Healthc Inform Res.  2010 Dec;16(4):260-272. 10.4258/hir.2010.16.4.260.

Integration and Evaluation of Clinical Decision Support Systems for Diagnosis Idopathics Pulmonary Fibrosis (IPF)

• Lee Y
• Chae Y
• Jeon S

• KMID: 2284539
• DOI: http://doi.org/10.4258/hir.2010.16.4.260

Abstract

OBJECTIVES
The purpose of this study was to develop clinical decision support systems (CDSS) that are integrated with hospital information systems for the differential diagnosis of idiopathic pulmonary fibrosis (IPF).
METHODS
The integrated CDSS were validated and evaluated by physicians. Knowledge modeling for diagnosing IPF was performed by knowledge working groups, composed of radiologists and respiratory specialists. In order to develop the model for CDSS diagnosis, the clinical cases were collected from 290 cases from Seoul National University Hospital and Sevrance Hospital of Yonsei University. For the evaluation of integrated CDSS, interviews were conducted with respiratory specialists and radiologist 2 weeks after applying CDSSs in clinical settings. The CDSS was integrated with the computer vision system (CVS) and diffuse parenchymal lung diseases (DPLD), CDSS developed in our previous project.
RESULTS
Eighteen cases diagnosed as IPF were applied to the collection of diagnostic knowledge and the refined knowledge, the former diagnosed 1 case (6%) and the latter diagnosed 14 cases (78%). Therefore, the refined knowledge performed better than collected knowledge. The validation results of integrated CDSSs showed that 81 cases (74.3%) were diagnosed correctly.
CONCLUSIONS
There were 109 cases of IPF diagnosed and initiated on treatment. The significance of this study is in developing integrated CDSS with PACS by acquiring and redefining the knowledge needed for IPF diagnosis. In addition, it is significant for the integration of CDSS to verification and clinical evaluation.

Keyword

Clinical Decision Support Systems; Idiopathic Pulmonary Fibrosis; Computer Vision System; Radiology Information Systems

MeSH Terms

Decision Support Systems, Clinical
Diagnosis, Differential
Hospital Information Systems
Idiopathic Pulmonary Fibrosis
Lung Diseases, Interstitial
Machine Learning
Pulmonary Fibrosis
Radiology Information Systems
Specialization

Figure

• 

  Figure 1 The architecture of two integrated CDSSs using a data warehouse. CDSS: clinical decision support systems, GGO: ground-glass opacities, DPLD: diffuse parenchymal lung diseases, PACS: picture archiving and communication system, LIS: laboratory information system, OCS: order communication system, PFT: pulmonary function tests, DPLD-CDSS: CDSS for radiological diagnosis on DPLD [13], CVS: computer vision system extracting GGO, HRCT: high-resolution computed tomography.

• 

  Figure 2 The flowchart on diagnosis of idopathics pulmonary fibrosis (IPF). DOE: dyspnoea on exertion, D: duration, PFT: pulmonary function test, HC: honey combing, Sub: subpleural location predominancy, No cons: absence of consolidation, GGO: ground glass opacity, CTD: connective tissue disease, ANA: antinuclear antibodies, RF: rheumatoid factor, BAL: bronchoaveolar lavage.

• 

  Figure 3 The idopathics pulmonary fibrosis (IPF) clinical decision support systems (CDSS) screen. Patient's information for diagnosis on IPF are extracted from the datawherehouse and presented on the CDSS screen. The buttons on screen; SAVE: save the all of patient clinical information from datawarehouse, HRCT results: a physician is able to evaluate the radiological findings resulted from CVS radiology diagnosis consolidation, GGO, traction bronchiectasis, subpleural location historical features & physical findings. C.C.: chief complaint, DOE: dyspnoea on exertion, Velcro: velcro rales, PFTs: pulmonary function standards for tests, ANA: antinuclear antibodies, FVC: forced vital capacity, FEV: forced expiratory volume, BAL: bronchoalveolar lavage; surgical lung biopsy, TBLB Bx: transbronchial biopsy, BAL Bx: bronchoalveolar lavage biopsy.

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