Literature DB >> 9268852

Developing a radiology data base for quality assurance.

P J Haug1, M Farrell, J Frear, D Blatter, P R Frederick.   

Abstract

Radiology Information Systems (RIS) are designed to capture and manage the data associated with ordering, executing, reporting, and billing x-ray procedures. The HELP Hospital Information System contains a radiology subsystem that supports these functions. In an effort to enhance quality assurance initiatives, we have created a supplemental data base. This data base contains not only the data traditionally generated by RISs but also data from the hospital system that is relevant to quality assurance. One of the goals associated with this data base is to use techniques from the discipline of Continuous Quality Improvement (CQI) in the radiology department. A focus of our initial efforts has been the time necessary to provide x-ray reports to ordering physicians once the imaging examination has been performed. Efforts to manage the portion of this time interval caused by transcription have resulted in a substantial decrease in the time required for this function. A second goal of this project is to evaluate the quality of x-ray ordering. This objective requires a computerized record of the outcome of the x-ray procedure. Initial analysis of data derived from this data base indicates significant differences in the ordering behavior for computed tomography (CT) examinations among a test group of physicians. A third goal is to do quality assurance on x-ray reports. Experience with pilot systems has shown promising results using a mathematical model of report quality. We hope to leverage these techniques and this quality assurance data base to define a COI process for medical reports in general and for x-ray reports in particular.

Mesh:

Year:  1997        PMID: 9268852      PMCID: PMC3452796          DOI: 10.1007/bf03168670

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  7 in total

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  7 in total
  1 in total

1.  Radiology Quality Measure Compliance Reporting: an Automated Approach.

Authors:  Marc Kohli; Duane Schonlau
Journal:  J Digit Imaging       Date:  2016-06       Impact factor: 4.056

  1 in total

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