The tremendous challenge of improving healthcare outcomes has become dependent upon creating, curating, managing, cleaning, and delivering data. To maintain the forward momentum toward digitization sparked by the pandemic, leading health systems are taking on a “digital-health-first mindset” in order to:
These goals are furthered when healthcare providers create clean, integrated, and authoritative repositories for data related to patients, providers, locations, and payers that improve crucial processes. Infoverity’s comprehensive methodology for using advanced technology to organize enterprise data is tailored for healthcare. Infoverity has targeted methods and expansive models for healthcare master data objects and hierarchies that allow companies to make rapid progress toward tangible benefits.
Healthcare organizations often suffer from a lack of interoperability. This impedes an efficient exchange of data between entities and leads to high rates of failed reimbursements, regulatory compliance fines, and an inability to use third-party data (such as CMS NPPES, payer, and insurance data).
Without quality data management, healthcare organizations cannot understand and utilize data to identify relationships between households and insurance groups. With Infoverity’s support, organizations can map patients and payers to providers, as well as providers to locations, connect physicians and services by location, and offer “Find a Doctor” functionality.
Healthcare companies often have disconnected data that prevents data from being used. With data management, businesses have consistent data across operational systems, ending data silos that lead to inefficiencies. Organizations can accurately track patients’ medical histories, validate provider identity information for governmental databases, and prevent fraudulent billing practices.
Low performance rankings such as from Vizient, Healthgrades, and others, can damage brand credibility and dissuade potential new customers. By improving healthcare outcomes and reducing the cost and accuracy of detailed reporting, healthcare organizations often achieve substantial improvements in these rankings, which helps to attract and retain clients.
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AI algorithms can predict individuals' risk of developing chronic diseases by analyzing lifestyle and genetic data. This allows for early interventions and personalized preventive measures.
Provide individualized treatment plan based on the patient's medical history and symptoms.
By analyzing data from wearable devices, Gen AI can provide immediate feedback and suggestions. A study demonstrated that AI-driven personalized nudges led to a significant increase in physical activity among participants.
Expiate the new process of discovering new drugs from preclinical trials.
Mastering multiple key provider & location data systems to deduplicate and enrich provider data for a hospital or payers public facing website.
Enable accurate data governance, reference data, and benchmarking for key metrics leveraging mastered data and transactional enterprise data sets: Readmission Rate, Length of Stay, Provider/Nurse Certification Status, Turnover by Hospital, Turnover by Position, Position Fill Rate, Bed Utilization, Revenue per Bed, etc.
Data Quality improvement to standardize critical data sets to HL7 FHIR or other HIE specific data standards, allowing for critical patient data to be shared with other providers, payers and health information exchanges. Interoperability and data sharing amongst HCOs allows for the best care possible throughout a patient’s care cycle.
Mastering of payers, plans, contracts, network tiers and relationships with Providers. Enable payer coverage gap analysis, improved patient scheduling and provide plan enrollment strategies. Additionally, combined with referral data, develop dashboards and predictive insights into patient network leakage.
Enable “Search Before Create” integration with EMRs and other patient registration systems to prevent duplicate patient creation in real-time. Synchronize patient EMR across enterprise systems upon creation. Advanced fuzzy patient auto-matching reduces HIM manual task effort.
Master all enterprise data sources for employee and employee working location. Enable accurate HR reporting by location, skillset, certification, provider clinical FTE%, etc.
Data governance and reference data management program for enabling standards and solutions for clinical codes : ICD-9, ICD-10, SNOMED, CPT, LOINC, IMO, etc.
See how we can deliver the power of data to the healthcare industry
