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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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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 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 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 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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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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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.