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Objective:To improve the evaluation method of hospital beds efficiency based on diagnosis-related groups (DRG), and to provide a basis for hospitals to allocate beds reasonably and improve bed efficiency.Methods:Taking a tertiary hospital in Beijing as the research object, the types of beds were evaluated by the beds utilization matrix with the time consumption index as the X-axis and the bed utilization rate as the Y-axis. The types of beds in the department were divided into efficiency type, pressure type, turnover type, and idle type. The efficiency of medical services and the level of diagnosis and treatment were evaluated by the weight of DRG per bed. The calculation method of theoretical number of beds was improved by incorporating hospital case mix index as a risk adjustment factor into the formula to evaluate the status of beds allocation. Combining the bed type, DRG weight per bed, and bed allocation status, the improvement emphasis and management strategy of bed utilization could be comprehensively analyzed.Results:Among the 24 departments in the hospital, there were 5, 9, 1 and 9 departments being efficiency type, pressure type, turnover type and idle type, respectively. The weight per bed of 11 departments was higher than the average level of the hospital. There were 16, 5, and 3 departments with appropriate, fewer, and excessive beds, respectively.Conclusions:The comprehensive analysis of beds utilization type, allocation status and weight of each bed based on DRG is an effective method to evaluate the efficiency of hospital beds, and can provide decision-making basis for hospital bed resource allocation, hospital operation focus adjustment, and subject development planning.
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In order to curb the excessive growth of medical expenses, the United States has initiated payment reform of diagnosis-related groups (DRG) since 1983, and developed a series of complementary measures to address issues such as overcoding and declining healthcare service quality which were exposed during the reform. The authors discussed the implementation of DRG payment reform in the United States, namely the case-mix specialization of medical institutions and the reduction of costs, as well as the relationship between the two. On this basis, the authors suggested that when implementing reforms to the medical insurance payment system in China, it is imperative to avoid such loopholes as overcoding by medical institutions and excessive pursuit of efficiency at the expense of quality control, as well as the decline of comprehensive rescue capability and quality of care incurred by the exacerbated specialization.
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Objective:Case mix index indicates the capacity of disease diagnosis and treatment, as well as the quality of health cares in related disciplines. Science and technology evaluation metrics represent the level of innovation and sustainable development of science and technology. Quality of health care and sustainable development are considered as two key evaluation indicators in the performance evaluation of national tertiary public hospitals. This study aimed to explore the effect of case mix index on the science and technology evaluation metrics.Methods:According to a cross-sectional design, the relationship between case mix index and science and technology evaluation metrics was analyzed in a tertiary public general hospital between 2017 and 2019.Results:In three years′ period time, the departments in top 100 disciplines of science and technology evaluation metrics had the case mix index 17% which was higher than other departments in non-top 100 disciplines ( P<0.05). In the multivariate analysis, higher case mix index increased a 2.29-fold higher probability to be in top 100 disciplines. They are under the receiver operative character curve between case mix index and top 100 disciplines in evaluation of departments was 0.716 ( P=0.001). Conclusions:Case mix index indicated the level of science and technology evaluation metrics and the clinical departments should improve the case mix index, service quality of health care and the motivation of sustainable development.
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Objective@#To explore characteristics of general inter-departmental consultations in a hospital and put forward management strategy suggestions.@*Methods@#A large tertiary general hospital in Beijing was cited as the research object. Data were extracted from the EMR of the in-hospital inter-departmental consultations from July 1, 2017 to June 30, 2018, including information such as applying departments, submission time, invited departments, consultation completion time among others. Also collected were data such as discharges, case combination index(CMI), and preoperative average hospitalization days of clinical departments. Pearson and Spearman methods were used to perform correlation analysis, and independent sample Wilcoxon rank sum test was performed for the mean comparison.@*Results@#The ratio of consultations to discharged patients was 0.44, while consultation workload of cardiovascular medicine, ophthalmology and neurology was higher, and consultation applications issued by neurology, rheumatology and endocrinology departments were higher.For surgical departments, the correlation between demand of consultations and CMI was strong, r=0.63(P<0.05). The completion rate of consultation within 24 hours was 90.08%, and 64.79% of overtime consultations were caused by 35.63% of the consultation physicians.@*Conclusions@#It is imperative to enhance infrastructure support and information system construction to meet huge demands of inter-departmental consultations and to ensure patient safety; To further examinations of consultation purposes and improve doctors′ integrative abilities of diagnosis and treatment by introducing HIM mode to the training system, for the purpose of reducing unnecessary consultations; Optimize the process, shorten preoperative average length of stay by bringing forward inpatient-consultations to outpatient department; Inspire consultation enthusiasm and ensure consultation quality through performance appraisal mechanism.
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Objective To explore the feasibility to apply case mix index ( CMI) in risk assessment of clinical nursing units. Methods Questionnaire was designed and used to evaluate risk ratings for 43 nursing units with wards, with the survey results subject to expert scoring. The units consisted of 16 in surgical system, 15 in internal medicine, and 7 in traditional Chinese medicine system. Statistical method was used to analyze the correlation of the expert scoring and CMI. Results The CMI of nursing units and expert scoring results had strong correlation (r=0. 69, P<0. 05). Two groups of data in surgical system and internal medicine system were highly correlated (r= 0. 716, P<0. 05; r= 0. 643, P<0. 05 respectively), while the two groups of data in traditional Chinese medicine system had no correlation (r=0. 572, P>0. 05). Conclusions CMI can be used as a reference for dynamic risk assessment of nursing units.
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Objective To regulate standardized ICD-10 case classification name and coding,and common clinical diagnosis name or expression of mapping rules,to systematically improve the quality of DRGs key data,and to assess the impact of medical diagnostic data quality on DRGs and the indicators based on the DRGs.Methods Extension of the glossaries of clinical diagnosis synonyms or near-synonyms,and establishment of a standardized maintenance procedure of ICD-10 dictionary.Adjustment of the impact extent of DRGs disease makeup on case classification,comparison of the consistency of principal diagnosis classification,and the consistency of DRGs grouping,as well as changes of such indicators as DRGs grouping reduction in variance (RIV) and case mix index (CMI).Results Data of the obstetrics,gynecology and pediatrics disciplines of a maternity and children hospital from 2012 to 2013 (72 005 cases)and 2014 to 2015 (77 705 cases) were chosen for prior-after comparison.The encoding consistency rate was 59.60％ before the improvement,with the improved standardized consistency rate rising to 66.38％afterwards;beforehand the DRGs grouping consistency rate was 69.30％,with the improved standardized consistency rate rising to 88.00％ afterwards;beforehand the cost RIV was 0.515,with the cost RIV rising to 0.576 afterwards;the CMI variations of individual campuses of healthcare institutions appear more reasonable.Conclusions Diagnostic quality control and improvement project can improve the data accuracy of coding.This empowers the RIV and CMI indexes calculated on such basis to better describe the complexity of clinical settings,conducive to establishing a value-oriented prepayment system which is more transparent,fair and reasonable.
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Objective To explore the relationship between case mix index ( CMI ) and the bed allocation in clinical departments, and to evaluate the performance of bed scale of departments at tertiary hospitals based on CMI. Methods Based on the HIS system of a tertiary hospital, the authors collected the disease treatment information and bed allocation information of each clinical department in 2015. The CMI value was calculated by means of diagnosis-related group( DRG) , while the proportion of cases and average daily beds occupancy corresponding to the quartile of the CMI value of each department was also counted. Then the bed occupancy and distribution of various patients were analyzed. Results The hospital′s overall CMI value, DRG groups, DRG cases at the departments, days of stay, DRGs, CMI values and its quartiles were calculated. It was found that the medical and surgical CMIs had a linear relationship with the critical proportion (r=0. 998, 0. 996, P<0. 001). The main influencing factors of average daily bed occupancy were ranged from high to low as followed: the number of cases that were allocated in the group, employee numbers and CMI (F=87. 656, P<0. 001). Conclusions CMI is an ideal indicator for the difficulty of medical services at different departments and for evaluating the bed scale performance. Hence it can be used as an important reference for bed number adjustment in hospitals.
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As introduced in the paper, the average days of stay of clinical department were calculated as a management target, in view of the complexity of disease and case mix index. This method could avoid the deficiency of traditional methods and make the management of average length of stay of clinical department more conforming to the actual situation, and also more scientific and reasonable.
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Objective To explore the feasibility to apply case mix index ( CMI) in risk assessment of clinical nursing units. Methods Questionnaire was designed and used to evaluate risk ratings for 43 nursing units with wards, with the survey results subject to expert scoring. The units consisted of 16 in surgical system, 15 in internal medicine, and 7 in traditional Chinese medicine system. Statistical method was used to analyze the correlation of the expert scoring and CMI. Results The CMI of nursing units and expert scoring results had strong correlation (r=0. 69, P<0. 05). Two groups of data in surgical system and internal medicine system were highly correlated (r= 0. 716, P<0. 05; r= 0. 643, P<0. 05 respectively), while the two groups of data in traditional Chinese medicine system had no correlation (r=0. 572, P>0. 05). Conclusions CMI can be used as a reference for dynamic risk assessment of nursing units.
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O gerenciamento de uma organização hospitalar exige provisionar seus custos/gastos com ferramentas que a aproximam da realidade. A tarefa de aferição da produtividade pode ser complexa e duvidosa, diversos métodos são experimentados e a utilização do DRG tem se mostrado eficiente, sendo utilizado na avaliação da produtividade através de desfechos assistenciais. Estudo transversal, avaliou 145.710 internações, no período de 2012-2014, utilizando a metodologia do DRG para medição de sua produtividade a partir da mediana do tempo de internação. Ao agruparmos todas as internações em clínicos (37,6%) e cirúrgicos (62,4%), várias análises puderam ser feitas de acordo com esse critério.O DRG como ferramenta para predição de dias de internação é uma alternativa eficiente, colaborando assim para o controle da produtividade que influencia diretamente nos gastos e custos dos produtos hospitalares e qualidade dos serviços.
The management requires a hospital organization to provision their costs/expenses with tools that approximate reality. The task of measuring productivity can be complex and uncertain, several methods are tested and the use of the DRG has been efficient, being used to assess the productivity through clinical outcomes. Cross-sectional study evaluated 145.710 hospitalizations in the period 2012-2014, using the DRG methodology for measuring productivity from the median length of hospitalization. When we group all hospitalizations in clinical (37.6%) and surgical (62.4%), multiple analyzes could be made according to this criterion. The DRG as a tool for prediction of hospital days is an effective alternative, thereby contributing tothe control of productivity that directly influences the costs of hospital expenses and product and service quality.
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Humans , Male , Female , Adult , International Classification of Diseases , Diagnosis-Related Groups/economics , Efficiency, Organizational/economics , Efficiency , Hospitalization/economics , Retrospective Studies , Congresses as Topic , Health Services Research/methods , Hospital Planning/economicsABSTRACT
BACKGROUND: Rehabilitations in subacute phase are different from acute treatments regarding the characteristics and required resource consumption of the treatments. Lack of accuracy and validity of the Korean Diagnosis Related Group and Korean Out-Patient Group for the acute patients as the case-mix and payment tool for rehabilitation inpatients have been problematic issues. The objective of the study was to develop the Korean Rehabilitation Patient Group (KRPG) reflecting the characteristics of rehabilitation inpatients. METHODS: As a retrospective medical record survey regarding rehabilitation inpatients, 4,207 episodes were collected through 42 hospitals. Considering the opinions of clinical experts and the decision-tree analysis, the variables for the KRPG system demonstrating the characteristics of rehabilitation inpatients were derived, and the splitting standards of the relevant variables were also set. Using the derived variables, we have drawn the rehabilitation inpatient classification model reflecting the clinical situation of Korea. The performance evaluation was conducted on the KRPG system. RESULTS: The KRPG was targeted at the inpatients with brain or spinal cord injury. The etiologic disease, functional status (cognitive function, activity of daily living, muscle strength, spasticity, level and grade of spinal cord injury), and the patient's age were the variables in the rehabilitation patients. The algorithm of KRPG system after applying the derived variables and total 204 rehabilitation patient groups were developed. The KRPG explained 11.8% of variance in charge for rehabilitation inpatients. It also explained 13.8% of variance in length of stay for them. CONCLUSION: The KRPG version 1.0 reflecting the clinical characteristics of rehabilitation inpatients was classified as 204 groups.
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Humans , Brain , Classification , Diagnosis , Inpatients , Korea , Length of Stay , Medical Records , Muscle Spasticity , Muscle Strength , Outpatients , Rehabilitation , Retrospective Studies , Spinal Cord , Spinal Cord InjuriesABSTRACT
BACKGROUND: Over the last few decades, because hospitals in South Korea also have undergone dramatic changes, Korean hospitals traditionally have provided specialized health care services in the health care market. Inner Herfindahl-Hirschman Index (IHI) measures hospital caseloads based on patient proportions, independent of patient volumes. However, IHI that rely solely on patient proportions might be problematic for larger hospitals that provide a high number of diagnosis categories, as the patient proportions in each category are naturally relatively smaller in such hospitals. Therefore, recently developed novel measure, category medical specialization (CMS) is based on patient volumes as well as patient proportions. METHODS: we examine the distribution of hospital specialization score by hospital size and investigate association between each hospital specialization and length of stay per case and hospital cost per case using Korean National Health Insurance Service-cohort sample data from 2002 to 2013. RESULTS: Our results show that IHI show a decreasing trend according to the number of beds and hospital type but CMS show an increasing trend according to the number of beds and hospital type. Further, inpatients admitted at hospitals with higher IHI and CMS had a shorter length of stay per case (IHI: B=-0.104, p<0.0001; CMS: B=-0.044, p=0.001) and inpatients admitted at hospitals with higher IHI and CMS had a shorter hospital cost per case (IHI: B=-0.110, p=0.002; CMS: B=-0.118, p=<0.0001). CONCLUSION: this study may help hospital policymakers and hospital administrators to understand the effects of hospital specialization strategy on hospital performance under recent changes in the Korean health care environment.
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Humans , Delivery of Health Care , Diagnosis , Health Care Sector , Health Facility Size , Hospital Administrators , Hospital Charges , Hospital Costs , Inpatients , Korea , Length of Stay , National Health ProgramsABSTRACT
The performance evaluation is an effective method to guide the public hospitals behavior and pro-mote their sustainable development.The introduction of disease severity could make the performance evaluation sys-tem more scientific and reasonable, and encourage the hospitals to improve their technical skills and services ability. Based on the Shanghai diagnosis related groups system, a case-mix index ( CMI) was introduced and a severity score of disease was developed after the relative weight ( RW) adjustment to evaluate different types of disease severity in hospitals.The results have shown that CMI effectively reflects the patients'disease severity and the intensity of treat-ment in those hospitals taken into consideration.Therefore, the scientific indicators should be selected and the evalu-ation system should be improved thereby establishing an effective monitoring and dynamic adjustment mechanism and further developing the diagnosis related group application.
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Objective To set the cost standards for hospitalization based on the eases of the clinical pathway in order to help set a reasonable ceiling for the expenses of various diseases.Methods The multiple linear regression analysis was applied to find out influencing factors of hospitalization costs of the hysteromyoma.Diagnosis Related Groups(DRGs)ease mix was used to group 1777 hysteromyoma cases.Results The main factors for the expenses,as listed by their influence,were surgical operation or not,disease(s)of concomitance and the amount,adjusted R2 =0.6545.Hysteromyoma patients were divided into four diagnosis related groups; the all coefficient of variation(CV)is as small as 0.068,0.104,0.102,and 0.116 respectively.The hospitalization costs of the hysteromyoma of standard reference value were then calculated.Conclusion The standards interval for hospitalization costs set with DRGs case mix is reasonable and efficient,significantly useful for regulating medical practice and harnessing excessive costs of hospitalization.
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PURPOSE: The purpose of this study was to measure home health resource utilization using a Case-Mix Adjustor Model developed in the U.S. METHOD: The subjects of this study were 484 patients who had received home health care more than 4 visits during a 60-day episode at 31 home health care institutions. Data on the 484 patients had to be merged onto a 60-day payment segment. Based on the results, the researcher classified home health resource groups (HHRG). RESULT: The subjects were classified into 34 HHRGs in Korea. Home health resource utilization according to clinical severity was in order of Minimum (C0) < 'Low (C1) < 'Moderate (C2) < 'High (C3), according to dependency in daily activities was in order of Minimum (F0) < 'High (F3) < 'Medium (F2) < 'Low (F1) < 'Maximum (F4). Resource utilization by HHRGs was the highest 564,735 won in group C0F0S2 (clinical severity minimum, dependency in daily activity minimum, service utilization moderate), and the lowest 97,000 won in group C2F3S1, so the former was 5.82 times higher than the latter. CONCLUSION: Resource utilization in home health care has become an issue of concern due to rising costs for home health care. The results suggest the need for more analytical attention on the utilization and expenditures for home care using a Case-Mix Adjustor Model.
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Middle Aged , Male , Humans , Female , Aged, 80 and over , Aged , Adult , Risk Adjustment , Korea , Home Care Services/statistics & numerical data , Health Resources/statistics & numerical dataABSTRACT
PURPOSE: This study was to classify elderly in long-term care hospitals for using Resource Utilization Group(RUG-III) and to consider feasibility of payment method based on RUG-III classification system in Korea. METHOD: This study designed by measuring resident characteristics using the Resident Assessment Instrument-Minimum Data Set(RAI-MDS) and staff time. The data were collected from 382 elderly over sixty-year old, inpatient in the five long-term care hospitals. Staff time was converted into standard time based on the average wage of nurse and aids. RESULT: The subjects were classified into 4 groups. The group of Clinically Complex was the largest(46.3%), Reduced Physical Function(27.2%), Behavior Problem(17.0%), and Impaired Cognition(9.4%). The average resource use for one resident in terms of care time(nurses, aids) was 183.7 minutes a day. Relative resource use was expressed as a case mix index(CMI) calculated as a proportion of mean resource use. The CMI of Clinically Complex group was the largest(1.10), and then Reduced Physical Function(0.93), Behavior Problem(0.93), and Impaired Cognition(0.83) followed. The difference of the resource use showed statistical significance between major groups(p<0.0001). CONCLUSION: The results of this study showed that the RUG-III classification system differentiates resources provided to elderly in long-term care hospitals in Korea.
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Objective: To investigate the case-mix method by clinical pathway. Methods: K-MEANS cluster analysis was applied to case-mix classification and artificial neural network was used for case-mix prediction. Results: Five hundred and twenty three inpatient records constructed a case-mix classification scheme of 4 groups.Statistical significant difference of costs existed in 4 groups.The training error of artificial neural network was low(0.0 029) and the predicting result was accurate(98.91%). Conclusion: Case-mix result was more reasonable using records under clinical pathway.The existing models of case-mix depend on dividing individual variables, but artificial neural network does not.
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Objective To formulate genuine case mix plans using medical record information available in China. Methods An account was given of the research background of case mix studies, the current status of the studies and applications at home and abroad, the case mix model for measuring medical "output", data sources and statistical methods of classification. Results Case mix plans for army inpatients, civilian inpatients and outpatients were respectively formulated, and software for calculating the case mix index of a hospital which can run on Windows 95/98 computer systems was developed. Conclusion The theoretical, methodological and data conditions necessary for the formulation of case mix plans based on the first pages of medical records in China are now ripe and the case mix plans formulated on the basis of data from large samples can now be used for the control of medical costs, the assessment of a hospital's medical "output" and the estimation of the financial compensations for hospitals.
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With expanded and extended coverage of the national medical insurance and fast growing health care expenditures, appropriateness of health service utilization and quality of care are concerns of both health care providers and insurers as well as patients. An accurate patient classification system is a basic tool for effective health care policies and efficient health services management. A classification system applicable to Korean medical information-Korean Diagnosis Related Groups (K-DRGs)-was developed based on the U. S. Refined DRGs, and the performance of the developed system was assessed in this study. In the process of the development, first the Korean coding systems for diagnoses and procedures were converted to the systems used in the definition of the U. S. Refined DRGs using the mapping tables formulated by physician panels. Then physician panels reviewed the group definition, and identified medical practice patterns different in two countries. The definition was modified for the difference in K-DRGs. The process resulted in 1,199 groups in the system. Several groups in Refined DRGs could not be differentiated in K-DRGs due to insufficient medical information, and several groups could not be defined due to procedures which were not practiced in Korea. However, the classification structure of Refined DRGs was retained in K-DRGs. The developed system was evaluated for its performance in explaining variations in resource use as measured by charges and length of stay(LOS), for both all and non-extreme discharges. The data base used in this evaluation included 373,322 discharges which was a random sample of discharges reviewed ad payed by the medical insurance during the five-month period from September 1990. The proportion of variance in resource use which was reduced by classifying patients into K-DRGs-r-square-was comparable to the performance of the U. S. Refined DRGs: .39 for charges and .25 for LOS for all discharges, and .53 for charges and .31 for LOS for non-extreme discharges. Another measure analyzed to assess the performance was the coefficient of variation of charges within individual K-DRGs. A total of 966 K-DRGs (87.7%) showed a coefficient below 100%, and the highest coefficient among K-DRGs with more than 30 discharges was 159%.
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Humans , Classification , Clinical Coding , Delivery of Health Care , Diagnosis , Diagnosis-Related Groups , Health Expenditures , Health Personnel , Health Services , Inpatients , Insurance , Insurance Carriers , KoreaABSTRACT
The objectives of the study were to provide the basic informations needed in the development of balanced medical services throughout the nation. As the national health care system was expanding rapidly along with the economic growth, quantitative re-evaluation of the system is of great need. For that reason, characteristics of the admitted patients were analyzed for the case-mix and patients' flow within and through regions. Materials were 421,530 cases of inpatients, who were reported through Medical Insurance Corporation(KMIC) for insurance claim, during the period of March 1, 1985 through February 28, 1987. Korean Diagnosis Related Groups(K-DRGs) classification system was adopted for the study of case-mix and 189 cities and countries were classified into 5 district groups by factor analysis results of K-DRGs. The major findings of this study were as follows ; 1) Factor analysis of case-mix, employing K-DRG system, revealed 5 distinct functional district groups. Group A(18 district) was prominent for tertiary medical care. In group B(36 districts), rather simple procedures were prevalent. Group C(26 districts) was distinctive for the medical care of well organized internal medicine practices with qualified clinical laboratories. Group D(17 districts) was characterized by relatively high balanced medical care. Group E (92 districts) was with very low level of medical care. 2) Analysis of the case-flow through the districts showed 3 types of flow patterns ; inflow, outflow, and balanced types. Inflow type of case-flow was found in Group A, C and D while Group B and E showed outflow type. Inflow was most prominent in Group A and Group E was of typical outflow type. Group B was consistently the outflow type except for Major Diagnostic Category XX regardless of the disease treaders, but Group C and D were inflow or outflow types according to the disease tracers.