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An Experiential Resident Module for Understanding Social Determinants of Health at an Academic Safety-Net Hospital.

ABSTRACT: Introduction:Half of the U.S. population has chronic illness. Many disparities exist in health care for management of chronic disease among poorer individuals, including decreased access to healthy foods, homelessness, and difficulty navigating large hospital systems due to low health literacy. A survey of resident physicians found significant gaps in preparedness to provide cross-cultural care. Education is needed to promote consideration of patients' social and cultural barriers in managing disease and navigating the health care system. This module was created as an introduction to social determinants of health, and highlights disparities in access to healthy food, water, shelter, and medical care in a sample of the residents' own continuity clinic patient panel. Methods:We designed this experiential module to help internal medicine residents at an urban institution better understand how social constructs might hinder patient health. Activities were chosen by learners from a list of options, and carried out in small groups during a half day of protected time. We used reflective writing exercises to elicit resident thoughts about the module. Results:Thirty-nine second-year residents participated in the module. Following the course, 41% of residents submitted reflective statements about their experience. Reflective responses suggest an enhanced appreciation for social determinants of health, a sense of empowerment to advocate for better patient resources, and an appreciation for systems-level factors that play a role in social determinants of health. Discussion:Our results demonstrate that a short, experience-based module can impact resident attitudes about social determinants and improve advocacy around identifying community resources.

SUBMITTER: Schmidt S

PROVIDER: S-EPMC6338147 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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An Experiential Resident Module for Understanding Social Determinants of Health at an Academic Safety-Net Hospital.

Schmidt Stacie S Higgins Stacy S George Maura M Stone Alanna A Bussey-Jones Jada J Dillard Rebecca R

MedEdPORTAL : the journal of teaching and learning resources 20171026

<h4>Introduction</h4>Half of the U.S. population has chronic illness. Many disparities exist in health care for management of chronic disease among poorer individuals, including decreased access to healthy foods, homelessness, and difficulty navigating large hospital systems due to low health literacy. A survey of resident physicians found significant gaps in preparedness to provide cross-cultural care. Education is needed to promote consideration of patients' social and cultural barriers in man ...[more]

PMID: 30800848

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Project description:ImportanceNo consensus exists on how to define safety-net hospitals (SNHs) for research or policy decision-making. Identifying which types of hospitals are classified as SNHs under different definitions is key to assessing policies that affect SNH funding.ObjectiveTo examine characteristics of SNHs as classified under 3 common definitions.Design, setting, and participantsThis cross-sectional analysis includes noncritical-access hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases from 47 US states for fiscal year 2015, linked to the Centers for Medicare & Medicaid Services Hospital Cost Reports and to the American Hospital Association Annual Survey. Data were analyzed from March 1 through September 30, 2018.ExposuresHospital characteristics including organizational characteristics, scope of services provided, and financial attributes.Main outcomes and measuresDefinitions of SNH based on Medicaid and Medicare Supplemental Security Income inpatient days historically used to determine Medicare Disproportionate Share Hospital (DSH) payments; Medicaid and uninsured caseload; and uncompensated care costs. For each measure, SNHs were defined as those within the top quartile for each state.ResultsThe 2066 hospitals in this study were distributed across the Northeast (340 [16.5%]), Midwest (587 [28.4%]), South (790 [38.2%]), and West (349 [16.9%]). Concordance between definitions was low; 269 hospitals (13.0%) or fewer were identified as SNHs under any 2 definitions. Uncompensated care captured smaller (200 of 523 [38.2%]) and more rural (65 of 523 [12.4%]) SNHs, whereas DSH index and Medicaid and uncompensated caseload identified SNHs that were larger (264 of 518 [51.0%] and 158 of 487 [32.4%], respectively) and teaching facilities (337 of 518 [65.1%] and 229 of 487 [47.0%], respectively) that provided more essential services than non-SNHs. Uncompensated care also distinguished remarkable financial differences between SNHs and non-SNHs. Under the uncompensated care definition, median (interquartile range [IQR]) bad debt ($27.1 [$15.5-$44.3] vs $12.8 [$6.7-$21.6] per $1000 of operating expenses; P < .001) and charity care ($19.9 [$9.3-$34.1] vs $9.1 [$4.0-$18.7] per $1000 of operating expenses) were twice as high and median (IQR) unreimbursed costs ($32.6 [$12.4-$55.4] vs $23.6 [$9.0-$42.7] per $1000 of operating expenses; P < .001) were 38% higher for SNHs than for non-SNHs. Safety-net hospitals defined by uncompensated care burden had lower median (IQR) total (4.7% [0%-9.9%] vs 5.8% [1.2%-11.2%]; P = .003) and operating (0.3% [-8.0% to 7.2%] vs 2.3% [-3.9% to 8.9%]; P < .001) margins than their non-SNH counterparts, whereas differences between SNH and non-SNH profit margins generally were not statistically significant under the other 2 definitions.Conclusions and relevanceDifferent SNH definitions identify hospitals with different characteristics and financial conditions. The new DSH formula, which accounts for uncompensated care, may lead to redistributed payments across hospitals. Our results may inform which types of hospitals will experience funding changes as DSH payment policies evolve.

Project description:BACKGROUND:Early readmission amongst older safety-net hospitalized adults is costly. Interventions to prevent early readmission have had mixed success. The role of perceived social support is unclear. We examined the association of perceived social support in 30-day readmission or death in older adults admitted to a safety-net hospital. METHODS:This is an observational cohort study derived from the Support From Hospital to Home for Elders (SHHE) trial. Participants were community-dwelling English, Spanish and Chinese speaking older adults admitted to medicine wards at an urban safety-net hospital in San Francisco. We assessed perceived social support using the Multidimensional Scale of Perceived Social Support (MSPSS). We defined high social support as the highest quartile of MSPSS. We ascertained 30-day readmission and mortality based on a combination of participant self-report, hospital and death records. We used multiple/multivariable logistic regression to adjust for patient demographics, health status, and health behaviors. We tested for whether race/ethnicity modified the effect high social support had on 30-day readmission or death by including a race-social support interaction term. RESULTS:Participants (n?=?674) had mean age of 66.2 (SD 9.0), with 18.8% White, 24.8% Black, 31.9% Asian, and 19.3% Latino. The 30-day readmission or death rate was 15.0%. Those with high social support had half the odds of readmission or death than those with low social support (OR?=?0.47, 95% CI 0.26-0.88). Interaction analyses revealed race modified this association; higher social support was protective against readmission or death among minorities (AOR?=?0.35, 95% CI 0.16-0.76) but increased likelihood of readmission or death among Whites (AOR?=?3.7, 95% CI 1.07-12.9). CONCLUSION:In older safety-net patients nearing discharge, high perceived social support may protect against 30-day readmission or death among minorities. Assessing patients' social support may aid targeting of transitional care resources and intervention design. How perceived social support functions across racial/ethnic groups in health outcomes warrants further study. TRIAL REGISTRATION:NIH trials registry number ClinicalTrials.gov: NCT01221532 .

Project description:The patient-centered medical home (PCMH) model holds promise for improving primary care delivery, but it has not been adequately tested in teaching settings.We implemented an intervention guided by PCMH principles at a safety-net teaching clinic with resident physician providers. Two similar clinics served as controls.Using a cross-sectional design, we measured the effect on patient and resident satisfaction using the Consumer Assessment of Healthcare Providers and Systems survey and a validated teaching clinic survey, respectively. Both surveys were conducted at baseline and 1 year after the intervention. We also measured the effect on emergency department and hospital utilization.Following implementation of our intervention, the clinic’s score on the National Committee for Quality Assurance’s PCMH certification tool improved from 35 to 53 of 100 possible points, although our clinic did not achieve all must-pass elements to qualify as a PCMH. During the 1-year study period, 4676 patients were exposed to the intervention; 39.9% of these used at least 1 program component. Compared with baseline, patient-reported access and overall satisfaction improved to a greater extent in the intervention clinic, and the composite satisfaction rating increased from 48% to 65% in the intervention clinic vs from 50% to 59% in the control sites (P?=?.04). The improvements were particularly notable for questions relating to access. For example, satisfaction with urgent appointment scheduling increased from 12% to 53% in the intervention clinic vs from 14% to 18% in the control clinics (P?<?.001). Resident satisfaction also improved in the intervention clinic: the composite satisfaction score increased from 39% to 51% in the intervention clinic vs a decrease from 46% to 42% in the control clinics (P?=?.01). Emergency department utilization did not differ significantly between the intervention and control clinics, and hospitalizations increased from 26 to 27 visits per 1000 patients per month in the intervention clinic vs a decrease from 28 to 25 in the control clinics (P?=?.02).Our PCMH-guided intervention, which represented a modest but substantive step toward the PCMH vision, had favorable effects on patient and resident satisfaction at a safety-net teaching clinic but did not reduce emergency department or hospital utilization in the first year. Our experience may provide lessons for other teaching clinics in safety-net settings hoping to implement PCMH-guided reforms.

Project description:Note: Data Use Restrictions: <ul> <li>The data must only be used for genetic research projects solely in the area of health-related social-network research.</li> </ul> This study compiles detailed information on family and social ties linked to participants in the offspring cohort of the Framingham Heart Study. The investigators took computerized information from self-report data used by the FHS for over 30 years to facilitate health exam scheduling. These tracking sheets asked participants to identify people close to them, which were assumed by the investigators to indicate a social tie. Individuals are listed as "egos" (if the ties are from their perspective) and/or "alters" (if they are linked as a friend or family members to one of the other participants). All egos were FHS offspring participants while alters could be FHS participants in any cohort or non-participants. This information was combined with internal FHS pedigree data on family ties to list family member alters (as well as the nature of their relationship). The resultant dataset therefore includes each ego-alter tie, the nature of their relationship and the start and end dates for their ties for each of seven waves for the offspring study. Due to privacy concerns, all exam dates for individuals are listed relative to the initial FHS exam date. The study investigators chose a random, confidential date, to which all initial exam dates are linked (by number of months from random date to initial exam date). With this information, researchers can have access to the temporal relationships among participants' exam dates while remaining unaware of the actual exam dates for individual participants. During each clinic exam cycle, the participants undergo a detailed examination including physical examination, medical history, laboratory testing, and electrocardiogram. Over the years, other tests (that may not be performed at every exam cycle) have included pulmonary function, lifestyle, physical function, cognitive function questionnaires, and various noninvasive cardiovascular tests including echocardiograms. This study involves phenotypic data from these exams including (when available) basic body measurements (height, weight, blood pressure), laboratory values (blood sugar levels, LDL levels), information on smoking and alcohol use, and tests of depression and cognitive functioning. Important links to apply for individual-level data <ol> <li><a href="http://dbgap.ncbi.nlm.nih.gov/aa/wga.cgi?view_pdf&stacc=phs000153.v3.p3" target="_blank">Data Use Certification Requirements (DUC)</a></li> <li><a href="GetPdf.cgi?id=phd001183.1" target="_blank">Instructions to Request Authorized Access</a></li> <li><a href="http://view.ncbi.nlm.nih.gov/dbgap-controlled" target="_blank">Apply here for controlled access to individual level data</a></li> <li><a href="GetPdf.cgi?id=phd000317" target="_blank">Participant Protection Policy FAQ</a></li> </ol> In 1948, researchers recruited men and women from the town of Framingham, Massachusetts, beginning the first round of extensive physical examinations and lifestyle interviews that would later be analyzed for common patterns related to CVD development. Initially, the Framingham Heart Study enrolled 5,209 men and women from the Framingham area who were between the ages of 28 and 62 years. Beginning in 1971, the Framingham Heart Study enrolled 5,124 men and women, who were either offspring of the original cohort or spouses of those offspring. In 2002, 4,095 third generation participants (men and women) were enrolled.

Project description:ImportanceAlthough readmission rates are declining under Medicare's Hospital Readmissions Reduction Program (HRRP), concerns remain that the HRRP will harm quality at safety-net hospitals because they are penalized more often. Disparities between white and black patients might widen because more black patients receive care at safety-net hospitals. Disparities may be particularly worse for clinical conditions not targeted by the HRRP because hospitals might reallocate resources toward targeted conditions (acute myocardial infarction, pneumonia, and heart failure) at the expense of nontargeted conditions.ObjectiveTo examine disparities in readmission rates between white and black patients discharged from safety-net or non-safety-net hospitals after the HRRP began, evaluating discharges for any clinical condition and the subsets of targeted and nontargeted conditions.Design, setting, and participantsCohort study conducting quasi-experimental analyses of patient hospital discharges for any clinical condition among fee-for-service Medicare beneficiaries from 2007 to 2015 after controlling for patient and hospital characteristics. Changes in disparities were measured within safety-net and non-safety-net hospitals after the HRRP penalties were enforced and compared with prior trends. These analyses were then stratified by targeted and nontargeted conditions. Analyses were conducted from October 1, 2017, through August 31, 2018.Main outcomes and measuresTrends in 30-day readmission rates among white and black patients by quarter and differences in trends across periods.ResultsThe study sample included 58 237 056 patient discharges (black patients, 9.8%; female, 57.7%; mean age [SD] age, 78.8 [7.9] years; nontargeted conditions, 50 372 806 [86.5%]). Within safety-net hospitals, disparities in readmission rates for all clinical conditions widened between black and white patients by 0.04 percentage point per quarter in the HRRP penalty period (95% CI, 0.01 to 0.07; P = .01). This widening was driven by nontargeted conditions (0.05 percentage point per quarter [95% CI, 0.01 to 0.08]; P = .006), whereas disparities for the HRRP-targeted conditions did not change (with an increase of 0.01 percentage point per quarter [95% CI, -0.07 to 0.10]; P = .74). Within non-safety-net hospitals, racial disparities remained stable in the HRRP penalty period across all conditions, whether the conditions were HRRP-targeted or nontargeted.Conclusions and relevanceFindings from this study suggest that disparities are widening within safety-net hospitals, specifically for non-HRRP-targeted conditions. Although increases in racial disparities for nontargeted conditions were modest, they represent 6 times more discharges in our cohort than targeted conditions.

Project description:OBJECTIVE:The 340B program allows safety-net hospitals to acquire discounted outpatient drugs and charge payers full price. We examined whether 340B participation increases safety-net engagement. DATA SOURCES:340B participation data, Medicare hospital cost reports, American Hospital Association Survey, and Schedule 990 nonprofit hospital tax returns. STUDY DESIGN:Quasi-experimental difference-in-differences design comparing 340B hospitals (the "treatment" group) before and after participating to changes over time to three alternative "control" groups: all other nonprofit and public hospitals, hospitals that are not participating during our study, and hospitals that were not-yet-participating but started after 2015. Outcome measures include a range of safety-net care measures that are alternatives to the standard uncompensated care: charity care, community benefit spending, charity care policies, and low-profit service-line provision. DATA EXTRACTION:We extracted data on all nonprofit and public hospitals from 2011 to 2015. We linked 340B participation data to Medicare hospital cost reports and American Hospital Association data using Medicare hospital identifiers. 990 Data was linked on name and address. PRINCIPAL FINDINGS:New 340B participation was not associated with a change in uncompensated care, but was associated with a 28.9 percent increase in charity care spending (SE = 8.8), or about $880,000 per hospital. However, total community benefit spending (including charity care) did not change. 340B was associated with an increase in the probability of offering discounted care (4.3 percentage points, SE = 1.6) from 84 to 88 percent and an increase in the income eligibility limit for discounted care (18.9 percentage points, SE = 5.6) from 294 to 313 percent. Participation was not associated with the probability of offering low-profit medical care services. CONCLUSIONS:Alternative measures show that newly participating hospitals may increase charity care, potentially through offering more patients discounted care. However, increases appear to be fully offset by reductions in other community benefit programs.

Dataset Information

An Experiential Resident Module for Understanding Social Determinants of Health at an Academic Safety-Net Hospital.

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An Experiential Resident Module for Understanding Social Determinants of Health at an Academic Safety-Net Hospital.

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