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1.
Health Inf Manag ; 44(2): 4-10, 2015.
Article in English | MEDLINE | ID: mdl-26157081

ABSTRACT

OBJECTIVE: To conduct a systematic review of the literature describing the impact of speech recognition systems on report error rates and productivity in radiology departments. METHODS: The search was conducted for relevant papers published from January 1992 to October 2013. Comparative studies reporting any of the following outcomes were selected: error rates, departmental productivity, and radiologist productivity. The retrieved studies were assessed for quality and risk of bias. RESULTS: The literature search identified 85 potentially relevant publications, but, based on the inclusion and exclusion criteria, only 20 were included. Most studies were before and after assessments with no control group. There was a large amount of heterogeneity due to differences in the imaging modalities assessed and the outcomes measured. The percentage of reports containing at least one error varied from 4.8% to 89% for speech recognition, and from 2.1% to 22% for transcription. Departmental productivity was improved with decreases in report turnaround times varying from 35% to 99%. Most studies found a lengthening of radiologist dictation time. CONCLUSION: Overall gains in departmental productivity were high, but radiologist productivity, as measured by the time to produce a report, was diminished.


Subject(s)
Medical Records Systems, Computerized/standards , Radiology Information Systems/standards , Speech Recognition Software , Efficiency, Organizational , Radiology Department, Hospital
2.
IEEE Trans Neural Syst Rehabil Eng ; 20(4): 432-42, 2012 Jul.
Article in English | MEDLINE | ID: mdl-22491131

ABSTRACT

In this paper, we present an implantable device for intra-cerebral electroencephalography (icEEG) data acquisition and real-time epileptic seizure detection with simultaneous focal antiepileptic drug injection feedback. This implantable device includes a neural signal amplifier, an asynchronous seizure detector, a drug delivery system (DDS) including a micropump, and a hybrid subdural electrode (HSE). The asynchronous detection algorithm is based on data-dependent analysis and validated with Matlab tools. The detector and DDS have a power saving mode. The HSE contacts are made of Platinum (Pt) encapsulated with polydimethylsiloxane (PDMS). Given the heterogeneity of electrographic seizure signals and seizure suppression threshold, the implantable device provides tunable parameters facility through an external transmitter to adapt to each individual's neurophysiology prior to clinical deployment. The proposed detector and DDS were assembled in Ø 50 mm and Ø 30 mm circular printed circuit boards, respectively. The detector was validated using icEEG recordings of seven patients who had previously undergone an intracranial investigation for epilepsy surgery. The triggering of the DDS was tested and a predefined seizure suppression dose was delivered ~16 s after electrographical seizure onsets. The device's power consumption was reduced by 12% in active mode and 49% in power saving mode compared to similar seizure detection algorithms implemented with synchronous architecture.


Subject(s)
Anticonvulsants/administration & dosage , Biofeedback, Psychology/instrumentation , Drug Therapy, Computer-Assisted/instrumentation , Electroencephalography/instrumentation , Epilepsy/diagnosis , Epilepsy/drug therapy , Infusion Pumps, Implantable , Adolescent , Adult , Chronic Disease , Drug Implants/administration & dosage , Drug Therapy, Computer-Assisted/methods , Electrodes, Implanted , Equipment Design , Equipment Failure Analysis , Female , Humans , Male , Middle Aged , Treatment Outcome , Young Adult
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