Search

Background: To date, claims data have not been used to study outcome differences between low and high socioeconomic status (SES) patients surviving ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) in the Netherlands. Aim: To evaluate STEMI and NSTEMI care among patients with low and high SES in the referral area of three Dutch percutaneous coronary intervention (PCI) centres, using claims data as a source. Methods: STEMI and NSTEMI patients treated in 2015–2017 were included. Patients' SES scores were collected based on their postal code via an open access government database. In patients with low (SES1) and high (SES4) status, revascularisation strategies and secondary prevention medication were compared. Results: A total of 2065 SES1 patients (age 68 ± 13 years, 58% NSTEMI) and 1639 SES4 patients (age 68 ± 13 years, 63% NSTEMI) were included. PCI use was lower in SES1 compared to SES4 in both STEMI (80% vs 84%, p < 0.012) and NSTEMI (42% vs 48%, p < 0.002) patients. Coronary artery bypass grafting was performed more often in SES1 than in SES4 in both STEMI (7% vs 4%, p = NS) and NSTEMI (11% vs 7%, p < 0.001) patients. Optimal medical therapy use in STEMI patients was higher in SES1 compared to SES4 (52% vs 46%, p = 0.01) but comparable among NSTEMI patients (39% vs 40%, p = NS). One-year mortality was comparable in SES1 and SES4 patients following STEMI (14% vs 16%, p = NS) and NSTEMI (10% vs 11%, p = NS). Conclusion: Combined analysis of claims data and area-specific socioeconomic statistics can provide unique insight into how to improve myocardial infarction care for low and high SES patients. [ABSTRACT FROM AUTHOR]

BackgroundAtrial fibrillation (AF) is the most common arrhythmia, and its prevalence is increasing. Early diagnosis is important to reduce the risk of stroke. Mobile health (mHealth) devices, such as single-lead electrocardiogram (ECG) devices, have been introduced to the worldwide consumer market over the past decade. Recent studies have assessed the usability of these devices for detection of AF, but it remains unclear if the use of mHealth devices leads to a higher AF detection rate. ObjectiveThe goal of the research was to conduct a systematic review of the diagnostic detection rate of AF by mHealth devices compared with traditional outpatient follow-up. Study participants were aged 16 years or older and had an increased risk for an arrhythmia and an indication for ECG follow-up—for instance, after catheter ablation or presentation to the emergency department with palpitations or (near) syncope. The intervention was the use of an mHealth device, defined as a novel device for the diagnosis of rhythm disturbances, either a handheld electronic device or a patch-like device worn on the patient’s chest. Control was standard (traditional) outpatient care, defined as follow-up via general practitioner or regular outpatient clinic visits with a standard 12-lead ECG or Holter monitoring. The main outcome measures were the odds ratio (OR) of AF detection rates. MethodsTwo reviewers screened the search results, extracted data, and performed a risk of bias assessment. A heterogeneity analysis was performed, forest plot made to summarize the results of the individual studies, and albatross plot made to allow the P values to be interpreted in the context of the study sample size. ResultsA total of 3384 articles were identified after a database search, and 14 studies with a 4617 study participants were selected. All studies but one showed a higher AF detection rate in the mHealth group compared with the control group (OR 1.00-35.71), with all RCTs showing statistically significant increases of AF detection (OR 1.54-19.16). Statistical heterogeneity between studies was considerable, with a Q of 34.1 and an I2 of 61.9, and therefore it was decided to not pool the results into a meta-analysis. ConclusionsAlthough the results of 13 of 14 studies support the effectiveness of mHealth interventions compared with standard care, study results could not be pooled due to considerable clinical and statistical heterogeneity. However, smartphone-connectable ECG devices provide patients with the ability to document a rhythm disturbance more easily than with standard care, which may increase empowerment and engagement with regard to their illness. Clinicians must beware of overdiagnosis of AF, as it is not yet clear when an mHealth-detected episode of AF must be deemed significant.

BackgroundPatient education is crucial in the secondary prevention of cardiovascular disease. Novel technologies such as augmented reality or mixed reality expand the possibilities for providing visual support in this process. Mixed reality creates interactive digital three-dimensional (3D) projections overlaying virtual objects on the real-world environment. While augmented reality only overlays objects, mixed reality not just overlays but anchors virtual objects to the real world. However, research on this technology in the patient domain is scarce. ObjectiveThe aim of this study was to understand how patients perceive information provided after myocardial infarction and examine if mixed reality can be supportive in this process. MethodsIn total, 12 patients that experienced myocardial infarction and 6 health care professionals were enrolled in the study. Clinical, demographic, and qualitative data were obtained through semistructured interviews, with a main focus on patient experiences within the hospital and the knowledge they gained about their disease. These data were then used to map a susceptible timeframe to identify how mixed reality can contribute to patient information and education. ResultsKnowledge transfer after myocardial infarction was perceived by patients as too extensive, not personal, and inconsistent. Notably, knowledge on anatomy and medication was minimal and was not recognized as crucial by patients, whereas professionals stated the opposite. Patient journey analysis indicated the following four critical phases of knowledge transfer: at hospital discharge, at the first outpatient visit, during rehabilitation, and during all follow-up outpatient visits. Important patient goals were understanding the event in relation to daily life and its implications on resuming daily life. During follow-up, understanding physical limitations and coping with the condition and medication side effects in daily life emerged as the most important patient goals. The professionals’ goals were to improve recovery, enhance medication adherence, and offer coping support. ConclusionsThere is a remarkable difference between patients’ and professionals’ goals regarding information and education after myocardial infarction. Mixed reality may be a practical tool to unite perspectives of patients and professionals on the disease in a more even manner, and thus optimize knowledge transfer after myocardial infarction. Improving medication knowledge seems to be a feasible target for mixed reality. However, further research is needed to create durable methods for education on medication through mixed reality interventions.

BackgroundAtrial fibrillation (AF), sternal wound infection, and cardiac decompensation are complications that can occur after cardiac surgery. Early detection of these complications is clinically relevant, as early treatment is associated with better clinical outcomes. Remote monitoring with the use of a smartphone (mobile health [mHealth]) might improve the early detection of complications after cardiac surgery. ObjectiveThe primary aim of this study is to compare the detection rate of AF diagnosed with an mHealth solution to the detection rate of AF diagnosed with standard care. Secondary objectives include detection of sternal wound infection and cardiac decompensation, as well as assessment of quality of life, patient satisfaction, and cost-effectiveness. MethodsThe Box 2.0 is a study with a prospective intervention group and a historical control group for comparison. Patients undergoing cardiac surgery at Leiden University Medical Center are eligible for enrollment. In this study, 365 historical patients will be used as controls and 365 other participants will be asked to receive either The Box 2.0 intervention consisting of seven home measurement devices along with a video consultation 2 weeks after discharge or standard cardiac care for 3 months. Patient information will be analyzed according to the intention-to-treat principle. The Box 2.0 devices include a blood pressure monitor, thermometer, weight scale, step count watch, single-lead electrocardiogram (ECG) device, 12-lead ECG device, and pulse oximeter. ResultsThe study started in November 2018. The primary outcome of this study is the detection rate of AF in both groups. Quality of life is measured with the five-level EuroQol five-dimension (EQ-5D-5L) questionnaire. Cost-effectiveness is calculated from a society perspective using prices from Dutch costing guidelines and quality of life data from the study. In the historical cohort, 93.9% (336/358) completed the EQ-5D-5L and patient satisfaction questionnaires 3 months after cardiac surgery. ConclusionsThe rationale and design of a study to investigate mHealth devices in postoperative cardiac surgery patients are presented. The first results are expected in September 2020. Trial RegistrationClinicalTrials.gov NCT03690492; http://clinicaltrials.gov/show/NCT03690492 International Registered Report Identifier (IRRID)DERR1-10.2196/16326

BackgroundImproving teamwork in surgery is a complex goal and difficult to achieve. Human factors questionnaires, such as the Safety Attitudes Questionnaire (SAQ), can help us understand medical teamwork and may assist in achieving this goal. ObjectiveThis paper aimed to assess local team and safety culture in a cardiovascular surgery setting to understand how purposeful teamwork improvements can be reached. MethodsTwo cardiovascular surgical teams performing complex aortic treatments were assessed: an endovascular-treatment team (ETT) and an open-treatment team (OTT). Both teams answered an online version of the SAQ Dutch Edition (SAQ-NL) consisting of 30 questions related to six different domains of safety: teamwork climate, safety climate, job satisfaction, stress recognition, perceptions of management, and working conditions. In addition, one open-ended question was posed to gain more insight into the completed questionnaires. ResultsThe SAQ-NL was completed by all 23 ETT members and all 13 OTT members. Team composition was comparable for both teams: 57% and 62% males, respectively, and 48% and 54% physicians, respectively. All participants worked for 10 years or more in health care. SAQ-NL mean scores were comparable between both teams, with important differences found between the physicians and nonphysicians of the ETT. Nonphysicians were less positive about the safety climate, job satisfaction, and working climate domains than were the physicians (P