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This study has demonstrated how technology may contribute to integrated care solutions by comparing conventional ward telemetry (WT) to a wearable ECG monitor (S-Patch) to detect atrial fibrillation (AF) in patients with stroke.

51 patients admitted for stroke workup were recruited across two major tertiary centres to compare WT monitoring for two days versus S-Patch for four days in the detection of AF. The efficacy to detect AF using both technologies was assessed via data extractions and medical officer review. A matrix was used to measure nursing/patient satisfaction and setup/resource times were assessed.

Patients (84–94%) and nursing staff (75–95%) preferred the S-Patch wearable technology. Non-parametric tests indicated significant time saving for removal of S-Patch versus WT [2.2 min vs 5.1 min (p = 0.00)]. Efficacy of S-Patch to detect AF following medical officer review was greater than WT, with seven patients identified with AF by S-Patch versus one using WT. The S-patch had a false positive rate of 78%.

The S-Patch is sensitive in the detection of AF; however, it showed a high false-positive rate with automated reporting. This study has provided insight into the details of delivery of integrated healthcare using wearable technology.

The technology and partnership were the first-in-kind in Australia. The S-Patch had a higher detection rate of AF compared to WT which allows patients to be anti-coagulated appropriately for the prevention of further stroke. The results of this study will be ideally placed to inform future policy in integrated healthcare using new technologies.

A novel method has been proposed to reduce the false alarm rate of arrhythmia patients regarding life-threatening conditions in the intensive care unit. In this purpose, the atrial blood pressure, photoplethysmogram (PLETH), electrocardiogram (ECG) and respiratory (RESP) signals are considered as input signals.

Three machine learning approaches feed-forward artificial neural network (ANN), ensemble learning method and k-nearest neighbors searching methods are used to detect the false alarm. The proposed method has been implemented using Arduino and MATLAB/SIMULINK for real-time ICU-arrhythmia patients' monitoring data.

The proposed method detects the false alarm with an accuracy of 99.4 per cent during asystole, 100 per cent during ventricular flutter, 98.5 per cent during ventricular tachycardia, 99.6 per cent during bradycardia and 100 per cent during tachycardia. The proposed framework is adaptive in many scenarios, easy to implement, computationally friendly and highly accurate and robust with overfitting issue.

As ECG signals consisting with PQRST wave, any deviation from the normal pattern may signify some alarming conditions. These deviations can be utilized as input to classifiers for the detection of false alarms; hence, there is no need for other feature extraction techniques. Feed-forward ANN with the Lavenberg–Marquardt algorithm has shown higher rate of convergence than other neural network algorithms which helps provide better accuracy with no overfitting.

Inappropriate cardiac monitoring leads to increased hospital resource utilization and alarm fatigue, which is ultimately detrimental to patient safety. Our institution implemented a continuous cardiac monitoring (CCM) policy that focused on selective monitoring for patients based on the American Heart Association (AHA) guidelines. The primary goal of this study was to perform a three-year median follow-up review on the longitudinal impact of a selective CCM policy on usage rates, length of stay (LOS), and mortality rates across the medical center. A secondary goal was to determine the effect of smaller-scale interventions focused on reeducating the nursing population on the importance of cardiac alarms.

A system-wide policy was developed at The Ohio State University in December 2013 based on guidelines for selective CCM in all patient populations. Patients were stratified into Critical Class I, II, and III with 72 hours, 48 hours, or 36 hours of CCM, respectively. Pre- and post-implementation measures included average cardiac monitoring days (CMD), emergency department (ED) boarding rate, mortality rates, and LOS. A 12-week evaluation period was analyzed prior to, directly after, and three years after implementation.

There was an overall decrease of 53.5% CMDs directly after implementation of selective CCM. This had remained stable at the three-year follow-up with slight increase of 0.5% (p = 0.2764). Subsequent analysis by hospital type revealed that the largest and most stable reductions in CMD were in noncardiac hospitals. The cardiac hospital CMD reduction was stable for roughly one year, then dipped into a lower stable level for nine months, then returned to the previous post-implementation levels. This change coincided with a smaller intervention to further reduce CMD in the cardiac hospital. There was no significant change in mortality rates with a slight decrease of 3.1% at follow-up (p = 0.781). Furthermore, there was no significant difference in LOS with a slight increase of 1.1% on follow-up (p = 0.649). However, there was a significant increase in ED boarding rate of 7.7% (p < 0.001) likely due to other hospital factors altering boarding times.

Implementing selective CCM decreases average cardiac monitoring rate without affecting LOS or overall mortality rate. Selective cardiac monitoring is also a sustainable way to decrease overall hospital resource utilization and more appropriately focus on patient care.

In the state of Hawaii, it has been shown that certain ethnic minority groups, such as Filipinos and Pacific Islanders, suffer disproportionally high rates of cardiovascular disease, evidence that local health-care systems and governing bodies fail to equally extend the human right to health to all. This study aims to examine whether these ethnic health disparities in cardiovascular disease persist even within an already globally disadvantaged group, the houseless population of Hawaii.

A retrospective chart review of records from Hawaii Houseless Outreach and Medical Education Project clinic sites from 2016 to 2020 was performed to gather patient demographics and reported histories of type II diabetes, obesity, hyperlipidemia, hypertension and other cardiovascular disease diagnoses. Reported disease prevalence rates were compared between larger ethnic categories as well as ethnic subgroups.

Unexpectedly, the data revealed lower reported prevalence rates of most cardiometabolic diseases among the houseless compared to the general population. However, multiple ethnic health disparities were identified, including higher rates of diabetes and obesity among Native Hawaiians and other Pacific Islanders and higher rates of hypertension among Filipinos and Asians overall. The findings suggest that even within a generally disadvantaged houseless population, disparities in health outcomes persist between ethnic groups and that ethnocultural considerations are just as important in caring for this vulnerable population.

To the best of the authors’ knowledge, this is the first comprehensive study focusing on ethnic health disparities in cardiovascular disease and the structural processes that contribute to them, among a houseless population in the ethnically diverse state of Hawaii.

The ultimate aim of this study is to investigate how health information needs’ satisfaction actually makes a difference to the patients' management of a chronic clinical condition. The literature falls short of providing evidence on the interaction between patients' health information seeking behaviour and the successful management of a clinical condition. On the other hand, patient education and good information seeking practices are deemed necessary for hypertension management daily decisions.

A specially designed questionnaire study was developed: The survey design was informed by the information seeking behaviour model of Wilson for studying hypertension patients' information needs, information resources and obstacles patients face while seeking hypertension-related information. Moreover, clinical information was collected in order to make associations and inference on the impact of information seeking on patients' clinical outcomes.

The study included 111 patients submitted to the outpatient hypertension clinic of a university hospital in Athens for a 24-h ambulatory blood pressure measurement (ABPM). The analysis showed that those reporting higher satisfaction level of their information needs achieved lower values in ABPM (ABPM<130/80mmHg, p = 0.049). Stepwise the logistic regression analysis revealed three independent factors to predict the possibility of being optimally treated (ABPM<130/80mmHg). Dipping status (OR: 14.052, 95% CI: 4.229–46.688, p = 0.0001) patients with high satisfaction level of their disease (OR: 13.450, 95% CI: 1.364–132.627, p = 0.026) and interpersonal relationships were used as the main source of information (OR: 1.762, 95% CI: 1.024–3.031, p = 0.41).

Hypertensive patients with high satisfaction level of information achieve better disease control. Among different sources of information, interpersonal relationships emerge as the most appropriate factor for patients' disease control.

The purpose of this paper is to analyse the accounts of Swedish cardiologists concerning patient involvement in consultations for atrial fibrillation (AF). The questions were: how cardiologists handle and provide scope for patient involvement in medical consultations regarding AF treatment and how cardiologists describe their familiarity with shared decision-making.

A descriptive study was designed. Ten interviews with cardiologists at four Swedish hospitals were held, and a qualitative content analysis was performed on the collected data.

The analysis shows cardiologists’ accounts of persuasive practice, protective practice, professional role and medical craftsmanship when it comes to patient involvement and shared decision-making. The term “shared decision-making” implies a concept of not only making one decision but also ensuring that it is finalised with a satisfactory agreement between both parties involved, the patient as well as the cardiologist. In order for the idea of patient involvement to be fulfilled, the two parties involved must have equal power, which can never actually be guaranteed.

Methodologically, this paper reflects the special contribution that can be made by the research design of descriptive qualitative content analysis (Krippendorff, 2004) to reveal and understand cardiologists’ perspectives on patient involvement and participation in medical consultation and shared decision-making. The utility of this kind of analysis is to find what cardiologists said and how they arrived at their understanding about patient involvement. Accordingly, there is no quantification in this type of research.

Cardiologists should prioritise patient involvement and participation in decision-making regarding AF treatment decisions in consultations when trying to meet the request of patient involvement.

Theoretically, the authors have learned that the patient involvement and shared decision-making requires the ability to see patients as active participants in the medical consultation process.

The aim was to test the feasibility of using automated data, and evaluate the impact of an emergency cardiac decision unit (CDU) on the overall outcomes of patients seen for chest discomfort. We used a retrospective, quasi‐experimental design to identify patients who had cardiac enzymes measured and an electrocardiogram performed during an ED visit in two six‐month periods, pre‐CDU (1 January‐30 June 1995) and post‐CDU (1 January‐ 30 June 1996). A total of 4,336 patients had outcomes assessed. After opening, 14.8 per cent of all chest pain cases were treated in the CDU. Hospital admission rates were reduced from 81.1 per cent to 66.7 per cent. Length of stay, myocardial infarction rates, and mortality were unchanged. The 14‐day revisit rates increased from 5.3 per cent to 10.3 per cent. We conclude that cardiac decision units decrease hospital admissions but increase ED revisit rates as a consequence of this now frequently used care pathway.

Older adults with atrial fibrillation (AF) have put growing demands on a poorly integrated healthcare system. This is of particular concern in rural communities with rapid population aging and few healthcare resources elevating risk of stroke and mortality. The purpose of this paper is to explore healthcare delivery risks for rural older adults with AF.

This qualitative study collected data from AF patients, healthcare providers and decision makers. Ten patients participated in six-month care journeys involving interviews, logs, photos, and chart reviews. In total, 13 different patients and ten healthcare providers participated in focus groups and two decision makers participated in interviews.

Three key health service risks emerged: lack of patient-focussed access and self-management; unplanned care coordination and follow-up across the continuum of care; and ineffective teamwork with variable perspectives among patients, providers, and decision makers.

This study extends the understanding of risks to the health system level. Results provide important information for further research aimed at interventions to improve health service delivery and policy change to mitigate risks for this population.