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Objective - The Vanderbilt Children's Hospital launched an innovative Technology-Based Patient and Family Engagement Consult Service in 2014. This paper describes our initial experience with this service, characterizes health-related needs of families of hospitalized children, and details the technologies recommended to promote engagement and meet needs.
Materials and Methods - We retrospectively reviewed consult service documentation for patient characteristics, health-related needs, and consultation team recommendations. Needs were categorized using a consumer health needs taxonomy. Recommendations were classified by technology type.
Results - Twenty-two consultations were conducted with families of patients ranging in age from newborn to 15 years, most with new diagnoses or chronic illnesses. The consultation team identified 99 health-related needs (4.5 per consultation) and made 166 recommendations (7.5 per consultation, 1.7 per need). Need categories included 38 informational needs, 26 medical needs, 23 logistical needs, and 12 social needs. The most common recommendations were websites (50, 30%) and mobile applications (30, 18%). The most frequent recommendations by need category were websites for informational needs (39, 50%), mobile applications for medical needs (15, 40%), patient portals for logistical needs (12, 44%), and disease-specific support groups for social needs (19, 56%).
Discussion - Families of hospitalized pediatric patients have a variety of health-related needs, many of which could be addressed by technology recommendations from an engagement consult service.
Conclusion - This service is the first of its kind, offering a potentially generalizable and scalable approach to assessing health-related needs, meeting them with technologies, and promoting patient and family engagement in the inpatient setting.
© The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: email@example.com
Tumor registries are held to a very high standard for identifying and reporting new analytic cancer cases. However, current approaches to new case detection are often inefficient and costly. Efficient and effective detection of new cancer cases has the potential to maintain a high accuracy of reporting while reducing costs, increasing timeliness of reporting, and ultimately advancing cancer research. We describe the development, implementation, and evaluation of an informatics tool that integrates multiple data sources to support the workflow of new case identification at the Vanderbilt University Medical Center (VUMC) tumor registry office. The new system reduced the total number of potential cases to analyze from roughly 13,000 to 2,500 records per month. This resulted in an efficiency gain of roughly 80 man hours per month with a respective annual savings of approximately 50,000 dollars. Further iterative refinement of this approach along with support for case abstraction could result in further efficiencies.
PURPOSE - High-resolution chest computed tomography (HRCT) is essential in the characterization of interstitial lung disease. The HRCT features of some diseases can be diagnostic. Longitudinal monitoring with HRCT can assess progression of interstitial lung disease; however, subtle changes in the volume and character of abnormalities can be difficult to assess. Accuracy of diagnosis can be dependent on expertise and experience of the radiologist, pathologist, or clinician. Quantitative analysis of thoracic HRCT has the potential to determine the extent of disease reproducibly, classify the types of abnormalities, and automate the diagnostic process.
MATERIALS AND METHODS - Novel software that utilizes histogram signatures to characterize pulmonary parenchyma was used to analyze chest HRCT data, including retrospective processing of clinical CT scans and research data from the Lung Tissue Research Consortium. Additional information including physiological, pathologic, and semiquantitative radiologist assessment was available to allow comparison of quantitative results, with visual estimates of the disease, physiological parameters, and measures of disease outcome.
RESULTS - Quantitative analysis results were provided in regional volumetric quantities for statistical analysis and a graphical representation. These results suggest that quantitative HRCT analysis can serve as a biomarker with physiological, pathologic, and prognostic significance.
CONCLUSIONS - It is likely that quantitative analysis of HRCT can be used in clinical practice as a means to aid in identifying a probable diagnosis, stratifying prognosis in early disease, and consistently determining progression of the disease or response to therapy. Further optimization of quantitative techniques and longitudinal analysis of well-characterized subjects would be helpful in validating these methods.
BACKGROUND - The last mile of the medication use system requires tools to help patients comply with medication administration rules and monitor for side effects. Personal health records (PHR) and emerging user-adopted communication tools promise to change the landscape of medication management; however, no research has been done to demonstrate how these tools might be constructed to support children with special healthcare needs. The overarching goal of the MyMediHealth project was to investigate ways in which PHRs and supported applications can improve the safety and quality of medication delivery in this population.
DESIGN APPROACH - This project employed user-centered design to identify requirements for a child-centered medication management system. We collected information through site visits, facilitated group discussions, and iterative design sessions with adult caregivers. Once design requirements were articulated and validated, we constructed an initial prototype medication scheduler, which was evaluated by 202 parents using scripted activities completed using an online interactive prototype. The results of this analysis informed the development of a working prototype.
STATUS - We have completed a working prototype of a scheduling system, a text-message-based alert and reminder system, and a medication administration record based on web-entered patient data.
IMPLICATIONS - Pilot testing of the working prototype by stakeholders yielded strong endorsement and helpful feedback for future modifications, which are now underway as a part of an expanded project to test this system in a real-world environment.
Copyright © 2010 Elsevier Inc. All rights reserved.
OBJECTIVE - Detecting adverse events is pivotal for measuring and improving medical safety, yet current techniques discourage routine screening. The authors hypothesized that discharge summaries would include information on adverse events, and they developed and evaluated an electronic method for screening medical discharge summaries for adverse events.
DESIGN - A cohort study including 424 randomly selected admissions to the medical services of an academic medical center was conducted between January and July 2000. The authors developed a computerized screening tool that searched free-text discharge summaries for trigger words representing possible adverse events.
MEASUREMENTS - All discharge summaries with a trigger word present underwent chart review by two independent physician reviewers. The presence of adverse events was assessed using structured implicit judgment. A random sample of discharge summaries without trigger words also was reviewed.
RESULTS - Fifty-nine percent (251 of 424) of the discharge summaries contained trigger words. Based on discharge summary review, 44.8% (327 of 730) of the alerted trigger words indicated a possible adverse event. After medical record review, the tool detected 131 adverse events. The sensitivity and specificity of the screening tool were 69% and 48%, respectively. The positive predictive value of the tool was 52%.
CONCLUSION - Medical discharge summaries contain information regarding adverse events. Electronic screening of discharge summaries for adverse events using keyword searches is feasible but thus far has poor specificity. Nonetheless, computerized clinical narrative screening methods could potentially offer researchers and quality managers a means to routinely detect adverse events.
CONTEXT - Although patient safety is a major problem, most health care organizations rely on spontaneous reporting, which detects only a small minority of adverse events. As a result, problems with safety have remained hidden. Chart review can detect adverse events in research settings, but it is too expensive for routine use. Information technology techniques can detect some adverse events in a timely and cost-effective way, in some cases early enough to prevent patient harm.
OBJECTIVE - To review methodologies of detecting adverse events using information technology, reports of studies that used these techniques to detect adverse events, and study results for specific types of adverse events.
DESIGN - Structured review.
METHODOLOGY - English-language studies that reported using information technology to detect adverse events were identified using standard techniques. Only studies that contained original data were included.
MAIN OUTCOME MEASURES - Adverse events, with specific focus on nosocomial infections, adverse drug events, and injurious falls.
RESULTS - Tools such as event monitoring and natural language processing can inexpensively detect certain types of adverse events in clinical databases. These approaches already work well for some types of adverse events, including adverse drug events and nosocomial infections, and are in routine use in a few hospitals. In addition, it appears likely that these techniques will be adaptable in ways that allow detection of a broad array of adverse events, especially as more medical information becomes computerized.
CONCLUSION - Computerized detection of adverse events will soon be practical on a widespread basis.