{"id":1570,"date":"2026-09-04T09:33:09","date_gmt":"2026-09-04T00:33:09","guid":{"rendered":"http:\/\/www.med.miyazaki-u.ac.jp\/home\/english-demo\/?page_id=462"},"modified":"2026-09-04T09:33:09","modified_gmt":"2026-09-04T00:33:09","slug":"public-health","status":"publish","type":"page","link":"http:\/\/www.med.miyazaki-u.ac.jp\/home\/english\/departments\/laboratories\/public-health\/","title":{"rendered":"Public Health"},"content":{"rendered":"\n

Tatsuyoshi Ikenoue, M.D., M.P.H.,Ph.D.<\/strong>
tatsuyoshi_ikenoue@med.miyazaki-u.ac.jp<\/p>\n\n\n\n

Summary<\/h2>\n\n\n\n

Public health is concerned with the health of populations rather than of single patients, and its central question today is how to turn data into decisions. Japan now generates an extraordinary volume of routinely collected health data \u2014 nationwide administrative claims, annual health checkup records, disease registries, and long-term care data \u2014 and our department uses these resources to answer questions that randomized trials cannot easily address. Our work spans three connected areas. First, big data science<\/strong>: we build, link, and analyze large-scale real-world databases to describe how care is actually delivered and how disease burden is distributed. Second, policy and practice evaluation<\/strong>: using interrupted time-series designs, comparative effectiveness methods with active comparators, instrumental variables, and analyses of hospital- and region-level variation, we estimate what national health policies and clinical practices actually achieve. Third, translation into decisions<\/strong>: we design pragmatic trials, including behavioral “nudge” interventions, develop clinical prediction models, and conduct systematic reviews, so that our findings can inform government, clinicians, and patients. We collaborate widely with clinical departments, other universities, and international partners.<\/p>\n\n\n\n

Research Projects<\/h2>\n\n\n\n
  1. Big data science: construction, linkage, and analysis of nationwide claims, health checkup, and registry databases<\/li>
  2. Evaluation of national health policies and health system performance (evidence-based policy making)<\/li>
  3. Comparative effectiveness and safety research on drugs and medical procedures using real-world data<\/li>
  4. Variation in clinical practice and quality of care across hospitals and regions<\/li>
  5. Pragmatic randomized trials and behavioral interventions for health promotion<\/li>
  6. Clinical prediction modeling, machine learning, and evidence synthesis<\/li><\/ol>\n\n\n\n

    Research Techniques<\/h2>\n\n\n\n
    1. Design and management of cohort, case\u2013control, case-crossover, and cross-sectional studies<\/li>
    2. Construction, cleaning, and record linkage of large-scale administrative and health checkup databases<\/li>
    3. Biostatistics and multivariable regression modeling<\/li>
    4. Causal inference (propensity score methods, instrumental variables, difference-in-differences, interrupted time-series, new-user active comparator designs)<\/li>
    5. Prediction modeling, machine learning, and deep learning applied to clinical and imaging data<\/li>
    6. Pragmatic randomized controlled trials and behavioral (nudge) intervention design<\/li>
    7. Systematic review and meta-analysis<\/li>
    8. Statistical programming (R, Python, SQL)<\/li><\/ol>\n\n\n\n

      For Students<\/h2>\n\n\n\n

      We welcome medical and graduate students interested in population health, data science, and health policy. Students can join ongoing database studies, learn statistical programming from the basics, and see how research evidence reaches clinicians and policymakers. Prior programming experience is not required, and programs are adapted to each student’s interests and available time.<\/p>\n\n\n\n

      Publications<\/h2>\n\n\n\n
      1. Yamamoto S, et al. Impact of national policies promoting appropriate antibiotic use on outpatient prescriptions and hospitalizations for bacterial complications of acute respiratory infections in Japan: an interrupted time-series analysis. Open Forum Infect. Dis., 13, ofag312 (2026)<\/li>
      2. Katsura M, et al. Hospital-level variation in early tracheostomy and withdrawal of life-sustaining treatment in severe traumatic brain injury: a nationwide analysis. Crit. Care Med., in press (2026)<\/li>
      3. Mori Y, et al. New-onset atrial fibrillation and accelerated kidney function decline in working-age adults. JAMA Netw. Open, 9, e2612823 (2026)<\/li>
      4. Tominaga R, et al. Comparative effectiveness of romosozumab versus teriparatide for fracture prevention: a new-user, active comparator design. Bone, 198, 117523 (2025)<\/li>
      5. Yamada Y, et al. Nudge-based interventions on health promotion activity among very old people: a pragmatic, 2-arm, participant-blinded randomized controlled trial. J. Am. Med. Dir. Assoc., 24, 390-394 (2023)<\/li>
      6. Fukuma S, et al. Association of the national health guidance intervention for obesity and cardiovascular risks with health outcomes among Japanese men. JAMA Intern. Med., 180, 1630-1637 (2020)<\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

        Tatsuyoshi Ikenoue, M.D., M.P.H.,Ph.D.tatsuyoshi_ikenoue@med.miyazaki-u.ac.jp Summary Public health is concern … <\/p>\n

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