Journal of General Internal Medicine

, Volume 21, Issue 9, pp 989–994 | Cite as

Computerized condition-specific templates for improving care of geriatric syndromes in a primary care setting

Innovations In Clinical Practice

Abstract

INTRODUCTION: As the U.S. population ages, primary care clinicians (PCCs) will encounter more patients with geriatric syndromes, such as urinary incontinence (UI) and falls. Yet, current evidence suggests that care of these conditions does not meet expected standards and that PCCs would benefit from tools to improve care of these conditions. Little is known about the role of computerized condition-specific templates for improving care of geriatric syndromes.

AIM: We sought to develop and assess the usefulness of condition-specific computerized templates in a primary care setting.

SETTING: A large academic Veterans Affairs medical center.

PROGRAM DESCRIPTION: We developed and tested the usefulness of 2 condition-specific computerized templates (UI and falls) that could be added on to an existing electronic health record system.

PROGRAM EVALUATION: Semistructured interviews were used to identify barriers to use of computerized templates. Usefulness and usability were assessed through a randomized-controlled trial involving standardized patients.

DISCUSSION: Use of condition-specific templates resulted in improved history and physical exam assessment for both UI and falls (P<.05). Our computerized, condition-specific templates are a promising method for improving care of geriatric conditions in a primary care setting, but require improvement in usability before widespread implementation.

Key Words

quality of care geriatrics decision support templates 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Campbell PA. State Population Projections. U.S. Census Bureau. 2005. Available at: http://www.census.gov/prod/2/pop/p25/p25-1131.pdf. Accessed March 16, 2006.Google Scholar
  2. 2.
    Wenger NS, Solomon DH, Roth CP, et al. The quality of medical care provided to vulnerable community-dwelling older patients. Ann Intern Med. 2003;139:740–7.PubMedGoogle Scholar
  3. 3.
    Bland DR, Dugan E, Cohen SJ, et al. The effects of implementation of the agency for health care policy and research urinary incontinence guidelines in primary care practices. J Am Geriatr Soc. 2003;51:979–84.PubMedCrossRefGoogle Scholar
  4. 4.
    Chang JT, Morton SC, Rubenstein LZ, et al. Interventions for the prevention of falls in older adults: systematic review and meta-analysis of randomised clinical trials. BMJ. 2004;328:680.PubMedCrossRefGoogle Scholar
  5. 5.
    Ostaszkiewicz J, Johnston L, Roe B. Habit retraining for the management of urinary incontinence in adults. Cochrane Database Syst Rev. 2004; (2):CD002801.Google Scholar
  6. 6.
    Wenger NS, Roth CP, Shekelle PG, et al. A controlled trial of a practice-based intervention to improve primary care for falls, incontinence, and dementia. J Gen Intern Med. 2005;20(suppl):52.Google Scholar
  7. 7.
    Reuben DB, Roth C, Kamberg C, Wenger NS. Restructuring primary care practices to manage geriatric syndromes: the ACOVE-2 intervention. J Am Geriatr Soc. 2003;51:1787–93.PubMedCrossRefGoogle Scholar
  8. 8.
    Wrenn K, Rodewald L, Lumb E, Slovis C. The use of structured, complaint-specific patient encounter forms in the emergency department. Ann Emerg Med. 1993;22:805–12.PubMedCrossRefGoogle Scholar
  9. 9.
    Mulvehill S, Schneider G, Cullen CM, Roaten S, Foster B, Porter A. Template-guided versus undirected written medical documentation: a prospective, randomized trial in a family medicine residency clinic. J Am Board Family Pract. 2005;18:464–9.Google Scholar
  10. 10.
    Flocke SA, Frank SH, Wenger DA. Addressing multiple problems in the family practice office visit. J Fam Pract. 2001;50:211–6.PubMedGoogle Scholar
  11. 11.
    Matsumura Y, Takeda H, Okada T, et al. Devices for structured data entry in electronic patient record. Medinfo. 1998;9(part 1):85–8.PubMedGoogle Scholar
  12. 12.
    Porter SC, Kohane IS. Optimal data entry by patients: effects of interface structure and design. Medinfo. 2001;10(part 1):141–5.PubMedGoogle Scholar
  13. 13.
    Gaul GM. Revamped Veterans’ Health Care Now a Model. Washington Post 2005 August 22: A01.Google Scholar
  14. 14.
    Department of Veterans Affairs. The Electronic Record: CPRS. Employee Orientation Toolkit. 2003. Available at: http://www.va.gov/oaa/orientation/admin_cprs.asp. Accessed May 17, 2004.Google Scholar
  15. 15.
    Weir CR, Hurdle JF, Felgar MA, Hoffman JM, Roth B, Nebeker JR. Direct text entry in electronic progress notes. An evaluation of input errors. Methods Inf Med. 2003;42:61–7.PubMedGoogle Scholar
  16. 16.
    Department of Veterans Affairs. U.S. Veteran Population (Includes Puerto Rico, Territories and Foreign Countries). Department of Veterans Affairs Veteran Data and Information Program Statistics. Available at: http://www.va.gov/vetdata/ProgramStatics/index.htm. Accessed March 16, 2006.Google Scholar
  17. 17.
    Rubenstein LV, Yano EM, Fink A, et al. Evaluation of the VA’s pilot program in institutional reorganization toward primary and ambulatory care: part I, changes in process and outcomes of care. Acad Med. 1996;71:772–83.PubMedCrossRefGoogle Scholar
  18. 18.
    A New Generation of American Innovation Transforming Health Care: The President’s Health Information Technology Plan. The White House. 2005. Available at: http://www.whitehouse.gov/infocus/technology/economic_policy200404/chap3.html. Accessed March 16, 2006.Google Scholar
  19. 19.
    Freemantle N, Wood J, Crawford F. Evidence into practice, experimentation and quasi experimentation: are the methods up to the task? J Epidemiol Commun Health. 1998;52:75–81.CrossRefGoogle Scholar
  20. 20.
    Campbell M, Fitzpatrick R, Haines A, et al. Framework for design and evaluation of complex interventions to improve health. BMJ. 2000; 321:694–6.PubMedCrossRefGoogle Scholar
  21. 21.
    Kushniruk AW, Patel VL. Cognitive and usability engineering methods for the evaluation of clinical information systems. J Biomed Inform. 2004;37:56–76.PubMedCrossRefGoogle Scholar
  22. 22.
    Glassman PA, Luck J, O’Gara EM, Peabody JW. Using standardized patients to measure quality: evidence from the literature and a prospective study. Jt Comm J Qual Improv. 2000;26:644–53.PubMedGoogle Scholar
  23. 23.
    Shekelle PG, Mac Lean CH, Morton SC, Wenger NS. Assessing care of vulnerable elders: methods for developing quality indicators. Ann Intern Med. 2001;135(part 2):647–52.PubMedGoogle Scholar
  24. 24.
    Asch SM, Baker DW, Keesey JW, et al. Does the collaborative model improve care for chronic heart failure. Med Care. 2005;43:667–75.PubMedCrossRefGoogle Scholar
  25. 25.
    Patterson ES, Nguyen AD, Halloran JP, Asch SM. Human factors barriers to the effective use of ten HIV clinical reminders. J Am Med Inform Assoc. 2004;11:50–9.PubMedCrossRefGoogle Scholar
  26. 26.
    Saliba D, Elliott M, Rubenstein LZ, et al. The Vulnerable Elders Survey: a tool for identifying vulnerable older people in the community. J Am Geriatr Soc. 2001;49:1691–9.PubMedCrossRefGoogle Scholar

Copyright information

© Society of General Internal Medicine 2006

Authors and Affiliations

  1. 1.VA Greater Los Angeles Healthcare System, Division of General Internal Medicine, David Geffen School of Medicine at UCLARAND CorporationLos AngelesUSA

Personalised recommendations