Real-World Data

UNMATCHED DATA GRANULARITY

30 Years of Health Data Across 20 Global Sites

Unlock a diverse population of data from large health systems, health maintenance organizations, and research organizations from across the United States, Canada, and Israel. Organized longitudinally with significant granularity, the available patient data date back as far as 30 years. Data include:

• Demographics

• Procedures

• Diagnoses

• Lab Results

• Medications

• Physician Notes

• Pathology Reports

• Patient Surveys

• Genetic Markers

• Imaging Results

• Utilization and Cost Data

• Social Determinants of Health

• Administrative Documentation

Connected Data for More Accurate Data Analysis

The influx of healthcare data is continuous, detailed, and difficult to consolidate into one, easy-to-view summary. With the Connect Platform, data are identified continuously, sorted appropriately, and organized longitudinally so administrators, clinicians, and researchers can dive into the information they need to find the insights that impact important discoveries for patient care.

The use of computers, mobile devices, wearables, and other biosensors to gather and store huge amounts of health-related data has been rapidly accelerating. These data carry the potential to improve the design and conduct of clinical trials and studies in the healthcare setting to answer questions previously thought infeasible.

MDClone’s ability to organize vast amounts of continuous data from health systems permits life science organizations to generate specific study designs.

Historically, it takes weeks, months, or even years to manually process charts, reviewing and transcribing notes and other unstructured clinical documentation.

MDClone’s powerful natural language processing engine is able to create structured data from unstructured sources such as physician notes. The conversion to structured data enables queryable formats for research.

Most data available outside of the health system are aggregated, with a data model applied that restricts which elements can be extracted. 

MDClone ingests and maintains all data elements – all labs, vitals, and medications – to enable any question to be explored. With a longitudinal organization and a semantic framework, these elements are presented in the right context and are easily identified during analysis.

From inpatient to outpatient settings, patient information is often siloed, even within hospitals and clinics. Data are often not shared between entities, limiting the view of an entire patient journey.

MDClone’s ability to connect data from different healthcare organizations helps to build a complete patient history. From medications prescribed to lab tests performed, data provide stories that complete the picture for more accurate data analysis.