Appl Clin Inform 2012; 03(01): 1-13
DOI: 10.4338/ACI-2011-08-CR-0053
Case Report
Schattauer GmbH

Capturing Information Needs of Care Providers to Support Knowledge Sharing and Distributed Decision Making

M. Rogers
1   Drexel University, Philadelphia
,
L. Zach
1   Drexel University, Philadelphia
,
Y. An
1   Drexel University, Philadelphia
,
P. Dalrymple
1   Drexel University, Philadelphia
› Author Affiliations
Further Information

Correspondence to:

Michelle Rogers, PhD
Drexel University
3141 Chestnut Street
Philadelphia, PA 19104

Publication History

received: 31 August 2011

accepted: 12 January 2011

Publication Date:
16 December 2017 (online)

 

Summary

Background: This paper reports on work carried out to elicit information needs at a trans-disciplinary, nurse-managed health care clinic that serves a medically disadvantaged urban population. The trans-disciplinary model provides a “one-stop shop” for patients who can receive a wide range of services beyond traditional primary care. However, this model of health care presents knowledge sharing challenges because little is known about how data collected from the non-traditional services can be integrated into the traditional electronic medical record (EMR) and shared with other care providers. There is also little known about how health information technology (HIT) can be used to support the workflow in such a practice.

Objectives: The objective of this case study was to identify the information needs of care providers in order to inform the design of HIT to support knowledge sharing and distributed decision making.

Methods: A participatory design approach is presented as a successful technique to specify requirements for HIT applications that can support a trans-disciplinary model of care.

Results: Using this design approach, the researchers identified the information needs of care providers working at the clinic and suggested HIT improvements to integrate non-traditional information into the EMR. These modifications allow knowledge sharing among care providers and support better health decisions.

Conclusions: We have identified information needs of care providers as they are relevant to the design of health information systems. As new technology is designed and integrated into various workflows it is clear that understanding information needs is crucial to acceptance of that technology.


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Competing Interest

The authors do not declare any conflicts of interest.

  • References

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  • 2 Berger RG, Kichak JP. Computerized physician order entry: Helpful or harmful?. Journal of the American Medical Informatics Association 2004; 11: 100-103.
  • 3 Yarbrough AK, Smith TB. Technology acceptance among physicians. Medical Care Research and Review 2007; 64: 650-672.
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  • 9 Wong FKY, Chung LCY. Establishing a definition for a nurse-led clinic: structure, process and outcome. Journal of Advanced Nursing 2006; 53 (03) 358-369.
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  • 11 Jerant AF, Hill DB. Does the use of electronic medical records improve surrogate patient outcomes in out-patient settings?. The Journal of Family Practice 2000; 49 (04) 349-357.
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  • 34 Liu L, Yu E. Designing information systems in social context: A goal and scenario modelling approach. Information Systems 2004; 29 (02) 187-203.
  • 35 Elahi G, Yu E. A goal oriented approach for modeling and analyzing security trade-offs. Proc. 26th International Conference on Conceptual Modeling 2007: 375-390.
  • 36 Pfleeger SL, Atlee J. Software engineering: Theory and practice. New York.: Pearson Prentice Hall.,; 2005
  • 37 Jackson M. The meaning of requirements. Annals of Software Engineering 1997; 3: 5-21.
  • 38 Yu ESK, Liu L. Modelling trust for system design using the i* strategic actors framework. In the Proceedings of the workshop on Deception, Fraud, and Trust in Agent Societies held during the Autonomous Agents Conference: 2001: 175-194.
  • 39 An Y. et al. Collaborative social modeling for designing a patient wellness tracking system in a nurse-managed health care center. In the Proceedings of 4th International Conference on Design Science Research in Information Systems and Technology (DESRIST‘09), 2009

Correspondence to:

Michelle Rogers, PhD
Drexel University
3141 Chestnut Street
Philadelphia, PA 19104

  • References

  • 1 Bates DW. Physicians and ambulatory electronic health records. Health Affairs 2005; 24 (05) 1180-1189.
  • 2 Berger RG, Kichak JP. Computerized physician order entry: Helpful or harmful?. Journal of the American Medical Informatics Association 2004; 11: 100-103.
  • 3 Yarbrough AK, Smith TB. Technology acceptance among physicians. Medical Care Research and Review 2007; 64: 650-672.
  • 4 Karsh B-T. Beyond usability: designing effective technology implementation systems to promote patient safety. Quality & safety in health care 2004; 13 (05) 388-394.
  • 5 Chan W. Increasing the success of physician order entry through human factors engineering. Journal of Heathcare Information Management 2002; 16 (01) 71-79.
  • 6 Harrison MI, Koppel R, Bar-Lev S. Unintended consequences of information technologies in health care –an interactive sociotechnical analysis. Journal of the American Medical Informatics Association 2007; 14 (05) 542-549.
  • 7 Bates DW. Using information technology to reduce rates of medication errors in hospitals. BMJ 2000; 320: 788-791.
  • 8 Cogdill KW. et al. Information needs and information seeking in community medical education. Academic Medicine 2000; 75 (05) 484-486.
  • 9 Wong FKY, Chung LCY. Establishing a definition for a nurse-led clinic: structure, process and outcome. Journal of Advanced Nursing 2006; 53 (03) 358-369.
  • 10 Ash JS. et al. Categorizing the unintended sociotechnical consequences of computerized provider order entry. International Journal of Medical Informatics 2007; 76 (Suppl. 01) S21-S27.
  • 11 Jerant AF, Hill DB. Does the use of electronic medical records improve surrogate patient outcomes in out-patient settings?. The Journal of Family Practice 2000; 49 (04) 349-357.
  • 12 Amarasingham R. et al. Clinical information technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med 2009; 169 (02) 108-114.
  • 13 Chaudhry B. et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med 2006; 144: 742-752.
  • 14 Hillestad R. et al. Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. Health Affairs 2005; 24: 1103-1117.
  • 15 Rosenfield PL. The potential of transdisciplinary research for sustaining and extending linkages between the health and social sciences. Social Science & Medicine 1992; 35 (11) 1343-1357.
  • 16 Grey M, Connolly CA. Coming together, keeping together, working together: Interdisciplinary to transdisciplinary research and nursing. Nursing Outlook 2008; 56 (03) 102-107.
  • 17 Mitchell PH. What’s In A Name?: Multidisciplinary, interdisciplinary, and transdisciplinary. Journal of Professional Nursing 2005; 21 (06) 332-334.
  • 18 Gorman PN. Information needs of physicians. Journal of the American Society for Information Science 1995; 46 (10) 729-736.
  • 19 Reddy M, Dourish P. A finger on the pulse: Temporal rhythms and information seeking in medical care. In: Proceedings of ACM Conference on Computer Supported Cooperative Work CSCW’02, ACM,. New York,: 2002: 344-353.
  • 20 Xu X. et al. Understanding nurses’ information needs and searching behavior in acute care settings. AMIA Annu Symp Proc 2005: 839-843.
  • 21 Darbyshire P. Rage against the machine? Nurses’ and midwives’ experiences of using computerized patient information systems for clinical information. Journal of Clinical Nursing 2004; 13 (01) 17-25.
  • 22 Randell R. et al. Supporting nurse decision making in primary care: Exploring use of and attitude to decision tools. Health Informatics Journal 2009; 15 (01) 5.
  • 23 Poissant L. et al. The impact of electronic health records on time efficiency of physicians and nurses: A systematic review. Journal of the American Medical Informatics Association 2005; 12 (05) 505-516.
  • 24 Lee T. Nursing information: users’ experiences of a system in Taiwan one year after its implementation. Journal of Clinical Nursing 2008; 17 (06) 763-771.
  • 25 Ziegler J. Inching toward and info technology revolution. Business and Health 1999; 17 (06) 51-55.
  • 26 Gugerty B, Wooldridge P, Brennan M. The CISQ: A tool to measure staff involvement in and attitudes toward the implementation of a clinical information system. In: Proceedings of the American Medical Informatics Association;. Los Angeles November 3–7, 2000
  • 27 Patterson ES, Roth EM, Render ML. Handoffs during nursing shift changes in acute care. Proceedings of the Human Factors and Ergonomics Society 49th Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society; 2005
  • 28 Orzano AJ. et al. Family medicine practice performance and knowledge management. Health Care Management Review 2008; 33 (01) 21.
  • 29 Irestig M, Eriksson H, Timpka T. The impact of participation in information system design: A comparison of contextual placements. Proceedings of the Eighth Conference on Participatory Design: Artful Integration: Interweaving Media, Materials and Practices, New York:: ACM Press; 2004: 102-111.
  • 30 Shneiderman B. Designing the user interface: Strategies for effective human-computer interaction. 3rd edn. Reading, MA: Addison-Wesley; 1998
  • 31 Sjoberg C, Timpka T. Participatory design of information systems in health care. Journal of the American Medical Informatics Association 1998; 5 (02) 177-183.
  • 32 Weng C. et al. Participatory design of a collaborative clinical trial protocol writing system. International Journal of Medical Informatics 2007; 76 (Suppl. 01) S245-S251.
  • 33 van Lamsweerde A. Goal-oriented requirements engineering: A guided tour. In: Proceedings of 5th IEEE International Symposium on Requirements Engineering,. 2001
  • 34 Liu L, Yu E. Designing information systems in social context: A goal and scenario modelling approach. Information Systems 2004; 29 (02) 187-203.
  • 35 Elahi G, Yu E. A goal oriented approach for modeling and analyzing security trade-offs. Proc. 26th International Conference on Conceptual Modeling 2007: 375-390.
  • 36 Pfleeger SL, Atlee J. Software engineering: Theory and practice. New York.: Pearson Prentice Hall.,; 2005
  • 37 Jackson M. The meaning of requirements. Annals of Software Engineering 1997; 3: 5-21.
  • 38 Yu ESK, Liu L. Modelling trust for system design using the i* strategic actors framework. In the Proceedings of the workshop on Deception, Fraud, and Trust in Agent Societies held during the Autonomous Agents Conference: 2001: 175-194.
  • 39 An Y. et al. Collaborative social modeling for designing a patient wellness tracking system in a nurse-managed health care center. In the Proceedings of 4th International Conference on Design Science Research in Information Systems and Technology (DESRIST‘09), 2009