Longitudinal data, which track observations of the same subject over a certain period of time, can be used to measure change. In the healthcare sector, longitudinal data are used to monitor an individual’s health over time, including their risk factors, treatments, and outcomes.
Longitudinal data combine information from sources across a health system, including from claims, devices, genomic information, and electronic medical records (EMRs). A longitudinal patient timeline provides a holistic view of a patient’s medical journey, from birth to death or from admission to discharge, and gives physicians new insights into their patients’ health states at different points in time.
Providers and other healthcare professionals can use longitudinal timelines to make data-driven decisions about patient care, including which treatment options may be the most efficacious for which patient cohorts. Longitudinal data can help a healthcare professional determine:
1. The ideal point in time for a patient to begin receiving a specific type of treatment for a specific disease stage
Some treatments work best when implemented at specific times during the course of a disease. Longitudinal data can show which patients experience the most successful outcomes based on the timing for the treatment administered.
2. Which medication combinations are most effective for certain conditions or diseases
Longitudinal data can provide information on the most successful medication combinations for specific patient cohorts. For instance, if patient cohorts with two comorbid conditions are compared with one another, time-stamped data can help physicians best understand when to add and/or discontinue one or more medications for the most favorable outcome for both conditions.
3. How often a specific patient cohort should schedule follow-up visits for the best outcome
Time-stamped data can show which patient cohorts experience the greatest benefit from follow-up visits and at which points in their disease trajectory follow-up visits are most critical for positive outcomes.
But healthcare professionals often don’t have access to longitudinal patient timelines. Instead, their data is spread out across a health system, disparate and disconnected.
Platforms like MDClone’s ADAMS, though, provide physicians and healthcare professionals with longitudinal patient timelines that they can analyze and use to come up with optimized treatment plans for their patients.
Longitudinal Data with ADAMS
MDClone’s ADAMS Platform enables users to view longitudinal timelines of their patients’ medical histories in a single, easy-to-read application in real time.
Rather than exploring static content, the MDClone ADAMS Platform dynamically stores detailed patient information into a time-stamped format so data is understandable and organized.
The ADAMS Platform ingests time-stamped data from numerous sources, including:
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Demographics
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Procedures & Diagnoses
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Medications
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Physician Notes
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Pathology Reports
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Genetic Markers
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EMR Data
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Device Data
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Claims
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Imaging Results
Exploring longitudinal data with ADAMS can help any user (1) distinguish cause-and-effect situations, (2) find correlation patterns between early-life circumstances and later-life outcomes, and (3) determine how generational, historical, economic, and social determinants affect patients’ health and wellness.
ABOUT THE Platform
The MDClone ADAMS Platform is a self-service data analytics environment that empowers users to quickly organize and access information, accelerate research, drive better patient outcomes, empower healthcare teams to action, and create impactful healthcare innovation.
Put your organization on a continuous learning path with real-time access to insights with our pioneering healthcare data platform that breaks down barriers in data exploration.
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