An automated vital sign monitoring system for congestive heart failure patients

Congestive heart failure (CHF) is a cardiovascular disorder that affects approximately 4.6 million Americans and is a leading cause of death in the United States. Current research shows that strategies to promote early recognition and treatment of symptoms and enhance self-care management behaviors reduce unnecessary hospitalizations. However, mechanisms to monitor patients' health status and behaviors are limited by constraints imposed by the patient's geography, infirmity, or resources. Remote monitoring supports a more dynamic connection between healthcare providers and patients, improves health promotion and patient care through monitoring of health data, communicates health reminders, and makes provisions for patient feedback. This paper will describe two versions of Weight and Activity with Blood Pressure Monitoring System (WANDA [22]) that leverages sensor technology and wireless communication to monitor health status of patients with CHF. The WANDA system is built on a three-tier architecture consisting of sensors, a web server, and back-end database tiers. The system was developed in conjunction with the UCLA School of Nursing and the UCLA Wireless Health Institute to enable early detection of key clinical symptoms indicative of CHF-related decompensation in a real-time automated fashion and allows health professionals to offer surveillance, advice, and continuity of care and triggers early implementation of strategies to enhance adherence behaviors. The small study has enabled patients to reduce or maintain the number of readings which are out of the acceptable range. For diastolic, systolic, and heart rate values, the t-test results show that the WANDA study is effective for patients with CHF. © 2010 ACM

Ontology-driven monitoring of patient's vital signs enabling personalized medical detection and alert

C

Complex Care Management Program Overview - Technology

This report provides an overview of technology based complex care management programs, including:Cook County Health and Hospitals System - Computer Assisted Quality of Life and Symptom Assessment of Complex PatientsUniversity of Missouri - TigerPlaceWenatchee Valley Medical Center - Health Buddy -- Patient Telemonitoring Progra

Ontology-driven monitoring of patient's vital signs enabling personalized medical detection and alert

A major challenge related to caring for patients with chronic conditions is the early detection of exacerbations of the disease. Medical personnel should be contacted immediately in order to intervene in time before an acute state is reached, ensuring patient safety. This paper proposes an approach to an ambient intelligence (AmI) framework supporting real-time remote monitoring of patients diagnosed with congestive heart failure (CHF). Its novelty is the integration of: (i) personalized monitoring of the patients health status and risk stage; (ii) intelligent alerting of the dedicated physician through the construction of medical workflows on-the-fly; and (iii) dynamic adaptation of the vital signs' monitoring environment on any available device or smart phone located in close proximity to the physician depending on new medical measurements, additional disease specifications or the failure of the infrastructure. The intelligence lies in the adoption of semantics providing for a personalized and automated emergency alerting that smoothly interacts with the physician, regardless of his location, ensuring timely intervention during an emergency. It is evaluated on a medical emergency scenario, where in the case of exceeded patient thresholds, medical personnel are localized and contacted, presenting ad hoc information on the patient's condition on the most suited device within the physician's reach

Discharge after acute kidney injury : recognising and managing risk

Peer reviewedPublisher PD

Monitoring Cardiovascular Disease-Patients with Mobile Computing Technologies

Physicians and healthcare networks have been slow to adopt electronic medical records and to integrate medical data with the ubiquitous mobile device. Mobile and wearable systems for continuous health monitoring constitute a key technology in helping the transition of health care to a more proactive and affordable healthcare. Cardiovascular Disease (CVD) includes dysfunctional conditions of the heart, arteries, and veins that supply oxygen to vital life-sustaining areas/organs of the body. CVD singly accounts for about 40% of all deaths worldwide. Over 80 per cent of CVD deaths take place in low- and middle-income countries. An estimated 17.5 million people died from cardiovascular disease in 2005, and expected to top 20 million per year by 2015. By 2030, more than 23 million people will die annually from CVDs. CVDs‘ patients face risks of recurrent acute cardiovascular events, hospital re-admission, and unfavourable quality of life. Heart Failure, (HF), leads to death if not properly managed and supervised. Current treatments for Congestive Heart Failure (CHF) provide a limited palliative outcome. New technologies are now pertinent to generate high-dimensional data that provide unprecedented opportunities for unbiased identification of biomarkers that can be used to optimize pre-operative planning, with the goal of avoiding costly post-operative complications and prolonged hospitalization. Due to the crucial role of remote monitoring for CVD patients, significant efforts from research communities and industry to propose and design a variety of CVD monitoring devices have become imperative. This paper builds a proof-of-concept and presents a cardiovascular monitoring system, Cardiovascular Disease Management System (CVDMS), for real-time information on patient‘s heart health status with respect to his/her heart beat in hemodynamics computation towards reducing re-admission incidence problem. Administered 485 questionnaires and interviewed 12 cardiologists, 45 physicians, and 23 pharmacists to gather details on vital CVD parameters. 469 of 485 questionnaires (96.70%) were validly completed and returned, while 16 (3.30%) were not. Searched internet databases and cognate texts for literature. A mobile CVDMS for HF was developed using UML, MySQL Server 5.0, Java servlets, Apache Tomcat 6.0 server, microcontroller, and Ozeki sms server. Patient completes a questionnaire on a J2ME platform-based computing device that measures the heartbeat rate. Biological signals acquired by CVDMS are processed by microcontroller. Pulses are counted within a space of one minute to know heartbeat rate per minute. The CVDMS application gets the heartbeat reading, and if the heart rate is abnormal, a trigger is set enabling the Ozeki SMS Gateway to send an alert to patient‘s next-of-kin and cardiologist. CVDMS guarantees individual patient‘s direct involvement to closely monitor changes in his/her vital signs and provide feedback to maintain an optimal health status. Medical personnel get alerted when life-threatening changes occur in establishing proper communication between patient and cardiologist via sms. Hemodynamics computation could be performed with the parameters obtained from the data supplied by CVDMS as a cardiovascular intervention to save many lives and improve quality of life. Keywords: artery stiffness; blood pressure; cardiologist; cardiovascular disease; heart attack; heart failure; hemodynamic volumetric parameters; hospital re-admission; hypertension; risk-factor

Rapid Response Teams versus Critical Care Outreach Teams: Unplanned Escalations in Care and Associated Outcomes

The incidence of unplanned escalations during hospitalization is undocumented, but estimates may be as high as 1.2 million occurrences per year in the United States. Rapid Response Teams (RRT) were developed for the early recognition and treatment of deteriorating patients to deliver time-sensitive interventions, but evidence related to optimal activation criteria and structure is limited. The purpose of this study is to determine if an Early Warning Score-based Critical Care Outreach (CCO) model is related to the frequency of unplanned intra-hospital escalations in care compared to a RRT system based on staff nurse identification of vital sign derangements and physical assessments. The RRT model, in which staff nurses identified vital sign derangements to active the system, was compared with the addition of a CCO model, in which rapid response nurses activated the system based on Early Warning Score line graphs of patient condition over time. Logistic regressions were used to examine retrospective data from administrative datasets at a 237-bed community non-teaching hospital during two periods: 1) baseline period, RRT model (n=5,875) (Phase 1: October 1, 2010 – March 31, 2011), and; 2) intervention period, RRT/CCO model (n=6,273). (Phase 2: October 1, 2011 – March 31, 2012). The strongest predictor of unplanned escalations to the Intensive Care Unit was the type of rapid response system model. Unplanned ICU transfers were 1.4 times more likely to occur during the Phase 1 RRT period. In contrast, the type of rapid response model was not a significant predictor when all unplanned escalations (any type) were grouped together (medical-surgical-to-intermediate, medical-surgical-to-ICU and intermediate-to-ICU). This is the first study to report a relationship between unplanned escalations and different rapid response models. Based on the findings of fewer unplanned ICU transfers in the setting of a CCO model, health services researchers and clinicians should consider using automated Early Warning score graphs for hospital-wide surveillance of patient condition as a safety strategy

Nonpharmacological interventions to improve quality of life in heart failure: an integrative review

Objective: to identify articles that assessed the effectiveness or efficacy of nonpharmacological interventions to improve quality of life of people with heart failure in the literature. Method: an integrative literature review was performed in Lilacs, MedLine and SciELO databases, including randomized or nonrandomized clinical trials and quasi-experimental studies published between 2003 and 2014, in Portuguese, English or Spanish. Results: twenty-three studies were included. The categories of nonpharmacological interventions that improved quality of life of people with heart failure were: Remote health monitoring, Instructions on health practices, Physical activity follow-up and Traditional Chinese Medicine practices. Conclusion: these results can guide the selection of interventions to be implemented by health professionals that treat people with heart failure. Future systematic reviews with meta-analyses are needed in order to identify the most effective interventions for improving these individuals' quality of life.Objetivo: identificar, na literatura, artigos que avaliaram a efetividade ou eficácia de intervenções não farmacológicas para melhorar a qualidade de vida de pessoas com insuficiência cardíaca. Método: revisão integrativa de literatura realizada nas bases de dados Lilacs, MedLine e SciELO, incluindo ensaios clínicos randomizados ou não randomizados e estudos quase-experimentais publicados entre 2003 e 2014, em português, inglês e espanhol. Resultados: foram incluídos 23 estudos. As categorias de intervenções não farmacológicas que melhoraram a qualidade de vida de pessoas com insuficiência cardíaca foram: Monitoramento remoto da saúde, Orientação sobre práticas de saúde, Acompanhamento de atividade física e Práticas de Medicina Tradicional Chinesa. Conclusão: estes resultados podem direcionar a seleção de intervenções a serem implementadas por profissionais de saúde que cuidam de pessoas com insuficiência cardíaca. Futuras revisões sistemáticas com metanálise são necessárias para identificar as intervenções mais eficazes para melhorar a qualidade de vida desses indivíduos.Univ Fed Sao Paulo, Paulista Sch Nursing, Nursing Undergrad Course, Sao Paulo, BrazilUniv Sao Paulo, Sch Med, Inst Heart, Sao Paulo, BrazilUniv Fed Sao Paulo, Paulista Sch Nursing, Clin & Surg Nursing Dept, Sao Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista de Enfermagem, Curso de Graduação em Enfermagem. São Paulo-SP, BrasilUniversidade Federal de São Paulo, Escola Paulista de Enfermagem, Departamento de Enfermagem Clínica e Cirúrgica. São Paulo-SP, BrasilWeb of Scienc

Simulated case management of home telemonitoring to assess the impact of different alert algorithms on work-load and clinical decisions

© 2017 The Author(s). Background: Home telemonitoring (HTM) of chronic heart failure (HF) promises to improve care by timely indications when a patient's condition is worsening. Simple rules of sudden weight change have been demonstrated to generate many alerts with poor sensitivity. Trend alert algorithms and bio-impedance (a more sensitive marker of fluid change), should produce fewer false alerts and reduce workload. However, comparisons between such approaches on the decisions made and the time spent reviewing alerts has not been studied. Methods: Using HTM data from an observational trial of 91 HF patients, a simulated telemonitoring station was created and used to present virtual caseloads to clinicians experienced with HF HTM systems. Clinicians were randomised to either a simple (i.e. an increase of 2 kg in the past 3 days) or advanced alert method (either a moving average weight algorithm or bio-impedance cumulative sum algorithm). Results: In total 16 clinicians reviewed the caseloads, 8 randomised to a simple alert method and 8 to the advanced alert methods. Total time to review the caseloads was lower in the advanced arms than the simple arm (80 ± 42 vs. 149 ± 82 min) but agreements on actions between clinicians were low (Fleiss kappa 0.33 and 0.31) and despite having high sensitivity many alerts in the bio-impedance arm were not considered to need further action. Conclusion: Advanced alerting algorithms with higher specificity are likely to reduce the time spent by clinicians and increase the percentage of time spent on changes rated as most meaningful. Work is needed to present bio-impedance alerts in a manner which is intuitive for clinicians

Implementation of a Post Discharge Education Intervention to Reduce 30 Day Readmission Rates in African American Males Ages 18-50 with Heart Failure

Implementation of a post-discharge education intervention to reduce 30 day readmission rates in African American males ages 18-50 with heart failure Abstract Purpose: Heart failure is a clinical condition caused by a variety of cardiovascular diseases that create changes in the structure and function of the heart. A high morbidity is associated with heart failure due to frequent exacerbations of the disease and resultant frequent hospital readmission rates. Hospital readmission rates are more pronounced in African Americans. This project evaluates the effects of a 90 day post-discharge education intervention on readmission rates in a convenience sample of African American males ages 18-50 obtained from an urban teaching hospital. Methods: A quality improvement project which utilized a 90 day post-discharge phone education intervention. Results: A total of 10 participants were recruited and a final number of 6 actually consented to participate. Four participants immediately withdrew from the intervention. The remaining 2 each experienced at least 2 readmissions during the first 30 days post discharge and eventually withdrew from the intervention prior to the end of data collection. Conclusion: The outcome of this project mirrors much of the current literature in terms of low compliance and high readmission rates in spite of education outreach. Key terms: African American, males, 18-50 years old, young adults, heart failure, health promotion, racial differences in HF, and education