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Kazakova Olga Kazakova Olga

Faculty: Computer sciences and technologies
Department: Аutomated сontrol systems
Speciality: Information control system and tehnologies

Theme of master's work: Development of a computerized decision support subsystems for optimization of ambulance station
Scientific adviser: Martynenko Tatiana
Materials on the theme of master's work: About author | Abstract |

Abstract of the qualification master’s work

INTRODUCTION

    The major value among the problems of reforming the health sector has improvement ambulance service, which provides around the clock emergency help to the adult and children's population at a pre-hospital stage, and transportation of patients in medical institutions.
    Ambulance station operates in clock duty and ready to provide emergency medical care. For support target time of arrival ambulance’s brigades (15 minutes) to a call place were create the network, which consist of 10 substations, which are located on zonal basis in each district of the city.
    There are ambulance’s brigades on each substation. Ambulance’s brigades can be grouped into the following types:
  • medical,
  • medical assistant's,
  • specialized (craniological, neurological, psychiatric, brigades of intensive therapy and others).
    The process of ambulance station management is a generation administrative solutions in following directions of the ambulance work:
  • establishment of an optimal schedule for ambulance’s brigades and operational personnel;
  • management of logistical supplies to maintenance the ambulance;
  • development of measures for joint action ambulance with other dispatching services, and medical institutions;
  • solving problems that are associated with the operational service calls by ambulance’s brigades and operational staff.

URGENCY

    Improving emergency medical services is one of the most important tasks of the health system organization. Rise of overall performance ambulance should provide equal availability and efficiency in reception of ambulance services for each person. First of all, Optimization of the ambulance station, demands informed planning of resources.

THE PURPOSES AND TASKS

    The purpose of the master’s work is increase efficiency of usage resources of ambulance station. Main tasks are:
    1. to perform the systems analysis of ambulance station work for definition the main parameters, that influence on the ambulance work;
    2. to analysis of calls for emergency medical care, to determine their dynamics and structure;
    3. to develop a model predicting the number of calls to ambulance and determine parameters of model;
    4. to implement a set of software tools for optimization ambulance stations works.

PLANNED SCIENTIFIC NOVELTY

    1. The model predicting the number of calls to ambulance services, which increases the efficiency of use of its resources, is developed.
     2. The decision support system, which allows carrying out scheduling of the ambulance services, is developed.

PLANNED PRACTICAL RESULTS

    The planned practical significance of master’s work consists of development software for optimization of ambulance stations works.
    The application of the decision support system will allow rational planning of ambulances resources.

REVIEW OF RESEARCHES ON THE TOPIC

    Moiseyev V., Butuzova A., Petrov E., Nikitin M. regarded the problem of efficient planning and organization of the ambulance in their works.
    In practice, to automate collection and processing information about the ambulance stations works, use the following automated systems: "Ambulance" ("Information systems"), the system "Ambulance" ("SITRONICS Information Technologies), "Service 03" ( "Svyazinformservis").
    Analysis of recent software systems in the subject area showed, that they are mainly focused on solving the problem of workflow. However, these systems do not provide the possibility of creation administrative solutions to optimize the ambulance.

SUMMARY OWN RESULTS

     It is necessary to predict quantity of expected ambulance calls for the various calendar periods for optimization of ambulance. Reliable forecasts of ambulance service demand are the major contribution for planning ambulance resources. Table 1 shows the options for use forecasts for different time periods

        Table 1 – Usage forecasts number of ambulance calls
The period of forecasting Usage of the received forecast
Annual forecast Definition of necessary number of purchasing medicines
Forecast for the month Substantiation of necessary quantity of beds for victims who are reserved in city hospitals.
The forecast for each substation for a month Storekeeping of medicines and a dressing on ambulance substations.
The forecast of calls of the certain profile for each month of year Is used at compilation of rational schedules of holidays of medical staff.
The forecast per day Substantiation solutions when it is necessary to involve additional resources.

    Forecasting process is the key moment at acceptance of administrative solutions. The forecast is a result of forecasting process, which is presented in verbal, mathematical, graphics or other opinion form about a possible object states in future period of time.
    There are following types of forecasts:
  • the operative;
  • the short-term;
  • intermediate term;
  • the long-term.
    The time gradation of forecasts is conditional in a certain measure and depends on character and the purpose of forecast. For our research the period of anticipation for short-term forecasting takes 1-2 weeks, for intermediate term – 1–3 months, and for long-term – 1–2 years.

CONCLUSIONS

     Ambulance is dispatching service. Normal functioning of a city is impossible without the ambulance work. It is necessary to predict ambulance service load during certain calendar periods for a substantiation of quantity ambulance brigades, and also operation personnel equipment, quantity of places for the victims, who are reserved in hospitals, material support etc.

Reference

  1. Антохонова И. В. Методы прогнозирования социально-экономических процессов: Учебное пособие. – Улан-Удэ: Изд-во ВСГТУ, 2004. – 212 с.
  2. Афанасьев В. Н., Юзбашев М.М. Анализ временных рядов и прогнозирование: Учебник. – М.: Финансы и статистика, 2001. – 228 с.
  3. Зимарин Г. И., Кравец О. Я. Анализ загрузки исполнительной подсистемы службы экстренной медицинской помощи, «Врач-аспирант», 2006, 2(11), 184–187
  4. Моисеев В. С., Бутузова А. В. Основные задачи разработки автоматизированной системы управления скорой медицинской помощью, «Исследования по информатике», 10, Отечество, Казань, 2006, 141–150
  5. Моисеев В. С., Сбоева А. В. Математическая модель прогнозирования численности населения, обслуживаемого оперативно-диспетчерскими службами, «Исследования по информатике», 8, Отечество, Казань, 2004, 63–74
  6. Автоматизированная информационно-диспетчерская система «Скорая медицинская помощь г. Киева». Сайт компании «СИТРОНИКС Информационные Технологии». [Электронный ресурс]. Режим доступа: URL:
    http://www.it.sitronics.com/about/projects/view.php?ID=571
  7. АСУ «Скорая помощь». Сайт компании «Информационные системы».[Электронный ресурс]. Режим доступа: URL:
    http://www.yarinsi.ru/products/detail.php?ID=1967&cat=opisanie
  8. Служба 03». Сайт компании «Связьинформсервис». [Электронный ресурс]. Режим доступа: URL:
    http://www.sis-group.com/products/officeatc/especial-service/03/
  9. Nabil Channouf, Pierre L’Ecuyer, Armann Ingolfsson, Athanassios N. Avramidis "The application of forecasting techniques to modeling emergency medical system calls in Calgary, Alberta". [Электронный ресурс]. Режим доступа: URL:
    http://www.iro.umontreal.ca/~lecuyer/myftp/papers/ambul.pdf
  10. Melania Calinescu "Forecasting and Capacity Planning for Ambulance Services". [Электронный ресурс]. Режим доступа: URL:
    http://www.few.vu.nl/en/Images/stageverslag-calinescu_tcm39-105827.pdf
  11. Ping-Sung Liao, Yung-Shu Tzeng, Tse-Sheng Chen. Ambulance Run Volume Prediction by Back-Propagation Neural Network[Электронный ресурс]. Режим доступа: URL: http://www.csu.edu.tw/csitshow/Hmanager/91data/427.doc
    Remark. While writing the given abstract the master's work has not been completed yet. The final date of the work completed is December, 2010. The text of master's work and materials on this topic can be received from the author or her research guide after the indicated date.
© DonNTU 2010, Kazakova Olga
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