Abstract
Background: “Social determinants of heath” (SDHs) are nonclinical factors that profoundly affect health. Helping community health centers (CHCs) document patients' SDH data in electronic health records (EHRs) could yield substantial health benefits, but little has been reported about CHCs' development of EHR-based tools for SDH data collection and presentation.
Methods: We worked with 27 diverse CHC stakeholders to develop strategies for optimizing SDH data collection and presentation in their EHR, and approaches for integrating SDH data collection and the use of those data (eg, through referrals to community resources) into CHC workflows.
Results: We iteratively developed a set of EHR-based SDH data collection, summary, and referral tools for CHCs. We describe considerations that arose while developing the tools and present some preliminary lessons learned.
Conclusion: Standardizing SDH data collection and presentation in EHRs could lead to improved patient and population health outcomes in CHCs and other care settings. We know of no previous reports of processes used to develop similar tools. This article provides an example of 1 such process. Lessons from our process may be useful to health care organizations interested in using EHRs to collect and act on SDH data. Research is needed to empirically test the generalizability of these lessons.
- Community Health Centers
- Data Collection
- Electronic Health Records
- Primary Health Care
- Referral and Consultation
- Social Determinants of Health
Numerous health outcomes are influenced by the social and physical characteristics of patients' lives. These “social determinants of heath” (SDHs) can affect health via diverse mechanisms (eg, chronic stress, hampering patients' ability to follow care recommendations).1 This impact is so great that addressing SDHs may improve health as much as addressing patients' medical needs.2⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓–21
The Institute of Medicine (IOM) recommended that 10 patient-reported SDH domains (and 1 neighborhood/community-level domain) be documented in electronic health records (EHRs)22,23 (Table 1). These domains were selected based on evidence of their health impacts; their potential clinical usefulness and ability to put into action; and the availability of valid measures. Some of these domains (eg, race/ethnicity) are already regularly collected by federally funded clinics; others (eg, social isolation, financial resource strain) are not. The Centers for Medicare & Medicaid Services intended that the IOM's report inform stage 3 meaningful use EHR incentive program requirements. Related to this, the Medicare Access & CHIP Reauthorization Act of 2015 and Centers for Medicare & Medicaid Services' 2016 Quality Strategy both emphasize care providers identifying and intervening in SDH-related needs. In addition, the Health Resources and Services Administration and the Office of the National Coordinator for Health Information Technology have both indicated that SDH data collection should continue to expand as part of federally qualified health center reporting, and may become required for EHR certification.24⇓⇓⇓⇓–29
Institute of Medicine Phase 2 Report: Summary of Candidate Domains for Inclusion in All Electronic Health Records
Systematically documenting patients' SDH data in EHRs could help care teams incorporate this information into patient care, for example, by facilitating referrals to community resources to address identified needs. This could be especially useful in “safety net” community health centers (CHCs), whose patients have higher health risks than the general US population.23,30⇓⇓⇓⇓⇓⇓⇓⇓–39 Many CHCs already try to address patients' SDHs, but their approaches to doing so have historically been manual and ad hoc.40⇓⇓⇓–44
EHRs present an opportunity to standardize the collection, presentation, and integration of SDH data in CHCs' clinical records.45 Toward that end, a national coalition of CHC-serving organizations created the “Protocol for Responding to and Assessing Patient Assets, Risks, and Experiences” (PRAPARE), which included a preliminary SDH data collection tool informed by the IOM's phase 1 report.45 PRAPARE includes most of the IOM-recommended domains and a few additional questions specific to CHC populations. Building on PRAPARE and the IOM recommendations, our study team asked CHC stakeholders about their opinions on how to optimize SDH data collection, documentation, and presentation in CHCs' EHRs, and on how they would like to use EHR tools to act on identified SDH-related needs, for example, by making referrals to community resources. This article describes our process and its results. We know of no previously published reports of processes used to develop EHR-based SDH data collection, summary, and referral tools, and therefore we present this article as an example that may inform others.
Methods
This work was conducted at OCHIN, a nonprofit community-based organization that centrally hosts and manages an Epic© EHR for >440 primary care CHCs in 19 states; it is the nation's largest CHC network on a single EHR system. Socioeconomic risks of patients in OCHIN member CHCs are clear from SDH data that are already collected: 23% are uninsured and 58% are publicly insured, 25% are nonwhite, 33% are of Hispanic ethnicity, 28% are primarily non–English speakers, and 91% are from households living <200% below the federal poverty level (among patients with available data).
The processes described here constituted the first phase of a pilot study designed to develop EHR-based tools that CHCs could use to systematically identify and act on their patients' SDH-related needs. We call these the “SDH data tools.”
With the goal of creating SDH-related workflows that parallel clinical referral processes, we began with the assumption that addressing patients' SDH needs require 5 key steps: (1) collecting SDH data; (2) reviewing patients' SDH-related needs; (3) identifying referral options to address those needs; (4) ordering referrals to appropriate services; and (5) tracking outcomes of past referrals. This assumption was based on team members' knowledge of the CHC workflows used to refer patients to specialty medical care.
We also considered the following factors:
CHCs are federally required to collect certain SDH measures from the IOM list, including race/ethnicity, tobacco/alcohol use, and depression. Our SDH data tools had to incorporate these data, without requiring duplicate data entry.
CHCs have varying staffing structures, resources, and workflows. To accommodate this, SDH data tools should be accessible to various team members (eg, front desk, medical assistants, community health workers, behavioral health staff).
SDH tools should use existing EHR-based functionalities to facilitate their adoption. Table 2 describes the options we initially considered to address each of these 5 steps.
Many CHCs already identify or address SDH needs using ad hoc methods. Some may already have mechanisms for tracking local resources, such as a 3-ring binder or files on a shared drive; some use online resources (eg, United Way 2-1-1, local department of human services). We sought to incorporate existing resources into our SDH referral tools.
Options Considered for Addressing Each of the Five Steps Involved in Using Social Determinants of Health Data in Community Health Centers
We recruited 3 OCHIN CHCs in Oregon and Washington as pilot sites and project partners. We also engaged OCHIN′s Clinical Operations Review Committee (CORC)—a group of CHC clinicians who collectively review proposed changes to their shared EHR—in all process steps. We conferred with leaders from PRAPARE, Kaiser Permanente (KP), Epic, and other national SDH experts (see the Acknowledgments). These stakeholders were asked to discuss 3 overarching questions.
1. Which SDH Domains Should be Included?
The CORC reviewed the IOM-recommended SDH domains and the wording for each domain, additional questions or alternate wording from PRAPARE and KP's SDH screening tools, and other domains currently collected in OCHIN′s EHR that were not in the IOM/PRAPARE recommendations. Based on these options, they chose which patient-reported SDH measures to include and the specific wording for each included domain. Geocoded domains were not considered, as the CORC felt they were not readily actionable. The pilot CHCs were present at most of the SDH-related CORC meetings.
2. How Do Care Teams Want to Collect, Review, and Act on Data on Patients' SDH Needs within the EHR?
We asked CORC members whether and how their clinics monitor patients' SDHs and what the SDH-related EHR tools should include. We presented options for how the SDH data could be collected and summarized using existing EHR structures, and we considered how existing tools aligned with the 5 key steps described above. We then mocked up a set of SDH data EHR tools and proposed workflows for using them. We presented the mock-ups and draft training materials to the CORC over multiple meetings, and to each of the pilot CHCs at staff meetings. We asked diverse CHC staff for critical feedback on the draft tools, suggestions for and potential barriers to collecting and acting on SDH data using the tools, and how best to train CHC staff in their use. Our team's Epic programmer attended these meetings to provide real-time input about the technical feasibility of any suggestions. The SDH data tools were revised based on the feedback received, and the pilot CHCs' various workflows and staff structures were considered. The revised tools were presented to the CORC (in person) and the study sites (via webinar) to verify that the revisions addressed requested changes.
This review and refinement process aligns with best practices for technology development,47 for example, user participation and prototyping.48⇓⇓⇓⇓⇓⇓–55 Evidence shows that for technology to be used effectively and as intended, end users must find it easy to use and must perceive that the technology will improve efficiency.56⇓–58 Therefore, we sought input from end users in order to increase the probability that the tools would be used.47 The EHR tools were then built in OCHIN′s testing environment, an off-line, internal “copy” of the EHR, and tested by an OCHIN quality assurance analyst.
3. How Can Care Teams Ensure That Patients Receive Up-to-Date Referrals?
The CHCs hoped to avoid referring patients to local resources that were not currently accepting new clients (service agencies sometimes close enrollment because of demand) or that had limitations about who could be assisted (eg, some services are not open to persons with past felonies). We discussed the options and approaches for identifying resources described above. We also conferred with colleagues at KP who were considering similar choices, and we spoke with representatives from organizations that create databases of community resource information (eg, United Way 2-1-1, Health Leads, and Purple Binder) to understand those options. The 3 pilot clinics then identified 3 to 5 prioritized SDH domains for which they wanted a list of community resources; based on these preferences, we provided lists of local resources for housing, food, transportation, social isolation, and intimate partner violence.
Participants
Participants from our study clinics consisted of primary care providers (n = 3), medical assistants (n = 5), clinic managers (n = 3), community health workers (n = 4), behavioral health staff (n = 2), nurses (n = 5), referral specialists (n = 3), EHR specialists (n = 3), and medical directors (n = 2).
Timeline
The development process took 10 months. Five 1-hour meetings with the CORC were held over the course of 6 months in order to reach consensus on which SDH domains to include and how the tool would function. The pilot sites were then given 6 weeks to test the tools for functional errors.
Results
Which SDH Measures?
Our stakeholders asked that the SDH tools include all the patient-reported IOM-recommended domains, made minor adaptations to the wording on some of these domains, and added a few questions (Tables 1 and 3). For example, the IOM's single question on financial resource strain asks, “How hard is it for you to pay for the very basics like food, housing, heating, medical care, and medications?” (not hard at all, somewhat hard, very hard). Because CHCs treat low-income patients, many of whom are likely to screen positive for financial hardship, the CHC stakeholders wanted to augment this broad question with more granular questions about specific areas of strain (eg, food, utilities, transportation). The hope was that this granularity would identify the specific areas in which assistance was needed. The stakeholders also preferred to not use the IOM-recommended screening tool for intimate partner violence; they considered its questions too sensitive for general SDH screening. They opted for a broader question about exposure to violence that was taken from KP's SDH questionnaire. They also opted to add 2 questions on social isolation from KP's questionnaire (eg, “How often do you feel lonely or isolated from those around you?”; “Do you have someone you could call if you needed help?”), along with the IOM-recommended questions on social isolation. They also added a question on preferred learning style (eg, reading, listening, viewing pictures).
Social Determinant of Health Domains and Measures Included in the ASSESS Tool and Overlap with Institute of Medicine–Recommended Domains and Measures
Collecting SDH Data
Stakeholder feedback, and our understanding that CHC workflows vary, indicated the need to enable SDH data collection by different care team members. Because EHR security measures limit which staff can access aspects of the EHR (for example, front desk staff often cannot access the problem list), we created several options for SDH data entry:
SDH “documentation flowsheets” were accessible to front desk staff at check-in, rooming staff, or community health workers (Figure 1).
Article versions of the SDH questions, in English or Spanish, that can be printed out and handed to the patient to complete at check-in or rooming, were provided on OCHIN′s member wiki site. These data would have to be hand-entered by CHC staff into 1 of the EHR flowsheets described above.
A questionnaire on the patient portal allowed patients who had an online portal account to be emailed and asked to enter the data online before a visit. The EHR's panel management tool can identify patients with pending visits and enable bulk secure messages to these patients. Within the portal, patients can choose navigational instructions in Spanish, but the screening questions are available only in English.
Social determinants of health flowsheet in EPIC.
We discussed various considerations during this process:
Making an electronic tablet available in the clinics' waiting rooms or examination rooms, on which patients could complete their SDH screening. Two of the pilot CHCs decided it would be too complex to manage, for example, identifying who would be the tablet's “keeper,” where it would be stored, and how to identify which patients should use it.
Creating a setting on the computer in the examination room where patients could sign up for a patient portal account then complete the SDH data through the portal immediately. In the end, this proved unfeasible because the patient must be sent the questionnaire after they sign up for the portal, necessitating an impractical multistep workflow.
Clinicians did not want to collect SDH data themselves, preferring to transfer that responsibility to another team member. Two of the pilot sites opted to use the Article forms for data collection, then have a staff person enter the data into the EHR. This approach creates potential workflow barriers to use of the SDH tools, because until the responses are manually transferred into the chart, the data will not be available to care team members to act on during the encounter.
All options for reminding the team to conduct SDH screening were considered inadequate. Clinics said that best practice advisories (also known as alerts) are largely ignored. They preferred health maintenance advisories (HMAs), which are closely integrated into clinic workflows. However, HMAs must be standardized across all clinics using a shared EHR; because a universal HMA was not possible, HMAs were not a feasible option.
Similar to other screening questionnaires administered in clinical settings, clinics asked that the patient-facing data collection form not include a “refuse to answer” option. The staff-entered methods did include this option.
Reviewing Data on Patients' SDH Needs
SDH data might be collected via multiple routes, and certain SDH data are already collected regularly by most CHCs. Thus, there was a need for an EHR-based summary that contains all of a patient's SDH data. We created an SDH data summary that is automatically populated with data from any of the SDH data entry options and from SDH-related data elsewhere in the EHR. The SDH Summary also shows any SDH-related International Classification of Diseases, Tenth Revisions (ICD-10), codes from the patient's problem list and any past SDH referrals if they were associated with an SDH-related ICD-10 code (see more on this in “Tracking Past Referrals,” below). “Positive screens” for SDH needs are visually highlighted. The algorithm used to identify positive screens is shown in Table 4. This summary could be accessed in 2 ways:
An SDH Summary tab can be accessed in an open Office Visit or Patient Outreach encounter. The most recent SDH data for the patient is displayed, and the date(s) of data collection and referral are shown (Figure 2).
A view in the EHR's Synopsis window can be accessed in a closed chart or open encounter displays a patient's SDH questionnaire responses over time, both as text and graphically (Figure 3).
Social determinants of health summary tab.
Social determinants of health summary in Synopsis.
Algorithm for Identifying Positive Social Determinant of Health Screens
For technical reasons, it was not feasible to show problem list data or referrals in the Synopsis version of the SDH Summary. Thus, each summary had information that the other lacked; that is, 1 had past referral information but only the most recent SDH data for a given patient; the other did not have past referrals but did present patients' SDH history, rather than just their most recent SDH data.
Identifying Referral Options
The pilot CHCs already had lists of SDH-related local resources in binders or on shared drives. These were not updated systematically, but rather only when someone on the team received new information and thought to update the list. The options for how CHC teams could do this systematically, using EHR-based tools, are shown in Table 2. All of them would be accessed via a hyperlink on the SDH Summary.
The preference list option was selected for several reasons. Creating linkages to an external agency's website was cost-prohibitive and required organizational contracts; thus, the study clinics might learn to rely on something that would incur costs after the study. Furthermore, some searches on these websites yielded results that were not specific to a location but rather gave statewide or nationwide data. The wiki options were rejected because users would have to leave the EHR system to access them, and the study sites were concerned about how to ensure that these documents were updated. The preference lists, however, used the same EHR function that the CHCs used for other referrals; involved discrete data fields, creating trackable data; and built on the CHC teams' local knowledge. One concern about the preference lists was that they must be updated manually. However, the study CHCs currently designate a staff member to update other preference lists (eg, for ordering laboratory tests), and the same person could be responsible for updating the SDH lists.
We helped the study clinics create “starter” preference lists for the SDH areas they prioritized (Figure 4). The resources listed in each were populated with data from each clinic's current method for keeping such information, then augmented by Web searches and reviewed by staff. The lists include names and contact information of relevant services and agencies, and include information such as “women and children only” and hours of operation, when available.
Social determinants of health preference lists.
Ordering Referrals
The SDH referrals preference lists can be used to make internal referrals (eg, to a community health worker), have clinic staff facilitate external referrals (eg, calling an agency to schedule an appointment for the patient), or share agency information with patients at the encounter or in the after-visit summary so patients can follow up on their own. To make these easier to use, we created a new referral priority option of “no follow-up needed,” which, if selected, informed CHC staff that they were not required to follow up on SDH referrals as they would for others. We also created a new referral type—“community referral, nonmedical”—so that SDH referrals would be excluded from related care quality measures. Another consideration here is that only certain care team members are authorized to make referrals of any kind; thus, support staff may need to be trained and authorized to use these tools.
Tracking Past Referrals
As described above, the SDH Summary accessed through the Summary tab (Figure 3) is automatically populated with information on past SDH-related referrals in order to enable CHC teams to track them. Referrals are shown in the SDH Summary if they are tied to a relevant ICD-10 code and/or if the SDH referral preference list was used. Presented data include the date of referral, contact information about the community resource, status of the referral, and who ordered it. Care team members authorized to edit referrals can manually update the referral status.
Lessons Learned
Lessons learned here may inform future efforts to build EHR tools for collecting and acting on SDH data. Because these lessons come from a pilot study conducted in 3 CHCs, we present them for consideration, not as a set of directions for SDH data tool development.
Considerations for Which SDH Questions to Include
Consider striking a balance between standardized SDH data collection (ie, aligned with the IOM-recommended measures) and the need to adapt to meet local needs, especially given that SDH data collection may become required for EHR certification and Uniform Data System reporting.
Considerations for Designing SDH Data Collection Tools
Patients may decline to answer SDH questions. Consider having SDH tools include a “patient refused to answer” option. Consider the advisability of including a “decline to answer” option on patient-facing data collection tools, which might make it too easy for patients to decline. Also, ensure that EHR-based SDH data tools do not require duplicate entry of SDH data collected elsewhere in workflows.
Patients with a positive SDH screening result may not want assistance in addressing the identified need. Consider creating EHR-based SDH data tools that include response options to indicate this preference, or to otherwise note that help was offered and declined.
Considerations for Designing SDH Data Summary Tools
Carefully consider which SDH data sources should populate the SDH data summary and how to manage potentially conflicting data.
Considerations for Designing SDH Referral Tracking Tools:
Monitoring the outcomes of past SDH-related referrals is challenging, and often requires outreach calls to patients. Consider whether this ability is desired.
ICD-10 codes related to SDH needs enable the tracking of such needs, but they may add to the complexity of the problem list. Consider creating an SDH “box” within the problem list.
Considerations for Maintaining Up-to-Date SDH Referral Tools:
SDH referral tools rely on updated lists of local resources. Consider whether established processes for maintaining other referral lists can be applied to SDH tools. Consider partnering with organizations that maintain such lists.
Considerations for SDH-Related Workflows
EHR-based SDH data tools need to accommodate diverse staffing structures, resources, and workflows. Consider ensuring that the appropriate care team members are authorized to access all aspects of the tools.
To avoid overwhelming clinic staff and care teams with SDH-related work, consider limiting SDH screening to a subset of patients and ensuring that EHR-based SDH data tools enable targeting this subset. Consider creating an alert to identify overdue patients. To avoid overwhelming care teams, consider designing the EHR tools so that SDH-related referrals can be marked “no follow-up needed.”
Consider using electronic tablets66⇓–68 to enable SDH screening at registration or upon rooming, with workflows for using and tracking them. Clinics will need wireless Internet to enable tablets to transmit SDH data to the EHR.
To use patient portals for SDH data collection, consider developing workflows for helping patients create portal accounts at registration then enter their SDH data through the portal on the spot. Tablets may be useful here as well.
Discussion
Standardized SDH data collection and presentation using EHR tools could facilitate diverse pathways to improved patient and population health outcomes in CHCs and other care settings. It could provide important contextual information to care teams, facilitate referrals to local resources, inform clinical decision making,69 enable targeted outreach efforts, and support care coordination with community resources.22,69,70 (We focused on how SDH data could be used to facilitate referring patients to local resources; research is needed on how else SDH data could inform clinical decisions). Such standardization will also provide data needed to document the SDH needs of CHC communities, inform policy and public health initiatives to improve health, and evaluate how addressing SDH risks affects health.
To attain these potential benefits, health care organizations need guidance on how to facilitate systematic SDH screening in primary care settings using EHR-based tools.43,71,72 Little such guidance currently exists; we know of no previously published reports on processes used to develop EHR-based SDH data collection, summary, and referral tools. This article presents an example of a process through which stakeholder input informed the development of a preliminary set of SDH-focused EHR tools. While the results and lessons learned from our process may be useful to other organizations undertaking such efforts, they are preliminary and based on opinions from a relatively small group of stakeholders, health informaticists, and health services researchers. Extensive research is needed to empirically test the generalizability of these lessons.
Acknowledgments
The authors thank Edward Mossman, MPH (OCHIN, Inc); Marla Dearing (OCHIN, Inc); and Katie Dambrun, MPH, for their contributions toward this manuscript and overall ASSESS & DO planning efforts. The authors also thank the staff at the pilot sites—Jennifer Hale, RN (Cowlitz Family Health Center); James Stoltz, RN (Cowlitz Family Health Center); and Maria Zambrano (La Clinica Health Center)—who provided feedback on clinic workflows and implementation efforts. The authors also thank collaborators Ranu Pandey, MHA (Kaiser Permanente Care Management Institute); Matthew C. Stiefel, MS, MPA (Kaiser Permanente Care Management Institute); and OCHIN′s Clinical Operations Review Committee for their input on development of the SDH data collection tool. All EHR images used with permission. Copyright Epic 2017.
Notes
This article was externally peer reviewed.
Funding: This publication was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (grant R18DK105463).
Conflict of interest: none declared.
To see this article online, please go to: http://jabfm.org/content/30/4/428.full.
- Received for publication February 14, 2017.
- Revision received February 14, 2017.
- Accepted for publication February 18, 2017.
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