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1.
JAMIA Open ; 6(3): ooad074, 2023 Oct.
Article in English | MEDLINE | ID: mdl-37649989

ABSTRACT

Objective: Patient-reported outcome measures (PROMs) are critical to drive patient-centered care and to understanding patients' perspectives on their health status, quality of life, and the overall effectiveness of the care they receive. PROMs are increasingly being used in clinical and research settings, but the mechanisms to aggregate data from different systems can be cumbersome. Materials and methods: As part of an FDA Real-World Evidence demonstration project, we enriched routine care clinical data from our Cerner electronic health record (EHR) with PROMs collected using REDCap. We used SSIS, sFTP, and the REDCap Application Programming Interface to aggregate both data sources into the Cerner HealtheIntent Population Health Platform. Results: We successfully built dashboards, reports, and datasets containing both REDCap and EHR data collected prospectively. Discussion: This technically straightforward approach using commonly available clinical and research tools can be readily adopted and adapted by others to better integrate PROMs with clinical data sources.

3.
Article in English | MEDLINE | ID: mdl-36992736

ABSTRACT

Diabetes is a uniquely quantifiable disease, and as technology and data have proliferated over the past two decades, so have the tools to manage diabetes. Patients and providers have at their disposal devices, applications, and data platforms that generate immense amounts of data, provide critical insights into a patient's disease, and allow for personalization of treatment plans. However, the proliferation of options also comes with new burdens for providers: selecting the right tool, getting buy-in from leadership, defining the business case, implementation, and maintenance of the new technology. The complexity of these steps can be overwhelming and sometimes lead to inaction, depriving providers and patients of the advantages of technology-assisted diabetes care. Conceptually, the adoption of digital health solutions can be thought of as occurring in five interconnected phases: Needs Assessment, Solution Identification, Integration, Implementation, and Evaluation. There are a number of existing frameworks to help guide much of this process, but relatively little attention has been focused on integration. Integration is a critical phase for a number of contractual, compliance, financial, and technical processes. Missing a step or doing them out of order can lead to significant delays and potentially wasted resources. To address this gap, we have developed a practical, simplified framework for integrating diabetes data and technology solutions that can guide clinicians and clinical leaders on the critical steps in adopting and implementing a new technology.

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