XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Standards of Medical Care in Diabetes

www.mobilehealthmap.org 617‐442‐3200 New research shows that mobile health clinics improve health outcomes for hard to reach populations in cost‐effective and culturally competent ways . A Harvard Medical School study determined that for every dollar invested in a mobile health clinic, the US healthcare system saves $30 on average. Mobile health clinics, which offer a range of services from preventive screenings to asthma treatment, leverage their mobility to treat people in the convenience of their own communities. For example, a mobile health clinic in Baltimore, MD, has documented savings of $3,500 per child seen due to reduced asthma‐related hospitalizations. The estimated 2,000 mobile health clinics across the country are providing similarly cost‐effective access to healthcare for a wide range of populations. Many successful mobile health clinics cite their ability to foster trusting relationships. Qualitative research in such mobile health clinics has found that patients value the informal, familiar environment in a convenient location, with staff who “are easy to talk to,” and that the staff’s “marriage of professional and personal discourses” provides patients the space to disclose information themselves. A communications academic argued that mobile health clinics’ unique use of space is important in facilitating these relationships. Mobile health clinics park in the heart of the community in familiar spaces, like shopping centers or bus stations, which lend themselves to the local community atmosphere.

Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care

We test whether significant differences in mental illness exist in a matched sample of Mental illness and the criminal justice system. In T. L. Scheid T. N. Brown (Eds.), A handbook for the study of mental health: Social contexts, theories. Find 9780521567633 A Handbook for the Study of Mental Health : Social Contexts, Theories, and Systems by Horwitz et al at over 30 bookstores. Buy, rent. A review of mental health problems in fathers following the birth of a child. for the study of mental health:Social contexts, theories, and systems (2nd ed., pp.

A Handbook for the Study of Mental Health: Social Contexts, Theories, and Systems

Objective To evaluate associations between the electronic environment, clerical burden, and burnout in US physicians. Participants and Methods Physicians across all specialties in the United States were surveyed between August and October 2014. Physicians provided information regarding use of electronic health records (EHRs), computerized physician order entry (CPOE), and electronic patient portals. Burnout was measured using validated metrics. Results Of 6375 responding physicians in active practice, 5389 (84.5%) reported that they used EHRs. Of 5892 physicians who indicated that CPOE was relevant to their specialty, 4858 (82.5%) reported using CPOE. Physicians who used EHRs and CPOE had lower satisfaction with the amount of time spent on clerical tasks and higher rates of burnout on univariate analysis. On multivariable analysis, physicians who used EHRs (odds ratio [OR]=0.67; 95% CI, 0.57-0.79; P P P Conclusion In this large national study, physicians' satisfaction with their EHRs and CPOE was generally low. Physicians who used EHRs and CPOE were less satisfied with the amount of time spent on clerical tasks and were at higher risk for professional burnout.

Relationship Between Clerical Burden and Characteristics of the Electronic Environment With Physician Burnout and Professional Satisfaction

BackgroundMajor depression is associated with significant disability, morbidity, and mortality. The current study estimated trends in the prevalence of major depression in the US population from 2005 to 2015 overall and by demographic subgroups.MethodsData were drawn from the National Survey on Drug Use and Health (NSDUH), an annual cross-sectional study of US persons ages 12 and over (total analytic sample N = 607 520). Past-year depression prevalence was examined annually among respondents from 2005 to 2015. Time trends in depression prevalence stratified by survey year were tested using logistic regression. Data were re-analyzed stratified by age, gender, race/ethnicity, income, and education.ResultsDepression prevalence increased significantly in the USA from 2005 to 2015, before and after controlling for demographics. Increases in depression were significant for the youngest and oldest age groups, men, and women, Non-Hispanic White persons, the lowest income group, and the highest education and income groups. A significant year × demographic interaction was found for age. The rate of increase in depression was significantly more rapid among youth relative to all older age groups.ConclusionsThe prevalence of depression increased significantly in the USA from 2005 to 2015. The rate of increase in depression among youth was significantly more rapid relative to older groups. Further research into understanding the macro level, micro level, and individual factors that are contributing to the increase in depression, including factors specific to demographic subgroups, would help to direct public health prevention and intervention efforts.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/8A2904A85BB1F4436102DB78E3854E35/S0033291717002781a.pdf/div-class-title-trends-in-depression-prevalence-in-the-usa-from-2005-to-2015-widening-disparities-in-vulnerable-groups-div.pdf

Trends in depression prevalence in the USA from 2005 to 2015: widening disparities in vulnerable groups

Objectives: To develop nationally representative estimates of rates of diagnosis of depression; to determine rates and type of treatment received by those diagnosed with depression; and to ascertain socioeconomic differences and trends in treatment rates of depression, including the effect of supplemental insurance coverage, for elderly Medicare fee-for-service beneficiaries.



Design: Analysis of merged interview and Medicare claims data for multiple years from merged Medicare claims and interview data from the Medicare Current Beneficiary Survey (MCBS), a nationally representative survey of Medicare participants.



Setting: Community dwellers.



Participants: Twenty thousand nine hundred sixty-six community-dwelling respondents aged 65 and older in the MCBS cost and use files for 1992 through 1998.



Measurements: Diagnoses recorded in Medicare claims were used to identify individuals who received a diagnosis of depression from a healthcare provider; pharmacy and claims data were used to identify receipt of antidepressants and psychotherapy by those diagnosed.



Results: The rate of depression diagnosis more than doubled, reaching 5.8% in 1998. Overall, about two-thirds of those diagnosed received treatment in each year; but those aged 75 and older, those of “Hispanic or other” ethnicity, and those without additional coverage to supplement Medicare were significantly less likely to receive treatment, controlling for other characteristics. If treated, members of these disadvantaged subgroups were less likely to receive psychotherapy.



Conclusion: Although depression has been thought until recent years to be underrecognized in the elderly, rates of diagnosis increased dramatically in the 1990s, with concomitant increases in treatment. Nevertheless, significant disparities by age, ethnicity, and supplemental insurance coverage persist in treatment of those diagnosed. Because depression is a major source of potentially treatable morbidity in older people, increased efforts are needed to ensure access to appropriate treatment across all subgroups of older people and to remove economic barriers to treatment.

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Diagnosis and treatment of depression in the elderly medicare population: predictors, disparities, and trends.

Depression imposes a substantial burden at the population level, with a lifetime prevalence of 13–16%, significant associated disability, and a liability to relapse.1–4 Its negative outcomes include suicide, substantial impairment, lower quality of life, increased health care utilization and cost, and adverse impact on employment productivity.3–10 Antidepressant treatment is efficacious, and treatment adherence is important in achieving effectiveness, ie, remission, restoring previous level of functioning, and preventing reoccurrence.11–13 Specifically, antidepressants are recommended to be continued for at least 4 months beyond the initial symptom resolution.14

Early discontinuation of antidepressant treatment has been documented in various populations and clinical settings.15–22 Existing findings on correlates/predictors of adherence to antidepressants often focus on a limited range of sociodemographic and clinical characteristics and have sometimes produced inconsistent findings. Comorbid medical conditions generally are associated with poor adherence,20 but findings on age and gender variations are mixed.15,20–23 Use of newer drugs20–22,24 and mental health specialty services15,16,20,21,25 generally have been associated with better antidepressant adherence. Economic status has rarely been included as an explanatory variable; we identified 1 study, which reported a positive association between income and adherence among veterans.15 Effects of economic-status variables on adherence have more often been studied with other pharmaceutical treatments, but the results are inconsistent.26 There is a need for up-to-date data because pronounced secular trends have been documented in depression care.27

Depression care improvement can be approached as a special case of the broader effort to improve management of chronic conditions of all kinds. The most prominent model, the chronic care model of Wagner and colleagues,28 frames clinical issues as multilevel challenges, and has motivated several initiatives to improve depression care.29–33 The Depression in Primary Care program, for example, identifies barriers and intervention opportunities at 6 levels (patient/consumer, provider, practice/delivery systems, plans, purchasers (public/private), and populations/policies).34

In this study, we investigated factors associated with poor adherence in a privately insured population using medical and pharmacy claims. Our goal was to examine the impact of patient characteristics in the context of provider, practice/delivery systems, or plan level variables, with the implications for policy and service system interventions likely to be of interest to purchasers and other stakeholders. Available variables include patients' demographic/economic characteristics, comorbid alcohol and other substance abuse, other prevalent comorbid conditions, depression treatment patterns, general use of health and pharmacy services, and insurance plan type. We conceptualized these variables based on their potential for modification by intervention at one or another level. For example, although patient behavior can be modified (eg, by education), most patient level variables available in our data are nonmodifiable (eg, demographics). Comorbid substance abuse is open to direct modification by treatment and to indirect influence by provider and practice innovations (eg, screening, prevention). Possibly open to some influence from higher level organizational interventions are the care sector of the initial depression diagnosis or use patterns of general medical services and pharmacy. Variables potentially open to organizational level interventions are follow-up care from mental health specialists, medication class, and company policies (eg, gate-keeping/authorization/referral requirements, financial incentives/costs etc.). We use plan type as a proxy for policies.

/pdf/adherence-to-antidepressant-treatment-among-privately-1yh6wnl2bq.pdf

Adherence to Antidepressant Treatment Among Privately Insured Patients Diagnosed With Depression

Medicaid claims and eligibility data, particularly when linked to other sources of patient-level and contextual information, represent a powerful and under-used resource for health services research on the use and outcomes of prescription drugs. However, their effective use poses many methodological and inferential challenges. This article reviews strengths, limitations, challenges, and recommended strategies in using Medicaid data for research on the initiation, continuation, and outcomes of prescription drug therapies. Drawing from published research using Medicaid data by the investigators and other groups, we review several key validity and methodological issues. We discuss strategies for claims-based identification of diagnostic subgroups and procedures, measuring and modeling initiation and persistence of regimens, analysis of treatment disparities, and examination of comorbidity patterns. Based on this review, we discuss "best practices" for appropriate data use and validity checking, approaches to statistical modeling of longitudinal patterns in the presence of typical challenges, and strategies for strengthening the power and potential of Medicaid datasets. Finally, we discuss policy implications, including the potential for the research use of Medicare Part D data and the need for further initiatives to systematically develop and optimally use research datasets that link Medicaid and other sources of clinical and outcome information.

/pdf/studying-prescription-drug-use-and-outcomes-with-medicaid-2cy9v9i2xs.pdf

Studying Prescription Drug Use and Outcomes With Medicaid Claims Data Strengths, Limitations, and Strategies

Objectives. We investigated racial/ethnic disparities in the diagnosis and treatment of depression among community-dwelling elderly.Methods. We performed a secondary analysis of Medicare Current Beneficiary Survey data (n = 33 708) for 2001 through 2005. We estimated logistic regression models to assess the association of race/ethnicity with the probability of being diagnosed and treated for depression with either antidepressant medication or psychotherapy.Results. Depression diagnosis rates were 6.4% for non-Hispanic Whites, 4.2% for African Americans, 7.2% for Hispanics, and 3.8% for others. After we adjusted for a range of covariates including a 2-item depression screener, we found that African Americans were significantly less likely to receive a depression diagnosis from a health care provider (adjusted odds ratio [AOR] = 0.53; 95% confidence interval [CI] = 0.41, 0.69) than were non-Hispanic Whites; those diagnosed were less likely to be treated for depression (AOR = 0.45; 95% CI = 0.30, 0.66).Concl...

Racial and Ethnic Disparities in Depression Care in Community-Dwelling Elderly in the United States

Objectives:Despite high prevalence rates of depression in primary care, depressive symptoms are often undetected by physicians. Screening for depression is now recommended as a part of routine primary care; however, recent estimates of rates and patterns of depression screening are lacking in the literature. This study examined national rates and patterns of depression screening among visits to office-based primary care physicians.Methods:A secondary analysis of data from the 2012 and 2013 National Ambulatory Medical Care Survey was conducted. The sample consisted of 33,653 physician-patient encounters.Results:The overall rate of depression screening was 4.2%. African Americans were half as likely to be screened compared with whites, and elderly patients were half as likely to be screened compared with middle-aged patients. Patients with a chronic condition were more likely than patients without a chronic condition to receive depression screening, and the likelihood of being screened increased with each a...

Ayse Akincigil

Papers

Diagnosis and treatment of depression in the elderly medicare population: predictors, disparities, and trends.

Adherence to Antidepressant Treatment Among Privately Insured Patients Diagnosed With Depression

Studying Prescription Drug Use and Outcomes With Medicaid Claims Data Strengths, Limitations, and Strategies

Racial and Ethnic Disparities in Depression Care in Community-Dwelling Elderly in the United States

National Rates and Patterns of Depression Screening in Primary Care: Results From 2012 and 2013