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Abstract: SA-PO391

The Impact of a Diagnostic Support System on Rare Disease Cases

Session Information

Category: Glomerular Diseases

  • 1203 Glomerular Diseases: Clinical, Outcomes, and Trials

Authors

  • Ronicke, Simon, Medizinische Hochschule Hannover, Hannover, Germany
  • Hirsch, Dr. martin Christian, Ada Health GmbH, Berlin, Germany
  • Türk, Ewelina, Ada Health GmbH, Berlin, Germany
  • Wagner, Annette D., Medizinische Hochschule Hannover, Hannover, Germany
Background

Diagnostic support systems (DSS) can be used to enhance clinical diagnosis. We report about the use of Ada/DX, a DSS in development, in an outpatient clinic for rare inflammatory systemic diseases with kidney involvement. Presenting preliminary results, we evaluate the system's diagnostic accuracy and potential impact on the time to diagnosis.

Methods

This retrospective study is being conducted at the outpatient clinic for rare inflammatory systemic diseases with kidney involvement at the Hannover Medical School, Germany. To date, 67 (of a total 120) patient cases with confirmed diagnosis were included.
The time of the visit of first documented symptoms and the time of diagnosis was identified. Time to diagnosis (TD) was calculated. Information from the medical record was transferred to the DSS and the disease suggestions in the DSS were evaluated. Primary endpoint was the correctness of top disease suggestions for the visit of diagnosis. In these cases, secondary endpoints were the time to first correct top rare disease suggestion (TR) and the time to first correct top 5 rare disease suggestion (T5R). The difference between TD and TR and the difference between TD and T5R was calculated. Wilcoxon signed-rank test was conducted.

Results

On preliminary evaluation, primary accuracy of top suggestions of the DSS at the time of diagnosis was 80.6% (71.1% to 90,3%, 95% CI).
The table shows a comparison of time to diagnosis with and without the aid of the DSS. The Wilcoxon signed-rank test shows a significant difference for TD - TR (z-score -4.78, α=0.05, p<0.001) and TD - T5R (z-score -5.44, α=0.05, p<0.001).

Conclusion

The DSS suggested the correct diseases based on information from the medical record in most of the analysed rare disease cases. The DSS often suggested the correct diseases at times prior to the visit of diagnosis. DSS might help to reduce time to diagnosis and improve patient outcomes. Prospective research is needed to verify the results.

Comparison of the original time to diagnosis and the time to correct DDS disease suggestions
 MeanStd DevPCTL 25PCTL 50PCTL 75
TD56.5187.22.017.055.5
TR23.047.40.02.019.0
T5R11.331.50.00.04.0
TD - TR32.474.50.01.020.5
TD - T5R44.282.70.88.039.4

Times expressed in months