Abstract
BACKGROUND:
A growing body of evidence supports the need for health systems to shift towards addressing social determinants of health (SDoH) as part of routine care. However, little is known about the state of the industry in terms of procurement and use of SDoH data.
OBJECTIVES:
To assess stakeholders’ perceptions and experiences in collecting and utilizing SDoH data.
METHODS:
A prospective, cross-sectional study was conducted using a 24-item electronic survey. The pilot-tested survey was distributed to a diverse convenience sample of 94 health care stakeholder organizations that are members of the Pharmacy Quality Alliance organization. Survey responses were collected from November to December 2020. Descriptive statistics were used to analyze responses.
RESULTS:
A total of 25 respondents completed the survey (response rate = 26.6%). More than half (n = 14, 56.0%) collected and tracked SDoH data, and of those, most (n = 6, 42.85%) reported using organization-specific tools instead of standardized SDoH tools. Economic stability and health and health care indicators were the most frequently identified types of SDoH data collected.
Participants reported that both identifying (mean = 3.88 ± SD = 0.88; 1 = not important to 5 = extremely important) and addressing (3.88 ± 0.93) patients’ SDoH were moderately important to their organization.
Lack of standard data format (72.0%), lack of time (52.0%), and lack of technological capabilities (44.0%) were the most commonly reported barriers to collecting SDoH data. However, value-based payment programs that reward addressing SDoH needs (76.0%) and a coding structure or reimbursement mechanism for identification and management of SDoH (60.0%) were most commonly reported as mechanisms to overcome SDoH data collection barriers.
CONCLUSIONS:
Health care stakeholders consider patient SDoH indicators important but report significant challenges in collecting these data. Solutions that address data standardization, time burden, technological barriers, and the offering of incentives could facilitate its collection and effective use.
Plain language summary
This survey assessed health care organizations’ capabilities to collect social determinants of health (SDoH) data. SDoH are nonmedical factors that impact health, such as housing or transportation. Twenty-five health care organizations participated in November and December 2020. Our findings highlight several barriers to collecting SDoH data and identify potential ways to overcome them. As SDoH have gained more attention, our results may be valuable to the development of future initiatives to improve SDoH data collection and use.
Implications for managed care pharmacy
Approximately half of health care organizations surveyed collect SDoH data. Stakeholders consider patient SDoH data important in their decision-making but report challenges in collecting SDoH data. Solutions that address data standardization, time burden, and technological barriers could facilitate SDoH data collection and effective use. A minority of participants reported using standardized SDoH data tools. Participants anticipated an increased focus on addressing SDoH in the future and suggest incentives to encourage collection under value-based payment programs.
Social determinants of health (SDoH are increasingly recognized as a priority by all health care stakeholders in various health care settings in the United States. The World Health Organization has defined SDoH as “the conditions in which people are born, grow, work, live, and age, as well as the set of forces and systems that shape daily life.”1 Such conditions are essentially formed by socioeconomic status and a variety of environmental factors.2 Healthy People 2030 framed SDoH in 5 key areas: (1) economic stability, (2) education access and quality, (3) social and community context, (4) health care access and quality, and (5) neighborhood and built environment.3 A growing body of evidence illustrates that the contradiction between high medical expenditures and poor health outcomes in the United States can be partly attributable to the lack of attention to SDoH components in health care systems.4 Therefore, addressing patients’ social needs as a part of routine care should be emphasized as a long-term solution to improve patient outcomes.
In January 2021, the Centers for Medicare & Medicaid Services (CMS) issued guidance to reinforce the adoption of strategies that address SDoH in Medicaid and Children’s Health Insurance Program beneficiaries to ultimately yield improved health outcomes, reduced health disparities, and lower overall costs.5 A review of studies that examined US-based programs that addressed SDoH revealed positive impacts on social needs in spite of mixed patient uptake of the programs. The interventions targeted patients with high social needs in clinical settings or as a part of the health care delivery or payment system. Common examples of social needs were insecure housing, access to education, economic security, access to childcare, and food insecurity. Subsequently, they provided services to meet those needs or linked patients to community-based social services organizations. The review reported primarily positive outcomes across the variety of factors (eg, clinical metrics, cost, and health outcomes).6
Given the increasing focus on the need to consider SDoH more broadly, there is a paucity of information about the extent to which health care stakeholders currently collect SDoH data and how they are using these data to support patient care and outcomes. This study aimed to assess SDoH data collection capabilities of various health care stakeholders, identify barriers and facilitators for building these capabilities, identify SDoH data collection and use, identify high-priority SDoH areas for health care stakeholders, and determine the extent to which SDoH data capture and assessment are involved in organizational decision-making.
Methods
A prospective, cross-sectional study was conducted using an electronic, self-reported, 24-item survey (Supplementary Exhibit 1 (96.1KB, pdf) , available in online article). Three SDoH subject matter experts from diverse stakeholder groups (ie, pharmacy, health plan, and technology vendor) provided input on the development of the survey prior to pilot testing using the electronic platform. Another set of 3 members chosen from the same stakeholder groups pretested the survey for clarity and completeness, and slight modifications to the survey were made.
The survey included questions about data collection (n = 9), SDoH tools (n = 4), importance of SDoH data in organizational decision-making (n = 4), barriers and facilitators pertaining to SDoH data collection and use (n = 3), and respondent characteristics (n = 4). Items utilized unipolar response scales (eg, not at all = 1 to extremely = 5) to assess levels of familiarity, importance, usefulness, and involvement, from respondents.
A convenience sample of 94 Pharmacy Quality Alliance (PQA) members was used in this study. PQA is a multistakeholder, national quality organization working to advance the quality of medication use and is comprises health care stakeholders, including technology vendors, pharmacies, and health care plans, among others. The survey was distributed via email to solicit voluntary participation. No incentives were offered for completing the survey. Data collection occurred from November to December 2020 and used 3 reminder emails.
The study was approved by the University of Texas at Austin Institutional Review Board.
Results
ORGANIZATION CHARACTERISTICS
A total of 25 health care stakeholders participated in this survey (response rate = 26.6%). Organizational characteristics representing the survey respondents are available in Table 1.
TABLE 1.
Organization Characteristics
| Organization characteristics (N = 25) | Frequency (%) |
|---|---|
| Organization type | |
| Pharmacy | 7 (28) |
| MTM vendors | 4 (16) |
| Health technology vendor | 4 (16) |
| Health plan | 4 (16) |
| Pharmacy benefit manager | 3 (12) |
| Specialty pharmacy provider | 2 (8) |
| Health system | 1 (4) |
| Regions covered by organization | |
| South Atlantic (DE, DC, FL, GA, MD, ND, SC, VA, and WV) | 15 (60) |
| East North Central (IN, IL, MI, OH, and WI) | 15 (60) |
| Middle Atlantic (NJ, NY, and PA) | 14 (56) |
| Pacific (AK, CA, HI, OR, and WA) | 13 (52) |
| West South Central (AR, LA, OK, and TX) | 12 (48) |
| New England (CT, ME, MA, NH, RI, and VT) | 12 (48) |
| Mountain (AZ, CO, ID, NM, MT, UT, NV, and WY) | 11 (44) |
| West North Central (IA, KS, MO, NE, ND, and SD) | 11 (44) |
| East South Central (AL, KY, MS, and TN) | 11 (44) |
| Othera | 4 (16) |
| Organization size | |
| For pharmacy participants | |
| < 5 stores | 1 (4) |
| 31-125 stores | 2 (8) |
| > 500 stores | 5 (20) |
| For nonpharmacy participants | |
| 10,000-49,999 lives | 1 (4) |
| 100,000-499,999 lives | 1 (4) |
| > 1,000,000 lives | 12 (48) |
aResponses to “other” included national and Canada.
AK = Alaska; AL = Alabama; AR = Arkansas; AZ = Arizona; CA = California; CO = Colorado; CT = Connecticut; DC = District of Columbia; DE = Delaware; FL = Florida; GA = Georgia; HI = Hawaii; ID = Idaho; IL = Illinois; IN = Indiana; IA = Iowa; KS = Kansas; KY = Kentucky; LA = Louisiana; MA = Massachusetts; MD = Maryland; ME = Maine; MI = Michigan; MO = Missouri; MS = Mississippi; MT = Montana; MTM = medication therapy management; NC = North Carolina; ND = North Dakota; NE = Nebraska; NH = New Hampshire; NM = New Mexico; ND = North Dakota; NJ = New Jersey; NV = Nevada; OH = Ohio; OK = Oklahoma; OR = Oregon; PA = Pennsylvania; RI = Rhode Island; SC = South Carolina; SD = South Dakota; TN = Tennessee; TX = Texas; UT = Utah; VA = Virginia; VT = Vermont; WA = Washington; WV = West Virginia; WY = Wyoming.
ORGANIZATIONAL SDoH CAPABILITIES
Approximately half (n = 14, 56.0%) of the respondents collected and tracked SDoH data and about a third (n = 8, 32%) partnered with community support organizations to address patients’ unmet social needs. Among those that collected and tracked data, 5 organizations integrated publicly available risk assessment data as part of their organization’s SDoH strategies. The reported intent of capturing SDoH data was to improve health outcomes for patients (n = 14, 56%), expand value-added services offered to patients (n = 11, 44%), increase patient engagement (n = 10, 40%), implement programs that address SDoH (n = 8, 32%), reduce costs for the organization (n = 7, 28%), reduce costs for patients (n = 7, 28%), increase patients’ retention (n = 5, 20%), and share data with others to address barriers (n = 5, 20%).
Six organizations (24%) reported linking SDoH data with patients’ and enrollees’ health outcomes to support segmentation and prioritization strategies (eg, targeted intervention for medication adherence based on SDoH data) (n = 5, 20%), patient referrals to community-based resources (n = 4, 16%), identification of opportunities and gaps for future interventions (n = 3, 12%), and implementation of pilot programs for risk adjustment based on SDoH data (n = 1, 4%).
SDoH DATA COLLECTION TOOLS
The most common SDoH indicators collected were economic stability (n = 8, 32%), health and health care (n = 8, 32%), neighborhood and built environment (n = 7, 28%), education (n = 5, 20%), social and community context (n = 5, 20%), and other indicators (n = 4, 16%), including patient demographics, and datasets that support SDoH identification activities.
Respondents reported using the following tools to collect SDoH data: organization-specific tools (n = 6, 24%), Z codes from the International Classification of Diseases, Tenth Revision, Clinical Modification (n = 2, 8%), the Accountable Health Communities (AHC) Health-Related Social Needs Screening Tool (n = 2, 8%), the Milliman Clinical Guidelines (n = 1, 4%), the Health Leads Screening Toolkit (n = 1, 4%), and Epic’s SDoH tool (n = 1, 4%). Other SDoH data tools, such as PRAPARE (Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences), American Academy of Family Physicians Social Needs Screening Tool, and Upstream Risks Screening Tool & Guide, were not utilized by respondents.
The SDoH data tools were most commonly used via surveys (n = 6, 24%), electronic medical record systems (n = 5, 20%), and other processes (n = 5, 20%), including inhouse system, claims data, government sources, and mobile applications.
IMPORTANCE OF SDoH DATA
Participants reported familiarity with SDoH (mean= 4.28 ± SD = 0.67) on a scale of 1 = not all familiar to 5 = extremely familiar. This scale from 1 to 5 was also implemented for questions assessing importance and usefulness. Identifying (mean = 3.88) and addressing (mean = 3) patients’ SDoH were both moderately important to organizations. In the past 12 months, addressing social needs of patients was somewhat involved in organizations’ decision-making (mean = 3.28), but respondents reported that involvement is expected to increase over the next 12 months (mean = 3.84) and even more in 3-5 years (mean = 4.12).
The stakeholders found SDoH data somewhat useful (mean = 2.78) to inform their organizational strategies. Based on responses, the stakeholders looked inward when considering engagement approaches to address SDoH. This was reflected in higher responses to taking organizational-focused approaches (n = 19, 76%) over community- (n = 12,48%) and individual-level (n = 12, 48%) engagement approaches. Only 3 (12%) organizations thought they should have no direct action in addressing SDoH.
BARRIERS AND FACILITATORS OF SDoH DATA COLLECTION
Figure 1 shows the perceived barriers to SDoH data collection by stakeholders. These included lack of standard data format (n = 18, 72%), lack of time (n = 13, 52%), and lack of technological capability (eg, lack of interoperability) (n = 11, 44%). Organizational activities that were being implemented to overcome these barriers included provider training (n = 6, 24%), adopting new technological capabilities (n = 6, 24%), dedicating time (n = 5, 20%), adopting a standard data format (n = 5, 20%), adopting standard definitions (n = 4, 16%), appropriating budget (n = 4, 16%) to collect SDoH data, and other strategies (n = 3, 12%), such as the use of different types of datasets that contain SDoH-related information. Given all of these various activities reported by certain stakeholders, nearly half of respondents did not implement solutions to overcome barriers to SDoH data collection (n = 12, 48%).
FIGURE 1.
Frequency of Barriers to SDoH Data Collection Indicated by Stakeholders (N = 25)
Respondents indicated incentives that would encourage organizations to address SDoH, which included value-based payment programs that reward closing of gaps in SDoH needs within target patient and enrollee populations (n = 19, 76%), a coding structure or reimbursement mechanism for identification and management of SDoH (n = 15, 60%), quality-reporting opportunities that integrate SDoH measures (n = 12, 48%), organization-specific research that shows the cost-effectiveness to the organization in addressing SDoH needs (n = 10, 40%), and organization-specific research that shows improvement in quality of care by addressing SDoH needs (n = 7, 28%). Two (8%) stakeholders offered other incentives, such as more funding and more interest from clients in addressing SDoH in the industry.
All participants felt that CMS will play a significant role in encouraging health plans to address SDoH in the next 3-5 years. PQA (n = 18, 72%) was identified as playing an influential role by a majority of respondents, followed by other organizations, such as America’s Health Insurance Plans (n = 5, 20%), the National Quality Forum, and the National Committee for Quality Assurance (n = 2, 8%).
Discussion
The primary objective of this study was to explore health care stakeholders’ experiences in collecting and utilizing SDoH data. Overall, our research found that stakeholders, although familiar with SDoH and aware of their importance, face challenges with collecting SDoH data. This highlights opportunities for system-wide collaborative efforts, such as the Gravity Project, to help standardize SDoH data–leveraging electronic health record data systems.7
The moderately low rate of organizations that collect SDoH data highlights an important need in the US health care system. Although there are some payer models with incentives to identify SDoH for their beneficiaries,8 there is an unmet need for more systematic payer-driven incentives to encourage a broader role of SDoH in organizations’ strategies. Indeed, stakeholders acknowledged that addressing SDoH will be increasingly involved in the organization’s future decision-making, especially with the implementation of value-based payment programs that reward addressing SDoH to improve outcomes.
The perceived time burden and infrastructure issues related to collecting SDoH data reported in this study are in line with a recent qualitative case study of Medicaid Accountable Care Organizations.9 A Massachusetts-based study reported challenges to addressing SDoH were related to items such as high caseloads, time limitations, inefficiencies in tracking, lack of community resources, and multiple sociodemographic patient characteristics. On the other hand, facilitators that may help overcome those barriers were reported as sustaining updated resource lists, partnering with community organizations, employee engagement strategies, and a positive relationship with patients.9
Within our study, only one-third of the stakeholders reported partnering with community-based support groups to address social needs. This is an important gap that needs to be addressed. It is crucial for key stakeholders to collect and track SDoH data to ultimately identify and direct patients to accessible solutions to promote health and health equity. A growing number of initiatives have recently emerged to address SDoH within health and nonhealth sectors.10 Connecting individuals with social needs with community services to address those needs is a short- and potentially long-term solution for this purpose.10 Robust SDoH data are a cornerstone to initiate such connection. Allocating resources to address SDoH before collecting the data can also avoid creating frustration and distress among both patients and providers once gaps are identified.11
Our finding that approximately half of organizations are currently collecting SDoH data also points to a need for acceleration of tool set development for capturing these data within patient populations. Enhancing current tools and leveraging social platforms to collect data can optimize both collection and assessment of SDoH data to identify gaps for better decision-making within organizations.
Additionally, our study highlighted that many standard SDoH tools are underutilized among organizations. We found that organizations preferred to develop and use their in-house screening SDoH tool because of a perceived lack of any uniformly accepted data tool. Some readily available SDoH screening tools listed in our survey, such as PRAPARE, American Academy of Family Physicians Social Needs Screening Tool, and Upstream Risks Screening Tool & Guide, are not being widely used among the respondents. Other tools, such as Z codes, AHC Health-Related Social Needs Screening Tool, and Milliman Clinical Guidelines, are also underutilized. Underutilization of standardized tools is a challenge for valid data aggregation across practices and communities, which potentially enables integrating SDoH data in clinical care, quality improvement, and research.12
Survey respondents also highlighted concerns over a lack of data standardization, impacting both how we identify care gaps and how to monitor improvements in addressing those care gaps. Although emerging technology and advanced analytics can be the first step to systematically capture what SDoH data are available in electronic medical records, the financial cost and lack of standardized SDoH definitions remain as challenges to more widespread SDoH data collection.13 Different screening instruments have been developed to assess an individual or multiple SDoH in clinical settings.14 In fact, many tools have been developed and validated to screen multiple SDoH in patient populations, resulting in various measures, indices, and mapping tools. However, health care stakeholders have not reached a consensus to consistently use these tools and indices across different organizations.15
Finally, the development of reimbursement and policy incentives for the collection of SDoH data is lacking.16 Health care organizations may fail to adequately consider how collecting and leveraging SDoH data can maximize overall population health and improve patient outcomes. Value-based payment systems, which are currently expanding, can potentially create a workable framework for this purpose.12 Thus, understanding the current status of SDoH data collection capabilities of key stakeholders remains critical to enhancing tool development, establishing SDoH data standardization, and providing financial incentives for their collection by incorporating SDoH metrics into value-based frameworks.
LIMITATIONS
This study has several limitations. First, the self-reported survey was subject to social desirability bias, which may have been minimized through anonymity of responses. Second, because of convenience sampling of PQA members, this study was subject to selection bias, which limits the generalizability of our findings to health care organizations that are not PQA members and those without a primary focus on medication safety, as is the case with PQA and its members. Finally, although we had a relatively small sample size and acknowledge the limitation inherent in attaining broader generalizability, many of our respondents represented organizations with national reach in terms of patient geographical locations and physical locations and sites.
Conclusions
Although stakeholders were familiar with SDoH and aware of its importance, only about half collected and tracked SDoH data because of barriers, including a lack of a standard SDoH data format, lack of time, budget constraints, and concerns over technological capabilities. Most standard SdoH screening tools available in the marketplace were underutilized among survey respondents, and most did not report near-term solutions to overcoming the common barriers. However, stakeholders anticipated more involvement of SDoH data in organizations’ strategies in the future through integration into value-based programs that reward addressing SDoH in patient populations.
This research provides a snapshot of the current state of SDoH data collection in key health care stakeholders settings. The results of our research pinpoint opportunities for policymakers and stakeholders to develop incentives and standards, improve tools, and promote strategies to address common barriers in the collection and use of SDoH data to ultimately improve patient and population health.
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