Browsing by Subject "collaborative care"
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Item Automated Self-management (ASM) vs. ASM-Enhanced Collaborative Care for Chronic Pain and Mood Symptoms: the CAMMPS Randomized Clinical Trial(Springer, 2019-06-21) Kroenke, Kurt; Baye, Fitsum; Lourens, Spencer G.; Evans, Erica; Weitlauf, Sharon; McCalley, Stephanie; Porter, Brian; Matthias, Marianne S.; Bair, Matthew J.; Medicine, School of MedicineBackground Chronic musculoskeletal pain is often accompanied by depression or anxiety wherein co-occurring pain and mood symptoms can be more difficult to treat than either alone. However, few clinical trials have examined interventions that simultaneously target both pain and mood conditions. Objective To determine the comparative effectiveness of automated self-management (ASM) vs. ASM-enhanced collaborative care. Design Randomized clinical trial conducted in six primary care clinics in a VA medical center. Participants Two hundred ninety-four patients with chronic musculoskeletal pain of at least moderate intensity and clinically significant depressive and/or anxiety symptoms. Intervention ASM consisted of automated monitoring and 9 web-based self-management modules. Comprehensive symptom management (CSM) combined ASM with collaborative care management by a nurse-physician team. Both interventions were delivered for 12 months. Main Measures Primary outcome was a composite pain-anxiety-depression (PAD) z-score consisting of the mean of the BPI, PHQ-9, and GAD-7 z-scores: 0.2, 0.5, and 0.8 represent potentially small, moderate, and large clinical differences. Secondary outcomes included global improvement, health-related quality of life, treatment satisfaction, and health services use. Key Results Both CSM and ASM groups had moderate PAD score improvement at 12 months (z = − 0.65 and − 0.52, respectively). Compared to the ASM group, the CSM group had a − 0.23 (95% CI, − 0.38 to − 0.08; overall P = .003) greater decline in composite PAD z-score over 12 months. CSM patients were also more likely to report global improvement and less likely to report worsening at 6 (P = .004) and 12 months (P = .013). Conclusions Two intervention models relying heavily on telecare delivery but differing in resource intensity both produced moderate improvements in pain and mood symptoms. However, the model combining collaborative care led by a nurse-physician team with web-based self-management was superior to self-management alone.Item The Critical Care Recovery Center: An Innovative Collaborative Care Model for ICU Survivors(Wolters, 2015-03) Khan, Babar A.; Lasiter, Sue; Boustani, Malaz A.; School of NursingFive million Americans require admission to ICUs annually owing to life-threatening illnesses. Recent medical advances have resulted in higher survival rates for critically ill patients, who often have significant cognitive, physical, and psychological sequelae, known as postintensive care syndrome (PICS). This growing population threatens to overwhelm the current U.S. health care system, which lacks established clinical models for managing their care. Novel innovative models are urgently needed. To this end, the pulmonary/critical care and geriatrics divisions at the Indiana University School of Medicine joined forces to develop and implement a collaborative care model, the Critical Care Recovery Center (CCRC). Its mission is to maximize the cognitive, physical, and psychological recovery of ICU survivors. Developed around the principles of implementation and complexity science, the CCRC opened in 2011 as a clinical center with a secondary research focus. Care is provided through a pre-CCRC patient and caregiver needs assessment, an initial diagnostic workup visit, and a follow-up visit that includes a family conference. With its sole focus on the prevention and treatment of PICS, the CCRC represents an innovative prototype aimed at modifying post–critical illness morbidities and improving the ICU survivor's quality of life.Item Effect of Depression Treatment on Health Behaviors and Cardiovascular Risk Factors Among Primary Care Patients with Depression: Data from the eIMPACT Trial(2023-12) Schuiling, Matthew D.; Stewart, Jesse; Hirsh, Adam; Wu, WeiBackground. Although depression is a risk factor for cardiovascular disease (CVD), few clinical trials in people without CVD have examined the effect of depression treatment on CVD-related outcomes. It’s unknown if successful depression treatment improves indicators of CVD risk, such as CVD-relevant health behaviors, traditional CVD risk factors, and CVD events. Methods. We examined data from eIMPACT trial, a phase II randomized controlled trial conducted from 2015-2020. Depressive symptoms, CVD-relevant health behaviors (self-reported CVD prevention medication adherence, sedentary behavior, and sleep quality) and traditional CVD risk factors (blood pressure and lipid fractions) were assessed. Incident CVD events over four years were identified using a statewide health information exchange. Results. The intervention group exhibited greater improvement in depressive symptoms (p < 0.01) and sleep quality (p < 0.01) than the usual care group, but there was no intervention effect on systolic blood pressure (p = 0.36), low-density lipoprotein cholesterol (p = 0.38), high-density lipoprotein cholesterol (p = 0.79), triglycerides (p = 0.76), CVD prevention medication adherence (p = 0.64), or sedentary behavior (p = 0.57). There was an intervention effect on diastolic blood pressure that favored the usual care group (p = 0.02). CVD-relevant health behaviors did not mediate any intervention effects on traditional CVD risk factors. Twenty-two participants (10%) experienced an incident CVD event. The likelihood of an CVD event did not differ between the intervention group (12.1%) and the usual care group (8.3%; HR = 1.45, 95% CI: 0.62-3.40, p = 0.39). Conclusions. Successful depression treatment alone improves self-reported sleep quality but is not sufficient to lower CVD risk of people with depression. Alternative approaches may be needed reduce CVD risk in depression. Trial Registration: ClinicalTrials.gov Identifier: NCT02458690Item Integrating mental health professionals in residencies to reduce health disparities(Springer, 2017-05) Delbridge, Emilee; Zubatsky, Max; Fowler, Jocelyn; Family Medicine, School of MedicineHealth disparities in primary care remain a continual challenge for both practitioners and patients alike. Integrating mental health services into routine patient care has been one approach to address such issues, including access to care, stigma of health-care providers, and facilitating underserved patients’ needs. This article addresses examples of training programs that have included mental health learners and licensed providers into family medicine residency training clinics. Descriptions of these models at two Midwestern Family Medicine residency clinics in the United States are highlighted. Examples of cross-training both medical residents and mental health students are described, detailing specific areas where this integration improves mental health and medical outcomes in patients. Challenges to effective integration are discussed, including larger system buy-in, medical providers’ knowledge of mental health treatment, and the skills for clinical providers to possess in order to present mental health options to patients. Patients who traditionally experience multiple barriers to mental health treatment now have increased access to comprehensive care. As a result of more primary care clinics ascribing to an integrated care model of practice, providers may benefit from not only increased coordination of patient services but also utilizing behavioral health professionals to address health barriers in patients’ lives.Item Modernized Collaborative Care for Depression: Impact on Psychological Risk and Protective Factors for Diabetes and Intervention Outcomes Among Diverse Sociodemographic Groups(2024-08) Williams, Michelle; Stewart, Jesse; Hirsh, Adam; Johnson, India; Gupta, SamirObjective: We examined the effect of a modernized collaborative care intervention for depression on multiple psychological risk and protective factors for diabetes and characterized intervention process outcomes using data from the eIMPACT-DM trial. Methods: Forty-six primary care patients with depression and elevated diabetes risk from a safety net healthcare system (Mage = 50 years, 78% women, 72% Black, Meducation = 13 years, 33% with income <$10,000/year) were randomized to 6 months of the eIMPACT-DM intervention (our modernized collaborative care intervention for depression involving internet cognitive-behavioral therapy [CBT], telephonic CBT, and/or select antidepressants; n=24) or active control (depression education, depressive symptom monitoring, and usual primary care for depression; n=22). Depressive symptoms (Patient Health Questionnaire-9 [PHQ-9], anxiety symptoms (Generalized Anxiety Disorder-7 [GAD-7]), trait positive affect (Positive and Negative Affect Schedule- Positive Affect Subscale [PANAS-PA]), life satisfaction (Satisfaction With Life Scale [SWLS]), and intervention process outcomes were measured across the treatment period. Results: Effect size metrics (standardized regression coefficients; bY) indicated that, compared to active control, the intervention group demonstrated clinically meaningful medium-to-large improvements in depressive symptoms (PHQ-9 bY = -0.69), anxiety symptoms (GAD-7 bY = - 0.76), and trait positive affect (PANAS-PA bY = 0.61) as well as small-to-medium improvements in life satisfaction (bY = 0.43). Although only 27% of participants assigned to iCBT had good engagement and 60% had good iCBT comprehension, the intervention group reported high skills implementation and treatment satisfaction. Conclusion: These findings demonstrate the potential of a modernized collaborative care intervention to improve multiple psychological risk and protective factors for diabetes in a diverse primary care population. Such an intervention could ultimately serve to bolster future diabetes prevention in diverse groups, helping to reduce diabetes-related health disparities.Item Peer Specialists in Collaborative Care for Older Adults With Depression(APA, 2015-09) Rollins, Angela L.; Frantz, Dana; Department of Psychology, School of ScienceItem When and Howto Treat Subthreshold Depression(AMA, 2017-02) Kroenke, Kurt; Medicine, School of Medicine