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A number of delivery and payment reform initiatives within Medicaid include a focus on linking health care and social needs. In many cases, these efforts are part of the larger multi-payer SIM models noted above and may be part of Section Medicaid demonstration waivers. Several other state Medicaid programs have launched Accountable Care Organization ACO models that often include population-based payments or total cost of care formulas, which may provide incentives for providers to address the broad needs of Medicaid beneficiaries, including the social determinants of health.

DSRIP initiatives link Medicaid funding for eligible providers to process and performance metrics, which may involve addressing social needs and factors. The state also has invested significant state dollars outside of its DSRIP waiver in housing stock to ensure that a better supply of appropriate housing is available.

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Medicaid programs also are providing broader services to support health through the health homes option established by the ACA. Under this option, states can establish health homes to coordinate care for people who have chronic conditions. Health home services include comprehensive care management, care coordination, health promotion, comprehensive transitional care, patient and family support, as well as referrals to community and social support services. Health home providers can be a designated provider, a team of health professionals linked to a designated provider, or a community health team.

A total of 21 states report that health homes were in place in fiscal year Some states are providing housing support to Medicaid enrollees through a range of optional state plan and waiver authorities. While states cannot use Medicaid funds to pay for room and board, Medicaid funds can support a range of housing-related activities, including referral, support services, and case management services that help connect and retain individuals in stable housing.

Through a range of optional and waiver authorities, some states are providing voluntary supported employment services to Medicaid enrollees. Supported employment services may include pre-employment services e. States often target these services to specific Medicaid populations, such as persons with serious mental illness or substance use disorders and individuals with intellectual or developmental disabilities.

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For example, under a Section waiver, Hawaii offers supportive employment services to Medicaid enrollees with serious mental illness SMI , individuals with serious and persistent mental illness SPMI , and individuals who require support for emotional and behavioral development SEBD. Medicaid MCOs are increasingly engaging in activities to address social determinants of health. Some providers have adopted screening tools within their practices to identify health-related social needs of patients.

Other organizations and entities have created screening tools, including Health Leads, a non-profit organization funded by the Robert Wood Johnson Foundation, which has developed a social needs screening toolkit for providers and CMMI, which released an Accountable Health Communities screening tool to help providers identify unmet patient needs. The ACA provided a key opportunity to help improve access to care and reduce longstanding disparities faced by historically underserved populations through both its coverage expansions and provisions to help bridge health care and community health.

To date, millions of Americans have gained coverage through the coverage expansions, but coverage alone is not enough to improve health outcomes and achieve health equity. With growing recognition of the importance of social factors to health outcomes, an increasing number of initiatives have emerged to address social determinants of health by bringing a greater focus on health within non-health sectors and increasingly recognizing and addressing health-related social needs through the health care system. Within the health care system, a broad range of initiatives have been launched at the federal and state level, including efforts within Medicaid.

Many of these initiatives reflect new funding and demonstration authorities provided through the ACA to address social determinants of health and further health equity.

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Although there has been significant progress recognizing and addressing social determinants of health, many challenges remain. Notably, these efforts require working across siloed sectors with separate funding streams, where investments in one sector may accrue savings in another. Moreover, communities may not always have sufficient service capacity or supply to meet identified needs. Further, there remain gaps and inconsistencies in data on social determinants of health that limit the ability to aggregate data across settings or to use data to inform policy and operations, guide quality improvement, or evaluate interventions.

The Administration has begun phasing out DSRIP programs, 50 is revising Medicaid managed care regulations, 51 and has signaled reductions in funding for prevention and public health. It has also announced plans to change the direction of models under the CMMI. Key Findings Social determinants of health are the conditions in which people are born, grow, live, work and age that shape health. This brief provides an overview of social determinants of health and emerging initiatives to address them.

It shows: Social determinants of health include factors like socioeconomic status, education, neighborhood and physical environment, employment, and social support networks, as well as access to health care. Addressing social determinants of health is important for improving health and reducing longstanding disparities in health and health care.

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There are a growing number of initiatives to address social determinants of health within and outside of the health care system. Outside of the health care system, initiatives seek to shape policies and practices in non-health sectors in ways that promote health and health equity. The study was conducted in accordance with the Guidelines for Good Pharmacoepidemiology Practices 23 and is registered with ClinicalTrials. Two questionnaires, one for PwO and one for HCPs Appendix S1, pages 28— , were developed by an international steering committee of obesity experts, representing primary care, medical specialities and psychology, from the participating countries, in addition to three medical doctors employed by the sponsor, Novo Nordisk.

This was to assess clarity, face validity and relevance of the questions. Surveys were designed to facilitate comparisons within and across respondent types. KJT Group oversaw all aspects of data collection and reporting. Demographic targets were monitored throughout data collection to ensure population representativeness.

Respondents were compensated for their time and were recruited, for the most part, via online panel companies to whom they had given permission to be contacted for research purposes Appendix S1, page 2. Respondents completed the survey in the native language of their country. All respondents could suspend taking the survey at any time and for any reason at any part of the survey.

Participants were allowed to complete the survey only once, as assessed by prior online consent and digital fingerprinting Appendix S1, page 2. To avoid bias, questionnaire items were carefully phrased and presented in the same order for each respondent and items in a list were displayed alphabetically, categorically, chronologically or randomly, as relevant for each response set.

Some of these outcomes will be published separately. Adjustment for multiple testing was not undertaken as this research was exploratory and descriptive in nature. Only data from those who completed the survey were included in the analyses. The final PwO sample, including those failing to qualify for the survey, was weighted to representative demographic targets within each country for age, gender, household income, education and region Appendix S1, page 4.

HCP data were not weighted. It took a median of 3 years and a mean of 6 years between the reported time that PwO first began struggling with excess weight or obesity and when they first had a weight management conversation with an HCP Figure 3 B. The most frequent methods for managing weight discussed between PwO and HCPs were general improvement in eating habits and general increase in physical activity level, whereas specific diet or exercise programmes, tracking, weight loss medications and bariatric surgery were less likely to have been discussed Figure S13A.

Referrals to specialists were recommended infrequently Figure S13A. More than half of the HCPs surveyed indicated that the limited appointment time is also a factor in not discussing weight loss Figure 4. Data concerning other outcomes are presented in Figures S16—S Both PwO and HCPs stated that they recognized obesity as a chronic disease; however, most PwO assumed complete responsibility for weight loss. The results suggest that many PwO are concerned about the impact of excess weight on their health and are making serious efforts to lose weight, but they have a limited response to such weight loss efforts on their own.

In contrast, the fact that HCPs believe that PwO are not interested or motivated to lose weight may be preventing conversations concerning weight loss.

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This might reflect the actual experience of HCPs or may represent an unconscious negative bias. Other studies have previously highlighted a disconnection between perceptions and actions. A potential barrier to effective obesity care that was identified here was the length of time years between when PwO began struggling with their weight and when they first had a weight management conversation with an HCP. Decreasing this time gap could reduce the complications of obesity experienced by PwO and, ultimately, would lessen the economic burden of the disease. Jointly agreeing that a patient has overweight or obesity, with a BMI calculation in the context of their personal health profile, may be an effective way to initiate such a conversation.

Recognizing positive patient responses to conversational cues may allow for therapeutic intervention or development of a management plan. Our data suggest that PwO are motivated to engage in weight loss efforts and would like their HCPs to initiate a conversation about weight. This is consistent with a UK study showing that most patients found discussing their weight with an HCP appropriate and helpful. Part of this effort calls for eradication of the prevalent stigmatizing attitudes that are highlighted in prior studies 33 and for eradication of HCPs' misperception that PwO are not motivated, as shown here.

Setting realistic and achievable weight loss goals could contribute to management of expectations, with collaborative communication and more manageable targets potentially providing encouragement for continued patient engagement. However, as recommended by current clinical practice guidelines, BMI is used for the initial assessment and diagnosis of obesity, taking into account factors such as age, ethnicity and muscularity.

Low response rates can affect sample representativeness and are a known limitation of this type of study. Internet access could also have restricted participation in some countries. Strengths of the study include the large number of respondents, the international nature of the study and the scientific rigor with which the survey was designed and implemented, including stratified sampling to provide a cohort representative of the general population.

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  • Overall, our data suggest that PwO are motivated to lose weight and that there is an opportunity for HCPs to initiate earlier, effective weight loss conversations with minimal fear of offence. Our study also reveals a global need for improved education of both PwO and HCPs concerning the biological basis and clinical management of obesity, and for a more positive attitude on the part of HCPs towards initiating discussions with PwO concerning weight and weight management.

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    We gratefully acknowledge the study participants and all personnel involved in the study. All authors received funding for travel expenses from Novo Nordisk to attend author meetings during the conduct of the study. All authors contributed to the design of the study. All authors participated in interpretation of the data and drafting and revision of the manuscript. All authors reviewed and approved the final, submitted version. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors.

    Any queries other than missing content should be directed to the corresponding author for the article. Volume 21 , Issue 8. The full text of this article hosted at iucr. If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account.

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    If the address matches an existing account you will receive an email with instructions to retrieve your username. Diabetes, Obesity and Metabolism Volume 21, Issue 8. Jason C. Funding information This study was sponsored by Novo Nordisk. Tools Request permission Export citation Add to favorites Track citation. Share Give access Share full text access. Share full text access. Please review our Terms and Conditions of Use and check box below to share full-text version of article.

    Abstract Aims Despite increased recognition as a chronic disease, obesity remains greatly underdiagnosed and undertreated. Materials and methods An online survey was conducted in 11 countries.