The rapidly evolving field of complex care management has emerged as an important advance in the effort to improve the lives of individuals with urgent health and social needs.1 2 The Blueprint for Complex Care defines this field as “a person-centered approach to address the needs of people who experience combinations of medical, behavioral health, and social challenges that result in extreme patterns of healthcare utilization and cost. Complex care works at the personal and systemic levels: it coordinates care for individuals while reshaping ecosystems of services and healthcare.”3
With the growth of the field, there are urgent calls for new and improved tools for measuring quality and outcomes. A monograph on effective care for high-needs patients produced in 2017 by the National Academy of Medicine concluded that “While condition-specific measures are important, high-need patients are more than the sum of their individual diseases. To better reflect this reality, measures for assessing the performance of care models for high-need patients could indicate the degree of care coordination, quality of life, independence, and overall mental and physical health status.” 4, 5
A 2020 report by the Center for Health Care Strategies identified specific activities needed to accomplish this goal; these include developing standardized approaches to identify the target population and m the effectiveness of treatment in improving health, wellbeing, and the quality of service and in reducing avoidable cost and utilization6. This finding underscores the need for a core set of measures for the longitudinal evaluation of programs. Cost and utilization are important to payers and are relatively easy to obtain but are not generally what is most important to patients or providers, such as patient experience, quality of life, health and racial equity, and coordination of care.7
Translating these recommendations into practice is challenging. There are many measures to choose from—one report identified 284—but many were not specifically developed for a population with complex needs. 8 A measurement development initiative used the Delphi method to create a library of 26 patient-reported and 32 staff-reported measures that span four domains: experience of care, equity, health and well-being, and care integration. Piloting and validation studies are needed to determine the utility of many of these candidate measures.9
A systematic analysis and review of 110 published studies of high-cost, high-need patients identified the challenge of identifying at-risk populations who would benefit from complex care interventions. 10 This analysis concluded that successful identification and prediction depend upon a model that incorporates complexity—that is, an interacting set of factors that includes patients’ prior use of healthcare services, chronic diseases, nonmedical barriers to accessing care, experience with the healthcare system, clinician judgment, and willingness to participate in an intervention.
One such approach, developed two decades ago, is the INTERMED method.11 12 INTERMED uses a biopsychosocial model as the basis of its Complexity Assessment Grid, a systematic representation of patients’ integrated health risks and needs and interaction with the healthcare system. Raters use lNTERMED to score patients' history, current state, and future vulnerability in each of four domains: biological, psychological, social systems, and healthcare. It can be interpreted based on individual items or summed into a total complexity score, which is used to identify patients with complex needs. There are a total of 20 items on the scale, each with a score of 0-3; more than 20 out of 60 possible points generally indicate complexity. Completion of this scale is based on a structured interview. Specific adaptations of INTERMED have been introduced, including patient-reported versions of the IM-SA13 and PCAM14 and versions for use with elderly populations (IM-E15, IM-E-SA16). INTERMED and its adaptations have been used to identify patients in need of care coordination in primary care settings.17
Many studies utilizing INTERMED-based measures in adult populations were summarized in two recent reviews that underlined its effectiveness in outcome prediction. 18, 19 These reviews highlight the significance of this measure as an important step toward operationalizing complexity into discrete, measurable variables and identifying populations who would benefit from case management. INTERMED requires 20-30 minutes to complete and is not appropriate for patients who have impaired memory or cognition. While useful in identifying populations who would benefit from case management, recent studies have noted its limitations in differentiating high-cost, high-need patients with multiple chronic conditions from other patients, 20 its validity with individuals with rheumatoid arthritis21 or its utility for treatment planning in a primary care practice 22. This finding resonates with a National Academy of Medicine monograph on the care of high-need patients, which notes that “… the current system of metrics is not designed in a way that encourages providers to organize care in the most effective manner.” 23
The Healthy Lives 5 Axis Scale (HL-5) was created to address this need. (Figure 1) [at end of manuscript] It was designed by the staff of a program that provided home- and community-based services to patients with very complex health and social needs. The measure has been piloted and field tested in a variety of settings, including community health centers, primary care practices, and ACO care management programs. 24, 25 To facilitate its integration into the workflow of busy multidisciplinary teams, the scale was designed to be concise, easy to administer and score, and based on readily observable data. Each of these axes can be used to create specific goals for case management interventions.
The HL-5 (Figure 1) [at end of document] incorporates a multidimensional, systemic approach in which health is understood as the complex interplay between patients’ needs and resources, their capacity for functioning and self-care, and their relationship with and utilization of health care systems.26, 27 The goal of this study was to develop a tool that promotes assessing patients from a variety of perspectives in a quantifiable format that can be translated directly into a care plan.
In clinical use, the HL-5 is completed by a provider, community health worker, or case manager in less than ten minutes after a brief patient interview or routine intake assessment and chart review. It can be used to identify patients in need of care management services and/or to identify concrete goals for these interventions. It includes anchor point descriptors to improve reliability and shorten the time needed to train users. Because it is completed by a staff member, it can be used with individuals with cognitive or physical communication challenges. Each item is scored on a 1-4 scale, and a total (range 2-8) is calculated for each axis. The axes can be summed into a total scale score (range 10-40). In clinical practice, the scale is used to detect individuals within a group of patients with a high level of need or dysfunction; to identify specific areas of focus to inform care management planning, and to track progress over time by repeated administration every three to six months.
Measure Development
A variety of clinical and diagnostic domains were considered, and five were selected based on the following criteria: 1) observable by a community health worker or nurse in the course of an initial evaluation session and brief record review; 2) established validity in studies of patients with complex health and social needs; 3) predictive of health outcomes; and 4) a stable indicator of patient status rather than one subject occasion-specific or situational fluctuations.
The scale measures three patient-focused domains—health-related functioning, social and physical needs, and capacity for self-care—and two health system domains—access to care and utilization. Each of the axes has two components.
Health-Related Functioning: Health-related functioning and quality of life measures have been used for more than thirty years to describe patients’ physical, mental, and social functioning. 28 These include the ability to care for oneself (e.g., bathing, dressing, walking); role functioning, such as work-related activities such as housework and career; and social functioning with family and friends. 29 This well-validated indicator of a patient’s abilities and disabilities is a strong and stable predictor of future health, cardiovascular diseases, future hospitalization, and all-cause mortality 30,31,32, 33,34,35 The Functioning Axis has two components: Medical Problems considers how a patient’s medical symptoms impact their functioning, and Behavioral Problems consider to what degree a patient’s mental state (including substance abuse) affects their ability to care for themself.
Physical and Social Needs: Social determinants of health (SDOHs) include food supply, housing, economic and social resources, transportation, and education. Across populations, these variables predict length and quality of life. 36 SDOHs have been shown to have a greater influence on health than either genetic factors or access to healthcare services 37. Access to food, housing, and supportive relationships are robust predictors of health outcomes. 38,39
Self-Care: The third axis measures an individual’s capacity for self-care and to engage productively in treatment. It has two components: adherence, defined as the extent to which a person’s behavior—taking medication, following a diet, and/or executing lifestyle changes—corresponds to accepted recommendations from a health care provider. 40,41,42,43,44 Patients with higher levels of adherence have better health care outcomes.
The second component is activation, defined as an individual’s knowledge, skills, and confidence in managing his/her health and health care 45. High activation is a measure of strong self-management skills, good knowledge of one’s own health, and a desire to prevent future ill health 46, 47. More activated patients are more likely to have positive clinical outcomes, including better blood glucose, blood pressure control, and body mass index (BMI), and better perceived health; high activation is associated with lower healthcare utilization and costs.48,49
Access (Provider Availability and Relationships): The fourth axis measures an individual’s interaction with the health care system. The first component is the availability of services (access) which reflects factors that include health insurance status, provider language proficiency, appointment availability, and transportation. Availability of health care, especially primary care, has been shown to be an important determinant of health.50,51,52
A second component is the quality of the relationship between patients and caregivers. If the relationship is negative or conflictual, if there is a lack of trust or communication, then care suffers. 53 The inverse is also true: better relationships lead to better outcomes54,55,56
Utilization: The fifth axis measures the individual’s pattern of healthcare utilization—the balance of intensive services (ED and inpatient care) versus ambulatory/primary care. There is an inverse relationship between these services: increased use of primary care is associated with decreased utilization of the emergency department and inpatient care. 57,58,59,60 A recent study, for example, found that the utilization of primary care in a regular and highly continuous pattern is associated with lower health care costs, fewer ED visits, and fewer hospitalizations compared with irregular, noncontinuous users.61