Hendrikus van Os
Please Note
2 records found
1
Tailoring remote patient management to optimise cardiovascular risk management in primary care
A mixed-methods implementation study informing large-scale implementation
Aim: Remote patient management (RPM) effectively aids cardiovascular risk management, but its large-scale implementation remains challenging. Panel management may facilitate implementation by using comprehensive data to identify patients at risk of cardiovascular diseases and tailor interventions. This study evaluated the implementation strategies and clinical outcomes of a multi-component RPM intervention ‘Connect@Heart’. Methods: We conducted a mixed-methods study over six months in four primary care practices in the Netherlands, evaluating two patient groups: (i) patients with a BMI < 25 received a blood pressure monitor alone (BP Box), and (ii) patients with a BMI > 25 or cardiovascular disease received a combination of a BP monitor, a scale, and an activity tracker (Lifestyle Box). Baseline and six-month follow-up assessments were performed using linear mixed-effects models, and implementation outcomes were evaluated using the RE-AIM framework. Results: Our approach achieved high enrolment, with 189 out of 200 initially interested patients (94%) participating. The intervention was associated with a significant reduction in BP levels within both groups (BP Box systolic BP from 139 ± 21 mmHg at baseline to 132 ± 18 mmHg at follow-up, p < 0.001 and Lifestyle Box 142 ± 16 mmHg to 131 ± 14 mmHg at follow-up, p < 0.001), especially for those with uncontrolled hypertension. After six months, 66% of patients performed measurements weekly. All participating practices continued using the intervention post-study. Conclusion: This study demonstrates that proactively identifying patient panels at risk for CVD and tailoring multi-component RPM interventions to patient panels are promising implementation strategies for reaching favourable clinical outcomes at scale.
Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists.
Objective:
This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.
Methods:
Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By “RPM interventions,” we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.
Results:
In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.
Conclusions:
At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain. ...
Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists.
Objective:
This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.
Methods:
Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By “RPM interventions,” we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.
Results:
In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.
Conclusions:
At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.