Development, internal reliability and preliminary construct validity of the Dutch Dietary Intention Evaluation Tool for In-patients (DIETI).

BACKGROUND AND AIMS: Diet is important in prevention and management of non-communicable disease and in particular, cardiovascular disease. Recently, more hospitals gear towards healthier dietary policies, however, a tool to assess the effect of these interventions in patient populations is currently lacking. The Theory of Planned Behavior (TPB) is generally used to assess health-related behavior and offers a framework for development of questionnaires. In this study, we aim to evaluate the reliability, internal consistency and preliminary construct validity of the newly developed Dietary Intention Evaluation Tool for In-hospital patients (DIETI) which is based on the TPB. METHODS AND RESULTS: An expert panel constructed the item list of the DIETI. A total of 312 patients admitted to the cardiology ward filled out the DIETI. Explanatory- and confirmatory factor analysis showed that our tool adequately discerns five TPB-consistent factors regarding a healthy diet in hospitalized patients. (N = 312, for the CFA model χ2 = 313.072 (df = 160, p < 0.001, CFI = 0.939, RMSEA = 0.058). Subsequent analysis of reliability showed satisfactory to strong internal consistency of the questionnaire as a whole and all subscales (Cronbach's alpha for the subscales ranging between 0.65 and 0.88). CONCLUSIONS: We conclude that the DIETI is an internally reliable tool to assess behavioral intentions regarding a healthy diet of in-hospital patients. Thus, this questionnaire can be used to evaluate the effect of dietary interventions aimed at hospitalized patients.

Identifying barriers and facilitators to adopting healthier dietary choices in clinical care: a cross-sectional observational study.

Background and aims: Adopting healthier diets can drastically improve societal health. Our environment plays a crucial role in daily dietary choices and hospitals in particular can stimulate patients to adopt healthier eating habits. Unfortunately, no robust clinically applicable cuing tools exist to help guide in-hospital dietary interventions. The purpose of this study was to identify patient-related barriers and facilitators to adopting healthier dietary choices. Methods and results: This cross-sectional observational study was conducted on the cardiology ward of a university medical center between June 2020 and January 2021. Of the 594 patients asked and the 312 completed surveys on healthy eating intentions, 285 responses were considered for analysis. Notably, the majority of respondents were male (68.8%), with an average hospital stay of 3.3 days. The results indicate that cardiac patients attribute significantly greater influence on their dietary behavior to doctors compared to other caregivers, including dieticians (X2 = 37.09, df = 9, p < 0.001). Also, younger patients (below 70 years of age) were more inclined to plan changing dietary behavior than older patients. Most mentioned facilitators for adopting a healthier diet were more information/counseling, help in preparing food, support from family and friends, and more emphasis from a doctor. Conclusion: The study highlights the importance of involving doctors in formulating dietary policies and patient-directed interventions within hospital settings. It also sheds light on the barriers and facilitators for promoting healthier dietary behaviors among patients during their hospitalization.

The Box-eHealth in the Outpatient Clinic Follow-up of Patients With Acute Myocardial Infarction: Cost-Utility Analysis.

BACKGROUND: Smartphone compatible wearables have been released on the consumers market, enabling remote monitoring. Remote monitoring is often named as a tool to reduce the cost of care. OBJECTIVE: The primary purpose of this paper is to describe a cost-utility analysis of an eHealth intervention compared to regular follow-up in patients with acute myocardial infarction (AMI). METHODS: In this trial, of which clinical results have been published previously, patients with an AMI were randomized in a 1:1 fashion between an eHealth intervention and regular follow-up. The remote monitoring intervention consisted of a blood pressure monitor, weight scale, electrocardiogram device, and step counter. Furthermore, two in-office outpatient clinic visits were replaced by e-visits. The control group received regular care. The differences in mean costs and quality of life per patient between both groups during one-year follow-up were calculated. RESULTS: Mean costs per patient were €2417±2043 (US $2657±2246) for the intervention and €2888±2961 (US $3175±3255) for the control group. This yielded a cost reduction of €471 (US $518) per patient. This difference was not statistically significant (95% CI -€275 to €1217; P=.22, US $-302 to $1338). The average quality-adjusted life years in the first year of follow-up was 0.74 for the intervention group and 0.69 for the control (difference -0.05, 95% CI -0.09 to -0.01; P=.01). CONCLUSIONS: eHealth in the outpatient clinic setting for patients who suffered from AMI is likely to be cost-effective compared to regular follow-up. Further research should be done to corroborate these findings in other patient populations and different care settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT02976376; https://clinicaltrials.gov/ct2/show/NCT02976376. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/resprot.8038.

Referral and participation in cardiac rehabilitation of patients following acute coronary syndrome; lessons learned.

PURPOSE: Cardiac rehabilitation (CR) after hospitalization for acute coronary syndrome (ACS) has shown to reduce mortality, readmissions, and improve quality of life. CR is recommended by international guidelines but previous studies have shown low participation rates. Systematic CR referral might improve CR participation. METHODS: The present study evaluates CR referral and CR participation of patients hospitalized for ACS in 2017 and treated according to local protocol, which includes systematic CR referral. Participation rate was divided into a group that finished the CR program and drop outs. In addition, factors associated with CR referral and participation rate were evaluated. RESULTS: A total of 469 patients eligible for CR were included in the study, of which 377 (80%) were referred for CR and 353 (75%) participated in CR. Ninety percent of participants completed the CR program. Factors independently associated with CR referral included age (50-60 year vs. > 70 year: odds ratio [OR] 4.7, 95% confidence interval [CI] 1.98-11.2), diagnosis (ST-elevation myocardial infarction vs. unstable angina: OR 17.7, CI 7.59-41.7), previous cardiovascular disease (OR 0.4, CI 0.19-0.73) and left ventricular dysfunction vs. normal function (OR 2.2, CI 1.11-4.52). A larger distance to the CR center was associated with lower CR participation (<5km vs. > 20 km: OR 3.1, CI 1.20-7.72). CONCLUSIONS: Systematic CR referral in ACS patients results in high CR referral (80%) and participation (75%) rates. CR adherence might be further improved by increasing CR referral, especially in older patients and patients with NSTEMI or unstable angina.

Effect of Smartphone-Enabled Health Monitoring Devices vs Regular Follow-up on Blood Pressure Control Among Patients After Myocardial Infarction: A Randomized Clinical Trial.

Importance: Smart technology via smartphone-compatible devices might improve blood pressure (BP) regulation in patients after myocardial infarction. Objectives: To investigate whether smart technology in clinical practice can improve BP regulation and to evaluate the feasibility of such an intervention. Design, Setting, and Participants: This study was an investigator-initiated, single-center, nonblinded, feasibility, randomized clinical trial conducted at the Department of Cardiology of the Leiden University Medical Center between May 2016 and December 2018. Two hundred patients, who were admitted with either ST-segment elevation myocardial infarction or non-ST-segment acute coronary syndrome, were randomized in a 1:1 fashion between follow-up groups using smart technology and regular care. Statistical analysis was performed from January 2019 to March 2019. Interventions: For patients randomized to regular care, 4 physical outpatient clinic visits were scheduled in the year following the initial event. In the intervention group, patients were given 4 smartphone-compatible devices (weight scale, BP monitor, rhythm monitor, and step counter). In addition, 2 in-person outpatient clinic visits were replaced by electronic visits. Main Outcomes and Measures: The primary outcome was BP control. Secondary outcomes, as a parameter of feasibility, included patient satisfaction (general questionnaire and smart technology-specific questionnaire), measurement adherence, all-cause mortality, and hospitalizations for nonfatal adverse cardiac events. Results: In total, 200 patients (median age, 59.7 years [interquartile range, 52.9-65.6 years]; 156 men [78%]) were included, of whom 100 were randomized to the intervention group and 100 to the control group. After 1 year, 79% of patients in the intervention group had controlled BP vs 76% of patients in the control group (P = .64). General satisfaction with care was the same between groups (mean [SD] scores, 82.6 [14.1] vs 82.0 [15.1]; P = .88). The all-cause mortality rate was 2% in both groups (P > .99). A total of 20 hospitalizations for nonfatal adverse cardiac events occurred (8 in the intervention group and 12 in the control group). Of all patients, 32% sent in measurements each week, with 63% sending data for more than 80% of the weeks they participated in the trial. In the intervention group only, 90.3% of patients were satisfied with the smart technology intervention. Conclusions and Relevance: These findings suggest that smart technology yields similar percentages of patients with regulated BP compared with the standard of care. Such an intervention is feasible in clinical practice and is accepted by patients. More research is mandatory to improve patient selection of such an intervention. Trial Registration: ClinicalTrials.gov Identifier: NCT02976376.

Using Smart Technology to Improve Outcomes in Myocardial Infarction Patients: Rationale and Design of a Protocol for a Randomized Controlled Trial, The Box.

BACKGROUND: Recent evidence suggests that frequent monitoring using smartphone-compatible wearable technologies might improve clinical effectiveness and patient satisfaction of care. OBJECTIVE: The aim of this study is to investigate the clinical effectiveness and patient satisfaction of a smart technology intervention in patients admitted with a ST elevation myocardial infarction (STEMI) or non-ST acute coronary syndrome (NST-ACS). METHODS: In this single center, open, randomized controlled trial patients who suffered from STEMI or NST-ACS will be randomized 1:1 to an intervention group or control group. Both groups will be followed up to one year after the index event. The intervention group will take daily measurements with a smartphone-compatible electrocardiogram device, blood pressure (BP) monitor, weight scale, and activity tracker. Furthermore, two of four outpatient clinic visits will be replaced by electronic visits (1 and 6 months after index event). The control group will receive regular care, consisting of four outpatient clinic visits (1, 3, 6, and 12 months after index event). All patients will be asked to fill in validated questionnaires about patient satisfaction, quality of life, propensity of medication adherence, and physical activity. RESULTS: The primary outcome of this trial will be percentage of patients with controlled BP. Secondary outcomes include patient satisfaction, health care utilization, major adverse cardiac events, medication adherence, physical activity, quality of life, and percentage of patients in which a sustained arrhythmia is detected. CONCLUSIONS: Smart technology could potentially improve care in postmyocardial infarction patients. This trial will investigate whether usage of smart technology can improve clinical- and cost-effectiveness of care. TRIAL REGISTRATION: Clinicaltrials.gov NCT02976376; https://clinicaltrials.gov/ct2/show/NCT02976376 (Archived by WebCite at http://www.webcitation.org/6tcvAdbdH).