med-health

name	med-health
description	Use when writing a medical or health news story — clinical research breakthroughs, public health alerts, drug approvals, epidemiology, health policy, patient stories, risk communication — from research papers, press releases, health authority statements, or interviews. Specializes the med-news-reporter workflow for health-beat discipline: relative risk framing, absolute baseline inclusion, evidence-hierarchy verification, deidentification protocol, and WHO suicide-reporting compliance. Triggers on phrases like '寫一篇醫學新研究', 'draft a health news piece', '整理流行病新聞', '幫我把這份臨床試驗結果寫成新聞', '健康新聞報導', 'write up this drug approval', 'health story from this study'. Do NOT use for medical advice (→ consult healthcare provider), pharmaceutical marketing (→ mkt-pharma), hospital PR/press release in house voice (→ pr-press-release).
metadata	{"category":"WP-50 大眾傳播","tags":["news","journalism","health-news","medical-journalism","public-health","epidemiology","media-ethics"]}

Medical & Health News Reporting

This skill specializes med-news-reporter for the medical/health beat. Read med-news-reporter first for the general 6-step workflow (type selection, material audit, fact-check, balance, ethics, literacy). This file adds health-specific discipline on top.

Overview

Distilled from health-journalism curricula at Stanford Medicine+Muse, Johns Hopkins SFDH, AHCJ (Association of Health Care Journalists), Columbia Mailman, NTU Public Health, and Taiwan health-media ethics standards. Covers five sub-types: research breakthroughs / public-health alerts / drug approval / health policy / patient stories. Core challenge: translating statistical evidence for public understanding without misrepresenting risk or false certainty.

IRON LAW: Relative Risk Without Absolute Risk Is Misleading

Every medical claim in the form "X% increase/decrease in risk" MUST cite
absolute baseline numbers: baseline incidence, NNT (Number Needed to Treat),
absolute risk reduction, or absolute risk change. "50% reduction in risk of
heart attack" is meaningless without "from 4 in 1000 to 2 in 1000 per year".
LLM default: lead with the relative risk (sounds dramatic), omit baseline.
Readers then overestimate the clinical significance. Override that default
by naming the denominator first, then the percentage.

Why this is non-obvious: "50% reduction" sounds much more impactful than "2 fewer heart attacks per 1000 per year", yet both describe the same result. Research-to-media translation routinely inverts this — the press release says "50% reduction", the outlet runs that number, and readers assume a larger clinical effect than evidence supports. This is the single most common source of health-news overclaim.

Rationalization Table — these justifications DO NOT override the Iron Law:

Claude might think...	Why it's still a violation
"'50% reduction' is the research result, I'll just quote it"	Quoting a relative-risk figure without the absolute baseline is relaying an incomplete fact. The journal paper has the baseline; the press release usually does not. Cite both or cite neither + flag.
"The baseline is in the methods section, readers can look it up"	Readers will not. The article is the only context they read. Omitting it is misleading by omission, not just incomplete.
"Adding the absolute number makes the story less dramatic"	That is the point. Accuracy is not a bug. If the absolute effect is small, the reader deserves to know.
"NNT is too technical for general audiences"	True, and it's also the clearest way to show clinical significance. Use NNT in a side sentence ('meaning doctors would need to treat about 500 people to prevent one case'). Not optional.
"The researcher said 'statistically significant'—that's the main story"	Statistically significant ≠ clinically significant. A study of 100,000 people can show a 0.5% effect as "significant" if it's real. Report both p-value and effect size.

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When to Use

Trigger conditions:

• User supplies health/medical material — journal abstracts, clinical trial results, drug approval announcements, public health advisories, epidemiological data, health-policy statements, patient interviews — and asks for a news piece.
• User asks for "醫學新聞", "健康新聞", "health story", "research reporting", "drug news", "epidemic coverage", "health policy piece", "clinical breakthrough".
• User paraphrases: "寫一篇醫學新研究", "整理流行病新聞", "幫我把這份臨床試驗結果寫成新聞", "turn this NIH press release into a story", "draft a piece on this WHO alert".

Input signals:

• Named disease, drug, treatment, researcher, institution, study name, clinical trial identifier, or epidemiological data.
• Direct quotes from clinicians, researchers, health authorities (CDC, 衛福部, WHO, etc.).
• Statistical claims (relative risk, incidence, prevalence, mortality, efficacy, confidence intervals).
• Regulatory status (FDA approval, 食藥署 listing, Phase III trial completion).

When NOT to use:

• "What do I have?" / personal medical symptom advice → direct user to healthcare provider, not journalism skill.
• Pharmaceutical company press release in the company's own voice → use pr-press-release.
• Hospital marketing / institutional PR ("Our Advanced Surgery Center Achieves...") → use pr-*.
• Promotion of unproven remedy or supplement as scientific fact → refuse; suggest user consult source integrity first.

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Methodology

Step 0: Defer general workflow to med-news-reporter

Read or have already loaded med-news-reporter for: material audit, fact-checking, source-strength tagging, balance principle, media-ethics check, media-literacy self-check. Do not re-implement those steps here. This file specializes Steps 1, 2, 3, and adds health-specific Step 7 (Evidence Hierarchy & Risk Framing Audit).

Step 1: Classify the health-story sub-type

Sub-type	Signals	Sub-template focus
Research breakthrough	Journal paper, pre-print, press release from university/NIH	Evidence level check; RR + AR framing; replication status
Public health alert	CDC alert, 衛福部 advisory, WHO statement, disease outbreak	Absolute numbers (cases, deaths); transmission risk; at-risk population; response guidance
Drug approval	FDA/食藥署 approval, Phase III completion, clinical trial results	Trial design rigor; efficacy + side-effect rate; NNT; cost/access; alternative treatments
Health policy	Coverage decision, vaccine recommendation, screening guideline, regulation	Policy rationale; affected population; evidence basis; expert consensus; dissenting opinion
Patient story	Interview, testimonial, case narrative	De-identification protocol; generalizability limits; attribution; expert context

If material spans sub-types (e.g. a policy change triggered by a study), classify by the primary news driver.

Step 2: Source vetting & evidence-hierarchy tagging

Every health claim must carry evidence-level tag at first mention:

Evidence Hierarchy (strongest → weakest):
1. Meta-analysis / systematic review of RCTs
2. Large RCT (n > 500)
3. Small RCT (n < 500)
4. Cohort study / case-control study
5. Case series / case report
6. Expert opinion / editorials
7. Anecdote / single patient story

Bad tagging: 「新研究表示...」(which study? what strength?) Good tagging: 「今年發表在 Lancet 的一項 1,200 人隨機對照試驗表示...」or 「基於個案報告（證據等級 5）...但尚未進行人體試驗」

Source tier (extends med-news-reporter):

Tier	Examples	Treatment
Government health authority	CDC, 衛福部、疾管署、食藥署、WHO	Direct citation; highest credibility tier
Peer-reviewed journal	Lancet, JAMA, BMJ, Nature Medicine, 台灣醫學會期刊	Always cite journal name + DOI; include publication date
Preprint / not yet peer-reviewed	medRxiv, bioRxiv	Must flag as "not yet peer-reviewed"; requires editor review before publication
University press release	Without access to actual paper	Treat as Tier 2.5; verify against journal preprint / abstract
Single researcher quote	Without published evidence	Tier 4; acceptable only as "expert opinion" with explicit caveat
Pharmaceutical company	Clinical trial sponsor	Tier 3–4; always disclose funding source; cross-verify against independent data when possible
Patient anecdote	Interview, testimonial, Facebook post	Tier 7; only acceptable as illustrative narrative, never as evidence

Step 3: Health-specific risk check

Beyond med-news-reporter's general ethics check, add:

1. 個人資料保護法 (PDPA) + 醫療法 §72 (Patient Privacy):

   • Patient case reports must be de-identified: age range (not exact), no named institution/hospital, no unique medical conditions that allow re-identification.
   • Example: ❌ "63-year-old Mr. Chen A treated at NTU Hospital on March 15 for liver cancer with rare genetic mutation" (re-identifiable)
   • Example: ✅ "A 60–65-year-old male with common cancer type" (anonymized)

2. WHO Suicide Reporting Guidelines (essential, non-negotiable):

   • Do NOT name the method, location, or date of death.
   • Do NOT publish a suicide note or detailed narrative.
   • ALWAYS include helpline number(s) (1925, 安心专线, international).
   • Do use framing: "died by suicide" or "suicide" (not "committed suicide", "successful attempt").
   • Breaking this rule increases copycat risk (Werther Effect documented by WHO); this is a professional liability.

3. 醫療廣告法 (Medical Advertising Law):

   • If a source has financial interest in the product (pharma company, researcher with stock, hospital with proprietary treatment), disclose it.
   • Do not amplify unproven claims (e.g., supplement "cure" claims without RCT evidence).

4. 藥物名稱使用合理性:

   • Generic name preferred over brand name ("ibuprofen" not "Advil") unless brand is essential to the story.
   • New drugs: include both generic + brand on first mention; thereafter use generic.

5. 傳染病防治法 (Communicable Disease Control Act):

   • Early epidemic numbers are often revised as data accumulates. State explicitly: "as of [date], [source] reports X cases".
   • Avoid implied causation ("after the vaccine" ≠ "caused by the vaccine"); use temporal language precisely.

Step 4: Evidence Hierarchy & Risk Framing Audit (health-specific addition)

Before output, apply:

1. Evidence Strength Audit: for each medical claim, verify it cites the evidence level. Single case reports must not be presented as "research shows".
2. Relative → Absolute Conversion: every claim of "X% increase/decrease" must be paired with absolute baseline (see Iron Law above).
3. NNT / ARR / Baseline Incidence: include at least one of these metrics to ground clinical significance.
4. Replication Status: if this is a single study, state so ("first evidence" / "needs confirmation" / "confirms earlier findings").
5. Confidence Interval / Uncertainty: include the range, not just the point estimate. "30% to 40%" not just "35%".
6. Funding Disclosure: if any source has financial stake in the result, disclose it early ("funded by Pharma Corp X").

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Output Format

Use the med-news-reporter base format, with health-specific additions to the meta footer:

[Headline / sub-headline / body paragraphs per med-news-reporter]

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**稿件類型**: 醫學研究報導 / 公衛警訊 / 藥品核准 / 健康政策 / 患者故事
**字數**: approx. XXX
**消息來源層級**: 政府公衛機構 N / 同儕評審期刊 N / 預印本 N / 企業新聞稿 N / 專家意見 N / 患者訪談 N
**醫學證據稽核**:
- 每項醫學宣稱之證據等級: ✅ / ⚠️ (列出未標的)
- 相對風險 + 絕對風險配對: ✅ / ⚠️ (列出缺項: RR 未伴絕對值、NNT、基礎風險)
- 單一研究 vs 系統性評論: ✅ / N/A / ⚠️
- 95% CI / 不確定性表述: ✅ / ⚠️ (列出未含的宣稱)
**患者隱私檢核**:
- 去識別化: ✅ / ⚠️ (列出仍可追蹤身份的資訊)
- 同意書揭露: ✅ / N/A / ⚠️
**WHO 自殺守則**:
- 適用: N/A / ✅ (已遵守) / ❌ (違反項目)
**利益衝突揭露**:
- 資金來源: ✅ / N/A / ⚠️ (列出未揭露的利益相關)
**待查證事項**: ...
**倫理 / 識讀檢核摘要**: 〔交給 med-news-reporter 的 Step 4-5 footer〕

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Examples

See examples/ directory for:

• sample_input.md — realistic health-news source material (clinical study press release + health authority statement + medical society response + patient anecdote)
• sample_output.md — produced piece + meta footer + skill-trace explanation

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Gotchas

• WHO 自殺報導守則不可選擇遵守: 不報導方法、地點、遺書;必附求助專線(1925);違反導致 copycat 效應(Werther Effect)之文件風險。這是法律 + 倫理 + 公衛的三重義務,不是新聞美學選擇。
• 絕對風險不伴相對風險才是報導失敗: 「某藥物將 X 病死亡風險降低 50%」若不說明基礎風險(例如 1000 人中 4 人 → 2 人),讀者高估臨床意義。必須兩項並列,或都不列。
• 預印本 (preprint) 是非同儕評審版本: medRxiv / bioRxiv 的論文尚未經 peer review,在描述時必須明確標註「未經同儕評審」。發稿前應檢驗是否已正式發表在期刊。
• 單一研究 ≠ 醫學共識: 即使 Lancet 刊登,一篇論文不足以宣稱「科學證明」。需meta-analysis / 多中心驗證或醫學會聲明。LLM 傾向誇大單一研究的通用性。
• NNT 的臨床意義直覺優於百分比: 「需治療 500 人才有 1 人受益」 vs 「療效提升 0.2%」——同一結果,直觀度差異極大。優先用 NNT;若無法計算則注明。
• 製藥/醫療機構資助須在引述時點明: 研究由廠商贊助、醫師兼任產業顧問、醫院銷售新技術——這些利益衝突不揭露等同隱瞞。放在第一次引述該來源時,不要藏在尾註。
• 患者故事去識別化不等於「模糊化」: 「一名 60 歲男性患者 A」≠ 「患者 X 是成功病例」;前者遵守個資法 §72,後者若細節足夠仍可追蹤(就醫時間+地點+罕見疾病組合)。審核時逐項檢驗。
• 疫情数据更新快,引用需註明日期: 「確診人數 X」不標明「截至 4 月 29 日」會在重新整理後過時或誤導。時間戳必要。
• 「治癒率」/ 「完治」/ 「成功率」各有定義: 無定冠詞引用會混淆:是 5 年存活率?完全緩解?部分緩解?必須明確定義或引用原始文件。

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References

File	Purpose	When to read
references/sources_and_beats.md	台灣衛生醫療消息來源、機構、官方資料庫	Step 2 source vetting
references/glossary.md	醫學統計、流行病學、臨床試驗術語對照	When unfamiliar medical terminology appears
references/ethics_and_law.md	PDPA / 醫療法 §72 / 醫療廣告法 / 自殺守則	Step 3 risk check
references/medical_evidence_reading.md	證據等級金字塔、相對風險誤導、P-hacking	Step 1/4 evidence hierarchy
references/risk_communication.md	風險溝通原則、絕對 vs 相對、不確定性表述	Step 4 risk framing

Related skills:

• med-news-reporter — general news workflow (this skill specializes it)
• med-political — health policy & regulatory news
• stat-hypothesis-testing — deeper statistical literacy on RCTs and meta-analyses
• stat-causal-inference — for causation claims in observational studies
• hum-source-criticism — source vetting frameworks

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Limitations

• Does not verify against live clinical trial databases or medical journals. This skill flags claims that need verification; it does not query ClinicalTrials.gov, PubMed, or Cochrane. Editor/user must verify or supply.
• Jurisdictional scope: legal references (PDPA, 醫療法, 醫療廣告法) reflect Taiwan law. For US (HIPAA), EU (GDPR), UK, HK, or PRC contexts, principles still apply but substitution required.
• WHO Suicide Reporting Guidelines apply globally, but enforcement and consequence differ by jurisdiction. Always apply these guidelines regardless of country of publication.
• Statistical literacy: judges poll quality, p-hacking risk, effect-size interpretation — partially covered in references/medical_evidence_reading.md, but for deep methodological critique use stat-hypothesis-testing or grad-survey-design.
• Not a substitute for legal review. Health-news pieces with named patients, drug/treatment criticism, or regulatory disputes should have attorney review before publication.
• Does not generate original reporting. If supplied material is insufficient or contradictory, this skill flags gaps — it will not source additional interviews or find additional studies.