Importance of Health Data in Policy Making

💡 Digital Patient Engagement – The Missing Link in Regulatory-Grade Real-World Evidence and the NHS 10-Year Plan? New research highlights serious weaknesses in the NHS data ecosystem — and points to the usual unsuspected villain: 🏥 Hospital administrative coding systems that capture data out of context, disconnected from the patient’s lived experience and the public health picture. As digital health gains momentum, one fact is becoming impossible to ignore: how we define and identify patient cohorts matters — not just for research, but for AI 🤖, clinical decision support 🩺, and health policy 📜. 🔍 In this recent study, authors examined how hospital clinical coding (e.g., the NHS Hospital Episode Statistics feed) identifies diabetes in cancer patients — and how those definitions affect survival estimates and clinical decisions. The question is, do the findings surprise us? ⚠️ More pessimistic survival estimates when diabetes was defined via coding alone vs. HbA1c or hybrid approaches. ❌ Entire patient cohorts missed or misclassified, especially in outpatient-heavy specialties. 📉 Commonly used comorbidity scores misrepresenting patient risk when based solely on administrative data. Why it matters: Regulatory-grade RWE depends on accuracy. If the baseline definitions are wrong — even in the NHS England Secure Development Environment — then AI models, clinical decisions, and policy strategies risk being built on shaky foundations. Globally, and especially in more economically developed countries, ageing populations are living longer with significant health problems. Multi-morbidity is therefore becoming a critical focus for both clinical care and research. The way forward: We must move beyond hospital coding alone. A connected, open, patient-centred digital ecosystem 🌐 — integrating telehealth 📱, diverse data sources 🗂️, and the lived patient experience 👥 — can: ✅ Improve comorbidity identification. ✅ Strengthen evidence for policy and regulation. ✅ Make RWE more meaningful and trustworthy. 💬 Digital patient engagement isn’t just about better care — it’s a regulatory evidence generation pathway. Zucker, K., McInerney, C., Glaser, A. et al. Why NHS hospital co-morbidity research may be wrong: how clinical coding fails to identify the impact of diabetes mellitus on cancer survival. Br J Cancer (2025). https://lnkd.in/dRvQqsQU #DigitalHealth #RWE #AI #HealthDataQuality #HealthDataReliability #AIinHealthcare #Telehealth #HealthData #NHS #HealthPolicy #PatientEngagement #HealthcareInnovation

‎Imagine being 15 years old and already knowing the layout of a hospital better than your school. ‎ ‎For many young people living with 𝗦𝗶𝗰𝗸𝗹𝗲 𝗖𝗲𝗹𝗹 𝗗𝗶𝘀𝗲𝗮𝘀𝗲 (𝗦𝗖𝗗), this isn’t imagination: it’s reality. ‎ ‎Every crisis feels like a battle against pain, every hospital visit a test of resilience. Yet behind every data point is a child, a family, and a care team doing their best to turn pain into progress. ‎ ‎As someone passionate about using data for better health outcomes, I wanted to understand this journey, not just in numbers, but to tell their story through data. ‎ ‎So I built a 𝗦𝗶𝗰𝗸𝗹𝗲 𝗖𝗲𝗹𝗹 𝗗𝗶𝘀𝗲𝗮𝘀𝗲 𝗖𝗹𝗶𝗻𝗶𝗰 𝗘𝗻𝗰𝗼𝘂𝗻𝘁𝗲𝗿𝘀 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱, designed to help providers, researchers, and policymakers see the story behind every data point. ‎ ‎ ‎𝗪𝗵𝗮𝘁 𝗪𝗲 𝗔𝗹𝗿𝗲𝗮𝗱𝘆 𝗞𝗻𝗼𝘄 𝗔𝗯𝗼𝘂𝘁 𝗦𝗖𝗗: ‎ ‎• It’s a genetic disorder that distorts red blood cells, leading to blockages, pain, and recurrent crises. ‎• Most patients are diagnosed in early childhood, requiring lifelong management. ‎• The disease burden is highest in sub-Saharan Africa, where early detection and consistent care are still limited. ‎• Yet, evidence shows early diagnosis and outpatient management significantly improve survival and quality of life. ‎ ‎ ‎𝗞𝗲𝘆 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: ‎ ‎☑️ 65% pediatric, average age 15, showing consistent clinic engagement. ‎☑️ 80% have experienced crises, with lowest hemoglobin in children under 10. ‎☑️ Outpatient care delivers better hemoglobin and oxygen outcomes, while ER visits record the highest pain levels. ‎☑️ 49% improved hemoglobin and 97% clinical stability despite 51% repeat admissions. ‎ ‎The dashboards I built turn those numbers into a narrative: 𝘸𝘩𝘰 𝘵𝘩𝘦 𝘱𝘢𝘵𝘪𝘦𝘯𝘵𝘴 𝘢𝘳𝘦, 𝘩𝘰𝘸 𝘵𝘩𝘦𝘪𝘳 𝘤𝘰𝘯𝘥𝘪𝘵𝘪𝘰𝘯𝘴 𝘦𝘷𝘰𝘭𝘷𝘦, 𝘸𝘩𝘦𝘳𝘦 𝘤𝘢𝘳𝘦 𝘪𝘴 𝘮𝘰𝘴𝘵 𝘦𝘧𝘧𝘦𝘤𝘵𝘪𝘷𝘦, 𝘢𝘯𝘥 𝘸𝘩𝘦𝘵𝘩𝘦𝘳 𝘰𝘶𝘳 𝘪𝘯𝘵𝘦𝘳𝘷𝘦𝘯𝘵𝘪𝘰𝘯𝘴 𝘢𝘳𝘦 𝘵𝘳𝘶𝘭𝘺 𝘤𝘩𝘢𝘯𝘨𝘪𝘯𝘨 𝘰𝘶𝘵𝘤𝘰𝘮𝘦𝘴 𝘰𝘷𝘦𝘳 𝘵𝘪𝘮𝘦. ‎ ‎ ‎𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿𝘀: ‎ ‎✅ 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗔𝗱𝗺𝗶𝗻𝗶𝘀𝘁𝗿𝗮𝘁𝗼𝗿𝘀: Strengthen outpatient and community-based programs to reduce emergency visits and enhance patient stability. ‎✅ 𝗖𝗹𝗶𝗻𝗶𝗰𝗶𝗮𝗻𝘀: Prioritize early interventions for children under 10 ‎✅ 𝗣𝘂𝗯𝗹𝗶𝗰 𝗛𝗲𝗮𝗹𝘁𝗵 𝗟𝗲𝗮𝗱𝗲𝗿𝘀: Expand carrier screening, premarital testing, and genetic counseling to prevent new SCD births. ‎✅ 𝗣𝗼𝗹𝗶𝗰𝘆𝗺𝗮𝗸𝗲𝗿𝘀 & 𝗗𝗼𝗻𝗼𝗿𝘀: Invest in data systems and sustainable telehealth models ‎ ‎ ‎Every data point is more than a metric: it’s someone’s child, someone’s hope, someone’s fight to live well. ‎ ‎And if we keep listening to what the data tells us, we can build a future where fewer children are born with SCD: and those who are, live stronger, longer, and freer. ‎ ‎#Healthcare #SickleCellAwareness #PublicHealth #HealthcareAnalytics #HealthTech #SickleCell #PublicHealth #GeneticCounseling #Datafam #Excel

The World Health Organization World Health Statistics 2026 report is out — and for anyone working in global health policy, the headline is uncomfortable: with fewer than 5 years to 2030, not a single health-related SDG target is on track at the global level. A few findings that should be shaping policy conversations right now: → The COVID-19 pandemic erased nearly a decade of gains in life expectancy by 2021. Recovery has been uneven — the Americas have yet to fully recover their healthy life expectancy, and the gap persists for higher-income countries. → Progress on Universal Health Coverage has slowed by two-thirds compared to 2000–2015. Around 1.6 billion people are living in poverty — or pushed into it — because of out-of-pocket health expenses. → Malaria is moving in the wrong direction, up 8.5% since 2015. Meanwhile, funding cuts now threaten the hard-won gains against HIV and TB. → Official development assistance for health was estimated to be 30–40% lower in 2025 than in 2023. The report documents the real-world consequences: job losses among health workers, disrupted training, and anticipated recruitment crises in 69% of surveyed low- and lower middle-income countries. → The data crisis is as serious as the health crisis. Of an estimated 61 million global deaths in 2023, only 12 million had meaningful cause-of-death information. One third of countries still meet WHO standards for high-quality mortality data. You cannot fix what you cannot measure. The report's framing is important: these are not just statistics. They reflect policy choices — about financing, about data investment, about what we treat as urgent. The SDG period ending without meeting its health targets is a policy failure, not an inevitability. #GlobalHealth #HealthPolicy #SDGs #UHC #WHO #PublicHealth #HealthFinancing #HealthData

If you cannot clearly distinguish prevalence from incidence, you are not yet making fully informed public health decisions. Prevalence gives us a snapshot—the total burden of disease at a given point in time. It answers: How widespread is the condition? Incidence, on the other hand, provides a dynamic lens—capturing new cases over a defined period. It answers: How fast is the disease spreading? Why does this matter? Because effective policy, resource allocation, and intervention design depend on interpreting both metrics together, not in isolation. A high prevalence with low incidence may signal improved survival or chronicity. A low prevalence with rising incidence may indicate an emerging public health threat. As epidemiologists and public health practitioners, our strength lies not just in measuring disease—but in translating these metrics into actionable insight. Data doesn’t save lives. How we interpret and act on it does. #PublicHealth #Epidemiology #DataDriven #GlobalHealth #HealthSystems #EvidenceBasedPolicy

🔥 European Medicines Agency - mHealth data for real world evidence in regulatory decision making 📢 This expert report prepared within the context of the Big Data Steering Group of the European Medicines Agency and Heads of Medicines Agencies reviews relevant literature related to the use of mHealth data in the context of medicine regulation and aims to discuss its utility for regulatory uses. While mHealth tools can also be used during clinical trials, this report focuses on their use in real-world settings (i.e. in clinical care or the daily life of patients), to generate RWE for regulatory decision-making. 🚀 mHealth data was found to be useful for EU medicine regulation in three domains: 🔹 to support planning and validity of applicant studies (design & feasibility, representativeness & validity) 🔹 to support the understanding of clinical context (disease epidemiology, clinical management, drug utilisation) 🔹 to investigate associations of products on safety and efficacy outcomes and impacts of regulatory actions (effectiveness & safety studies, impact of regulatory actions) 🐸 Obviously, challenges will need to be overcome: 🔹 Data protection, accessibility and a complex regulatory landscape were identified as main operational challenges. 🔹 In terms of technical challenges, mHealth data quality can suffer from environmental conditions, the accuracy and placement of sensor and ability of patient to use the tool correctly. Interoperability of mHealth data is impacted by the different data sharing standards used by device developers and the sometimes unstructured and unlabelled data sets. 🔹 Several methodological challenges must be considered when using mHealth data. 🔹 Younger and wealthier populations are more likely to frequently use digital devices to measure their health, raising issues around the representativeness of mHealth data, although at the same time it may be useful for collecting more complete data from specific populations. 👣 In conclusion EMA is considering following points for future action: 1. Leverage work on patient experience data and expedite access to mHealth data 2. Increase discoverability of data sources and studies using mHealth data 3. Ensure compliance with data protection and ethical use of mHealth data 4. Engage and collaborate with all actors and relevant initiatives in the healthcare sector 5. Engage with EU and international standards for mHealth data 6. Increase the understanding and tracking of the use of mHealth data in EU Medicine Regulation 7. Support the development of mHealth derived measures to meet regulatory standards #digitalhealth #mhealth #rwe #interoperability #dataprotection

(HiAP) Health in All Policies: Explained & Why Every Government Needs It 🌍 ⁉️ Every decision a government makes affects public health from transport to housing, education, or corporate regulation That’s where Health in All Policies (HiAP) comes in: a strategy to embed and attach health considerations into every sector of government not just health ministries. 🔹 What is HiAP? HiAP is a policy approach where all government decisions are assessed for their health and equity impact. Because health is shaped by far more than hospitals: → Safe roads reduce injuries → Clean air and water prevent disease → Quality education improves lifelong wellbeing → Affordable housing supports physical and mental health Without HiAP, policies can unintentionally harm health. With HiAP, they actively improve it. 🌍 Who’s Doing It? Several countries have embedded HiAP through formal governance structures: • 🇫🇮 Finland • 🇸🇦 Saudi Arabia • 🇦🇺 Australia • 🇰🇷 South Korea They bring together transport, education, urban planning, finance, and health at the same table. Health should influence every department not just the Ministry of Health. 🔹 Why Do Governments Need HiAP? Almost every sector shapes health outcomes. Here's how: Transport ↳ Safer roads and speed limits reduce injuries ↳ Efficient Public transport lowers pollution and disease risk ↳ Walkable cities boost physical and mental health Education ↳ Healthy meals and physical activity support development ↳ Health education empowers better decisions ↳ Safe schools reduce injury and absenteeism Housing & Urban Planning ↳ Better ventilation and sanitation reduce infections ↳ Green spaces support mental wellbeing ↳ Affordable housing improves health equity Workplaces & Corporate Policies ↳ Safe working conditions reduce illness ↳ Mental health support boosts productivity ↳ Wellness programs lower absenteeism 🔹 Key Strategies That Make HiAP Work → Health Impact Assessments before policies are approved → Cross-sector collaboration between ministries → Public engagement in policymaking → Evidence-based decisions supported by data and research teams → Accountability mechanisms to track health outcomes 🔹 The Economic & Social Payoff • Lower healthcare costs through prevention • Higher productivity and fewer sick days • Reduced inequalities between communities • Improved quality of life • More efficient, coordinated governance Example: Countries that invest in early childhood education, school meals, and safe playgrounds see healthier children, better academic performance, and a more productive workforce. Bottom Line Health is everyone’s business. If we want healthier nations, we must design healthier policies. #HiAP #PublicHealth #Policy #HealthSystems #Epidemiology #QualityOfLife

We are sounding the alarm on an urgent threat to evidence-based policymaking. With the elimination of the 17 people running the National Survey on Drug Use and Health (NSDUH), we will lose up-to-date information on tobacco, alcohol, and drug use, mental health, and other health-related issues in the United States. This irreplaceable national survey is our only comprehensive window into substance use across America. Without it, researchers will be unable to track trends, identify emerging issues, or use reliable data to evaluate the impact of interventions, leaving policymakers to navigate a national crisis completely blind. This devastation extends beyond NSDUH. All population-based studies conducted by the Department of Health and Human Services face imminent threat. Why should this concern every American? These studies form the scientific foundation for improving health outcomes and saving lives nationwide. Consider Alzheimer's Disease, which devastates millions of Americans and their families. Early detection through population-based surveys is dramatically more cost-effective than clinical assessments yet provides powerful insights for identifying risks. These surveys drive prevention strategies that both save lives and reduce the enormous financial burden of care, a burden that falls on patients and their loved ones. The recent funding cuts eliminate these opportunities at precisely the wrong moment. My colleague Tristanne Staudt, Executive Director of the American Association of Public Opinion Research (AAPOR), joins me in demanding immediate government action to restore these critical data collection capabilities. As of this moment, though the support at SAMHSA is gone, the research contract is still in place. It is crucial that this contract is not terminated. For our colleagues outside of the federal government, we urge you to contact your legislators today with this message: Eliminating these research tools directly undermines our ability to protect public health efficiently and effectively. The cost of this data is minimal; the cost of flying blind is immeasurable. #DataInfrastructure #CountOnStats Tristanne Staudt, MBA Frauke Kreuter Steve Pierson https://lnkd.in/eZ-J4Ut8

Most People and policymakers still think #health is just the Ministry of Health Saudi Arabia 's job. That's why we keep treating symptoms instead of causes. Think about this: transport #policy determines if people can walk safely. Education shapes health literacy. Housing affects mental wellbeing. Economic policy controls access to healthy food. and the others that interact with social determinants of health. Every policy is a health policy, whether we acknowledge it or not. Health in All Policies (HiAP) isn't a new bureaucratic layer. It's a practical framework to ensure we consider health impacts before policies are locked in, not after damage is done. Saudi Arabia recognized this early. A Royal Decree established the Ministerial Committee for Saudi Health in All Policies (HiAP), bringing together over 11 ministries—from Education and Labor to Housing and Environment. The results? Tangible wins like reducing salt consumption to combat hypertension and cardiovascular disease. This wasn't just policy talk; it was coordinated action across sectors. I've mapped out 6 critical steps. for you to understand and to think of HiAP in your organization: Understanding → Know what HiAP actually means beyond the buzzword Political Will → Build the case with evidence, not just passion Governance → Create structures that actually have decision-making power Stakeholders → Engage sectors early, not as an afterthought Tools → Use practical frameworks like Health Impact Assessments and Sustainability → Institutionalize it so it survives leadership changes. The game changer? Starting small. Pick one sector with existing goodwill, maybe education or transport prove the value, then scale. Saudi Arabia's approach shows that when you combine high-level political commitment with cross-sectoral collaboration, HiAP moves from concept to reality.