Abstract
Introduction:
Poverty and associated health-related social needs can negatively impact child health. As pediatric health systems implement social needs screening programs, they should aim to measure and promote equal rates of screening across demographic groups and to support families in connecting to resources.
Methods:
We describe implementation of the Linking Families to Support (LiFTS) quality improvement initiative, an inpatient social needs screening and support program. Our objectives were to (1) implement screening across inpatient units, (2) promote equal screening rates across demographic groups, and (3) optimize rates of resource connection. LiFTS was implemented at a quaternary care children’s hospital. Families of children admitted to participating units during the study period (September 2022-February 2024) were eligible for screening.
Results:
Over the 18-month project period, we implemented screening on nine inpatient units. Of 2,582 eligible caregivers, 1,741 (67.4%) were offered screening. Of these caregivers, 667 (38.3%) declined screening and 1,074 (61.6%) completed screening. 496 families (46.2%) reported one or more social needs. In analyses stratified by child race, ethnicity, insurance status, and preferred language, we observed equal rates of screening. Among 233 families reached in follow-up, 183 (78.5%) recalled receiving resources and 133 (57.1%) reported connecting to one or more resources.
Discussion:
Our interdisciplinary team successfully implemented social needs screening across nine inpatient units, achieved equal rates of screening, and measured caregiver-reported rates of resource connection. Our approach could guide other health systems as they implement social needs screening programs that meet regulatory requirements, prioritize equality in screening, and support resource connection.
INTRODUCTION
Poverty and associated health-related social needs, such as food insecurity, housing instability, and difficulty paying for transportation or utilities, can negatively impact children’s health and well-being.1–3 There is growing interest in implementing social needs screening and support programs across pediatric health care settings, driven in part by incentives and mandates from the Centers for Medicare and Medicaid Services,4 Joint Commission requirements,5 and incorporation of social needs screening into U.S. News and World Reports hospital rankings.6–8 As pediatric health systems integrate social needs screening into clinical care, there is an urgent need to develop evidence on how to implement social care programs that not only meet regulatory requirements but also ensure equity in screening and optimize rates of resource connection.
Prior research suggests that social needs screening and referral programs are feasible to implement and acceptable to healthcare providers.9,10 Family-centered research also suggests that these programs can be acceptable to patients and caregivers, particularly when autonomy, privacy, and safety are prioritized and caregivers are provided with concrete, accessible resources.11–17 However, few studies have focused on strategies for measuring and ensuring equal rates of screening across demographic groups or on tracking and promoting resource connection among families who endorse social needs.18
This Quality Report describes implementation and evaluation of the Linking Families to Support (LiFTS) initiative, an inpatient social needs screening and support program. We aimed to implement social needs screening across several inpatient units at a large quaternary care children’s hospital and to provide families with meaningful support for their identified needs. Our specific aims were to (1) implement screening across nine inpatient units, (2) track and promote equal rates of screening across demographic groups, and (3) track and optimize rates of caregiver-reported resource connection.
METHODS
Context
LiFTS was implemented as a quality improvement project on nine inpatient units that care for both general pediatric and medical subspecialty patients at an academic, quaternary care children’s hospital in West Philadelphia that serves children from a large surrounding catchment area.10 The hospital has approximately 560 inpatient beds and more than 28,000 admissions annually. Each unit is led by a medical director and nurse manager, and clinicians providing direct patient care on these units include pediatric hospitalists, advanced practice providers, and resident physicians.
Planning the Intervention
Project Team and Intervention Development
To develop the LiFTS intervention, we worked with a large, multidisciplinary team including unit social workers and social work supervisors, bedside nurses and nurse managers, clinical informaticists, quality improvement advisors, physicians, and health services researchers. We developed a screening tool (Supplemental Table 1) with questions across six domains: (1) food, (2) housing, (3) utilities, (4) transportation to medical appointments, (5) caregiver depressed mood, and (6) intimate partner violence, adapted from the validated WE CARE questionnaire.9 We selected these domains based on prevalence of needs in our population and availability of resources within our hospital and community.10,18 We chose to use a tablet-based, self-administered screening tool based on previous research showing caregivers were more comfortable answering these questions on a tablet than verbally.18
We subsequently established a core leadership team to guide implementation, including physician leads, social work leads, and a quality improvement advisor. This team met monthly to review key process and outcome measures. We also established a larger working group including unit social workers, registration staff, and Care Team Assistants. This working group met every 2 weeks to proactively identify and address challenges in the screening and referral process.
Implementation of Screening
We engaged patient registration staff and Care Team Assistants to form the core team introducing the screener to families. Care Team Assistants are trained team members who attend rounds and assist with non-clinical tasks, including engaging with family members to support their participation in rounds, obtaining medical records, and scheduling follow-up appointments.19
Our screening process involved having a member of the care team introduce the tablet-based screener to caregivers during their child’s admission. Initially, we asked registration staff and Care Team Assistants to introduce the screener during their existing interactions with families. However, these initial efforts resulted in low screening rates. In April 2023, we therefore began asking registration staff to assign one dedicated patient registration team member to introduce the screener to families each day.
The screener was administered through REDCap (Research Electronic Data Capture), a secure, web-based platform designed to support data capture for quality improvement and research.20 We worked with clinical informaticists to develop a process for staff to document and review in the electronic health record (EHR) whether each family had (1) completed the screener, (2) declined to complete the screener, or (3) asked to be approached later. This allowed us to minimize redundancy and ensure families could be approached at multiple times during their child’s admission, based on their preferred time for screening.
Expansion of Screening to Additional Units
At the start of the study period, screening had been implemented on one pilot unit.10 As we expanded, we aimed to maximize awareness of and buy-in for the program. Prior to implementation on each new unit, we held presentations with unit social workers, nurses, and physicians, asked for suggestions on how to adapt our program to their unique workflow and included testimonials from families regarding the perceived value of the program. We also identified physicians on each team to be unit champions and proactively identify and address challenges during implementation.
Equality in Screening
We aimed to offer the screener to families at equal rates across demographic groups. We recognize that families with public insurance, families from minoritized racial and ethnic groups, and families who speak a language other than English might have disproportionate rates of social needs, due to the effects of poverty, racism, xenophobia, and discrimination. We aimed to screen all patients at equal rates, rather than disproportionately screening families from these higher-risk groups, because prior research suggests that families find screening acceptable when it is offered universally and framed as a routine part of their child’s care and that universal, rather than targeted, screening may increase identification of needs.16
To promote equality in screening, we engaged multiple team members to administer the screener at different times of day and developed the capacity to text the screener to caregivers who may face barriers to being at their child’s bedside. In addition, in April 2023, we worked with our hospital’s language services team to translate our screening tool into the six written languages other than English that are most prevalent among our patient population, specifically Spanish, Arabic, French, Simplified Chinese, Portuguese, and Vietnamese. We used a rigorous forward and back-translation process to ensure that screener translations were easily understandable while retaining the meaning and context of our original questions.21 We also developed a workflow allowing care team members to ask screening questions verbally, with assistance from an interpreter, in cases where families were unable to complete the questionnaire in their preferred language.
Promoting Resource Connection
After caregivers completed the screener, results were automatically sent by email to the unit social work team. Masters-level social workers responded to high-level, urgent needs such as homelessness and intimate partner violence. For less urgent needs, such as food insecurity, caregivers were able to request a list of resources sent via text or email, in-person support from a member of the social work team, or both. All caregivers who completed the screener, including those who did not endorse needs, received information about community-based resources through a searchable electronic resource map.10
To promote resource provision, we also developed a new job description for and subsequently hired a Social Work Care Coordinator, a bachelor’s level staff member trained to respond to concrete resource needs such as the need for food or transportation vouchers. Introducing this position, which was funded by our institution in response to preliminary data on the prevalence of needs among hospitalized patients, allowed unit social workers to prioritize responding to higher-level needs, recognizing that they often had competing responsibilities.
Measures
We selected primary outcome measures corresponding to each of our study aims. To measure expansion, we tracked the rate at which the screener was offered to families across included units. To measure equality in screening, we tracked rates of offering the screener stratified by caregiver-reported child race and ethnicity, as well as insurance status and preferred language. We recognize that race and ethnicity are social constructs and examined these variables because we hypothesized that racism and discrimination might impact whether caregivers were offered the screener.22
To measure caregiver-reported receipt of and connection to resources, we developed a standardized process for conducting phone outreach. Beginning in February 2023, a team member called all caregivers who screened positive for at least one social need to ask whether they recalled receiving resources during their child’s hospitalization and whether they connected with any resources. We attempted to contact each family by phone three times, approximately 6–8 weeks after they were screened.
We partnered with hospital informaticists and data analysts to build a real-time dashboard tracking these metrics by integrating demographic information from the EHR with screening and resource connection results from our REDCap database.
Data Analysis
We used descriptive statistics to examine demographic characteristics for families offered the screener, compared to all eligible families, and for families reached for follow-up calls, compared to all families with one or more social need. We conducted chi-squared tests to assess for differences in demographic characteristics between these groups. Statistical analyses were performed using Stata version 17.0 (StataCorp LLC, College Station, TX). This quality improvement project was deemed to be non-human subjects research by our Institutional Review Board. This publication was written according to Standards for Quality Improvement Reporting Excellence 2.0 guidelines (Supplemental Table 2).23
RESULTS
Expanding Screening
From September 2022 through February 2024, we expanded screening from one unit to nine units covering general pediatrics, complex care, and subspecialty care patients. Rates of screening increased in April 2023, when we began assigning one member of the patient registration team to introduce screeners to families each day and introduced translated screeners, with a centerline shift from 12% to 58% (Figure 1). At the end of the study period, approximately 42% of caregivers on included units were being offered the screener each week.
Figure 1. Proportion of Caregivers Offered the Screener (Screening Rate), September 2022 through February 2024.
This statistical process control chart shows the proportion of caregivers who were offered the screener on each of our included units, as well as the timing of screening expansion. Upper control limits (UCL) and lower control limits (LCL) are depicted as dashed lines, with the centerline (CL, corresponding to the mean) as a solid line. We noted five centerline shifts during our study period. Screening rate was defined as the proportion of eligible families to whom the screener was offered each week. The blue boxes indicate timing of unit expansion. As we expanded to additional units, the number of caregivers eligible for screening increased. We observed a downward centerline shift after several of these expansions, due to limited staff available to administer the screener despite an increase in eligible families. The green boxes indicate QI interventions, including (1) when a dedicated patient registration staff member was assigned to conduct screening daily, (2) when translated screening tools were first introduced, and (3) when our social work care coordinator began administering screening.
Of 2,582 eligible caregivers, 1,741 (67.4%) were offered screening and 667 (38.3%) declined, resulting in 1,074 caregivers who completed screening (Figure 2). There were no significant demographic differences between eligible caregivers and those who were offered the screener (Table 1).
Figure 2.
LiFTS Program Flow Diagram
Table 1.
Demographic Characteristics of All Eligible Caregivers and Caregivers Offered the Screening
| Characteristica | All Eligible Caregivers N= 2,582 N (%) | Caregivers Offered Screening N=1,741 n (%) | p-valueb |
|---|---|---|---|
| Child race | |||
| White | 1,049 (40.7%) | 731 (42.1%) | 0.22 |
| Black or African American | 912 (35.4%) | 603 (34.7%) | |
| Asian | 102 (3.9%) | 66 (3.8%) | |
| American Indian or Alaskan Native | 7 (0.3%) | 4 (0.2%) | |
| Native Hawaiian or Other Pacific Islander | 4 (0.2%) | 4 (0.2%) | |
| Other | 505 (19.6%) | 330 (19.0%) | |
| Unknown | 3 (0.1%) | 3 (0.2%) | |
| Child ethnicity | |||
| Hispanic or Latino | 439 (17.1%) | 285 (16.3%) | 0.37 |
| Non-Hispanic or Latino | 2,124 (82.9%) | 1,445 (83.0%) | |
| Unknown | 19 (0.7%) | 12 (0.7%) | |
| Child insurance status | |||
| Public insurance | 1,487 (57.9%) | 990 (57.3%) | 0.56 |
| Private insurance | 1,064 (41.5%) | 728 (42.1%) | |
| Uninsured | 16 (0.6%) | 11 (0.6%) | |
| Unknown | 15 (0.6%) | 12 (0.7%) | |
| Preferred language | |||
| English | 2,382 (92.6%) | 1,599 (92.1%) | 0.45 |
| Spanish | 129 (5.0%) | 91 (5.2%) | |
| Arabic | 17 (0.7%) | 14 (0.8%) | |
| All other non-English languages | 45 (1.8%) | 32 (1.8%) | |
Child race, child ethnicity, and child insurance status were extracted from the electronic health record.
p-values correspond to comparison of participants offered screening with those who were not offered screening.
Across our study period, 46.2% of caregivers screened positive for social needs, with the most common needs being mental health support (27.4%), food (18.8%), and transportation (12.0%). Among caregivers screened in languages other than English, 62.2% reported one or more social needs. Almost all families who screened positive for social needs requested support (94.2%).
Equality in Screening
Our second aim was to ensure screening was implemented equally and was inclusive of families using languages other than English. Figure 3 shows rates of screening (defined as proportion of families to whom the screener offered over eligible families) over time stratified by race, ethnicity, insurance status, and preferred language. As shown in the figure, we were able to achieve and maintain relative equality in screening across child race, ethnicity, and insurance status by the end of the project period. Rates of screening among families with a preferred language of Spanish or Arabic increased with the introduction of translated screeners in April 2023 and were comparable to screening rates among families with English as their preferred language during the remainder of the study period.
Figure 3.
Screening Rates Stratified by Patient Race, Ethnicity, Insurance Status, and Preferred Language, September 2022 through February 2024a
a Rates reflect the percentage of patients whose caregivers were offered the screener. The denominator includes all patients who were admitted to a unit where the screener had been implemented, and the numerator includes patients whose caregivers were offered the screener during their admission. Patients whose caregivers declined the screener are included in the numerator.
b Child race, ethnicity, and insurance status were extracted from the electronic health record (EHR). In this graph, “Other” includes Asian, American Indian or Alaska Native, and Native Hawaiian or Other Pacific Islander, as well as “Other Race/Ethnicity”. These categories were collapsed due to small sample sizes. Screening rates were extracted from REDCap and merged with EHR demographic data using children’s medical record number (MRN).
c Preferred language was extracted from the electronic health record (EHR). Screening rates were extracted from REDCap. We included only the three most common languages (English, Spanish, and Arabic), because sample sizes for all other languages were small, with no eligible families admitted during many included weeks.
Tracking and Promoting Resource Connection
Our third aim was to track and promote rates of resource connection. We were able to reach 233 caregivers for follow-up calls, representing 46.9% of caregivers with positive screens. Demographic characteristics of caregivers who completed follow-up calls were similar to those of all caregivers with social needs, although a greater proportion of caregivers reached for follow-up calls spoke Spanish (11.2% of caregivers reached by phone spoke Spanish, as compared to 7.9% of all caregivers with social needs, p = 0.04) (Table 2). Of caregivers who completed follow-up calls, 183 (78.5%) reported receiving information about resources during their admission, and 138 (59.2%) reported connecting with one or more resources (Figure 2).
Table 2.
Demographic Characteristics of All Participants with Health-Related Social Needs and Participants Reached for Follow-Up Phone Calls
| Characteristica | All Participants With Social Needs N=496 n (%) | Participants Reached by Phone N=233 n (%) | p-value |
|---|---|---|---|
| Child race | |||
| White | 143 (28.2%) | 62 (26.7%) | 0.95 |
| Black or African American | 243 (47.3%) | 113 (48.7%) | |
| Asian | 15 (2.9%) | 7 (3.0%) | |
| American Indian or Alaskan Native | 2 (0.4%) | 1 (0.4%) | |
| Native Hawaiian or Other Pacific Islander | 2 (0.4%) | 1 (0.4%) | |
| Other | 102 (20.1%) | 48 (20.7%) | |
| Unknown | 1 (0.2%) | 1 (0.4%) | |
| Child ethnicity | |||
| Hispanic or Latino | 101 (20.4%) | 48 (20.6%) | 0.99 |
| Non-Hispanic or Latino | 393 (79.2%) | 184 (79.0%) | |
| Unknown | 2 (0.4%) | 1 (0.4%) | |
| Child insurance status | |||
| Public insurance | 366 (73.8%) | 181 (77.7%) | 0.09 |
| Private insurance | 122 (24.6%) | 51 (21.9%) | |
| Uninsured | 4 (0.8%) | 1 (0.4%) | |
| Unknown | 4 (0.8%) | 0 (0.0%) | |
| Preferred language | |||
| English | 445 (89.9%) | 204 (87.5%) | 0.04 |
| Spanish | 39 (7.9%) | 26 (11.2%) | |
| Arabic | 4 (0.8%) | 1 (0.4%) | |
| All other non-English languages | 7 (1.4%) | 2 (0.9%) | |
| Number of health-related social needs | |||
| 1 | 245 (49.4%) | 113 (48.5%) | 0.54 |
| 2 | 126 (25.4%) | 57 (24.5%) | |
| 3 | 69 (13.9%) | 38 (16.3%) | |
| 4+ | 56 (11.3%) | 25 (10.7%) | |
| Domain of health-related social needs | |||
| Transportation | 127 (25.6%) | 54 (23.2%) | 0.24 |
| Food | 201 (40.5%) | 98 (42.1%) | 0.51 |
| Utilities | 185 (37.3%) | 92 (39.5%) | 0.34 |
| Housing | 119 (24.0%) | 56 (24.0%) | 0.98 |
| Mental Health Support | 290 (58.5%) | 143 (61.4%) | 0.22 |
| Intimate Partner Violence | 25 (5.0%) | 10 (4.3%) | 0.47 |
Child race, child ethnicity, and child insurance status were extracted from the electronic health record.
p-values correspond to comparison of participants reached for follow-up calls with those who were not reached.
These follow-up calls allowed us to both measure rates of resource connection and provide continued support for families. Families who did not recall receiving resources while in the hospital were provided with resources over the phone, and families who reported challenges with accessing resources were offered the option of receiving additional support from our Social Work Care Coordinator.
DISCUSSION
This study describes the implementation and evaluation of Linking Families to Support (LiFTS), an inpatient health-related social needs screening and support quality improvement initiative. We report on key strategies used to expand screening, monitor and support equal rates of screening across demographic groups, and track and optimize rates of resource connection.
Over an 18-month project period, we successfully expanded screening from one pilot unit to nine units. Successful expansion was aided by proactive coalition building, including through unit-specific meetings prior to expansion, identifying local clinical champions, and interdisciplinary collaboration, including close collaboration with unit social workers. Expansion was also bolstered by assembling a multi-disciplinary team, including Care Team Assistants and a dedicated registration team member, to introduce the screener to families. Despite assembling this multi-disciplinary team, however, we were only able to reach an average of 40–60% of eligible families on each unit. Several recent studies of inpatient social needs screening programs have similarly noted screening rates plateauing at a maximum of 50–70%.24–26 Collectively, these findings suggest that there may be systematic barriers to implementing high reliability social needs screening processes in the inpatient setting. For our project, these barriers included (1) a tablet-based screener that was not yet integrated into the EHR, requiring a staff member to verbally introduce and present the screener to each family; (2) difficulty identifying the optimal time for screening, both for caregivers and for screening staff; and (3) a small number of staff members available to introduce the screener, each of whom had many competing responsibilities. As we expanded to additional units and had an increasing number of families eligible for screening without a concurrent increase in the number of staff members introducing the screener, the proportion of eligible families we were able to reach decreased. Nevertheless, we were able to advocate for hiring an additional social work staff member to respond to positive screens by presenting hospital leadership with data on the high prevalence of needs among our patient population and by highlighting emerging incentives and mandates around inpatient screening from the Centers for Medicare and Medicaid Services4 and the Joint Commission.5 Other health systems developing and implementing screening programs must consider whether they have the processes and staffing models needed to both introduce and respond to screeners, and if not, how they might modify existing workflows or hire additional staff to meet these needs.
Over our project period, we were able to achieve equal screening rates stratified by patient race, ethnicity, language, and insurance status. This was particularly notable as data from our pilot unit previously showed lower screening rates among publicly insured as compared to privately insured patients,10 prior to implementation of workflows for screening throughout the day and texting the screener to caregivers. We therefore believe that our current success may have been supported by having team members screen throughout the day and by developing the capability to text the screener to caregivers unable to be at their child’s bedside.
Rates of screening among families who speak languages other than English increased with the introduction of translated screeners. Almost two-thirds of families screened in other languages reported social needs, in line with prior studies demonstrating increased need among this population.27 Health systems should recognize the potential for increased need among families who speak languages other than English, including immigrant and refugee families, and should ensure they are able to not only offer screening tools in multiple languages, but also provide families with culturally and linguistically appropriate resources and support.
Among families reached for follow-up calls, we found that almost 80% reported receiving information about resources during their admission, and more than half reported connecting with one or more resources. These rates of resource connection are relatively high as compared to previous studies of “low touch” interventions that provided families with written or electronic information about resources alone.28 This may reflect both our tiered social care model, including in-person support from a unit social worker or Social Work Care Coordinator, and our ability to provide families with concrete resources, such as food and transportation vouchers, during their admission. It may also reflect response bias among the families whom we were able to reach by phone, although it is reassuring that their demographic characteristics were similar to families who were not reached. Reporting these rates of resource connection has increased institutional buy-in for program expansion. Health systems should ideally develop strategies for providing caregivers with tiered support and for measuring caregiver-reported resource connection, in order to track this important family-centered outcome and help build institutional support for investment in this work.
Limitations
Our findings should be interpreted in the context of this study’s limitations. First, we describe our experience implementing this program within a single hospital, and the approaches we describe may not be generalizable to other settings. Second, screener responses and follow-up calls may have been subject to response bias and social desirability bias. We attempted to mitigate this with the use of language encouraging honest responses in our screener and follow-up call script. Third, and importantly, implementation of this program required substantial resource investment in terms of paid and unpaid time provided by team members, development of an electronic resource map, and creation and hiring of a new full-time role, the Social Work Care Coordinator. The exact dollar investment and return on investment in terms of patient’s health and health care utilization were not quantified in this study. More work is needed to determine the cost-effectiveness of social needs screening and support programs and their effectiveness in improving children’s health and well-being.
CONCLUSION
This study describes the implementation and evaluation of Linking Families to Support (LiFTS), an inpatient social needs screening and support program. Using quality improvement methodology, we report on key strategies used to expand screening, track and promote equal rates of screening, and track and optimize rates of resource connection. Our approach and lessons learned may help guide other health systems as they develop and implement health-related social needs programs that aim to not only meet regulatory requirements, but also prioritize equality in screening and maximize rates of resource connection.
Supplementary Material
Acknowledgements
We thank the Oscar and Elsa Mayer Family Foundation for funding this project and our institution’s Center for Health Equity for their institutional sponsorship and support of this work. We also thank all members of the LiFTS Working group for their contributions to this work and the multidisciplinary teams who contributed to program operations on each unit.
Funding/Support:
This work was supported by the Agency for Healthcare Research and Quality grant no. K08HS029396 (AV) and the Oscar and Elsa Mayer Foundation (AV, ZB).
Role of Funder/Sponsor (if any):
The funders had no role in the design and conduct of the study.
Abbreviations:
- HRSNs
Health-related social needs
- LiFTS
Linking Families to Support
- LOE
Languages other than English
- CTAs
Care Team Assistants
- FVS
Family Visitor Services
- IPV
Intimate Partner Violence
- EHR
Electronic Health Record
- SWCC
Social Work Care Coordinator
Footnotes
Clinical Trial Registration (if any): N/A
Conflict of Interest Disclosures (includes financial disclosures): The authors have no conflicts of interest to disclose.
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