scholarly journals Leveraging Electronic Tablets for General Pediatric Care

2015 ◽  
Vol 06 (01) ◽  
pp. 1-15 ◽  
Author(s):  
S. McKee ◽  
T.M. Dugan ◽  
S.M. Downs ◽  
V. Anand
Keyword(s):  
Decision Support ◽  
User Interface ◽  
Pilot Study ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Self Report ◽  
Pediatric Care ◽  
Patient Questionnaire ◽  
Health Improvement ◽  
Completion Rates

SummaryBackground: We have previously shown that a scan-able paper based interface linked to a computerized clinical decision support system (CDSS) can effectively screen patients in pediatric waiting rooms and support the physician using evidence based care guidelines at the time of clinical encounter. However, the use of scan-able paper based interface has many inherent limitations including lacking real time communication with the CDSS and being prone to human and system errors. An electronic tablet based user interface can not only overcome these limitations, but may also support advanced functionality for clinical and research use. However, use of such devices for pediatric care is not well studied in clinical settings.Objective: In this pilot study, we enhance our pediatric CDSS with an electronic tablet based user interface and evaluate it for usability as well as for changes in patient questionnaire completion rates.Methods: Child Health Improvement through Computers Leveraging Electronic Tablets or CHICLET is an electronic tablet based user interface. It is developed to augment the existing scan-able paper interface to our CDSS. For the purposes of this study, we deployed CHICLET in one outpatient pediatric clinic. Usability factors for CHICLET were evaluated via caregiver and staff surveys.Results: When compared to the scan-able paper based interface, we observed an 18% increase or 30% relative increase in question completion rates using CHICLET. This difference was statistically significant. Caregivers and staff survey results were positive for using CHICLET in clinical environment.Conclusions: Electronic tablets are a viable interface for capturing patient self-report in pediatric waiting rooms. We further hypothesize that the use of electronic tablet based interfaces will drive advances in computerized clinical decision support and create opportunities for patient engagement.Citation: Anand V, McKee S, Dugan TM, Downs SM. Leveraging electronic tablets for general pediatric care – a pilot study. Appl Clin Inf 2015; 6: 1–15http://dx.doi.org/10.4338/ACI-2014-09-RA-0071

scholarly journals Evaluation of User-Interface Alert Displays for Clinical Decision Support Systems for Sepsis

2018 ◽  
Vol 38 (4) ◽  
pp. 46-54 ◽  
Author(s):  
Devida Long ◽  
Muge Capan ◽  
Susan Mascioli ◽  
Danielle Weldon ◽  
Ryan Arnold ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Support ◽  
User Interface ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Care Providers

BACKGROUND Hospitals are increasingly turning to clinical decision support systems for sepsis, a life-threatening illness, to provide patient-specific assessments and recommendations to aid in evidence-based clinical decision-making. Lack of guidelines on how to present alerts has impeded optimization of alerts, specifically, effective ways to differentiate alerts while highlighting important pieces of information to create a universal standard for health care providers. OBJECTIVE To gain insight into clinical decision support systems–based alerts, specifically targeting nursing interventions for sepsis, with a focus on behaviors associated with and perceptions of alerts, as well as visual preferences. METHODS An interactive survey to display a novel user interface for clinical decision support systems for sepsis was developed and then administered to members of the nursing staff. RESULTS A total of 43 nurses participated in 2 interactive survey sessions. Participants preferred alerts that were based on an established treatment protocol, were presented in a pop-up format, and addressed the patient’s clinical condition rather than regulatory guidelines. CONCLUSIONS The results can be used in future research to optimize electronic medical record alerting and clinical practice workflow to support the efficient, effective, and timely delivery of high-quality care to patients with sepsis. The research also may advance the knowledge base of what information health care providers want and need to improve the health and safety of their patients.

scholarly journals Understanding Why Clinicians Answer or Ignore Clinical Decision Support Prompts

2012 ◽  
Vol 03 (03) ◽  
pp. 309-317 ◽  
Author(s):  
V. Anand ◽  
S. M. Downs ◽  
A.E. Carroll
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Health Improvement ◽  
Key Factors ◽  
Factors Influencing ◽  
Number Of Factors ◽  
Computer Automation ◽  
Computer Decision Support

Summary Introduction: The identification of key factors influencing responses to prompts and reminders within a computer decision support system (CDSS) has not been widely studied. The aim of this study was to evaluate why clinicians routinely answer certain prompts while others are ignored. Methods: We utilized data collected from a CDSS developed by our research group – the Child Health Improvement through Computer Automation (CHICA) system. The main outcome of interest was whether a clinician responded to a prompt. Results: This study found that, as expected, some clinics and physicians were more likely to address prompts than others. However, we also found clinicians are more likely to address prompts for younger patients and when the prompts address more serious issues. The most striking finding was that the position of a prompt was a significant predictor of the likelihood of the prompt being addressed, even after controlling for other factors. Prompts at the top of the page were significantly more likely to be answered than the ones on the bottom. Conclusions: This study detailed a number of factors that are associated with physicians following clinical decision support prompts. This information could be instrumental in designing better interventions and more successful clinical decision support systems in the future.

scholarly journals Standards-Based Clinical Decision Support Platform to Manage Patients Who Meet Guideline-Based Criteria for Genetic Evaluation of Familial Cancer

2020 ◽  
pp. 1-9 ◽  
Author(s):  
Guilherme Del Fiol ◽  
Wendy Kohlmann ◽  
Richard L. Bradshaw ◽  
Charlene R. Weir ◽  
Michael Flynn ◽  
...  
Keyword(s):  
Decision Support ◽  
Pilot Study ◽  
Clinical Decision Support ◽  
Familial Cancer ◽  
Family Health ◽  
Clinical Decision ◽  
Target Population ◽  
Population Based ◽  
Genetic Evaluation ◽  
Pathogenic Variants

PURPOSE The ubiquitous adoption of electronic health records (EHRs) with family health history (FHH) data provides opportunities for tailoring cancer screening strategies to individuals. We aimed to enable a standards-based clinical decision support (CDS) platform for identifying and managing patients who meet guidelines for genetic evaluation of hereditary cancer. METHODS The CDS platform ( www.opencds.org ) was used to implement algorithms based on the 2018 National Comprehensive Cancer Network guidelines for genetic evaluation of hereditary breast/ovarian and colorectal cancer. The platform was designed to be interfaced with different EHR systems via the Health Level Seven International Fast Healthcare Interoperability Resources standard. The platform was integrated with the Epic EHR and evaluated in a pilot study at an academic health care system. RESULTS The CDS platform was executed against a target population of 143,012 patients; 5,245 (3.7%) met criteria for genetic evaluation based on the FHH recorded in the EHR. In a clinical pilot study, genetic counselors attempted to reach out to 71 of the patients. Of those patients, 25 (35%) scheduled an appointment, 10 (14%) declined, 2 (3%) did not need genetic counseling, 7 (10%) said they would consider it in the future, and 27 (38%) were unreachable. To date, 13 (52%) of the scheduled patients completed visits, and 2 (15%) of those were found to have pathogenic variants in cancer predisposition genes. CONCLUSION A standards-based CDS platform integrated with EHR systems is a promising population-based approach to identify patients who are appropriate candidates for genetic evaluation of hereditary cancers.

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