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Innovative Digital Tools and Surveillance Systems for the Timely Detection of Adverse Events at the Point of Care: A Proof-of-Concept Study

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Abstract

Introduction and Objective

Regulatory authorities often receive poorly structured safety reports requiring considerable effort to investigate potential adverse events post hoc. Automated question-and-answer systems may help to improve the overall quality of safety information transmitted to pharmacovigilance agencies. This paper explores the use of the VACC-Tool (ViVI Automated Case Classification Tool) 2.0, a mobile application enabling physicians to classify clinical cases according to 14 pre-defined case definitions for neuroinflammatory adverse events (NIAE) and in full compliance with data standards issued by the Clinical Data Interchange Standards Consortium.

Methods

The validation of the VACC-Tool 2.0 (beta-version) was conducted in the context of a unique quality management program for children with suspected NIAE in collaboration with the Robert Koch Institute in Berlin, Germany. The VACC-Tool was used for instant case classification and for longitudinal follow-up throughout the course of hospitalization. Results were compared to International Classification of Diseases , Tenth Revision (ICD-10) codes assigned in the emergency department (ED).

Results

From 07/2013 to 10/2014, a total of 34,368 patients were seen in the ED, and 5243 patients were hospitalized; 243 of these were admitted for suspected NIAE (mean age: 8.5 years), thus participating in the quality management program. Using the VACC-Tool in the ED, 209 cases were classified successfully, 69 % of which had been missed or miscoded in the ED reports. Longitudinal follow-up with the VACC-Tool identified additional NIAE.

Conclusion

Mobile applications are taking data standards to the point of care, enabling clinicians to ascertain potential adverse events in the ED setting and during inpatient follow-up. Compliance with Clinical Data Interchange Standards Consortium (CDISC) data standards facilitates data interoperability according to regulatory requirements.

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Correspondence to Barbara Rath.

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Funding

No sources of funding were used to assist in the preparation of this study. Virus diagnostics for the quality management program were provided in-kind by the Robert Koch Institute.

Conflicts of interest

Christian Hoppe, Patrick Obermeier, Susann Muehlhans, Maren Alchikh, Lea Seeber, Franziska Tief, Katharina Karsch, Xi Chen, Sindy Boettcher, Sabine Diedrich, Tim Conrad, Bron Kisler, and Barbara Rath have no conflicts of interest that are directly relevant to the content of this study.

Ethical approval

The quality management program was approved by the Charité Institutional Review Board (EA2/161/11). Informed consent procedures were waived by the Institutional Review Board for the purpose of quality improvement and infection control.

Additional information

C. Hoppe, P. Obermeier and B. Rath contributed equally to the article.

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Hoppe, C., Obermeier, P., Muehlhans, S. et al. Innovative Digital Tools and Surveillance Systems for the Timely Detection of Adverse Events at the Point of Care: A Proof-of-Concept Study. Drug Saf 39, 977–988 (2016). https://doi.org/10.1007/s40264-016-0437-6

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