Mariana Nikolova-Simons

Nurses strategies to address self-care aspects related to medication adherence and symptom recognition in heart failure patients: An in- depth look

OBJECTIVE Despite an increasing body of knowledge on self-care in heart failure patients, the need for effective interventions remains. We sought to deepen the understanding of interventions that heart failure nurses use in clinical practice to improve patient adherence to medication and symptom monitoring. METHODS A qualitative study with a directed content analysis was performed, using data from a selected sample of Dutch-speaking heart failure nurses who completed booklets with two vignettes involving medication adherence and symptom recognition. RESULTS Nurses regularly assess and reassess patients before they decide on an intervention. They evaluate basic/factual information and barriers in a patients behavior, and try to find room for improvement in a patients behavior. Interventions that heart failure nurses use to improve adherence to medication and symptom monitoring were grouped into the themes of increasing knowledge, increasing motivation, and providing patients with practical tools. Nurses also described using technology-based tools, increased social support, alternative communication, partnership approaches, and coordination of care to improve adherence to medications and symptom monitoring. CONCLUSION Despite a strong focus on educational strategies, nurses also reported other strategies to increase patient adherence. Nurses use several strategies to improve patient adherence that are not incorporated into guidelines. These interventions need to be evaluated for further applications in improving heart failure management.

Healthcare utilization in older patients using personal emergency response systems: an analysis of electronic health records and medical alert data

BackgroundPersonal Emergency Response Systems (PERS) are traditionally used as fall alert systems for older adults, a population that contributes an overwhelming proportion of healthcare costs in the United States. Previous studies focused mainly on qualitative evaluations of PERS without a longitudinal quantitative evaluation of healthcare utilization in users. To address this gap and better understand the needs of older patients on PERS, we analyzed longitudinal healthcare utilization trends in patients using PERS through the home care management service of a large healthcare organization.MethodsRetrospective, longitudinal analyses of healthcare and PERS utilization records of older patients over a 5-years period from 2011–2015. The primary outcome was to characterize the healthcare utilization of PERS patients. This outcome was assessed by 30-, 90-, and 180-day readmission rates, frequency of principal admitting diagnoses, and prevalence of conditions leading to potentially avoidable admissions based on Centers for Medicare and Medicaid Services classification criteria.ResultsThe overall 30-day readmission rate was 14.2%, 90-days readmission rate was 34.4%, and 180-days readmission rate was 42.2%. While 30-day readmission rates did not increase significantly (p = 0.16) over the study period, 90-days (p = 0.03) and 180-days (p = 0.04) readmission rates did increase significantly. The top 5 most frequent principal diagnoses for inpatient admissions included congestive heart failure (5.7%), chronic obstructive pulmonary disease (4.6%), dysrhythmias (4.3%), septicemia (4.1%), and pneumonia (4.1%). Additionally, 21% of all admissions were due to conditions leading to potentially avoidable admissions in either institutional or non-institutional settings (16% in institutional settings only).ConclusionsChronic medical conditions account for the majority of healthcare utilization in older patients using PERS. Results suggest that PERS data combined with electronic medical records data can provide useful insights that can be used to improve health outcomes in older patients.

Evaluating the Impact of a Web-Based Risk Assessment System (CareSage) and Tailored Interventions on Health Care Utilization: Protocol for a Randomized Controlled Trial

Background Soaring health care costs and a rapidly aging population, with multiple comorbidities, necessitates the development of innovative strategies to deliver high-quality, value-based care. Objective The goal of this study is to evaluate the impact of a risk assessment system (CareSage) and targeted interventions on health care utilization. Methods This is a two-arm randomized controlled trial recruiting 370 participants from a pool of high-risk patients receiving care at a home health agency. CareSage is a risk assessment system that utilizes both real-time data collected via a Personal Emergency Response Service and historical patient data collected from the electronic medical records. All patients will first be observed for 3 months (observation period) to allow the CareSage algorithm to calibrate based on patient data. During the next 6 months (intervention period), CareSage will use a predictive algorithm to classify patients in the intervention group as “high” or “low” risk for emergency transport every 30 days. All patients flagged as “high risk” by CareSage will receive nurse triage calls to assess their needs and personalized interventions including patient education, home visits, and tele-monitoring. The primary outcome is the number of 180-day emergency department visits. Secondary outcomes include the number of 90-day emergency department visits, total medical expenses, 180-day mortality rates, time to first readmission, total number of readmissions and avoidable readmissions, 30-, 90-, and 180-day readmission rates, as well as cost of intervention per patient. The two study groups will be compared using the Student t test (two-tailed) for normally distributed and Mann Whitney U test for skewed continuous variables, respectively. The chi-square test will be used for categorical variables. Time to event (readmission) and 180-day mortality between the two study groups will be compared by using the Kaplan-Meier survival plots and the log-rank test. Cox proportional hazard regression will be used to compute hazard ratio and compare outcomes between the two groups. Results We are actively enrolling participants and the study is expected to be completed by end of 2018; results are expected to be published in early 2019. Conclusions Innovative solutions for identifying high-risk patients and personalizing interventions based on individual risk and needs may help facilitate the delivery of value-based care, improve long-term patient health outcomes and decrease health care costs. Trial Registration ClinicalTrials.gov NCT03126565; https://clinicaltrials.gov/ct2/show/NCT03126565 (Archived by WebCite at http://www.webcitation.org/6ymDuAwQA).