Individual-Level and Neighborhood-Level Factors Associated with Longitudinal Changes in Cardiometabolic Measures in Participants of a Clinic-Based Care Coordination Program: A Secondary Data Analysis.

Background: Identifying individual and neighborhood-level factors associated with worsening cardiometabolic risks despite clinic-based care coordination may help identify candidates for supplementary team-based care. Methods: Secondary data analysis of data from a two-year nurse-led care coordination program cohort of Medicare, Medicaid, dual-eligible adults, Leveraging Information Technology to Guide High Tech, High Touch Care (LIGHT2), from ten Midwestern primary care clinics in the U.S.

An index of geospatial disadvantage predicts both obesity and unmeasured body weight.

Neighborhood context impacts health. Using an index of geospatial disadvantage measures to predict neighborhood socioeconomic disparities would support area-based allocation of preventative resources, as well as the use of location as a clinical risk factor in care of individual patients. This study tested the association of the Area Deprivation Index (ADI), a neighborhood-based index of socioeconomic contextual disadvantage, with elderly obesity risk.

The Effect of Neighborhood Disadvantage on Diabetes Prevalence.

Patient socioeconomic data is not usually included in medical records nor easily accessible to clinicians, yet socioeconomic disadvantage can be an important guide to disease management. This study evaluated the neighborhood-level Area Deprivation Index (ADI), a measure of neighborhood socioeconomic disadvantage, as a factor in diabetes mellitus prevalence. Electronic health records at an academic hospital system identified 4,770 Medicare beneficiaries.

The Paradox of Higher Charges for Lower-Risk Inpatient Admissions: When Healthier Patients Cost More.

Risk stratification is essential to achieving the Triple Aim of better health, better care, and lower costs. Although risk tiers based on chronic disease diagnoses and recent healthcare utilization were predictive of healthcare utilization and charges in a managed population, their correlation with specific high-cost outcomes was unknown. More detailed analyses were performed to confirm that admissions for higher-risk patients were more expensive.

Longitudinal Changes in Risk Stratification for a Managed Population.

The LIGHT project managed the care of approximately 10,000 Medicare (primarily elderly) and Medicaid (low income) patients between 2013 and 2015. Risk tiers based on chronic disease diagnoses and recent healthcare utilization were strongly predictive of future healthcare utilization, and the authors expected that the members of an aging and well-insured population would gradually rise in risk of healthcare utilization over the course of three years. Various analytic techniques were used to characterize the members of higher risk tiers.

Contrast Mining for Pattern Discovery and Descriptive Analytics to Tailor Sub-Groups of Patients Using Big Data Solutions.

The shift to electronic health records has created a plethora of information ready to be examined and acted upon by those in the medical and computational fields. While this allows for novel research on a scale unthinkable in the past, all discoveries still rely on some initial insight leading to a hypothesis. As the size and variety of data grows so do the number of potential findings, making it necessary to optimize hypothesis generation to increase the rate and importance of discoveries produced from the data.

Combining Contrast Mining with Logistic Regression To Predict Healthcare Utilization in a Managed Care Population.

Background: Because 5% of patients incur 50% of healthcare expenses, population health managers need to be able to focus preventive and longitudinal care on those patients who are at highest risk of increased utilization. Predictive analytics can be used to identify these patients and to better manage their care. Data mining permits the development of models that surpass the size restrictions of traditional statistical methods and take advantage of the rich data available in the electronic health record (EHR), without limiting predictions to specific chronic conditions.

Identifying Patients at Risk of High Healthcare Utilization.

To develop a systematic and reproducible way to identify patients at increased risk for higher healthcare costs. Medical records were analyzed for 9,581 adults who were primary care patients in the University of Missouri Health System and who were enrolled in Medicare or Medicaid. Patients were categorized into one of four risk tiers as of October 1, 2013, and the four tiers were compared on demographic characteristics, number of healthcare episodes, and healthcare charges in the year before and the year after cohort formation.

Secondary Use of Clinical Data to Enable Data-Driven Translational Science with Trustworthy Access Management.

University of Missouri (MU) Health Care produces a large amount of digitized clinical data that can be used in clinical and translational research for cohort identification, retrospective data analysis, feasibility study, and hypothesis generation. In this article, the implementation of an integrated clinical research data repository is discussed. We developed trustworthy access-management protocol for providing access to both clinically relevant data and protected health information.

Monitoring Resource Utilization in a Health Care Coordination Program.

Purpose Of The Study: This initial article describes the development of a health care coordination intervention and documentation system designed using the Agency for Healthcare Research and Quality (AHRQ) Care Coordination Atlas framework for Centers for Medicare & Medicaid-funded innovation project, Leveraging Information Technology to Guide High-Tech, High-Touch Care (LIGHT).

Primary Practice Setting(s): The study occurred at an academic medical center that serves 114 counties. Twenty-five registered nurse care managers (NCMs) were hired to work with 137 providers in 10 family community and internal medicine clinics.

Online electronic data capture and research data repository system for clinical and translational research.

Data is at the core of any clinical and translational research (CTR). In many studies, the electronic data capture (EDC) method has been found to be more efficient than standard paper-based data collection methods in many aspects, including accuracy, integrity, timeliness, and cost-effectiveness. The objective of this article is to present a secure, web-based EDC system for CTR that has been implemented by the Institute for Clinical and Translational Science (iCATS) at the University of Missouri School of Medicine.

Access to musculoskeletal specialists and resources in free and charitable clinics: a survey of clinic directors.

Objective: To evaluate the capabilities and resources of free and charitable clinics in the United States to deliver musculoskeletal care to an indigent population.

Design: A voluntary, anonymous, cross-sectional survey.

Setting: Electronic mailing list for the National Association of Free and Charitable Clinics in September 2011, and in person at the Annual Summit for the National Association of Free and Charitable Clinics in October 2011.

Relationship of psychiatric history to pain reports in rheumatoid arthritis.

Objective: The purpose was to examine the relationship of pre-existing psychiatric history to pain reports in a cohort of persons with RA and concomitant major depression who were receiving a trial of antidepressant medication.

Method: RA patients (n = 41) with a current episode of major depression were divided into two subgroups comprised of those with a previous psychiatric history (PSY+) (n = 20) and those without a previous psychiatric history (PSY-) (n = 21). The groups were compared with regard to their responsiveness to a regimen of antidepressive medication on measures of depression, pain, coping, and life stress over a period of 15 months.

Analyzing reliability of change in depression among persons with rheumatoid arthritis.

Objective: To examine several methods of determining reliability of change constructs in depressive symptoms in patients with rheumatoid arthritis (RA) and to demonstrate the strengths, weaknesses, and uses of each method.

Methods: Data were analyzed from a cohort of 54 persons with RA who participated in a combined behavioral/pharmacologic intervention of 15 months duration. These longitudinal data were used to examine 3 methodologies for assessing the reliability of change for various measures of depression.

Health status, cognitive coping, and depressive symptoms: testing for a mediator effect.

Objective: Research has established a link between health status and symptoms of depression in persons with rheumatoid arthritis (RA), but the effects of "cognitive coping" variables have not been extensively studied. We examined the mediator effect of a cognitive coping variable (Pain Control and Rational Thinking factor score from the Coping Strategies Questionnaire) over the course of a pharmacological intervention.

Method: Data were analyzed from 54 persons with RA, all of whom met diagnostic criteria for major depression.

Anxiety in rheumatoid arthritis.

Objective: To examine the level of anxiety experienced by individuals with rheumatoid arthritis (RA).

Methods: Data from 2 previous studies were used to compare the level of anxiety (measured by the State-Trait Anxiety Inventory) in the following 4 subgroups: a general RA sample, a general osteoarthritis sample, a sample with both RA and major depression, and a normative sample of age-equivalent, working adults. Canonical correlations were used to examine associations between measures of anxiety and measures of both stress and depression.

Management of depression in rheumatoid arthritis: a combined pharmacologic and cognitive-behavioral approach.

Objective: To examine the effectiveness of cognitive-behavioral and pharmacologic treatment of depression in rheumatoid arthritis (RA).

Methods: Subjects (n = 54) with confirmed diagnoses of both major depression and RA were randomly assigned to 1 of 3 groups: 1) cognitive-behavioral/pharmacologic group (CB-PHARM), 2) attention-control/pharmacologic group, or 3) pharmacologic control group. Measures of depression, psychosocial status, health status, pain, and disease activity were collected at baseline, posttreatment (10 weeks), 6-month followup, and 15-month followup.

Assessment of depression in rheumatoid arthritis: a modified version of the center for epidemiologic studies depression scale.

Objective: The Center for Epidemiologic Studies Depression Scale (CES-D) is an instrument commonly used to assess depressive symptoms. Although the psychometric properties of the instrument are well established, the instrument's ability to identify confirmed cases of major depression has been unclear. The purpose of this study was to evaluate the ability of cutoff scores from both a full scale and a modified CES-D to detect major depression in people with rheumatoid arthritis (RA).

Research activities and perspectives of individuals completing a research enrichment program for physiatrists.

Objective: To investigate the research activity and perspectives, and the predictors and barriers to research activity, in a cohort of individuals completing a research enrichment program for physiatrists.

Design: A retrospective cohort study design was utilized. Data collection was accomplished with a mailed survey, which was sent to 68 individuals who had completed the Research Enrichment Program for Physiatrists between 1991 and 1998.

Clinical outcomes following a trial of sertraline in rheumatoid arthritis.

We report an open-label trial of sertraline in the treatment of major depression in 54 consecutive rheumatoid arthritis (RA) patients meeting DSM-IV criteria for major depressive disorder. We initially surveyed 628 RA outpatients with the Center for Epidemiologic Studies Depression Scale (CES-D) and invited those with depression to be evaluated further and treated. Eighty-four RA patients reporting depressive symptoms agreed to participate in person, and 56 met the criteria for major depressive disorder.

Self-efficacy and pain behavior among subjects with fibromyalgia.

Given the lack of objective physical measures for assessing fibromyalgia syndrome (FS), the role of pain assessment is particularly important. The role of psychological factors is controversial among FS patients. This study was designed to better understand the relationship between pain behaviors and psychological variables.