ObjectivesTo 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. MethodsInput 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). ResultsOutput 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. ConclusionsThe 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 summaryWe 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.
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