---
title: VisualMed | Healthcare Data Visualization | FxMed Research
description: Learn how FMRTC is leading efforts to create a new high-tech, data-driven, chronic illness care ecosystem.
---

# Transforming Chronic Illness Care With a New Data-driven Ecosystem

As part of our commitment to funding groundbreaking research and providing life-changing treatment, we are building a brand new data-driven ecosystem.

VisualMed, our chronic illness management platform, will be incorporated into all of our current and future programs. It will use patient-reported data and high-tech tools and wearables to optimize patient care and aid ongoing research into chronic illness.

![data-viz-image-1-960x800](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/data-viz-image-1-960x800.jpg)

## Our Process for Data Visualization

![patient-doctor](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/fxmed-assets/icons/dark/patient-doctor.svg)

### Manage patient care in real-time

![magnify-data](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/fxmed-assets/icons/dark/magnify-data.svg)

### Optimize chronic illness treatments

![holding-lightbulb](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/fxmed-assets/icons/dark/holding-lightbulb.svg)

### Drive forward future research

### Manage patient care in real-time

By recording symptoms, treatments and ancillary data, VisualMed will allow patients and doctors to collaborate in real-time. It will enable us to better track fluctuating symptoms, help inform disease trajectory, and closely monitor a patient’s recovery.

![patient-doctor](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/fxmed-assets/icons/dark/patient-doctor.svg)

![data-viz-image-4-600x500](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/data-viz-image-4-600x500.jpg)

### Optimize chronic illness treatments

Adjustments to a patient’s care plan often only happen when they meet with their doctor, face-to-face. Since all patient data is recorded in VisualMed, doctors can analyze progress and adjust treatments whenever necessary. In addition, with improved visibility on illness trajectory and outcomes, we will be able to better understand which treatments are effective and for whom. 

![magnify-data](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/fxmed-assets/icons/dark/magnify-data.svg)

![data-viz-image-3-600x500](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/data-viz-image-3-600x500.jpg)

## Drive forward future research

The data captured by VisualMed will be used to track trends, inform best practices, and determine the most effective treatment paths for patients. It will also become available to other health practitioners to aid in the wider research, prevention, and treatment of chronic illness.

![holding-lightbulb](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/fxmed-assets/icons/dark/holding-lightbulb.svg)

![data-viz-image-4-600x500](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/data-viz-image-4-600x500.jpg)

## Help us transform lives

Support the development of this brand new care ecosystem by making a donation today.

[Donate Now](https://www.fxmedresearch.org/donate?hsLang=en)

## Data Visualization Resources

[![](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/digitalgov-logo-350x150.png)

Organization Link

### Academy Health HealthEquity Data Jam Winner 2022

Learn More 

](https://digital.gov/2019/03/18/deep-dive-on-top-health-data-technology-innovation-for-lyme-disease/)

[![](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/clyme-health-new-1-350x150.png)

Organization Link

### Clyme Health

Learn More 

](https://www.clymehealth.com/)

[![](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/nick-jio-oel-by-1-ph-pf-y-unsplash-350x150.jpg)

Information

### Snyder Lyme Wearable Study

“Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information”

Learn More 

](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5230763/)

[![](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/long-covid-image-1-1-960-x-800-350x150.jpg)

Information

### Ben Smarr COVID Oura TemPredict Studies

“Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study”

Learn More 

](https://pubmed.ncbi.nlm.nih.gov/35236896/)

[![](https://5714482.fs1.hubspotusercontent-na1.net/hubfs/5714482/covid-600-x-500-350x150.jpg)

Information

### Jennifer Radin COVID Research

“Wearable sensor data and self-reported symptoms for COVID-19 detection”

Learn More 

](https://www.nature.com/articles/s41591-020-1123-x)

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