Clinician and Staff Perspectives on a Social Drivers of Health Program Implementation
Abstract
Introduction: Health systems are increasingly pursuing efforts to screen for and address social drivers of health (SDOH), the nonmedical factors that contribute to health outcomes and inequities. A large integrated health system (Intermountain Health) launched a program in 2019 to universally screen for and address SDOH.
Methods: Five primary care clinics within Intermountain were purposefully chosen for diversity of setting and practice type (family medicine and pediatric). We conducted 20 semistructured interviews with frontline clinicians and staff from 7/1/2020 to 9/1/2020 to explore attitudes related to feasibility, workflow processes, and facilitators and barriers to successful implementation. We conducted an inductive-deductive analysis to identify key themes and best practices.
Results: Five clinics conducted 16,659 SDOH patient screenings from 12/1/2019 to 11/30/2020 (705 to 7,723 screens per clinic with rates ranging from 7.4% to 52.8% per clinic). Respondent perspectives about the program were mixed. Dominant implementation barriers included staff time constraints, limited availability of social services, and reduced morale. Key facilitators included triage protocols for positive screens independent of the primary care clinician, standardizing previsit digital screening, and instilling a culture of shared ownership through education and team SDOH-focused huddles.
Conclusions: This evaluation of an early systemwide SDOH program implementation called into question the feasibility of universal screening in primary care given staff time constraints and social service availability. Future investigations should explore the impact of targeted screening approaches in diverse clinical settings and quantifying trade offs between SDOH programs and other clinical and organizational priorities.
- Diagnostic Screening Programs
- Health Plan Implementation
- Health Services Research
- Implementation Science
- Integrated Health Care Systems
- Primary Health Care
- Qualitative Research
- Social Determinants of Health
- Social Factors
Introduction
Health systems are increasingly being called on to address social drivers of health (SDOH) to improve health care quality, equity, and value.1⇓⇓–4 While a growing literature links adverse SDOH with these outcomes, less is known about widescale implementation of patient-level SDOH screening and resource provision in diverse clinical settings.5⇓–7
Widespread implementation of patient-level programs to screen and address adverse SDOH must overcome numerous challenges. Clinicians have reported personal and patient discomfort with discussing social challenges.8⇓⇓⇓–12 Perspectives on the extent to which health systems should be responsible for addressing patients’ social needs are also mixed.13,14 Most clinicians do not have formal SDOH training and may be unfamiliar with screening tool content or its integration into clinical practice.15,16 Clinical teams also face difficulties addressing positive screens due to limited resources.8,9,17 Finally, ongoing data collection requires significant investment by health care systems.18,19
Despite these challenges and fueled by nationwide incentive programs20,21, a growing number of health systems have adopted SDOH programs with reported improvements in equity and health system performance, and mixed effects on health outcomes.15,22⇓⇓–25 Supporting factors include standardizing SDOH screening tools, involving multi-disciplinary teams, and strengthening the regional social services network.17,26 Less well understood are how this seismic shift to bring social care under the purview of health care clinicians across the US is impacting frontline clinicians and staff in primary care as they simultaneously seek to perform their clinical duties on a day to day basis. In addition understudied is how variations in implementation at the clinic level may contribute to program success or failure.
We used qualitative interviews with frontline clinicians and staff to understand attitudes related to feasibility, workflow processes, and facilitators and barriers affecting implementation of a health system-wide program to screen for and address SDOH needs in a subset of primary care clinics within a large integrated health system.
Methods
Setting
In July 2019, Intermountain Health, a large integrated not-for-profit health system based in Salt Lake City, UT, which operated 24 hospitals and 160 clinics (including 14 internal medicine, 41 family medicine, and 16 pediatrics outpatient clinics) with 38,000 employees, launched an institution-wide program to screen for and address SDOH across its patient population of 1.65 million patients. In the primary care setting, the program was implemented in coordination with a 3-year community demonstration project called the Alliance for Determinants of Health (“The Alliance”).27 As part of The Alliance, a subset of Intermountain Health care clinics (including Sites 1 and 5 in our sample, see below) and community partners aimed to address social needs of SelectHealth Medicaid members in Washington County and Weber County through deployment of validated screening tools, and implementation of a digital platform to facilitate referrals to and closed-loop communication with social services (UniteUs, New York, NY). All clinics could refer to national and local SDOH resources (eg, 211 Helpline28), Between September 1, 2019, and December 1, 2020, primary care clinics deployed standardized SDOH screening tools in use throughout the US that focus on food, housing, utilities, safety, transportation, mental health/stress, and substance abuse concerns among patients. Specifically, the organization used a shortened “LITE” version of the NACHC and AAPCHO’s Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE) in its adult population ages 18 and over; the Division of Child Protection, Department of Pediatrics at the University of Maryland School of Medicine Department of Pediatrics’ Social Check assessment for children ages 6 to 18, and the Safe Environment for Every Kid (SEEK) one page screen for caregivers of children ages 0 to 5. Additional screening protocols can be found in the organization’s SDOH Care Process Model publication29 and Appendix A.
Sample
We purposefully selected 5 primary care clinics that were at least 12 months into their initial launch of the SDOH program with at least 100 screens performed and varied in terms of screening rates (range 7.4% to 52.8%), population served (3 family medicine, 2 pediatric), setting (1 rural, 3 semiurban, 1 urban) involvement in The Alliance (2 Alliance clinics, 3 non-Alliance clinics), and staffing (Table 1).
Characteristics of Participating Intermountain Primary Care Clinics
At each clinic, we sought interviews with individuals performing all clinician and staff roles involved in SDOH program execution: primary care clinicians (PCC) including medical doctors, doctors of osteopathy, physician assistants, and nurse practitioners; nurse care managers (NCM), who managed care coordination and social services; and care guides (CG), who worked under the NCM to facilitate care coordination. We interviewed individuals performing additional roles, considered related to the SDOH workflow, as available: Practice Managers (PM), Medical Assistants (MA), Registered Nurses (RN), and Licensed Clinical Social Workers (LCSW).
Data Collection
We conducted qualitative, semistructured interviews with frontline clinician and staff involved in SDOH-related activities from July to September 2020. A novel interview guide sought to elicit information about how primary care practices screen for and address SDOH, specifically capturing variation across practices, facilitators and barriers to program success, and best practices (Appendix B). We asked a point of contact at each clinic, typically a medical or administrative director, to suggest individuals who could be available at times when our team could conduct interviews. We then invited participants by e-mail to participate in an online interview and obtained verbal consent before initiating the interview. At least 2 researchers with qualitative training were present during each interview, alternating roles between conducting the interview and taking notes. Interviews were recorded and transcribed (Rev.com, San Francisco, CA) for analysis (NVivo Version 12, released March 2020). The primary interviewer also prepared summary notes following each interview. From these summaries, we compiled a Field Note for each clinic, which provided context during data analysis.
Data Analysis
We drew on the interview topic guide to generate an initial set of deductive codes. Four research team members independently applied deductive codes to an initial transcript and generated additional inductive codes, which were then shared and discussed with the larger group until consensus was reached.30 We added the agreed-on inductive codes to the working codebook. We repeated this process twice more, with the team meeting regularly to compare and align coding practices and to brainstorm, discuss, and adopt new inductive codes. We then divided the remaining transcripts among the 4 researchers for coding, with 1 reviewer per transcript. Researchers met regularly during the analytic phase to clarify coding, review emerging themes, and generate a novel theoretical framework based on the data that described how factors influenced SDOH program implementation. We did so with reference to the implementation science literature, particularly Proctor et al. (2011)31 and the Consolidated Framework for Implementation Research (CFIR).32
We further explored thematic categories using a matrix to identify facilitators and barriers to successful SDOH program implementation by framework category, where rows represented key themes and columns represented individual participants grouped by practice setting. We mapped these factors to CFIR inTable 2 to translate findings for an audience familiar with CFIR.32 The matrix also supported our ability to assess convergence of opinion at the clinic level, which we used to characterize consistency of support for a given factor.33 Finally, we followed a nominal group technique including individual ideation, sharing within the group, discussion, and ranking to compile a set of best practices for health systems adopting similar programs.34 We shared early learnings with health system leaders to inform operational improvement and confirm findings. The Institutional Review Board at Intermountain Health approved this research (Protocol #52491).
Emergent Factors Mapped to the Consolidated Framework for Implementation Research (CFIR) Influencing SDOH Program Implementation in Primary Care in a Large Integrated Health System as Derived through Qualitative Interviews with Frontline Clinicians and Staff
Results
We conducted 20 total interviews, 3 to 5 per clinic, and consisting of 5 PCPs, 4 NCMs, 5 CGs, 2 PMs, 2 RNs, and 2 MAs.
Our analysis revealed 4 categories of factors—contextual, organizational, patient, and processual—influenced SDOH activities (Figure 1).Table 2 reports the themes within each of these categories, maps them to CFIR, and provides examples of how they served as facilitators or barriers to successful SDOH program implementation.
Emerging factors impacting efforts to screen for and address social determinants of health in a large integrated health system.
Contextual Factors
Contextual factors are elements internal or external to the clinic, not directly related to the SDOH initiative, that nevertheless influence the SDOH program.
Time Constraints
Clinicians and staff in every role, with few exceptions, reported insufficient time to complete SDOH activities. Respondents cited understaffing or increasing work burden as key systemic challenges. Consequently, some reported working late, and MAs reported being unable to complete all rooming activities, including SDOH screening. Some physicians felt that despite their best intentions, they could not adequately address both clinical and SDOH needs during an encounter. In particular, social needs could “blow up a well visit,” typically scheduled for 15 to 20 minutes, causing a clinician to be late for the rest of the day (PCP/017). No satisfactory solutions were reported.
Availability of Community Services
Respondents repeatedly identified lack of social services in the community as a barrier to clinicians’ ability to successfully address positive SDOH screens. Particularly in rural areas, mental and dental health, housing, and transportation services were scarce, and some felt the default resource endorsed by the health system (ie, the 211 Helpline app) was inadequate. In an effort to secure local resources, NCMs proactively built custom inventories of local SDOH resources and shared this information during monthly NCM meetings with other local clinics. Sometimes the closest organization that accepted public insurance was over an hour away. When a patient was unable to make the journey or no service could be located, the clinical team would simply “do the best we can down here [rural area]” (PCP/005).
Community Organization Follow-up
Respondents noted that community organizations varied in their responsiveness to referrals in terms of initial patient outreach and in providing closed-loop communication to the referring clinical team. For the 2 clinics with access to a digital platform built to facilitate referrals to social services (ie, UniteUs), respondents highly valued its provision of confirmation that the service has been received. However, the additional consent form, which required patients to release medical information to each social service organization to which a patient was referred, presented a barrier to use, as it was challenging to engage patients outside of a clinical encounter.
Organizational Factors
Organizational factors are aspects of the larger health care system or localized clinic that impacted the SDOH program.
SDOH-Related Culture
Respondents’ comments revealed variation in the degree to which a clinic’s leadership emphasized the importance of SDOH activities, which in turn impacted how frontline clinicians and staff viewed their work. In the clinics where SDOH activities were presented unfavorably, staff viewed the program as a burden:
"So when it first came out, it was kind of presented as like, ‘this is one more thing we have to do.’ Like I said, it slowed down the intake process. It just took that much more time away from the clinician spending time with their patients.” (RN/009)
“At other clinics with greater reported success, leaders held team discussions at which they highlighted success stories and welcomed input from all members. These meetings reportedly fostered a sense of shared ownership. A few respondents regarded the overall health system favorably for pursuing an SDOH agenda: “…when you look at other medical platforms… They may care less about social drivers of health because it does not help their balance sheet… I mean, that is why I am working for [Intermountain].” (PCP/017)
Technology
Participants reported using both “high-tech” (eg, electronic health record, EHR) and “low-tech” (eg, sticky notes, article folders) tools to support SDOH program activities. The EHR facilitated automated advisories noting when patients were due for SDOH screening and interclinician messaging regarding SDOH services. These features were sometimes substituted with other article-based reminders such as file folders and sticky notes: “The [patients] that have been tracked and have been positive—those I just keep on my back burner, and I have a file and a folder with their names in it” (CG/018). At least one clinician noted the need to occasionally override an EHR advisory that was inappropriately triggered for a patient, suggesting ongoing EHR challenges.
Communication and Division of Responsibilities within Clinical Team
Respondents described needing to communicate about patient needs, goals, plans, and resources provided to ensure coordinated follow-up, and indicated that such communication generally went smoothly. While not all forms of assistance required following-up with patients (eg, referral to poison control phone number for pediatric patients), the NCMs and CGs performed patient outreach when follow up was required. One respondent said: “We set an [EHR] reminder to remind us to call them and to see how they are doing” (CG/004). Staff used EHR messaging for basic communication and phone calls for more interactive conversations. Respondents cited closed-loop communication as a best practice: “So our care manager does provide feedback. Like if we refer someone to her and she accepts them, as far as ‘This is a patient of mine now’” (PCP/002).
All clinics relied on NCMs and CGs to help address SDOH needs if they were not adequately addressed in the initial visit. However, not all staff felt comfortable with this role. At least one NCM without formal social work training in a clinic without an LSW felt uncomfortable with paperwork required to connect patients to social services. As application requirements and services changed frequently, this led to discomfort among some staff.
Patient Factors
Patient factors are how clinicians and staff perceive patient characteristics, beliefs, desires, and SDOH needs to impact SDOH activities.
Beliefs and Characteristics
Respondents regarded some patients themselves as a barrier. Reported patient reluctance to be screened stemmed from fear of legal reprisal in the case of noncitizens, personal reprisal in the setting of domestic violence, financial instability, or shame, especially for those living in a small town: “Patient embarrassment—shame—is a barrier to screening, particularly given [this] small town in which ‘everyone knows everyone’” (PCP/002).
In one clinic, staff responded to reported patient hesitation by temporarily boycotting the SDOH program due to the “awkward situation for the medical assistants to ask these questions” (RN/009). Strategies for making patients feel more comfortable included providing a dry-erase board that could be wiped clean between visits, rephrasing questions in a nonthreatening way, and having a physician revisit the SDOH screen toward the end of the visit after building rapport with the patient. All clinics eventually shifted to screening via a silent article or digital form, rather than having MAs ask questions aloud.
Desire for Change
Respondents noted that not all patients accepted support with SDOH needs following a positive screen. The organization’s on-the-job training addressed patient readiness as well as insurance as potential barriers. One respondent explained: “… we’ve been told that, ‘no, we cannot work harder than the patient works” (NCM/001). Some respondents, however, felt uncomfortable setting boundaries and limiting the work they would do on behalf of a patient, particularly when confronted with mental health challenges. In one example, “…[the patient] could not do it himself. He was too confused, and he did not understand the process; so, we just called him and had him come into the clinic and filled out the paperwork with him while he was here” (NCM/006). This approach was reportedly rare, but a few respondents felt extreme efforts were occasionally necessary.
Finally, a few respondents described a sense of futility in the health systems’ role in addressing SDOH: “I think we all are interested in helping our families function better. But… I feel like sometimes, by the time we recognize everything that had gone wrong, it is a little bit late… I think in that regard, there’s only incremental help available” (PCP/017).
Comorbid Disease
Respondents noted that patients’ coexisting clinical conditions influenced how they screened for and addressed SDOH needs. Patients with high burdens of comorbid clinical disease, who more regularly visited the clinic for appointments, were therefore more likely screened for SDOH needs. Frequent visits also enabled staff to more easily follow up on social needs. A few clinicians noted difficulty separating social and medical needs—these were ultimately “all mixed together” (PCP/003). NCMs often addressed both simultaneously during appointments and follow up calls.
Processual Factors
Processual factors are the processes that facilitated completion of SDOH activities within clinics throughout the large integrated health system.
Stratifying SDOH Needs
Respondents in all clinics described some type of triage approach to account for variation in number and acuity of SDOH needs. One clinic explicitly categorized each patient with a positive SDOH screen as having low, medium, or high acuity needs. These levels determined the response and frequency of follow-up. A high-acuity SDOH need received more intense attention relative to a low-acuity concern. For example, a patient who needed the poison control number (considered low acuity) received a magnet with this information, whereas a high-acuity need prompted a referral and “warm handoff” from a lead clinician to the NCM who thereafter conducted regular outreach regarding both clinical and social needs, pulling in a licensed social worker (LSW) in a minority of cases as needed. This triage process took place both formally and informally. One respondent said, “We would just follow up with the phone calls. There are some where if it is a higher intensity… our care manager will ask us to follow up weekly or monthly. We set our own reminders just to double check and see how the patient’s doing. Some of it is required. Some of it is just our own choice” (CG/004). LSWs were not readily available in 2 clinics, yet at least one clinician from one of these clinics felt comfortable calling a social workers from an external clinical setting (eg, inpatient) to help a patient in need.
Workflow Variation
Standard workflow did not account for all types of patients, and adherence to standard workflow sometimes varied. Some respondents pointed out that, because CGs or PSRs prepared physical article charts the evening before an appointment with a flag for patients who required SDOH screening, patients who were scheduled for a same-day or walk-in appointment often did not undergo SDOH screening. No solution to this challenge was discussed. Human error also accounted for some variation. To prevent missing screens due to human error, one clinic built redundancy into its SDOH screening process by pairing MAs to check each other’s work at the end of the day, an estimated 10-minute exercise.
Some respondents described physicians’ discretion as a source of variation in determining which patients received additional services. Following a positive screen for a higher-acuity need, physicians sometimes, though not always, referred patients to the NCMs and CGs to determine eligibility for services.
Intake Article Burden
Respondents at nearly every clinic felt that patients received too many article surveys at the start of their encounter, including consent, release of information, and now SDOH screening, among others, noting some forms duplicated questions. Respondents felt this risked irritating patients, particularly those managing small children. Staff hoped to capture these data electronically in the future, including allowing patients to complete forms digitally before their visit, if possible. At the same time, respondents identified the need for flexibility in the process for families without digital resources.
Discussion
This qualitative study assessed frontline clinician and staff perspectives of a program to universally screen for and address SDOH needs in primary care within a large integrated health system. We identified contextual, organizational, patient, and processual factors, which roughly aligned with CFIR’s categories and influenced SDOH activities.
Our contribution is novel for its setting in an integrated health system at the forefront of universal SDOH screening in 2019 and inclusion of diverse disciplines involved in frontline primary care. Despite reports of patient benefit and pockets of beneficial adaptations to universal SDOH screening, the overwhelming barriers identified by diverse members of the clinical team call into question the feasibility, acceptance, and appropriateness of widescale SDOH screening in the primary care setting. Our data suggest universal screening may reduce workflow variability and staff bias while unveiling opportunities to support patients, yet also necessitates unfavorable and unmeasured trade-offs against other clinical and organizational objectives.
Our data validated previously identified barriers to implementation including time constraints, disparate availability of social services at the local level, and the need for SDOH-specific clinician and staff training. However, variability in processes across clinics provide novel insight into how health systems might better implement SDOH programs. The authors compiled a set of best practices for the implementation of an SDOH program in primary care based on the qualitative data and following a nominal group technique (Table 3). These included the need to triage positive screens with adequate staffing resources reserved for high acuity needs, to encourage previsit digital screening, and to invest in a digital system to streamline closed-loop social service referrals35, among others.
Recommended Practices for SDOH Program Implementation in Primary Care Derived from Qualitative Interviews with Frontline Clinicians and Staff
As suggested inTable 3, a subset of clinics benefited from triaging social needs without necessarily relying on the PCP. Whereas simple needs could be addressed by the MA or NCM, higher acuity needs (eg, domestic violence) were flagged for the PCP, discussed during the visit, and then responsibility transferred in a “warm handoff” to NCMs. Removing the bottleneck of relying on the busy PCP as the key decision maker for all social service referrals appeared to unlock efficiencies in alignment with a team-based care model.36
Shifting to previsit, digitized screening where possible was also identified as a way to reduce the time and paperwork burden on staff and facilitate patient privacy.17 Indeed, the literature suggests previsit digital screening could free workflow resources while focusing attention where needed37,38, but it also suggests high need patients may be less likely to complete digital screening.39 Further, primary care visit screenings may present an opportunity to destigmatize social needs discussions.40 Future studies might explore a combination approach where in-person screening is still used for patients flagged as potentially high need (eg, those Medicaid insurance39), patients with walk-in/same-day appointments, and patients without “smart” digital resources.41
In contrast to prior work where health care workers were found to generally accept SDOH programs42, insufficient local availability of social services contributed to mixed staff acceptance of the program and motivation to complete screenings. While particularly rural clinics collaborated to identify and maintain an inventory of local resources to address SDOH needs, major gaps remained (eg, housing, dental, mental health). The promise of SDOH screening programs is to highlight social service gaps to better direct limited government or health system funding.40,43 Our data suggests a negative feedback loop wherein MAs who roomed patients were reluctant to complete screenings if they did not believe resources existed to support those with identified needs. The resulting incomplete datasets could ultimately limit future social investments, particularly in rural areas. Even within a single health system, clinic screening rates in this setting varied widely. This is in line with other SDOH program implementations.17 Our data underscores the need for robust frontline staff education—including standardized workflows, resources available to patients, use of data to garner future investment in social services, and benefits to social screening outside of the referral pathway such as care tailored to the patient and enhanced patient-clinician relationship40,44—should be a priority in all SDOH programs so the clinical team understands the ‘why’ behind new work processes.
Ideally, health systems would benefit from the positive potential of capturing social needs data without placing undue burden on frontline clinicians and staff. Of the recommendations uncovered in these data, only a few (ie, Previsit digital screening, triage processes) had the potential to address the time barriers so many clinicians and staff described without significant new investment. Instead, alternatives to the current ‘every patient every year’ SDOH screening approach may be explored. A targeted approach could trigger an SDOH screen based on objective factors such as patient age (eg, turning 18, 65, etc.), patient diagnoses (eg, giving birth), comorbidities, care utilization events (eg, emergency department encounters), area deprivation index45, and insurance and/or socioeconomic changes (eg, job loss, divorce).45 The optimal setting to conduct SDOH activities also requires further attention. While primary care may be best suited to address social needs from a longitudinal perspective, patients with the greatest social needs often enter the system through higher acuity settings such as the emergency department.46 A site-agnostic approach to SDOH screening that facilitates multiple points of entry may better serve patients. Further investigations to optimize SDOH programs should test the impact of such variations on screening and social referral rates and quantify trade-offs against other clinical and organizational priorities. Buy-in to such investigations at the national level may be needed given the current emphasis on universal screening.20,21
This study is limited by the timing of interviews, which took place within the year following program implementation during the COVID-19 pandemic. The health system has since shifted toward a virtual social work model; more work is needed to understand how early successes and challenges evolved over time within the new model. In addition, we worked with a large, well-resourced health system in which a majority of patients are managed under an affiliate health insurance and a relatively small proportion of patients have identified needs.47 This health system is at the forefront of investing in SDOH services among others48–51; additional research is therefore needed in other settings. We were also unable to interview all clinicians and staff members from each clinic due to resource constraints; a diversity of perspectives was sought to mitigate this bias. Finally, future studies will benefit from inclusion of the patient perspective to further optimize SDOH clinical workflows.
Conclusion
Intermountain Health was one of the first health systems to embark on an ambitious universal SDOH screening program in primary care in 2019 with mixed results. While clinicians and frontline staff reported benefits to patients, they also outlined significant workflow challenges given barriers of time, local availability of social services, and others. Robust clinician and frontline staff education regarding underlying benefits from SDOH screening is needed. Given significant barriers to implementation and wide variation in screening rates, future investigations should explore the impact of targeted screening approaches in diverse clinical settings and quantifying how SDOH programs trade off against other clinical and organizational priorities.
Notes
This article was externally peer reviewed.
Funding: This project was supported by an internal grant from Intermountain Health and Stanford Health Care.
Conflict of interest: Dr. Thomas reports receiving equity from PocketRN outside the submitted work. Dr. Brunisholz reports receiving stock options from Johnson and Johnson outside the submitted work. Dr. Srivastava reports receiving grants paid to his institution from AHRQ, CDC, National Institutes of Health, and Patient-Centered Outcomes Research Institute outside the submitted work; being a founder of the I-PASS Patient Safety Institute, with his equity owned by Intermountain Health; and receiving monetary awards, honoraria, and travel reimbursement from Cincinnati Children’s Hospital in Ohio, Mount Sinai Kravis Children’s Hospital in New York, Hospital for Sick Children in Ontario, Canada, Phoenix Children’s Hospital in Arizona, and the Pediatric Neurological Annual. The authors have no other disclosures to report.
To see this article online, please go to:http://jabfm.org/content/36/7/1103.full.
- Received for publicationAugust 22, 2023.
- Revision receivedFebruary 29, 2024.
- Revision receivedApril 25, 2024.
- Accepted for publicationMay 28, 2024.
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