Significance of Data in Healthcare

"The data is clear: US patients aren’t loyal customers. They split their care across an avg of 4-5 different provider networks each year. To remain competitive, provider orgs must seek to better understand patients as health care consumers: how/why they make decisions, how/where/why they receive care, and how the forces of demand and supply shape their markets. And compete they must. While 44% of Americans have an active Amazon Prime membership—giving Amazon even more consumer data—the US' largest health system, HCA Healthcare, only engages with 1% of Americans. Health systems must take a page from big tech companies’ consumer strategy handbooks—starting with leveraging the right data and establishing the right metrics. One challenge is the very limited nature of info being tracked in this category. Another is that health systems often use the few traditional patient sat measures that do exist (eg NPS and HCAHPS) to project what patients may do in the future—despite being unrealiable indicators. Health system leaders need to look at what patients actually do and incorporate that info into strategic planning accordingly, incl: 1. Consumer Preferences & Proclivities Leading retailers such as Amazon and Walmart have been using data to better understand different customer segments for years and employ those insights to decide on the way in which consumers are served. And consumer packaged goods companies have long relied on psychographic data to better understand consumers and inform their business strategies. Health systems are woefully behind in adopting such data-driven practices, but they must embrace them to compete for patients in the long run. By building a more comprehensive tech infrastructure, health system leaders can devote data-engineering resources to connect patient-healthcare-utilization patterns to behavioral profiles at scale. 2. Share of Care Non-healthcare, consumer-facing orgs do everything possible to understand the economic factors affecting their businesses, incl knowing their TAM, market share for certain services, market value, and how to acquire market share from the competition. Health systems should be doing the same and can look to both internal and external data. Claims clearinghouses can be particularly rich sources of raw data across payers and provider types, and while they lack context w/o layering on consumer data, applying AI algorithms on top of aggregated claims data can help a health system determine its share of care and network integrity. Understanding the TAM and applying patient behavior metrics are also essential for health systems to make strategic investment decisions. Many have invested in specific access points with the notion that these will be a 'front door' to future care needs. Data on the longitudinal patient journey, however, show this is not always true, and knowing this could have a tremendous impact on service line and investment decisions"

Utilizing patient data from sources such as RPM #digitalpathways, #wearables, core personal data, fitness apps, treatment history, and general #healthbehavior can substantially optimize healthcare delivery and create significant value. 💡 Insights into patterns of disease progression and treatment effectiveness enable personalized #pathways and #careplans. 💡Market data can help identify health trends and predict patient needs, facilitating proactive interventions. 💡#Wearables and fitness apps generate real-time health data, enabling continuous monitoring, earlier detection of potential health issues, and timely interventions. 💡Core personal data and treatment history can help identify risk factors and drive preventive care. Integrating and analyzing these diverse data sources can enable a holistic view of a patient’s #healthstatus and behavior. General health behavior data can provide insights into lifestyle factors that impact health outcomes and can be used to encourage healthy habits. For example, tracking a patient's diet, physical activity, and sleep patterns can provide valuable insights into their health and allow for personalized recommendations and interventions. By leveraging comprehensive and timely patient data, healthcare providers can deliver more effective, personalized, and timely care, ultimately improving #patientoutcomes and reducing #healthcarecosts.

TechTarget’s recent article provides a clear overview of eight essential data and coding standards that form the backbone of modern healthcare: HL7, FHIR, ICD‑10, CPT, CCD, CDA, DICOM, and SNOMED CT. These standards aren’t just technical details. They enable everything from interoperability to accurate billing, imaging, and clinical documentation. Key Takeaways -HL7 & FHIR: Core to interoperability. FHIR’s API-based design allows more flexible, real-time data exchange compared to traditional HL7. -ICD‑10 & SNOMED CT: ICD‑10 underpins billing and surveillance; SNOMED CT provides rich clinical detail and maps seamlessly to ICD codes. -CPT: Essential for accurate procedure coding and reimbursement. -CCD & CDA: Support consistent patient summaries and safe transitions of care. -DICOM: The standard ensuring reliable imaging data sharing across systems and devices. Each is important in its own way in leveraging data for better outcomes and patient care. My Perspective Data is everything in modern healthcare. And the quality of data matters even more! Clinicians and students must understand not just what these standards are, but why they’re critical to patient safety, equity, and seamless care coordination. Without high-quality, standardized data, even the best AI tools, EHRs, and analytics fall short. If we want to leverage the AI systems of the future, we need quality and interoperability of our data. https://lnkd.in/eHJvAsc4

Strong data analytics are not just for tech giants or healthcare innovators - they're critical for clinical organizations too. The real value in healthcare lies in data - and how we use it to drive decisions for patient management, operations, and marketing. Entering new reimbursement schemes? Data analytics is key for managing profitable, high-quality patient care. Marketing decisions to clinical outcomes - data empowers all aspects of healthcare to make informed, strategic choices. It's not just about collecting data, but using it effectively to benefit all stakeholders, especially in value-based arrangements. If your organization hasn't embraced data analytics yet, it's time. The next few years will only heighten its necessity and accessibility. Utilize data for everything from clinical decision-making to revenue cycle management. It's the backbone of innovation in healthcare. Remember, data isn't about reducing patients to numbers - it's about enhancing personalized care and achieving better health outcomes. Start with understanding your data to make impactful decisions that improve efficiency, profitability, and most importantly, patient care. #HealthcareAnalytics #DataDriven #ClinicalDecisionMaking #PatientCare #Innovation

The healthcare landscape is evolving rapidly, with Real-World Data (#RWD) and Real-World Evidence (#RWE) leading the transformation. Unlike traditional clinical trials, RWD and RWE offer insights from real-life patient experiences, providing a comprehensive view of treatment effectiveness and safety. 🔍 Key Highlights of the paper by Kelly H. Zou, PhD, PStat, FASA and Marc Berger. - Data Quality Frameworks: Exploring DQFs in the US and EU, focusing on assessment criteria convergence. - Screening Criteria: Criteria for assessing RWD source quality to ensure suitability. - Regulatory Landscapes: Regulatory agencies' role in using RWE for treatment decisions. - Challenges and Opportunities: Addressing data transparency, quality assurance, and sensitive data protection. The potential for enhancing therapeutic strategies and supporting a learning healthcare system through RWD and RWE is significant. Collaboration among healthcare providers, technology firms, regulators, and patients is crucial for establishing a robust RWD and RWE infrastructure. 📚 Citation: Zou, K.H.; Berger, M.L. Real-World Data and Real-World Evidence in Healthcare in the United States and Europe Union. Bioengineering 2024, 11, 784. https://lnkd.in/ewTmNRaK #HealthcareInnovation #RealWorldData #RealWorldEvidence #DataQuality #RegulatoryScience #PatientCare #DigitalHealth #AIinHealthcare

Health devices and apps outside clinical environments are a really innovative area in healthcare right now.   From wearable fitness trackers to remote monitoring tools, patients are generating more health data than ever.   Tapping into these new streams alongside traditional EHR records holds great potential: ✅ Provide a more holistic view of a person's health over time. ✅ Enable early detection of issues based on changes. ✅ Allow physicians to intervene before acute events. ✅ Reduce utilization by addressing small declines before escalation. ✅ Personalize care plans based on individual behaviors and trends.   But it requires thoughtfully bridging siloed data sources into connected insights. Technology needs to integrate device and app data with clinical systems to paint a comprehensive portrait.   Approaching this judiciously based on use cases where it adds high value is key, along with governance to ensure proper data use. But expanding the definition of "patient data" beyond traditional settings offers a fuller understanding of each person.   I'm eager to see how organizations leverage this wealth of information to individualize care in impactful new ways. How could you apply these emerging streams in your healthcare system?   #datagovernance #digitalhealth #ehr

Love & Data: The Data-Driven Future of Healthcare for You & Your Loved Ones I am asked about Data, AI and Healthcare....a lot. As President of the 2nd largest Healthcare Data aggregation company, it is an integral part of daily discussions. If information is power, and data is information, then healthcare data is power personified. And since all 7.8 Billion people on this planet care about their and their families' health, healthcare is central to all. The days of paper-based records and manual processes are quickly giving way to an era that has every piece of healthcare information digitized, accessible, and actionable. The Role of Data in Healthcare: Data is transforming how healthcare is delivered, from improving patient care to redefining drug development processes. It's not just about collecting data; it's about deriving actionable insights that can save lives and drive efficiencies across the healthcare ecosystem. That means your sick child can receive the life saving medicine they need to make them comfortable and healthy. And it means that instead of paper copies of their chart being carried from office to office to hospital to pharmacy to office, the information can be shared across health systems, accelerating timelines and decreasing mistakes. Benefits of Data-Driven Healthcare: Data-driven healthcare leads to more accurate diagnoses, personalized treatment plans and the ability to predict disease outbreaks. Additionally, it can streamline administrative tasks, reduce mistakes, enhance access to best in class treatment options and patient experience. Challenges and Considerations: The path to data-driven healthcare utopia is not without its challenges. Ensuring data privacy and security remains paramount. Additionally, software systems across hospitals and various healthcare providers don't always connect. This means linkages, and longitudinal connections across systems do not happen automatically; errors, imperfections and gaps can occur as a result. Standardized formats and platforms will enhance interoperability among healthcare systems and enhance data quality. In conclusion, data-driven healthcare isn't just a buzzword; it's the future. By harnessing the power of patient data, we have the potential to accelerate the quality of patient care, improve quality of life for loved ones, and help our loved ones and patients who need the best care. #innovation #healthcare #data #dataanalytics #future #VC #venturecapital #futurism

I recently took some lab tests. My HDL level is a little low (always has been), so my physician suggested I need to spend more time in Zone 2 exercise. I'm a runner. Depending on travel and weather, I average 15–20 miles running per week (or more, if I'm training for a race), plus an additional 15+ miles of walking with my dog. I sent screenshots of my activities to my physician and asked what more I should be doing. The response? "Oh, keep doing that." 3 reasons your healthcare provider doesn’t know how healthy you are: 1️⃣ The data lives on your wrist. Apple Watch, Oura, Fitbit, Whoop, CGMs—we're generating real-time insights every day. However, most of that data never reaches your physician. 2️⃣ EHRs are rearview mirrors. They show what happened, not what’s happening. They weren’t built to ingest daily behaviors, trends, or proactive signals. 3️⃣ There's nowhere to put it. Even if your doctor had the time (they don’t), there’s no structured place in the clinical workflow for bringing together and quickly summarizing physical activity, sleep, and glucose trends. Healthcare (not sick care) is a behavioral approach. Personal health data quantifies our everyday behavior. But our healthcare system manages all of us—inclusive of an aging population with an increasing prevalence of chronic conditions—with short visits, static labs, and incomplete health histories. The reality is that those of us tracking our personal health data aren't getting full value from the system. And those of us without access to wearables? They get even less—just a quick physical exam and a best guess. It's not the clinicians' fault. They don't have the time, training, or incentives. We need a healthcare system that values ongoing engagement, prevention, and context. The solution: personal health data with behavioral insights, summarized by AI and embedded in the clinical workflow. Take the cognitive burden off clinicians. Give them context. Help patients and providers work together as a team. We have the sensors. ⌚️ We have the data. 📊 We have the tech. (👋 Validic) Now we need the system to catch up. The leading health systems of the future will utilize behavioral health data from our everyday personal health devices to enhance the quality of care, while also identifying which patients require immediate attention and which ones are doing well. Personal health data can help a health system steer patients in for an ambulatory appointment early, before they end up in the ED or urgent care. Let's build a responsive, proactive health system based on real data and a comprehensive picture of a person's health.

Are we making data work for patients—or letting it gather dust? A few insights to challenge the status quo in medicine: Data in healthcare today: 👉 Vast amounts of health data are collected daily, yet much of it remains underutilized. Imagine the missed opportunities to improve outcomes. 👉 Poor communication of data often leads to confusion, disengagement, or even mistrust—whether it’s among patients, providers, or policymakers. The myths: ❌ “Data speaks for itself.” Not true. Without a clear narrative, even the best insights fall flat. ❌ “Visuals are enough.” Nope. Charts need context. What’s the story behind the trend? Why does it matter? The opportunity: The art of data storytelling can turn numbers into actionable insights: Simplify complex information for faster understanding. Use relatable narratives to connect on a human level. Highlight the real-world impact, not just the stats. The takeaway: Data storytelling isn’t just about presentation—it’s about driving better decisions, fostering trust, and ultimately improving patient care. Are we ready to move beyond raw numbers and start truly leveraging the stories behind the data? Your thoughts?