PURPOSE:Little is known about whether different types of physician and nonphysician primary care clinicians vary in their propensity to care for underserved populations. The objective of this study was to compare the geographic distribution and patient populations of physician and nonphysician primary care clinicians.
Strategies to reduce nurse shortages should consider differences in education, work patterns, and commuting behavior among rural and urban RNs. Solutions for rural areas require understanding of the impact of the workplace on these behaviors.
Objective. To quantify the total contribution to generalist care made by nurse practitioners (NPs) and physician assistants (PAs) in Washington State. Data Sources. State professional licensure renewal survey data from 1998-1999. Study Design. Cross-sectional. Data on medical specialty, place of practice, and outpatient visits performed were used to estimate productivity of generalist physicians, NPs, and PAs. Provider head counts were adjusted for missing specialty and productivity data and converted into family physician full-time equivalents (FTEs) to facilitate estimation of total contribution to generalist care made by each provider type. Principal Findings. Nurse practitioners and physician assistants make up 23.4 percent of the generalist provider population and provide 21.0 percent of the generalist outpatient visits in Washington State. The NP/PA contribution to generalist care is higher in rural areas (24.7 percent of total visits compared to 20.1 percent in urban areas). The PAs and NPs provide 50.3 percent of generalist visits provided by women in rural areas, 36.5 percent in urban areas. When productivity data were converted into family physician FTEs, the productivity adjustments were large. A total of 4,189 generalist physicians produced only 2,760 family physician FTEs (1 FTE 5 105 outpatient visits per week). The NP and PA productivity adjustments were also quite large. Conclusions. Accurate estimates of available generalist care must take into account the contributions of NPs and PAs. Additionally, simple head counts of licensed providers are likely to result in substantial overestimates of available care. Actual productivity data or empirically derived adjustment factors must be used for accurate estimation of provider shortages.
Background: Tailoring implementation strategies and adapting treatments to better fit the local context may improve their effectiveness. However, there is a dearth of valid, reliable, pragmatic measures that allow for the prospective tracking of strategies and adaptations according to reporting recommendations. This study describes the development and pilot testing of three tools to be designed to serve this purpose. Methods: Measure development was informed by two systematic reviews of the literature (implementation strategies and treatment adaptation). The three resulting tools vary with respect to the degree of structure (brainstorming log = low, activity log = moderate, detailed tracking log = high). To prospectively track treatment adaptations and implementation strategies, three stakeholder groups (treatment developer, implementation practitioners, and mental health providers) were randomly assigned one tool per week through an anonymous web-based survey for 12 weeks and incentivized to participate. Three established implementation outcome measures, the Acceptability of Intervention Measure, Intervention Appropriateness Measure, and Feasibility of Intervention Measure, were used to assess the tools. Semi-structured interviews were conducted to gather more nuanced information from stakeholders regarding their perceptions of the tools and the tracking process. Results: The three tracking tools demonstrated moderate to good acceptability, appropriateness, and feasibility; the activity log was deemed the most feasible of the three tools. Implementation practitioners rated the tools the highest of the three stakeholder groups. The tools took an average of 15 min or less to complete. Conclusion: This study sought to fill methodological gaps that prevent stakeholders and researchers from discerning which strategies are most important to deploy for promoting implementation and sustainment of evidence-based practices. These tools would allow researchers and practitioners to track whether activities were treatment adaptations or implementation strategies and what barrier(s) each targets. These tools could inform prospective tailoring of implementation strategies and treatment adaptations, which would promote scale out and spread. Plain Language Summary Strategies to support the implementation of evidence-based practices may be more successful if they are carefully customized based on local factors. Evidence-based practices themselves may be thoughtfully changed to better meet the needs of the settings and recipients. This study reports on a pilot study that aimed to create various types of tools to help individuals involved in implementation efforts track the actions they take to modify and implement interventions. These tools allow individuals to track the types of activities they are involved in, when the activities occurred, who was involved in the implementation efforts, and the reasons or rationale for the actions. The three tools in this study used a combination of open-ended and forced-response questions to test how the type of data recorded changed. Participants generally found the tools quick and easy to use and helpful in planning the delivery of an evidence-based practice. Most participants wanted more training in implementation science terminology and how to complete the tracking tools. Participating mental health providers would have liked more opportunities to review the data collected from the tools with their supervisors to use the data to improve the delivery of the evidence-based practice. These tools can help researchers, providers, and staff involved in implementation efforts to better understand what actions are needed to improve implementation success. Future research should address gaps identified in this study, such as the need to involve more participants in the tool development process.
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