We have located links that may give you full text access.
Developing and implementing a heart failure data mart for research and quality improvement.
Informatics for Health & Social Care 2018 April 20
OBJECTIVE: The purpose of this project was to build and formatively evaluate a near-real time heart failure (HF) data mart. Heart Failure (HF) is a leading cause of hospital readmissions. Increased efforts to use data meaningfully may enable healthcare organizations to better evaluate effectiveness of care pathways and quality improvements, and to prospectively identify risk among HF patients.
METHODS AND PROCEDURES: We followed a modified version of the Systems Development Life Cycle: 1) Conceptualization, 2) Requirements Analysis, 3) Iterative Development, and 4) Application Release. This foundational work reflects the first of a two-phase project. Phase two (in process) involves the implementation and evaluation of predictive analytics for clinical decision support.
RESULTS: We engaged stakeholders to build working definitions and established automated processes for creating an HF data mart containing actionable information for diverse audiences. As of December 2017, the data mart contains information from over 175,000 distinct patients and >100 variables from each of their nearly 300,000 visits.
CONCLUSION: The HF data mart will be used to enhance care, assist in clinical decision-making, and improve overall quality of care. This model holds the potential to be scaled and generalized beyond the initial focus and setting.
METHODS AND PROCEDURES: We followed a modified version of the Systems Development Life Cycle: 1) Conceptualization, 2) Requirements Analysis, 3) Iterative Development, and 4) Application Release. This foundational work reflects the first of a two-phase project. Phase two (in process) involves the implementation and evaluation of predictive analytics for clinical decision support.
RESULTS: We engaged stakeholders to build working definitions and established automated processes for creating an HF data mart containing actionable information for diverse audiences. As of December 2017, the data mart contains information from over 175,000 distinct patients and >100 variables from each of their nearly 300,000 visits.
CONCLUSION: The HF data mart will be used to enhance care, assist in clinical decision-making, and improve overall quality of care. This model holds the potential to be scaled and generalized beyond the initial focus and setting.
Full text links
Related Resources
Trending Papers
Challenges in Septic Shock: From New Hemodynamics to Blood Purification Therapies.Journal of Personalized Medicine 2024 Februrary 4
Molecular Targets of Novel Therapeutics for Diabetic Kidney Disease: A New Era of Nephroprotection.International Journal of Molecular Sciences 2024 April 4
Perioperative echocardiographic strain analysis: what anesthesiologists should know.Canadian Journal of Anaesthesia 2024 April 11
The 'Ten Commandments' for the 2023 European Society of Cardiology guidelines for the management of endocarditis.European Heart Journal 2024 April 18
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app