Morbidity Pattern and Medical Care Utilization Behavior of Residents in Urban Poor Area (도시 영세지역 주민의 상병양상과 의료이용행태)
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- Journal of Yeungnam Medical Science
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- v.8 no.1
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- pp.107-126
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- 1991
The purpose of the study was to assess the morbidity pattern and the medical care utilization behavior of the urban residents in the poor area. The study population included 2,591 family members of 677 households in the poor area of Daemyong 8 Dong, Nam-Gu, Taegu and 2,686 family members of 688 households, near the poor area in the same Dong, were interviewed as a control group. On this study the household interview method was applied. Well-trained interviewers visited every household in the designated area and individually interviewed heads of households or housewives for general information, morbidity condition, and medical care utilization with a structured questionnaire. Individuals were interviewed from 1 to 30 December 1988. The major results were summarized as follows : The proportion of the people below 5 years of age was 4.2% of the total study population and 5.5% were above 65 years of age in the poor area. This was slightly higher than in the control area. The average monthly income of a household in the poor area was 403,000 won versus 529,000 won in the control area. Fifty-eight percent of the residents in the poor area and sixty-one percent in the control area were medical security beneficiaries, but the proportion of medical aid beneficiaries was 7.8% in the poor area and 4.6% in the control area. The 15-day period morbidity rate of acute illnesses was 57.1 per 1,000 in the poor area and 24.2 per 1,000 in the control area. Respiratory disease is the most common acute illness in both areas. The most frequently utilized medical facility was the pharmacy among the patients with acute illnesses in the poor area. Among them 58.1% visited pharmacy initially while 38.4% of the patients in the control area visited a clinic. Among persons with illnesses during the 15 days 8.8% in the poor area and 4.6% in the control area did not seek any medical facility. Mean duration of utilization of medical facilities was 3.5 days in the poor area and 3.3 days in the control area. Initially of the medical facilities in Daemyong 8 Dong, The pharmacy in the poor area and the clinic in the control area were most commonly utilized. The most common reason for visiting the hospital was 'regular customers' in the poor area and 'geographical accessibility' in the control area. The one year period morbidity rate of chronic illness in the poor area was 83.0 per 1,000 population and 28.0 per 1,000 in the control area. Disease of nervous system was the most common chronic illness in the poor area while cardiovascular disease in male and gastrointestinal disease in female were most prevalent in the control area. The most frequently utilized medical facility was the pharmacy among the patients with chronic illnesses in the poor area. Among them 24.2% visited the pharmacy initially while 34.7% of the patients in the control area visited the out-patient department of the hospital within a 15-day period. Among the patients with chronic illnesses 34.9% in the poor area and 16.0% in the control area did not seek any medical facility. Mean duration of utilization of medical facilities was 9.2 days in the poor area and 9.9 days in the control area within a 15-day period. Initially of the medical facilities in Daemyong 8 Dong, the pharmacy in the poor area and the hospital in the control area were most commonly utilized. The most common reason for visiting the hospital, clinic, health center or pharmacy in the poor area was 'geographical accessibility' while the reason for visiting herb clinic was 'good result' and 'reputation' in both areas.
To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.