Mary Dierich

Medication regimens in older home care patients.

Medication regimens in older patients have been strongly associated with adverse events leading to hospitalization in ambulatory care settings. Despite a 29% hospitalization rate, to date, no research regarding medication regimens and readmission to the hospital has been completed in the home care setting. As part of a larger study evaluating predictors of readmission to the hospital from home care, descriptive analyses, chi-square tests, and t tests for independent samples were used in this secondary analysis to evaluate the Outcome and Assessment Information Set and medication records from 911 older patients admitted from the hospital to 15 home care agencies. Patients readmitted back to the hospital were older, sicker, and more cognitively impaired, and had complex medication regimens that included significant polypharmacy and inappropriate medication use. Nurses working with older adults need to be especially vigilant in monitoring medication regimens of patients to reduce opportunities for adverse drug events and subsequent hospitalization.

Interpretable Predictive Models for Knowledge Discovery from Home-Care Electronic Health Records

The purpose of this methodological study was to compare methods of developing predictive rules that are parsimonious and clinically interpretable from electronic health record (EHR) home visit data, contrasting logistic regression with three data mining classification models. We address three problems commonly encountered in EHRs: the value of including clinically important variables with little variance, handling imbalanced datasets, and ease of interpretation of the resulting predictive models. Logistic regression and three classification models using Ripper, decision trees, and Support Vector Machines were applied to a case study for one outcome of improvement in oral medication management. Predictive rules for logistic regression, Ripper, and decision trees are reported and results compared using F-measures for data mining models and area under the receiver-operating characteristic curve for all models. The rules generated by the three classification models provide potentially novel insights into mining EHRs beyond those provided by standard logistic regression, and suggest steps for further study.

Urinary tract dysfunction in neurological disorders: The nurses' role in assessment and management

Urinary dysfunction is a common feature and may often be a presenting symptom of neurological conditions including spinal cord injury, stroke, multiple sclerosis, spina bifida, cerebral palsy, and Parkinson disease. Such dysfunction leads to morbidity and decreased quality of life for patients with these conditions. The diagnosis and treatment of neurogenic urinary dysfunction is complex, dynamic, and multifaceted. An individualized management strategy, incorporating medical, educational, and psychosocial components, is required to achieve optimum outcomes for patients and their caregivers. Accurate diagnosis, referral for urological assessment, and selection of the most appropriate treatment are vital in ensuring that the individual patient has the best possible outcome and improvement in quality of life. In view of these facts, nurses play a key role in ensuring that patients with neurogenic urinary dysfunction receive the assessment and treatment they need. In addition, the nursing role in the monitoring of treatment and educational support for patients and their caregivers is a strong driver of successful management.

Essentials of Ambulatory Care: An Interprofessional Workshop to Promote Core Skills and Values in Team-based Outpatient Care

Introduction Team-based, interprofessional approaches to outpatient care are critical to high-quality patient care. However, few specific educational interventions promoting these skills in graduate level health care trainees have been described to date. Methods University of Minnesota faculty from the Schools of Medicine, Pharmacy, and Nursing created an interprofessional workshop experience exploring core concepts in outpatient care for graduate level trainees in pediatrics, family medicine, medicine-pediatrics, internal medicine, graduate-level nursing, and pharmacy. We focused on four key content areas: teamwork, systems thinking, the patient-centered health care home, and patient-centered communication. The workshop included brief didactics, role-plays, team-based experiences, and interactive skill practice. Participants completed an end-of-day survey reflecting on knowledge and attitude. Results From 2014–2017, nine workshops reached 305 trainees. Survey results from the 2015–2016 academic year are representative of our overall results and revealed that learners found the content high yield, and that they valued the opportunity to learn with their interprofessional colleagues. Improvements in perceived knowledge were noted in all domains. Trainees also reported increased skills, with 81% reporting both increased confidence in working within the interprofessional team, and change in attitude, and 90% reporting increased interest in working with their interprofessional colleagues after the workshop. Discussion Creating an opportunity for postgraduate level trainees from a variety of disciplines and professions to convene and focus on interprofessional team-based skills can fill a gap in interprofessional learning as they enter practice. Trainees were able to draw on their everyday experiences and find common ground with their interprofessional colleagues.