Mary C. Ruhe

A clinical trial of tailored office systems for preventive service delivery: The Study to Enhance Prevention by Understanding Practice (STEP-UP)

BACKGROUND The potential of primary care practice settings to prevent disease and morbidity through health habit counseling, screening for asymptomatic disease, and immunizations has been incompletely met. This study was designed to test a practice-tailored approach to increasing preventive service delivery with particular emphasis on health habit counseling. DESIGN Group randomized clinical trial and multimethod process assessment. SETTING/PARTICIPANTS Seventy-seven community family practices in northeast Ohio. INTERVENTION After a 1-day practice assessment, a nurse facilitator met with practice clinicians and staff and assisted them with choosing and implementing individualized tools and approaches aimed at increasing preventive service delivery. MAIN OUTCOME MEASURE Summary scores of the health habit counseling, screening and immunization services recommended by the U.S. Preventive Services Task Force up to date for consecutive patients during randomly selected chart review days. RESULTS A significant increase (p=0.015) in global preventive service delivery rates at the 1-year follow-up was found in the intervention group (31% to 42%) compared to the control group (35% to 37%). Rates specifically for health habit counseling (p=0.007) and screening services (p=0.048) were increased, but not for immunizations. CONCLUSIONS An approach to increasing preventive service delivery that is individualized to meet particular practice needs can increase global preventive service delivery rates.

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 tbo 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.

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.

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 (α = .94). A Rasch model-derived capacity for change score correlated well with an independently determined, qualitatively derived summary assessment of each practices capacity for change (ρS = 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.

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.

Modeling the Paradox of Primary Care

A paradox exists in the outcomes of primary care: despite delivering apparently poorer quality disease care compared to that delivered by specialists, primary care is associated with better population health, lower inequality, and lower cost. Understanding the dynamics that give rise to this paradox could lead to better-informed interventions to promote more patient-centered, holistic, equitable, and cost-effective models of care. In this chapter, we articulate the paradox and how complexity science principles can make sense of its contradictions. We suggest a novel approach to advancing understanding through a participatory group modeling process to build and conduct experiments with an agent-based computational model.

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). Spearmans 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.