131 research outputs found
Managing Health Care After Cancer Treatment: A Wellness Plan
Many patients and health care providers lack awareness of both the existence of, and treatments for, lingering distress and disability after treatment. A cancer survivorship wellness plan can help ensure that any referral needs for psychosocial and other restorative care after cancer treatment are identified
Ascertainment of Minimal Clinically Important Differences in the Diabetes Distress Scale-17: a Secondary analysis of a Randomized Clinical Trial
IMPORTANCE: The Diabetes Distress Scale-17 (DDS-17) is a common measure of diabetes distress. Despite its popularity, there are no agreed-on minimal clinically important difference (MCID) values for the DDS-17.
OBJECTIVE: to establish a distribution-based metric for MCID in the DDS-17 and its 4 subscale scores (interpersonal distress, physician distress, regimen distress, and emotional distress).
DESIGN, SETTING, AND PARTICIPANTS: This secondary analysis of a randomized clinical trial used baseline and postintervention data from a hybrid (implementation-effectiveness) trial evaluating Empowering Patients in Chronic Care (EPICC) vs an enhanced form of usual care (EUC). Participants included adults with uncontrolled type 2 diabetes (glycated hemoglobin A1c [HbA1c] level \u3e8.0%) who received primary care during the prior year in participating Department of Veterans Affairs clinics across Illinois, Indiana, and Texas. Data collection was completed in November 2018, and data analysis was completed in June 2023.
INTERVENTIONS: Participants in EPICC attended 6 group sessions led by health care professionals based on collaborative goal-setting theory. EUC included diabetes education.
MAIN OUTCOMES AND MEASURES: The main outcome was distribution-based MCID values for the total DDS-17 and 4 DDS-17 subscales, calculated using the standard error of measurement. Baseline to postintervention changes in DDS-17 and its 4 subscale scores were grouped into 3 categories: improved, no change, and worsened. Multilevel logistic and linear regression models examined associations between treatment group and MCID change categories and whether improvement in HbA1c varied in association with MCID category.
RESULTS: A total of 248 individuals with complete DDS-17 data were included (mean [SD] age, 67.4 [8.3] years; 235 [94.76%] men), with 123 participants in the EPICC group and 125 participants in the EUC group. The MCID value for DDS-17 was 0.25 and MCID values for the 4 distress subscales were 0.38 for emotional and interpersonal distress and 0.39 for physician and regimen distress. Compared with EUC, more EPICC participants were in the MCID improvement category on DDS-17 (63 participants [51.22%] vs 40 participants [32.00%]; P = .003) and fewer EPICC participants were in the worsened category (20 participants [16.26%] vs 39 participants [31.20%]; P = .008). There was no direct association of DDS-17 MCID improvement (β = -0.25; 95% CI, -0.59 to 0.10; P = .17) or worsening (β = 0.18; 95% CI, -0.22 to 0.59; P = .38) with HbA1c levels among all participants.
CONCLUSIONS AND RELEVANCE: In this secondary analysis of data from a randomized clinical trial, an MCID improvement or worsening of more than 0.25 on the DDS-17 was quantitatively significant and patients in the EPICC group were more likely to experience improvement than those in the EUC group.
TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01876485
Patient Priorities Care increases Long-Term Service and Support Use: Propensity Match Cohort Study
OBJECTIVES: Patient priorities care (PPC) is an evidence-based approach designed to help patients achieve what matters most to them by identifying their health priorities and working with clinicians to align the care they provide to the patient\u27s priorities. This study examined the impact of the PPC approach on long-term service and support (LTSS) use among veterans.
DESIGN: Quasi-experimental study examining differences in LTSS use between veterans exposed to PPC and propensity-matched controls not exposed to PPC adjusting for covariates.
SETTING AND PARTICIPANTS: Fifty-six social workers in 5 Veterans Health Administration (VHA) sites trained in PPC in 2018, 143 veterans who used the PPC approach, and 286 matched veterans who did not use the PPC approach.
METHODS: Veterans with health priorities identified through the PPC approach were the intervention group (n = 143). The usual care group included propensity-matched veterans evaluated by the same social workers in the same period who did not participate in PPC (n = 286). The visit with the social worker was the index date. We examined LTSS use, emergency department (ED), and urgent care visits, 12 months before and after this date for both groups. Electronic medical record notes were extracted with a validated natural language processing algorithm (84% sensitivity, 95% specificity, and 92% accuracy).
RESULTS: Most participants were white men, mean age was 76, and 30% were frail. LTSS use was 48% higher in the PPC group compared with the usual care group [odds ratio (OR), 1.48; 95% CI, 1.00-2.18; P = .05]. Among those who lived \u3e2 years after the index date, new LTSS use was higher (OR, 1.69; 95% CI, 1.04-2.76; P = .036). Among nonfrail individuals, LTSS use was also higher in the PPC group (OR, 1.70; 95% CI, 1.06-2.74; P = .028). PPC was not associated with higher ED or urgent care use.
CONCLUSIONS AND IMPLICATIONS: PPC results in higher LTSS use but not ED or urgent care in these veterans. LTSS use was higher for nonfrail veterans and those living longer. The PPC approach helps identify health priorities, including unmet needs for safe and independent living that LTSS can support
Guiding Post-Hospital Recovery By \u27What Matters:\u27 Implementation of Patient Priorities Identification in a Va Community Living Center
BACKGROUND: Patient priorities care (PPC) is an effective age-friendly health systems (AFHS) approach to aligning care with goals derived from \u27what matters\u27. The purpose of this quality improvement program was to evaluate the fidelity and feasibility of the health priorities identification (HPI) process in VA Community Living Centers (CLC).
METHODS: PPC experts worked with local CLC staff to guide the integration of HPI into the CLC and utilized a Plan-Do-Study-Act (PDSA) model for this quality improvement project. PPC experts reviewed health priorities identification (HPI) encounters and interdisciplinary team (IDT) meetings for fidelity to the HPI process of PPC. Qualitative interviews with local CLC staff determined the appropriateness of the health priorities identification process in the CLC.
RESULTS: Over 8 months, nine facilitators completed twenty HPI encounters. Development of a Patient Health Priorities note template, staff education and PPC facilitator training improved fidelity and documentation of HPI encounters in the electronic health record. Facilitator interviews suggested that PPC is appropriate in this setting, not burdensome to staff and fostered a person-centered approach to AFHS.
CONCLUSIONS: The HPI process is an acceptable and feasible approach to ask the \u27what matters\u27 component of AFHS in a CLC setting
Patient Priorities-Aligned Care For Older adults With Multiple Conditions: a Nonrandomized Controlled Trial
IMPORTANCE: Older adults with multiple conditions receive health care that may be burdensome, of uncertain benefit, and not focused on what matters to them. Identifying and aligning care with patients\u27 health priorities may improve outcomes.
OBJECTIVE: to assess the association of receiving patient priorities care (PPC) vs usual care (UC) with relevant clinical outcomes.
DESIGN, SETTING, AND PARTICIPANTS: In this nonrandomized controlled trial with propensity adjustment, enrollment occurred between August 21, 2020, and May 14, 2021, with follow-up continuing through February 26, 2022. Patients who were aged 65 years or older and with 3 or more chronic conditions were enrolled at 1 PPC and 1 UC site within the Cleveland Clinic primary care multisite practice. Data analysis was performed from March 2022 to August 2023.
INTERVENTION: Health professionals at the PPC site guided patients through identification of values, health outcome goals, health care preferences, and top priority (ie, health problem they most wanted to focus on because it impeded their health outcome goal). Primary clinicians followed PPC decisional strategies (eg, use patients\u27 health priorities as focus of communication and decision-making) to decide with patients what care to stop, start, or continue.
MAIN OUTCOMES AND MEASURES: Main outcomes included perceived treatment burden, Patient-Reported Outcomes Measurement Information System (PROMIS) social roles and activities, CollaboRATE survey scores, the number of nonhealthy days (based on healthy days at home), and shared prescribing decision quality measures. Follow-up was at 9 months for patient-reported outcomes and 365 days for nonhealthy days.
RESULTS: A total of 264 individuals participated, 129 in the PPC group (mean [SD] age, 75.3 [6.1] years; 66 women [48.9%]) and 135 in the UC group (mean [SD] age, 75.6 [6.5] years; 55 women [42.6%]). Characteristics between sites were balanced after propensity score weighting. At follow-up, there was no statistically significant difference in perceived treatment burden score between groups in multivariate models (difference, -5.2 points; 95% CI, -10.9 to -0.50 points; P = .07). PPC participants were almost 2.5 times more likely than UC participants to endorse shared prescribing decision-making (adjusted odds ratio, 2.40; 95% CI, 0.90 to 6.40; P = .07), and participants in the PPC group experienced 4.6 fewer nonhealthy days (95% CI, -12.9 to -3.6 days; P = .27) compared with the UC participants. These differences were not statistically significant. CollaboRATE and PROMIS Social Roles and Activities scores were similar in the 2 groups at follow-up.
CONCLUSIONS AND RELEVANCE: This nonrandomized trial of priorities-aligned care showed no benefit for social roles or CollaboRATE. While the findings for perceived treatment burden and shared prescribing decision-making were not statistically significant, point estimates for the findings suggested that PPC may hold promise for improving these outcomes. Randomized trials with larger samples are needed to determine the effectiveness of priorities-aligned care.
TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04510948
Two Mental Models of integrated Care For advanced Liver Disease: Qualitative Study of Multidisciplinary Health Professionals
OBJECTIVES: The purpose of this paper is to present two divergent mental models of integrated advanced liver disease (AdvLD) care among 26 providers who treat patients with AdvLD.
SETTING: 3 geographically dispersed United States Veterans Health Administration health systems.
PARTICIPANTS: 26 professionals (20 women and 6 men) participated, including 9 (34.6%) gastroenterology, hepatology, and transplant physicians, 2 (7.7%) physician assistants, 7 (27%) nurses and nurse practitioners, 3 (11.5%) social workers and psychologists, 4 (15.4%) palliative care providers and 1 (3.8%) pharmacist.
MAIN OUTCOME MEASURES: We conducted qualitative in-depth interviews of providers caring for patients with AdvLD. We used framework analysis to identify two divergent mental models of integrated AdvLD care. These models vary in timing of initiating various constituents of care, philosophy of integration, and supports and resources needed to achieve each model.
RESULTS: Clinicians described integrated care as an approach that incorporates elements of curative care, symptom and supportive care, advance care planning and end-of-life services from a multidisciplinary team. Analysis revealed two mental models that varied in how and when these constituents are delivered. One mental model involves sequential transitions between constituents of care, and the second mental model involves synchronous application of the various constituents. Participants described elements of teamwork and coordination supports necessary to achieve integrated AdvLD care. Many discussed the importance of having a multidisciplinary team integrating supportive care, symptom management and palliative care with liver disease care.
CONCLUSIONS: Health professionals agree on the constituents of integrated AdvLD care but describe two competing mental models of how these constituents are integrated. Health systems can promote integrated care by assembling multidisciplinary teams, and providing teamwork and coordination supports, and training that facilitates patient-centred AdvLD care
Emergency clinicians\u27 perceptions of communication tools to establish the mental baseline of older adults: A qualitative study
Background Evaluating older adults with altered mental status in emergency settings can be challenging due to the inability to obtain a history from patients directly and limited collateral information about the change from a patient\u27s mental status baseline. Documents and videos establishing a patient\u27s mental baseline could represent useful communication tools to aid emergency clinicians. Methods Qualitative interviews conducted with 22 emergency clinicians (12 physicians and 10 advanced practice providers) identified methods they use to determine baseline mental status of older adults in the ED and the perceived utility of document- and video-based information about an older adult\u27s baseline mental status. Interview transcripts were coded for dominant themes using deductive and inductive approaches. Results Participants determine an older adult\u27s baseline mental status by obtaining information about the patient\u27s baseline cognition (memory and communication) and function (activities of daily living and mobility). The techniques they use include 1) reviewing the electronic medical record, 2) speaking with family members or caregivers by phone or in person, and 3) obtaining verbal or phone reports from emergency medical services personnel or health care providers from short- or long-term care facilities. The majority of participants thought that a document or video with information about a patient\u27s baseline mental status would be useful (n=15, 68%), qualifying that content ought to be brief, clearly dated, and periodically updated. Conclusions Documents or videos could assist emergency clinicians in establishing baseline cognitive function when evaluating geriatric patients and may have implications for improving the detection of delirium
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Cancer survivor rehabilitation and recovery: Protocol for the Veterans Cancer Rehabilitation Study (Vet-CaRes)
Background: Cancer survivors are a rapidly growing and aging population in the U.S., but there are many challenges associated with the survivorship experience such as functional disabilities and psychosocial distress. When viewed next to the general population, Veterans are especially at risk for these challenges as they are older and have a high incidence of co-morbid conditions. While the Institute of Medicine (IOM) has called for further cancer survivorship research to address these challenges, we still know little about this experience from the perspective of aging Veterans. Methods/design We conducted a longitudinal, mixed-methods study over the course of three and a half years at the Boston and Houston VA Medical Centers. We recruited 170 Veterans diagnosed with head and neck, colorectal and esophageal/gastric cancers that were identified from the VA tumor registry. Veterans completed three in-depth interviews, conducted at 6, 12 and 18 months after pathology confirmation, measuring the physical, social and psychological factors related to cancer survivorship. The longitudinal design allowed us to assess any changes in cancer related disability and distress over time. Discussion Weekly teleconference study team meetings were a key aspect to the research process. Issues related to recruitment, data management and analysis, and the dissemination of research results was discussed. Interviewers presented detailed case reports of completed interviews that allowed us to refine our interview protocols. We also discussed issues relevant to the Veteran population of which we were previously unaware and some of the challenges of the research process itself. This novel study produced a robust data set that documents the functional and psychosocial cancer survivorship experiences of aging Veterans. The longitudinal design will help us more fully understand the recovery patterns for this specific population, and identify the unique needs and gaps in health services
What Is the Additive Value of Nutritional Deficiency to Va-Fi in the Risk Assessment For Heart Failure Patients?
OBJECTIVES: to assess the impact of adding the Prognostic Nutritional Index (PNI) to the U.S. Veterans Health Administration frailty index (VA-FI) for the prediction of time-to-death and other clinical outcomes in Veterans hospitalized with Heart Failure.
METHODS: A retrospective cohort study of veterans hospitalized for heart failure (HF) from October 2015 to October 2018. Veterans ≥50 years with albumin and lymphocyte counts, needed to calculate the PNI, in the year prior to hospitalization were included. We defined malnutrition as PNI ≤43.6, based on the Youden index. VA-FI was calculated from the year prior to the hospitalization and identified three groups: robust (≤0.1), prefrail (0.1-0.2), and frail (\u3e0.2). Malnutrition was added to the VA-FI (VA-FI-Nutrition) as a 32
RESULTS: We identified 37,601 Veterans hospitalized for HF (mean age: 73.4 ± 10.3 years, BMI: 31.3 ± 7.4 kg/m
CONCLUSION: Adding PNI to VA-FI provides a more accurate and comprehensive assessment among Veterans hospitalized for HF. Clinicians should consider adding a specific nutrition algorithm to automated frailty tools to improve the validity of risk prediction in patients hospitalized with HF
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