Literature DB >> 33456594

Oncology Information System: A Qualitative Study to Identify Cancer Patient Care Workflows.

Azadeh Yazdanian1.   

Abstract

Oncology information systems provide solutions for managing the information of cancer patients and enable monitoring of different aspects of cancer patient care. Since the use of oncology information systems enhances the quality of care, improves documentation, optimizes resource allocation, and increases the cost-effectiveness of care services, attention to these systems' performance and their adaptation to workflows seems necessary. The purpose of this study was to identify cancer patient care workflows to design an oncology information system for Iran. This study employed a qualitative design and was conducted in 2019. Semi-structured interviews were conducted with 25 experts to determine their views on identifying workflows for cancer patients' care. The participants were clinical and non-clinical staff at six university hospitals equipped with oncology wards. The method of data analysis was framework analysis. The cancer patient care workflows consisted of two categories, including cancer diagnosis workflows and cancer treatment workflows. Cancer diagnosis workflows fall into three subcategories, i.e., the patient's referral to the clinic, an examination of the patient's condition, and pathology workflows. On the other hand, cancer treatment workflows are divided into various treatments offered to cancer patients and workflows in the chemotherapy and radiotherapy wards. Given the variety of services and the complexity of caring for cancer patients as well as the involvement of various specialists in the process of care, identifying and optimizing workflows in the oncology information system reduces errors, enhances data accuracy, eliminates unnecessary steps, and ultimately improve the service delivery to cancer patients. ©Carol Davila University Press.

Entities:  

Keywords:  Neoplasm; hospital; oncology information system; qualitative study; workflows

Year:  2020        PMID: 33456594      PMCID: PMC7803303          DOI: 10.25122/jml-2019-0169

Source DB:  PubMed          Journal:  J Med Life        ISSN: 1844-122X


  8 in total

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2.  Five-year experience with setup and implementation of an integrated database system for clinical documentation and research.

Authors:  Kerstin A Kessel; Christian Bohn; Uwe Engelmann; Dieter Oetzel; Nina Bougatf; Rolf Bendl; Jürgen Debus; Stephanie E Combs
Journal:  Comput Methods Programs Biomed       Date:  2014-02-18       Impact factor: 5.428

3.  Implementing a regional oncology information system: approach and lessons learned.

Authors:  W K Evans; F D Ashbury; G L Hogue; A Smith; J Pun
Journal:  Curr Oncol       Date:  2014-10       Impact factor: 3.677

4.  Improving chemotherapy processes with a protocol-based information system: a pre and post-implementation study.

Authors:  Habibollah Pirnejad; Chen Gao; Roel Reddingius; Anita Rijneveld; Roland Bal
Journal:  Int J Med Inform       Date:  2013-01-05       Impact factor: 4.046

5.  Analysis and classification of oncology activities on the way to workflow based single source documentation in clinical information systems.

Authors:  Stefan Wagner; Matthias W Beckmann; Bernd Wullich; Christof Seggewies; Markus Ries; Thomas Bürkle; Hans-Ulrich Prokosch
Journal:  BMC Med Inform Decis Mak       Date:  2015-12-22       Impact factor: 2.796

Review 6.  Functional imaging for radiotherapy treatment planning: current status and future directions-a review.

Authors:  D Thorwarth
Journal:  Br J Radiol       Date:  2015-04-01       Impact factor: 3.039

7.  Patient and work flow and costs associated with staff time and facility usage at a comprehensive cancer centre in Quebec, Canada--a time and motion study.

Authors:  Gayle A Shinder; Pierre Emmanuel Paradis; Marianne Posman; Natalia Mishagina; Marie-Pascale Guay; Dina Linardos; Gerald Batist
Journal:  BMC Health Serv Res       Date:  2012-10-29       Impact factor: 2.655

8.  Workflow-driven clinical decision support for personalized oncology.

Authors:  Anca Bucur; Jasper van Leeuwen; Nikolaos Christodoulou; Kamana Sigdel; Katerina Argyri; Lefteris Koumakis; Norbert Graf; Georgios Stamatakos
Journal:  BMC Med Inform Decis Mak       Date:  2016-07-21       Impact factor: 2.796

  8 in total

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