Background : Health insurance claims contain invaluable data for epidemiological survey. However their use for research purposes has been hampered by both bureaucratic red-tape and technical limitations. These include the lack of legal rationale for disclosure and the lack of electronic data transfer. In response to the recent advancement in these field, such as the governmental policy change to allow disclosure of the claims to patients and a rapid computerization of the claims, researchers interested in health insurance claims held liaison meetings to exchange views and know-hows to facilitate the epidemiological research using health insurance claims.
Reports on the Meeting : The liason meetings have so far been held twice as part of Japan Public Health Association annual assembly, at Yamagata in 1995 and at Yokohama in 1997, both sponsored by the author. Fourteen researchers presented their research activities using health insurance claims and discussed with the attendants on their experience to overcome the bureaucratic red-tape and technical limitations. Two of the presenters beside the author were pharmacoepidemiologists : Dr. Hayashi addressed the value and possibilities of the claims as data source for pharmacoepidemiology and Dr. Kubota proposed PEM (Prescription Event Monitoring) using health insurance claims as triggers to complement the present voluntary ADR reporting.
Implications : Since the bureaucratic and technical obstacles may be better handled through a coordinated and liaisoned action of the researchers, it is necessary to form a consortium of researchers and professionals who have any interest in health insurance claims regardless of their purposes and make guidelines and recommendations to assure legitimate and appropriate utilization of the potentially sensitive but useful individual information.

Objective : To elucidate the availability and applicability of the information contained in health insurance claims to pharmacoepidemiological studies with particular reference to the computerization of insurance claims submitted by dispensing pharmacies.
Data Sources : Outpatient insurance claims of two health insurance societies based in the Kanto region. The survey, funded by the Federation of Health Insurance Societies, was undertaken as part of a demonstration project to develop methodologies for insurers to evaluate the clinical performance of providers.
Study Selection : Disease-specific, provider-specific and clinical procedure specific comparison of the per-claim cost. All claims from pharmacies were matched with the prescribing hospitals or clinics to capture the entire medication.
Data Extraction : All claims were reviewed by trained reviewers and procedure specific costs were classified into five disease categories to obtain the best estimate of disease-specific cost.
Results : Inter-provider variations were assessed based on overlapping of the overall average and the confidence interval of the doubled standard error after adjusting for age. Contrary to popular belief, academic medical centers showed significantly lower medication cost than clinics for the treatment of acute upper respiratory infection. Prescription pattern to favor high cost antibiotics accounted for higher per-claim medication cost of clinics with concentration of high cost claims.
Conclusion : Based on the authors' experience and methodologies developed, computerization of insurance claims will achieve consistency, efficiency and timelines which are of utmost importance for pharmacoepidemiological studies. On the other hand, insurers may preempt the claims review and reimbursement organizations by appealing to the pharmacy claims through electronically matching the prescribing claims. The nature of evidence sought by both pharmacoepidemiological researchers and insurers, whether it be for the purpose of post-marketing survey or cost cutting, would eventually converge.

Prevalence of age-dependent diseases such as asthma is confounded not only by aging effects but also by cohort and period effects. Age-period-cohort (APC) analysis is commonly performed to isolate the effects of these three factors from two-way tables of prevalence by age and birth cohort. However, APC analysis suffers from technical difficulties such as non-identifiability problems. We isolated the effects of these three factors in a step-by-step manner by analyzing Japan's school health data collected from 1984 to 2004 focusing on asthma prevalence among school children aged 6-17 years consisting of 30 birth cohorts (entering classes). We verified the accuracy of our method showing high agreement of the observed age-, period- and cohort-specific data and the data predicted by our method. The aging effects were found to follow cubic equations whose multinomial coefficients were determined by an optimization technique. The obtained aging effect curves of age-specific asthma prevalence showed that boys reach the peak prevalence at 13 and girls at 14, declining markedly afterward. The cohort effects, defined as the arithmetic asthma prevalence means for ages 6-17 years, showed consistent upward trends for the 30 birth cohorts born in 1968-97 for both sexes. The period effects showed a consistent decline since 1984 but abruptly increased in 1999 and then declined again. We were not able to identify the exact cause of the increase in 1999, therefore, this should be examined in the future studies. Because the cohort effects show no sign of leveling off yet, asthma prevalence will likely increase in the foreseeable future.