DICOM image integration into an electronic medical record using thin viewing clients

Purpose -- To integrate radiological DICOM images into our currently existing web-browsable Electronic Medical Record (MINDscape). Over the last five years the University of Washington has created a clinical data repository combining in a distributed relational database information from multiple departmental databases (MIND). A text-based view of this data called the Mini Medical Record (MMR) has been available for three years. MINDscape, unlike the text based MMR, provides a platform independent, web browser view of the MIND dataset that can easily be linked to other information resources on the network. We have now added the integration of radiological images into MINDscape through a DICOM webserver. Methods/New Work -- we have integrated a commercial webserver that acts as a DICOM Storage Class Provider to our, computed radiography (CR), computed tomography (CT), digital fluoroscopy (DF), magnetic resonance (MR) and ultrasound (US) scanning devices. These images can be accessed through CGI queries or by linking the image server database using ODBC or SQL gateways. This allows the use of dynamic HTML links to the images on the DICOM webserver from MINDscape, so that the radiology reports already resident in the MIND repository can be married with the associated images through the unique examination accession number generated by our Radiology Information System (RIS). The web browser plug-in used provides a wavelet decompression engine (up to 16-bits per pixel) and performs the following image manipulation functions: window/level, flip, invert, sort, rotate, zoom, cine-loop and save as JPEG. Results -- Radiological DICOM image sets (CR, CT, MR and US) are displayed with associated exam reports for referring physician and clinicians anywhere within the widespread academic medical center on PCs, Macs, X-terminals and Unix computers. This system is also being used for home teleradiology application. Conclusion -- Radiological DICOM images can be made available medical center wide to physicians quickly using low-cost and ubiquitous, thin client browsing technology and wavelet compression.