Toward an Interdisciplinary Approach to Constructing Care Delivery Pathways From Electronic Health Care Databases to Support Integrated Care in Chronic Conditions: Systematic Review of Quantification and Visualization Methods

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.

Keywords: data visualization; electronic health care databases; long-term care; patient pathway; systematic review.

Figure 1

Definition of quantification and visualization methods of data-driven long-term care delivery pathways (CDPs) and illustration of a hypothetical example of a patient: In the time window selected for CDP construction, several health care use events occurred, including primary care visits, medication prescribing and dispensing, and hospitalization, and were recorded in 3 separate databases. For informing decisions in clinical encounters or at the organizational or policy level, this information needs to be extracted, linked across data sources, prepared for analysis, and results displayed in a user interface available in the intended situations. EHD: electronic health care database.

Figure 2

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart describing the identification and screening of records and selection of included studies.

Figure 3

Key points to developing new data-driven care delivery pathway visualization and quantification methods.