Initiating and Implementing Social Determinants of Health Data Collection in Community Health Centers.
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SUBMITTER: Gruß I
PROVIDER: S-EPMC7875127 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:National leaders recommend documenting social determinants of health and actions taken to address social determinants of health in electronic health records, and a growing body of evidence suggests the health benefits of doing so. However, little evidence exists to guide implementation of social determinants of health documentation/action. METHODS:This paper describes a 5-year, mixed-methods, stepped-wedge trial with realist evaluation, designed to test the impact of providing 30 community health centers with step-by-step guidance on implementing electronic health record-based social determinants of health documentation. This guidance will entail 6 months of tailored support from an interdisciplinary team, including training and technical assistance. We will report on tailored support provided at each of five implementation steps; impact of tailored implementation support; a method for tracking such tailoring; and context-specific pathways through which these tailored strategies effect change. We will track the competencies and resources needed to support the study clinics' implementation efforts. DISCUSSION:Results will inform how to tailor implementation strategies to meet local needs in real-world practice settings. Secondary analyses will assess impacts of social determinants of health documentation and referral-making on diabetes outcomes. By learning whether and how scalable, tailored implementation strategies help community health centers adopt social determinants of health documentation and action, this study will yield timely guidance to primary care providers. We are not aware of previous studies exploring implementation strategies that support adoption of social determinants of action using electronic health and interventions, despite the pressing need for such guidance. TRIAL REGISTRATION:clinicaltrials.gov, NCT03607617 , registration date: 7/31/2018-retrospectively registered.
| S-EPMC6348649 | biostudies-literature
Project description:BACKGROUND:Vietnam has a smoking prevalence that is the second highest among Southeast Asian countries (SEACs). According to the World Health Organization (WHO), most reductions in mortality from tobacco use in the near future will be achieved through helping current users quit. Yet, largely due to a lack of research on strategies for implementing WHO-endorsed treatment guidelines in primary care settings, services to treat tobacco dependence are not readily available to smokers in low middle-income countries (LMICs) like Vietnam. The objective of this study is to conduct a cluster randomized controlled trial that compares the effectiveness of two system-level strategies for implementing evidence-based guidelines for the treatment of tobacco use in 26 public community health centers (CHCs) in Vietnam. METHODS/DESIGN:The current study will use a cluster-randomized design and multiple data sources (patient exit interviews, provider and village health worker (VHW) surveys, and semi-structured provider/VHW interviews) to study the process of adapting and implementing clinical practice guidelines in Vietnam and theory-driven mechanisms hypothesized to explain the comparative effectiveness of the two strategies for implementation. CHCs will be randomly assigned to either of the following: (1) training plus clinical reminder system (TC) or (2) TC?+?referral to a VHW (TCR) for three in person counseling sessions. The primary outcome is provider adherence to tobacco use treatment guidelines. The secondary outcome is 6-month biochemically verified smoking abstinence. DISCUSSION:The proposed implementation strategies draw on evidence-based approaches and a growing literature that supports the effectiveness of integrating community health workers as members of the health care team to improve access to preventive services. We hypothesize that the value of these implementation strategies is additive and that incorporating a referral resource that allows providers to delegate the task of offering counseling (TCR) will be superior to TC alone in improving delivery of cessation assistance to smokers. The findings of this research have potential to guide large-scale adoption of promising strategies for implementing and disseminating tobacco use treatment guidelines throughout the public health system in Vietnam and will serve as a model for similar action in other LMICs. TRIAL REGISTRATION:NCT01967654.
| S-EPMC4600252 | biostudies-literature
Project description:ImportanceResponding to the substantial research on the relationship between social risk factors and health, enthusiasm has grown around social risk screening in health care settings, and numerous US health systems are experimenting with social risk screening initiatives. In the absence of standard social risk screening recommendations, some health systems are exploring using publicly available community-level data to identify patients who live in the most vulnerable communities as a way to characterize patient social and economic contexts, identify patients with potential social risks, and/or to target social risk screening efforts.ObjectiveTo explore the utility of community-level data for accurately identifying patients with social risks by comparing the social deprivation index score for the census tract where a patient lives with patient-level social risk screening data.Design, setting, and participantsCross-sectional study using patient-level social risk screening data from the electronic health records of a national network of community health centers between June 24, 2016, and November 15, 2018, linked to geocoded community-level data from publicly available sources. Eligible patients were those with a recorded response to social risk screening questions about food, housing, and/or financial resource strain, and a valid address of sufficient quality for geocoding.ExposuresSocial risk screening documented in the electronic health record.Main outcomes and measuresCommunity-level social risk was assessed using census tract-level social deprivation index score stratified by quartile. Patient-level social risks were identified using food insecurity, housing insecurity, and financial resource strain screening responses.ResultsThe final study sample included 36 578 patients from 13 US states; 22 113 (60.5%) received public insurance, 21 181 (57.9%) were female, 17 578 (48.1%) were White, and 10 918 (29.8%) were Black. Although 6516 (60.0%) of those with at least 1 social risk factor were in the most deprived quartile of census tracts, patients with social risk factors lived in all census tracts. Overall, the accuracy of the community-level data for identifying patients with and without social risks was 48.0%.Conclusions and relevanceAlthough there is overlap, patient-level and community-level approaches for assessing patient social risks are not equivalent. Using community-level data to guide patient-level activities may mean that some patients who could benefit from targeted interventions or care adjustments would not be identified.
| S-EPMC7596576 | biostudies-literature
Project description:Social determinants of health (SDH) impact health outcomes. Medical centers have begun to collect SDH data, urged by government and scientific entities. Provider perspectives on collecting SDH are unknown. The aim is to understand differences in views and preferences according to provider characteristics. A cross-sectional survey of University of Miami clinical faculty was conducted in late 2016. The survey contained 11 questions: 8 demographic and departmental responsibilities questions and 3 Likert scale questions to capture collection and use of SDH perspectives. The main outcome was whether providers thought the benefit of collecting SDH outweighs the burden and risks. In all, 240 faculty members were included. The majority were men (64%), with a mean age of 51 years. Among participants, 53.5% were non-Hispanic white, 32% were Hispanic, 5% were Black/African American, and 5% were Asian. The majority agreed that SDH are important predictors of health outcomes and quality of care (83%). When comparing minority to nonminority faculty, 25% believed that SDH should only be available to PCPs, compared to 8% of nonminorities (P?<?0.01). In a multivariate model, belonging to a racial ethnic minority was the only characteristic associated with believing that benefits of collecting SDH outweigh the risks (odds ratio 1.87, 95% confidence interval 1.02- 3.5) after adjusting for age, sex, minority status, health care provider type, type of responsibilities, and department. This study reveals that although most providers of a health system believe social risks impact health outcomes and quality metrics, the buy-in to collect SDH varies according to the racial/ethnic composition of the faculty.
| S-EPMC6425987 | biostudies-literature
Project description:Objectives. To describe the types of social services provided at community health centers (CHCs), characteristics of CHCs providing these services, and the association between on-site provision and health care quality.Methods. We surveyed CHCs in 12 US states and the District of Columbia during summer 2017 (n = 208) to identify referral to and provision of services to address 8 social needs. Regression models estimated factors associated with the provision of social services by CHCs and the association between providing services and health care quality (an 8-item composite).Results. CHCs most often offered on-site assistance for needs related to food or nutrition (43%), interpersonal violence (32%), and housing (30%). Participation in projects with community-based organizations was associated with providing services on-site (odds ratio = 2.48; P = .018). On-site provision was associated with better performance on measures of health care quality (e.g., each additional social service was associated with a 4.3 percentage point increase in colorectal cancer screenings).Conclusions. Some CHCs provide social services on-site, and this was associated with better performance on measures of health care quality.Public Health Implications. Health care providers are increasingly seeking to identify and address patients' unmet social needs, and on-site provision of services is 1 strategy to consider.
| S-EPMC7067112 | biostudies-literature
Project description:ObjectivesUsing predictive modeling techniques, we developed and compared appointment no-show prediction models to better understand appointment adherence in underserved populations.Methods and materialsWe collected electronic health record (EHR) data and appointment data including patient, provider and clinical visit characteristics over a 3-year period. All patient data came from an urban system of community health centers (CHCs) with 10 facilities. We sought to identify critical variables through logistic regression, artificial neural network, and naïve Bayes classifier models to predict missed appointments. We used 10-fold cross-validation to assess the models' ability to identify patients missing their appointments.ResultsFollowing data preprocessing and cleaning, the final dataset included 73811 unique appointments with 12,392 missed appointments. Predictors of missed appointments versus attended appointments included lead time (time between scheduling and the appointment), patient prior missed appointments, cell phone ownership, tobacco use and the number of days since last appointment. Models had a relatively high area under the curve for all 3 models (e.g., 0.86 for naïve Bayes classifier).DiscussionPatient appointment adherence varies across clinics within a healthcare system. Data analytics results demonstrate the value of existing clinical and operational data to address important operational and management issues.ConclusionEHR data including patient and scheduling information predicted the missed appointments of underserved populations in urban CHCs. Our application of predictive modeling techniques helped prioritize the design and implementation of interventions that may improve efficiency in community health centers for more timely access to care. CHCs would benefit from investing in the technical resources needed to make these data readily available as a means to inform important operational and policy questions.
| S-EPMC6243417 | biostudies-literature
Project description:Evidence is needed about how to effectively support health care providers in implementing screening for social risks (adverse social determinants of health) and providing related referrals meant to address identified social risks. This need is greatest in underresourced care settings. The authors tested whether an implementation support intervention (6 months of technical assistance and coaching study clinics through a five-step implementation process) improved adoption of social risk activities in community health centers (CHCs). Thirty-one CHC clinics were block-randomized to six wedges that occurred sequentially. Over the 45-month study period from March 2018 to December 2021, data were collected for 6 or more months preintervention, the 6-month intervention period, and 6 or more months postintervention. The authors calculated clinic-level monthly rates of social risk screening results that were entered at in-person encounters and rates of social risk-related referrals. Secondary analyses measured impacts on diabetes-related outcomes. Intervention impact was assessed by comparing clinic performance based on whether they had versus had not yet received the intervention in the preintervention period compared with the intervention and postintervention periods. In assessing the results, the authors note that five clinics withdrew from the study for various bandwidth-related reasons. Of the remaining 26, a total of 19 fully or partially completed all 5 implementation steps, and 7 fully or partially completed at least the first 3 steps. Social risk screening was 2.45 times (95% confidence interval [CI], 1.32-4.39) higher during the intervention period compared with the preintervention period; this impact was not sustained postintervention (rate ratio, 2.16; 95% CI, 0.64-7.27). No significant difference was seen in social risk referral rates during the intervention or postintervention periods. The intervention was associated with greater blood pressure control among patients with diabetes and lower rates of diabetes biomarker screening postintervention. All results must be interpreted considering that the Covid-19 pandemic began midway through the trial, which affected care delivery generally and patients at CHCs particularly. Finally, the study results show that adaptive implementation support was effective at temporarily increasing social risk screening. It is possible that the intervention did not adequately address barriers to sustained implementation or that 6 months was not long enough to cement this change. Underresourced clinics may struggle to participate in support activities over longer periods without adequate resources, even if lengthier support is needed. As policies start requiring documentation of social risk activities, safety-net clinics may be unable to meet these requirements without adequate financial and coaching/technical support.
| S-EPMC10161727 | biostudies-literature
Project description:BackgroundUntil 2016, community health centers (CHCs) reported community health workers (CHWs) as part of their overall enabling services workforce, making analyses of CHW use over time infeasible in the annual Uniform Data System (UDS).ObjectiveThe objective of this study was to examine changes in the CHW workforce among CHCs from 2016 to 2018 and factors associated with the use of CHWs.Research design, subjects, measuresThe two-part model estimated separate effects for the probability of using any CHW and extent of CHW full-time equivalents (FTEs) reported in those CHCs, using a total of 4102 CHC-year observations from 2016 to 2018. To estimate the extent to which increases in CHW workforce are attributable to real growth or rather are a consequence of a change in reporting category, we also conducted a difference-in-differences analysis to compare non-CHW enabling services FTEs between CHCs with and without CHWs before (2013-2015) and after (2016-2018) the reporting change in 2016.ResultsThe rate of CHCs that employed CHWs rose from 20.04% in 2016 to 28.34% in 2018, while average FTEs stayed relatively flat (3.32 FTEs). Patient visit volume (larger CHCs) and grant funding (less reliant on federal but more reliant on private funding) were significant factors associated with CHW use. However, we found that a substantial portion of this growth was attributable to a change in UDS reporting categories.ConclusionWhile we do not address the reasons why CHCs have been slow to use CHWs, our results point to substantial financial barriers associated with CHCs' expanding the use of CHWs.
| S-EPMC8428847 | biostudies-literature
Project description:PurposeTo quantify and characterize social determinants of health (SDoH) data coverage using single-center electronic health records (EHRs) and the National Institutes of Health All of Us research program.DesignRetrospective cohort study from June 2014 through June 2021.ParticipantsAdults 18 years of age or older with a diagnosis of diabetic retinopathy, glaucoma, cataracts, or age-related macular degeneration.MethodsFor All of Us, research participants completed online survey forms as part of a nationwide prospective cohort study. In local EHRs, patients were selected based on diagnosis codes.Main outcome measuresSocial determinants of health data coverage, characterized by the proportion of each disease cohort with available data regarding demographics and socioeconomic factors.ResultsIn All of Us, we identified 23 806 unique adult patients, of whom 2246 had a diagnosis of diabetic retinopathy, 13 448 had a diagnosis of glaucoma, 6634 had a diagnosis of cataracts, and 1478 had a diagnosis of age-related macular degeneration. Survey completion rates were high (99.5%-100%) across all cohorts for demographic information, overall health, income, education, and lifestyle. However, health care access (12.7%-29.4%), housing (0.7%-1.1%), social isolation (0.2%-0.3%), and food security (0-0.1%) showed significantly lower response rates. In local EHRs, we identified 80 548 adult patients, of whom 6616 had a diagnosis of diabetic retinopathy, 26 793 had a diagnosis of glaucoma, 40 427 had a diagnosis of cataracts, and 6712 had a diagnosis of age-related macular degeneration. High data coverage was found across all cohorts for variables related to tobacco use (82.84%-89.07%), alcohol use (77.45%-83.66%), and intravenous drug use (84.76%-93.14%). However, low data coverage (< 50% completion) was found for all other variables, including education, finances, social isolation, stress, physical activity, food insecurity, and transportation. We used chi-square testing to assess whether the data coverage varied across different disease cohorts and found that all fields varied significantly (P < 0.001).ConclusionsThe limited and highly variable data coverage in both local EHRs and All of Us highlights the need for researchers and providers to develop SDoH data collection strategies and to assemble complete datasets.
| S-EPMC9162036 | biostudies-literature
Project description:Colorectal cancer (CRC) screening can reduce cancer deaths. However, screening and abnormal test follow-up rates are low among underserved populations. The screening rates of 19-58%, and rates of colonoscopy completion after abnormal stool tests of 18-57% in community health centers (CHC) systems are low. This highlights an opportunity to improve early detection and decrease burden of CRC in our region. Mailed outreach and navigation programs have been shown to increase colonoscopy completion rate. The next step is to understand how to best implement these programs in the community on a larger scale. To achieve this goal, the investigators propose a Hub-and-Spoke intervention combining centralized strategies to maximize CRC screening, follow-up, and referral-to-care. The investigators hypothesize that this intervention will be superior to usual care for increasing CRC screening, abnormal test follow-up, and referral-to-care.
The investigators will conduct a randomized trial to determine effectiveness in: 1) improvement in proportion of individuals up-to-date with screening 3 years post implementation; 2) proportion with abnormal FIT who complete diagnostic colonoscopy within 6 months; and 3) proportion with CRC completing first treatment evaluation.
The investigators will also evaluate the implementation, scalability, and sustainability of the multi-level implementation strategy. The intervention consists of: Mailed FIT and Reminders. Eligible individuals will receive an introductory letter describing the importance of CRC screening and noting that follow-up mail will include a FIT Kit. It will also be offered to patients who completed prior mailed FIT with normal test results. All materials will be in English and Spanish. Two weeks later, participants will receive a packet via mail containing the FIT kit, a one-page invitation inviting FIT completion and FIT instructions, a postage-paid envelope for return to the patient’s CHC, and COVID-19 message. For non-compliant individuals not returning the kit, a reminder phone call and text message will be delivered 2 weeks later. The investigators will track returned letters, individuals who are later found to be up-to date with screening, and those who decline screening. The CHC will provide care coordination for patients with an abnormal FIT result.
| 2381718 | ecrin-mdr-crc