The Future of Employer Health Insurance

Employers are always looking for ways to reduce one of their biggest expenditures–the cost of providing health insurance to employees. Many employers have explored solutions such as adding wellness plans, reducing usage, and providing different provider access mechanisms, all with modest success. Stemming the rising costs of health insurance requires management to understand and improve healthcare outcomes for their employee and dependent populations. Changing the future of employer health insurance will require a multi-faceted approach:

1. Driving additional value by reducing utilization of healthcare services within these employer populations.
2. Utilizing a wider lens through which to view performance of various providers, then making decisions based on those who are consistently providing low cost, high quality care.
3. Employer will need to combine their data with other companies across a geographic region to get a better picture of the provider landscape than has ever been possible before.

Pairing HIE Data with an Analytics Platform: Four Key Improvement Categories

Population health and value-based payment demand data from multiple sources and multiple organizations. Health systems must access information from across the continuum of care to accurately understand their patients’ healthcare needs beyond the acute-care setting (e.g., reports and results from primary care and specialists). While health system EHRs have a wealth of big-picture data about healthcare delivery (e.g., patient satisfaction, cost, and outcomes), HIEs add the clinical data (e.g., records and transactions) to round out the bigger picture of patient care, as well as the data sharing capabilities needed to disseminate the information. By pairing HIE capability with an advanced analytics platform, a health system can leverage data to improve processes in four important outcomes improvement areas:

1. Workflow
2. Machine learning
3. Professional services
4. Data governance

Social Determinants of Health: Tools to Leverage Today’s Data Imperative

Social determinants of health (SDOH) data captures impacts on patient health beyond the healthcare delivery system. Traditional health data (e.g., from healthcare encounters) only tells a portion of the patient and population health story. To understand the full spectrum of health impacts (e.g., from environment to relationship and employment status), organizations need data from their patient’s daily lives. The urgency for SDOH data is particularly strong today, as value-based payment increasingly presses health systems to raise quality and lower cost. Without fuller insight into patient health (what happens beyond healthcare encounters) organizations can’t align with community services to help patients meet needs of daily living—prerequisites for maintaining good health. Standardizing SDOH data into healthcare workflows, however, requires an informed strategy. Health systems will benefit by following a standardization protocol that includes relevant and comprehensive domains, engages patients, enables broader understanding of patient health, integrates with organizational EHRs, and is easy for clinicians to follow.

Employer Health Plans: Keys to Lowering Cost, Boosting Benefits

Employers that offer robust employee health plans at affordable costs are more likely to attract and retain a great workforce. Healthcare, however, is often a top expense for organizations, making balancing attractive benefits with attractive costs a complex undertaking. Employers need a deep understanding of employee populations and opportunities to manage health plan costs without sacrificing quality. An analytics-driven approach to employee population health management gives employers insight into two key steps to lower healthcare costs and enhance benefits:

1. Manage easily fixed cost issues.
2. Use healthcare cost savings to fund expanded benefits.

Six Challenges to Becoming a Data-Driven Payer Organization

As healthcare transitions from fee-for-service to value-based payment, payer organizations are increasingly looking to population health management strategies to help them lower costs. To manage individuals within their populations, payers must become data driven and establish the technical infrastructure to support expanding access to and reliance on data from across the continuum of care. To fully leverage the breadth and depth of data that an effective health management strategy requires, payers must address six key challenges of becoming data driven:

1. Data availability.
2. Data access.
3. Data aggregation.
4. Data analysis.
5. Data adoption.
6. Data application.

Episode Analytics Now Mission Critical as Outcomes Meet Incomes: Partners HealthCare Paves Volume-To-Value Path With Late-Binding Data Warehouse

In this reprint from Microsoft, Dennis Schmuland, MD, FAAFP (Chief Health Strategy Officer, Microsoft US Health & Life Sciences), sits down with Sree Chaguturu, MD (Vice President and Chief Population Health Officer, Partners HealthCare) to learn how Partners HealthCare has prepared for the tipping point of value-based care.

Four Population Health Management Strategies that Help Organizations Improve Outcomes

Population health management (PHM) strategies help organizations achieve sustainable outcomes improvement by guiding transformation across the continuum of care, versus focusing improvement resources on limited populations and acute care. Because population health comprises the complete picture of individual and population health (health behaviors, clinical care social and economic factors, and the physical environment), health systems can use PHM strategies to ensure that improvement initiatives comprehensively impact healthcare delivery. Organizations can leverage four PHM strategies to achieve sustainable improvement:

1. Data transformation
2. Analytic transformation
3. Payment transformation
4. Care transformation

Custom Care Management Algorithms that Actually Reveal Risk

Care management is a tool for population health that focuses scarce healthcare resources on the sickest patients. Care management leaders need to know who those sickest patients are (or may be). The static risk models typically used for stratifying patients into risk categories only paint a partial picture of health and are ineffective for modern care management programs. Custom algorithms are now capable of predicting risk based on multiple risk models and multiple data sources. They help care management teams confidently stratify patient populations to paint a complete picture of care needs and efficiently deliver care to those who need it most. This article explains how custom algorithms work on static risk models to normalize risk scores and improve patient stratification, care management, and, ultimately, population health management.

The Top Three Healthcare Financial Trends in 2017: Payment Transitions, Disruption, and New Skills

Influential healthcare financial trends in 2017 emerged in three areas:

1. Transitions in payment.
2. Disruption from familiar players and newcomers.
3. Emerging data skillsets.

Uncertainty has been a common theme for 2017. Organizations continue waiting for clarity on the future of the Affordable Care Act (ACA), while working to implement value-based care. Changes from established healthcare organizations as well as the arrival of prominent newcomers (e.g., Amazon) add to the unsettled outlook, as do emerging data skillsets. Amid the uncertainty, however, healthcare is clearly continuing on the path to patient-centered care. Organizations best positioned for 2018 will understand their performance in 2017’s top three healthcare financial trends as they evaluate their preparedness for the coming year.

8 in 10 Hospitals Stand Pat on Population Health Strategy, Despite Uncertainty Over the Affordable Care Act’s Future

A 2017 survey by Health Catalyst shows that despite uncertainty about the future of the Affordable Care Act, 80 percent of healthcare executives have not paused or otherwise changed their population health management strategy. 68 percent said that PHM is “very important” to their healthcare delivery strategy, while fewer than 3 percent said it was not important at all. The results show that executives view the move to value-based care as inevitable, and they view a PHM strategy as an integral part of their future efforts.

Population Health Documentary Highlights Three Success Stories Transforming Healthcare

The documentary, “A Coalition of the Willing: Data-Driven Population Health and Complex Care Innovation in Low-Income Communities” shows how precision medicine and care management can be effective tools for successful population health. The film highlights three programs that use data to hotspot populations of high-risk, high-need patients, and then deploy unique, targeted care management inventions. The documentary, which initially aired during the 2017 Healthcare Analytics Summit, presents hopeful solutions, scalable across diverse patient populations, that are leading to exceptional results and the future of healthcare transformation.

A Landmark, 12-Point Review of Population Health Management Companies (Executive Report)

Population health management (PHM) is in its early stages of maturity, suffering from inconsistent definitions and understanding, overhyped by vendors and ill-defined by the industry. Healthcare IT vendors are labeling themselves with this new and popular term, quite often simply re-branding their old-school, fee-for-service, and encounter-based analytic solutions.  Even the analysts —KLAS, Chilmark, IDC, and others—are also having a difficult time classifying the market. In this paper, I identify and define 12 criteria that any health system will want to consider in evaluating population health management companies.  The reality of the market is that there is no single vendor that can provide a complete PHM solution today.  However there are a group of vendors that provide a subset of capabilities that are certainly useful for the next three years.  In this paper, I discuss the criteria and try my best to share an unbiased evaluation of sample of the PHM companies in this space.

Patient Registries Turn Knowledge into Outcomes Improvements

In today’s data-rich healthcare environment, patient registries put knowledge in front of the people who will use it to improve outcomes and population health. Non-IT professionals (e.g., clinicians and researchers) often don’t have direct, timely access to operational and clinical data. As a result, organizations miss out on important improvement opportunities and data-driven point-of-care decisions. Knowledge too often remains siloed in the enterprise data warehouse (EDW) or among specialized groups. Patient registries remove these barriers. It allows clinicians and researchers to make informed choices and frees up data analysts to focus on their priority areas.

A Critical Role for Better Population Health Management

Unnecessary barriers to practice and licensing limitations have severe consequences for health systems’ population health initiatives, especially as the nationwide shortage of healthcare practitioners continues to grow:

• Delayed access to clinicians.
• Decreased access to care, particularly primary care and care in rural areas.
• Limited labor supply.
• Increased costs of services.
• Loss of potential revenue for healthcare organizations.

Using clinical nurse specialists as an example—one of many critical roles in population health management—effectively demonstrates the importance of removing unnecessary barriers to practice, from reductions in unnecessary readmissions and reduced length of stay (LOS), to less frequent ED visits and higher patient satisfaction. The bottom line, when it comes to barriers to practice, is that removing them (with solutions like uniform regulations) will do more than improve population health management—it will also reduce costs and improve patient outcomes.

How Care Management Done Right Improves Patient Satisfaction and ROI

A comprehensive care management program organizes many moving parts into an efficient workflow and brings order to the complex, often messy, world of healthcare. Care coordination harmonizes the workflow of clinicians, patients, family, social workers, and therapists, to name a few. It facilitates medication reconciliation, care compliance, appointment scheduling, and communication with patients, as well as engagement between patients and the care team. Care coordination concentrates on the highest-utilization, highest-cost patients to produce better clinical, operational, and financial outcomes, the bottom line goals for healthcare systems involved in population health and value-based care. This article details the benefits of, and barriers to, care management and coordination, their role in population health, and the technology that’s helping to automate this area of healthcare.

Three Essential Systems for Effective Population Health Management

An effective population health management program must include three systems: Healthcare Analytics, Best Practice, and Adoption. Organizations with only one or two of these systems often display symptoms of weak and ineffective capability for population health management.  But when you have a analytics foundation based upon a data warehouse, combined with evidence-based practices contained in a best practice system, and the ability to deploy and implement systematic changes to healthcare processes, health systems are truly prepared to manage population of patients.