955
Views
5
CrossRef citations to date
0
Altmetric
Research Papers

Preferences regarding the way of use and design of a work ability prognosis support tool: a focus group study among professionals

, , , , &
Pages 2031-2037 | Received 18 Dec 2018, Accepted 12 Nov 2019, Published online: 26 Nov 2019

References

  • De Boer WEL, Besseling JJM, Willems JHBM. Organisation of disability evaluation in 15 countries. Prat Organ Soins. 2007;3(38):205–217.
  • Anner J, Kunz R, de Boer W. Reporting about disability evaluation in European countries. Disabil Rehabil. 2014;36(10):848–854.
  • Louwerse I, Huysmans MA, van Rijssen HJ, et al. Characteristics of individuals receiving disability benefits in the Netherlands and predictors of leaving the disability benefit scheme: a retrospective cohort study with five-year follow-up. BMC Public Health. 2018;18(1):157.
  • Wise DA. Social security programs and retirement around the world: Historical trends in mortality and health, employment, and disability insurance participation and reforms. Chicago: University of Chicago Press; 2012.
  • OECD. Sickness, disability and work: breaking the barriers: a synthesis of findings across OECD countries. Paris: OECD Publishing; 2010.
  • Waddell G, Burton AK. Is work good for your health and well-being? London: The Stationery Office; 2006.
  • Kok R, Verbeek JAHM, Faber B, et al. A search strategy to identify studies on the prognosis of work disability: a diagnostic test framework. BMJ Open. 2015;5(5):e006315.
  • Louwerse I, Huysmans MA, van Rijssen JH, et al. Predicting future changes in work ability of individuals receiving a work disability benefit: weighted analysis of longitudinal data. Scand J Work Environ Health. 2019. DOI:10.5271/sjweh.3834
  • Sim I, Gorman P, Greenes RA, et al. Clinical decision support systems for the practice of evidence-based medicine. J Am Med Inform Assoc. 2001;8(6):527–534.
  • Roshanov PS, Fernandes N, Wilczynski JM, et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ. 2013;346(feb14 1):f657.
  • Bates DW, Kuperman GJ, Wang S, et al. Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J Am Med Inform Assoc. 2003;10(6):523–530.
  • Bates DW, Cohen M, Leape LL, et al. Reducing the frequency of errors in medicine using information technology. J Am Med Inform Assoc. 2001;8(4):299–308.
  • Ahlstrom L, Grimby-Ekman A, Hagberg M, et al. The work ability index and single-item question: associations with sick leave, symptoms, and health – a prospective study of women on long-term sick leave. Scand J Work Environ Health. 2010;36(5):404–412.
  • Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.
  • Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–357.
  • Hsieh H-F, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–1288.
  • Boeije H. Analysis in qualitative research. London: Sage publications; 2009.
  • van Muijen P, Duijts SFA, Kornet-van der Aa DA, et al. Work disability assessment of cancer survivors: insurance physicians’ perspectives. OCCMED. 2015;65(7):558–563.
  • Kawamoto K, Houlihan CA, Balas EA, et al. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ. 2005;330(7494):765.
  • Lee F, Teich JM, Spurr CD, et al. Implementation of physician order entry: user satisfaction and self-reported usage patterns. J Am Med Inform Assoc. 1996;3(1):42–55.
  • Shojania KG, Yokoe D, Platt R, et al. Reducing vancomycin use utilizing a computer guideline: results of a randomized controlled trial. J Am Med Inform Assoc. 1998;5(6):554–562.
  • Reyna VF, Brainerd CJ. The importance of mathematics in health and human judgment: numeracy, risk communication, and medical decision making. Learn Individ Differ. 2007;17(2):147–159.
  • Maviglia SM, Zielstorff RD, Paterno M, et al. Automating complex guidelines for chronic disease: lessons learned. J Am Med Inform Assoc. 2003;10(2):154–165.
  • Lipkus IM, Samsa G, Rimer BK. General performance on a numeracy scale among highly educated samples. Med Decis Making. 2001;21(1):37–44.
  • Gigerenzer G, Gaissmaier W, Kurz-Milcke E, et al. Helping doctors and patients make sense of health statistics. Psychol Sci Public Interest. 2007;8(2):53–96.
  • Waters EA, McQueen A, Cameron LD. Perceived risk and health risk communication. In: Heidi E. Hamilton, Wen-ying Sylvia Chou, editors. The Routledge handbook of language and health communication. New York; London: Routledge; 2014. p. 47–60.
  • Trevena LJ, Zikmund-Fisher BJ, Edwards A, et al. Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers. BMC Med Inform Decis Mak. 2013;13(S2):S7.
  • Garg AX, Adhikari NKJ, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293(10):1223–1238.