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Quantification and visualisation methods of data-driven chronic care delivery pathways: protocol for a systematic review and content analysis
  1. Luiza Siqueira do Prado1,
  2. Samuel Allemann1,2,
  3. Marie Viprey1,3,
  4. Anne-Marie Schott1,3,
  5. Dan Dediu4,
  6. Alexandra L Dima1
  1. 1Health Services and Performance Research EA 7425, Université Claude Bernard Lyon 1, Lyon, France
  2. 2Pharmaceutical Care Research Group, University of Basel, Basel, Switzerland
  3. 3Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France
  4. 4Laboratoire Dynamique du Langage UMR 5596, Université Lumière Lyon 2, Lyon, France
  1. Correspondence to Luiza Siqueira do Prado; luiza.siqueira-do-prado{at}


Introduction Chronic conditions require long periods of care and often involve repeated interactions with multiple healthcare providers. Faced with increasing illness burden and costs, healthcare systems are currently working towards integrated care to streamline these interactions and improve efficiency. To support this, one promising resource is the information on routine care delivery stored in various electronic healthcare databases (EHD). In chronic conditions, care delivery pathways (CDPs) can be constructed by linking multiple data sources and extracting time-stamped healthcare utilisation events and other medical data related to individual or groups of patients over specific time periods; CDPs may provide insights into current practice and ways of improving it. Several methods have been proposed in recent years to quantify and visualise CDPs. We present the protocol for a systematic review aiming to describe the content and development of CDP methods, to derive common recommendations for CDP construction.

Methods and analysis This protocol followed the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols. A literature search will be performed in PubMed (MEDLINE), Scopus, IEEE, CINAHL and EMBASE, without date restrictions, to review published papers reporting data-driven chronic CDPs quantification and visualisation methods. We will describe them using several characteristics relevant for EHD use in long-term care, grouped into three domains: (1) clinical (what clinical information does the method use and how was it considered relevant?), (2) data science (what are the method’s development and implementation characteristics?) and (3) behavioural (which behaviours and interactions does the method aim to promote among users and how?). Data extraction will be performed via deductive content analysis using previously defined characteristics and accompanied by an inductive analysis to identify and code additional relevant features. Results will be presented in descriptive format and used to compare current CDPs and generate recommendations for future CDP development initiatives.

Ethics and dissemination Database searches will be initiated in May 2019. The review is expected to be completed by February 2020. Ethical approval is not required for this review. Results will be disseminated in peer-reviewed journals and conference presentations.

PROSPERO registration number CRD42019140494.

  • clinical decision support systems
  • medical informatics application
  • data visualisation
  • clinical pathway
  • delivery of health care, integrated
  • electronic healthcare databases

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  • Contributors LSP, ALD and SA designed the protocol and planned data extraction and quality assessment. LSP put together the search strategy and SA helped adapt it to the different databases. LSP and ALD conceived the content analysis stages and conceptual framework. LSP wrote the first version of the manuscript, ALD extensively reviewed it, SA, DD, A-MS and MV revised it critically for important intellectual content. All authors have approved the publication of this protocol and contributed to the final manuscript.

  • Funding DD was supported by an IDEXLYON (16-IDEX-0005) Fellowship grant (2018-2021), LSP was supported by a PhD funding within the same grant, ALD by a Marie Curie Individual Fellowship from the European Commission (MCRA-IF n°706028) during the preparation of this review protocol and SA by the Swiss Science Foundation (P2BSP3_ 178648).

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.