ABSTRACTBackgroundAs a component of goal‐oriented care, goal‐setting is an important strategy to improve self‐management and reduce the economic and personal burden of chronic illness. Primary care nurses, as integral members of the healthcare team, play a pivotal role in providing self‐management support to patients with multiple chronic illnesses. Yet, little is known about their perspectives on partnering with patients to set meaningful goals within self‐management support programmes.AimTo explore perspectives of primary care nurses about their practice of goal‐setting with patients to improve self‐management.MethodsFor this qualitative exploratory study, we conducted semi‐structured interviews with 28 primary care nurses who provided self‐management support to patients with multiple chronic illnesses. Data were analysed using inductive thematic analysis. This research was approved by the Mayo Clinic Institutional Review Board.ResultsKey themes from interviews focused on: (1) goal‐setting practices; (2) challenges encountered in goal‐setting; and (3) the perceived value‐add of using a patient‐centred goal‐setting approach. Nurses described practices that empower patients to take charge of goal‐setting, emphasising that the opportunity to create personal goals enhances motivation and enables the development of realistic action plans. Key challenges faced were patients' lack of familiarity with personal goal‐setting, competing life stressors and patients' reluctance to change.ConclusionOur findings contribute valuable insights about how primary care nurses approach goal‐setting within a self‐management support program. Notably, unlike previous studies where clinicians reported that time‐limited appointments and institutional expectations hindered patient‐centred goal‐setting, our participants practicing in an institutionally supported goal‐oriented patient‐centred model of care did not report time constraints or pressures to prioritise clinical goals over patient goals. Instead, they described patient‐centred goal‐setting practices that are associated with positive patient and clinical outcomes. To potentially corroborate and expand upon our findings and inform practice and training, future research should include qualitative and survey studies to explore primary care RNs perspectives about goal‐setting and observational research to evaluate nurse–patient goal‐setting interactions.
Overcoming challenges in real‐world evidence generation: An example from an Adult Medical Care Coordination program
AbstractThe Adult Medical Care Coordination program (“the program”) was implemented at Mayo Clinic to promote patient self‐management and improve 30‐day unplanned readmission for patients with high risk for readmission after hospital discharge. This study aimed to evaluate the impact of the program compared to usual care using a pragmatic, stepped wedge cluster randomized trial (“stepped wedge trial”). However, several challenges arose including large differences between the study arms. Our goal is to describe the challenges and present lessons learned on how to overcome such challenges and generate evidence to support practice decisions. We describe the challenges encountered during the trial, the approach to addressing these challenges, and lessons learned for other learning health system researchers facing similar challenges. The trial experienced several challenges in implementation including several clinics dropping from the study and care disruptions due to COVID‐19. Additionally, there were large differences in the patient population between the program and usual care arms. For example, the mean age was 76.8 for the program and 68.1 for usual care. Due to these differences, we adapted the methods using the propensity score matching approach that is traditionally applied to observational designs and adjusted for differences in observable characteristics. When conducting pragmatic research, researchers will encounter factors beyond their control that may introduce bias. The lessons learned include the need to weigh the tradeoffs of pragmatic design elements and the potential value of adaptive designs for pragmatic trials. Applying these lessons would promote the successful generation of evidence that informs practice decisions.
A quality improvement project aimed at adapting primary care to ensure the delivery of evidence-based psychotherapy for adult anxiety
Primary care patients frequently present with anxiety with prevalence ratios up to 30%. Brief cognitive–behavioural therapy (CBT) has been shown in meta-analytic studies to have a strong effect size in the treatment of anxiety. However, in surveys of anxious primary care patients, nearly 80% indicated that they had not received CBT. In 2010, a model of CBT (Coordinated Anxiety Learning and Management (CALM)) adapted to primary care for adult anxiety was published based on results of a randomised controlled trial. This project aimed to integrate an adaptation of CALM into one primary care practice, using results from the published research as a benchmark with the secondary intent to spread a successful model to other practices. A quality improvement approach was used to translate the CALM model of CBT for anxiety into one primary care clinic. Plan-Do-Study-Act steps are highlighted as important steps towards our goal of comparing our outcomes with benchmarks from original research. Patients with anxiety as measured by a score of 10 or higher on the Generalized Anxiety Disorder 7 item scale (GAD-7) were offered CBT as delivered by licensed social workers with support by a PhD psychologist. Outcomes were tracked and entered into an electronic registry, which became a critical tool upon which to adapt and improve our delivery of psychotherapy to our patient population. Challenges and adaptations to the model are discussed. Our 6-month response rates on the GAD-7 were 51%, which was comparable with that of the original research (57%). Quality improvement methods were critical in discovering which adaptations were needed before spread. Among these, embedding a process of measurement and data entry and ongoing feedback to patients and therapists using this data are critical step towards sustaining and improving the delivery of CBT in primary care.