- An Approach to Survey Data with Nonresponse: Evaluation of KEPEC Data with BMI.
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Jieun Baek, Weechang Kang, Youngjo Lee, Byung Joo Park
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Korean J Prev Med. 2002;35(2):136-140.
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 Abstract
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- OBJECTIVES
A common problem with analyzing survey data involves incomplete data with either a nonresponse or missing data. The mail questionnaire survey conducted for collecting lifestyle variables on the members of the Korean Elderly Phamacoepidemiologic Cohort(KEPEC) in 1996 contains some nonresponse or missing data. The proper statistical method was applied to evaluate the missing pattern of a specific KEPEC data, which had no missing data in the independent variable and missing data in the response variable, BMI. METHODS: The number of study subjects was 8,689 elderly people. Initially, the BMI and significant variables that influenced the BMI were categorized. After fitting the log-linear model, the probabilities of the people on each category were estimated. The EM algorithm was implemented using a log-linear model to determine the missing mechanism causing the nonresponse. RESULTS: Age, smoking status, and a preference of spicy hot food were chosen as variables that influenced the BMI. As a result of fitting the nonignorable and ignorable nonresponse log-linear model considering these variables, the difference in the deviance in these two models was 0.0034(df=1). CONCLUSION: There is a lot of risk if an inference regarding the variables and large samples is made without considering the pattern of missing data. On the basis of these results, the missing data occurring in the BMI is the ignorable nonresponse. Therefore, when analyzing the BMI in KEPEC data, the inference can be made about the data without considering the missing data.
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- Comparison of Efficiency between Individual Randomization and Cluster Randomization in the Field Trial.
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Hye Won Koo, Min Jeong Kwak, Youngjo Lee, Byung Joo Park
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Korean J Prev Med. 2000;33(1):51-55.
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- OBJECTIVES
In large-scale field trials, randomization by cluster is frequently used because of the administrative convenience, a desire to reduce the effect of treatment contamination, and the need to avoid ethical issues that might otherwise arise. Cluster randomization trials are experiments in which intact social unit, e.g., families, schools, cities, rather than independent individuals are randomly allocated to intervention groups. The positive correlation among responses of subjects from the same cluster is in matter in cluster randomization. This thesis is to compare the results of three randomization methods by standard error of estimator of treatment effect. METHODS: We simulated cholesterol data varing the size of the cluster and the level of the correlation in clusters and analyzed the effect of cholesterol-lowering agent. RESULTS: In intra-cluster randomization the standard error of the estimator of treatment effect is smallest relative to that in inter-cluster randomization and that in individual randomization. CONCLUSIONS: Intra-cluster randomization is the most efficient in its standard error of estimator of treatment effect but other factor should be considered when selecting a specific randomization method.
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- An Evaluative Analysis of the Referral System for Insurance Patients.
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Dalsun Han, Byungyik Kim, Youngjo Lee, Sangsoo Bae, Soonho Kwon
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Korean J Prev Med. 1991;24(4):485-495.
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- This study examined the effects of referral requirements for insurance patients which have been enforced since July 1, 1989 when medical insurance coverage was extended to the whole population except beneficiaries of medical assistance program. The requirements are mainly aimed at discourag - ing the use of to Vii; ry care hospitals by imposing restrictions on the patient's choice of a medical service facility. The expectation is that such change in the pattern of medical care utilization would produce several desirable effects including increased efficiency in patient care and balanced development of various types of medical service facilities. In this study, these effects were assessed by the change in the number of out-patient visits and bed-days per illness episode and the share of each type of facility in the volume of services and the amount of expenditures after the implementation of the new referral system. The data for analysis were obtained from the claims to the insurance for government and school employees. The sample was drawn from the claims for the patients treated during the first six months of 1989, prior to the enforcement of referral requirements, and those of the patients treated during the first six months of 1990, after the enforcement. The 1989 sample included 299,824 claims (3.6% of total) and the 1990 sample included 332,131(3.7% of total). The data were processed to make the unit of analysis an illness episode instead of an insurance claim. The facilities and types of care utilized for a given illness episode are defined to make up the pathway of medical care uti lization. This pathway was conceived of as a Markov Chain process for further analysis. The conclusion emerged from the analysis is that the enforcement of referral requirements resulted in less use of tertiary care hospitals, and thereby decreased the volume of services and the amount of insurance expenses per illness episode. However, there are a few points that have to be taken into account in relation to the conclusion. The new referral system is likely to increase the use of medical services not covered by insurance, so that its impact on national health expenditures would be different from. that on insurance expenditures. The extension of insurance coverage must have inereased patient load for all types of medical service organizations, and this increase may be partly responsible for producing the effects attributed to the new referral system. For example, excessive patient load for tertiary care hospitals may lead to the transfer of their patients to other types of facilities. Another point is that the data for this study correspond to very early phase of the new system. But both patients and medical care providers would adapt themselves to the new system to avoid or overcome its disadvantages for them, so as that its effects could change over time. Therefore, it is still necessary to closely monitor the impact of the referral requirements.
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Summary
- Change in Medical Care Utilization over Time in Early Years of Insurance Coverage.
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Byoung Yik Kim, Youngjo Lee, Dal Sun Han
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Korean J Prev Med. 1990;23(2):185-193.
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- The purpose of this study is to observe the pattern of change in medical care utilization over time in early years of insurance coverage. The source of data is the benefit records file of a voluntary medical insurance society for covering the four-year period, from 1982 to 1985. The measure of medical care utilization used in this study is the age-sex standardized percentage of the enrollee who have visited a physician over total analytical population during a three-month period. For six cohorts by the year of enrollment (1979-1984), the relationship between the utilization and duration of insurance coverage was examined controlling for the calender year and season. In the analysis, logistic multiple regression and residual analysis were employed. It was observed that medical care utilization rapidly increased during the early stage of insurance coverage, and after then increased at a slower rate over time to become almost stable in about twenty months.
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