Digitalization is bringing the often disjointed operations of healthcare into closer union through healthcare payer analytics. As we edge toward a new synthesis of using data to drive better services, we see the potential for improved collaboration between providers, payers, and intermediaries.
How Do Health Plans Take Advantage of Digitalization?
Healthcare has entered the era of instantaneous information sharing. Patient diagnosis, treatment, and medication all require an interconnected network of providers, payers, and third parties.
Personalized data travels in real-time through networks that need to retrieve, detect, approve, and analyze patient data while simultaneously living up to a high standard of privacy and security. Sharing data at this pace can only be accomplished with intelligent digitalization.
Digitalization is used to:
- Improve patient outcomes by identifying alternative payment models to match patient needs.
- Recruit providers that align with competitive compensation.
- Manage high-risk, high-cost plan members who have limited resources.
- Optimize reimbursements.
- Control costs.
- Reduce administrative costs.
- Uncover cost-saving opportunities.
- Optimize payment structures.
How Can Payers Navigate Risks in Recruiting Providers and Managing High-Risk Patient Needs?
Payers face challenges in identifying providers that can best serve patients within the costs their plans allow. Digitalization provides cost-effective solutions using real-time payer analytics.
What Is Payer Quality Analytics?
Payer quality analytics is about using insights from data to improve healthcare services from insurance companies and other coverage. This can include KPIs and other metrics to determine a service’s efficiency. These analytics are used across every type of payer system in healthcare.
What Are the Different Types of Payer Systems in Healthcare?
Different types of payer systems exist to provide financial coverage for healthcare services. These are the most commonly used payer systems:
- Private health insurance provided by private companies or organizations
- Preferred provider organizations (PPOs)
- Health maintenance organizations (HMOs)
- High-deductible health plans (HDHPs)
- Government healthcare programs (Medicare, Medicaid)
- Children’s Health Insurance Program (CHIP)
- Employer-sponsored health plans
- Self-funded plans
- Accountable care organizations (ACOs)
How Can These Healthcare Payers Use Analytics to Improve Their Level of Care?
The following are several steps where digitalization provides solutions. Analytics can help payers:
Identify trends and opportunities dealing with provider recruitment and retention.
Improve interoperability, coordinating care and boosting communication by sharing metrics.
Collaborate more efficiently with technology vendors and providers.
Leverage analytics to help manage changes in federal and state legislation and affected payment changes.
What Types of Data Analytics Are Used in Healthcare?
Four main types of analytics are used to measure patient care, efficiencies, and outcomes in healthcare.
Descriptive analytics involves statistics, visualization, and reports from historical data to represent trends, patterns, and valuable insights,
Diagnostic analytics focuses on uncovering the reasons behind healthcare outcomes, studying patterns, examining root causes for issues, and driving better decisions based on findings.
Predictive analytics builds forecasting data for future results based on historical data and statistics. It uses machine learning (ML) to pinpoint patterns and connections between data points, which is useful to allocate resources and assess:
- Future health risks
- The impact of medication
- Potential diseases
Prescriptive analytics involves producing recommended actions based on data. Modeling and metrics are used to define a course of action for treatment and to assign resources for healthcare.
What Are the Benefits of Using Real-Time Analytics?
The ability to connect with providers, patients, and intermediaries is built on the foundation of accurate, shared data. In today’s healthcare system, this can only truly be done using real-time analytics. This data helps payers better identify patterns, trends, and anomalies that drive better decisions.
Real-time analytics help healthcare payers:
- Monitor the cost of different prescription options.
- Instantly analyze pharmacy transactions.
- Identify cost-saving opportunities.
- Better allocate resources.
- Negotiate better prices.
- Identify and act upon suspicious patterns and fraudulent activities.
- Use data to find proactive solutions for better patient outcomes.
What Is Payer Strategy in Healthcare?
Payer strategy involves managing a payer’s network of hospitals, physicians, and healthcare facilities to source the best standard of care for members while controlling costs for treatments, medications, procedures, deductibles, and other expenses.
Payers strategically negotiate contracts with healthcare providers, including payment rates, discounts, and value-based reimbursement, to ensure optimal financial arrangements and incentivize high-quality care.
What Is All-Payer Claims Data?
All-payer claims data (APCD) is a comprehensive database that aggregates and integrates claims data from multiple payers, including private insurance and government programs. This APCD provides a centralized and standardized repository for costs and outcomes.
APCD helps analyze cost trends and develop insights for policymakers, researchers, payers, and providers alike.
What Is the Current Status of Regulation Around Healthcare Payer Analytics?
The following are three important regulatory requirements involving payers and the immediacy of their interaction with patient data.
Since January 1, 2021, all hospitals have been obligated to provide clear pricing that helps consumers compare and estimate hospital costs. Healthcare payer analytics ensure real-time alignment with all current costs to assist patients and consumers with accurate information.
This act is part of the Consolidated Appropriations Act of 2021. It restricts excessive patient costs in emergency situations where the patient cannot consent to treatment.
As payers connect with a patient’s health plan, providers, and hospitals in an emergency, real-time analytics can help all parties act on the patient’s behalf to find the most affordable cost solution.
The Privacy Rule is a federal law granting patient privacy rights based on limits on who can view and receive personal health information. This holds true for electronic, written, and oral data.
As data is shared in real-time between providers, payers, and intermediaries regarding individual cases, it stresses the payers’ responsibility for data security and regulated protections.
What Does the Future Look Like for Healthcare Payer Analytics?
The future of healthcare will be driven by technology aimed at improving efficiency, reducing costs, and better utilizing resources. This includes using artificial intelligence (AI) and machine learning (ML) to scale real-time data intelligence. Better data opens opportunities for payers, providers, and intermediaries to forge stronger collaborations and negotiate better healthcare outcomes for patients.
Real-time insights will also foster improvements in preventative care, using data to drive public education on the benefits of making wise health decisions and coordinating with physicians to develop positive daily habits.
When analytics help payers base decisions on accurate metrics, they can uncover new, innovative ways to save on costs while improving patient care.
Xevant: Real-Time Analytics Solutions for Healthcare
If you’re interested in what real-time analytics can provide, try Xevant’s free trial and talk to one of our experts today.