Modeling Recreation Site Choice: Do Hypothetical Choices Reflect Actual Behavior?

We examine the ability of revealed preference (RP), site-specific stated preference (SP), transferred SP, and joint RP-SP models to predict aggregate and individual recreation site choice in a holdout sample. For two statistical comparisons, the RP model provided the most accurate predictions of individual choices. However, the transferred SP model, applied directly or estimated jointly with the RP data, performed best in three aggregate and one individual prediction test. These findings suggest that data from well-designed and conducted SP surveys from one site can be combined with site-specific RP data from another site to generate improved models of recreation site choice. Copyright 2001, Oxford University Press.

Aggregation Bias in Recreation Site Choice Models: Resolving the Resolution Problem

This paper examines the effect of differing levels of spatial resolution on recreation site choice models and welfare resulting from changes in site attributes. These issues are important where the spatial scale at which recreationists make choices is unknown, but information exists on choice attributes at larger spatial scales. We estimate choice models at various scales of spatial resolution and incorporate the size of the aggregate sites and heterogeneity parameters in the model. Accounting for the size of the aggregates in estimation improved model fit and alleviated aggregate parameter bias. We provide advice for applied modeling based on these results.

Co-designing person-centred quality indicator implementation for primary care in Alberta: a consensus study

Abstract Background We aimed to contribute to developing practical guidance for implementing person-centred quality indicators (PC-QIs) for primary care in Alberta, Canada. As a first step in this process, we conducted stakeholder-guided prioritization of PC-QIs and implementation strategies. Stakeholder engagement is necessary to ensure PC-QI implementation is adapted to the context and local needs. Methods We used an adapted nominal group technique (NGT) consensus process. Panelists were presented with 26 PC-QIs, and implementation strategies. Both PC-QIs and strategies were identified from our extensive previous engagement of patients, caregivers, healthcare providers, and quality improvement leaders. The NGT objectives were to: 1. Prioritize PC-QIs and implementation strategies; and 2. Facilitate the participation of diverse primary care stakeholders in Alberta, including patients, healthcare providers, and quality improvement staff. Panelists participated in three rounds of activities. In the first, panelists individually ranked and commented on the PC-QIs and strategies. The summarized results were discussed in the second-round face-to-face group meeting. For the last round, panelists provided their final individual rankings, informed by the group discussion. Finally, we conducted an evaluation of the consensus process from the panelists’ perspectives. Results Eleven primary care providers, patient partners, and quality improvement staff from across Alberta participated. The panelists prioritized the following PC-QIs: ‘Patient and caregiver involvement in decisions about their care and treatment’; ‘Trusting relationship with healthcare provider’; ‘Health information technology to support person-centred care’; ‘Co-designing care in partnership with communities’; and ‘Overall experience’. Implementation strategies prioritized included: ‘Develop partnerships’; ‘Obtain quality improvement resources’; ‘Needs assessment (stakeholders are engaged about their needs/priorities for person-centred measurement)’; ‘Align measurement efforts’; and ‘Engage champions’. Our evaluation suggests that panelists felt that the process was valuable for planning the implementation and obtaining feedback, that their input was valued, and that most would continue to collaborate with other stakeholders to implement the PC-QIs. Conclusions Our study demonstrates the value of co-design and participatory approaches for engaging stakeholders in adapting PC-QI implementation for the primary care context in Alberta, Canada. Collaboration with stakeholders can promote buy-in for ongoing engagement and ensure implementation will lead to meaningful improvements that matter to patients and providers.Plain English summary Person-centred care (PCC) is a model of care where patient needs and preferences are included in decisions about care and treatment. To improve PCC in primary care in Alberta, Canada, we plan to use person-centred quality indicators (PC-QIs). Using PC-QIs involves surveying patients about their care experiences and using this information to make improvements. For example, if 20% of patients do not feel they are getting enough information, the clinic may create a checklist for the providers so information is not missed. We engaged a panel of 11 people, including patients, family doctors, and staff who support quality improvement in clinics across the province to decide together which PC-QIs primary care clinics in Alberta should use. We also asked the panel to decide the most important strategies that would make using the PC-QIs more successful. The panel chose PC-QIs related to: patient and caregiver involvement in decisions about care and treatment, a trusting relationship with the healthcare provider, having health information technology to support PCC, partnering with communities in healthcare, and the patient’s overall experience. The most important strategies were: developing partnerships among people working in primary care in Alberta, discussing their needs and common efforts for improving PCC, engaging “champions,” and securing funding that would be needed. Finally, we asked the panelists to share their experiences with participating in this process. Panelists found the process useful and that their input was valued. Most panelists would also like to continue to work together to put the PC-QIs into practice

Additional file 1 of Co-designing person-centred quality indicator implementation for primary care in Alberta: a consensus study

Additional file 1. The table provided shows where each implementation strategy is mapped to one or more broad strategy from the Consolidated Framework for Implementation Research (CFIR) - Expert Recommendations for Implementing Change (ERIC) Strategy Matching Tool