Practice-tailored facilitation to improve pediatric preventive care delivery: a randomized trial.

OBJECTIVE: Evolving primary care models require methods to help practices achieve quality standards. This study assessed the effectiveness of a Practice-Tailored Facilitation Intervention for improving delivery of 3 pediatric preventive services. METHODS: In this cluster-randomized trial, a practice facilitator implemented practice-tailored rapid-cycle feedback/change strategies for improving obesity screening/counseling, lead screening, and dental fluoride varnish application. Thirty practices were randomized to Early or Late Intervention, and outcomes assessed for 16 419 well-child visits. A multidisciplinary team characterized facilitation processes by using comparative case study methods. RESULTS: Baseline performance was as follows: for Obesity: 3.5% successful performance in Early and 6.3% in Late practices, P = .74; Lead: 62.2% and 77.8% success, respectively, P = .11; and Fluoride: <0.1% success for all practices. Four months after randomization, performance rose in Early practices, to 82.8% for Obesity, 86.3% for Lead, and 89.1% for Fluoride, all P < .001 for improvement compared with Late practices' control time. During the full 6-month intervention, care improved versus baseline in all practices, for Obesity for Early practices to 86.5%, and for Late practices 88.9%; for Lead for Early practices to 87.5% and Late practices 94.5%; and for Fluoride, for Early practices to 78.9% and Late practices 81.9%, all P < .001 compared with baseline. Improvements were sustained 2 months after intervention. Successful facilitation involved multidisciplinary support, rapid-cycle problem solving feedback, and ongoing relationship-building, allowing individualizing facilitation approach and intensity based on 3 levels of practice need. CONCLUSIONS: Practice-tailored Facilitation Intervention can lead to substantial, simultaneous, and sustained improvements in 3 domains, and holds promise as a broad-based method to advance pediatric preventive care.

Boundary spanning and health: invitation to a learning community.

Boundaries, which are essential for the healthy functioning of individuals and organisations, can become problematic when they limit creative thought and action. In this article, we present a framework for promoting health across boundaries and summarise preliminary insights from experience, conversations and reflection on how the process of boundary spanning may affect health. Boundary spanning requires specific individual qualities and skills. It can be facilitated or thwarted by organisational context. Boundary spanning often involves risk, but may reap abundant rewards. Boundary spanning is necessary to optimise health and health care. Exploring the process, the landscape and resources that enable boundary spanning may yield new opportunities for advancing health. We invite boundary spanners to join in a learning community to advance understanding and health.

Appreciative Inquiry for quality improvement in primary care practices.

PURPOSE: To test the effect of an Appreciative Inquiry (AI) quality improvement strategy on clinical quality management and practice development outcomes. Appreciative inquiry enables the discovery of shared motivations, envisioning a transformed future, and learning around the implementation of a change process. METHODS: Thirty diverse primary care practices were randomly assigned to receive an AI-based intervention focused on a practice-chosen topic and on improving preventive service delivery (PSD) rates. Medical-record review assessed change in PSD rates. Ethnographic field notes and observational checklist analysis used editing and immersion/crystallization methods to identify factors affecting intervention implementation and practice development outcomes. RESULTS: The PSD rates did not change. Field note analysis suggested that the intervention elicited core motivations, facilitated development of a shared vision, defined change objectives, and fostered respectful interactions. Practices most likely to implement the intervention or develop new practice capacities exhibited 1 or more of the following: support from key leader(s), a sense of urgency for change, a mission focused on serving patients, health care system and practice flexibility, and a history of constructive practice change. CONCLUSIONS: An AI approach and enabling practice conditions can lead to intervention implementation and practice development by connecting individual and practice strengths and motivations to the change objective.

A systematic approach to practice assessment and quality improvement intervention tailoring.

BACKGROUND: The ways in which tailored interventions foster sustained improvement in the quality of health care delivery across different practice settings are not well understood. Using the empirically developed Practice Change Model (PCM), we identify and describe assessment and tailoring activities with potential to enhance the fit between proposed interventions and practice settings. METHODS: We obtained quantitative and qualitative data from 2 quality improvement trials conducted in diverse primary care practices in northeast Ohio. A multidisciplinary team used a PCM-based template to identify features of practice assessment and tailoring associated with practices' willingness and ability to change. RESULTS: Our results suggest that intervention tailoring requires assessment of key stakeholders' motivations, external influences, resources and opportunities for change, and the interactions between these factors. Using this information, intervention tailoring then includes seeking and working with key stakeholders, building assets, providing options, keeping change processes flexible, offering feedback, providing exposure to scientific evidence, facilitating group processes, involving new partners, brainstorming, using stories/play acting/humor, assuming a consultant role, reframing, moving meetings off-site, and stepping back or pausing. CONCLUSIONS: A model-driven approach guiding practice assessment enables tailored responses to the unique and emerging conditions that distinguish health care practices and influence implementation of quality management interventions.

Measuring practice capacity for change: a tool for guiding quality improvement in primary care settings.

PURPOSE: Capacity for change, or the ability and willingness to undertake change, is an organizational characteristic with potential to foster quality management in health care. We report on the development and psychometric properties of a quantitative measure of capacity for change for use in primary care settings. METHODS: Following review of previous conceptual and empirical studies, we generated 117 items that assessed organizational structure, climate, and culture. Using information from direct observation and key informant interviews, a research team member rated these items for 15 primary care practices engaged in a quality improvement intervention. Distributional statistics, pairwise correlation analysis, Rasch modeling, and item content review guided item reduction and instrument finalization. Reliability and convergent validity were assessed. RESULTS: Ninety-two items were removed because of limited response distributions and redundancy or because of poor Rasch model fit. The final instrument comprising 25 items had excellent reliability (alpha = .94). A Rasch model-derived capacity for change score correlated well with an independently determined, qualitatively derived summary assessment of each practice's capacity for change (rhoS = 0.82), suggesting good convergent validity. CONCLUSION: We describe a new instrument for quantifying organizational capacity for change in primary care settings. The ability to quantify capacity for change may enable better recognition of practices likely to be successful in their change efforts and those first requiring capacity building prior to change interventions.

Making sense of primary care practices' capacity for change.

A deeper understanding of the forces that shape the motivation and willingness of primary care practices to adopt and implement new procedures-their "capacity for change"-may better guide development of interventions to foster adoption and implementation of evidence-based care. This study applies and evaluates the utility of a previously described framework for making sense of this complex construct in a diverse sample of primary care practices. A multidisciplinary team of 3 analysts examined ethnographic field notes that describe 15 single-physician or multiphysician practices in different organizational settings. Examples of the 4 components within the framework (ie, staff motivations, resources, opportunities for change, and external influences) and their interactions were identified. Cross-practice comparisons identified emerging themes relevant to capacity for change. Not surprisingly, variation among examples of individual components of change capacity across practices was present. Patterns among these components, however, seemed less informative in making sense of practices' capacity for change than patterns across component interactions. For example, the ability of practice members to recognize and act on opportunities for change seemed to be shaped by the extent to which motivations were broadly shared within the practice and by tangible and intangible resources (eg, leadership style, relationships among practice members, and financial resources of the practice). Revised operational definitions for framework components and careful reflection on the nature of their interactions helped make sense of practices' capacity for change in our sample and will enable future hypothesis testing to refine our understanding of factors that influence the translation of scientific knowledge in primary care settings.

Correlates of baseline performance do not predict results of an intervention to improve preventive care.

BACKGROUND: Cross-sectional analyses of baseline performance often inform the development of interventions to improve care. An implicit assumption in these studies is that factors associated with better performance at baseline may also be useful in predicting change in performance over time. METHODS: We analyzed data collected from 1997-2002 at 77 practices in Northeast Ohio participating in an intervention to increase evidence-based preventive services delivery (PSD). Spearman's correlation coefficients and multivariable models assessed associations between practice-level characteristics (e.g., organizational structure, objectives, climate, and culture) and baseline PSD, and with final PSD controlling for baseline values. Patterns of associations for both outcomes were inspected for overlap. RESULTS: The mean PSD rate was 36.8% (+/-8.8%) at baseline. This measure increased by an average of 4.9% (+/-6.3%) by the end of the intervention. Of eight practice characteristics correlated with either baseline performance or change from baseline in PSD, only two were common to both: characteristics associated with baseline PSD did not predict final PSD in multivariable models. CONCLUSIONS: Correlates of baseline performance differ from those related to change in performance. Practice assessments that focus on factors associated with change may be more useful in developing and implementing interventions to improve care.

Association of intervention outcomes with practice capacity for change: subgroup analysis from a group randomized trial.

BACKGROUND: The relationship between health care practices' capacity for change and the results and sustainability of interventions to improve health care delivery is unclear. METHODS: In the setting of an intervention to increase preventive service delivery (PSD), we assessed practice capacity for change by rating motivation to change and instrumental ability to change on a one to four scale. After combining these ratings into a single score, random effects models tested its association with change in PSD rates from baseline to immediately after intervention completion and 12 months later. RESULTS: Our measure of practices' capacity for change varied widely at baseline (range 2-8; mean 4.8 +/- 1.6). Practices with greater capacity for change delivered preventive services to eligible patients at higher rates after completion of the intervention (2.7% per unit increase in the combined effort score, p < 0.001). This relationship persisted for 12 months after the intervention ended (3.1%, p < 0.001). CONCLUSION: Greater capacity for change is associated with a higher probability that a practice will attain and sustain desired outcomes. Future work to refine measures of this practice characteristic may be useful in planning and implementing interventions that result in sustained, evidence-based improvements in health care delivery.

An appreciative inquiry approach to practice improvement and transformative change in health care settings.

Amid tremendous changes and widespread dissatisfaction with the current health care system, many approaches to improve practice have emerged; however, their effects on quality of care have been disappointing. This article describes the application of a new approach to promote organizational improvement and transformation that is built upon collective goals and personal motivations, invites participation at all levels of the organization and connected community, and taps into latent creativity and energy. The essential elements of the appreciative inquiry (AI) process include identification of an appreciative topic and acting on this theme through 4 steps: Discovery, Dream, Design, and Destiny. We describe each step in detail and provide a case study example, drawn from a composite of practices, to highlight opportunities and challenges that may be encountered in applying AI. AI is a unique process that offers practice members an opportunity to reflect on the existing strengths within the practice, leads them to discover what is important, and builds a collective vision of the preferred future. New approaches such as AI have the potential to transform practices, improve patient care, and enhance individual and group motivation by changing the way participants think about, approach, and envision the future.

Facilitating practice change: lessons from the STEP-UP clinical trial.

BACKGROUND: The Study To Enhance Prevention by Understanding Practice (STEP-UP) clinical trial (1997-2000) resulted in sustainable increases in preventive service delivery in primary care practices. However, the process by which practice change can be facilitated has not been well described. METHODS: Comparative case studies were conducted of eight STEP-UP practices with the largest increases in preventive service delivery rates and compared to seven practices with the lowest increases. A multidisciplinary team (research nurse, nurse facilitator, physician principal investigator) used an editing analysis approach to create individual case studies. Then, using an immersion-crystallization approach, the team identified pragmatic lessons for people working to improve primary care practice, and validated these lessons with a participating practice and an additional facilitator. RESULTS: It is not always possible to predict which practices will change based on understanding initial practice conditions. "Malleable moments" can be identified during which practices become open to change. It is important to tie change strategies with existing motivations, or to develop new motivation among potential change agents. Motivation can be developed by discrepant information that challenges self-image, aligning change plans with existing values, or identifying feasible ways of responding to outside pressures or internal demands. Instrumental interventions (such as office systems, tools, new processes) are useful when motivation to change exists, and can build motivation when they meet a perceived need. Disruption in previously workable approaches, either by purposeful information seeking or unanticipated changes, promotes openness to change. CONCLUSIONS: Despite limited ability to predict which practices will change and when, understanding practices' initial conditions and evolution can identify opportunities to craft individualized approaches to positive change.

Physician and staff turnover in community primary care practice.

The effect of a rapidly changing healthcare system on personnel turnover in community family practices has not been analyzed. We describe physician and staff turnover and examine its association with practice characteristics and patient outcomes. A cross-sectional evaluation of length of employment of 150 physicians and 762 staff in 77 community family practices in northeast Ohio was conducted. Research nurses collected data using practice genograms, key informant interviews, staff lists, practice environment checklists, medical record reviews, and patient questionnaires. The association of physician and staff turnover with practice characteristics, patient satisfaction, and preventive service data was tested. During a 2-year period, practices averaged a 53% turnover rate of staff. The mean length of duration of work at the current practice location was 9.1 years for physicians and 4.1 years for staff. Longevity varied by position, with a mean of 3.4 years for business employees, 4.0 years for clinical employees, and 7.8 years for office managers. Network-affiliated practices experienced higher turnover than did independent practices. Physician longevity was associated with a practice focus on managing chronic illness, keeping on schedule, and responding to insurers' requests. No association was found between turnover and patient satisfaction or preventive service delivery rates. Personnel turnover is pervasive in community primary care practices and is associated with employee role, practice network affiliation, and practice focus. The potentially disruptive effect of personnel turnover on practice functioning, finances, and longitudinal relationships with patients deserves further study despite the reassuring lack of association with patient satisfaction and preventive service delivery rates.

A practice change model for quality improvement in primary care practice.

Faced with a rapidly changing healthcare environment, primary care practices often have to change how they practice medicine. Yet change is difficult, and the process by which practice improvement can be understood and facilitated has not been well elucidated. Therefore, we developed a model of practice change using data from a quality improvement intervention that was successful in creating a sustainable practice improvement. A multidisciplinary team evaluated data from the Study To Enhance Prevention by Understanding Practice (STEP-UP), a randomized clinical trial conducted to improve the delivery of evidence-based preventive services in 79 northeastern Ohio practices. The team conducted comparative case-study analyses of high- and low-improvement practices to identify variables that are critical to the change process and to create a conceptual model for the change. The model depicts the critical elements for understanding and guiding practice change and emphasizes the importance of these elements' evolving interrelationships. These elements are (1) motivation of key stakeholders to achieve the target for change; (2) instrumental, personal, and interactive resources for change; (3) motivators outside the practice, including the larger healthcare environment and community; and (4) opportunities for change--that is, how key stakeholders understand the change options. Change is influenced by the complex interaction of factors inside and outside the practice. Interventions that are based on understanding the four key elements and their interrelationships can yield sustainable quality improvements in primary care practice.