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Evaluation factors for testing and validation of Clinical Reporting System

Meenakshi Sharma1 , Himanshu Aggarwal2

  1. Computer Science and Engineering Department,G.I.M.E.T,Amritsar, India.
  2. Computer Engineering Department, Punjabi University, Patiala, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-2 , Page no. 264-268, Feb-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i2.264268

Online published on Feb 28, 2018

Copyright © Meenakshi Sharma, Himanshu Aggarwal . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Meenakshi Sharma, Himanshu Aggarwal, “Evaluation factors for testing and validation of Clinical Reporting System,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.2, pp.264-268, 2018.

MLA Style Citation: Meenakshi Sharma, Himanshu Aggarwal "Evaluation factors for testing and validation of Clinical Reporting System." International Journal of Computer Sciences and Engineering 6.2 (2018): 264-268.

APA Style Citation: Meenakshi Sharma, Himanshu Aggarwal, (2018). Evaluation factors for testing and validation of Clinical Reporting System. International Journal of Computer Sciences and Engineering, 6(2), 264-268.

BibTex Style Citation:
@article{Sharma_2018,
author = {Meenakshi Sharma, Himanshu Aggarwal},
title = {Evaluation factors for testing and validation of Clinical Reporting System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2018},
volume = {6},
Issue = {2},
month = {2},
year = {2018},
issn = {2347-2693},
pages = {264-268},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1736},
doi = {https://doi.org/10.26438/ijcse/v6i2.264268}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i2.264268}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1736
TI - Evaluation factors for testing and validation of Clinical Reporting System
T2 - International Journal of Computer Sciences and Engineering
AU - Meenakshi Sharma, Himanshu Aggarwal
PY - 2018
DA - 2018/02/28
PB - IJCSE, Indore, INDIA
SP - 264-268
IS - 2
VL - 6
SN - 2347-2693
ER -

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Abstract

Automate Clinical decision support system(CRS) provide assistance to physician as well as to society to enhance quality of healthcare. Methodical and apposite testing a of automate reporting system prior to liberate to end-users is kind of critical aspect any automate expert system related to healthcare domain. Testing and validation, is one of the most vital and critical step of CRS because lack of well defined testing tools , oversight this step may lead to dangerous and severe outcome issues. Great efforts are required for testing of system as data collecting form number of resources and may be in different formats. Clinic data available in Electronic Health Records (EHR) form. Testing of such huge amount of clinical data by human became to tedious and risky because chances of mistakes are there. Adaption rate of clinical reporting system quite slow, as many of them not tested properly prior to liberate .Testing and Validation of CRS depends on various factors that considered in this paper. For testing technique, considered functional and structural techniques by receiving information for input from every level of progress.

Key-Words / Index Term

Testing, Clinical reporting System, Evaluation factors, EHR

References

[1]Schmittdiel JA, Gopalan A, Lin MW, Banerjee S, Chau CV, Adams AS. Population management for diabetes: health care system-level approaches for improving quality and addressing disparities. Curr Diab, 2017;17:31.
[2] Meenakshi sharma and Dr. Himanshu Aggarwal," Methodologies of Legacy Clinical Decision Support System -A Review",Journal of Telecommunication, Electronic and Computer Engineering, 2017, Vol. 9 No. 3-6 41.
[3] Meenakshi sharma and Dr. Himanshu Aggarwal,“EHR Adoption in India: Potential and the Challenges”, Indian Journal of Science and Technology,2016.
[4] Wasson J, Sox H, Neff R, Goldman L. Clinical Prediction Rules. Applications and Methodological Standards. N Engl J Med 1985;313:793-799.
[5] Sailors RM, East TD. A model-based simulator for testing rule-based decision support systems for mechanical ventilation of ARDS patients. Proc Annu Symp Comput Appl Med Care 1994;1007:1007.
[6] Kinder AT, East TD, Littman WD, et al. A Computerized Decision Support System for Management of Mechanical Ventilation in Patients with ARDS: An Example of Exportation of a Knowledge Base. Proc Annu Symp Comput Appl Med Care 1994:888.
[7] Li AC, Kannry JL, Kushniruk A, Chrimes D, McGinn TG, Edonyabo D, Mann DM. Integrating ability testing and think-aloud protocol analysis with "near-live" clinical simulations in evaluating clinical decision support. Int J Med Inform. 2012 Nov;81(11):761–772. doi: 10.1016/j.ijmedinf.2012.02.009.
[8] Fieschi M, Dufour JC, Staccini P. Medical decision support systems: old dilemmas and new paradigms? Tracks for successful integration and adoption. Methods Inf Med 2003;42(3):190-8.
[9] Meenakshi sharma and Dr. Himanshu Aggarwal," Grand Barrier In Clinical Decision Support System," International Journal of Latest Trends In Engineering And Technology, Nov.2017,Vol. 9(2) p.no111- 115.
[10] Kushniruk AW, Kaufman DR, Patel VL, Lévesque Y, Lottin P. Assessment of a computerized patient record system: A cognitive approach to evaluating medical technology. MD Comput. 1996;13(5):406– 415.
[11] Li, W., Liu, L. and Gong, W. ,"Multi-objective uniform design as a SVM model selection tool for face recognition", Expert Systems with Applications, Vol. 38, no., pp.6689–6695,2011.
[12] P.R. Harper," A review and comparison of classification algorithms for medical decision making", Health Policy ,vol.71 ,no.3, pp.315–331,2005.
[13] Zhu, W., Zeng, N., Wang, N.," Sensitivity, specificity, accuracy, associated confidence interval and roc
analysis with practical SAS implementations. In",: NESUG Proceedings: Health Care and Life Sciences, Baltimore, Maryland., 2010.
[14] Kushniruk Andre W, Borycki Elizabeth M, Kuwata Shigeki, Kannry Joseph. Emerging approaches to usability evaluation of health information systems: Towards in-situ analysis of complex healthcare systems and environments. Stud Health Technol Inform. 2011;169:915–919