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Querying the ill-defined stroke diagnoses on death certificates and their effects on type-specific mortality in

Tsung-Hsueh Lu1, Shiuh-Ming Huang

  • 1Department of Public Health, Chung Shan Medical University, No. 110, Section 1, Chien Kuo North Road, Taichung 402, Taiwan. robertlu@ms1.hinet.net

Insights

Querying physicians significantly improved stroke subtype classification on death certificates in Taiwan. This method enhances cause of death statistics, revealing substantial changes in cerebral hemorrhage and infarction mortality rates.

Area of Science:

  • Public Health
  • Epidemiology
  • Medical Statistics

Background:

  • Ill-defined causes of death in Taiwan impede accurate stroke subtype mortality studies.
  • Accurate classification of stroke subtypes is crucial for effective public health interventions.

Purpose of the Study:

  • To evaluate the impact of physician queries on refining stroke subtype classification and mortality data.
  • To assess the suitability of non-queried mortality data for type-specific stroke analysis.

Main Methods:

  • Reviewed 2632 death certificates with ill-defined cerebrovascular disease codes (ICD-9 436, 437.9).
  • Queried certifying physicians for 2035 hospital-issued certificates, obtaining responses for 1505 (74%).
  • Analyzed changes in stroke subtype coding (cerebral hemorrhage, cerebral infarction) and age-adjusted death rates post-querying.

Main Results:

  • Physician queries led to more specific coding for 79% of cases, primarily changing to cerebral hemorrhage (CH) or cerebral infarction (CI).
  • Age-adjusted death rates increased significantly: CH by +16% (men) and +20% (women); CI by +100% (men) and +130% (women).
  • Changes in CH/CI ratios were more pronounced in younger age groups (<65 years).

Conclusions:

  • Physician querying is an effective method for improving the quality and specificity of stroke subtype data in mortality statistics.
  • Unqueried mortality data in Taiwan are unsuitable for reliable type-specific stroke analysis due to significant under-classification.
  • Enhanced data accuracy supports better epidemiological research and targeted public health strategies for stroke.

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