Zachary Pruitt, PhD

 To determine whether self-identified social needs, such as financial assistance with utilities, food programs, housing support, transportation, and medication assistance, collected using a passive social health surveillance system were associated with inpatient readmissions.

 This retrospective observational study linked social service referral data collected from a call center—based passive social health surveillance system with healthcare claims data extracted from a managed care organization (MCO). Mixed-effects logistic regression models calculated the odds of all-cause hospital readmissions within 30, 90, and 180 days among individuals with self-identified social service needs compared with those without.

Individuals who identified social service needs

had 68% (odds ratio [OR], 1.68; 95% CI, 1.51-1.86), 89% (OR, 1.89; 95% CI, 1.74-2.05), and 101% (OR, 2.01; 95% CI, 1.87-2.17) higher odds of readmission within 30, 90, and 180 days, respectively, after controlling for other study variables. Examining each social service need separately, individuals had higher odds of hospital readmission within 30 days of discharge if they identified a financial (OR, 1.19; 95% CI, 1.07-1.33), food (OR, 1.32; 95% CI, 1.17-1.48), housing (OR, 1.31; 95% CI, 1.09-1.57), or transportation (OR, 1.21; 95% CI, 1.08-1.36) need compared with those without those social needs. In all study outcomes, medication assistance was not associated with readmissions.

 An MCO created a passive social health surveillance program to more effectively integrate medical and social care. Understanding individual-level social health needs provides the insights needed to develop interventions to prevent hospital readmissions.

A passive social health surveillance system—a managed care organization (MCO)’s call center—based social service referral program&mdash;enabled examination of whether self-identified social needs are associated with inpatient readmissions.

This study linked referral and claims data for 19,817 individuals to examine the odds of inpatient readmissions for individuals with self-identified social needs, such as food and housing insecurity, compared with those without self-identified needs.

Results showed that individuals with self-identified social needs had higher odds of 30-day inpatient readmissions.

Passive social health surveillance systems could enable MCOs to play an important role in integrating medical and social care by complementing the social health screenings of medical care providers.

Social needs, such as adequate housing, food security, and access to transportation services, affect population health outcomes.

 Neglecting to integrate social care with medical care may burden the healthcare system with unnecessary or unplanned utilization.

 Excess inpatient readmissions represent one such problem that US policy makers seek to address.

 Significant Medicare payment penalties motivate hospitals to develop strategies to curtail these readmissions. One approach includes hospital-defined algorithms that identify individuals with the greatest risk of readmission at the time of discharge.

Social health surveillance systems, which can identify social needs and connect people to community resources, may support medical and social care integration.

 Active social health surveillance uses screening tools to directly identify patient social needs at medical facilities.

 However, medical care providers may lack the time, training, and resources to effectively conduct social health screenings or link patients to community service providers.

A passive social health surveillance system—analogous to public health surveillance systems&mdash;consists of the ongoing collection, storage, and classification of social health needs information identified and reported by individuals or their caregivers. Two nationwide passive social health surveillance systems, the 2-1-1 programs

 and WellCare Health Plan’s Community Assistance Line,

 have been identified as effective approaches for identifying and tracking individual-level social health needs, including financial assistance to pay for utilities, food programs, assistance with medication, housing support, and free or low-cost transportation, among others.

The objective of this study was to determine whether self-identified social service needs collected through a passive social health surveillance system were associated with inpatient readmissions within 30, 90, and 180 days.

WellCare Health Plan’s Community Assistance Line, a part of its Center for CommUnity Impact, provides referrals to community-based social service organizations to individuals who contact the call center and report a social need. This cross-sectional study linked self-identified social needs collected in the social service referral program’s database with the managed care organization (MCO)’s health service claims data.

The study examined claims and social service referral data from January 1, 2013, through October 19, 2017, from 27,189 individuals insured by WellCare Health Plan’s Medicaid managed care and Medicare Advantage programs. The sample included individuals who were at least 18 years of age with at least 1 admission to an acute care hospital. Individuals who were pregnant (n = 638), were younger than 18 years (n = 1469), were transferred to a different hospital (n = 757), had 1 admission but less than 6 months of enrollment and claims data (n = 4210), received chemotherapy (n = 88), lived outside the 13 established states of interest (n = 84), had claims data errors (n = 11), or had incomplete data on study variables (n = 115) were excluded. The final study population included 19,817 individuals from 13 states who were readmitted to 1064 hospitals.

Outcome measures consisted of 3 all-cause hospital readmissions: individuals who were admitted within 30, 90, and 180 days of prior inpatient discharge. An admission was considered a readmission only if it occurred within the stipulated time frame (eg, 30 days) and was not a transfer to a different hospital. To identify a readmission, we calculated the difference between the first and subsequent admission and categorized the individuals as having 30-, 90-, and 180-day readmissions. Individuals with a single admission and who had utilization data for at least 6 months were classified as not having a readmission.

The study population was further classified into 2 groups: (1) individuals with self-identified social service needs reported to the Community Assistance Line and (2) individuals without self-identified social service needs. The study further classified individuals with a self-identified need based on the presence of any of the following 5 social service needs: financial assistance for utilities, food programs, housing support, transportation, and medication assistance. Individuals contacting the Community Assistance Line with self-identified social needs either had exhausted their defined health insurance benefit for services such as food programs, transportation, or medication assistance, or the social service was not a part of the health plan benefit, such as financial assistance and health literacy programs. These 5 domains of social needs were selected based on the recommendation by CMS and their previous associations with health outcomes.

 The study also examined the individuals with each of these 5 aforementioned domains of social needs separately compared with individuals without them.

To account for the maldistribution of established risk factors for hospital readmissions between study groups, several variables were included in our analyses. These variables included state of residence (Arkansas, Florida, Georgia, Illinois, Kentucky, Louisiana, Mississippi, Missouri, New Jersey, New York, South Carolina, Tennessee, or Texas), age at index admission, sex, race (black, white, Hispanic, or other), type of insurance (Medicaid managed care or Medicare Advantage), length of stay of the index admission, and whether the individual received case management services before the date of readmission.

The study also quantified the illness severity of individuals by calculating the Charlson Comorbidity Index (CCI) score using 

International Classification of Diseases, Ninth Revision

) diagnosis codes from claims data within the 12 months before hospitalization.

 diagnosis codes, the study further identified individuals with alcohol abuse, severe mental illness, and anxiety and depression. To account for neighborhood characteristics, the study included 2 measures of the socioeconomic status of the individual’s community: percentage of people 25 years or older with less than a high school diploma and percentage of people 25 years or older living below the poverty level.

The characteristics of individuals who identified a social need and those who did not were described using frequencies, proportions, means, and medians. The differences in these characteristics were tested using χ

 tests of independence for proportions, 2 independent sample 

 tests for differences in means, and Wilcoxon tests for differences in medians. Tables were created to describe the distribution of the identified social needs among applicable individuals.

The study accounted for the hierarchical nature of the data by performing mixed-effects logistic regression with the hospital included as a random intercept to account for clustering of individuals within hospitals. This modeling approach accounts for the variation of hospital-related factors on readmission and controls the type I error rate.

 A test of multicollinearity was performed between variables with potentially common underlying determinants using the variance inflation factor (VIF). All selected covariates had a VIF of less than 10, indicating that the variables included in the model were not strongly correlated (

]). Odds ratios (ORs) and their 95% CIs were used to compare the odds of readmission (within 30, 90, and 180 days) between the 2 study groups before and after adjusting for risk factors. This sequential approach highlights the change in odds of readmission in the presence of known risk factors for readmission.

Three groups of analyses were conducted according to the study groups under observation. First, a model was created to compare the odds of readmission on all study outcomes between individuals with any self-identified social need and those without. Second, the study compared the odds of readmission among individuals with at least 1 of the 5 domains of social needs (financial assistance with utilities, food programs, housing support, transportation, and medication assistance) and individuals with other social needs with those without any social need. The final model compared the odds of readmission on all study outcomes for individuals with a social need except for financial assistance, food programs, housing support, transportation, and medication assistance versus those without any of these needs. All 3 models controlled for the differences in risk factors including age, gender, race, state of residence, type of insurance, length of stay, comorbidities, case management status, severe mental illness, anxiety/depression, alcohol abuse, and, in their neighborhood, percentage of people 25 years or older with less than a high school diploma and percentage of people 25 years or older living below the poverty level.

All statistical tests were 2-sided and conducted using SAS 9.4 (SAS Institute Inc; Cary, North Carolina). 

 values and ORs, along with their 95% CIs, were calculated. 

 values <.05 were considered statistically significant.

The study was classified as exempt by the University of South Florida Institutional Review Board (#Pro00028372), as the data used in the study were previously collected for existing program operations by WellCare Health Plans.

Our study population consisted of 19,817 individuals with a mean (SD) age of 56.6 (16.2) years; 64.4% were female, and 75.3% were white. About 69.2% of the study population identified at least 1 social need, resulting in 24,867 social service referrals. The 10 most frequent social service referrals, accounting for approximately 88.7% of referrals in this population, are shown in 

Compared with members who did not identify a social need, members with a self-identified social need were younger (55.8 vs 58.2 years) and had a higher median CCI score (1.0 vs 0.0). They were more likely to be female (66.4% vs 60.0%), be insured by Medicaid (50.0% vs 41.6%), be in case management (88.8% vs 86.0%), have a severe mental illness diagnosis (9.5% vs 4.9%), have anxiety or depression (22.3% vs 13.6%), abuse alcohol (1.3% vs 0.8%), and live in neighborhoods with a higher proportion of adults with less than a high school diploma (32.8% vs 32.2%). These differences were statistically significant (

Before adjusting for other study variables, individuals with any self-identified social service need had 70%, 90%, and 102% higher odds of readmission within 30, 90, and 180 days, respectively (30 days: OR, 1.70; 95% CI, 1.53-1.88; 90 days: OR, 1.90; 95% CI, 1.75-2.05; 180 days: OR, 2.02; 95% CI, 1.88-2.17), compared with individuals without a self-identified social need. After controlling for other study variables, the odds of readmission attenuated slightly but remained higher in all study periods for individuals with a social need compared with those without one (30 days: OR, 1.68; 95% CI, 1.51-1.86; 90 days: OR, 1.89; 95% CI, 1.74-2.05; 180 days: OR, 2.01; 95% CI, 1.87-2.17) (

 shows the results of the 30-day readmission adjusted mixed-effects logistic regression model, including the independent variables, where the odds of readmission for those with a self-identified need were 68% higher (95% CI, 1.51-1.86). Length of stay of index admission showed increased odds of readmission (OR, 1.04; 95% CI, 1.03-1.05) for every day spent in the hospital. Female sex (OR, 0.90; 95% CI, 0.82-0.98) and case management before readmission (OR, 0.57; 95% CI, 0.48-0.67) were each associated with reduced odds of 30-day readmission in the adjusted logistic regression model.

The odds of readmission remained higher in all study periods for individuals who identified at least 1 of the 5 social service needs (financial assistance for utilities, food programs, housing support, transportation, or medication assistance). The odds of readmission observed in this group were comparable with the effect observed in the main group but slightly higher in most study outcomes than in the group with other social needs (

The results in Table 5 show that individuals needing financial assistance had 19% higher odds of being readmitted within 30 days of discharge (95% CI, 1.07-1.33) after controlling for other study variables. The increased statistical significance was maintained within 90 (OR, 1.18; 95% CI, 1.08-1.29) and 180 (OR, 1.25; 95% CI, 1.16-1.35) days. Similarly, individuals with food needs (30 days: OR, 1.32; 95% CI, 1.17-1.48; 90 days: OR, 1.31; 95% CI, 1.19-1.44; 180 days: OR, 1.31; 95% CI, 1.20-1.42), housing needs (30 days: OR, 1.31; 95% CI, 1.09-1.57; 90 days: OR, 1.28; 95% CI, 1.10-1.48; 180 days: OR, 1.44; 95% CI, 1.26-1.65), and transportation service needs (30 days: OR, 1.21; 95% CI, 1.08-1.36; 90 days: OR, 1.34; 95% CI, 1.23-1.47; 180 days: OR, 1.43; 95% CI, 1.31-1.55) had higher odds of readmission within 30, 90, and 180 days compared with others who did not identify these needs. In all study outcomes, individuals needing medication assistance did not have higher odds of inpatient readmissions compared with individuals who did not identify assistance with medication as a need (30 days: OR, 1.05; 95% CI, 0.89-1.24; 90 days: OR, 1.11; 95% CI, 0.97-1.26; 180 days: OR, 1.08; 95% CI, 0.96-1.22).

This study examined the association between self-identified social needs collected from a passive social service surveillance system and inpatient readmissions extracted from healthcare claims covering almost 5 years. Combining social service referrals with healthcare utilization data supports efforts to integrate medical and social care. Results show that individuals with self-identified social needs have higher odds of 30-, 90-, and 180-day inpatient readmission compared with individuals without a self-identified social need. This underscores the potential of passive social health surveillance systems in identifying individuals at risk of inpatient readmissions.

Although the mechanism by which social needs affect readmissions is not confirmed, it is possible that the self-identified social needs exacerbate the health conditions of the original diagnosis or hinder complete recovery and/or adherence to the postdischarge plan. For example, individuals without transportation services might miss doctor’s appointments and those in need of food might lack the nutritional requirements for adequate recovery. These social needs, if unmet, could potentially lead to a return to the hospital. Although examining the mediating effect of social needs on subsequent inpatient readmission and access to medical care among people of low socioeconomic status is beyond the scope of this paper, we believe that this might be an opportunity for further research.

In addition, although unmet social needs may be associated with readmissions, it is plausible that the result could be influenced by unmeasured confounders related to both self-reported social service needs and readmissions. For example, the apparent association between social needs and readmission may be that patients lack social support, which, in turn, leads to both contacting the call center to report a social need and returning to the hospital for readmission. Thus, our results may be overestimated. If factors related to social support that were unavailable in the present data were added to the models, the observed association reflected in our results may have been attenuated. However, even if self-reported social needs simply act as a spurious marker for readmissions, from a practical standpoint, this is problematic only if interventions focus solely on addressing the social needs, such as housing instability and food insecurity, while ignoring possible underlying determinants, such as shortage of affordable housing and inconsistent access to food. Additional research should be conducted to elucidate the actual nature of the relationship between social needs and readmission rates in order to properly identify the best interventions for preventing inpatient readmissions.

Individual-level social health surveillance information has not been previously evaluated when estimating inpatient readmission outcomes. Most readmission predictive models have incorporated clinical and demographic variables obtained from administrative databases.

 Other research predicting hospital readmissions used community-level factors as proxies for unmeasured individual-level measures of social health.

 The results from this study support the addition of individual-level social health factors collected through social health surveillance—both active and passive&mdash;to models seeking to predict individuals at risk of readmission.

The study also analyzed individuals with each of the following social service needs: financial assistance for utilities, food programs, housing support, transportation, and medication assistance. Compared with individuals without each of those social service needs, the odds of readmission for each of these social service types except medication assistance were higher at 30, 90, and 180 days. These findings are consistent with those of previous research showing that a variety of social determinants of health, such as financial insecurity,

Furthermore, this study highlights the contribution of nonclinical organizations to social health surveillance efforts. MCOs

 and social care coordination programs conduct passive social health surveillance that requires adequate investment to operate effectively.

 For example, the social service referral program should be appropriately promoted to ensure awareness by all stakeholders, including individuals with social health needs and medical care providers seeking resources to address patients’ social determinants of health. In addition, sufficient staffing of social health surveillance programs facilitates the connection of patients to community resources, supports technologies that track social service referrals, and enables robust program evaluation.

 The social health surveillance function highlighted in this study—the Community Assistance Line call center—based social service referral program&mdash;could be a useful tactic for accountable care organizations (ACOs). ACOs represent a risk-based financing model similar to the MCO evaluated in this study. ACOs are a type of alternative payment model that holds healthcare organizations financially responsible for the cost and quality of care of a population.

 Some ACOs also seek to combine their medical care capacity with social service coordination to achieve improved health outcomes, a concept called Accountable Health Communities.

 However, most ACOs lack the social health surveillance functions and community organization relationships necessary to address their patients’ social determinants of health.

 The Community Assistance Line represents 1 potential medical and social care integration model for organizations financially responsible for improving quality and reducing costs of care.

Future studies should examine the benefits of using passive social health surveillance data, such as those presented in this study, to assist in preventing inpatient readmissions. Programs combining social health surveillance with social care interventions, including hospital-based community health workers,

 have demonstrated success at reducing preventable readmissions. In addition, future investigation should build on this retrospective observational study to examine the optimal nature, quantity, and timing of social health surveillance and social care interventions that could prevent readmissions among populations with social care needs.

Several limitations of this study are worth noting. First, the study design precludes any causal and temporal inferences about the relationships between the self-identified social care needs and readmissions. Although observed group differences were accounted for in the analysis, the impact of unmeasured factors unavailable in our claims data, such as discharge location, marital status, and other social support, is unknown.

Also, this study analyzed individuals enrolled in the Medicare Advantage and Medicaid health plans of a single MCO. Although the large sample size drawn from 1064 hospitals in 13 states supports the generalizability of the results, extrapolation of the findings to other social surveillance systems or the broader US population will require further research.

Furthermore, it should be noted that the classification of readmissions was such that an individual readmitted within 30 days of discharge was also classified in the 90- and 180-day outcomes. Therefore, it is expected that the ORs of all study outcomes would follow an increasing linear response. Thus, we caution the interpretation of the dose—response relationship observed in our results.

In addition, the self-identified need does not mean that the referral resulted in access to or satisfaction with social services. Although these metrics were tracked, the focus on this study was to examine the hospitalization pattern of subjects with a social need. Future prospective randomized studies should determine if the fulfillment of social needs leads to a reduction in readmissions or unnecessary healthcare utilization.

Articles

By collecting self-identified social needs and linking them to claims data, this study analysis reveals that social needs are associated with inpatient readmissions.

Passive Social Health Surveillance and Inpatient Readmissions

We described the social support provided by CommUnity Liaisons, a layperson role that addresses participants’ unmet social needs with linkages to community resources. The call center—based role operates within Health

, a managed care organization’s program responsible for developing a nationwide network of local community-based social service organizations.

We utilized an explanatory case study approach to describe a new health layperson role.

 Multiple evidentiary sources, including in-depth interviews, training documents, and program data, enabled analysis of the application of the CommUnity Liaison role to social support theory within a logic model framework.

To alleviate the impacts of stress on participant health, the call center—based program created a social support layperson role. Consistent with social support theory, CommUnity Liaisons’ experiences enabled them to match participants’ unmet social needs with community resources not covered by their insurance benefits. Social service referrals most commonly included patient and family support, transportation, and housing assistance.

This study’s results demonstrated the feasibility of managed care organizations to address social determinants of health using a social support layperson role. Future study should investigate whether this form of social support protects population health and reduces healthcare spending.

The American Journal of Accountable Care. 2018;6(1):e16-e22

The presence of stress is related to increased morbidity and mortality,

 whereas social support from a person’s network, such as family, friends, and valued peers, may protect their health.

 A majority of physicians acknowledge that unmet social needs contribute to poor health outcomes, but most report a lack of time during the clinical appointment to address patients’ social needs in addition to their medical needs.

 They also may be unwilling or unable to address patients’ social determinants of health.

 Garg et al have suggested that when providers screen for issues, such as food insecurity, unemployment, and interpersonal violence, without the capacity to link to community resources, their effort becomes “ineffective and, arguably, unethical.”

To more effectively address unmet social needs, most physicians want social service coordination to be funded by payers, such as managed care organizations (MCOs).

 Alternative social support roles have been introduced by MCOs but have not been formally studied. Existing literature describes layperson roles that leverage the advantages of social support to improve the delivery of medical care.

 These individuals, such as community health workers,

 seek to achieve patient-specific clinical goals by improving access to social services, such as transportation, food, and housing.

This study describes the new social support role, CommUnity Liaisons, developed by WellCare Health Plans, an MCO based in Tampa, Florida, that serves Medicaid and Medicare beneficiaries nationwide.

 to improve plan members’ health and reduce unnecessary healthcare services utilization. The program comprises multiple operational components, including CommUnity Liaisons who make referrals to social service organizations. Other program elements include a research team that identifies local community resources, a field-based community relations team, an outbound call team that confirms referral access, and an analytics team. According to Carman and McGladrey,

 acts as a public health facilitator by identifying gaps between needs and services in the community, encouraging collaboration among community health stakeholders, and expanding local public health and social services capacity.

Since September 2014, participants with unmet social needs have contacted a call center to obtain free referrals to a nationwide network of local community-based public assistance programs. The social services have been provided to participants outside of the health plan benefits package. The call center, called the CommUnity Assistance Line, is available through a toll-free number or video link on weekdays from 9 am to 6 pm Eastern Standard Time. Participants learn of the referral program through numerous sources, including the MCO customer service and case management units, member materials (eg, provider directories), advertisements, and healthcare service providers. CommUnity Liaisons support all participants, including members, family, and other individuals unaffiliated with the MCO.

The present case study investigated the role of the CommUnity Liaison at a single MCO.

 Consistent with social support theory constructs, we posited that CommUnity Liaisons supported individuals who faced stressful circumstances and needed information about community resources.

 In addition, we expected that CommUnity Liaisons would provide informational and emotional support, both enabled by personal experiences with the social services system.

Case study research enables descriptions of the characteristics, patterns, structures, or processes of individuals or complex systems.

 A case study protocol, including propositions related to social support theory, logic linking the evidence to the propositions, an analytical approach, and criteria for interpretation, was developed to guide this investigation.

According to social support theory, interactions with similar and valued peers can be protective of individuals’ health in times of stress.

 Four types of social support are distinguished in the literature: emotional, instrumental, informational, and appraisal.

 The 5 propositions related to social support theory advanced by Cohen and Wills,

  were: 1) participants sought informational support from CommUnity Liaisons; 2) a CommUnity Liaison’s main goal was to provide informational support through advice, suggestions, and information that participants could use to address their problems; 3) CommUnity Liaison interventions provided emotional support conveyed through empathy, love, trust, and caring; 4) participants contacted the CommUnity Assistance Line because they experienced adversity; and 5) CommUnity Liaisons’ life experiences enabled empathic understanding and delivery of tailored information.

In-depth interviews with CommUnity Liaisons and managers of the program were conducted by researchers using semi-structured interview instruments, provided in 

]. The questionnaires consisted of 26 questions for CommUnity Liaisons and 28 questions for program managers. The interviews were organized using a logic model that enabled systematic review of the CommUnity Liaison role.

 describes the logic model used for the evaluation. Using purposeful sampling, 9 study participants were selected by a Health

 administrative staff member from the total of 28 CommUnity Liaisons. Each of Health

’ 4 managers were interviewed. All interviews were conducted in December 2016 at the MCO headquarters. Additional information supplied by the MCO included number of referrals given, number of referrals accessed, call statistics, and training materials.

The analytic strategy of the interviews involved 3 key steps: 1) transcription, 2) analysis, and 3) interpretation. After the audio-&#8203;recorded interviews were transcribed, responses were coded by multiple researchers. These coded responses then were categorized according to theoretical propositions, and patterns of responses were analyzed. We interpreted the explanatory evidence according to consistency with the 5 social support theory—based propositions.

Interviews revealed that CommUnity Liaisons mostly worked part time in the call center and were recruited through a variety of sources, including the state vocational rehabilitation agency, recruitment firms specializing in employment for people with disabilities, and the MCO’s employment website. Many CommUnity Liaisons had a variety of disabilities, including deafness and physical limitations. The ideal qualities of a CommUnity Liaison included being empathetic, engaging, and investigatory and having similar “lived experiences” as participants. Required skills included interpersonal communication, computer aptitude, and knowledge of social service programs. CommUnity Liaisons completed 2 weeks of training, including education on compliance, software, motivational interviewing, observational learning, and mock calls. 

 identifies distinguishing functions of the CommUnity Liaison role and other layperson roles.

CommUnity Liaisons utilized an extensive software suite that allowed them to locate more than 160,000 community resources in a database, identify service gaps in the local social services network, and manage referrals. The liaisons entered referral information into a dedicated “social services electronic health record” accessible by the liaisons and other MCO employees, such as nurse case managers. CommUnity Liaisons delivered referrals in 10 languages, including American Sign Language. Participants were responsible for making contact with the community organization directly. 

 indicates the most common types of social services that received referrals in 2016. The services were categorized consistent with the Nonprofit Program Classification System taxonomy developed for tax-exempt organizations by the National Center for Charitable Statistics.

The following quotes were selected from the in-depth interviews as they related to the 5 social support theory propositions:

“We exist as an informational resource for what [social services] they can access in their communities.”

Proposition 1. Participants sought informational support from CommUnity Liaisons.

Each of the respondents confirmed that participants sought informational support:

“[Participants] don’t know how to navigate the social service arena to get help. So, they’re looking for someone to guide them through that process.”

“… share knowledge and to empower people to be able to find help and to let them know that there may be help out there and it just may not be common knowledge.”

One respondent cited advice on social services as a reason participants called the CommUnity Assistance Line:

Proposition 2. A CommUnity Liaison’s main goal was to provide informational support through advice, suggestions, and information that participants could use to address their problems.

All interviews with CommUnity Liaisons and CommUnity Assistance Line management confirmed this proposition. A CommUnity Liaison stated that the CommUnity Assistance Line’s purpose was to:

“I love sharing information. People that don’t realize that there are a lot of different types of assistance programs out there, they may think, ‘Oh, I didn’t think of getting help for my utility bill to be able to pay for this surgery I’m supposed to get … or going to [a] food pantry and getting food, and then the money I would have spent on that food I can put toward this bill.’”

The information could be used to support participants’ medical and social needs:

“Even if they just call in for 1 issue, our [CommUnity Liaisons] are so good that they say, like, ‘Okay, is there anything else going on? Anything else we need to talk about? Okay, you need transportation to the grocery store or the pharmacy?’”

CommUnity Liaisons addressed more than 1 need:

“In the beginning of the call, they sound very disheartened … and embarrassed for asking for assistance. And then by the end of the call, typically their attitude changes, their tone of voice changes. And it’s just providing the information for them to be able to help themselves. It’s tremendous! I think that’s better than just giving assistance.”

“Sometimes when they call, they’re emotional. So, on our end, we have to find out the proper cause, and to bring them emotionally down, and see how we can help them.”

Proposition 3. CommUnity Liaison interventions provided emotional support conveyed through empathy, love, trust, and caring.

 We found inconsistent evidence regarding the CommUnity Liaisons’ delivery of emotional support. Only 7 of the 13 respondents described providing emotional support to participants. One of the 7 respondents acknowledged that emotional support was a precondition of delivering informational support:

Again, although most respondents did not report providing emotional support, a CommUnity Liaison suggested that participants’ emotional needs must be met before providing informational support:

“They call up, and they’ll give me a whole story about everything that’s gone wrong in their life. They only need 1 thing that I could probably give [to them] in 5 minutes and get them on their way, but they just want somebody who’ll listen to all that. Because doctors are limited in time, nurses are limited in time, social workers are limited in time.”

According to another CommUnity Liaison, healthcare providers often lacked the time to support participants’ unmet social needs:

“It’s any number of life circumstances—they’ve lost their job, their hours were cut at their job, their lease ended and their landlord is increasing their rent by 25%, they’re going through a divorce, or they got into a car accident.”

Proposition 4. Participants contacted the CommUnity Assistance Line because they experienced adversity. 

All respondents reported that adverse circumstances in the participants’ lives caused them to contact the CommUnity Assistance Line:

“When I say crisis, I mean emergency help. Most likely it’s financial assistance. They need help with their rent and utility and water bills.”

Financial needs often caused individuals to contact the CommUnity Assistance Line:

“They’re more worried about putting food on the table and keeping the electric on than they are going to a doctor’s office.”

A CommUnity Liaison articulated the impact of stressful events on participants’ health behaviors:

“Actually, I’m disabled. I went to vocational

ehab to find information on how to help myself with my financial need and with my medical need and stuff like that. They gave me a job coach, and from the job coach … that’s how I learned about [the CommUnity Assistance Line].”

“For example, if you have transportation [benefits], it’s limited; some people have 12 rides for the year, some people have 24. It depends on their benefits. So after they access all of their rides, they will come to us for assistance. Then we check personally. If I don’t like something, I don’t give it to no one. So I usually use the paratransit door-to-door services that I use, and I know they provide good services.”

Proposition 5. CommUnity Liaisons’ life experiences enabled empathic understanding and delivery of tailored information. 

The evidence supporting this proposition was mixed. In all cases, CommUnity Liaisons had involvement with social services through either previous training or personal experience. Most CommUnity Liaisons who were hired at the beginning of the CommUnity Assistance Line’s operation were recruited from vocational rehabilitation services or other recruitment firms specializing in supporting nontraditional workers:

Specific experiences with certain services led some CommUnity Liaisons to recommend those services:

“I learned of [this job] through vocational rehab, because I had a [serious illness]. Then [when I became a CommUnity Liaison], I talked to somebody who has had [the same serious illness], but they lost their job because they couldn’t do it anymore. Then they had no income… It took me like 2-and-a-half years to get Social Security income coming in.”

In one instance, a CommUnity Liaison could offer social support based on a disease-specific experience and the government benefits related to that illness:

“I have an 86-year-old mother, so I just picture everyone calling is that range or siblings in their 60s. Those are people in need. I grew up in Chicago, and I know poor sections and I know what they need, so I’m just trying to assist them.”

However, as the program evolved, the CommUnity Assistance Line management started an alternative recruiting approach to rapidly expand the call center. As of 2016, fewer recently hired CommUnity Liaisons had received social services. Individuals seeking part-time and flexible employment, such as students, caregivers, or veterans, joined the staff as CommUnity Liaisons. Although not exclusively disabled, these employees demonstrated familiarity with the social service system and the ability to empathize with the participants. Some of these CommUnity Liaisons used early life experiences to deliver tailored informational support:

“I never really had to worry about these things, you know, but [I try] to relate to the members, especially people that are cancer patients. I think of people in my family who have had cancer. So it hits at home where you can do this important thing we’re doing.”

Other CommUnity Liaisons used earlier experiences in their families to provide informational support:

Clinical care providers may lack the incentive to invest in addressing unmet social needs, especially in the short term,

 and most seek compensation for any effort associated with connecting patients to needed community programs.

 In contrast, MCOs accept financial risk and therefore retain the incentive to build community capacity to address social determinants of health, under the assumption that social support protects population health

initiative, including the CommUnity Assistance Line and CommUnity Liaisons, demonstrated the feasibility of MCOs instituting programs to address social determinants of health.

represents 2 innovations. First, the MCO built a large referral network of local community-based social services organizations, including food banks, housing programs, and transportation. These services, intended to address social determinants of health and reduce preventable healthcare spending, occurred outside of benefits packages and were provided at no cost to consumers and the government. Second, the MCO staffed the call center with laypeople. The creators of Health

 recognized that to effectively alleviate the health impacts of stressful life events, participants needed to identify with CommUnity Liaisons as peers.

 This approach was comparable to social support roles in health services delivery settings, such as community health workers

In most circumstances, social support involves a combination of emotional, instrumental, informational, and appraisal support.

 According to the matching hypothesis of the social support theory, effective social support requires that supporters’ advice matches participants’ needs.

 Participants contacted the CommUnity Assistance Line for social service referrals, and CommUnity Liaisons provided this needed informational support. We found that CommUnity Liaisons inconsistently reported providing emotional support. In the majority of cases, however, respondents acknowledged that emotional support was complementary to informational support. Due to the nature of their stressful life circumstances, participants often needed to be given empathic understanding before accurate community resource information could be delivered.

CommUnity Liaisons did not provide instrumental support, which involves the provision of tangible aid, nor did we find that CommUnity Liaisons directly coordinated medical and social services within the healthcare provider team. Rather, CommUnity Liaisons connected participants to community organizations or internal professionals (ie, nurse case managers) who provided direct assistance. Whereas other layperson roles within clinical care provider systems focus on enabling patients to meet specific clinical health goals, CommUnity Liaisons responded to an array of stressful life circumstances with a variety of community resources. Additionally, CommUnity Liaisons neither delivered health education nor provided limited medical care, which are functions generally associated with the community health worker role.

 CommUnity Liaisons also did not deliver appraisal support, which involves constructive feedback, affirmation, or social comparison.

Our study had several limitations. Although the interviewers were independent evaluators of the program, their presence during in-depth interviews may have affected the subjects’ responses to the questions. Also, our case study served to describe a single program and, therefore, has limited generalizability to other social support programs. In addition, the unit analysis of study was limited to CommUnity Liaisons and, thus, the description of Health

 and its CommUnity Assistance Line was beyond the scope of this paper. Health

 includes other important functions not investigated in the present study, such as field-based CommUnity Advocacy described by Carman and McGladrey,

 data analytics, social service organization grant making, and outbound satisfaction assessment.

Evidence in the existing literature is mixed regarding the abi&shy;lity of social support interventions to improve primary outcomes, such as morbidity

 or secondary outcomes, such as preventable hospitalizations.

 Future research should evaluate the relationship between participants’ access to social services and medical spending and health services utilization. Additional analysis is needed regarding the costs and composition of social services networks in local communities.

The MCO-based social service referral program represents an alternative approach for coordination of the health system’s capacity to link patients to community resources. In implementing a program designed to address unmet social needs, a new social support role was created, the CommUnity Liaison. Similar to policies designed to increase funding opportunities for navigators

 future health policy could enhance the health workforce by promoting a role similar to the CommUnity Liaison.

University of South Florida, College of Public Health, Department of Health Policy and Management (ZP, KMB), Tampa, FL; WellCare Health Plans, Inc (PLT), Tampa, FL.

 This research was funded by WellCare Health Plans, Inc.

 Dr. Pruitt has received a grant paid by WellCare Health Plans, Inc. Ms Lyons Taylor is employed at and holds stock in WellCare Health Plans, Inc. The remaining author reports no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Concept and design (ZP, PLT); acquisition of data (ZP, PLT, KB); analysis and interpretation of data (ZP, KB); drafting of the manuscript (ZP, KB); critical revision of the manuscript for important intellectual content (ZP, PLT); provision of study materials or patients (ZP, KB); obtaining funding (ZP); administrative, technical, or logistic support (KB); and supervision (ZP).

Zachary Pruitt, PhD, University of South Florida, College of Public Health, 13201 Bruce B. Downs Blvd, MDC56, Tampa, FL 33612-3805. Email: zpruitt1@health.usf.edu.

1. Thoits PA. Stress, coping, and social support processes: where are we? what’s next? 

This study describes an alternative approach to linking patients to community resources, such as food banks, housing, and medical transport, using a call center–based layperson role.

Zachary Pruitt, PhD

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