Warning: fopen(/home/virtual/epih/journal/upload/ip_log/ip_log_2023-02.txt): failed to open stream: Permission denied in /home/virtual/lib/view_data.php on line 83 Warning: fwrite() expects parameter 1 to be resource, boolean given in /home/virtual/lib/view_data.php on line 84 A stochastic model for determining the number of outpatient-visits
Skip Navigation
Skip to contents

Epidemiol Health : Epidemiology and Health

OPEN ACCESS
SEARCH
Search

Articles

Page Path
HOME > Epidemiol Health > Volume 6(1); 1984 > Article
Original Article A stochastic model for determining the number of outpatient-visits
Dong Ki Kim, Han Joong Kim
Epidemiol Health 1984;6(1):62-69
DOI: https://doi.org/
  • 3,706 Views
  • 46 Download
  • 0 Crossref
  • 0 Scopus

It is a hypothesized that the number of outpatient visits can be represented by some of three different probability models, i.e., the truncated Poisson, Zeta, and logarithmic series distributions. Maximum likelihood estimates of parameters of above distributions were obtained by using grouped data according to the number of visits. A X2 goodness of fit test was also made to compare the fits of the three distributions, and the value of this statistic was classified and compared according to the types of medical care facilities. For the study, we analized the 1,900,000 data claimed at the Korea Medical Insurance Corporation for three months in 1984. The results are summarized as follows: 1. Based on the likelihood ratio statistic as a test criterion, both the truncated poisson and Zeta distribution are not appropriate for the model of the number of outpatient visits. The results show that the expected frequencies of the truncated Poisson are smaller than the observed in the tail, but those of Zeta are larger in it. 2. The logarithmic series distribution it found to provide a good fit to data in case of University Hospital, General Hospital, and Hospital. When we apply this distribution in the 10 common diseases, the estimates of the parameter vary from 0.39567 to 0.54176 for University Hospita, from 0.45329 to 0.65387 for General Hospital, and from 0.55104 to 0.77625 for Hospital. This finding might be applicable to the health utilization study, for example, outpatient administrations etc. 3. On the other hand, in case of Clinic, even the logarithmic series distribution cannot be fitted to the data well. The characteristic of clinic utilization such as little variety of its patterns regardless of a large numbers could be the reason of the above results. It is reserved for a further research to construct the compound or modified distributions which are able to explain the number of outpatient visits in case of Clinic.


Epidemiol Health : Epidemiology and Health