Reusable components for imaging informatics:

1. HIPAA logging
2. User Authentication and Authorization (LDAP)
3. Report and order data Warehouse via HL7
4. Context Web Portal
5. Integrated Content Management Systems and Wikis
6. Workflow engine
7. Graphical dashboarding

After reading our poster, you should be able to answer the following questions for each core component.

1. What is it?
2. Why do I need it?
3. What should I tell my IT folks?

The HIPAA tag-team includes a high-performance centralized HIPAA log for all next-generation applications, coupled with lightweight directory access protocol (LDAP(1)) to centralize authorization and authentication. This combination provides a one-stop-shop for auditing and user management, in addition to providing single-sign-on functionality.

Much of the data necessary to calculate valuable metrics, such as turn-around time, patient wait time, and scanner utilization, already exist in HL7 messages sent between RIS, PACS, SR, and the hospital information system (HIS). We will describe using Mirth,(2) an open-source HL7 engine to harness this data and wrangle it into a highly usable data warehouse.(3-5)

Many practices struggle with information systems that do not share patient and study context. This requires users to navigate to a particular patient several times during their normal workflow, and creates a significant barrier to entry.(6) Context integration maintains access to a specific patient or study in PACS, as well as several other applications. As more and more new applications are built that require context integration, a portal becomes useful. A context web portal is a simple application that takes context, and provides the user with context-specific links into multiple systems. This serves to maintain usability, and a clean user interface.

Documentation is integral to the support, management, and implementation of advanced systems. We will describe, using distributed knowledge management technology including content management systems and wikis,(7) to document, track, and manage these new radiology IT resources.

We will also describe effective use of issue tracking and management systems(8) which, when combined with other sources of data, can be used to generate powerful report cards and illuminate problems that could go unrecognized without novel data combinations.

We also advocate for a workflow engine that exists outside existing PACS or RIS systems to facilitate activities, such as quality assurance that is currently not well addressed with vendor-based solutions.

Graphical dashboards have become commonplace in industry and business, outside of medicine. The medical industry is only now beginning to realize the potential that exists in the large amount of electronic data that is generated.(9-12) Graphical dashboards provide radiologists, as well as department management, with easy-to-digest, real-time feedback on key metrics throughout the department, and can help identify problems before they would otherwise be realized.

Many current RIS systems do not allow for full-text report searching. By aggregating reports in a data warehouse outside of the RIS, reports can be indexed to allow keyword searching. By combining the following components: HL7 engine, data warehouse, HIPAA a tag team, and context sharing as illustrated in Figure 1, we can provide a new tool for decision support, quality assurance, and research.

Imagine the ability for one of your radiologists or residents faced with a tough case of right lower quadrant pain to quickly find 10 cases of acute appendicitis, and browse through several examples. Electronic reports provide the fodder for an automatically-updated teaching file that can provide decision support at the point-of-care.

Many of us struggle to comply with the 2008 JCAHO patient safety goals for reporting of critical test results.(13) In the absence of a dedicated-result delivery system, a report-searching tool can be useful to identify and monitor delivery of critical results. In addition, with a graphical dashboard, a radiology department can quickly see how many critical results are being delivered over any given timeframe.

Imagine being able to quickly identify how many patients have been seen in the past year with autoimmune pancreatitis, and how many of those have an MRI. This type of data mining can be performed prior to embarking down the lengthy institutional review board (IRB) process, saving valuable research time. This is one small step away from a HIPAA honest broker,(14,15) which when using the same report by archiving a system, could strip protected health information from reports and assign a research ID, allowing researchers to examine reports and identify patients more specifically, without IRB approval.

2. Webreach I. Mirth [Internet]. Webreach, Inc; Available from: http://www.mirthproject.org/

3. Prevedello L, Andriole K, Hanson R, Kelly P, Khorasani R. Business Intelligence Tools for Radiology: Creating a Prototype Model Using Open-Source Tools [Internet]. Journal of Digital Imaging. Available from: http://dx.doi.org/10.1007/s10278-008-9167-3.

4. Rubin DL, Desser TS. A data warehouse for integrating radiologic and pathologic data. J Am Coll Radiol. 2008;5(3):210-7.

5. Einbinder JS, Scully KW, Pates RD, Schubart JR, Reynolds RE. Case study: A data warehouse for an academic medical center. J Healthc Inf Manag. 2001;15(2):165-75.

6. Boonn W, Langlotz C. Radiologist Use of and Perceived Need for Patient Data Access. Journal of Digital Imaging. 2009;22(4):357-362.

7. Meenan C, King A, Toland C, Daly M, Nagy P. Use of a Wiki as a Radiology Departmental Knowledge Management System [Internet]. J Digit Imaging. January 2009;[cited 2009 Sep 10 ] Available from: http://www.ncbi.nlm.nih.gov/pubmed/19184221

8. Nagy P, Warnock M, Daly M, Rehm J, Ehlers K. Radtracker: A web-based open-source issue tracking tool. J Digit Imaging. 2002;15 Suppl 1114-119.

9. Morgan M, Branstetter B, Mates J, Chang P. Flying Blind: Using a Digital Dashboard to Navigate a Complex PACS Environment. Journal of Digital Imaging. 2006;19(1):69-75.

10. Nagy PG, Pierce B, Otto M, Safdar NM. Quality control management and communication between radiologists and technologists. J Am Coll Radiol. 2008;5(6):759-65.

11. Morgan M, Branstetter B, Lionetti D, Richardson J, Chang P. The Radiology Digital Dashboard: Effects on Report Turnaround Time. Journal of Digital Imaging. 2008;21(1):50-58.

12. Nagy PG, Warnock MJ, Daly M, Toland C, Meenan CD, Mezrich RS. Informatics in Radiology: Automated Web-based Graphical Dashboard for Radiology Operational Business Intelligence [Internet]. Radiographics. 2009;9:[cited 2009 Sep 11]. Available from: http://radiographics.rsna.org/content/early/2009/08/20/rg.297095701.full.

13. 2008 Critical Access Hospital National Patient Safety Goals | Joint Commission [Internet]. [cited 2009 Sep 10 ] Available from: http://www.jointcommission.org/PatientSafety/NationalPatientSafetyGoals/08_cah_npsgs.htm

14. Boyd AD, Saxman PR, Hunscher DA, et al. The University of Michigan Honest Broker: A Web-based Service for Clinical and Translational Research and Practice. J Am Med Inform Assoc. August 2009;M2985.

15. Silvey SA, Schulte J, Smaltz DH, Kamal J. Honest broker protocol streamlines research access to data while safeguarding patient privacy. AMIA Annu Symp Proc.