Care gaps exist when patients can’t access applicable preventative services, screenings or treatment protocols, or when they elect not to follow prescribed care regimens, resulting in poor health outcomes and increased healthcare costs.
Salient Health provides out-of-the-box insight and advanced custom analysis capabilities to effectively leverage claims data and advanced cost intelligence to identify opportunities for improvement in closing care gaps. Influence data-driven intervention strategies with granular insight from the organization level to the physician level, down to the individual patient level.
Optimize care quality with actionable intelligence you can use
Quantify quality metrics and assess progress
Aggregate and quantify care quality metrics across payers, understand opportunities for improvement across facilities and providers
Segment patient populations to monitor health trends
Group patient populations into meaningful cohorts to accurately gauge and score risk. Identify, monitor and improve care quality and population health, noting positive and negative trends.
Manage and assess preventative care procedures
Preventative care can lessen the burden of disease and ultimately, save lives. Track and analyze patterns in your data to determine the most impactful preventative care procedures for your patient population.
Identify at-risk beneficiaries and close care gaps
Effectively care for and manage at-risk patient populations with in-depth identification on an individual level.
Determine appropriate intervention methodologies
Use data to guide patient intervention strategies based on patient need, trends and clinical competencies.
Use data insights to support clinical strategy
Identify and proactively respond to patients due for necessary treatments and procedures to ensure timely, relevant care is received.
Redefine a new quality standard
Highlight inefficient patterns of care
- SalientHealth empowers healthcare organizations with the tools to categorize and segment patient populations across multiple factors to identify care needs
- Leverage claims data and ICD-10 codes to analyze treatment outcomes to understand their efficacy and establish data-driven care strategies for future care
- Quantify costs associated with treatment and care patterns to reveal areas of financial opportunity within the care lifecycle
Create data-driven intervention strategies
- Analyze patterns of disease within your patient population to gauge appropriate interventions
- Maximize preventative care adoption by identifying optimal patient beneficiaries
- Segment patient populations by condition and risk stratification to optimize wellness care and chronic care management
Evaluate medical adherence to intervene when appropriate
- Highlight patient populations not adhering to prescribed medication regimens such as failure to fill prescriptions or experiencing gaps in medication refills.
- Determine the best course of intervention support such as wellness education or medication management services
- Improve health outcomes such as with diabetes, chronic kidney disease, congestive heart failure and hypertension.
Track and analyze transitions of care
- Understand utilization of downstream care providers and outcomes, specifically with specialist diagnoses, hospital discharges and transitions between healthcare settings (Admit/Discharge/Transfer – ADT)
- Identify opportunities to improve care coordination, medication reconciliation and patient education
- Reduce the risk of adverse events and hospital readmissions by analyzing patient care tendencies, lifestyle demographics and downstream care utilization
Highlight inefficient patterns of care
- SalientHealth empowers healthcare organizations with the tools to categorize and segment patient populations across multiple factors to identify care needs
- Leverage claims data and ICD-10 codes to analyze treatment outcomes to understand their efficacy and establish data-driven care strategies for future care
- Quantify costs associated with treatment and care patterns to reveal areas of financial opportunity within the care lifecycle
Create data-driven intervention strategies
- Analyze patterns of disease within your patient population to gauge appropriate interventions
- Maximize preventative care adoption by identifying optimal patient beneficiaries
- Segment patient populations by condition and risk stratification to optimize wellness care and chronic care management
Evaluate medical adherence to intervene when appropriate
- Highlight patient populations not adhering to prescribed medication regimens such as failure to fill prescriptions or experiencing gaps in medication refills.
- Determine the best course of intervention support such as wellness education or medication management services
- Improve health outcomes such as with diabetes, chronic kidney disease, congestive heart failure and hypertension.
Track and analyze transitions of care
- Understand utilization of downstream care providers and outcomes, specifically with specialist diagnoses, hospital discharges and transitions between healthcare settings (Admit/Discharge/Transfer – ADT)
- Identify opportunities to improve care coordination, medication reconciliation and patient education
- Reduce the risk of adverse events and hospital readmissions by analyzing patient care tendencies, lifestyle demographics and downstream care utilization
