Internet of things based patient-centered care model for elderly healthcare

Providing quality healthcare services to the rising elderly population is a significant challenge, as they often have multiple diseases (multimorbidity) and require proper treatment. Current healthcare systems lack effective care coordination for patients with multimorbidity, and result in increased hospital readmissions and costs. Researchers recommend adopting a Patient Centered Care (PCC) approach for effective care coordination among healthcare systems. However, current health IT solutions are inefficient for recording and sharing patient data as PCC requires. The Internet of things (IoT) has the potential to overcome these obstacles. loT is a network of interconnected computing devices that can collect and share data without human interference. However, the heterogeneous nature of loT devices causes data standardization and interoperability issues between loT devices and Health Information Technology systems (HITs). Moreover, there is a lack of studies that address the interoperability of IT systems for data collection and sharing, as PCC requires. Therefore, this study aims to develop an IoT based PCC model for elderly healthcare to address the issues related to the interoperability of loT and HITs for data collection and sharing. To achieve this objective, PCC and IoT elements suitable for elderly healthcare services have been identified using a qualitative approach. The empirical investigation has been done using face-to-face interviews with elderly healthcare and loT experts. The proposed model has been evaluated through expert review. This study has produced a novel model incorporating loT elements with PCC principles for elderly healthcare services to achieve interoperability of loT and HITs for care coordination. This model will provide useful insights and information for effective healthcare decisions and increase efficient resource utilization for elderly healthcare. Thus, it will enable the loT and HITs to interoperate, improving multimorbidity treatment and the effectiveness of healthcare coordination