Healthcare

The healthcare industry is experiencing rapid change in how care is delivered, driven by consumer expectations, technological advances, continually rising healthcare costs, and a dramatic increase in information availability.

Healthcare information can be mined and insights extracted for improved patient outcomes and cost savings in the Operational, Financial, and Clinical Pillars of healthcare. Health insurance claims data and Electronic Health Records provide significant detail about healthcare services and drugs provided. With widespread use of wearable sensors and Internet of Things (IoT), there are new opportunities to advise subscribers, providers, and care givers with even more relevant information and insights. However, access to these data streams is only the start to realizing the benefits data analytics can provide patients and healthcare providers.

Elder Research can provide analytics consulting support in all pillars of the healthcare industry—from assessing analytics strategy to managing the institutional challenges of integrating analytics into healthcare systems and processes. Making insights readily accessible to clinical and business decision-makers will continue to be a critical differentiator for healthcare organizations.

Expert analytics for healthcare delivers a wide range of benefits, including:

• Improving outcomes of care and utilization of resources
• Developing quality performance metrics to improve service and reduce cost
• Increasing patient-responsible pay rate
• Identifying pharmacy and service provider fraud, waste and abuse
• Optimizing claim management
• Diagnosing disease and rate of disease progression
• Reducing opioid risk

Provider Performance and Quality Scoring Analytics

High-quality, high-value healthcare is foundational to achieving desired patient outcomes, attracting new consumers, retaining staff, and obtaining optimal reimbursement. Analyzing data on provider performance and the quality of care allows for review and adjustment.

We provide analytics consulting services to:

• Create data-driven provider quality scores
• Perform performance-based referrals and network creation
• Identify over- and under-utilization by providers

Accurately assessing provider performance allows more effective healthcare services at a lower cost.

Healthcare Fraud, Waste, and Abuse Analytics

Excessive or redundant medical services, medical coding errors, improper billing, as well as outright fraud, continue to challenge health insurers. Healthcare fraud is hard to detect due to the variety of nuanced deceits employed, the fact that investigative evidence is often buried in text documents, and that there is often collusion among network providers.

• Provider Fraud, Waste, and Abuse: We identify questionable provider practices and prioritize work for investigators, then measure the impact of the actions taken to further reduce the losses and promote best practices among providers.
• Pharmacy Fraud, Waste, and Abuse: We detect and investigate prescription shorting, drug switching, drug diversion, drug recycling, kickbacks, and many other techniques used by individuals or networks to commit prescription drug fraud.

We use advanced data science and predictive modeling techniques to prioritize investigative caseload, improve efficiency of investigative resources, and maximize recoveries.

Healthcare Claims Analytics

Claims analytics can pinpoint subrogation opportunities and the likelihood of claim litigation.  With accurate risk measurement, low-risk claims can be fast-tracked for settlement.  Insurance loss reserves can be accurately estimated and insurance adjusters optimally assigned.  Claims workflow optimization and automation frees adjustors and investigators to work on the most difficult high-value cases.  Our claims analytics work with your in-house team to uncover additional opportunities to reduce costs and loss ratios by:

• Improving underwriting risk management
• Increasing claims approval speed and accuracy
• Improving claims management resource utilization

Pharmaceutical and Biotech Analysis

We have deep experience helping pharmaceutical, biotech, and agricultural clients derive actionable insights from their clinical data. We have helped organizations make the decision to develop or market new medical or wearable devices or to determine the efficacy of a new drug in the marketplace.  Drug or device, we can help you make valuable data-driven decisions with your life sciences data.

Case Studies

The savings from healthcare analytics solutions can be substantial for all parties involved.  Our clients—whether newly-formed analytics teams or established pros—find that we help them understand their data, strengthen their teams’ abilities, and bring to the forefront advanced insights aligned to their needs. Examples of our healthcare solutions include:

Improving Provider Performance and Patient Outcomes

We provided analytics consulting services to DentaQuest to assess the performance of Medicaid dental providers, including a team of clinicians and network providers with operational expertise.  An analytics solution was developed to produce long-term savings by assigning new patients to providers having the highest quality care for the lowest cost. Claims data from hundreds of programs over 5 years in 38 states were used to model quality information for specific procedures among 22 million members.

Results: The Outcomes model provided quality information for specific procedures over time and enabled DentaQuest to reduce the amount paid per patient by 25% in the pilot state and to increase revenue by more than one dollar per patient per month.

Detecting Health Insurance Fraud, Waste, and Abuse

Our team developed a predictive fraud detection model that scored and ranked Medicare and Medicaid dental insurance claims by risk. Having explainable scoring was a key component of success, since the model results would be used as evidence to warrant opening an investigation for providers identified as suspicious.

Results: The solution generated leads with the highest potential return on investment for investigators and increased the fraud detection rate from 5% to 48% for the top 50 riskiest providers identified by the model.

Optimizing Federal Workers Compensation Claims Approval

We developed a data-driven risk assessment framework to triage Worker’s Compensation claims, prioritizing high-risk cases for review and fast-tracking other cases to avoid manual review and adjudication. Claims that are routed to the fast track are assigned risk-based maximum payment limits for intelligent ongoing claims management.

Results: Claims examiners use the risk assessment framework to triage Worker’s Compensation claims, prioritizing high-risk cases for review and fast-tracking other cases to avoid manual review and adjudication and to distribute case load more effectively. The expected performance improvement includes reducing the number of fast-tracked case decisions overturned by 39% and reducing total medical amount for missed denials by 25%.

Improving Claims Approval Speed and Accuracy

For the Social Security Administration identifying claims for disability that met the requirements for approval was a time-consuming and error prone process. Some claims were taking over two years to be processed, much too long for very ill or elderly claimants. The challenge was to effectively integrate the data.  Our solution combined text mining with traditional statistical techniques to rank disability claims for approval.

Results: Our solution enabled 20% of the claims to be approved immediately which in turn allowed the SSA to focus their resources on the most challenging cases and ensure that all statutory requirements were met.