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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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5

Recommended Core Domains and Measures

During its foundational work (Chapters 14), the committee considered each domain individually. To recommend core measures of social and behavioral domains for inclusion in all electronic health records (EHRs), the committee sought to identify a parsimonious panel of measures that would be complete, interoperable, and efficient. To do so, it stepped back and considered overlap and interaction of domains. The stability of measures was also considered. The former considerations inform which combination of domains provides the best coverage of major determinants of health, while the latter informs how frequently the domains need to be assessed. The committee considered the suitability of available measures, first individually as described in Chapter 4, and then relative to one another as described in this chapter. Finally, the committee used a consensus process to construct a coherent panel and agree on recommended core measures.

OVERVIEW OF THE CANDIDATE DOMAINS

This section presents an overview of the candidate domains, organized by the levels in the committee’s conceptual outline presented in Chapter 2 (see Table 2-1). Table 5-1 summarizes the needed frequency of assessment as well as the ways that information about the domains might be used for direct patient care, by health systems and public health entities, and how it might be used by researchers.

The domains differ in their stability over a person’s life course. Sociodemographic characteristics of the person, which have implications for an individual’s resources and adverse exposures, are relatively unlikely to

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×

TABLE 5-1 Candidate Domains Organized by Levels and Suggested Frequency of Assessment

Level Domain Frequency of Assessment Examples of Use in Direct Care of Patient Examples of Use by Health System or Public Health Examples of Use in Research to Test
Sociodemographic

• Race and ethnicity

• Country of origin

• Education

• Employment

• Financial resource strain

■ General

■ Food insecurity

• Health literacy

• Sexual orientation

• Identity

• Behavior

• At entry

• At entry

• At entry

• Screen and follow up

• Screen and follow up

• Screen and follow up

• At entry

• Screen and follow up

• Screen and follow up

• Reduce risk level associated with few resources

• Service planning

• Characterize population

• Identify high-risk groups

• Interaction with census-tract variables

Behavioral

• Dietary patterns

• Physical activity

• Tobacco use and exposure

• Alcohol

• Screen and follow up for all these domains

• Reduce risk behavior via prescriptions, referral, motivational interviews

• Quality measure (rate of risk behaviors)

• Address obstacles (e.g., gym access)

• Mediating role in disparities

• Interaction with genetics

• Best ways to change behavior in subgroups

 

• Stress:

■ General

■ Childhood history (ACES)

• Negative mood and affect

• Screen and follow up

• At entry

• Take into account literacy in management of patients

• Reduction in risk level

• Service planning

• Characterize population

• Direct effects on disease onset, progression, and response to treatment

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×
Psychological

■ Depression

■ Anxiety

• Psychological assets

■ Conscientiousness

■ Patient engagement/activation

■ Optimism

■ Self-efficacy

• Screen and follow up

• Screen and follow up

• At entry

• By condition

• At entry

• By condition

• Setting goals for care

• Stress management

 

• Interaction with genetic factors

• Best ways to increase assets

Individual-Level Social Relationships and Living Conditions

• Social connections and social isolation

• Intimate partner violence

• Screen and follow up for these domains

• Reduce risk level (e.g., social work linkage to senior centers, support groups)

• Benefit of group visits

• Service planning (e.g., programs to engage socially isolated individuals)

• Direct effects on disease onset, progression, and response to treatment

• Interaction with genetic factors

Neighborhoods and Communities

• Patient address

• Use address to geocode median household income and racial/ethnic composition (census-tract)

• Verify every visit

• Update on address change

• Identify individual’s access to resources and exposure to hazards

• Identify resources and hazards affecting populations

• Role of built and social environment on health behaviors and on disease onset and progression

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×

change, especially once one reaches adulthood. Other risk factors are more fluid. Although some health behaviors are habitual, they may fluctuate on their own or in response to an intervention or treatment. Social relationships and affective states are likely to vary over time and with changing circumstances.

The stability of a domain affects the frequency with which it needs to be assessed for various uses. A stable domain (e.g., race and ethnicity) can be assessed once at entry; others (e.g., depression) require periodic screening with detailed assessment and follow-up on a positive screen. Still others (e.g., residential address) require verification at every visit. Frequency of assessment is a factor in evaluating the feasibility of including a measure of the domain in EHRs; a detailed assessment may be feasible if needed only at entry, but not if needed frequently. Similarly, domains that can be assessed with a brief screen with targeted follow up are more feasible than are in-depth assessments that need to be repeated.

The use of social and behavioral information made accessible in the EHR varies by level and domain. Assessing the risk associated with the patient’s profile should inform diagnosis and enable more effective treatment plans that set goals with patients for promoting health and reducing disability that take into account the patient’s social context, behaviors, and psychosocial risks (HealthIT.gov, no date). For some domains, interventions are already available for those identified at risk (e.g., stress management programs for those under chronic stress or cognitive behavioral therapy for depressed patients). However, acting on other domains will require the development and testing of efficient, cost-effective interventions. Public health entities and health systems should find the committee’s identified domains and measures useful for planning their services and characterizing their populations. Researchers can use the information to inform the design of interventions to (1) reduce health-damaging behaviors, attitudes, and emotional states; (2) to increase health-promoting ones; and (3) to address adverse social conditions.

Knowledge of social and behavioral determinants of health is useful in all clinical settings. Most frequently this information will initially be collected in primary care settings or by practitioners who have had a long-term relationship with the patient. Where there are large integrated health care delivery systems, multispecialty centers, or effective health information exchange, this information will be available to all practitioners in the system without the need to recollect data. Because of the current limits of interoperability across systems, many practitioners outside of an integrated system will not have the benefit of knowledge of their patients’ social and behavioral risks and resources unless they collect it themselves. Because these determinants may be important in the evaluation and treatment of problems seen by specialists (e.g., abdominal pain, headaches) as in primary

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×

care, the committee believes that health care professionals at all sites should have the ability to collect and add information to the EHRs in order to best treat and care for the patient.

In Chapter 6, the committee provides a more robust description of both the benefits and the challenges for a variety of stakeholders in obtaining the recommended social and behavioral information in the EHR. The levels in Table 5-1 reflect consideration of the processes that serve as pathways connecting domains at each level with “downstream” determinants of health. These processes are part of the conceptual models described in Chapter 2; they guided the committee’s work but were not explicitly identified and reviewed in detail as part of the committee’s charge. However, it is worth noting that the direct and indirect pathways connecting some domains to health have been subject to extensive scientific investigation, whereas other domains remain to have the key processes identified. Perhaps most proximal to health are the identified behavioral domains, which directly affect biological pathways affecting disease onset and progression. For example, smoking cigarettes harms nearly every organ in the body, making smoking the leading preventable cause of death in the United States (CDC, 2014). Health-related behaviors are, however, shaped by the more “upstream” domains whose effect on health may be direct and may be partially mediated by behavioral risks. For example, the likelihood that someone smokes is affected by the rates of smoking of those in her or his community, social norms about smoking, and policies such as taxation of tobacco products (IOM, 2011). Psychological domains may also have a direct effect on pathophysiological processes. For example, stress can elicit alterations in the sympathetic nervous system and the hypothalamic pituitary adrenal system, influencing inflammation, cellular aging, and immune function (Hawkley and Cacioppo, 2004; Smith and Vale, 2006). Psychological domains, such as optimism or conscientiousness, may also contribute to a patient’s desire or ability to carry out a prescribed treatment.

SUITABILITY OF THE MEASURES

Chapter 4 describes the process the committee used to evaluate the suitability of individual measures of each of the candidate domains for inclusion in all EHRs or for specific populations. The committee’s rating of each measure on four criteria and the overall committee judgment of the priority of including the measure in EHRs are summarized in Chapter 4. The four criteria can be collapsed into two dimensions reflecting the readiness of a measure for use in the EHR and the usefulness of having the information in the patient record for clinical, population management, and research purposes. Figure 5-1 displays all the measures the committee rated across these two dimensions.

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×

images

FIGURE 5-1 Standard domain measures by usefulness, minimum readiness, and committee judgment.
NOTE: Q = question(s); bolded items = measures routinely collected.

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×

The readiness axis reflects the ease of obtaining and storing information on a given domain; this is affected by the availability of a standard, freely available measure; the feasibility of attaining the information; and how sensitive the information is to collect. Readiness was quantified by taking the minimum of the committee’s ratings (1 = low, 3 = high) reported in Chapter 4 for any of the three criteria (availability of a standard measure, feasibility, and lacks sensitive information or causes patient discomfort). The committee considered using the average of those ratings. However, a weakness in any of these three criteria engendered caution about the readiness of a measure because a higher rating on one criterion does not offset weakness on another. Use of the minimum rather than the average score produced a graph more consistent with the committee’s overall judgment.

The usefulness axis was quantified by the committee rating (1 = low, 3 = high) of the usefulness of the information on that measure in the EHR for improving health outcomes reflecting broad applicability and usefulness in clinical settings. Figure 5-1 arrays where each measure falls on the committee judgment (low, moderate, high) and on two dimensions (usefulness and readiness). The symbol in front of each measure (◆ highest priority, images medium priority, ▲ lowest priority) represents the committee’s overall judgment of priority of including the measure in the EHR. The items bolded are domains that are routinely collected in EHRs.

Different measures of the same domain sometimes received different degrees of endorsement in usefulness and readiness. For example, a two-question screening measure (PHQ-2) on depression was rated as highly useful and highly feasible while the PROMIS-8b depression scale, which is longer and more useful for monitoring change in symptoms over time than as an initial screener, received lower ratings for feasibility and usefulness in all EHRs. Not surprisingly, measures in the upper-right quadrant (most favored on usefulness and on readiness) had the strongest endorsement from the committee members while those in the lower-left quadrant (least favorable on usefulness and readiness) were rated the lowest. Figure 5-1 makes clear that the committee placed more emphasis on overall rating on the usefulness of the data provided by a measure than on its readiness.

CONSTRUCTING A PANEL OF MEASURES

The committee’s statement of task included identifying the specific measures of social and behavioral determinants of health that should be included in all EHRs. In addition to identifying individual measures with the most favorable combination of usefulness and readiness, the committee aspired to construct a coherent panel that, taken together, would minimize overlap and fill gaps in knowledge about patients and populations. Rather than maximizing the usefulness of each individual measure, an ideal panel

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×

aims to identify a small set of measures that are easily implemented, are broadly applicable, are not redundant, and are representative of patients’ psychological and social states.

The term social vital sign has been used in the past primarily to indicate the social health of a population rather than that of an individual (Eichberg and Petry, 2009). The committee makes direct analogy between the physiologic vital signs and the psychosocial vital signs intending to create a parsimonious panel of characteristics that are easy to measure and broadly applicable to all individuals.

Physiological vital signs are readily accessible measures of a patient’s physiologic state. Traditionally, they have included body temperature, blood pressure, weight, heart rate, and respiratory rate. While one can imagine numerous other measures of the physiologic state, this small set can be measured quickly and accurately, and it provides a deep view of the patient’s physiological status that is relevant to most patients. Over the years, most diseases have come to be characterized in terms of vital signs because they are generally available.

For at least half a century, a set of social characteristics have also been collected during routine clinical evaluations and recorded in the chief complaint and social history sections of the clinician’s note (Delbanco et al., 2010). They generally include race (usually mixed with ethnicity), occupation, marital status, living situation, use of alcohol, use of tobacco, and recent unusual travel. This set is a starting point in the sense that many years of experience led to its creation. Nevertheless, evidence is lacking from the literature that any given set is the correct one and is clearly beneficial. Future research can test the usefulness of a coherent panel of “psychosocial vital signs” for diagnosing and treating various conditions as well as the contribution of single indicators.

Creating a parsimonious panel of recommended measures does not detract from the importance of measures that were not included. To the contrary, the others may also be useful in EHRs. The small panel tends to favor measures that are broadly applicable and important (and therefore are considered most useful), such as screening tools for important and common clinical conditions like alcohol abuse, tobacco use, and depression. A broader variety of measures are useful for less common conditions for which a minority of patients require screening and for monitoring progress of treatment on conditions that were previously screened. While these measures might not be presented for every clinical encounter or for every type of care provider, identifying standard measures that could be included in EHRs and collected as needed will still be useful (e.g., monitoring progress in depression treatment). The definition of a small panel does not detract from the definition of a more comprehensive panel for special cases or settings where a more detailed social assessment is indicated. Table 5-2

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×

TABLE 5-2 The Committee’s Analytic Process in Narrowing Domains and Measures to a Parsimonious Measurement Panel

Process Steps Method Results
Conceptual Framework Analysis Integrate models relevant to SBD of health (Figures 2-1 to 2-4) 5 Levels
Domain Identification From extensive list of SBD concepts identified domains for consideration (Table 2-1) 31 Domains
Candidate Domains Selection Applied criteria: strength of association with health; and clinical, population health, and research usefulness 17 Domains
Measure Identification Domain workgroups conducted literature reviews of measures Measure set identified based on psychometric properties 17 Domains/31 Measures
Parsimonious Measurement Panel Construction Applied criteria: readiness (standard measure, feasibility, lack of sensitive information); usefulness for inclusion in the EHR; and overall committee judgment 11 Domains/12 Measures

NOTE: EHR = electronic health record; SBD = social and behavioral determinants.

presents the committee’s analytic process, summarizing its efforts to reach its recommendations of which measures the committee identified as having high priority for inclusion in all EHRs.

What follows are the committee findings and recommendations regarding measures for inclusion.

COMMITTEE FINDINGS AND RECOMMENDED CORE DOMAINS

Finding 5-1: Four social and behavioral domains of health are already frequently collected in clinical settings. The value of this information would be increased if standard measures were used in capturing these data.

Recommendation 5-1: The Office of the National Coordinator for Health Information Technology and the Centers for Medicare & Medicaid Services should include in the certification and meaningful use regulations the standard measures recommended by this committee for

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×

four social and behavioral domains that are already regularly collected: race/ethnicity, tobacco use, alcohol use, and residential address.

Finding 5-2: The addition of selected social and behavioral domains, together with the four domains that are already routinely collected, constitute a coherent panel that will provide valuable information on which to base problem identification, clinical diagnoses, treatment, outcomes assessment, and population health measurement.

Recommendation 5-2: The Office of the National Coordinator for Health Information Technology and the Centers for Medicare & Medicaid Services should include in the certification and Meaningful Use regulations addition of standard measures recommended by this committee for eight social and behavioral domains: educational attainment, financial resource strain, stress, depression, physical activity, social isolation, intimate partner violence (for women of reproductive age), and neighborhood median-household income.

REFERENCES

CDC (Centers for Disease Control and Prevention). 2014. Smoking & tobacco use: Health effects of cigarette smoking. http://www.cdc.gov/tobacco/data_statistics/fact_sheets/health_effects/effects_cig_smoking (accessed August 1, 2014).

Delbanco, T., J. Walker, J. D. Darer, J. G. Elmore, H. J. Feldman, S. G. Leveille, J. D. Ralston, S. E. Ross, E. Vodicka, and V. D. Weber. 2010. Open notes: Doctors and patients signing on. Annals of Internal Medicine 153(2):121–125.

Eichberg, S., and D. Petry. 2009. Vital signs 2009—Measuring Long Island’s social health. Garden City, NY: Adelphi University.

Hawkley, L. C., and J. T. Cacioppo. 2004. Stress and the aging immune system. Brain, Behavior, and Immunity 18(2):114–119.

HealthIT.gov. no date. Benefits of electronic health records (EHRS). http://www.healthit.gov/providers-professionals/benefits-electronic-health-records-ehrs (accessed August 1, 2014).

IOM (Institute of Medicine). 2011. For the public’s health: Revitalizing law and policy to meet new challenges. Washington, DC: The National Academies Press.

Smith, S. M., and W. W. Vale. 2006. The role of the hypothalamic-pituitary-adrenal axis in neuroendocrine responses to stress. Dialogues in Clinical Neuroscience 8(4):383–395.

Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
×
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Suggested Citation:"5 Recommended Core Domains and Measures." Institute of Medicine. 2014. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Washington, DC: The National Academies Press. doi: 10.17226/18951.
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Determinants of health - like physical activity levels and living conditions - have traditionally been the concern of public health and have not been linked closely to clinical practice. However, if standardized social and behavioral data can be incorporated into patient electronic health records (EHRs), those data can provide crucial information about factors that influence health and the effectiveness of treatment. Such information is useful for diagnosis, treatment choices, policy, health care system design, and innovations to improve health outcomes and reduce health care costs.

Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2 identifies domains and measures that capture the social determinants of health to inform the development of recommendations for the meaningful use of EHRs. This report is the second part of a two-part study. The Phase 1 report identified 17 domains for inclusion in EHRs. This report pinpoints 12 measures related to 11 of the initial domains and considers the implications of incorporating them into all EHRs. This book includes three chapters from the Phase 1 report in addition to the new Phase 2 material.

Standardized use of EHRs that include social and behavioral domains could provide better patient care, improve population health, and enable more informative research. The recommendations of Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2 will provide valuable information on which to base problem identification, clinical diagnoses, patient treatment, outcomes assessment, and population health measurement.

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