Building for Value: A Foundational Structure to Support Population Health.

The journey to value relies heavily on a strong foundation in population health and on supporting systems of care. However, as the Centers for Medicare & Medicaid Services and commercial insurers rethink reimbursements to achieve cost savings, both patients and payments to health care organizations are at risk. The case for value-based care is ever stronger yet health systems will have to mature their culture, population health infrastructure, technologies and analytics capabilities, and leadership and management systems. In this article, the authors describe the functional organizational structure of the clinical transformation team responsible for population health in the University Hospitals Accountable Care Organizations (ACO). Based on their experiences building and evolving population health for the University Hospitals ACO, the authors layout the 3 pillars supporting their structure, including operations, clinical design, and data and analytics, and key areas of focus for each pillar.

A Path to Risk: Critical Elements of a Structured Approach.

Value-based care arrangements have been the cornerstone of accountable care for decades. Risk arrangements with government and commercial insurance plans are ubiquitous, with most contracts focusing on upside risk only, meaning payers reward providers for good performance without punishing them for poor performance on quality and cost. However, payers are increasingly moving into downside risk arrangements, bringing to mind global capitation in the 1990s wherein several health systems failed. In this article, the authors focus on their framework for succeeding in value-based arrangements at University Hospitals Accountable Care Organization, including essential structural elements that provider organizations need to successfully assume downside risk in value-based arrangements. These elements include quality performance and reporting, risk adjustment, utilization management, care management and clinical services, network integrity, technology, and contracting and financial reconciliation. Each of these elements has an important place in the strategic roadmap to value, even if downside risk is not taken. This roadmap was developed through an applied approach and intends to fill the gap in published practical models of how provider organizations can maneuver value-based arrangements.

Achieving Large-Scale Quality Improvement in Primary Care Annual Wellness Visits and Hierarchical Condition Coding.

BACKGROUND: Completion of Medicare Annual Wellness Visits (AWV) and documentation of Hierarchical Condition Categories (HCC) are important metrics in accountable care organizations (ACO) with quality and financial implications. To improve performance in large healthcare organizations, quality improvement (QI) efforts need to be scaled up in a way that is feasible within available system-wide resources. OBJECTIVE: We describe a 3-year effort using a multifaceted QI framework called the fractal management system for AWV and HCC performance. DESIGN: Pre-post evaluation of a multi-level, health system-wide QI management system intervention between 2018 and 2020. The system provided project management, coaching, communications, feedback of performance, and health informatics. PARTICIPANTS: The intervention was delivered to all 97 primary care practices within an Ohio-based accountable care organization, comprising 72,603 attributed Medicare and Medicare Advantage patients as of 2018. Eighty-nine of these practices were included in the analysis. APPROACH: AWV completion was defined as percent of eligible patients with a documented AWV during the calendar year. HCC completion was defined as documented reassessment of all prior-year HCC conditions. KEY RESULTS: AWV completion at the practice level increased from 23.7% (SD .14) in 2018 to 34.9% (SD .18) in 2019, and 59.8% (SD .17) in 2020. This was a statistically significant effect of time on AWV completion rates overall (F[2, 87] = 164.43, p < .000). More than half (56.2%) of practices met or exceeded the 60% goal in 2020. Practice-level HCC completion tracking started in 2019 (M = 75.9%, SD 7.4%) and increased in 2020 (M = 79.7%, SD 7.1%); t(172) = 2.0, p < .001. CONCLUSIONS: AWV and HCC performance goals were met in 2020, despite service disruptions due to COVID-19. The QI approach we used is applicable to other problems and other large healthcare systems.

Chatbot-Assisted Care Management.

PURPOSE/OBJECTIVES: Chatbots are automated conversation pathways that users can access through text message or email on smartphones or other connected devices. In care management, they can be used to monitor patients' health conditions or recovery from procedures. This article describes nurse care managers' experiences using chatbots in patient care, illustrated through two patient case reviews. Considerations for planning and implementing chatbot technology in care management settings are discussed. PRIMARY PRACTICE SETTING: This care management service is part of an accountable care organization that serves 582,000 patients in University Hospitals of Cleveland, Ohio. Care management focuses on patients with chronic conditions, recent hospital discharges, and other needs. Care managers comprise a centralized team as well as embedded staff in select primary care practices. FINDINGS/CONCLUSIONS: The two patient cases are exemplars from the care management program serving patients recently discharged from the hospital with ongoing chronic conditions that increase risk for readmission. Use of chatbots helped overcome obstacles to conventional care management outreach and resulted in improved outcomes and strong trusting relationships with the care managers. IMPLICATIONS FOR CARE MANAGEMENT PRACTICE: Patients who typically do not respond to other types of care manager outreach may respond to text message-based, asynchronous chatbot communication. Interpersonal relationships between care managers and patients can be strengthened by chatbot support. Chatbot technology tracks patients' progress and offers insights to patients and clinicians to facilitate earlier interventions when problems occur. Chatbots make frequent patient contact to collect and provide routine information, allowing care managers to spend more time on high-value interactions that require clinical judgment. Potential concerns about chatbots include effect on labor force, information security, health equity, and oversight of content.

Stratifying for Value: An Updated Population Health Risk Stratification Approach.

Most risk stratification approaches attempt to predict clinical outcomes rather than value. For a provider organization or health system to have financial success in value-based contracting, future risk models must analyze costs as well as disease burden. The purpose of this study was to create a customized risk stratification algorithm that considered a patient's medical spend alongside disease burden while delivering a scoring system that improves the efficiency of a care coordination program. The authors focused on University Hospitals (UH) Health System's Accountable Care Organization population of 554,805 because this patient cohort is engaged with UH's primary care network and has the most robust data. The 5-category risk algorithm was found to be meaningful and impactful after integrating the foundation of the Minnesota Tiering system with an expanded comorbidity list and weighting the result by the previous 12 months of medical spend. This new technique can identify patients in need of intensive care coordination. The complex risk tier of the stratification system reduces the number of patients from 551,045 to 27,552, or 5% of the patient population, and accounts for 67.9% ($1,107,822,887) of total annual medical spend. Expanding care coordination efforts to patients in the top 2 tiers would account for 15% of the patients and 83.2% ($1,357,545,872) of annual medical spend. The novelty of the new approach allows clinical teams to focus intense resources on a smaller sample of the patient population and to identify chronic conditions contributing to costs, and feel confident that they have greater explanatory power regarding value.