Definitive Healthcare Features

Data Management (14)

Data Warehouse: Maintain a health care-specific data warehouse that organizes all clinical, operational, financial, and patient data
Data Analysis: Process collected data to pull out relevant insights
Data Capture: Accurately capture and store health care data
Data Integration: Consolidates data from various sources including Electronic Health Records (EHR), billing systems, and patient management systems into a unified platform.
Integration with Wearable Devices: Connects with wearable health devices to capture real-time patient data like heart rate, activity levels, and sleep patterns.
Interoperability: Ensures compatibility with various healthcare systems and standards like HL7, FHIR, and DICOM, facilitating seamless data exchange.
Security and Privacy Controls: Implements data security mechanisms and compliance with regulations like HIPAA to safeguard patient data.
Data Querying: Provides a user-friendly interface to construct custom queries for in-depth data analysis without needing advanced technical skills.
Health Data Exchange: Allows for the exchange, collection, and consolidated storage of health data across multiple clinical systems
Regulation & Compliance: Supports the migration to and ongoing adherance to health care-specific standards like HIPAA (Health Insurance Portability and Accountability Act) and ICD (International Classification of Diseases), and data formats like HL7 (Health Level Seven), NCPDP (National Countil for Presription Drug Programs), and EDI (Electronic Data Interchange)
User Access: Provides the capability to set up and/or restrict user access to stored health data
Data Warehouse: Maintain a health care-specific data warehouse that organizes all clinical, operational, financial, and patient data
Data Analysis: Process collected data to pull out relevant insights
Data Capture: Accurately capture and store health care data

Operations Management (5)

Third-Party Software Integrations: Facilitates effective IT integration between existing health care solutions and new to-be-incorporated applications
System Interoperability: Ensures the communication and connection between multiple, disparate health care solutions to further their effectiveness
Integration Services: Supplies an implementation or optimization service team to streamline the adoption of the integration engine
Interface Status Updates: Analyzes and presents the status of each integration and allocated resource to staff
Operational Support: Supports clinical operations and streamlines clinical workflows

Data Visualization (4)

Insights (5)

Steps to Answer: Requires a minimal number of steps/clicks to explore data and insights for user enquiries.
Data Discovery: Users can drill down and explore data to discover new insights.
Search: Ability to search available data sources to find and discover data and insights.
Collaboration /Workflow: Ability for users to share data and insights (reports, dashboards, etc.) they have built within the tool and outside the tool through other collaboration software or within popular enterprise appications.
Predictive Analytics: Analyze current and historical trends to make predictions about future events.

Data Preparation (4)

Big Data: Ability to handle large, complex, and/or siloed datasets.
Data Transformation: Can read of convert data formats of source data into the format required for the analytics platform without creating data quality issues.
Connectors: Ability to connect the analytics platform with a wide range of connector options for common data sources, including popular enterprise applications.
Data Governance: Connects to enterprise data governance software, or provides integrated data governance features to avoid misuse of data

Data Modeling and Blending (5)

Data Modeling: Ability to (re)structure data in a manner that allows insights to be created quickly and accurately.
Data Querying: Using formulas based on existing data elements, users can create and calculate new field values
Data Filtering: Business users have the ability to filter data in a report based on predefined or automodeled parameters.
Automodeling: Tool automatically suggests data types, schemas and hierarchies.
Data Blending: Allows the user to combine data from multiple sources into a functioning dataset.

Analytic Tools - Healthcare Analytics (6)

Data Visualization: Provides graphical representations of data through charts, graphs, and dashboards to facilitate easier interpretation and decision-making.
Cost Analysis: Evaluates treatment costs, resource utilization, and financial performance to optimize healthcare expenditures.
Real-Time Analysis: Enables the analysis and monitoring of healthcare data as it is generated, allowing timely interventions.
Predictive Analytics: Employs statistical algorithms and machine learning techniques to predict future outcomes based on historical data.
Patient Risk Scoring: Calculates risk scores for patients based on their health data, helping providers identify those who may need urgent care or preventive measures.
Natural Language Processing (NLP): Utilizes NLP to extract meaningful information from unstructured text data, such as clinical notes and patient records.