workflow trigger of the CDS tool (57%) as compared to chief complaint (30%) and diagnosis/antibiotic combinations (13%). Conversely, chief complaint was associated with the highest rate (83%) of triggers leading to an initiation of the CDS tool (opening the risk prediction calculator). Similar patterns were noted for initiation of the CDS bundled ordered set and completion of the entire CDS tool pathway. Completion of risk prediction and bundled order set components were associated with lower rates of antibiotic prescribing (OR 0.5; CI 0.2-1.2 and OR 0.5; CI 0.3-0.9, respectively). Discussion: Different CDS trigger points in the clinician user workflow lead to substantial variation in downstream use of the CDS tool components. These variations were important as they were associated with significant differences in antibiotic ordering. Conclusions: These results highlight the importance of workflow integration and flexibility for CDS success

ATR-FTIR Spectroscopic Studies of Polymer-Based Identification Cards

Counterfeit production of polymer identity cards poses a significant economic cost to society and a threat to national security. Identifying these counterfeits is a challenge for ‘frontline’ personnel who lack training in specialised document examination. This study investigates the use of attenuated total reflectance Fourier Transform infrared (ATR-FTIR) spectroscopy with chemometrics as a potential approach to assessing polymer card authenticity. In situ analysis of several cards found that differentiation could be achieved based on the core polymer composition. A chemometric model was thus built for three driver’s licence series produced in Western Australia and tested using a separate set of seven licences. The majority of test samples were correctly matched to the series of issue, with atypical samples recognisable based on their discriminant values. Synchrotron FTIR imaging revealed that differentiation between each series was possibly related to the adhesive used between the core layers. The approach presented in this work has the potential to be developed as a rapid screening method to identify suspect polymer cards warranting further examination