In this study, population census(2005 & 2008) from Statistics Korea and the statistical data of the number of hospital beds by healthcare facilities classification from Ministry of Health and Welfare were used. For analyzing distribution of hospital beds, hospital beds were classified as acute care beds, long-term care beds and all hospital beds, which is including acute and long-term care beds. Regional areas, which are city(si), county(goon) for the study and district(gu) were reclassified as metropolitan city, city(si) and county(goon). Because there were 165 regional areas in 2005 and 2008, 84 and 81 areas were classified as metropolitan city and/or city and county, respectively. Gini index were calculated for hospital beds from each year, and Lorenz curves were drawn. The following summary presents the findings of this study. Compared to the year 2005 and 2008, the Gini index was 0.24472, and hospital bed numbers increased slightly by 0.80% than in 2005. In case of acute care beds, the Gini index was 0.23797(0.13%), and there was no big difference; however, the Gini index for long-term care beds was 0.41091, and there was a 30.25% decrease, which shows improvement to reduce disparities. It might result from an increase in long-term care beds up to 476.2%. For geographical equality of hospital beds, the Gini index and Lorenz curve, which can be compared the degree of inequality in the distribution of hospital beds reasonably and possibly show statistical data, should be used. Through this study, the distribution policy of hospital beds should be established.
This study examines the statistical relationship between medical specialists and managerial performance, using regression analysis with the number of medical specialists per 100 beds as the independent variable and the managerial performance index as the dependent variable. Managerial performance index incorporated the number of out-patients per specialist, the number of in-patients per specialist, the volume of revenue per specialist, the number of beds per specialist, and the average length of stay. To compare different groups of hospitals, dummy variable was applied to five groups of hospitals according to size: 100-299 beds, 300-599 beds, 600-899 beds, 900-1199 beds, and more than 1200 beds. The data consisted of 181 general hospitals with more than 100 beds, which included 28 public hospitals, 73 corporate hospitals, 64 university hospitals and 16 private hospitals. Of those, 87 hospitals were located in big cities and 94 hospitals in medium to small cities. This study used hospitals from the Korean Hospital Association, and data published in 2004. The collected data sample was analyzed using the SPSSWIN 12.0 version, and the study hypothesis was tested using regression analysis. The findings of this study are summarized as follows: Hypothesis 1 predicting a negative effect of the number of medical specialists on the number of out-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in all the hospital groups larger than the group of 100-299 beds. Hypothesis 2 predicting a negative effect of the number of medical specialists on the number of in-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds when compared to the group of 100-299 beds. Hypothesis 3 predicting a negative effect of the number of medical specialists on the volume of revenue per specialist was not supported. However, the analysis of dummy variable showed that the volume of revenue per specialist increased in the hospital groups of 600-899 beds, 900-1199 beds, and over 1200 beds, when compared to the group of 100-299 beds. Hypothesis 4 predicting a negative effect of the number of medical specialists on the average length of stay was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds, when compared to the group of 100-299 beds. Results of this study show that the number of the medical specialists per 100 beds is an important factor in hospital managerial performance. Most hospitals have tried to retain as many medical specialists as possible to keep the number of patients stable, to ensure adequate revenue, and to maintain efficient managerial performance. Especially, the big hospitals with greater number of beds and medical specialists have shown greater revenue per medical specialist despite the smaller number of patients per medical specialist. Findings of this study explains why hospitals in Korea are getting bigger.
Information on productivity of hospital personnel is required for optimum staffing and hospital management. This study deals with the quantitative aspects of workload of medical personnel in training hospitals by their specific characteristics. Specifically this study attempted to find relevant determinants of the productivity of medical personnel using multiple stepwise regression analysis based on data obtained from 135 training hospitals. The findings of this study were as follows: 1) Daily average number of outpatients and inpatients treated by a physician were 20.4 and 10.2, respectively. 2) Daily average number of patients cared by a nurse was 8.2. Daily average number of tests performed by pathologic technician and radiologic technician were 83.2 and 21.5, respectively. 3) Productivity of medical personnel were significantly different for the three groups of factors: hospital sire (number of beds, number of medical personnel per 100 beds): institutional characteristics (medical school affiliation, training type, profit status); and environmental factors (location, number of physician and beds per 1,000 population in the region). 4) The factors a(footing the productivity varied according to the types of medical profession: the number if beds, the number of physicians per 100 beds, training type, and profit status for physicians; the number of nurses per 100 beds, the number of beds, medical school affiliation for nurses; the number of physicians per 100 beds, the number of technicians per 100 beds, and ownership for pathologic technicians; the number o( technicians, training type, and the number of physicians per 100 beds for radiologic technician.
Motivated by reducing the uncertainties in quantification of debris bed coolability, this paper reports an experimental study on two-phase flow resistances and interfacial drag in packed porous beds. The experiments are performed on the DEBECO-LT (DEbris BEd COolability-Low Temperature) test facility which is constructed to investigate the adiabatic single and two phase flow in porous beds. The pressure drops are measured when air-water two phase flow passes through the porous beds packed with different size particles, and the effects of interfacial drag are studied especially. The results show that, for two phase flow through the beds packed with small size particles such as 1.5 mm and 2 mm spheres, the contribution of interfacial drag to the pressure drops is weak and ignorable, while the significant effects are conducted on the pressure drops of the beds with bigger size particles like 3 mm and 6 mm spheres, where the interfacial drag in beds with larger particles will result in a descent-ascent tendency in the pressure drop curves along with the fluid velocity, and the effect of interfacial drag should be considered in the debris coolability analysis models for beds with bigger size particles.
The purpose of this study is to explore the ecosystem service and benefit indicators of natural seaweed beds. Ecosystems of natural seaweed beds provide a wide range of services and benefits to human society including provisioning services, regulating services, supporting services, and cultural services. Indicators for each of the ecosystem services are chosen by marine plants ecologists and as follows. Ecosystem indicators of natural seaweed beds for provisioning services are well-being food(amount of seaweed harvested/amount of fish landed, fish biomass, area of natural seaweed beds, the number of species, contribution to the second production), raw materials(amount of biomass by breed, amount of aquaculture feed), genetic resources(amount of genetic material extracted, amount of genetic material contained by age and habitat), and medicinal resources(amount of medicinal material extracted). Ecosystem indicators of natural seaweed beds for regulating services are air purification(amount of fine dust/NOx or $SO_2$ captured), climate regulation(amount of $CO_2$ sequestered), waste treatment(amount of N, P stored, biochemical degradation capacity COD), and costal erosion prevention(length and change of natural coast line, amount of sediment prevented). Ecosystem indicators of natural seaweed beds for supporting services are lifecycle and maintenance(primary production, contribution to the second production) and gene pool protection(amount of compositional factors in ecosystem, introduced species). Ecosystem indicators of natural seaweed beds for cultural services are recreation and tourism(the number of visits of an area) and information for cognitive development(amount of time spent in education, research and individual learning about ecosystem of natural seaweed beds).
This study was attempted to identify the factors affecting profitability of general hospital in Kyung-In Region. Operating profit to gross revenues and net profit to gross revenues were used as a proxy indicator for profitability of hospitals. The unit of analysis was hospital, and the data were collected 5 years data from 20 hospitals. The major findings are as follows; (1) The average operating profit rate was 1.03% and the net profit rate was -5.00% in twenty hospitals in the Kyung-In Region for the last five years. In terms of maximum surplus, the operating profit rate was 14% and net profit rate was 3.40%. In terms of maximum loss revenue, the operating profit rate was -16.56% and the net profit rate was -22.83%. (2) Since the year 1993, which was the starting year of this study, the operating profits and the net profits consistently decreased. (3) Analyzing the difference in profits among various hospital groups, the tertiary hospital group and the 501-1000 beds group exhibited the highest in operating profit rate. Also, among the higher grade number of beds in hospital group, per 100 beds group, the 41-50 beds group exhibited the highest in operating profit rate. There is a statistically significant difference in those groups(p<0.05, p<0.01). (4) In the health care delivery system, the profit gain in the secondary hospital was 51.5% and in the tertiary hospital was 72.4%. Based on the number of beds in each hospital group, the highest profit gain was 75.0% in the over 1001 beds group, and 71.4% in the 501-1000 beds group. Also, among the higher grade number of beds in hospital group, per 100 beds group, the 41-50 beds group exhibited 88.6% surplus. (5) According to the surplus difference based on the analysis of health care utilization, a group with over 31 patients in bed turnover rate, a group with over 96% in bed occupancy rate and group with over 9% in emergency cases to outpatient visits exhibited the highest profit gains. In addition, a group with over 301 patients in daily outpatient visits per 100 beds and group with 11-12 days average length of stay exhibited the highest profit gains. These results are statistically significant(p<0.05, p<0.01). (6) According to a stepwise regression analysis, the variables measuring the bed turnover rate, number of licensed beds, and number of outpatient visits per specialist explain 34.1% of the variation in operating profits. In terms of net profits, the new outpatient visits, the bed turnover rates and the number of general bed variables explain 30.6%. These results are statistically significant(p<0.01).
Purpose: This study analyzed the status of general hospitals as an expanded concept of medical resources including medical staff and equipment. The purpose of this study is to provide a basic for the feasibility study of the scale and establishment of facility guidelines at the planning stage of general hospitals. Methods: The subjects of this study were limited to general hospitals. The status of medical resources was based on the data of the Health Insurance Review and Assessment Service. The number of beds, doctors, nursing grades and major medical equipment were surveyed in 335 general hospitals. Results: 1) The characteristic of general hospitals varies depending on the number of inpatient beds. To be concrete, there were differences in the number of medical staffs and equipments in general hospitals based on 300 500 800 1,000 beds. 2) As the number of hospital beds increases, the number of medical staff increases more than medical equipment and facilities. Medical equipment and facilities remain constant, even when the number of beds increases. On the other hand, the number of medical staff increased about 1.5 times in each level. Implications: Architectural plans for medical staff should be considered differently depending on the number of beds. In particular, architectural planning and facility guidelines should be applied differently based on 300 and 500 beds.
Many alternatives have been discussed to reduce the medical expenditure and to use the medical resources effectively. Many studies about the economies of scale have been done for the last several decades. This study has analyzed the relationship between the number of beds and the mean expense per hospitalization day in Korea. A Cost Function Model was identified and we wanted to see the minimum optimal size with the cheapest mean expense per hospitalization day. The result is as follows; 1. In the Cost Function Mode, (the number of beds)$^{2}$, the number of personnel, productivity and training institutions are the factors that statisticaly influence the mean expenses. 2. By the univariate analysis the mean expense proved to be the smallest as the level of 150-200bed, The breaked down of the components of expenses shows that the mean labor cost is much different from the mean value of material and administration costs, and that hospital with 150-200 beds also have the minimal expense. The mean expense goes up dramatically in hospitals of 450 beds or more. 3. When the other conditions are constant, according to the multiple regression analysis of the mean expense per adjusted hospitalization day the minimum optimal size with the cheapest expense is a hospital with 191 beds and the hospital with 230 beds takes the lowest mean labor cost. The material or administration costs are not influenced by hospital size. This research has limitation in measuring the variables that influence hospital xpenses, in estimating hospital output by the number of beds in considering outpatient cost and in securing representativeness of hospitals because many hospitals made no responses to the research questionnare. But it is valuable and helpful for development of health policy to figure out the number of beds with the cheapest expense per hospitalization day.
Background : There were so many patients who are waiting for admission in Emergency room in spite of more than one hundred empty beds everyday. This study was conducted to evaluate admission-discharge module system by OCS which reduce empty beds. Methods : The data of bed utilization in general beds from 2004 were reviewed. For evaluation of performance at admission-discharge module system by OCS, the change of Occupancy of bed were calculated. Results : The percentage of Average Bed Emptiness was changed from 13.8% to 9.2%. The residents in surgery(100%) and in internal medicine(75.5%) approved this system. Conclusion : The personnel in hospital recognized that it was very important to manage bed. The management of beds by OCS was helpful to reduce empty beds and was important.
The change of consumers' lifestyles causes frequent study on beds along with growth of economy, improvement of education and increase of dwelling in new towns and nuclear family. Beds are frequently developed in recent years since consumers' lifestyles increasingly change caused by transformation of types of dwelling, influence of western lifestyle, and increase uses of a bed. Also, this transformation causes needs for research on bed designs. A Bed is an essential item in a life since people spend one third of a day in Also, in contemporary, the ages of consumers are varied from infants to seniors. The study examines the importance of beds which playa major role in households. Moreover, the purpose of this study of beds focused on surface materials, colors, and designs is suggesting bases for future developments.
본 웹사이트에 게시된 이메일 주소가 전자우편 수집 프로그램이나
그 밖의 기술적 장치를 이용하여 무단으로 수집되는 것을 거부하며,
이를 위반시 정보통신망법에 의해 형사 처벌됨을 유념하시기 바랍니다.
[게시일 2004년 10월 1일]
이용약관
제 1 장 총칙
제 1 조 (목적)
이 이용약관은 KoreaScience 홈페이지(이하 “당 사이트”)에서 제공하는 인터넷 서비스(이하 '서비스')의 가입조건 및 이용에 관한 제반 사항과 기타 필요한 사항을 구체적으로 규정함을 목적으로 합니다.
제 2 조 (용어의 정의)
① "이용자"라 함은 당 사이트에 접속하여 이 약관에 따라 당 사이트가 제공하는 서비스를 받는 회원 및 비회원을
말합니다.
② "회원"이라 함은 서비스를 이용하기 위하여 당 사이트에 개인정보를 제공하여 아이디(ID)와 비밀번호를 부여
받은 자를 말합니다.
③ "회원 아이디(ID)"라 함은 회원의 식별 및 서비스 이용을 위하여 자신이 선정한 문자 및 숫자의 조합을
말합니다.
④ "비밀번호(패스워드)"라 함은 회원이 자신의 비밀보호를 위하여 선정한 문자 및 숫자의 조합을 말합니다.
제 3 조 (이용약관의 효력 및 변경)
① 이 약관은 당 사이트에 게시하거나 기타의 방법으로 회원에게 공지함으로써 효력이 발생합니다.
② 당 사이트는 이 약관을 개정할 경우에 적용일자 및 개정사유를 명시하여 현행 약관과 함께 당 사이트의
초기화면에 그 적용일자 7일 이전부터 적용일자 전일까지 공지합니다. 다만, 회원에게 불리하게 약관내용을
변경하는 경우에는 최소한 30일 이상의 사전 유예기간을 두고 공지합니다. 이 경우 당 사이트는 개정 전
내용과 개정 후 내용을 명확하게 비교하여 이용자가 알기 쉽도록 표시합니다.
제 4 조(약관 외 준칙)
① 이 약관은 당 사이트가 제공하는 서비스에 관한 이용안내와 함께 적용됩니다.
② 이 약관에 명시되지 아니한 사항은 관계법령의 규정이 적용됩니다.
제 2 장 이용계약의 체결
제 5 조 (이용계약의 성립 등)
① 이용계약은 이용고객이 당 사이트가 정한 약관에 「동의합니다」를 선택하고, 당 사이트가 정한
온라인신청양식을 작성하여 서비스 이용을 신청한 후, 당 사이트가 이를 승낙함으로써 성립합니다.
② 제1항의 승낙은 당 사이트가 제공하는 과학기술정보검색, 맞춤정보, 서지정보 등 다른 서비스의 이용승낙을
포함합니다.
제 6 조 (회원가입)
서비스를 이용하고자 하는 고객은 당 사이트에서 정한 회원가입양식에 개인정보를 기재하여 가입을 하여야 합니다.
제 7 조 (개인정보의 보호 및 사용)
당 사이트는 관계법령이 정하는 바에 따라 회원 등록정보를 포함한 회원의 개인정보를 보호하기 위해 노력합니다. 회원 개인정보의 보호 및 사용에 대해서는 관련법령 및 당 사이트의 개인정보 보호정책이 적용됩니다.
제 8 조 (이용 신청의 승낙과 제한)
① 당 사이트는 제6조의 규정에 의한 이용신청고객에 대하여 서비스 이용을 승낙합니다.
② 당 사이트는 아래사항에 해당하는 경우에 대해서 승낙하지 아니 합니다.
- 이용계약 신청서의 내용을 허위로 기재한 경우
- 기타 규정한 제반사항을 위반하며 신청하는 경우
제 9 조 (회원 ID 부여 및 변경 등)
① 당 사이트는 이용고객에 대하여 약관에 정하는 바에 따라 자신이 선정한 회원 ID를 부여합니다.
② 회원 ID는 원칙적으로 변경이 불가하며 부득이한 사유로 인하여 변경 하고자 하는 경우에는 해당 ID를
해지하고 재가입해야 합니다.
③ 기타 회원 개인정보 관리 및 변경 등에 관한 사항은 서비스별 안내에 정하는 바에 의합니다.
제 3 장 계약 당사자의 의무
제 10 조 (KISTI의 의무)
① 당 사이트는 이용고객이 희망한 서비스 제공 개시일에 특별한 사정이 없는 한 서비스를 이용할 수 있도록
하여야 합니다.
② 당 사이트는 개인정보 보호를 위해 보안시스템을 구축하며 개인정보 보호정책을 공시하고 준수합니다.
③ 당 사이트는 회원으로부터 제기되는 의견이나 불만이 정당하다고 객관적으로 인정될 경우에는 적절한 절차를
거쳐 즉시 처리하여야 합니다. 다만, 즉시 처리가 곤란한 경우는 회원에게 그 사유와 처리일정을 통보하여야
합니다.
제 11 조 (회원의 의무)
① 이용자는 회원가입 신청 또는 회원정보 변경 시 실명으로 모든 사항을 사실에 근거하여 작성하여야 하며,
허위 또는 타인의 정보를 등록할 경우 일체의 권리를 주장할 수 없습니다.
② 당 사이트가 관계법령 및 개인정보 보호정책에 의거하여 그 책임을 지는 경우를 제외하고 회원에게 부여된
ID의 비밀번호 관리소홀, 부정사용에 의하여 발생하는 모든 결과에 대한 책임은 회원에게 있습니다.
③ 회원은 당 사이트 및 제 3자의 지적 재산권을 침해해서는 안 됩니다.
제 4 장 서비스의 이용
제 12 조 (서비스 이용 시간)
① 서비스 이용은 당 사이트의 업무상 또는 기술상 특별한 지장이 없는 한 연중무휴, 1일 24시간 운영을
원칙으로 합니다. 단, 당 사이트는 시스템 정기점검, 증설 및 교체를 위해 당 사이트가 정한 날이나 시간에
서비스를 일시 중단할 수 있으며, 예정되어 있는 작업으로 인한 서비스 일시중단은 당 사이트 홈페이지를
통해 사전에 공지합니다.
② 당 사이트는 서비스를 특정범위로 분할하여 각 범위별로 이용가능시간을 별도로 지정할 수 있습니다. 다만
이 경우 그 내용을 공지합니다.
제 13 조 (홈페이지 저작권)
① NDSL에서 제공하는 모든 저작물의 저작권은 원저작자에게 있으며, KISTI는 복제/배포/전송권을 확보하고
있습니다.
② NDSL에서 제공하는 콘텐츠를 상업적 및 기타 영리목적으로 복제/배포/전송할 경우 사전에 KISTI의 허락을
받아야 합니다.
③ NDSL에서 제공하는 콘텐츠를 보도, 비평, 교육, 연구 등을 위하여 정당한 범위 안에서 공정한 관행에
합치되게 인용할 수 있습니다.
④ NDSL에서 제공하는 콘텐츠를 무단 복제, 전송, 배포 기타 저작권법에 위반되는 방법으로 이용할 경우
저작권법 제136조에 따라 5년 이하의 징역 또는 5천만 원 이하의 벌금에 처해질 수 있습니다.
제 14 조 (유료서비스)
① 당 사이트 및 협력기관이 정한 유료서비스(원문복사 등)는 별도로 정해진 바에 따르며, 변경사항은 시행 전에
당 사이트 홈페이지를 통하여 회원에게 공지합니다.
② 유료서비스를 이용하려는 회원은 정해진 요금체계에 따라 요금을 납부해야 합니다.
제 5 장 계약 해지 및 이용 제한
제 15 조 (계약 해지)
회원이 이용계약을 해지하고자 하는 때에는 [가입해지] 메뉴를 이용해 직접 해지해야 합니다.
제 16 조 (서비스 이용제한)
① 당 사이트는 회원이 서비스 이용내용에 있어서 본 약관 제 11조 내용을 위반하거나, 다음 각 호에 해당하는
경우 서비스 이용을 제한할 수 있습니다.
- 2년 이상 서비스를 이용한 적이 없는 경우
- 기타 정상적인 서비스 운영에 방해가 될 경우
② 상기 이용제한 규정에 따라 서비스를 이용하는 회원에게 서비스 이용에 대하여 별도 공지 없이 서비스 이용의
일시정지, 이용계약 해지 할 수 있습니다.
제 17 조 (전자우편주소 수집 금지)
회원은 전자우편주소 추출기 등을 이용하여 전자우편주소를 수집 또는 제3자에게 제공할 수 없습니다.
제 6 장 손해배상 및 기타사항
제 18 조 (손해배상)
당 사이트는 무료로 제공되는 서비스와 관련하여 회원에게 어떠한 손해가 발생하더라도 당 사이트가 고의 또는 과실로 인한 손해발생을 제외하고는 이에 대하여 책임을 부담하지 아니합니다.
제 19 조 (관할 법원)
서비스 이용으로 발생한 분쟁에 대해 소송이 제기되는 경우 민사 소송법상의 관할 법원에 제기합니다.
[부 칙]
1. (시행일) 이 약관은 2016년 9월 5일부터 적용되며, 종전 약관은 본 약관으로 대체되며, 개정된 약관의 적용일 이전 가입자도 개정된 약관의 적용을 받습니다.