From Basics to Breakthroughs – Clinical Data Explained

Unlocking the Power of Patient Information

Ever wonder what fuels the cutting-edge advancements in healthcare today? It’s clinical data—the electronic health information collected during every patient interaction. From electronic health records (EHRs) to lab results and imaging data, clinical data is the emerging powerhouse driving innovation in the medical field. Unlike claims data, which is primarily about billing, clinical data provides a rich, detailed picture of patient health. This treasure trove of information enables healthcare experts to conduct advanced research, perform insightful analytics, and engage in real-time patient outreach. By harnessing the full potential of clinical data, healthcare systems can revolutionize patient care, streamline operations, and propel groundbreaking medical research. Dive in with us as we explore why clinical data is truly the backbone of modern healthcare innovation.

Understanding Clinical Data in 60 seconds

• Clinical Data Defined: Clinical data is electronic health information from patient interactions, including Electronic Health records (EHRs), lab results, and imaging – some structured and searchable, and unstructured.
• Significance: Having access to a complete patient history takes research and analytics beyond the small scope of dated claims data, and real-time data access enables patient outreach for those who need it most.
• Completeness: Clinical data is more comprehensive than claims data.
• Timeliness: Claims data is usually 90 – 120 days after the fact, whereas Clinical data is “near real-time”
• Challenges to unlock the value:
  • Often optimized for clinical operations, not patient care.
  • Legacy formats and data silos create challenges for accessing valuable information.
  • Large amounts of data come with noise; it’s crucial to sift through it to find valuable insights
  • Electronic health records have their limits, and the generated summary records may leave parts out.
• Solutions: New technologies are helping overcome these challenges and unlocking the value of clinical data.
• Purpose of Clinical Data Explained Series: To provide a comprehensive understanding of clinical data’s role in transforming healthcare.

Clinical Data Defined

Let’s dive into what makes up the lifeblood of healthcare today: clinical data. This is the treasure trove of health information gathered from every encounter a patient has with the healthcare system, capturing everything from medical histories and lab tests to imaging results, prescriptions, and treatment plans. Like most data sources, clinical data can be categorized into two main types: structured and unstructured.

• Structured Data: consists of neatly organized information, such as lab test results and vital signs, stored in specific, regulated fields within electronic health records (EHRs). While it is more easily searchable and plays a crucial role in generating statistics, spotting trends, and monitoring patient health, structured data still requires significant work to clean and consolidate.
• Unstructured Data: is where the narrative magic happens. It includes detailed descriptions found in clinical notes, medical records, and imaging reports. Unstructured data is a bit of a wild card—diverse and lacking uniformity. It often requires advanced technology to extract meaningful insights. 

Both structured and unstructured data are indispensable for making informed healthcare decisions, tailoring personalized care, and boosting research and operational efficiency.

Structured Clinical Data

• Electronic Health Records (EHRs): Picture a digital vault where elements like medical history, diagnoses, medications, treatment plans, immunization dates, allergies, and lab results are stored for quick reference by healthcare providers. It’s all of the information that a provider has collected about their patients in one place – including everything from insurance information to doctors notes. Some EHR record for a patient will exist at every healthcare facility they have ever visited – like breadcrumbs across the healthcare landscape.
• Lab Results: These are the quantitative results from blood tests, biopsies, and other diagnostics that provide crucial insights into a patient’s health status.
• Vital Signs: Systematically recorded in EHRs, these include essential metrics like blood pressure, heart rate, oxygen level and temperature—key indicators of a patient’s current health.
• Wearable Device Data: This data almost always fits into the vital-signs category, but the volume of data is significantly more than measurements at the doctor’s office (Heart Rate every minute versus every 6 months). Wearables data fills in the gaps between doctor visits and often provides a more accurate picture of health.
• Medications: The list of current and past medications is crucial to understanding a patient’s current condition and preventing drug interactions or duplicating therapies. The medication list should also include dosages and instructions for taking the medication.
• Conditions: These are the list of conditions that a patient has been diagnosed with at any point. These can include anything from chronic conditions like diabetes to risk predictors like sleep apnea.
• Procedures: These are the things that have been done to a patient, including serious things like surgeries, as well as the patient’s last mammogram.
• Allergies: Allergies are crucial to ensure that no patient is exposed to allergic reactions from medications or more benign intolerances to things like latex
• Family History: Knowing that a patient’s close family members suffered from serious conditions like heart failure or diabetes influences a providers treatment plan.

Unstructured Clinical Data

• Progress Notes: These narrative descriptions capture the nuances of medical records and clinician observations, offering a rich context for patient care.
• Plan of Care: Most patients leave an appointment with a list of instructions to follow after the doctor visit. These instructions provide insight into the intentions of doctors and then can be compared to the actual behavior of the patient.
• Wearable Device Data: While most wearable devices are used for vital signs, narrative insights or logs from fitness trackers often fall into the unstructured category. While wearables data is ubiquitous in sports medicine, it has yet to penetrate primary care.
• Imaging Reports: The interpretations of X-rays, MRIs, CT scans, and ultrasounds provide a visual narrative of what’s happening inside the body.
• Patient-Reported Outcomes: This is the subjective data that patients share about their health status, either during an office visit, portal message, or survey. Which adds a personal dimension to clinical assessments.
• Genetic Information: While some genetic data can be structured, the narrative reports and interpretations often remain unstructured.

Each type of clinical data is a vital piece of the healthcare puzzle, contributing to a comprehensive view of patient health. Structured data is your go-to for quick searches and statistical analysis, while unstructured data requires a bit more finesse, with data platforms helping uncover those hidden insights.

Unlocking the Value of Clinical Data

It’s time to discover how this treasure trove locked way in legacy systems and data silos, can truly transform healthcare. Clinical data is not just about collecting information—it’s about leveraging that data to drive impactful change in patient care and operational efficiency.

• Data-driven Decision-Making: With comprehensive clinical data filling in the patient story, healthcare providers can make informed decisions, ensuring continuity and quality of care.
• Proactive Health Management: Lab results offer precise diagnostics and monitoring, allowing for timely interventions and personalized treatment plans.
• Personalized Medicine: Detailed patient data opens the door to a level of personalization in healthcare that is common place in other industries.
• Holistic Patient Insights: Genetic, behavioral health data, patient surveys, and wearable data offer a complete picture of patient health, enabling proactive and personalized care strategies.

The key to unlocking this potential lies in consolidating chaotic data sources, normalizing the inconsistencies, and extracting insights from the unlocked unstructured data. Narrative information from clinical notes, imaging reports, and patient feedback is rich with context but often underutilized due to its complexity. Clinical data platforms can add structure to these narratives, allowing for keyword searching and extraction of valuable insights.

Turning clinical data into actionable insights is a game-changer, transforming perceived barriers into opportunities for innovation, efficiency, and personalized patient care. The value isn’t just in the data itself, but in how we unlock and apply it to revolutionize healthcare.

The Power of Combining Claims and Clinical Data

• If you’re accustomed to the neat and tidy world of claims data, you might not realize the untapped potential lying within clinical data. Claims data is the financial backbone of healthcare, crucial for billing, reimbursement, and cost management, providing a clear record of who received what treatment and when. Yet, it primarily focuses on billing and often lags 90 – 120 days behind actual patient care events, limiting its scope for real-time decision-making.
• Now, imagine unlocking a treasure trove of detailed health information through clinical data. This data captures the nuances of patient interactions, offering real-time insights that claims data simply can’t provide. Clinical data is essential for advanced research and risk analytics, offering a comprehensive view of patient health that enables precise predictions and personalized care strategies.
• With new technologies, the value of clinical data is no longer trapped in complexity. These innovations allow for the seamless integration and analysis of clinical data, opening up new opportunities to enhance patient care and operational efficiency. By combining the financial insights of claims data with the rich, real-time wisdom of clinical data, healthcare IT can elevate their analytics, innovate, and improve risk stratification. Together, they open the door to a future where patient care is more informed, precise, and effective than ever before.

From Data to Decisions

• Comprehensive Insight: Clinical data provides a detailed view beyond claims data, essential for informed decision-making.
  Use Case: A healthcare provider uses comprehensive clinical data to understand the full patient story, enabling providers to see patients as more that a number.
• Technological Advancements: New technologies unlock the full patient context for advanced analytics and research.
  Use Case: A population health researcher employs a clinical data platform to extract key words from clinical notes, to gain insight beyond the limits of claims
• Operational Efficiency: Clinical data streamlines intake procedures with review of summarized history, instead of manual inquiry and supports digital transformation by taking the patient context into account.
  Use Case: A clinic expedites onboarding of new patients by retrieving patient histories digitally in minutes (say goodbye to fax machines)
• Strategic Data Utilization: Overcoming legacy formats and data silos transforms data into actionable insights.
  Use Case: A healthcare IT team integrates disparate data sources into a unified platform for a longitudinal patient record.

Clinical data is transforming healthcare by turning raw information into powerful insights that drive decision-making. As we unlock its full potential, we stand on the brink of a future where healthcare is not only more innovative but truly patient-centered. Are we ready to embrace this transformation?

Next, learn about what is driving healthcare innovation…

Stay tuned for the next article, where we will delve into the importance of clinical data in driving healthcare innovation, exploring its role in advancing patient care, research, and operational improvements.