Amy Irwin, Susan L. Moore, Connie S. Price, Tim Jenkins, Lauren DeAlleaume, David R. West
Abstract
Overuse of antimicrobial agents fosters the spread of antimicrobial-resistant organisms, which have become a leading public health threat. The Institute of Medicine has prioritized decreasing the inappropriate use of antibiotics as one of the primary solutions to address the growing problem of antimicrobial resistance. Despite numerous efforts, inappropriate antibiotic prescribing in primary care practices remains common. As part of a large-scale practical trial, a qualitative analysis of key informant interviews was conducted to assess paper-based and electronic implementation methods of antibiotic prescribing clinical decision support tools in primary care clinics. Sensitivity of the intervention to the specific needs of individual practices is necessary to sustaining positive effects in prescribing behavior. While intervention educational materials and decision aids were consistent across practices, implementation included the flexibility to conform to clinicians' preferences and the workflows, policies, and resource limitations of each individual clinic. Key lessons learned include the flexibility to accommodate (1) variability in local antimicrobial resistance and formularies to ensure relevance in almost any primary care practice; (2) ability of practices to modify treatment and diagnostic guidelines within reason, based on contextual factors such as whether practices were part of an integrated system of care and their relative access to diagnostic testing equipment; and (3) availability and recognition of a local antibiotic stewardship champion to answer questions and inform local decisionmaking.
Introduction
Appropriate antibiotic prescribing has long been an issue of great concern to practitioners and policymakers alike.1 Overuse of antimicrobial agents fosters the spread of antimicrobial-resistant organisms, which have become a leading public health threat.2,3 Antimicrobial resistance is ultimately associated with poorer clinical outcomes and increased health care costs, much of which can be attributed to complications of antibiotic use.4,5 The Institute of Medicine has prioritized decreasing the inappropriate use of antibiotics as one of the primary solutions to address the growing problem of antimicrobial resistance.1
Research has shown that inappropriate prescribing (wrong indication or indication or use of unnecessarily broad-spectrum agents) may be due to multiple factors. These may include (1) provider knowledge gaps6,7 or lack of awareness of guidelines;8 (2) patient demand (perceived or actual);9-13 (3) difficulty in distinguishing bacterial from viral infections;14-16 (4) provider or patient perception that a course of antibiotics is the “safest” strategy; (5) time necessary for the provider to explain why antibiotics are not indicated;17,18 and (6) health beliefs of the provider,19,20 among others.7,21 Given the multidimensional nature of this critical problem, a variety of interventions have been designed to improve antibiotic prescribing in the primary care setting. Such interventions have included dissemination of educational materials to providers and patients, educational meetings and lectures, academic detailing, audit and feedback, guideline development, clinical decision support systems, mass media campaigns, and delayed prescriptions.22-24
The selection of the most effective of these interventions to improve the prescribing of antibiotics appears to be condition- and situation-specific.25 A Cochrane review evaluated 66 studies that met criteria for time series analysis, controlled trials, or controlled pre-post studies. Seventy-seven percent of the studies reported improved outcomes, but no relationship between the type of intervention and the outcome was noted. The authors concluded that lack of a standard study design or direct comparison of interventions limited their ability to recommend specific interventions.26 In designing an intervention to reduce the inappropriate use of antibiotics in office-based primary care practices, with practical application to a broad variety of settings, a recent assessment of these strategies concluded that multifaceted interventions that include active clinician education combined with clinician decision support systems appear to be the most effective in changing antibiotic-prescribing behaviors.23
Indeed, the study demonstrating the largest impact on antibiotic prescribing involved use of clinical decision support (CDS) systems.27 Because the impact was seen only with the use of CDS, and not with education alone, the success was likely attributable to systematizing and standardizing the decisionmaking process, akin to the “checklist” approach that has shown similar success in infection control initiatives aimed at reducing central line-associated bloodstream infections.28 Previous studies indicate that clinicians who have been in practice longer and are not involved in medical teaching appear to misuse antibiotics most frequently.7 CDS tools would likely provide the greatest benefit to those providers, particularly in settings that have limited access to consultation and subspecialty services.29
The State Networks of Colorado Ambulatory Practices and Partners (SNOCAP) undertook a study to conduct a pragmatic trial to evaluate the impact of CDS tools in primary care practice. SNOCAP is a practice-based research network that was expanded throughout the USA, in partnership with the American Academy of Family Physicians—National Research Network, to form SNOCAP-USA. This collaboration of practice-based research networks makes it possible to perform this and other related studies to provide practices, policymakers, and patients with actionable information with which to improve care.
In this study, clinical pathways for eight common adult and pediatric infections were developed: nonspecific upper respiratory infection, acute bronchitis, acute rhinosinusitis, pharyngitis, acute otitis media, urinary tract infection, skin and soft tissue infection (cellulitis or cutaneous abscess), and community-acquired pneumonia. Clinics were given binders with hard copies and electronic copies of the CDS tools on the local intranet, with some clinics adopting a combined implementation approach, and others opting for either the binders or the electronic copies. The CDS tools were implemented over a 1-year intervention period.30 In addition, clinics were provided with patient education materials, and clinic champions were identified who assisted with intervention implementation throughout the study. While the CDS tools did indeed have a positive impact on prescribing behavior change,30 the use of a mixed methods implementation approach provided valuable qualitative insight regarding the practice-specific dynamics surrounding the successful implementation and use of these tools. One aspect of our inquiry centered on the need for and value of flexible and adaptive processes to accommodate the needs of local settings.
Methods
After receipt of all required institutional research board approvals, the study was implemented at eight family medicine and internal medicine outpatient clinics in an integrated urban safety net health system in the Rocky Mountain region of the United States. Key informants at each clinic were asked to identify a minimum of one health care provider per site with reasonable knowledge of the clinic's antibiotic prescribing practices. Identified providers at each clinic were then contacted and asked to consent to confidential in-person interviews. Eight providers agreed to participate, representing all eight clinic sites. Six participants represented physician perspectives (MDs), and two participants represented the perspectives of mid-level practitioners (nurse practitioners or physician assistants).
Interviews were conducted by a doctorally prepared qualitative health and behavior scientist over a 2-week period in July 2012. Interviews were conducted at each clinic site in the participant's choice of setting. All interviews were audio recorded, with the recorded data augmented by the investigator's observations made during the interview session. Interviews were conducted in a semi-structured format, according to an interview guide developed by the investigators, which ensured that key topics of interest were addressed with all providers while also allowing for exploration of additional topics and content areas that might emerge during the discussion. Interview topics included providers' awareness of antibiotic stewardship programs in the care setting; how providers were made aware of good antibiotic stewardship practices; what materials and tools were available to help providers in making prescribing decisions and discussing appropriate antibiotic use with patients; patients' perceptions of antibiotic prescribing practices; how providers used available materials in their own care practices; and providers' opinions of, and recommendations for, antibiotic stewardship overall.
Interview data were subjected to analysis through review of written notes and audio recordings. Manual coding and immersive exposure approaches to the data, interview transcripts, notes from the audio recordings, personal observations, and several reviews of all written and audio materials were employed to analyze the qualitative data. Next, an inductive approach using an open, heuristic coding process was taken to identify initial emergent topics mentioned by participants.31 Individual topics were then further categorized into themes based on the number of participants who mentioned or agreed with reference to a topic. Topics were classified as themes if they emerged in discussion with three or more participants. Identified themes and patterns were then reexamined in context and incorporated into a synthesis of results.32
Results
General Awareness and Use of Computerized Decision Support
Primary care providers reported a general awareness of the CDS tools, with the majority of providers reporting themselves and their colleagues as being familiar with both the health system-specific antibiogram and the condition-specific prescribing algorithms provided. Providers reported using the antibiogram and algorithms both for self-education and reference purposes and for guidance at the time of prescribing. Use of CDS tools was reported to be maintained over time; more than one provider reported having accessed guideline materials to confirm their own knowledge when prescribing for a less frequently encountered diagnosis.
Personal communication methods were widely referenced as a way in which providers initially became aware of CDS tools. Three-quarters of the participants mentioned dissemination in system-based meetings such as grand rounds, departmental meetings, and committee sessions, and half of the participants recalled presentations being made by study personnel at clinic sites and in clinic-based provider meetings. Discussion among colleagues in clinic-based settings and provider meetings were also mentioned by over a third of the participants as a means of promoting awareness, as were informational and review sessions conducted by team leads. No consensus was observed with respect to the means used to inform new providers or residents of CDS tools and associated materials. Two informants indicated that reference information about the CDS tools was included in the educational packets provided to them by clinic supervisors, and two reported making mention of CDS tools during new provider orientation upon employment by the hospital, while two reported dependence on residents' preceptors to share stewardship information. New providers were largely presumed to bear the responsibility for becoming conscious of antibiotic stewardship in clinic practices and health system culture, primarily through asking questions or gaining the information through a perceived emergent awareness and shared community knowledge base.
Email was perceived by the majority of providers as an efficient, effective, and preferred means of disseminating new and updated CDS tools, although a few providers also noted that high volumes of email contributed to some providers exhibiting a tendency to ignore or delete large-group or mass-distribution email messages. The majority of providers also reported acknowledgment of the organization's intranet as an accepted source of information, although this observation was accompanied almost unanimously by a strong perception of the organizational intranet as unwieldy, slow, and difficult to use effectively. It is of note that half of participants specifically identified the sub-site where CDS tools were housed as being easy to access and use, in exception to the perceived general rule.
Clinician and Practice Variation and the Need to Adapt
Providers perceived themselves and their colleagues as generally adhering to prescribing guidelines in concordance with the CDS tools made available. Variations in prescribing practices among primary care providers were attributed to providers' own knowledge as influenced by age, years since completing clinical education, and training background. Several providers noted a willingness to deviate from guideline-based practices in favor of their own clinical judgment and expertise when they disagreed with guideline recommendations, whether for reasons of poor guideline quality or clinical considerations on a case-by-case basis.
Respondents were consistently able to share their clinic-specific challenges to guideline-concordant prescribing, such as availability of certain medications in a clinic dispensary, limited availability of point-of-care diagnostic tests, and barriers to access affecting patients' willingness or ability to return for followup visits. At the same time, the majority of providers were in agreement that the CDS tools were useful and helpful. The guidelines were described as being of good quality, evidence-based, appropriate to the setting, and generally accepted.
Workflow Integration
Paper-based methods were also mentioned by half of the participants. Clinic providers reported actively continuing to use the educational materials in the reference notebooks provided; two clinic providers also described printing and distributing algorithm materials for review and discussion in provider meetings. The availability of provider time during clinic visits was repeatedly noted as a scarce resource and limiting factor, both in general and with regard to the use of antibiotic guidelines; in this connection, participants mentioned the guidelines as easy to access and use, which was perceived as a factor in their value as a reference tool.
Providers expressed strong preference for, and interest in, electronic health record (EHR)-based prompting at the point of prescribing as a way to promote good stewardship practices. Specific suggestions were made for the design of prompts that incorporate informational/educational aspects and recommendations tailored to the active prescription context. For example, such a prompt might be triggered in response to the combination of a diagnosis and a non-recommended medication selection to inform the provider of current resistance patterns and ask whether the provider was aware that an alternate medication was the recommended first-line agent. Providers also recommended the use of electronic methods for guideline updates. In addition, they were cognizant of challenges inherent in maintaining and improving stewardship practices and suggested involving providers as partners in developing new guidelines of interest. It was observed by participants that, in general, sharing appropriate prescribing information in the context of current events or news of interest—such as infectious disease surveillance rates, current resistance rates, or antibiotic cost—would increase provider interest in, retention of, and adherence to recommendations.
Discussion
This intervention was designed with three simple components to be practical and widely generalizable: (1) clinical pathways, (2) patient education materials, and (3) peer champion support. The availability of our clinical pathways in a format adapted to the practice setting (paper or electronic) and widely accessible patient education materials should enable implementation at any primary care practice.
The long-term sustainability of system-wide quality improvement programs is infrequently studied. A systematic literature review published in 2010 identified no studies on the long-term sustainability of such programs.33 This study provides preliminary insight into the central components of quality improvement initiatives aimed at decreasing antibiotic overuse. Qualitative themes that emerged from the analysis revealed the importance of flexibility in intervention implementation to support sustainability of decreased antibiotic overuse in primary care. Flexible components noted included incorporating information about CDS tools into the provider orientation packets, annual training for providers, and making the tools available at the point of care within the provider's workflow. Other factors were suggested by providers to promote sustainability, such as EHR-based prompting at the point of prescribing, with specific informational/educational aspects and recommendations tailored to the active prescription context (e.g., a prompt that might be triggered in response to the combination of a diagnosis and a non-recommended medication selection). Audit and feedback, not studied as part of this intervention, were also suggested to increase sustained adherence to recommendations. The findings of the present study are supported by the quantitative results yielded in the study by Jenkins and colleagues,30 which adopted a flexible implementation approach and demonstrated a positive reduction of antibiotic prescribing for non-pneumonia acute respiratory infections and a reduction in the use of broad-spectrum antibiotics.
Limitations of the present study include the small sample size of providers interviewed and a single, individual interview methodology. Recommendations for further inquiry should include increasing sample size, expanding to include focus groups, and surveying all providers to quantitatively assess factors that support flexible intervention approaches.
Conclusion
The findings of the present study suggest that there is not a one-size-fits-all approach to implementing CDS tools in primary care settings. Key lessons learned include the flexibility to accommodate for:
- Variability in local antimicrobial resistance and formularies to ensure relevance in almost any primary care practice.
- Ability of practices to modify treatment and diagnostic guidelines within reason, based on contextual factors such as whether practices were part of an integrated system of care and their relative access to diagnostic testing equipment.
- Availability and recognition of a local antibiotic stewardship champion to answer questions and inform local decisionmaking.
While electronic implementation is preferred by primary care clinicians, positive outcomes in the reduction of inappropriate use of antibiotics may also be observed with the implementation of CDS guidelines in paper format. CDS tools in primary care settings need to be flexible and respectful of the available resources at the clinic management level.
Acknowledgments
This project was funded under contract number HHSA290200710008, Task Order No. 7, from the Agency for Healthcare Research and Quality (AHRQ), U.S. Department of Health and Human Services. The findings and conclusions in this document are those of the authors, who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
Authors' Affiliations
Denver Health & Hospital Authority, Denver, CO (AI, SLM, CSP, TJ, LD). University of Colorado School of Medicine, Aurora, CO (CSP, TJ, LD, DRW).
Address Correspondence to: David R. West, Ph.D., Director, SNOCAP-USA, Director, Colorado Health Outcomes Program, Professor, School of Medicine, University of Colorado, 13199 Montview Blvd, Suite 300, Aurora CO 80045; Email: david.west@ucdenver.edu.
References
1. Institute of Medicine. Antimicrobial Resistance: Issues and Options: Workshop Report. Forum on Emerging Infections; Harrison, PF, Lederberg, J, eds.Washington DC: National Academy of Sciences; 1998.
2.Goossens H, Ferech M, Vander Stichele R, et al. Outpatient antibiotic use in Europe and association with resistance: a cross-national database study. Lancet 2005 Feb 12-18;365 (9459):579-87. PMID: 15708101.
3. Lipsitch M, Samore MH. Antimicrobial use and antimicrobial resistance: a population perspective. Emerg Infect Dis 2002 Apr;8(4):347-54. Erratum in: Emerg Infect Dis 2002 May;8(5):540. PMID: 11971765.
4. Cosgrove SE, Carmeli Y. The impact of antimicrobial resistance on health and economic outcomes. Clin Infect Dis 2003 June 1;36(11):1433-7. PMID: 12766839.
5. Giske CG, Monnet DL, Cars O, et al. ReAct-Action on Antibiotic Resistance. Clinical and economic impact of common multidrug-resistant gram-negative bacilli. Antimicrob Agents Chemother 2008 Mar;52(3):813-21. PMID: 18070961.
6. Steinke DT, Bain DJ, MacDonald TM, et al. Practice factors that influence antibiotic prescribing in general practice in Tayside. J Antimicrob Chemother 2000 Sep;46(3):509-12. PMID: 10980184.
7. Mainous AG 3rd, Hueston WJ, Love MM, et al. An evaluation of statewide strategies to reduce antibiotic overuse. Fam Med 2000 Jan;32(1):22-9. PMID: 10645510.
8. Christian AH, Mills T, Simpson SL, et al. Quality of cardiovascular disease preventive care and physician/practice characteristics. J Gen Intern Med 2006 Mar;21(3):231-7. PMID: 16637822.
9. Bauchner H, Pelton SI, Klein JO. Parents, physicians, and antibiotic use. Pediatrics 1999 Feb;103(2):395-401. PMID: 9925831.
10. Palmer DA, Bauchner H. Parents' and physicians' views on antibiotics. Pediatrics 1997 Jun;99(6):E6. PMID: 9164802.
11. Scott JG, Cohen D, DiCicco-Bloom B, et al. Antibiotic use in acute respiratory infections and the ways patients pressure physicians for a prescription. J Fam Pract 2001 Oct;50(10):853-8. Erratum in: J Fam Pract 2001 Dec;50(12):1077. PMID: 11674887.
12. Kuzujanakis M, Kleinman K, Rifas-Shiman S, et al. Correlates of parental antibiotic knowledge, demand, and reported use. Ambul Pediatr 2003 Jul-Aug;3(4):203-10. PMID: 12882598.
13. Watson RL, Dowell SF, Jayaraman M, et al. Antimicrobial use for pediatric upper respiratory infections: reported practice, actual practice, and parent beliefs. Pediatrics 1999 Dec;104(6):1251-7. PMID: 10585974.
14. Murray S, Del Mar C, O'Rourke P. Predictors of an antibiotic prescription by GPs for respiratory tract infections: a pilot. Fam Pract 2000 Oct;17(5):386-8. PMID: 11021896.
15. Mainous AG 3rd, Hueston WJ, Eberlein C. Colour of respiratory discharge and antibiotic use. Lancet 1997 Oct 11;350(9084):1077. PMID: 10213556.
16. McIsaac WJ, Goel V, To T, et al. The validity of a sore throat score in family practice. CMAJ 2000 Oct 3;163(7):811-5. PMID: 11033707.
17. Linder JA, Singer DE, Stafford RS. Association between antibiotic prescribing and visit duration in adults with upper respiratory tract infections. Clin Ther 2003 Sep;25(9):2419-30. PMID: 14604741.
18. Hutchinson JM, Foley RN. Method of physician remuneration and rates of antibiotic prescription. CMAJ 1999 Apr 6;160(7):1013-7. PMID: 10207340.
19. Brinsley KJ, Sinkowitz-Cochran RL, Cardo DM; CDC Campaign to Prevent Antimicrobial Resistance Team. Assessing motivation for physicians to prevent antimicrobial resistance in hospitalized children using the Health Belief Model as a framework. Am J Infect Control 2005 Apr;33(3):175-81. PMID: 15798673.
20. Goldmann DA, Weinstein RA, Wenzel RP, et al. Strategies to prevent and control the emergence and spread of antimicrobial-resistant microorganisms in hospitals. A challenge to hospital leadership. JAMA 1996 Jan 17;275(3):234-40. PMID: 8604178.
21. Patel SJ, Larson EL, Kubin CJ, et al. A review of antimicrobial control strategies in hospitalized and ambulatory pediatric populations. Pediatr Infect Dis J 2007 Jun;26(6):531-7. PMID: 17529873.
22. Arnold SR, Straus SE. Interventions to improve antibiotic prescribing practices in ambulatory care. Cochrane Database Syst Rev 2005 Oct 19:(4) CD003539. doi: 10.1002/14651858.CD003539.pub2. PMID: 16235325.
23. Ranji SR, Steinman MA, Shojania KG, et al. Interventions to reduce unnecessary antibiotic prescribing: a systematic review and quantitative analysis. Med Care 2008 Aug;46(8):847-62. doi: 10.1097/MLR.0b013e318178eabd. PMID: 18665065.
24. Spurling GK, Del Mar CB, Dooley L, et al. Delayed antibiotics for respiratory infections. Cochrane Database Syst Rev 2013 Apr 30;4:CD004417. doi: 10.1002/14651858.CD004417.pub4. PMID: 23633320.
25. Cabana MD, Rand CS, Powe NR, et al. Why don't physicians follow clinical practice guidelines? A framework for improvement. JAMA 1999 Oct 20;282(15):1458-65. PMID: 10535437.
26. Davey P, Brown E, Charani E, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev 2013 Apr 30;4:CD003543. doi: 10.1002/14651858.CD003543.pub3. PMID: 23633313.
27. Samore MH, Bateman K, Alder SC, et al. Clinical decision support and appropriateness of antimicrobial prescribing: a randomized trial. JAMA 2005 Nov 9;294(18):2305-14. PMID: 16278358.
28. Pronovost P, Needham D, Berenholtz S, et al. An intervention to decrease catheter-related bloodstream infections in the ICU. N Engl J Med 2006 Dec 28;355(26):2725-32. PMID: 17192537.
29. Dorsch JL. Information needs of rural health professionals: a review of the literature. Bull Med Libr Assoc 2000 Oct;88(4):346-54. PMID: 11055302.
30. Jenkins TC, Irwin, A, Coombs L, et al. Effects of clinical pathways for common outpatient infections on antibiotic prescribing. Am J Med 2013 Apr;126(4):327-335. doi: 10.1016/j.amjmed.2012.10.027. PMID: 23507206.
31. Miles MB, Huberman, AM. Qualitative Data Analysis: An Expanded Source Book. Thousand Oaks, CA: Sage Publications; 1994.
32. Crabtree BF, Miller, WL, eds. Doing Qualitative Research. 2nd ed. Thousand Oaks, CA: Sage Publications; 1999.
33. Robert G, Greenhalgh T, MacFarlane F, et al. Adopting and assimilating new non-pharmaceutical technologies into health care: a systematic review. J Health Serv Res Policy 2010 Oct;15(4):243-50. PMID: 20592046.