Operationalizing Surveillance of Chronic Disease Self-Management and Self-Management Support
SPECIAL TOPIC — Volume 15 — April 5, 2018
Teresa J. Brady, PhD1; Jeffrey J. Sacks, MD, MPH2; Albert J. Terrillion, DrPH3; Erin M. Colligan, PhD4 (View author affiliations)
Suggested citation for this article: Brady TJ, Sacks JJ, Terrillion AJ, Colligan EM. Operationalizing Surveillance of Chronic Disease Self-Management and Self-Management Support. Prev Chronic Dis 2018;15:170475. DOI: http://dx.doi.org/10.5888/pcd15.170475.
Sixty percent of US adults have at least one chronic condition, and more than 40% have multiple conditions. Self-management (SM) by the individual, along with self-management support (SMS) by others, are nonpharmacological interventions with few side effects that are critical to optimal chronic disease control. Ruiz and colleagues laid the conceptual groundwork for surveillance of SM/SMS at 5 socio-ecological levels (individual, health system, community, policy, and media). We extend that work by proposing operationalized indicators at each socio-ecologic level and suggest that the indicators be embedded in existing surveillance systems at national, state, and local levels. Without a robust measurement system at the population level, we will not know how far we have to go or how far we have come in making SM and SMS a reality. The data can also be used to facilitate planning and service delivery strategies, monitor temporal changes, and stimulate SM/SMS–related research.
Sixty percent of US adults have at least one chronic condition, and more than 40% have 2 or more chronic conditions (1). Individual self-management (SM) of chronic conditions, also called self-care, is central to effective disease management. The Chronic Care Model identifies productive interactions between patients with the knowledge, skill, and motivation to participate in their care (also known as “activated patients”) and their proactive practice team as critical to achieving positive functional and clinical outcomes (2). Self-management support (SMS), or efforts to support individuals in their SM, is one of the Chronic Care Model’s pillars of quality improvement needed to effectively manage chronic conditions in health care (2). A robust measurement system for measuring SM/SMS at the population level could be beneficial for assessing whether the nation is making progress in SM/SMS. The data could be used to facilitate planning and service delivery, monitor temporal changes, and stimulate SM/SMS–related research.
Ruiz and colleagues identified concepts that could be developed into SM/SMS surveillance indicators (3). These concepts spanned 5 socio-ecological levels (individual, health system, community, policy, and media), mirroring Frieden’s pyramid of public health impact (4) and reflecting the multiple dimensions of SMS (5). We attempt to operationalize Ruiz et al’s concepts (3) and, where they were not feasible for surveillance, we propose new indicators that can be used to assess status, trends, and disparities in SM/SMS at the local, state, and national levels.
Moving From the Forest to the Trees — Operationalizing Surveillance of Self-Management and Self-Management Support
We adopted Ruiz et al’s definitions of SM/SMS (3). SM consists of the tasks people must do to live well with chronic conditions and to pursue the life they desire (3,6). SMS is the systematic provision of education and supportive interventions by health care providers and others to strengthen patients’ skills and confidence in managing their health problems (ie, things done by others to support individuals in their SM efforts) (6).
We sought surveillance indicators that were sensitive to change, were actionable, had easily definable numerators and denominators, had face validity, were low-cost, required minimal effort to collect and analyze data, and — most importantly — had an existing system available to collect the data. If following a recommendation from Ruiz et al (3) was not feasible per these criteria, we explored other possible indicators to identify ones with the desired characteristics.
To standardize surveillance, we adopted the definitions in the strategic framework for multiple chronic conditions (7). We debated attempting surveillance of a single chronic disease or all chronic diseases. Should we select a single condition (like diabetes) and ascertain SM/SMS for that “sentinel” as an indicator of what is happening in other conditions? Although single conditions are likely to have specific SM activities (eg, a person with diabetes testing their blood sugar), our notion of SM addresses cross-cutting dimensions rather than disease-specific activities. Thus, we concluded that we needed to measure SM/SMS dimensions relevant across all chronic diseases, because focusing on a single condition might not be representative.
For each indicator proposed by Ruiz et al, we attempted to craft a question and specify the potential data source and numerator and denominator necessary for calculation of the indicator. As we attempted to operationalize the Ruiz et al concepts (3), we encountered consistent feasibility problems. First, we had difficulty defining a “case” of SM or SMS (the numerator) and the relevant denominator. We also lacked existing data-collection systems. The remainder of the article summarizes our deliberations on the indicators we discarded (Table 1) and our recommendations for indicators at each socio-ecological level (Table 2).
Self-management at the individual level
SM at the individual level involves a variety of activities, including adopting healthy behaviors (eg, not smoking, appropriate diet, taking medications), action planning, self-monitoring, coping with emotions, managing disability, and navigating the health care system (5,6,8). SM objectives (disease control, symptom control, prevention of deterioration) vary by condition (9). In an attempt to identify core cross-cutting elements of SM, attendees at a 2014 Self-Management Alliance meeting were asked to identify observable actions that would indicate that a person was actively and effectively self-managing his or her chronic condition. (See the Alliance’s membership list in Ruiz et al ). The divergent written answers indicated that SM is an abstract concept defined in many ways, including many behaviors that are hard to differentiate from general wellness behavior and that are not necessarily reflective of chronic condition SM (eg, resolutions to lose weight or exercise). The most frequently reported observation reflected taking action to manage the condition. We reasoned that other mentioned items like goal-setting and action-planning are skills taught to help transform someone into a self-manager, that is, more a means to the end rather than the end itself. We felt that the essence of SM is being able to make wise decisions and recognize and respond to changing circumstances, adapting to the changes in the disease’s trend and tempo and to the complicated realities of life with chronic disease (10,11). Taking action applies to any chronic disease and encapsulates a range of activities to respond to symptoms or situations as they arise. Action reflects the embodiment and culmination of translating education, plans, and counseling in daily life (12). The general idea of taking action to improve a chronic condition or avoid making it worse offers a comprehensive, action-oriented indicator of SM.
Because many people have multiple chronic conditions, the relative importance of the conditions may shift over time (13), and because SM may differ across conditions (9), we suggest first identifying the condition that is of most concern to consistently anchor responses. We also recommend focusing on the past 3 months to lessen recall problems (Table 2). Such questions could be used in any survey that ascertains whether respondents have a chronic disease.
Several of the recommendations of Ruiz et al (3) related to self-management education, a common cross-cutting strategy to facilitate transformation into a self-manager (10). As a secondary individual-level indicator, we suggest including a question about taking a course or class (Table 2).
Self-management support at the health system level
The most commonly recognized site for provision of SMS is within health care systems; the Institute of Medicine definition of SMS specifies only health care providers (14). SMS at this level can take the form of motivational interactions (eg, motivational interviewing), collaborative care planning strategies, tools to enhance the patient–provider interaction, self-management education programs, and referrals to community SMS resources (15). Goal-setting and action-planning feature prominently in many primary care quality improvement projects (16) and allow the clinician to help create the self-management plan (17).
Action planning, or collaborating with patients to develop an SM plan, is a key means of SMS and a key activity in most health care provider–based SMS strategies (15). Privacy concerns make it difficult to ascertain what happens in clinical encounters. Consequently, we propose an indicator to capture from health care providers how frequently action planning occurred in the past 7 days. A parallel indicator is available from the National Committee for Quality Assurance’s 2017 standards for recognition as a patient-centered medical home, which includes an elective element on developing a self-management plan (18). Because providing SMS is not a traditional part of health care provider training (19), we also recommend an indicator on specialized training in helping patients develop an SM plan (Table 2). These questions could be added to existing surveys of physicians or other health care providers.
Self-management support at the community level
Community resources are one of the pillars of quality improvement in the original (2) and in the Expanded Chronic Care Model (20). SMS at this level could be reflected by the availability, accessibility, and awareness of SMS programs or by community structures (coalitions, parks, greenspaces, access to appropriate foods) that support SM (5,6). Clinical–community linkages could be reflected in referrals to community programs.
We encountered difficulties enumerating SMS programs and supportive community structures (Table 1). We considered identifying a sentinel SM program (eg, diabetes SM programs  or the Stanford Chronic Disease Self Management Program ) and using number of programs listed on a centralized listing of available programs (ie, a program locator) as the indicator. However, as with using SM practices for only a single disease, we were concerned with the representativeness of one program.
To examine geography-based community availability measures, we explored the use of web-based search services (eg, Google Maps) to search for nearby SMS programs. However, searches for “self-management” or “managing X condition” returned little of value. Until there is a roster of SMS programs and robust program locators, developing an indicator based on the geography of SMS programs is not feasible.
We concluded that the most feasible indicator of community-level SMS was the availability of SMS programs in the community. Directly asking people with chronic disease if they were aware of a course appeared to be the most feasible way to measure community-level SMS, because it implicitly integrates awareness and availability. This question, used in combination with a question about taking a course (see individual-level secondary indicator in Table 2), could capture both access and uptake.
Self-management support at the policy level
Policy can be an effective facilitator of SM/SMS at all levels of the socio-ecological model and is highlighted in the Expanded Chronic Care Model (20). Many major changes in public health (eg, decreased smoking, increased use of seat belts) came from policy interventions. Policy can help reduce barriers or enhance facilitators such as SMS program availability or financing. Ruiz et al (3) suggested a focus on health care systems and health insurance policies; however, we identified multiple issues that rendered them infeasible (Table 1). Instead, we identified alternative approaches in health care professional training and certification, professional practice guidelines, and federal rules and grants.
Professional training and certification
Health professionals’ promotion of SM can influence patients’ use. However, most providers receive no formal training in SM/SMS (19). A content review of curriculum standards from the American Association of Colleges of Nursing (23) indicated no SMS-related standards. A survey of medical school curricula did not list SMS specifically, although some curricula included counseling for behavior change, which could be a component of SMS (24). Continuing medical education (CME) requirements for physician and nurse relicensure, on the other hand, is a potentially useful metric to follow (baseline = zero), given the ease in searching requirements and variation by state. Although some states dictate CME in certain topics (eg, pain management), none mention SMS (Table 2).
Professional practice guidelines
Treatment guidelines can reflect the integration of SMS into routine care delivery. PubMed provides a standardized searchable source for peer-reviewed literature, where physicians likely look for guidelines. Using the strategy shown in Table 2, we found mentions of SMS in practice guidelines for diabetes (n = 28), asthma (n = 6), arthritis (n = 4), chronic obstructive pulmonary disease (n = 1), and HIV (n = 1).
US government policy as reflected in the Federal Register
We found no ongoing inventory of federal activities or funding on SMS (Table 1). Monitoring issuance of federal government rules on SM/SMS over time can reflect policy changes. The Federal Register has a searchable database containing rules, notices, and proposed federal rules. Two searches (Table 2) of the database identified modest variability in numbers by year, but numbers were very low (Table 3).
Self-management support at the media level
Media coverage of SM/SMS could help set social norms and influence people with chronic disease to explore SM/SMS (5,10). We identified several impediments to exposure-based indicators proposed by Ruiz et al (3) (Table 1) but found that measuring volume of coverage was possible. Several services routinely monitor media streams (eg, newspapers, wire feeds). We searched ProQuest (ProQuest LLC) for English-language articles containing “self-management” and “condition” (specifying the list of chronic conditions ) from 2010–2016 in newspapers, wire feeds, or magazines. On the basis those results (Table 4), we concluded that using such a database with a consistent search strategy (Table 2) can reflect the volume of SM–related content.
We propose operationalized indicators for surveillance of SM/SMS at 5 levels of the socio-ecological model (Table 2). Measuring both SM and SMS is important, as is measuring SMS at multiple levels. SMS indicators could be considered process indicators for the eventual outcome of SM. If society effectively promotes SMS at multiple levels, more people with chronic disease may actively self-manage.
Identifying indicators that are a reasonable reflection of SM/SMS at each level was challenging (Table 1). A recurring constraint was our assumption that resources for such surveillance would be minimal. Thus, we limited ourselves to using existing surveys, systems, and databases rather than creating new surveillance systems as would have been required by the indicators proposed by Ruiz et al (3). Our proposed indicators provide only small glimpses of the big picture. Nevertheless, we believe they can provide useful information on SM/SMS status. Survey-dependent indicators will require cognitive testing.
Our proposed indicators of individual-level SM and community-level SMS rely on surveys of individuals with chronic diseases, such as the Behavioral Risk Factor Surveillance System. Local communities, health systems, or other organizations could gather data to reflect SM/SMS within their nexus of control. Surveillance of community-based SMS programs would be strengthened by development of consistent, accurate program-locator services, which could also facilitate program participation.
Two of our proposed indicators at the health system level (co-development of an SM plan and specialized training in SMS) require surveys of health care providers. Local health systems could survey their affiliated providers to assess SMS in their systems. One way to both strengthen surveillance and facilitate SMS delivery at the health system level would be the creation of Current Procedural Terminology codes within the Healthcare Common Procedure Coding System specific to chronic disease SMS (25).
We were unable to identify a strong surveillance indicator of SMS at the policy level. However, the indicators we proposed are promising because they are searchable and likely to detect change if consistent search strategies are used. Finally, we suggest surveillance of media coverage that includes mention of SM, and we identified a potential database for national-level surveillance. Similar media monitoring could be conducted at the state or local level by adding geographic restrictions to the search.
Consistent with the idea that “what gets measured gets done,” surveillance of SM/SMS can serve as both a progress report and a motivator for expansion (26). Gathering data directly from people with chronic conditions is essential to national and state surveillance to capture SM and SMS provided beyond the health care system. Inclusion of the proposed indicators into surveys like the National Health Interview Survey, Behavioral Risk Factor Surveillance System, and Medicare Current Beneficiary Survey and adding provider-based indicators to provider surveys would advance SM/SMS surveillance. Achieving the improved functional and clinical outcomes predicted by the Chronic Care Model (2,20,26) is unlikely without leadership and investment in promoting SM/SMS. Without surveillance, we will not know how far we have come or how far we have to go in making SM/SMS an integral part of health and health care.
The authors thank Richard Birkel, Casey Dicocco, Russell Glasgow, and Michele Spafford for valuable insights during preliminary discussions of one or more of these surveillance indicators. Dr Sacks was funded by a Centers for Disease Control and Prevention contract with the National Association of Chronic Disease Directors. The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the Centers for Medicare and Medicaid Services.
Corresponding Author: Teresa J. Brady, PhD, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, Mail Stop F-78, Atlanta GA 30341. Telephone: 678-357-4587. E-mail: email@example.com.
Author Affiliations: 1Division of Population Health, Centers for Disease Control and Prevention, Atlanta, Georgia. 2Sue Binder Consulting, Inc, Decatur, Georgia. 3Walden University, School of Health Sciences, Minneapolis, Minnesota. 4Center for Medicare and Medicaid Innovation, Centers for Medicare & Medicaid Services, Baltimore Maryland.
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