Studies in health technology and informatics
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Stud Health Technol Inform · Jan 2013
Detecting software failures in the MAUDE database: a preliminary analysis.
The MAUDE (Manufacturer and User facility Device Experience) was analyzed to identify challenges in detecting software failure causing Medical Device (MD) adverse events.
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MMVR has provided the leading forum for the multidisciplinary interaction and development of the use of Virtual Reality (VR) techniques in medicine, particularly in surgical practice. Here we look back at the foundations of our field, focusing on the use of VR in Surgery and similar interventional procedures, sum up the current status, and describe the challenges and opportunities going forward.
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Stud Health Technol Inform · Jan 2013
Comparative StudyAre smartphones comparable to laptops for image diagnosis in teleophthalmology?
To assess the reliability and accuracy of smartphones in diagnosing transmitted fundus images in comparison with a laptop. ⋯ Smartphones are as effective as the laptop in diagnosing fundus pathologies and hold promise for teleophthalmology in future.
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Stud Health Technol Inform · Jan 2013
Clinical decision support systems: data quality management and governance.
This chapter examines data quality management (DQM) and information governance (IG) of electronic decision support (EDS) systems so that they are safe and fit for use by clinicians and patients and their carers. This is consistent with the ISO definition of data quality as being fit for purpose. ⋯ It must also include protocols and mechanisms to monitor the safety of EDS, which will feedback into DQM & IG activities. Ultimately, DQM & IG must be integrated across the data cycle to ensure that the EDS systems provide guidance that leads to safe and effective clinical decisions and care.
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Stud Health Technol Inform · Jan 2013
Automatic system testing of a decision support system for insulin dosing using Google Android.
Hyperglycaemia in hospitalized patients is a common and costly health care problem. The GlucoTab system is a mobile workflow and decision support system, aiming to facilitate efficient and safe glycemic control of non-critically ill patients. Being a medical device, the GlucoTab requires extensive and reproducible testing. ⋯ In 144 data points (12.1%), calculation errors of physicians and nurses in the PBCT were detected. The test framework was able to verify manual calculation of insulin doses and detect relatively many user errors and workflow anomalies in the PBCT data. This shows the high potential of the electronic decision support application to improve safety of implementation of an insulin titration protocol and workflow management system in clinical wards.