2010 Fiscal Year Final Research Report
Development of IT infrastructure for active disease surveillance
| Project/Area Number |
19390181
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Public health/Health science
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| Research Institution | National Institute of Public Health |
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Principal Investigator |
OKAMOTO Etsuji 国立保健医療科学院, 経営科学部・経営管理室, 室長 (90247974)
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| Co-Investigator(Kenkyū-buntansha) |
TACHIBANA Tomoko 国立保健医療科学院, 研究情報センター情報デザイン, 室長 (40221387)
TANAKA Hiroshi 東京医科歯科大学, 教授 (60155158)
TANIHARA Shinichi 福岡大学, 医学部, 准教授 (40285771)
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| Project Period (FY) |
2007 – 2010
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| Keywords | 積極的サーベイランス / レセプトナショナルデータベース / 新型インフルエンザ / オントロジー / ファーマコビジランス |
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| Research Abstract |
Accurate and prompt surveillance and/or monitoring of the number of patients diagnosed with target diseases are indispensable for any public health activities. A variety of surveillance/monitoring are instituted by law, for example, the sentinel surveillance for infectious disease pursuant to the Infectious Diseases Control Act, mandatory reporting of food poisoning pursuant to the Food Safety Act, spontaneous reporting of drug adverse events pursuant to the Pharmaceutical Affairs Act and regional cancer registry as a voluntary reporting. Unfortunately, however, these surveillance/monitoring may not be exhaustive and prompt because not all doctors/providers report what they are required to do particularly in the absence of penalty. Rather than waiting passively for voluntary reporting, the possibility of active surveillance on the administrative data such as the national claims database(NDB) was investigated through this project. The NDB may be exhaustive give the universal coverage of
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Japan's health insurance system, but there may be technical difficulties when one tries to use the claims data for disease surveillance/monitoring. 1) Claims tend to include numerous diagnoses, some of which are rule-out diagnoses to justify the clinical services rendered. Also, the rate of such rule-out diagnoses vary from diagnostic categories to diagnostic categories. Once must take into consideration the inter-category variance of such rule-out diagnoses when estimating the real incidence. 2) To make accurate estimates of diagnosed patients, it is better to combine not only diagnoses but also pharmaceutical data and clinical procedures, the"Claims ontology" combining multiple dimensions of data included in claims. And, 3) statistical and geographical method to determine the onset of epidemic of acute infections like influenza using daily data in a small geographical area such as cities, towns and villages. The newly created NDB contained claims since April 2009, an ideal timing to evaluate the novel(swine) influenza epidemic starting from Kansai area. Unfortunately, NDB was not available for research use due to privacy restrictions and an alternative surveillance system using pharmaceutical claims data of Kumamoto prefecture was developed with. Less
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