Computer Supported Cooperative Work (CSCW)

, Volume 20, Issue 3, pp 123–153 | Cite as

Layers in Sorting Practices: Sorting out Patients with Potential Cancer

Article

Abstract

In the last couple of years, widespread use of standardized cancer pathways has been seen across a range of countries, including Denmark, to improve prognosis of cancer patients. In Denmark, standardized cancer pathways take the form of guidelines prescribing well-defined sequences where steps are planned and pre-booked in order to manage patient trajectories. They are different from typical medical guidelines because they combine both administrative and clinical prescriptions. A key issue related to the enactment of a standardized cancer pathway concerns the decision to initiate a pathway for a particular patient. Due to the limited resources within the Danish healthcare system, initiating cancer pathways for all patients with a remote suspicion of cancer would crash the system, as it would be impossible for healthcare professionals to commit to the prescribed schedules and times defined by the standardized pathways. Thus, sorting patients with symptoms of potential cancer becomes an essential activity. In this paper, we investigate the pre-diagnostic work of sorting patients with symptoms that may potentially be cancer. We identify and conceptualize the sorting practices for potential cancer patients in the pre-diagnostic work as being structured in layers of the interrelated, iterative practices of constructing, organizing, re-organizing, and merging the multiple queues within which each patient is simultaneously situated. We find that the ordering of patients in queues is guided by the formal sorting mechanism, but is handled by informal sorting mechanisms. We identify two informal sorting mechanisms with large impact on the sorting practices, namely subtle categorizing and collective remembering. These informal sorting mechanisms have implications for the design of electronic booking systems because they show that sorting patients before initiating a standardized cancer pathway is not a simple process of deciding on a predefined category that will stipulate particular dates and times. Instead, these informal sorting mechanisms show that the process of sorting patients prior to diagnosis is a collaborative process of merging multiple queues while continuously deciding whether or not a patient’s symptoms point to potential cancer.

Key words

pre-diagnostic work cancer sorting collaboration 

References

  1. Alby, F., & Zucchermaglio, C. (2009). Time, narratives and participation frameworks in software troubleshooting. Computer Supported Cooperative Work, 18, 129–146.CrossRefGoogle Scholar
  2. Bannon, L. J., & Kuutti, K. (1996). Shifting perspectives on organizational memory: From storage to active remembering. HICSS 1996: Proceedings of the 29th Annual Hawaii International Conference on System Sciences (pp. 156–167).Google Scholar
  3. Bates, D. (2002). The quality case for information technology in healthcare. BMC Medical Informatics and Decision Making, 2(7), 1–9.MathSciNetGoogle Scholar
  4. Berg, M. (1997). Rationalizing medical work: Decision-support techniques and medical practices. Cambridge: MIT.Google Scholar
  5. Bjerager, M., Palshof, T., Dahl, R., & Olesen, F. (2006). Praktiserende Lægers Holdninger til Udredning af Lungecancer og Organiseringen af Udredningen [General practitioners opinions on diagnostics of lung cancer and organization of diagnostics]. Ugeskrift for Laeger, 168(14), 1443–1448.Google Scholar
  6. Bjørn, P., & Balka, E. (2007). Health care categories have politics too: Unpacking the managerial agendas of electronic triage systems. ECSCW 2007: Proceedings of the Tenth European Conference on Computer Supported Cooperative Work (pp. 371–390). Limerick, Ireland, September 24–28.Google Scholar
  7. Bjørn, P., & Rødje, K. (2008). Triage drift: a workplace study in a pediatric emergency department. Computer Supported Cooperative Work, 17(4), 395–419.CrossRefGoogle Scholar
  8. Blaxter, M. (1978). Diagnosis as category and process: the case of alcoholism. Social Science & Medicine, 12, 9–17.Google Scholar
  9. Bowker, G. C., & Star, S. L. (2000). Sorting things out: Classification and its consequences. Cambridge: MIT.Google Scholar
  10. Büscher, M., O’Neil, J., & Rooksby, J. (2009). Designing for diagnosing: introduction to the special issue on diagnostic work. Computer Supported Cooperative Work, 18, 109–128.CrossRefGoogle Scholar
  11. Forsythe, D. (1999). “It’s just a matter of common sense”: ethnography as invisible work. Computer Supported Cooperative Work, 8, 127–145.CrossRefGoogle Scholar
  12. Gerson, E. M., & Star, S. L. (1986). Analyzing due process in the workplace. ACM Transactions on Office Information Systems, 4(3), 257–270.CrossRefGoogle Scholar
  13. Hartswood, M., Procter, R., Rouncefield, M., et al. (2003). ‘Repairing’ the machine: A case study of the evaluation of computer-aided detection tools in breast screening. Proceedings of ECSCW 2003 the Eighth European Conference on Computer Supported Cooperative Work (pp. 375–394). Helsinki, Finland.Google Scholar
  14. Jensen, A. R., Mainz, J., & Overgaard, J. (2002). Impact of delay on diagnosis and treatment of primary lung cancer. Acta Oncológica, 41(2), 147–152.CrossRefGoogle Scholar
  15. Jutel, A. (2009). Sociology of diagnosis: a preliminary review. Sociology of Health & Illness, 31(2), 278–299.CrossRefGoogle Scholar
  16. Kane, B., & Luz, S. (2009). Achieving diagnosis by consensus. Computer Supported Cooperative Work, 18, 357–392.CrossRefGoogle Scholar
  17. Klein, H., & Myers, M. (1999). A set of principles for conducting and evaluating interpretive field studies in information systems. MIS Quarterly, 23(1), 67–93.CrossRefGoogle Scholar
  18. Luff, P., Hindmarch, J., & Heath, C. (2000). Workplace studies: Recovering work practice and informing system design. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  19. Martin, D., O’Neill, J., Randall, D., & Rouncefield, M. (2007). How Can I Help You? Call centres, classification work and coordination. Computer Supported Cooperative Work, 16, 231–264.CrossRefGoogle Scholar
  20. Mesman, J. (2010). Diagnostic work in collaborative practices in neonatal care. In M. Büscher, D. Goodwin, & J. Mesman (Eds.), Ethnographies of diagnostic work: Dimensions of transformative practice (pp. 95–112). London: Palgrave Macmillian.Google Scholar
  21. Mol, A., & Elsman, M. (1996). Detecting disease and designing treatment. Duplex and the diagnosis of diseased leg vessels. Sociology of Health & Illness, 18(5), 609–631.CrossRefGoogle Scholar
  22. Nevile, M. (2009). You are well clear of friendlies: diagnostic error and cooperative work in an Iraq war friendly fire incident. Computer Supported Cooperative Work, 18, 147–173.CrossRefGoogle Scholar
  23. Orr, J. E. (1986). Narratives at work: Story telling as cooperative diagnostic activity. Proceedings of the 1986 ACM conference on Computer Supported Cooperative Work (pp. 62–72). Austin, Texas.Google Scholar
  24. Paoletti, I. (2009). Communication and diagnostic work in medical emergency calls in Italy. Computer Supported Cooperative Work, 18, 229–250.CrossRefGoogle Scholar
  25. Raghupathi, W. (1997). Health care information systems. Communications of the ACM, 40(8), 80–82.CrossRefGoogle Scholar
  26. Randall, D., Harper, R., & Rouncefield, M. (2007a). Fieldwork for design: Theory and practice. London: Springer.CrossRefGoogle Scholar
  27. Randall, D., Sharrock, W., Lin, Y., Procter, R., & Rooksby, J. (2007b). Ontology building as practical work: Lessons from CSCW. 3rd International Conference on e-Social Science 2007. Michigan, USA.Google Scholar
  28. Ryan, M., McIntosh, E., Dean, T., & Old, P. (2000). Trade-offs between location and waiting times in the provision of health care: the case of elective surgery on the Isle of Wight. Journal of Public Health Medicine, 22(2), 202–210.CrossRefGoogle Scholar
  29. Schmidt, K. (1997). Of maps and scripts. The status of formal constructs in cooperative work. Group’97 ACM Conference on Supporting Group Work (pp. 138–147). Arizona, USA.Google Scholar
  30. Schmidt, K., & Bannon, L. (1992). Taking CSCW seriously: supporting articulation work. Computer Supported Cooperative Work, 1(1–2), 7–40.CrossRefGoogle Scholar
  31. Schmidt, K., & Wagner, I. (2004). Ordering systems: coordinative practices and artifacts in architectural design and planning. Computer Supported Cooperative Work, 13, 349–408.CrossRefGoogle Scholar
  32. Siciliani, L., & Hurst, J. (2004). Explaining waiting-time variations for elective surgery across OECD countries. OECD Economic Studies, 38, 1–73.Google Scholar
  33. Star, S. L., & Strauss, A. (1999). Layers of Silence, arenas of voice: the ecology of visible and invisible work. Computer Supported Cooperative Work, 8, 9–30.CrossRefGoogle Scholar
  34. Strauss, A. L., Fagerhaugh, S., Suczek, B., & Wiener, C. (1985). Social organization of medical work. Chicago and London: The University of Chicago Press.Google Scholar
  35. Suchman, L. A. (2007). Human-machine reconfigurations. Plans and situated actions. Cambridge University Press.Google Scholar
  36. Sundhedsstyrelsen (2005). Kræft i Danmark. Et Opdateret Billede af Forekomst, Dødelighed og Overlevelse [Cancer in Denmark. An updated picture of incidence, mortality and survival] (pp. 1–100). Sundhedsstyrelsen [The Danish National Board of Health].Google Scholar
  37. Sundhedsstyrelsen (2008a). Akut Handling og Klar Besked: Generelle Rammer for Indførelse af Pakkeforløb for Kræftpatienter [Acute action and clear message: General framework for the introduction of packages for cancer patients] (pp. 1–6). Sundhedsstyrelsen [The Danish National Board of Health].Google Scholar
  38. Sundhedsstyrelsen (2008b). Udkast. Generelle Retningslinjer for Henvisning fra Almen Praksis af Patienter med Mulig Cancerdiagnose [Work memo in progress. General guidelines for referral from general practise of patients with a possible cancer diagnose] (pp. 1–4). Sundhedsstyrelsen [The Danish National Board of Health].Google Scholar
  39. Sundhedsstyrelsen (2009a). Pakkeforløb for Lungekræft [Package pathway for lung cancer] (pp. 1–35). Sundhedsstyrelsen [The Danish National Board of Health].Google Scholar
  40. Sundhedsstyrelsen (2009b). Pakkeforløb for Kræft i Spiserøret, Mavemunden og Mavesækken [Package pathway for cancer in oesophagus, cardia abdomen and abdomen] (pp. 1–38). Sundhedsstyrelsen [The Danish National Board of Health].Google Scholar
  41. Sundhedsstyrelsen (2009c). Pakkeforløb for Kræft i Bugspytkirtlen [Package pathways for pancreatic cancer] (pp. 1–34). Sundhedsstyrelsen [The Danish National Board of Health].Google Scholar
  42. Sundhedsstyrelsen (2009d). Pakkeforløb for Brystkræft [Package pathway for breast cancer] (pp. 1–35). Sundhedsstyrelsen [The National Board of Health].Google Scholar
  43. Tjora, A. (2000). The technological mediation of the nursing-medical boundary. Sociology of Health & Illness, 22(6), 721–741.CrossRefGoogle Scholar
  44. Vedsted, P., Larsen, M. B., Tørring, M. L., Andersen, R. S., Bro, F., Hansen, R. P., et al. (2008). Fra Symptom til Behandling. Viden og Strategier for Optimeret Udredning af Kræftsygdom [From symptom to treatment. Knowledge and strategies for optimized diagnostics of cancer disease]. Forskningsenheden for Almen Praksis [The Research Department for General Practice].Google Scholar
  45. Watts-Perotti, J., & Woods, D. D. (2009). Cooperative advocacy: an approach for integrating diverse perspectives in anomaly response. Computer Supported Cooperative Work, 18, 175–198.CrossRefGoogle Scholar
  46. Wennberg, J. (1984). Dealing with medical practice variations: a proposal for action. Health Affairs, 3(2), 6–32.CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer 2011

Authors and Affiliations

  1. 1.IT University of CopenhagenCopenhagenDenmark

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