| 1. BackgroundsThere are a large amount of chronic and geriatric patients in General Practice, who normally suffer from chronic diseases in their whole life. They tend to Health-Related Quality of Life (HRQoL) on the condition that their diseases can not be completely healed. Subjective HRQoL are worthy of special applicable to General Practice because General Practice focuses on whole individual and heterogeneous status, not the special problems of patients.HRQoL has become the most important measurement of Health Care and Clinic Practices. SF-36 developed by Ware et al. is the most popular measurement tool used in HRQoL, which is also translated and validated by over 40 countries. Meanwhile, the Norm of HRQoL has been established in 13 countries. The Institute of Social Medicine and Family Medicine in Zhejiang University developed the Chinese SF-36, which kept the meaning and structure of the origin and solved the distortion problem evoked by applying foreign SF-36 directly into China, as well as established the first Norm of SF-36 in Hangzhou city, P.R.C. Moreover, the applicable conditions and deployment possibilities are explored for the generality of Chinese SF-36.Traditional HRQoL wastes a wealth of resources (e.g. time, manpower) during data collection. Besides, the procedure of data input consumes a great deal of time so that the ratio of error increases. It is the main reason why the evaluation technology of HRQoL can not be applied widely into the reality. With the development of computer technology, electronic method of data collection is invested, dramatically saving the time and cost. Furthermore, the interactive platform is suitable for general people to complete the investigation. Western countries have already deployed this technology into HRQoL assessment.To our best knowledge, there is no report, until now, that electronic method of data collection is applied in HRQoL assessment in China. In cooperation with Dr. Sigle in Goettingen Univeristy of Germany, I developed the Chinese SF-36 based on the QL-Recorder. Afterwards, I also estimated the acceptance and equivalence of the Chinese SF-36 based on the QL-Recorder. In terms of results from "Randomized controlled trial of electronic measurement of health-related quality of life with software QL-Recorder", the Chinese SF-36 based on QL-Recorder can substitute the paper version. Several advantages have been outstood that electronic SF-36 is speedy, high qualified and data would not be lost. By using electronic SF-36, we can conveniently obtain the results which can be output directly into other software because of its good compatibility of data. The detailed information can be found in Appendix 1. "Cross-Over Randomized Control Trial of Electronic Measurement of Health-Related Quality of Life: Comparison between SF-36 Electronic Version and Paper Version".In western developed countries, most researches focus on the effect of chronic diseases on HRQoL. In recent years, several researches take considerations on the relationships between chronic diseases and Health Service Utilization, and the effect of HRQoL on Health Service Utilization. It has been shown that Objective Health is the fundamental determinant of Health Service Utilization due to those researches. Similarly, Lam et al. claimed that there is linearity relationship between the number of chronic diseases and Health Service Utilization in Hong Kong. They also declared thatHRQoL (SF-36) has linear relation with Health Service Utilization, where five of eight dimensions are independent determinants of consultation rate. Thus, it leads to that annual consultation rate and monthly consultation rate increase two and three times respectively. However, this outcome may not be directly appropriate for mainland of China because Health Care system in Hong Kong is greatly differentiated from in mainland. It is necessary to make similar research to identify whether the results from Lam is suitable for mainland or not.According to the review result based on the main Chinese database from 1978 to November 2005, there is no systematic research about influence factors on Health Service Utilization. Some researches mainly concern on factors related to Health Service Utilization, in which objectives are mostly single disease and little features related to General Practice. Besides, no relations between HRQoL and Health Service Utilization are involved.Chronic diseases is not equal to Health Service Utilization for patients since some families consider socio-demographic variable such as economic conditions, medical insurance so that they either give up the chance of consulting a doctor or use self-care method regardless of Health Service resources. HRQoL should represent the objective want of patients on Health Service Utilization, that is to say, individuals have objective want on Health Service Utilization without any considerations on economic conditions or medical insurance. Therefore, subjective HRQoL is a possible independent determinate of Health Service Utilization except for objective chronic diseases and socio-demographic variable. Maybe there are more complex relationships among chronics, socio-demographic factors and HRQoL.If this research can prove that there is a linear relation between HRQoL and Health Service Utilization in mainland of China, it can provide the evidences that HRQoL has clinical significance on patients in General Practice. Then, it can ensure that HRQoL is of importance in Health Service Utilization. Such health technologies like SF-36 can be regarded as specific art to evaluate Health Service Utilization and we can simplify somesensitive problems of investigations and socio-demographic. Especially, we can utilize convenient electronic SF-36 to evaluate Health Service Utilization.2. Objectives2.1 to estimate the prevalence of chronic disease of patients in General Practice;2.2 to know the effect of chronic diseases (eight common chronics) on Health Service Utilization (annual consultation rate, monthly consultation and annual hospitalization rate);2.3 to screen the determinants of Health Service Utilization2.4 to validate whether HRQoL is the independent determinant of Health Service Utilization(annual consultation rate, monthly consultation and annual hospitalization rate), namely, is there a separate linear relation among SF-36 score, annual consultation rate, monthly consultation and annual hospitalization rate;2.5 if this study can prove that the assumption of linear relation among SF-36 score, annual consultation rate, monthly consultation and annual hospitalization rate, the linear relation can be further quantified.2.6 to calculate the effect of variables on Health Service Utilization, those variables involved on three groups named socio-demographic, common chronic disease and SF-36 dimensions. Moreover, we establish the influence model of Health Service Utilization containing subjective HRQoL.3. Methods3.1 Design scheme and samplesOur research is actually cross-sectional design. With respect to that SF-36 is actually classified variables and the basis on the research of Hong-Mei Wang in our institute that the Morbidity Rate of Chronic Diseases of patients in Community Health Service of Zhejiang province is 36.4%. The minimal example is 699 based on the following formulation: n=PQ/S2=400*(Q/P), p=36.4%, Q=l-P.3.2 The sample source, adoption and eliminate standardsThe sample source and adoption standards: patients visiting in Community Health Service Center of Hangzhou city were recruited to the study. Samples were obtained via three stages of randomized cluster principle. Within two weeks started from lth December of 2005, we investigated literal patients more than 14 years, who visited in the Community Health Service Center of Tianshui-wuilin in Xia-cheng district and the Community Health Service Center of Beishang Road in Xi-hu district. Each of them fulfilled "structural questionnaire" and "the Chinese SF-36 based on QL-Recorder "or "paper version of Chinese SF-36" (according to patients' freewill and convenience of investigation) until at least 700 questionnaires are completed.Elimination standard of samples: patients who were unwilling or refused to cooperate with our investigations.3.3 Measurement Tools 3.3.1 Structural questionnaireIt mainly includes 3 types of data in socio-demographic, chronic diseases and Health Service Utilization variables.Socio-demographic data: age, gender, education level, marriage status, professional status, situation of medical insurance and monthly incomeChronic diseases data: common chronic diseases measured based on the overall number of chronic diseases and type of chronic disease. Each investigator will be inquired if he suffers from the following chronic diseases: hypertension,diabetes,any kind of cardiopathy,apoplexy,asthma or other respiratory disease (COPD,chronic arthropathy^ psychological diseases ^ other diseases last over 4 weeks. The totality is summed up as the 8 chronic diseases.Health Service Utilization data: calculate the annual consultation rate (in the last year), monthly consultation rate (in the last month) and annual hospitalization rate (in the last year)3.3.2 the Chinese SF-36 based on the QL-RecorderWe selected the Chinese SF-36 based on the QL-Recorder as the measurement tool of HRQoL according to the results from "Randomized controlled trial of electronic measurement of health-related quality of life with software QL-Recorder" which approved the acceptance and equivalence of the Chinese SF-36 based on the QL-Recorder. Most important, electronic SF-36 has some advantages that paper version of SF-36 can not provide. In the end, it depended on the patients' preference and the convenience of the investigation to choose either electronic or paper version of SF-36. Even if the investigator selected paper version, questionnaire would be collected and checked off, and then be inputted into the electronic SF-36. All data would finally be outputted into SPSS software for further analysis.3.4 Analysis methodWe mainly use QL-Recorder and SPSS software. All data of SF-36 are obtained via QL-Recorder (questionnaire collected by paper version of SF-36 would be checked off and inputted into the QL-Recorder), and then be directly outputted into SPSS vl3. The data from structural questionnaires will be directly recorded into SPSS vl3. To forward stepwise regression model, the input and eliminate standard of variables: P variable of F statistics is 0.05 and 0.10.Data processing: adopting forward stepwise regression model and structured multiphase regression model proposed by Cohen et al.4. Main Results4.1 General demographic features of sampleThis research collected 750 available samples, in which the average age is 52.26 (SD is 16.38), masculine rate is 48.1%, married rate is 83.9%, education level over high school is 60.9%, people who have job is 44.4%, people attending in the basic medical insurance is 87.6%, monthly income over 1600 RMB (cut-off of tax) is 47.9%.This study takes 293 samples (39.1%) which have no type of chronic diseases related to this study as the reference group. Compared with reference: chronic patients are older, the lower education level, the ratio of on work is lower, the ratio of monthly income over 1600 RMB (cut-off of tax) is lower as well. But the ratio of attending in the basic medical insurance is comparatively higher.4.2 The rate of patients with common chronic diseasesThe ratio of patients with common chronic diseases in Community Health Service Center is 60.9%. With increasing in age, the possibility of chronic diseases increased. Most chronic diseases are converged at 40-59 years, 60 years and more than 60 years. Moreover, the groups age of 60 and more than 60 have higher morbidity rate than the corresponding group of 40-59. Simultaneously, we found at least one type of disease existed in the group age of 40-59 is high than 61.6%, in which the morbidity rate of hypertension is very high (43.2%). Besides, the possibility of at lease one chronic disease in the group age of 40 is not low (20.4%). Classified in gender, female patients are generally much more than male patients.4.3 The effect of chronic diseases on Health Service UtilizationOur research has shown that Health Service Utilization (annual consultation rate, monthly consultation rate and annual hospitalization rate) of each chronic disease are all higher than reference group.The overall number of chronic diseases has the linear relation with annual consultation rate, monthly consultation rate and annual hospitalization rate separately. Meanwhile, increasing one type of chronic disease leads to adding additional 8.3 annual consultation rat;the OR value of annual hospitalization rate (the rate of hospitalization in the last year) is 1.786, which hints that increase one type of chronic diseases will induce more 78.6% relative risk of possible hospitalization rate.The effect of chronic diseases on Health Service Utilization: except for apoplexy, other seven types of chronic diseases have a positive linear relation with annual consultation rate;diabetes, cardiopathy and apoplexy have respectively positive linear relation with annual hospitalization rate (the rate of hospitalization at last year).4.4 The determinants of Health Service Utilization4.4.1 forward stepwise regression modelThe variables in this model: first, monthly consultation rate: RE and hypertension;second, annual consultation rate: the overall number of chronic diseases: age, RE, apoplexy, RP, PF and respiratory disease;third, annual hospitalization rate: the overall number of chronic diseases, GH, PF and psychological diseases.4.4.2 structured multiphase regression modelThe variables in this model: first, monthly consultation rate: age, monthly income, hypertension and RE;second, annual consultation rate: age, the overall number of chronic diseases, respiratory disease, apoplexy, RE, RP, and PF;third, annual hospitalization rate: age, marriage status, education level, the overall number of chronic diseases, GH.4.4.3 The advantages of structured multiphase regression modelStructured multiphase regression model is better than forward stepwise regression model when it is required to determine the relation between several independent variables and one dependent variable, since these independent variables have related effect on the dependent variable. Because the structured multiphase regression model forced the variables from previous stage firstly into the model in order to maintain their contributions, it ensures and measures the mutual influences among these variables. Thus, structured multiphase regression model can really represent the relative contributions of each variable on Health Service Utilization.4.5 The validation and quantification of the assumption on linear relation between SF-36 scores and Health Service UtilizationOur research proved, for the first time in Mainland China, that the assumption on linear relation between SF-36 scores and Health Service Utilization. We further calculated, in quantification, the separate contribution rate of SF-36 score to Health Service Utilization, namely, the ration of subjective want of Health Service Utilization to the final realization of Health Service Utilization. Furthermore, we evaluated the total contribution rate of three groups' variable (inclusive SF-36 score) to Health Service Utilization.From the structured multiphase regression model, the followings are identified. Firstly, in terms of monthly consultation rate, SF-36 score separately intercepted 5.1% contribution, while both socio-demographic variables and the variables of chronic diseases explained only 6.9%. Secondly, with respect to annual consultation rate, SF-36 score solely explained 2.7% contribution and both socio-demographic variables and the variables of chronic diseases explained 25.3%. Thus, it totally explained 28% contribution concerning the variables of above two stages. Thirdly, referring to annual hospitalization rate, both socio-demographic variables and the variables of chronicdiseases explained 18.4% contribution, while SF-36 score explained 4.7% by itself. So, there is 23.1% contribution when summing up the variables of above two stages.Therefore, both socio-demographic variables and the variables of chronic diseases have much more impact on Health Service Utilization than SF-36 score, in terms of monthly consultation rate, annual consultation rate and annual hospitalization rate. Conclusively, the factors of socio-demographic variables and the variables of chronic diseases have larger influences on Health Service Utilization than SF-36 score, in Mainland China.4.6 The effect model of Health Service UtilizationThe effect model of Health Service Utilization as adopting structured multiphase regression model is denoted as follows:Monthly consultation rate = ao+ai* age+a2*(monthly income)+a3* hypertension +O4*RE=2.966 + 0.017* age + -0.207*(monthly income) + 1.324* hypertension + -0.025*REAnnual consultation rate = Po+pi* age +p2* (the sum of chronic diseases)+P3* (respiratory disease)+p4*apoplexy+p5* RE +p6* RP +p7* PF=5.968 + 0.227* age + 6.206*(the sum of chronic diseases) + 6.429* (respiratory disease) + -13.275* apoplexy +-0.091* RE + 0.073* RP +-0.110* PFAnnual hospitalization rate = yo+yi* age +y2* (marriage status)-Hy3* (education level )-Hy4* (the sum of chronic diseases)-^* (psychological diseases) +76* GH = -1.513 + 0.038* age + 0.328*(marriage status)+ -0.242*(education level )+ 0.507*(the sum of chronic diseases) + -1.571*(psychological diseases) + -0.032* GHIt is obvious that the effect model of Health Service Utilization (monthly consultation rate, annual consultation rate, annual hospitalization rate) includes at least one of SF-36 dimensions. Thus, our research established the effect model of HealthService Utilization based on variable of socio-demographic variables, variable of common chronic diseases and variable of SF-36 dimension (including subjective HRQoL).5. Conclusions5.1 Prevalence of common chronic diseasesOur research clues to: the ratio of common chronic diseases to all examples from visiting patients in Community Health Service Center is 60.9%. The department of public health should not only concern on that chronic diseases have high possible incursion at old people, but also can not ignore that these working people at the age of 40-59, even those younger people under 40 years old. By doing this way, it can facilitate the deployment of health resources.5.2 The impact of chronic diseases on Health Service UtilizationOur research focuses on 8 types of common chronic diseases. We also discussed the relation between common chronic diseases and Health Service Utilization, respectively regarding monthly consultation rate, annual consultation rate, and annual hospitalization rate. Significantly, our systematical approach addressed the scarcity that most researches in China only focus on single disease, regardless of the feature of General Practice.5.3 The determinants of Health Service UtilizationThe variables applied in forward stepwise regression model: first, monthly consultation rate: RE and hypertension;second, annual consultation rate: the sum of chronic diseases, age, RE, apoplexy, RP, PF and respiratory disease;third, annual hospitalization rate: the sum of chronic diseases, GH, PF and psychological diseases.The variables applied in structured multiphase regression model: first, monthly consultation rate: age, monthly income, hypertension and RE;second, annual consultation rate: age, the sum of chronic diseases, respiratory disease, apoplexy, RE, RP, and PF;third, annual hospitalization rate: age, marriage status, education level, the sum of chronic diseases, GH.5.4 The comparison of forward stepwise regression model and structured multiphase regression model.Our research identified the result from Cohen et al.: structured multiphase regression model is better than forward stepwise regression model when it is required to determine the relation between several independent variables and one dependent variable, since these independent variables have related effect on the dependent variable.5.5 The validation and quantification of the assumption on linear relation between SF-36 scores and Health Service UtilizationOur research proved, for the first time in Mainland China, that the assumption on linear relation between SF-36 scores and Health Service Utility. We further calculated in quantification, the separate contribution rate of SF-36 score to Health Service Utilization. Besides, our research induces that there is gender difference of SF-36 score on Health Service Utilization, namely, the female are higher than the male. That is to say, our research sustained the studies of Nelson, Lam, et al. that the female have generally higher Health Service Utilization compared to the male.In Mainland China, the factors of both socio-demographic variables and chronic diseases have much more impact on Health Service Utilization than SF-36 score.5.6 The effect model of Health Service UtilizationThere is at least one of SF-36 dimensions included in Health Service Utilization (monthly consultation rate, annual monthly consultation rate, annual hospitalization rate). Thus, our research set up the effect model of Health Service Utilization based on socio-demographic variables, variable of common chronic diseases and variable of SF-36 dimension (including subjective HRQoL).
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