Bmc Med Inform Decis
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Bmc Med Inform Decis · Nov 2011
Randomized Controlled TrialDesigning a patient-centered personal health record to promote preventive care.
Evidence-based preventive services offer profound health benefits, yet Americans receive only half of indicated care. A variety of government and specialty society policy initiatives are promoting the adoption of information technologies to engage patients in their care, such as personal health records, but current systems may not utilize the technology's full potential. ⋯ The IPHR demonstrates that a patient-centered personal health record that interfaces with the electronic medical record can give patients a high level of individualized guidance and be successfully adopted by busy primary care practices. Further study and refinement are necessary to make information systems even more patient-centered and to demonstrate their impact on care.
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Bmc Med Inform Decis · Oct 2011
Feasibility test of a UK-scalable electronic system for regular collection of patient-reported outcome measures and linkage with clinical cancer registry data: the electronic Patient-reported Outcomes from Cancer Survivors (ePOCS) system.
Cancer survivors can face significant physical and psychosocial challenges; there is a need to identify and predict which survivors experience what sorts of difficulties. As highlighted in the UK National Cancer Survivorship Initiative, routine post-diagnostic collection of patient reported outcome measures (PROMs) is required; to be most informative, PROMs must be linked and analysed with patients' diagnostic and treatment information. We have designed and built a potentially cost-efficient UK-scalable electronic system for collecting PROMs via the internet, at regular post-diagnostic time-points, for linking these data with patients' clinical data in cancer registries, and for electronically managing the associated patient monitoring and communications; the electronic Patient-reported Outcomes from Cancer Survivors (ePOCS) system. This study aims to test the feasibility of the ePOCS system, by running it for 2 years in two Yorkshire NHS Trusts, and using the Northern and Yorkshire Cancer Registry and Information Service. ⋯ There is currently no system in the UK for collecting PROMs online and linking these with patients' clinical data in cancer registries. If feasible, ePOCS has potential to provide an affordable UK-scalable technical platform to facilitate and support longitudinal cohort research, and improve understanding of cancer survivors' experiences. Comprehensive understanding of survivorship difficulties is vital to inform the development and provision of supportive services and interventions.
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Bmc Med Inform Decis · Sep 2011
Enhanced health event detection and influenza surveillance using a joint Veterans Affairs and Department of Defense biosurveillance application.
The establishment of robust biosurveillance capabilities is an important component of the U.S. strategy for identifying disease outbreaks, environmental exposures and bioterrorism events. Currently, U.S. Departments of Defense (DoD) and Veterans Affairs (VA) perform biosurveillance independently. This article describes a joint VA/DoD biosurveillance project at North Chicago-VA Medical Center (NC-VAMC). The Naval Health Clinics-Great Lakes facility physically merged with NC-VAMC beginning in 2006 with the full merger completed in October 2010 at which time all DoD care and medical personnel had relocated to the expanded and remodeled NC-VAMC campus and the combined facility was renamed the Lovell Federal Health Care Center (FHCC). The goal of this study was to evaluate disease surveillance using a biosurveillance application which combined data from both populations. ⋯ Biosurveillance in a joint VA/DoD facility showed potential utility as a tool to improve surveillance and situational awareness in an area with Veteran, active duty and beneficiary populations. Based in part on the results of this pilot demonstration, both agencies have agreed to support the creation of a combined VA/DoD ESSENCE biosurveillance system which is now under development.
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Bmc Med Inform Decis · Jan 2011
Integrating an internet-mediated walking program into family medicine clinical practice: a pilot feasibility study.
Regular participation in physical activity can prevent many chronic health conditions. Computerized self-management programs are effective clinical tools to support patient participation in physical activity. This pilot study sought to develop and evaluate an online interface for primary care providers to refer patients to an Internet-mediated walking program called Stepping Up to Health (SUH) and to monitor participant progress in the program. ⋯ Providers successfully referred patients using the SUH provider interface, but were less willing to monitor patient compliance in the program. Patients who completed the program significantly increased their step counts. Future research is needed to test the effectiveness of integrating SUH with clinical information systems over a longer evaluation period.
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Bmc Med Inform Decis · Jan 2011
Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model.
The intensive care unit (ICU) length of stay (LOS) of patients undergoing cardiac surgery may vary considerably, and is often difficult to predict within the first hours after admission. The early clinical evolution of a cardiac surgery patient might be predictive for his LOS. The purpose of the present study was to develop a predictive model for ICU discharge after non-emergency cardiac surgery, by analyzing the first 4 hours of data in the computerized medical record of these patients with Gaussian processes (GP), a machine learning technique. ⋯ A GP model that uses PDMS data of the first 4 hours after admission in the ICU of scheduled adult cardiac surgery patients was able to predict discharge from the ICU as a classification as well as a regression task. The GP model demonstrated a significantly better discriminative power than the EuroSCORE and the ICU nurses, and at least as good as predictions done by ICU physicians. The GP model was the only well calibrated model.