Definitive Healthcare Features
What are the features of Definitive Healthcare?
Data Management
- Data Analysis
- Data Capture
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Definitive Healthcare Categories on G2
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Data Management
Data Warehouse | Maintain a health care-specific data warehouse that organizes all clinical, operational, financial, and patient data | Not enough data | |
Data Analysis | Process collected data to pull out relevant insights This feature was mentioned in 11 Definitive Healthcare reviews. | 89% (Based on 11 reviews) | |
Data Capture | As reported in 11 Definitive Healthcare reviews. Accurately capture and store health care data | 89% (Based on 11 reviews) | |
Data Integration | Consolidates data from various sources including Electronic Health Records (EHR), billing systems, and patient management systems into a unified platform. | Not enough data | |
Integration with Wearable Devices | Connects with wearable health devices to capture real-time patient data like heart rate, activity levels, and sleep patterns. | Not enough data | |
Interoperability | Ensures compatibility with various healthcare systems and standards like HL7, FHIR, and DICOM, facilitating seamless data exchange. | Not enough data | |
Security and Privacy Controls | Implements data security mechanisms and compliance with regulations like HIPAA to safeguard patient data. | Not enough data | |
Data Querying | Provides a user-friendly interface to construct custom queries for in-depth data analysis without needing advanced technical skills. | Not enough data | |
Health Data Exchange | Allows for the exchange, collection, and consolidated storage of health data across multiple clinical systems | Not enough data | |
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) | Not enough data | |
User Access | Provides the capability to set up and/or restrict user access to stored health data | Not enough data | |
Data Warehouse | Maintain a health care-specific data warehouse that organizes all clinical, operational, financial, and patient data | Not enough data | |
Data Analysis | Process collected data to pull out relevant insights | Not enough data | |
Data Capture | Accurately capture and store health care data | Not enough data |
Operations Management
Third-Party Software Integrations | Facilitates effective IT integration between existing health care solutions and new to-be-incorporated applications | Not enough data | |
System Interoperability | Ensures the communication and connection between multiple, disparate health care solutions to further their effectiveness | Not enough data | |
Integration Services | Supplies an implementation or optimization service team to streamline the adoption of the integration engine | Not enough data | |
Interface Status Updates | Analyzes and presents the status of each integration and allocated resource to staff | Not enough data | |
Operational Support | Supports clinical operations and streamlines clinical workflows | Not enough data |
Data Visualization
Reports | User interface for standard and self-service reports is intuitive and easy to use. | Not enough data | |
Graphs and Charts | Offers a variety of graph and chart formats for visualzation of data. | Not enough data | |
Score Cards | Score cards visually track pre- and user-defined KPIs. | Not enough data | |
Dashboards | Provides business users an interface to easily design, refine and collaborate on their dashboards | Not enough data |
Insights
Steps to Answer | Requires a minimal number of steps/clicks to explore data and insights for user enquiries. | Not enough data | |
Data Discovery | Users can drill down and explore data to discover new insights. | Not enough data | |
Search | Ability to search available data sources to find and discover data and insights. | Not enough data | |
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. | Not enough data | |
Predictive Analytics | Analyze current and historical trends to make predictions about future events. | Not enough data |
Data Preparation
Big Data | Ability to handle large, complex, and/or siloed datasets. | Not enough data | |
Data Transformation | Can read of convert data formats of source data into the format required for the analytics platform without creating data quality issues. | Not enough data | |
Connectors | Ability to connect the analytics platform with a wide range of connector options for common data sources, including popular enterprise applications. | Not enough data | |
Data Governance | Connects to enterprise data governance software, or provides integrated data governance features to avoid misuse of data | Not enough data |
Data Modeling and Blending
Data Modeling | Ability to (re)structure data in a manner that allows insights to be created quickly and accurately. | Not enough data | |
Data Querying | Using formulas based on existing data elements, users can create and calculate new field values | Not enough data | |
Data Filtering | Business users have the ability to filter data in a report based on predefined or automodeled parameters. | Not enough data | |
Automodeling | Tool automatically suggests data types, schemas and hierarchies. | Not enough data | |
Data Blending | Allows the user to combine data from multiple sources into a functioning dataset. | Not enough data |
Analytic Tools - Healthcare Analytics
Data Visualization | Provides graphical representations of data through charts, graphs, and dashboards to facilitate easier interpretation and decision-making. | Not enough data | |
Cost Analysis | Evaluates treatment costs, resource utilization, and financial performance to optimize healthcare expenditures. | Not enough data | |
Real-Time Analysis | Enables the analysis and monitoring of healthcare data as it is generated, allowing timely interventions. | Not enough data | |
Predictive Analytics | Employs statistical algorithms and machine learning techniques to predict future outcomes based on historical data. | Not enough 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. | Not enough data | |
Natural Language Processing (NLP) | Utilizes NLP to extract meaningful information from unstructured text data, such as clinical notes and patient records. | Not enough data |
