Appl Clin Inform 2010; 01(04): 466-485
DOI: 10.4338/ACI-2010-05-RA-0029
Research Article
Schattauer GmbH

Impact of Clinical Reminder Redesign on Physicians’ Priority Decisions

Sze-jung Wu
1   School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
,
Mark R. Lehto
1   School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
,
Yuehwern Yih
1   School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
,
Jason J. Saleem
2   VA HSR&D Center on Implementing Evidence-based Practice, Roudebush VAMC, Indianapolis, IN 46202, USA
3   School of Engineering & Technology, IUPUI, Indianapolis, IN 46202, USA
4   IU Center for Health Services & Outcomes Research, Regenstrief Institute, Indianapolis, IN 46202, USA
,
B.N. Doebbeling
2   VA HSR&D Center on Implementing Evidence-based Practice, Roudebush VAMC, Indianapolis, IN 46202, USA
4   IU Center for Health Services & Outcomes Research, Regenstrief Institute, Indianapolis, IN 46202, USA
5   Department of Medicine, IU School of Medicine, Indianapolis, IN 46202, USA
› Author Affiliations
Further Information

Correspondence to:

Yuehwern Yih, Ph.D.
School of Industrial Engineering
Purdue University
315 N. Grant Street
West Lafayette, IN 47907
Phone: (765) 494-0826   
Fax: (765) 494-1212   

Publication History

received: 05 May 2010

accepted: 10 December 2010

Publication Date:
16 December 2017 (online)

 

Summary

Objective: Computerized clinical reminder (CCR) systems can improve preventive service delivery by providing patient-specific reminders at the point of care. However, adherence varies between individual CCRs and is correlated to resolution time amongst other factors. This study aimed to evaluate how a proposed CCR redesign providing information explaining why the CCRs occurred would impact providers’ prioritization of individual CCRs.

Design: Two CCR designs were prototyped to represent the original and the new design, respectively. The new CCR design incorporated a knowledge-based risk factor repository, a prioritization mechanism, and a role-based filter. Sixteen physicians participated in a controlled experiment to compare the use of the original and the new CCR systems. The subjects individually simulated a scenario-based patient encounter, followed by a semi-structured interview and survey.

Measurements: We collected and analyzed the order in which the CCRs were prioritized, the perceived usefulness of each design feature, and semi-structured interview data.

Results: We elicited the prioritization heuristics used by the physicians, and found a CCR system needed to be relevant, easy to resolve, and integrated with workflow. The redesign impacted 80% of physicians and 44% of prioritization decisions. Decisions were no longer correlated to resolution time given the new design. The proposed design features were rated useful or very useful.

Conclusion: This study demonstrated that the redesign of a CCR system using a knowledge-based risk factor repository, a prioritization mechanism, and a role-based filter can impact clinicians’ decision making. These features are expected to ultimately improve the quality of care and patient safety.


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Conflict of interest Statement

The authors declare no conflict of interest in the study.

  • References

  • 1 Doebbeling BN, Vaughn TE, McCoy KD, Glassman P. Informatics implementation in the Veterans Health Administration (VHA) healthcare system to improve quality of care. AMIA Annu Symp Proc 2006: 204-208.
  • 2 Balas EA, Li ZR, Spencer DC, Jaffrey F, Brent E, Mitchell JA. An expert system for performance-based direct delivery of published clinical evidence. Journal of the American Medical Informatics Association 1996; 3 (01) 56-65.
  • 3 Cannon DS, Allen SN. A comparison of the effects of computer and manual reminders on compliance with a mental health clinical practice guideline. Journal of the American Medical Informatics Association 2000; 7 (02) 196-203.
  • 4 Hasman A, Safran C, Takeda H. Quality of health care: informatics foundations. Methods Inf Med 2003; 42 (05) 509-518.
  • 5 Eslami S, Abu-Hanna A, de Keizer NF. Evaluation of outpatient computerized physician medication order entry systems: a systematic review. J Am Med Inform Assoc 2007; 14 (04) 400-406.
  • 6 Vashitz G, Meyer J, Parmet Y, Peleg R, Goldfarb D, Porath A. et al. Defining and measuring physicians’ responses to clinical reminders. J Biomed Inform 2009; 42 (02) 317-326.
  • 7 Dexter PR, Perkins S, Overhage JM, Maharry K, Kohler RB, McDonald CJ. A computerized reminder system to increase the use of preventive care for hospitalized patients. New England Journal of Medicine. 2001; 345 (13) 965-970.
  • 8 Ornstein SM, Garr DR, Jenkins RG, Rust PF, Arnon A. Computer-generated physician and patient reminders - tools to improve population adherence to selected preventive services. Journal of Family Practice. 1991; 32 (01) 82-90.
  • 9 RAND Corporation.. A systematic review of the literature on interventions to increase the use of clinical preventive services under Medicare. 1999
  • 10 Sintchenko V, Coiera E, Iredell JR, Gilbert GL. Comparative impact of guidelines, clinical data, and decision support on prescribing decisions: An interactive web experiment with simulated cases. Journal of the American Medical Informatics Association 2004; 11 (01) 71-77.
  • 11 Gorton TA, Cranford CO, Golden WE, Walls RC, Pawelak JE. Primary care physicians’ response to dissemination of practice guidelines. Arch Fam Med 1995; 4 (02) 135-142.
  • 12 Shea S, DuMouchel W, Bahamonde L. A meta-analysis of 16 randomized controlled trials to evaluate computer-based clinical reminder systems for preventive care in the ambulatory setting. Journal of the American Medical Informatics Association 1996; 3 (06) 399-409.
  • 13 Kralj B, Iverson D, Hotz K, Ashbury FD. The impact of computerized clinical reminders on physician prescribing behavior: Evidence from community oncology practice. American Journal of Medical Quality 2003; 18 (05) 197-203.
  • 14 Sequist TD, Gandhi TK, Karson AS, Fiskio JM, Bugbee D, Sperling M. et al., editors. A randomized trial of electronic clinical reminders to improve quality of care for diabetes and coronary artery disease. 27th Annual Meeting of the Society of General Internal Medicine; 2004 May 12-15; Chicago, IL.:
  • 15 Gandhi TK, Sequist TD, Poon EG, Karson AS, Murff H, Fairchild DG. et al. Primary care clinician attitudes towards electronic clinical reminders and clinical practice guidelines. AMIA Annu Symp Proc 2003; 848.
  • 16 Calabrisi RR, Czarnecki T, Blank C. The impact of clinical reminders and alerts on health screenings. The VA Pittsburgh Healthcare System achieves notable results by enhancing an automated clinical reminder system within its CPR –and has the data to prove it. Health Manag Technol 2002; 23 (12) 32-34.
  • 17 Schellhase KG, Koepsell TD, Norris TE. Providers’ reactions to an automated health maintenance reminder system incorporated into the patient’s electronic medical record. American Board of Family Practice 2003; 16: 312-317.
  • 18 Agrawal A, Mayo-Smith MF. Adherence to computerized clinical reminders in a large healthcare delivery network. Medinfo 2004; 11: 111-114.
  • 19 Goldberg HI, Wagner EH, Fihn SD, Martin DP, Horowitz CR, Christensen DB. et al. A randomized controlled trial of CQI teams and academic detailing: can they alter compliance with guidelines?. Jt Comm J Qual Improv 1998; 24 (03) 130-142.
  • 20 Tierney WM, Overhage JM, Murray MD, Harris LE, Zhou XH, Eckert GJ. et al. Effects of computerized guidelines for managing heart disease in primary care - A randomized, controlled trial. Journal of General Internal Medicine 2003; 18 (12) 967-976.
  • 21 Wu SJ, Lehto M, Yih Y, Saleem JJ, Doebbeling BN. Relationship of estimated resolution time and computerized clinical reminder adherence. AMIA Annu Symp Proc 2007: 334-338.
  • 22 Weir CR, Nebeker JJR, Hicken BL, Campo R, Drews F, LeBar B. A cognitive task analysis of information management strategies in a computerized provider order entry environment. Journal of the American Medical Informatics Association 2007; 14 (01) 65-75.
  • 23 U. S. Preventive Services Task Force (USPSTF).. website: http://www.ahrq.gov/clinic/uspstfix.htm.
  • 24 National Guideline Clearinghouse. website: http://www.guideline.gov.
  • 25 Sheldon R, OBrien BJ, Blackhouse G, Goeree R, Mitchell B, Klein G. et al. Effect of clinical risk stratification on cost-effectiveness of the implantable cardioverter defibrillator: the Canadian implantable defibrillator study. Circulation 2001; 104 (14) 1622-1626.
  • 26 Read TE, Kodner IJ. Colorectal cancer: Risk factors and recommendations for early detection. American Family Physician 1999; 59 (11) 3083-3092.
  • 27 Dalal M, Bradley E, Braithwaite RS. Prioritizing clinical practice guidelines in the primary care setting. The 29st annual meeting of the Society for Medical Decision Making, Pittsburgh, PA. 2007 October.
  • 28 Saleem JJ, Patterson ES, Militello L, Render ML, Orshansky G, Asch SM. Exploring barriers and facilitators to the use of computerized clinical reminders. Journal of the American Medical Informatics Association 2005; 12 (04) 438-447.
  • 29 Linder JA, Rose AF, Palchuk MB, Chang F, Schnipper JL, Chan JC, Middleton B. Decision support for acute problems: the role of the standardized patient in usability testing. J Biomed Inform 2006; 39 (06) 648-655.
  • 30 Saleem JJ, Patterson ES, Militello L, Anders S, Falciglia M, Wissman JA, Roth EM, Asch SM. Impact of clinical reminder redesign on learnability, efficiency, usability, and workload for ambulatory clinic nurses. J Am Med Inform Assoc 2007; 14 (05) 632-640.
  • 31 Yngve Dahl. Ole Andreas Alsos and Dag Svanæs. Evaluating mobile usability: The role of fidelity in full-scale laboratory simulations with mobile ICT for hospitals. Lecture Notes in Computer Science 2009; 5610: 232-241.

Correspondence to:

Yuehwern Yih, Ph.D.
School of Industrial Engineering
Purdue University
315 N. Grant Street
West Lafayette, IN 47907
Phone: (765) 494-0826   
Fax: (765) 494-1212   

  • References

  • 1 Doebbeling BN, Vaughn TE, McCoy KD, Glassman P. Informatics implementation in the Veterans Health Administration (VHA) healthcare system to improve quality of care. AMIA Annu Symp Proc 2006: 204-208.
  • 2 Balas EA, Li ZR, Spencer DC, Jaffrey F, Brent E, Mitchell JA. An expert system for performance-based direct delivery of published clinical evidence. Journal of the American Medical Informatics Association 1996; 3 (01) 56-65.
  • 3 Cannon DS, Allen SN. A comparison of the effects of computer and manual reminders on compliance with a mental health clinical practice guideline. Journal of the American Medical Informatics Association 2000; 7 (02) 196-203.
  • 4 Hasman A, Safran C, Takeda H. Quality of health care: informatics foundations. Methods Inf Med 2003; 42 (05) 509-518.
  • 5 Eslami S, Abu-Hanna A, de Keizer NF. Evaluation of outpatient computerized physician medication order entry systems: a systematic review. J Am Med Inform Assoc 2007; 14 (04) 400-406.
  • 6 Vashitz G, Meyer J, Parmet Y, Peleg R, Goldfarb D, Porath A. et al. Defining and measuring physicians’ responses to clinical reminders. J Biomed Inform 2009; 42 (02) 317-326.
  • 7 Dexter PR, Perkins S, Overhage JM, Maharry K, Kohler RB, McDonald CJ. A computerized reminder system to increase the use of preventive care for hospitalized patients. New England Journal of Medicine. 2001; 345 (13) 965-970.
  • 8 Ornstein SM, Garr DR, Jenkins RG, Rust PF, Arnon A. Computer-generated physician and patient reminders - tools to improve population adherence to selected preventive services. Journal of Family Practice. 1991; 32 (01) 82-90.
  • 9 RAND Corporation.. A systematic review of the literature on interventions to increase the use of clinical preventive services under Medicare. 1999
  • 10 Sintchenko V, Coiera E, Iredell JR, Gilbert GL. Comparative impact of guidelines, clinical data, and decision support on prescribing decisions: An interactive web experiment with simulated cases. Journal of the American Medical Informatics Association 2004; 11 (01) 71-77.
  • 11 Gorton TA, Cranford CO, Golden WE, Walls RC, Pawelak JE. Primary care physicians’ response to dissemination of practice guidelines. Arch Fam Med 1995; 4 (02) 135-142.
  • 12 Shea S, DuMouchel W, Bahamonde L. A meta-analysis of 16 randomized controlled trials to evaluate computer-based clinical reminder systems for preventive care in the ambulatory setting. Journal of the American Medical Informatics Association 1996; 3 (06) 399-409.
  • 13 Kralj B, Iverson D, Hotz K, Ashbury FD. The impact of computerized clinical reminders on physician prescribing behavior: Evidence from community oncology practice. American Journal of Medical Quality 2003; 18 (05) 197-203.
  • 14 Sequist TD, Gandhi TK, Karson AS, Fiskio JM, Bugbee D, Sperling M. et al., editors. A randomized trial of electronic clinical reminders to improve quality of care for diabetes and coronary artery disease. 27th Annual Meeting of the Society of General Internal Medicine; 2004 May 12-15; Chicago, IL.:
  • 15 Gandhi TK, Sequist TD, Poon EG, Karson AS, Murff H, Fairchild DG. et al. Primary care clinician attitudes towards electronic clinical reminders and clinical practice guidelines. AMIA Annu Symp Proc 2003; 848.
  • 16 Calabrisi RR, Czarnecki T, Blank C. The impact of clinical reminders and alerts on health screenings. The VA Pittsburgh Healthcare System achieves notable results by enhancing an automated clinical reminder system within its CPR –and has the data to prove it. Health Manag Technol 2002; 23 (12) 32-34.
  • 17 Schellhase KG, Koepsell TD, Norris TE. Providers’ reactions to an automated health maintenance reminder system incorporated into the patient’s electronic medical record. American Board of Family Practice 2003; 16: 312-317.
  • 18 Agrawal A, Mayo-Smith MF. Adherence to computerized clinical reminders in a large healthcare delivery network. Medinfo 2004; 11: 111-114.
  • 19 Goldberg HI, Wagner EH, Fihn SD, Martin DP, Horowitz CR, Christensen DB. et al. A randomized controlled trial of CQI teams and academic detailing: can they alter compliance with guidelines?. Jt Comm J Qual Improv 1998; 24 (03) 130-142.
  • 20 Tierney WM, Overhage JM, Murray MD, Harris LE, Zhou XH, Eckert GJ. et al. Effects of computerized guidelines for managing heart disease in primary care - A randomized, controlled trial. Journal of General Internal Medicine 2003; 18 (12) 967-976.
  • 21 Wu SJ, Lehto M, Yih Y, Saleem JJ, Doebbeling BN. Relationship of estimated resolution time and computerized clinical reminder adherence. AMIA Annu Symp Proc 2007: 334-338.
  • 22 Weir CR, Nebeker JJR, Hicken BL, Campo R, Drews F, LeBar B. A cognitive task analysis of information management strategies in a computerized provider order entry environment. Journal of the American Medical Informatics Association 2007; 14 (01) 65-75.
  • 23 U. S. Preventive Services Task Force (USPSTF).. website: http://www.ahrq.gov/clinic/uspstfix.htm.
  • 24 National Guideline Clearinghouse. website: http://www.guideline.gov.
  • 25 Sheldon R, OBrien BJ, Blackhouse G, Goeree R, Mitchell B, Klein G. et al. Effect of clinical risk stratification on cost-effectiveness of the implantable cardioverter defibrillator: the Canadian implantable defibrillator study. Circulation 2001; 104 (14) 1622-1626.
  • 26 Read TE, Kodner IJ. Colorectal cancer: Risk factors and recommendations for early detection. American Family Physician 1999; 59 (11) 3083-3092.
  • 27 Dalal M, Bradley E, Braithwaite RS. Prioritizing clinical practice guidelines in the primary care setting. The 29st annual meeting of the Society for Medical Decision Making, Pittsburgh, PA. 2007 October.
  • 28 Saleem JJ, Patterson ES, Militello L, Render ML, Orshansky G, Asch SM. Exploring barriers and facilitators to the use of computerized clinical reminders. Journal of the American Medical Informatics Association 2005; 12 (04) 438-447.
  • 29 Linder JA, Rose AF, Palchuk MB, Chang F, Schnipper JL, Chan JC, Middleton B. Decision support for acute problems: the role of the standardized patient in usability testing. J Biomed Inform 2006; 39 (06) 648-655.
  • 30 Saleem JJ, Patterson ES, Militello L, Anders S, Falciglia M, Wissman JA, Roth EM, Asch SM. Impact of clinical reminder redesign on learnability, efficiency, usability, and workload for ambulatory clinic nurses. J Am Med Inform Assoc 2007; 14 (05) 632-640.
  • 31 Yngve Dahl. Ole Andreas Alsos and Dag Svanæs. Evaluating mobile usability: The role of fidelity in full-scale laboratory simulations with mobile ICT for hospitals. Lecture Notes in Computer Science 2009; 5610: 232-241.