Dataset Information

Provider Survey on Automated Clinical Decision Support for Cardiovascular Risk Assessment.

ABSTRACT: Objective:To investigate provider opinions regarding a clinical decision support (CDS) system for cardiovascular risk assessment and for the creation of a replacement system. Methods:From March to April 2018, an invitation letter with a link to a self-administered web-based survey was sent via e-mail to 279 providers with primary appointment in the Department of Cardiovascular Medicine, Mayo Clinic, Rochester. The e-mail was sent to providers on March 8, 2018 and the survey closed on April 16, 2018. Results:One hundred providers responded to the survey yielding an overall response rate of 35.8%. Of these, 52 (52%) indicated they had used the cardiovascular (CV) risk profile CDS system and were classified as users and prompted to continue the survey. Among users, 42 (80.8%) indicated use of the CDS was either important (25; 48.1%) or very important (17; 32.7%) in their clinical practice; 45 (86.5%) responded that the system was very easy (17; 32.7%) or easy (28; 53.8%) to use. In addition, 48 (96.0%) users indicated that the CV risk profile supported their thought process at the point-of-care; 47 (97.9%) users indicated similar functionalities should be implemented into the new electronic health record system and 41 (85.4%) users reported new functionalities should also be incorporated. Conclusions:For most users, the CDS system was easy to use and supported clinical thought process at the point-of-care. Users also felt their practice was supported and should continue to be supported by CDS systems providing individualized patient information at the point-of-care.

SUBMITTER: Chaudhry AP

PROVIDER: S-EPMC6410336 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Provider Survey on Automated Clinical Decision Support for Cardiovascular Risk Assessment.

Chaudhry Alisha P AP Samudrala Sujith S Lopez-Jimenez Francisco F Shellum Jane L JL Nishimura Rick A RA Chaudhry Rajeev R Liu Hongfang H Arruda-Olson Adelaide M AM

Mayo Clinic proceedings. Innovations, quality & outcomes 20190226 1

<h4>Objective</h4>To investigate provider opinions regarding a clinical decision support (CDS) system for cardiovascular risk assessment and for the creation of a replacement system.<h4>Methods</h4>From March to April 2018, an invitation letter with a link to a self-administered web-based survey was sent via e-mail to 279 providers with primary appointment in the Department of Cardiovascular Medicine, Mayo Clinic, Rochester. The e-mail was sent to providers on March 8, 2018 and the survey closed ...[more]

PMID: 30899905

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Project description:BackgroundColorectal Cancer (CRC) is the third leading cause of cancer death among men and women in the United States. Research has shown that the risk of CRC associates with genetic and lifestyle factors. It is possible to prevent or minimize certain CRC risks by adopting a healthy lifestyle. Existing Clinical Decision Support Systems (CDSS) mainly targeted physicians as the CDSS users. As a result, the availability of patient-oriented CDSS is limited. Our project is to develop patient-oriented CDSS for active CRC management.MethodsWe implemented an online patient-oriented CRC CDSS for the public to learn about CRC, assess CRC risk levels, understand personalized CRC risk factors, and seek professional advices for people with CRC concerns. The system is implemented based on the Django Model-View-Controller (MVC) framework with an extensible background MySQL database. A CRC absolute risk prediction model is applied to calculate the personalized CRC risk score with a user-friendly web survey. An interactive dashboard using advanced data visualization technics will display and interpret the risk scores and factors. Based on the risk assessment, a structured decision tree algorithm will provide the recommendations on customized CRC screening methods. The CDSS also provides a search function for preferred providers and hospitals based on geographical information and patient preferences.ResultsA prototype of the patient-oriented CRC CDSS has been developed. It provides an open assessment of potential CRC risks via an online survey. The CRC risk predictive model has been implemented. The prediction outcomes of risk levels and factors are presented to the users through a personalized interactive visualization interface, to guide the public on how to reduce the CRC risks by changing their living styles (such as smoking and drinking) and diet characteristics (such as consumptions of red meat and milk). The CDSS will also provide customized recommendations on screening methods based on the corresponding risk factors. For users seeking professional clinicians, the CDSS also provides a convenient tool for searching nearby hospitals and available doctors based on the location preferences and providers characteristics (such as gender, language, and specialty).ConclusionsThis CRC CDSS prototype provides a patient-friendly interface for CRC risk assessment and gives a personalized interpretation on important CRC risk factors. It is a useful tool to educate the public on CRC, to provide guidance on minimizing CRC risks, and to promote early CRC screening that reduces the CRC occurrences.

Dataset Information

Provider Survey on Automated Clinical Decision Support for Cardiovascular Risk Assessment.

Publications

Provider Survey on Automated Clinical Decision Support for Cardiovascular Risk Assessment.

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