Jedidja Lok-Visser , Jobbe P.L. Leenen , Heleen M. den Hertog , Gina van Vemde , Jeroen Rekveldt , Jan W.K. van den Berg , Gijs A. Patijn , Judith R. Cornelisse-Vermaat , Gréanne Leeftink , Jan Gerard Maring
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The model was applied to three types of interventions in a large Dutch teaching hospital: 1) home telemonitoring for chronic patients (case (COPD), 2) remote aftercare for patients with acute illnesses (case: stroke), and 3) parenteral medication administration at home (case: prosthetic hip or knee joint infections).</div></div><div><h3>Results</h3><div>Output of the PCA model showed that the cost savings can exceed the intervention costs if an intervention decreases the length of stay of patients. For COPD telemonitoring 10.1 % of the healthcare utilization should be reduced to reach break-even, and for antibiotic treatment at home break-even is reached if 4.6 % of the length of stay is reduced. The cost savings of remote aftercare for stroke patients is focused on reducing outpatient visits, and in the current Dutch reimbursement system this does not completely cover the costs.</div></div><div><h3>Conclusions</h3><div>The PCA model is an easy to implement and useful tool for assessing the financial impact of CC interventions from a hospital perspective. It supports decision makers to prospectively assess the cost and capacity benefits of interventions and to inform decisions on implementation. Further studies are needed to extend the model across the entire healthcare continuum.</div></div><div><h3>Public interest summary</h3><div>We present a prospective cost analysis (PCA) model for estimating the financial impact of Connected Care interventions in hospitals to support managerial decision-making. Connected Care interventions are based on an integrated care approach utilizing digital health technologies to enhance patient-centred, collaborative care, where patients receive care at home. Examples are telemonitoring of chronic obstructive pulmonary disease (COPD) patients, remote aftercare for stroke patients and infusion treatment at home for orthopaedic patients with an infection. These interventions have additional costs, but also save part of the costs of the conventional care, and have benefits in terms of a decrease in outpatient visits or hospitalizations. We provide a model where a hospital can calculate the impact in costs and benefits of Connected Care interventions and test this on these three examples. We show that the cost savings are able to exceed the intervention costs if an intervention has impact on the hospitalization.</div></div>","PeriodicalId":48672,"journal":{"name":"Health Policy and Technology","volume":"13 6","pages":"Article 100926"},"PeriodicalIF":3.4000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A prospective cost analysis model for financial impact of Connected Care interventions on hospitals’ budget\",\"authors\":\"Jedidja Lok-Visser , Jobbe P.L. Leenen , Heleen M. den Hertog , Gina van Vemde , Jeroen Rekveldt , Jan W.K. van den Berg , Gijs A. Patijn , Judith R. Cornelisse-Vermaat , Gréanne Leeftink , Jan Gerard Maring\",\"doi\":\"10.1016/j.hlpt.2024.100926\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><div>To present a prospective cost analysis (PCA) model for estimating the financial impact of Connected Care interventions in hospitals to support managerial decision-making, and describe its application to three different care pathways.</div></div><div><h3>Methods</h3><div>Input of the developed PCA model consisted of standard of care input and intervention-specific input. The output of the model included: capacity benefits, costs, and reimbursements. The model was applied to three types of interventions in a large Dutch teaching hospital: 1) home telemonitoring for chronic patients (case (COPD), 2) remote aftercare for patients with acute illnesses (case: stroke), and 3) parenteral medication administration at home (case: prosthetic hip or knee joint infections).</div></div><div><h3>Results</h3><div>Output of the PCA model showed that the cost savings can exceed the intervention costs if an intervention decreases the length of stay of patients. For COPD telemonitoring 10.1 % of the healthcare utilization should be reduced to reach break-even, and for antibiotic treatment at home break-even is reached if 4.6 % of the length of stay is reduced. The cost savings of remote aftercare for stroke patients is focused on reducing outpatient visits, and in the current Dutch reimbursement system this does not completely cover the costs.</div></div><div><h3>Conclusions</h3><div>The PCA model is an easy to implement and useful tool for assessing the financial impact of CC interventions from a hospital perspective. It supports decision makers to prospectively assess the cost and capacity benefits of interventions and to inform decisions on implementation. Further studies are needed to extend the model across the entire healthcare continuum.</div></div><div><h3>Public interest summary</h3><div>We present a prospective cost analysis (PCA) model for estimating the financial impact of Connected Care interventions in hospitals to support managerial decision-making. 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A prospective cost analysis model for financial impact of Connected Care interventions on hospitals’ budget
Objectives
To present a prospective cost analysis (PCA) model for estimating the financial impact of Connected Care interventions in hospitals to support managerial decision-making, and describe its application to three different care pathways.
Methods
Input of the developed PCA model consisted of standard of care input and intervention-specific input. The output of the model included: capacity benefits, costs, and reimbursements. The model was applied to three types of interventions in a large Dutch teaching hospital: 1) home telemonitoring for chronic patients (case (COPD), 2) remote aftercare for patients with acute illnesses (case: stroke), and 3) parenteral medication administration at home (case: prosthetic hip or knee joint infections).
Results
Output of the PCA model showed that the cost savings can exceed the intervention costs if an intervention decreases the length of stay of patients. For COPD telemonitoring 10.1 % of the healthcare utilization should be reduced to reach break-even, and for antibiotic treatment at home break-even is reached if 4.6 % of the length of stay is reduced. The cost savings of remote aftercare for stroke patients is focused on reducing outpatient visits, and in the current Dutch reimbursement system this does not completely cover the costs.
Conclusions
The PCA model is an easy to implement and useful tool for assessing the financial impact of CC interventions from a hospital perspective. It supports decision makers to prospectively assess the cost and capacity benefits of interventions and to inform decisions on implementation. Further studies are needed to extend the model across the entire healthcare continuum.
Public interest summary
We present a prospective cost analysis (PCA) model for estimating the financial impact of Connected Care interventions in hospitals to support managerial decision-making. Connected Care interventions are based on an integrated care approach utilizing digital health technologies to enhance patient-centred, collaborative care, where patients receive care at home. Examples are telemonitoring of chronic obstructive pulmonary disease (COPD) patients, remote aftercare for stroke patients and infusion treatment at home for orthopaedic patients with an infection. These interventions have additional costs, but also save part of the costs of the conventional care, and have benefits in terms of a decrease in outpatient visits or hospitalizations. We provide a model where a hospital can calculate the impact in costs and benefits of Connected Care interventions and test this on these three examples. We show that the cost savings are able to exceed the intervention costs if an intervention has impact on the hospitalization.
期刊介绍:
Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments.
HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology.
Topics covered by HPT will include:
- Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems
- Cross-national comparisons on health policy using evidence-based approaches
- National studies on health policy to determine the outcomes of technology-driven initiatives
- Cross-border eHealth including health tourism
- The digital divide in mobility, access and affordability of healthcare
- Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies
- Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies
- Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making
- Stakeholder engagement with health technologies (clinical and patient/citizen buy-in)
- Regulation and health economics