AI Article Synopsis

  • Electronic health care databases can enhance clinical decision-making and coordination in long-term care by linking information from various providers, though current methods for creating data-driven care delivery pathways (CDPs) need to address clinical, technological, and behavioral prerequisites more comprehensively.
  • A systematic review identified 14 studies about CDP methods, revealing that most focused on treatment decision-making and care coordination, with a standard process for technological development from initial definition to validation.
  • The review suggests the future development of common standards for integrating these methods, ensuring they meet interdisciplinary needs across the clinical, technological, and behavioral domains.

Article Abstract

Background: Electronic health care databases are increasingly used for informing clinical decision-making. In long-term care, linking and accessing information on health care delivered by different providers could improve coordination and health outcomes. Several methods for quantifying and visualizing this information into data-driven care delivery pathways (CDPs) have been proposed. To be integrated effectively and sustainably into routine care, these methods need to meet a range of prerequisites covering 3 broad domains: clinical, technological, and behavioral. Although advances have been made, development to date lacks a comprehensive interdisciplinary approach. As the field expands, it would benefit from developing common standards of development and reporting that integrate clinical, technological, and behavioral aspects.

Objective: We aimed to describe the content and development of long-term CDP quantification and visualization methods and to propose recommendations for future work.

Methods: We conducted a systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. We searched peer-reviewed publications in English and reported the CDP methods by using the following data in the included studies: long-term care data and extracted data on clinical information and aims, technological development and characteristics, and user behaviors. The data are summarized in tables and presented narratively.

Results: Of the 2921 records identified, 14 studies were included, of which 13 (93%) were descriptive reports and 1 (7%) was a validation study. Clinical aims focused primarily on treatment decision-making (n=6, 43%) and care coordination (n=7, 50%). Technological development followed a similar process from scope definition to tool validation, with various levels of detail in reporting. User behaviors (n=3, 21%) referred to accessing CDPs, planning care, adjusting treatment, or supporting adherence.

Conclusions: The use of electronic health care databases for quantifying and visualizing CDPs in long-term care is an emerging field. Detailed and standardized reporting of clinical and technological aspects is needed. Early consideration of how CDPs would be used, validated, and implemented in clinical practice would likely facilitate further development and adoption.

Trial Registration: PROSPERO CRD42019140494; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=140494.

International Registered Report Identifier (irrid): RR2-10.1136/bmjopen-2019-033573.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10755664PMC
http://dx.doi.org/10.2196/49996DOI Listing

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