Designing a Clinical Decision Support System for Managing and Treating Patients with the Chief Complaint of Vertigo

Document Type : Original Article (s)

Authors

1 Associate Professor, Department of Emergency Medicine, School of Medicine AND Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran

2 Resident, Department of Emergency Medicine, School of Medicine AND Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran

Abstract

Background: One of the challenging issues for emergency specialists is the etiology of dizziness. Using portable software installing in the mobile cell can help the clinicians to reduce the effects of confounders in emergency treatment of patients.Methods: This study was conducted in 2017 in the Department of Emergency, Rasoul-e Akram hospital, Tehran, Iran. After designing the management protocol for patients with vertigo based on the literature and standards, the validity of the protocol was approved by the expert panel. A number of 190 patients with vertigo were diagnosed using two methods for treatment and management of the disease. The first group were assessed using designed clinical decision support system, and the second group were assessed using routine method. Treatment duration, maintenance duration, and the differences between the primary and the final diagnosis were compared between the groups.Findings: Differences between the primary and the final diagnosis were significant among both groups (P < 0.050). Mean treatment duration was 3.38 and 4.96 hours in the first and second groups using support system and routine methods, respectively (P < 0.001). Mean hospitalization period was significantly shorter in support system group (9.37 hours) compared to routine method group (11.17 hours) (P < 0.001). The level of physician satisfaction with the support system was average (47.9%).Conclusion: Using clinical decision support system can greatly help physicians to improve the diagnosis, decrease the hospitalization period, and manage the patients with the chief complaint of vertigo much better.

Keywords

References

  1. Semaan MT, Megerian CA. Meniere's disease: A challenging and relentless disorder. Otolaryngol Clin North Am 2011; 44(2): 383-403, ix.
  2. Goddard JC, Fayad JN. Vestibular neuritis. Otolaryngol Clin North Am 2011; 44(2): 361-5.
  3. Huppert D, Strupp M, Muckter H, Brandt T. Which medication do I need to manage dizzy patients? Acta Otolaryngol 2011; 131(3): 228-41.
  4. Power DJ, Sharda R. Decision support systems. In: Nof SY, editor. Springer handbook of automation. Berlin, Heidelberg, Germany: Springer Berlin Heidelberg; 2009. p. 1539-48.
  5. Berner ES. Clinical decision support systems. New York, NY: Springer; 2007.
  6. Saronga HP, Dalaba MA, Dong H, Leshabari M, Sauerborn R, Sukums F, et al. Cost of installing and operating an electronic clinical decision support system for maternal health care: case of Tanzania rural primary health centres. BMC Health Serv Res 2015; 15: 132.
  7. Bouaud J, Lamy JB. A medical informatics perspective on clinical decision support systems. Findings from the yearbook 2013 section on decision support. Yearb Med Inform 2013; 8: 128-31.
  8. Tavakoli N, Hosseini Kasnavieh SM, Yasinzadeh M, Amini M, Mahmoudi NM. Evaluation of appropriate and inappropriate admission and hospitalization days according to Appropriateness Evaluation Protocol (AEP). Arch Iran Med 2015; 18(7): 430-4.
  9. Hayward J, Thomson F, Milne H, Buckingham S, Sheikh A, Fernando B, et al. 'Too much, too late': mixed methods multi-channel video recording study of computerized decision support systems and GP prescribing. J Am Med Inform Assoc 2013; 20(e1): e76-e84.
  10. Yin Z, Dong Z, Lu X, Yu S, Chen X, Duan H. A clinical decision support system for the diagnosis of probable migraine and probable tension-type headache based on case-based reasoning. J Headache Pain 2015; 16: 29.
  11. Halldorsson BV, Bjornsson AH, Gudmundsson HT, Birgisson EO, Ludviksson BR, Gudbjornsson B. A clinical decision support system for the diagnosis, fracture risks and treatment of osteoporosis. Comput Math Methods Med 2015; 2015: 189769.
  12. Anchala R, Kaptoge S, Pant H, Di AE, Franco OH, Prabhakaran D. Evaluation of effectiveness and cost-effectiveness of a clinical decision support system in managing hypertension in resource constrained primary health care settings: results from a cluster randomized trial. J Am Heart Assoc 2015; 4(1): e001213.
  13. Graham TA, Kushniruk AW, Bullard MJ, Holroyd BR, Meurer DP, Rowe BH. How usability of a web-based clinical decision support system has the potential to contribute to adverse medical events. AMIA Annu Symp Proc 2008; 2008: 257-61.
Journal of Isfahan Medical School
Volume 35, Issue 460 - Serial Number 460
November and December 2018
Pages 1806-1811

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History

  • Receive Date: 16 December 2017
  • Revise Date: 02 November 2024
  • Accept Date: 06 April 2022

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