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  • Clinical Decision Support Systems in outpatient pediatric practice

    Редактор | 2019, Original articles, Practical medicine part 17 №5. 2019 | 2 декабря, 2019

    E.A. BALASHOVA, L.I. MAZUR

    Samara State Medical University, Samara

     Contact details:

    Balashova E.A. — Ph. D. (medicine), Associate Professor of the Hospital Pediatrics Department

    Address: 89 Chapaevskaya St., Samara, Russian Federation, 443099, tel.: +7 (846) 207-31-04; e-mail: mine22@yandex.ru

    When conducting dynamic monitoring of children in outpatient settings, the unified methods of clinical examination and health assessment play an important role. Electronic Clinical Decision Support Systems (DSS) can assist a physician in systematization of patient’s medical information.

    The disadvantages of DSS are the costs of development, implementation and maintenance, providing personal data security and difficulties in personnel training, as well as the need for duplication of information and disruption of work when a system fails. On the other hand, the introduction of DSS increases the examination and history completeness and stimulates a patient for an active dialogue.

    In our opinion, DSS are most effective when aimed at bringing the doctor’s tactics in line with clinical guidelines. In collaboration with Samara State University of Economics, we developed a DSS for outpatient pediatric setting. Based on the family and obstetric history and examination results, DSS determines risk groups and whether there is a need to correct the observation program in the first year of life. The program dynamically tracks physical, motor and cognitive development, creates a vaccination calendar and a calendar of check-ups by a pediatrician, specialists, laboratory and instrumental tests.

    Key words: decision-making support systems, children, outpatient setting.

     (For citation: Balashova E.A, Mazur L.I. Clinical Decision Support Systems in outpatient pediatric practice. Practical Medicine. 2019. Vol. 17, № 5, P. 185-190)

    REFERENCES

    1. Frolova M.S., Frolov S.V., Tolstukhin I.A. Decision support systems for the tasks of equipping medical institutions with medical equipment. Voprosy sovremennoy nauki i praktiki, 2014, no. 52, pp. 106–111 (in Russ.).
    2. Taranov Yu.A. Analysis of significant factors in the development of a decision support system in the perinatal center for the south of the Tyumen region. Fundamental’nye issledovaniya, 2013, no. 4–3, pp. 602–607 (in Russ.).
    3. Castaneda C., Nalley K., Mannion C. et al. Clinical decision support system for improving diagnostic accuracy and achieving precision medicine. Journal of Clinical Bioinformatics, 2015, vol. 5, p. 4.
    4. Kobrinskiy B.A. Decision support systems in healthcare and training. Vrach i informatsionnye tekhnologii, 2010, no. 2, pp. 39–45 (in Russ.).
    5. Bychenkov K.V., Gritsenko E.A., Martyshkin D.M. et al. Razrabotka intellektual’noy sistemy podderzhki prinyatiya resheniy dlya okazaniya personifitsirovannoy meditsinskoy pomoshchi patsientam na osnove ontologiy i komp’yuternykh sredstv predstavleniya znaniy [Development of an intelligent decision support system for providing personalized medical care to patients based on ontologies and computer-based knowledge representation tools]. Problemy upravleniya i modelirovaniya v slozhnykh sistemakh: Trudy XIII mezhdunarodnoy konferentsii. Samara: Samarskiy NTs RAN, 2011.
    6. Khalafyan A.A. Analiz i sintez meditsinskikh sistem podderzhki prinyatiya resheniy na osnove tekhnologiy statisticheskogo modelirovaniya: avtoref. dis. … d-ra tekh. nauk [Analysis and synthesis of medical decision support systems based on statistical modeling technologies. Synopsis of dis. Dr technical sciences]. Krasnodar, 2010.
    7. Conejar R.J., Kim H.-K. A medical decision support system (DSS) for ubiquitous healthcare diagnosis system. International Journal of Software Engineering and Its Applications, 2014, vol. 8 (10), pp. 237–244.
    8. Bauer N.S., Carroll A.E., Saha C., Downs S.M. Computer decision support changes physician practice but not knowledge regarding autism spectrum disorders. Appl Clin Inform, 2015, vol. 6 (3), pp. 454–465.
    9. Shojania K.G., Jennings A., Mayhew A. et al. Effects of point-of-care computer reminders on physician behavior: a systematic review. CMAJ, 2010, vol. 182 (5), pp. E216–E225.
    10. Roshanov P.S., You J.J., Dhaliwal J. et al. Can computerized clinical decision support systems improve practitioners’ diagnostic test ordering behavior? A decision-maker-researcher partnership systematic review. Implementation Science, 2011, vol. 6, pp. 88.
    11. Nijman R.G., Vergouwe Y., Thompson M. et al. Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: diagnostic study. BMJ, 2013, vol. 346, p. f1706.
    12. de Vos-Kerkhof E., Nijman R.G., Vergouwe Y. et al. Impact of a clinical decision model for febrile children at risk for serious bacterial infections at the emergency department: a randomized controlled trial. PLoS ONE, 2015, vol. 10 (5), pp. e0127620.
    13. Bright T.J., Wong A., Dhurjati R. et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med, 2012, vol. 157 (1), pp. 29–43.
    14. Fillmore C.L., Bray B.E., Kawamoto K. Systematic review of clinical decision support interventions with potential for inpatient cost reduction. BMC Medical Informatics and Decision Making, 2013, vol. 13, p. 135.
    15. Sim I., Gorman P., Greenes R.A. et al. Clinical decision support systems for the practice of evidence-based medicine. Journal of the American Medical Informatics Association, 2001, vol. 8 (6), pp. 527–534.
    16. Peiris D.P., Joshi R., Webster R.J. et al. An electronic clinical decision support tool to assist primary care providers in cardiovascular disease risk management: development and mixed methods evaluation. J Med Internet Res, 2009, v. 11, vol. 4, p. e51.
    17. Kotel’nikov G.P., Kolsanov A.V. nnovation activities of Samara State Medical University: infrastructure, training, formation of breakthrough projects, transfer of technology to practice, participation in the Russian and regional innovation ecosystem. Nauka i innovatsii v meditsine, 2016, no. 1, pp. 6–11 (in Russ.).
    18. VOZ. Normy dlya otsenki rosta detey [WHO. Norms for assessing the growth of children], available at: http://www.who.int/childgrowth/standards/ru/
    19. Mazurin A.N., Vorontsov I. M. Propedevtika detskikh bolezney: uchebnik. 3-e izd., dop. i pererab. [Propaedeutics of childhood diseases: a textbook. 3rd ed., Supplemented and revised]. Saint Petersburg: Foliant, 2009.

    Метки: 2019, Children, decision-making support systems, E.A. BALASHOVA, L.I. MAZUR, outpatient setting, Practical medicine part 17 №5. 2019

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