Purposeful sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest. Although there are several different purposeful sampling strategies, criterion sampling appears to be used most commonly in implementation research. However, combining sampling strategies may be more appropriate to the aims of implementation research and more consistent with recent developments in quantitative methods. This paper reviews the principles and practice of purposeful sampling in implementation research, summarizes types and categories of purposeful sampling strategies and provides a set of recommendations for use of single strategy or multistage strategy designs, particularly for state implementation research.

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Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research.

Background
The introduction of evidence-based programs and practices into healthcare settings has been the subject of an increasing amount of research in recent years. While a number of studies have examined initial implementation efforts, less research has been conducted to determine what happens beyond that point. There is increasing recognition that the extent to which new programs are sustained is influenced by many different factors and that more needs to be known about just what these factors are and how they interact. To understand the current state of the research literature on sustainability, our team took stock of what is currently known in this area and identified areas in which further research would be particularly helpful. This paper reviews the methods that have been used, the types of outcomes that have been measured and reported, findings from studies that reported long-term implementation outcomes, and factors that have been identified as potential influences on the sustained use of new practices, programs, or interventions. We conclude with recommendations and considerations for future research.

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The sustainability of new programs and innovations: a review of the empirical literature and recommendations for future research.

This paper describes the application of mixed method designs in implementation research in 22 mental health services research studies published in peer-reviewed journals over the last 5 years. Our analyses revealed 7 different structural arrangements of qualitative and quantitative methods, 5 different functions of mixed methods, and 3 different ways of linking quantitative and qualitative data together. Complexity of design was associated with number of aims or objectives, study context, and phase of implementation examined. The findings provide suggestions for the use of mixed method designs in implementation research.

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Mixed Method Designs in Implementation Research

New financial penalties for institutions with high readmission rates have intensified efforts to reduce rehospitalization. Several interventions that involve multiple components (e.g., patient needs assessment, medication reconciliation, patient education, arranging timely outpatient appointments, and providing telephone follow-up) have successfully reduced readmission rates for patients discharged to home. The effect of interventions on readmission rates is related to the number of components implemented; single-component interventions are unlikely to reduce readmissions significantly. For patients discharged to postacute care facilities, multicomponent interventions have reduced readmissions through enhanced communication, medication safety, advanced care planning, and enhanced training to manage medical conditions that commonly precipitate readmission. To help hospitals direct resources and services to patients with greater likelihood of readmission, risk-stratification methods are available. Future work should better define the roles of home-based services, information technology, mental health care, caregiver support, community partnerships, and new transitional care personnel.

Reducing Hospital Readmission Rates: Current Strategies and Future Directions

OBJECTIVES: To examine the frequency and reasons for potentially avoidable hospitalizations of nursing home (NH) residents. DESIGN: Medical records were reviewed as a component of a project designed to develop and pilot test clinical practice tools for reducing potentially avoidable hospitalization. SETTING: NHs in Georgia. PARTICIPANTS: In 10 NHs with high and 10 with low hospitalization rates, 10 hospitalizations were randomly selected, including long- and short-stay residents. MEASUREMENTS: Ratings using a structured review by expert NH clinicians. RESULTS: Of the 200 hospitalizations, 134 (67.0%) were rated as potentially avoidable. Panel members cited lack of on-site availability of primary care clinicians, inability to obtain timely laboratory tests and intravenous fluids, problems with quality of care in assessing acute changes, and uncertain benefits of hospitalization as causes of these potentially avoidable hospitalizations. CONCLUSION: In this sample of NH residents, experienced long-term care clinicians commonly rated hospitalizations as potentially avoidable. Support for NH infrastructure, clinical practice and communication tools for health professionals, increased attention to reducing the frequency of medically futile care, and financial and other incentives for NHs and their affiliated hospitals are needed to improve care, reduce avoidable hospitalizations, and avoid unnecessary healthcare expenditures in this population. J Am Geriatr Soc 58:627–635, 2010.

https://www.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1532-5415.2010.02768.x

Potentially avoidable hospitalizations of nursing home residents: frequency, causes, and costs: [see editorial comments by Drs. Jean F. Wyman and William R. Hazzard, pp 760-761].

Hospitalization of nursing home residents is costly and potentially exposes residents to iatrogenic disease and psychological harm. This article critically reviews the association between the decision to hospitalize and factors related to the residents' welfare and preferences, the providers' attitudes, and the financial implications of hospitalization. Regarding the resident's welfare, factors associated with hospitalization included sociodemographics, health characteristics, nurse staffing, the presence of ancillary services, and the use of hospices. Patient preferences (e.g., advance directives) and provider attitudes (e.g., overburdening of staff) were also associated with increased hospitalization. Finally, financial variables related to hospitalization included nursing home ownership status and state Medicaid policies, such as nursing home payment rates and bed-hold requirements. Most studies relied on potentially confounded research designs, which leave open the issue of selection bias. Nevertheless, the existing literature asserts that nursing home hospitalizations are frequent, often preventable, and related to facility practices and state Medicaid policies.

Predictors of Nursing Home Hospitalization A Review of the Literature

Objectives: This study examined turnover rates of teams implementing psychosocial evidence-based practices in public-sector mental health settings. It also explored the relationship between turnover and implementation outcomes in an effort to understand whether practitioner perspectives on turnover are related to implementation outcomes. Methods: Team turnover was measured for 42 implementing teams participating in a national demonstration project examining implementation of five evidence-based practices between 2002 and 2005. Regression techniques were used to analyze the effects of team turnover on penetration and fidelity. Qualitative data collected throughout the project were blended with the quantitative data to examine the significance of team turnover to those attempting to implement the practices. Results: High team turnover was common (M±SD=81%±46%) and did not vary by practice. The 24-month turnover rate was inversely related to fidelity scores at 24 months (N=40, beta=–.005, p=.01). A negative trend was observed for penetration. Further analysis indicated that 71% of teams noted that turnover was a relevant factor in implementation. Conclusions: The behavioral health workforce remains in flux. High turnover most often had a negative impact on implementation, although some teams were able to use strategies to improve implementation through turnover. Implementation models must consider turbulent behavioral health workforce conditions. (Psychiatric Services 59:732–737, 2008)

https://ps.psychiatryonline.org/doi/pdf/10.1176/ps.2008.59.7.732

Laura A. Coots

Papers

Predictors of Nursing Home Hospitalization A Review of the Literature

The role of staff turnover in the implementation of evidence-based practices in mental health care