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Figure 1.
Study Overview
Study Overview

aStratified by rurality in block sizes of 2.

Figure 2.
Wisconsin UTI Improvement Toolkit Logic Model
Wisconsin UTI Improvement Toolkit Logic Model

UTI indicates urinary tract infection.

Table 1.  
Structure of the Wisconsin UTI Improvement Toolkit
Structure of the Wisconsin UTI Improvement Toolkit
Table 2.  
Urinary Tract Infection Implementation Approach by Facilities
Urinary Tract Infection Implementation Approach by Facilities
Table 3.  
Study Outcomes and Control Variables
Study Outcomes and Control Variables
1.
Crnich  CJ, Jump  R, Trautner  B, Sloane  PD, Mody  L.  Optimizing antibiotic stewardship in nursing homes: a narrative review and recommendations for improvement.  Drugs Aging. 2015;32(9):699-716. doi:10.1007/s40266-015-0292-7PubMedGoogle ScholarCrossref
2.
Crnich  CJ, Drinka  P.  Improving the management of urinary tract infections in nursing homes: it’s time to stop the tail from wagging the dog.  Ann Longterm Care. 2014;22(9):32-36.Google Scholar
3.
Nace  DA, Drinka  PJ, Crnich  CJ.  Clinical uncertainties in the approach to long term care residents with possible urinary tract infection.  J Am Med Dir Assoc. 2014;15(2):133-139. doi:10.1016/j.jamda.2013.11.009PubMedGoogle ScholarCrossref
4.
van Buul  LW, Veenhuizen  RB, Achterberg  WP,  et al.  Antibiotic prescribing in Dutch nursing homes: how appropriate is it?  J Am Med Dir Assoc. 2015;16(3):229-237. doi:10.1016/j.jamda.2014.10.003PubMedGoogle ScholarCrossref
5.
Finucane  TE.  “Urinary tract infection”—requiem for a heavyweight.  J Am Geriatr Soc. 2017;65(8):1650-1655. doi:10.1111/jgs.14907PubMedGoogle ScholarCrossref
6.
Center for Health Systems Research and Analysis. Wisconsin long-term care urinary tract infection toolkit. https://crc.chsra.wisc.edu/uti-toolkit/index.php. Updated June 2019. Accessed June 10, 2019.
7.
Loeb  M, Brazil  K, Lohfeld  L,  et al.  Effect of a multifaceted intervention on number of antimicrobial prescriptions for suspected urinary tract infections in residents of nursing homes: cluster randomised controlled trial.  BMJ. 2005;331(7518):669. doi:10.1136/bmj.38602.586343.55PubMedGoogle ScholarCrossref
8.
Zabarsky  TF, Sethi  AK, Donskey  CJ.  Sustained reduction in inappropriate treatment of asymptomatic bacteriuria in a long-term care facility through an educational intervention.  Am J Infect Control. 2008;36(7):476-480. doi:10.1016/j.ajic.2007.11.007PubMedGoogle ScholarCrossref
9.
Zimmerman  S, Sloane  PD, Bertrand  R,  et al.  Successfully reducing antibiotic prescribing in nursing homes.  J Am Geriatr Soc. 2014;62(5):907-912. doi:10.1111/jgs.12784PubMedGoogle ScholarCrossref
10.
Trautner  BW, Grigoryan  L, Petersen  NJ,  et al.  Effectiveness of an antimicrobial stewardship approach for urinary catheter-associated asymptomatic bacteriuria.  JAMA Intern Med. 2015;175(7):1120-1127. doi:10.1001/jamainternmed.2015.1878PubMedGoogle ScholarCrossref
11.
van Buul  LW, van der Steen  JT, Achterberg  WP,  et al.  Effect of tailored antibiotic stewardship programmes on the appropriateness of antibiotic prescribing in nursing homes.  J Antimicrob Chemother. 2015;70(7):2153-2162. doi:10.1093/jac/dkv051PubMedGoogle Scholar
12.
McMaughan  DK, Nwaiwu  O, Zhao  H,  et al.  Impact of a decision-making aid for suspected urinary tract infections on antibiotic overuse in nursing homes.  BMC Geriatr. 2016;16:81. doi:10.1186/s12877-016-0255-9PubMedGoogle ScholarCrossref
13.
Kitson  A, Harvey  G, McCormack  B.  Enabling the implementation of evidence based practice: a conceptual framework.  Qual Health Care. 1998;7(3):149-158. doi:10.1136/qshc.7.3.149PubMedGoogle ScholarCrossref
14.
Damschroder  LJ, Aron  DC, Keith  RE, Kirsh  SR, Alexander  JA, Lowery  JC.  Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science.  Implement Sci. 2009;4:50. doi:10.1186/1748-5908-4-50PubMedGoogle ScholarCrossref
15.
Powell  BJ, Waltz  TJ, Chinman  MJ,  et al.  A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project.  Implement Sci. 2015;10:21. doi:10.1186/s13012-015-0209-1PubMedGoogle ScholarCrossref
16.
Lewis  CC, Klasnja  P, Powell  BJ,  et al.  From classification to causality: advancing understanding of mechanisms of change in implementation science.  Front Public Health. 2018;6:136. doi:10.3389/fpubh.2018.00136PubMedGoogle ScholarCrossref
17.
Rantz  MJ, Zwygart-Stauffacher  M, Flesner  M,  et al.  Challenges of using quality improvement methods in nursing homes that “need improvement”.  J Am Med Dir Assoc. 2012;13(8):732-738. doi:10.1016/j.jamda.2012.07.008PubMedGoogle ScholarCrossref
18.
Castle  NG, Engberg  J.  Staff turnover and quality of care in nursing homes.  Med Care. 2005;43(6):616-626. doi:10.1097/01.mlr.0000163661.67170.b9PubMedGoogle ScholarCrossref
19.
Seers  K, Rycroft-Malone  J, Cox  K,  et al.  Facilitating Implementation of Research Evidence (FIRE): an international cluster randomised controlled trial to evaluate two models of facilitation informed by the Promoting Action on Research Implementation in Health Services (PARIHS) framework.  Implement Sci. 2018;13(1):137. doi:10.1186/s13012-018-0831-9PubMedGoogle ScholarCrossref
20.
Lohfeld  L, Loeb  M, Brazil  K.  Evidence-based clinical pathways to manage urinary tract infections in long-term care facilities: a qualitative case study describing administrator and nursing staff views.  J Am Med Dir Assoc. 2007;8(7):477-484. doi:10.1016/j.jamda.2007.05.006PubMedGoogle ScholarCrossref
21.
Baskerville  NB, Liddy  C, Hogg  W.  Systematic review and meta-analysis of practice facilitation within primary care settings.  Ann Fam Med. 2012;10(1):63-74. doi:10.1370/afm.1312PubMedGoogle ScholarCrossref
22.
Wells  S, Tamir  O, Gray  J, Naidoo  D, Bekhit  M, Goldmann  D.  Are quality improvement collaboratives effective? A systematic review.  BMJ Qual Saf. 2018;27(3):226-240. doi:10.1136/bmjqs-2017-006926PubMedGoogle ScholarCrossref
23.
Ivers  N, Jamtvedt  G, Flottorp  S,  et al.  Audit and feedback: effects on professional practice and healthcare outcomes.  Cochrane Database Syst Rev. 2012;(6):CD000259. doi:10.1002/14651858.CD000259.pub3PubMedGoogle Scholar
24.
Curran  GM, Bauer  M, Mittman  B, Pyne  JM, Stetler  C.  Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact.  Med Care. 2012;50(3):217-226. doi:10.1097/MLR.0b013e3182408812PubMedGoogle ScholarCrossref
25.
Centers for Medicare & Medicaid Services; University of Minnesota; StratisHealth. QAPI at a glance: a step by step guide to implementing quality assurance and performance improvement (QAPI) in your nursing home. https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/QAPI/Downloads/QAPIAtaGlance.pdf. Accessed March 22, 2019.
26.
Eure  T, LaPlace  LL, Melchreit  R,  et al.  Measuring antibiotic appropriateness for urinary tract infections in nursing home residents.  Infect Control Hosp Epidemiol. 2017;38(8):998-1001. doi:10.1017/ice.2017.96PubMedGoogle ScholarCrossref
27.
Fries  BE, Schneider  DP, Foley  WJ, Gavazzi  M, Burke  R, Cornelius  E.  Refining a case-mix measure for nursing homes: Resource Utilization Groups (RUG-III).  Med Care. 1994;32(7):668-685. doi:10.1097/00005650-199407000-00002PubMedGoogle ScholarCrossref
28.
Schapira  MM, Shea  JA, Duey  KA, Kleiman  C, Werner  RM.  The nursing home compare report card: perceptions of residents and caregivers regarding quality ratings and nursing home choice.  Health Serv Res. 2016;51(suppl 2):1212-1228. doi:10.1111/1475-6773.12458PubMedGoogle ScholarCrossref
29.
Crnich  CJ, Dreis  M, Hess  T, Drinka  P, Zimmerman  DR. Patterns and discrepancies between different metrics of antibiotic use in nursing homes. Paper presented at: IDWeek 2012, a Joint Meeting of the Infectious Diseases Society of America, Society for Healthcare Epidemiology of America, HIV Medical Association, and Pediatric Infectious Disease Society; October 20, 2012; San Diego, CA.
30.
Fereday  J, Muir-Cochrane  E.  Demonstrating rigor using thematic analysis: a hybrid approach of inductive and deductive coding and theme development.  Int J Qual Methods. 2006;5(1):80-92. doi:10.1177/160940690600500107Google ScholarCrossref
31.
Carayon  P, Wetterneck  TB, Rivera-Rodriguez  AJ,  et al.  Human factors systems approach to healthcare quality and patient safety.  Appl Ergon. 2014;45(1):14-25. doi:10.1016/j.apergo.2013.04.023PubMedGoogle ScholarCrossref
32.
Wooldridge  AR, Carayon  P, Hundt  AS, Hoonakker  PLT.  SEIPS-based process modeling in primary care.  Appl Ergon. 2017;60:240-254. doi:10.1016/j.apergo.2016.11.010PubMedGoogle ScholarCrossref
33.
Bacci  JL, Coley  KC, McGrath  K, Abraham  O, Adams  AJ, McGivney  MS.  Strategies to facilitate the implementation of collaborative practice agreements in chain community pharmacies.  J Am Pharm Assoc (2003). 2016;56(3):257-265.e2. doi:10.1016/j.japh.2016.02.014PubMedGoogle ScholarCrossref
34.
Barker  AK, Krasity  B, Musuuza  J, Safdar  N.  Screening for asymptomatic Clostridium difficile among bone marrow transplant patients: a mixed-methods study of intervention effectiveness and feasibility.  Infect Control Hosp Epidemiol. 2018;39(2):177-185. doi:10.1017/ice.2017.286PubMedGoogle ScholarCrossref
35.
Katz  MJ, Gurses  AP, Tamma  PD, Cosgrove  SE, Miller  MA, Jump  RLP.  Implementing antibiotic stewardship in long-term care settings: an integrative review using a human factors approach.  Clin Infect Dis. 2017;65(11):1943-1951. doi:10.1093/cid/cix566PubMedGoogle ScholarCrossref
36.
Bond  C, Seneque  M.  Conceptualizing coaching as an approach to management and organizational development.  J Manage Dev. 2012;32:57-72. doi:10.1108/02621711311287026Google ScholarCrossref
37.
O’Cathain  A, Murphy  E, Nicholl  J.  Three techniques for integrating data in mixed methods studies.  BMJ. 2010;341:c4587. doi:10.1136/bmj.c4587PubMedGoogle ScholarCrossref
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    Views 886
    Original Investigation
    Infectious Diseases
    September 11, 2019

    Effect of a Standard vs Enhanced Implementation Strategy to Improve Antibiotic Prescribing in Nursing Homes: A Trial Protocol of the Improving Management of Urinary Tract Infections in Nursing Institutions Through Facilitated Implementation (IMUNIFI) Study

    Author Affiliations
    • 1School of Pharmacy, University of Wisconsin, Madison
    • 2School of Medicine and Public Health, University of Wisconsin, Madison
    • 3Center for Health Systems Research and Analysis, University of Wisconsin, Madison
    • 4Wisconsin Department of Health Services, Division of Quality Assurance, Bureau of Education Services & Technology, Madison
    • 5Marshfield Medical Center, Eau Claire, Wisconsin
    • 6Wisconsin Healthcare-Associated Infections in Long-Term Care Coalition, Madison
    • 7Aurora Health Care, West Allis, Wisconsin
    • 8William S. Middleton Veterans Administration Hospital, Madison, Wisconsin
    JAMA Netw Open. 2019;2(9):e199526. doi:10.1001/jamanetworkopen.2019.9526
    Key Points español 中文 (chinese)

    Question  Does external facilitation improve adoption and effects of a complex antibiotic stewardship intervention in nursing homes?

    Findings  This trial protocol describes a cluster-randomized hybrid type 2 effectiveness-implementation clinical trial of implementation of a multicomponent toolkit focused on improving the recognition and management of suspected urinary tract infection (UTI) in nursing homes. The trial seeks to evaluate whether delivery of external facilitation—coaching, collaborative learning, and peer comparison feedback—to implement this toolkit results in higher rates of toolkit adoption and reduced rates of urine testing and initiation of antibiotics for treatment of suspected UTI.

    Meaning  If successful, external facilitation could become an effective approach for improving spread and adoption of antibiotic stewardship interventions, as well as other quality improvement initiatives, in the nursing home setting.

    Abstract

    Importance  Suspicion of urinary tract infection (UTI) is the major driver of overuse and misuse of antibiotics in nursing homes (NHs). Effects of interventions to improve the recognition and management of UTI in NHs have been mixed, potentially owing to differences in how interventions were implemented in different studies. An improved understanding of how implementation approach influences intervention adoption is needed to achieve wider dissemination of antibiotic stewardship interventions in NHs.

    Objective  To compare the effects of 2 implementation strategies on the adoption and effects of a quality improvement toolkit to enhance recognition and management of UTIs in NHs.

    Design, Setting, and Participants  This cluster-randomized hybrid type 2 effectiveness-implementation clinical trial will be performed over a 6-month baseline (January to June 2019) and 12-month postimplementation period (July 2019 to June 2020). A minimum of 20 Wisconsin NHs with 50 or more beds will be recruited and randomized in block sizes of 2 stratified by rurality (rural vs urban). All residents who are tested and/or treated for UTI in study NHs will be included in the analysis. All study NHs will implement a quality improvement toolkit focused on enhancing the recognition and management of UTIs. Facilities will be randomized to either a usual or enhanced implementation approach based on external facilitation (coaching), collaborative peer learning, and peer comparison feedback. Enhanced implementation is hypothesized to be associated with improvements in adoption of the quality improvement toolkit and clinical outcomes. Primary outcomes of the study will include number of (1) urine cultures per 1000 resident days and (2) antibiotic prescriptions for treatment of suspected UTI per 1000 resident-days. Secondary outcomes of the study will include appropriateness of UTI treatments, treatment length, use of fluoroquinolones, and resident transfers and mortality. A mixed-methods evaluation approach will be used to assess extent and determinants of adoption of the UTI quality improvement toolkit in study NHs.

    Discussion  Knowledge gained during this study could help inform future efforts to implement antibiotic stewardship and quality improvement interventions in NHs.

    Trial Registration  ClinicalTrials.gov identifier: NCT03520010

    Introduction

    Antibiotics are among the most commonly prescribed medications in nursing homes (NHs). More than half of individuals who reside in an NH for 6 months or longer will be prescribed at least 1 course of antibiotics.1 Suspicion of urinary tract infection (UTI) is the most common trigger for prescription of antibiotics in NHs and the condition most commonly associated with inappropriate antibiotic use in these facilities.2 Improving the recognition and management of UTI has, therefore, been identified as a major need in NHs.3-5

    Recently, a stakeholder group comprising health care professionals from long-term care facilities as well as partners from academia and public health in Wisconsin6 have developed a quality improvement toolkit focused on enhancing staff and health care professional practices around recognition and management of UTI in NHs (hereafter, referred to as the Wisconsin UTI Improvement Toolkit). This toolkit is built around a previously published decision-support algorithm2 for managing suspected UTI and contains a number of tools and resources for improving the practice and interactions between nursing staff and health care professionals in situations in which UTI is suspected. Prior efforts to improve UTI recognition and management in NHs using decision support tools similar to those used in the Wisconsin UTI Improvement Toolkit have met with mixed results.7-12 The heterogeneous effects of behavioral interventions across different health care settings is not unique to NHs and likely reflects complexity in the interactions between the intervention, the context into which the intervention is being introduced, and the strategies used to facilitate its implementation.13 Despite improvements in specification of implementation strategies,14,15 knowledge about their mechanisms and effects on uptake of behavioral interventions remains rudimentary.16 The challenges of implementing behavioral interventions is particularly germane to NHs, which lack local access to individuals with expertise in quality improvement17 and face higher levels of staff turnover18 compared with other health care settings.

    Studies focused on implementation of quality improvement interventions in NHs are rare.19 While several studies have identified factors that have contributed to lack of fidelity to UTI improvement interventions in NHs,11,12,20 we are unaware of any studies that have explicitly studied the effects of different implementation strategies on UTI improvement intervention uptake in NHs. External facilitation (also referred to as practice facilitation or coaching),21 peer learning collaboratives (also referred to as quality improvement collaboratives),22 and peer comparison feedback23 are 3 implementation strategies that have been shown to positively affect uptake of behavioral interventions in health care settings. The Improving Management of UTIs in Nursing Institutions Through Facilitated Implementation (IMUNIFI) study described in this protocol is designed to test the hypothesis that an enhanced implementation approach based on these 3 implementation supports will be associated with greater adoption of the Wisconsin UTI Improvement Toolkit and improve its impact on targeted behavioral outcomes compared with a standard implementation approach that does not include these additional supports.

    Methods
    Study Aims

    The first aim of the study is to assess the effect of the Wisconsin UTI Improvement Toolkit on the recognition and management of UTI in a sample of Midwestern NHs. Measures of testing (urine culture order rate) and treatment (UTI treatment rate) behaviors, which are the primary targets of the intervention, will be used to assess toolkit effects.

    The second aim of the study is to compare the effects of 2 different facilitation approaches on uptake and effectiveness of the Wisconsin UTI Improvement Toolkit. Study NHs will be randomly assigned to 1 of 2 facilitation approaches (usual vs enhanced), which are described further in this article. Primary outcome measures observed in each group will be compared to detect whether there are statistically significant differences between the 2 study implementation groups.

    Overall Study Design

    A hybrid type 2 effectiveness-implementation cluster randomized trial of NHs that have elected to implement the Wisconsin UTI Improvement Toolkit (Figure 1) will be used in this study. This design is appropriate when the objective is to evaluate clinical effects of an intervention and the influence of context and/or facilitation strategies on intervention adoption.24 Following a 6-month baseline period, study NHs will be randomized to either a usual (control) or enhanced implementation (intervention) group based on external facilitation, peer learning sessions, and peer comparison feedback. Implementation rollout will occur simultaneously in all NHs. The study will compare urine testing and UTI treatment rates in the 2 study groups. The extent and determinants of adoption of the Wisconsin UTI Improvement Toolkit in study NHs will be assessed using a mixed-methods approach. The full trial protocol is available in Supplement 1.

    Ethical Considerations

    The Human Subjects Institutional Review Board at the University of Wisconsin School of Medicine and Public Health approved this study protocol. Given the focus on quality improvement that targets health care practitioners, a waiver of informed consent was requested and approved.

    Participants

    Nursing staff and practitioners in study NHs are the targets of the Wisconsin UTI Toolkit Improvement intervention. While not primary targets, all residents of NHs who develop a change-in-condition potentially caused by a UTI will potentially be affected by the intervention.

    Setting

    At least 20 Wisconsin NHs, purposively selected for their geographic location across the state and to achieve a balance between rural and urban facilities, will be recruited. The rationale for this sampling approach is that rural NHs are less likely to be members of an NH network and may have limited access to improvement resources and expertise. This approach will enhance our capacity to identify barriers to implementation and further disseminate the toolkit. Facilities will be recruited through a listserv maintained by the Wisconsin Department of Health Services and through referrals from members of for-profit and not-for-profit NH advocacy associations in Wisconsin.

    Inclusion Criteria

    Medicare- and Medicaid-certified NHs with 50 or more long-term care and skilled nursing beds in Wisconsin will be eligible for this study. The NHs that agree to participate will be asked to submit monthly data on facility urine cultures and UTI treatment events through a web-based portal designed for this study during a baseline period before implementing the Wisconsin UTI Improvement Toolkit. Facilities that demonstrate commitment by submitting 3 sequential months of preintervention data will remain eligible for randomization.

    Exclusion Criteria

    Facilities less than 50 beds in size, those that primarily provide advanced specialty care (ventilator or strict rehabilitation care), and assisted living facilities will be excluded. Nursing homes that otherwise meet inclusion criteria but fail to submit 3 sequential months of baseline data will not be randomized.

    Study Intervention

    The Wisconsin UTI Improvement Toolkit is a multicomponent suite of tools, resources, and best practices structured around a previously published decision support algorithm for managing suspected UTI.2 The behavioral objectives of the decision support algorithm used in the toolkit are similar to those used in other UTI improvement interventions previously tested in the NH setting.7-12

    The components of the toolkit focus on enhancing the development of professional human resources in NHs and target both nursing staff and clinicians. The tools and resources that compose the Wisconsin UTI Improvement Toolkit are arranged in modules that focus on different aspects of UTI recognition and management (Table 1). The behavioral objectives of the toolkit are to (1) improve nursing staff assessment of residents experiencing a change in condition potentially attributable to UTI; (2) improve the quality of interprofessional communication when a diagnosis of UTI is being considered; (3) ensure that nursing staff and clinicians ascertain the likelihood of UTI (low vs high probability); (4) defer urine testing and antibiotic therapy when the probability of UTI is low; and (5) prescribe antibiotics appropriately (choice of agent and treatment duration) when the probability of UTI is high (Figure 2).

    Study Implementation Groups
    Usual Implementation

    Study NHs randomized to the usual implementation (control) will participate in a kickoff meeting. The meeting will introduce the different toolkit components and address concepts germane to implementation and their relationship to the NH Quality Assessment Process Improvement (QAPI) process.25 These NHs will have ongoing access to online training resources and improvement tools, including a web-based tool for tracking and visualizing facility urine culture and UTI treatment rates. Study NHs assigned to the usual implementation group will be able to contact the research team with questions but will not receive additional support (Table 2).

    Enhanced Implementation

    Study NHs randomized to the enhanced implementation (intervention) group will attend the same kickoff meeting and have access to the same online resources, but will also (1) be assigned a clinical coach, (2) have the opportunity to participate in peer learning activities, and (3) receive peer comparison feedback reports. The coaching support will be delivered by a trained nurse through regular telephone calls with a study NH staff member responsible for local implementation of the UTI toolkit (referred to as an internal champion). Initial calls will focus on reviewing current UTI diagnosis- and management-related workflows and identification of opportunities to integrate different aspects of the Wisconsin UTI Improvement Toolkit. Subsequent calls will focus on reinforcing important aspects of the QAPI process, including (1) establishing a change team; (2) identifying barriers and facilitators to change; (3) reviewing and interpreting primary outcomes feedback reports; (4) identifying and prioritizing future change efforts; and (5) developing a plan to sustain improvement efforts. The peer learning support will be delivered through quarterly webinars in which NH champions will be encouraged to discuss successes and challenges and share strategies for implementing the toolkit. The peer comparison feedback support will be delivered through the web-based data tracking and visualization tool described. Nursing homes assigned to the enhanced implementation group will be able to visualize their performance over time and see how they are performing relative to other participating NHs (Table 2).

    Study Outcomes
    Primary Outcomes

    Urine culture orders per 1000 resident-days and antibiotic prescriptions for treatment of suspected UTI per 1000 resident-days will be the co–primary outcomes assessed. Urine cultures triggered by an abnormal urinalysis result, even if obtained for reasons other than suspicion of UTI, will be included as an outcome. The treatment indication included in clinician orders and documentation will be used to define antibiotic prescriptions for treatment of suspected UTI (Table 3).

    Secondary Outcomes

    The secondary clinical outcomes will include (1) days of therapy for treatment of suspected UTI per 1000 resident-days; (2) fluoroquinolone antibiotic prescriptions and days of therapy per 1000 resident-days for treatment of suspected UTI; (3) percentage of urine cultures meeting Wisconsin UTI Improvement Toolkit criteria; (4) percentage of antibiotic prescriptions for UTI meeting the Wisconsin UTI Improvement Toolkit criteria2,26; (5) percentage of urine cultures positive for bacteria resistant to common first-line and second-line oral antibiotics; (6) Clostridioides difficile–positive tests per 1000 resident-days; (7) transfers to hospitals or emergency departments per 1000 resident-days; and (8) resident deaths per 1000 resident-days.

    Measures of adoption of the Wisconsin UTI Improvement Toolkit in study NHs will include (1) staff participation in study meetings and coaching calls; (2) consistency of clinical data submission; (3) toolkit website use; (4) intensity of staff and clinician education; (5) use of intervention tools; and (6) knowledge, attitudes, and perceptions about the toolkit. Potential determinants of adoption of the Wisconsin UTI Improvement Toolkit, including barriers and facilitators, will be elicited from nursing staff, clinicians, and facility leadership (referred to as key informants) (Table 3).

    Data Collection Methods

    A mixed-methods approach will be used to collect data in this study. Information sources will include (1) data submitted through the web-based data portal; (2) surveys administered to internal champions, nursing staff, and clinicians; (3) aggregated data obtained from pertinent administrative, laboratory, and pharmacy records; and (4) interviews and focus groups with key informants in study NHs. Table 3 provides a summary of study outcomes and the data sources used to derive these outcomes. A detailed description of the project key tasks and timeline is given in the eTable in Supplement 2.

    Facility Demographic Characteristics

    Each study NH will complete a facility-level survey that captures information on characteristics of leadership as well as structure and process of existing antibiotic stewardship and infection prevention efforts. Additional information on geographic location, bed size, ownership status, skilled services provided (eg, parenteral therapy and wound care), resident complexity,27 staffing turnover and retention measures, and Medicare star rating28 will be abstracted from existing state and national administrative data records. Frontline nursing staff in study NHs will be asked to complete a survey on existing team climate and aspects of communication around identification and reporting of changes in condition of residents that may require antibiotic therapy. This survey will be administered at the time of randomization as well as 6 and 12 months following implementation of the Wisconsin UTI Improvement Toolkit.

    Clinical Outcomes

    The internal champion from each study NH will submit data on the number of resident-days, urine cultures, antibiotic prescriptions, and clinical information to ascertain if these meet Wisconsin appropriateness criteria via a web-based data submission portal on a monthly basis. Champions will be trained to use the data submission portal via a webinar. The portal will include frequently asked questions and help desk access for technical issues related to data submission. Each NH will be asked to submit test records, and members of the research team will follow up with NHs to identify problems with data submission prior to randomization.

    The research team will obtain aggregate data on antibiotic prescriptions from the consultant pharmacist to determine days of antibiotic therapy ordered per 1000 resident-days as well as the fluoroquinolone prescriptions and days of fluoroquinolone antibiotic therapy ordered. Deidentified aggregate data on urine culture results from laboratories used by study NHs will be obtained to cross-validate self-reported rates of urine culture orders and characterize antibiotic resistance patterns. Results for C difficile tests at a facility level will be obtained in a similar manner. The research team will work with facility administrative staff to collect data on monthly rates of resident transfers and mortality.

    Measures and Determinants of Toolkit Adoption

    Webinar and meeting attendance as well as coaching call records will be used to measure study NH participation in group and coaching call activities. Weblogs will be used to measure consistency of study NH data submission and frequency with which staff access the different training modules within the UTI toolkit and review their feedback reports as well as other components of the IMUNIFI website.

    A survey instrument will be used to assess (1) intensity of staff education activities; (2) reported use of different toolkit resources (informational posters, family and practitioner educational materials, and decision aids); (3) staff perceptions about the usefulness and effects of the Wisconsin UTI Improvement Toolkit; and (4) staff perceptions about the likelihood of sustaining the intervention. The survey instrument will be administered to frontline nursing staff (registered nurses and licensed practical nurses) via email during months 6 and 12 of the postimplementation period. A second email followed by telephone calls to facility leadership will be used to enhance survey response. Based on facility staffing levels and a projected response rate of 50%, we anticipate that 160 surveys will be completed at each point.

    Interviews with key informants in 3 to 4 high- and low-performing study NHs, determined by rank order of the primary study outcomes, will be performed to identify specific barriers and facilitators to implementation of the Wisconsin UTI Improvement Toolkit. Information from logs created during coaching calls will be used to identify common challenges to implementation encountered in NHs assigned to the enhanced implementation arm of the study and the types and effectiveness of strategies that the internal champion and coaches had codeveloped to overcome these challenges.

    Statistical Analysis
    Sample Size

    Based on data previously collected by our group,29 the expected rate of UTI treatment is approximately 4.0 per 1000 resident-days. Assuming 10 facilities of equal cluster sizes in each study group and an intraclass correlation (ρ) of 0.49, we estimate our study will have 90% power to detect a 15% reduction in the UTI treatment rate (antibiotic prescriptions for UTI per 1000 resident-days). We plan to recruit at least 35 NHs and randomize at least 26 NHs to account for a 25% facility dropout rate before and after randomization.

    Randomization

    Randomization will be computer generated and stratified based on geographic location (urban vs rural) in block sizes of 2. An individual uninvolved with the study will be responsible for generating the randomization and allocation of NHs to the 2 treatment groups of the study. Given the nature of the intervention, neither the participants nor the investigators will be blinded during this study.

    Analyses of Clinical Outcomes

    Generalized estimating equations using segmented regression and a Poisson distribution accounting for autocorrelation of data within facilities will be used to evaluate the 2 primary outcomes across all study sites in aggregate. Four estimates from these models will be evaluated: (1) the preintervention trend (β1); (2) the immediate change in the outcomes following the kickoff webinar (β2); (3) the difference between preimplementation and postimplementation trend (β3); and (4) the postimplementation outcome rate change (β1 + β3). First- and second-order autocorrelation will be assessed using the Durbin-Watson statistic. Robust standard errors will be used to estimate variance. Similar generalized linear models will be fit to analyze secondary and safety outcomes. To assess the effect of enhanced implementation on the effectiveness of the toolkit, the segmented regression model developed will be extended to include a covariate for the study implementation group (usual implementation = 0; enhanced implementation = 1). We will explore adding control variables into our models if significant imbalances in NH characteristics (eg, size, staffing ratios, profit status, geographic location, Centers for Medicare & Medicaid Services 5-star rating) and level of intervention adoption (described in the following section) are identified in our preliminary analyses.

    Analyses of Toolkit Adoption Measures and Determinants

    Data from study event attendance records, weblogs of toolkit website use, frontline staff responses to survey questions focused on familiarity, and use of the different toolkit elements will be integrated into a measure that stratifies randomized NHs into 3 levels of intervention adoption (high, medium, and low). The generalized estimating equation models described above will be extended by including the facility adoption measure as an independent variable to assess the relationships between toolkit adoption and the primary and secondary study outcomes.

    Determinants of toolkit adoption will be identified through qualitative analyses of key informant interviews and coach notes. Interviews with key informants in high- and low-performing NHs will be recorded, deidentified, and transcribed verbatim. A mixed deductive and inductive thematic analysis30 guided by the Systems Engineering Initiative for Patient Safety framework31 will be used to analyze interview data. The Systems Engineering Initiative for Patient Safety framework is a human factors engineering framework that has been used extensively in a variety of health care settings to characterize work systems and document changes to the work system following implementation of quality improvement interventions.32-35 Interview transcripts will be coded independently with tests for reliability. Analyses will focus on identifying the changes (or lack thereof) that occurred in study NH work systems as a result of implementing the Wisconsin UTI Toolkit in an effort to identify key barriers and facilitators to adoption. A similar approach will be used in the analyses of coach notes to assess the effects of coaching on toolkit adoption. We will use the comparative conceptual framework proposed by Bond and Seneque,36 which suggests that organizational coaching occurs across 1 of 5 domains (managerial, consulting, mentoring, facilitating, or coaching), to classify the advice provided during the coaching interactions. Members of the research team will attempt to integrate information from the different data sources using a triangulation approach37 to better explain the relationships between the 2 implementation approaches, adoption of the Wisconsin UTI Improvement Toolkit, and observed effects on clinical outcomes.

    Discussion

    During this project, we expect to demonstrate significant reductions in antibiotic use for treatment of suspected UTI in study NHs following adoption of the Wisconsin UTI Improvement Toolkit. We also expect that NHs that receive externally facilitated support during the implementation of the toolkit will demonstrate greater levels of adoption as well as greater reductions in urine culture testing and antibiotic use compared with NHs that receive usual support during implementation. We further expect to generate important information on the types of barriers NHs encountered during the implementation and the strategies they found to be most successful for overcoming these barriers. Finally, we expect to generate knowledge on the mechanisms by which enhanced implementation influenced adoption of the Wisconsin UTI Improvement Toolkit and, in turn, the influence of adoption on clinical outcomes in study NHs.

    At project conclusion, we will have (1) assessed the effects of enhanced implementation on adoption of evidence-based antibiotic stewardship practices in Wisconsin NHs and (2) determined the key facilitators and barriers associated with the 2 implementation approaches used. The knowledge generated from this project could benefit subsequent projects focused on dissemination of the Wisconsin UTI Improvement Toolkit to other facilities in the state and facilitating implementation of other types of interventions to improve the quality of antibiotic prescribing in NHs. The intervention implemented in this study is complex and our findings may not be applicable to the implementation of simple interventions. However, many of the problems encountered in NHs are complex in nature, including other medication safety problems (eg, antipsychotic medications), care transitions, and fall prevention. Consequently, we believe this study will generate knowledge that can support the implementation of interventions to address these, as well as other, important problems.

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    Article Information

    Accepted for Publication: June 24, 2019.

    Published: September 11, 2019. doi:10.1001/jamanetworkopen.2019.9526

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Ford JH II et al. JAMA Network Open.

    Corresponding Author: Christopher J. Crnich, MD, PhD, School of Medicine and Public Health, University of Wisconsin, 2500 Overlook Terr, 5112E, Madison, WI 53705 (cjc@medicine.wisc.edu).

    Author Contributions: Drs Ford and Crnich had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Ford and Crnich contributed equally to this work.

    Concept and design: Ford, Vranas, Coughlin, Selle, Ryther, Griffin, Eslinger, Boero, Hardgrove, Crnich.

    Acquisition, analysis, or interpretation of data: Nordman-Oliveira, Ewers, Eslinger.

    Drafting of the manuscript: Ford, Vranas, Eslinger, Boero, Crnich.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Ewers, Crnich.

    Obtained funding: Ford, Crnich.

    Administrative, technical, or material support: Ford, Vranas, Coughlin, Nordman-Oliveira, Ryther, Ewers, Griffin, Eslinger, Boero, Crnich.

    Supervision: Nordman-Oliveira, Crnich.

    Conflict of Interest Disclosures: Ms Nordman-Oliveira reported grants from the University of Wisconsin (UW) Madison and the UW School of Medicine and Public Health and contracts from the Wisconsin Department of Health Services during the conduct of the study. Dr Crnich reported grants from the UW School of Medicine and Public Health, the Centers for Disease Control and Prevention, the Agency for Healthcare Research and Quality, and the Veterans Administration Health Services Research and Development during the conduct of the study. No other disclosures were reported.

    Funding/Support: This work was supported by the UW School of Medicine and Public Health through a grant from the Wisconsin Partnership Program (Collaborative Health Sciences Program).

    Role of the Funder/Sponsor: The funders/sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    References
    1.
    Crnich  CJ, Jump  R, Trautner  B, Sloane  PD, Mody  L.  Optimizing antibiotic stewardship in nursing homes: a narrative review and recommendations for improvement.  Drugs Aging. 2015;32(9):699-716. doi:10.1007/s40266-015-0292-7PubMedGoogle ScholarCrossref
    2.
    Crnich  CJ, Drinka  P.  Improving the management of urinary tract infections in nursing homes: it’s time to stop the tail from wagging the dog.  Ann Longterm Care. 2014;22(9):32-36.Google Scholar
    3.
    Nace  DA, Drinka  PJ, Crnich  CJ.  Clinical uncertainties in the approach to long term care residents with possible urinary tract infection.  J Am Med Dir Assoc. 2014;15(2):133-139. doi:10.1016/j.jamda.2013.11.009PubMedGoogle ScholarCrossref
    4.
    van Buul  LW, Veenhuizen  RB, Achterberg  WP,  et al.  Antibiotic prescribing in Dutch nursing homes: how appropriate is it?  J Am Med Dir Assoc. 2015;16(3):229-237. doi:10.1016/j.jamda.2014.10.003PubMedGoogle ScholarCrossref
    5.
    Finucane  TE.  “Urinary tract infection”—requiem for a heavyweight.  J Am Geriatr Soc. 2017;65(8):1650-1655. doi:10.1111/jgs.14907PubMedGoogle ScholarCrossref
    6.
    Center for Health Systems Research and Analysis. Wisconsin long-term care urinary tract infection toolkit. https://crc.chsra.wisc.edu/uti-toolkit/index.php. Updated June 2019. Accessed June 10, 2019.
    7.
    Loeb  M, Brazil  K, Lohfeld  L,  et al.  Effect of a multifaceted intervention on number of antimicrobial prescriptions for suspected urinary tract infections in residents of nursing homes: cluster randomised controlled trial.  BMJ. 2005;331(7518):669. doi:10.1136/bmj.38602.586343.55PubMedGoogle ScholarCrossref
    8.
    Zabarsky  TF, Sethi  AK, Donskey  CJ.  Sustained reduction in inappropriate treatment of asymptomatic bacteriuria in a long-term care facility through an educational intervention.  Am J Infect Control. 2008;36(7):476-480. doi:10.1016/j.ajic.2007.11.007PubMedGoogle ScholarCrossref
    9.
    Zimmerman  S, Sloane  PD, Bertrand  R,  et al.  Successfully reducing antibiotic prescribing in nursing homes.  J Am Geriatr Soc. 2014;62(5):907-912. doi:10.1111/jgs.12784PubMedGoogle ScholarCrossref
    10.
    Trautner  BW, Grigoryan  L, Petersen  NJ,  et al.  Effectiveness of an antimicrobial stewardship approach for urinary catheter-associated asymptomatic bacteriuria.  JAMA Intern Med. 2015;175(7):1120-1127. doi:10.1001/jamainternmed.2015.1878PubMedGoogle ScholarCrossref
    11.
    van Buul  LW, van der Steen  JT, Achterberg  WP,  et al.  Effect of tailored antibiotic stewardship programmes on the appropriateness of antibiotic prescribing in nursing homes.  J Antimicrob Chemother. 2015;70(7):2153-2162. doi:10.1093/jac/dkv051PubMedGoogle Scholar
    12.
    McMaughan  DK, Nwaiwu  O, Zhao  H,  et al.  Impact of a decision-making aid for suspected urinary tract infections on antibiotic overuse in nursing homes.  BMC Geriatr. 2016;16:81. doi:10.1186/s12877-016-0255-9PubMedGoogle ScholarCrossref
    13.
    Kitson  A, Harvey  G, McCormack  B.  Enabling the implementation of evidence based practice: a conceptual framework.  Qual Health Care. 1998;7(3):149-158. doi:10.1136/qshc.7.3.149PubMedGoogle ScholarCrossref
    14.
    Damschroder  LJ, Aron  DC, Keith  RE, Kirsh  SR, Alexander  JA, Lowery  JC.  Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science.  Implement Sci. 2009;4:50. doi:10.1186/1748-5908-4-50PubMedGoogle ScholarCrossref
    15.
    Powell  BJ, Waltz  TJ, Chinman  MJ,  et al.  A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project.  Implement Sci. 2015;10:21. doi:10.1186/s13012-015-0209-1PubMedGoogle ScholarCrossref
    16.
    Lewis  CC, Klasnja  P, Powell  BJ,  et al.  From classification to causality: advancing understanding of mechanisms of change in implementation science.  Front Public Health. 2018;6:136. doi:10.3389/fpubh.2018.00136PubMedGoogle ScholarCrossref
    17.
    Rantz  MJ, Zwygart-Stauffacher  M, Flesner  M,  et al.  Challenges of using quality improvement methods in nursing homes that “need improvement”.  J Am Med Dir Assoc. 2012;13(8):732-738. doi:10.1016/j.jamda.2012.07.008PubMedGoogle ScholarCrossref
    18.
    Castle  NG, Engberg  J.  Staff turnover and quality of care in nursing homes.  Med Care. 2005;43(6):616-626. doi:10.1097/01.mlr.0000163661.67170.b9PubMedGoogle ScholarCrossref
    19.
    Seers  K, Rycroft-Malone  J, Cox  K,  et al.  Facilitating Implementation of Research Evidence (FIRE): an international cluster randomised controlled trial to evaluate two models of facilitation informed by the Promoting Action on Research Implementation in Health Services (PARIHS) framework.  Implement Sci. 2018;13(1):137. doi:10.1186/s13012-018-0831-9PubMedGoogle ScholarCrossref
    20.
    Lohfeld  L, Loeb  M, Brazil  K.  Evidence-based clinical pathways to manage urinary tract infections in long-term care facilities: a qualitative case study describing administrator and nursing staff views.  J Am Med Dir Assoc. 2007;8(7):477-484. doi:10.1016/j.jamda.2007.05.006PubMedGoogle ScholarCrossref
    21.
    Baskerville  NB, Liddy  C, Hogg  W.  Systematic review and meta-analysis of practice facilitation within primary care settings.  Ann Fam Med. 2012;10(1):63-74. doi:10.1370/afm.1312PubMedGoogle ScholarCrossref
    22.
    Wells  S, Tamir  O, Gray  J, Naidoo  D, Bekhit  M, Goldmann  D.  Are quality improvement collaboratives effective? A systematic review.  BMJ Qual Saf. 2018;27(3):226-240. doi:10.1136/bmjqs-2017-006926PubMedGoogle ScholarCrossref
    23.
    Ivers  N, Jamtvedt  G, Flottorp  S,  et al.  Audit and feedback: effects on professional practice and healthcare outcomes.  Cochrane Database Syst Rev. 2012;(6):CD000259. doi:10.1002/14651858.CD000259.pub3PubMedGoogle Scholar
    24.
    Curran  GM, Bauer  M, Mittman  B, Pyne  JM, Stetler  C.  Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact.  Med Care. 2012;50(3):217-226. doi:10.1097/MLR.0b013e3182408812PubMedGoogle ScholarCrossref
    25.
    Centers for Medicare & Medicaid Services; University of Minnesota; StratisHealth. QAPI at a glance: a step by step guide to implementing quality assurance and performance improvement (QAPI) in your nursing home. https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/QAPI/Downloads/QAPIAtaGlance.pdf. Accessed March 22, 2019.
    26.
    Eure  T, LaPlace  LL, Melchreit  R,  et al.  Measuring antibiotic appropriateness for urinary tract infections in nursing home residents.  Infect Control Hosp Epidemiol. 2017;38(8):998-1001. doi:10.1017/ice.2017.96PubMedGoogle ScholarCrossref
    27.
    Fries  BE, Schneider  DP, Foley  WJ, Gavazzi  M, Burke  R, Cornelius  E.  Refining a case-mix measure for nursing homes: Resource Utilization Groups (RUG-III).  Med Care. 1994;32(7):668-685. doi:10.1097/00005650-199407000-00002PubMedGoogle ScholarCrossref
    28.
    Schapira  MM, Shea  JA, Duey  KA, Kleiman  C, Werner  RM.  The nursing home compare report card: perceptions of residents and caregivers regarding quality ratings and nursing home choice.  Health Serv Res. 2016;51(suppl 2):1212-1228. doi:10.1111/1475-6773.12458PubMedGoogle ScholarCrossref
    29.
    Crnich  CJ, Dreis  M, Hess  T, Drinka  P, Zimmerman  DR. Patterns and discrepancies between different metrics of antibiotic use in nursing homes. Paper presented at: IDWeek 2012, a Joint Meeting of the Infectious Diseases Society of America, Society for Healthcare Epidemiology of America, HIV Medical Association, and Pediatric Infectious Disease Society; October 20, 2012; San Diego, CA.
    30.
    Fereday  J, Muir-Cochrane  E.  Demonstrating rigor using thematic analysis: a hybrid approach of inductive and deductive coding and theme development.  Int J Qual Methods. 2006;5(1):80-92. doi:10.1177/160940690600500107Google ScholarCrossref
    31.
    Carayon  P, Wetterneck  TB, Rivera-Rodriguez  AJ,  et al.  Human factors systems approach to healthcare quality and patient safety.  Appl Ergon. 2014;45(1):14-25. doi:10.1016/j.apergo.2013.04.023PubMedGoogle ScholarCrossref
    32.
    Wooldridge  AR, Carayon  P, Hundt  AS, Hoonakker  PLT.  SEIPS-based process modeling in primary care.  Appl Ergon. 2017;60:240-254. doi:10.1016/j.apergo.2016.11.010PubMedGoogle ScholarCrossref
    33.
    Bacci  JL, Coley  KC, McGrath  K, Abraham  O, Adams  AJ, McGivney  MS.  Strategies to facilitate the implementation of collaborative practice agreements in chain community pharmacies.  J Am Pharm Assoc (2003). 2016;56(3):257-265.e2. doi:10.1016/j.japh.2016.02.014PubMedGoogle ScholarCrossref
    34.
    Barker  AK, Krasity  B, Musuuza  J, Safdar  N.  Screening for asymptomatic Clostridium difficile among bone marrow transplant patients: a mixed-methods study of intervention effectiveness and feasibility.  Infect Control Hosp Epidemiol. 2018;39(2):177-185. doi:10.1017/ice.2017.286PubMedGoogle ScholarCrossref
    35.
    Katz  MJ, Gurses  AP, Tamma  PD, Cosgrove  SE, Miller  MA, Jump  RLP.  Implementing antibiotic stewardship in long-term care settings: an integrative review using a human factors approach.  Clin Infect Dis. 2017;65(11):1943-1951. doi:10.1093/cid/cix566PubMedGoogle ScholarCrossref
    36.
    Bond  C, Seneque  M.  Conceptualizing coaching as an approach to management and organizational development.  J Manage Dev. 2012;32:57-72. doi:10.1108/02621711311287026Google ScholarCrossref
    37.
    O’Cathain  A, Murphy  E, Nicholl  J.  Three techniques for integrating data in mixed methods studies.  BMJ. 2010;341:c4587. doi:10.1136/bmj.c4587PubMedGoogle ScholarCrossref
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