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Background The Veterans Affairs (VA) Clinical Resource Hub (CRH) program aims to improve patient access to care by implementing time-limited, regionally based primary or mental health staffing support to cover local staffing vacancies. VA’s Office of Primary Care (OPC) designed CRH to support more than 1000 geographically disparate VA outpatient sites, many of which are in rural areas, by providing virtual contingency clinical staffing for sites experiencing primary care and mental health staffing deficits. The subsequently funded CRH evaluation, carried out by the VA Primary Care Analytics Team (PCAT), partnered with CRH program leaders and evaluation stakeholders to develop a protocol for a six-year CRH evaluation. The objectives for developing the CRH evaluation protocol were to prospectively: 1) identify the outcomes CRH aimed to achieve, and the key program elements designed to achieve them; 2) specify evaluation designs and data collection approaches for assessing CRH progress and success; and 3) guide the activities of five geographically dispersed evaluation teams. Methods The protocol documents a multi-method CRH program evaluation design with qualitative and quantitative elements. The evaluation’s overall goal is to assess CRH’s return on investment to the VA and Veterans at six years through synthesis of findings on program effectiveness. The evaluation includes both observational and quasi-experimental elements reflecting impacts at the national, regional, outpatient site, and patient levels. The protocol is based on program evaluation theory, implementation science frameworks, literature on contingency staffing, and iterative review and revision by both research and clinical operations partners. Discussion Health systems increasingly seek to use data to guide management and decision-making for newly implemented clinical programs and policies. Approaches for planning evaluations to accomplish this goal, however, are not well-established. By publishing the protocol, we aim to increase the validity and usefulness of subsequent evaluation findings. We also aim to provide an example of a program evaluation protocol developed within a learning health systems partnership.

We examined how emergency department (ED) visits for potentially preventable, mental health, and other diagnoses were related to same-day access and provider continuity in primary care using administrative data from 71,296 patients in 22 VHA clinics over a three-year period. ED visits were categorized as non-emergent; primary care treatable; preventable; not preventable; or mental health-related. We conducted multi-level regression models adjusted for patient and clinic factors. More same-day access significantly predicted fewer non-emergent and primary care treatable ED visits while continuity was not significantly related to any type of ED visit. Neither measure was related to ED visits for mental health problems.

BACKGROUND: The persistence of a large quality gap between what we know about how to produce high quality clinical care and what the public receives has prompted interest in developing more effective methods to get evidence into practice. Implementation research aims to supply such methods. PURPOSE: This article proposes a set of recommendations aimed at establishing a common understanding of what implementation research is, and how to foster its development. METHODS: We developed the recommendations in the context of a translation research conference hosted by the VA for VA and non‐VA health services researchers. IMPACTS: Health care organizations, journals, researchers and academic institutions can use these recommendations to advance the field of implementation science and thus increase the impact of clinical and health services research on the health and health care of the public.

ObjectiveChronic pain disproportionately affects medically and psychosocially complex patients, many of whom are at high risk of hospitalisation. Pain prevalence among high-risk patients, however, is unknown, and pain is seldom a focus for improving high-risk patient outcomes. Our objective is to (1) evaluate pain frequency in a high-risk patient population and (2) identify intensive management (IM) programme features that patients and providers perceive as important for promoting patient-centred pain care within primary care (PC)-based IM.DesignSecondary observational analysis of quantitative and qualitative evaluation data from a multisite randomised PC-based IM programme for high-risk patients.SettingFive integrated local Veterans Affairs (VA) healthcare systems within distinct VA administrative regions.ParticipantsStaff and high-risk PC patients in the VA.InterventionA multisite randomised PC-based IM programme for high-risk patients.Outcome measures(a) Pain prevalence based on VA electronic administrative data and (b) transcripts of interviews with IM staff and patients that mentioned pain.ResultsMost (70%, 2593/3723) high-risk patients had at least moderate pain. Over one-third (38%, 40/104) of the interviewees mentioned pain or pain care. There were 89 pain-related comments addressing IM impacts on pain care within the 40 interview transcripts. Patient-identified themes were that IM improved communication and responsiveness to pain. PC provider-identified themes were that IM improved workload and access to expertise. IM team member-identified themes were that IM improved pain care coordination, facilitated non-opioid pain management options and mitigated provider compassion fatigue. No negative IM impacts on pain care were mentioned.ConclusionsPain is common among high-risk patients. Future IM evaluations should consider including a focus on pain and pain care, with attention to impacts on patients, PC providers and IM teams.

Background Effective implementation strategies might facilitate patient-centered medical home (PCMH) uptake and spread by targeting barriers to change. Evidence-based quality improvement (EBQI) is a multi-faceted implementation strategy that is based on a clinical-researcher partnership. It promotes organizational change by fostering innovation and the spread of those innovations that are successful. Previous studies demonstrated that EBQI accelerated PCMH adoption within Veterans Health Administration primary care practices, compared with standard PCMH implementation. Research to date has not documented fidelity to the EBQI implementation strategy, limiting usefulness of prior research findings. This paper develops and assesses clinical participants’ fidelity to three core EBQI elements for PCMH (EBQI-PCMH), explores the relationship between fidelity and successful QI project completion and spread (the outcome of EBQI-PCMH), and assesses the role of the clinical-researcher partnership in achieving EBQI-PCMH fidelity. Methods Nine primary care practice sites and seven across-sites, topic-focused workgroups participated (2010–2014). Core EBQI elements included leadership-frontlines priority-setting for QI, ongoing access to technical expertise, coaching, and mentoring in QI methods (through a QI collaborative), and data/evidence use to inform QI. We used explicit criteria to measure and assess EBQI-PCMH fidelity across clinical participants. We mapped fidelity to evaluation data on implementation and spread of successful QI projects/products. To assess the clinical-researcher partnership role in EBQI-PCMH, we analyzed 73 key stakeholder interviews using thematic analysis. Results Seven of 9 sites and 3 of 7 workgroups achieved high or medium fidelity to leadership-frontlines priority-setting. Fidelity was mixed for ongoing technical expertise and data/evidence use. Longer duration in EBQI-PCMH and higher fidelity to priority-setting and ongoing technical expertise appear correlated with successful QI project completion and spread. According to key stakeholders, partnership with researchers, as well as bi-directional communication between leaders and QI teams and project management/data support were critical to achieving EBQI-PCMH fidelity. Conclusions This study advances implementation theory and research by developing measures for and assessing fidelity to core EBQI elements in relationship to completion and spread of QI innovation projects or tools for addressing PCMH challenges. These results help close the gap between EBQI elements, their intended outcome, and the finding that EBQI-PCMH resulted in accelerated adoption of PCMH.

Background Stepped wedge designs have gained recognition as a method for rigorously assessing implementation of evidence-based quality improvement interventions (QIIs) across multiple healthcare sites. In theory, this design uses random assignment of sites to successive QII implementation start dates based on a timeline determined by evaluators. However, in practice, QII timing is often controlled more by site readiness. We propose an alternate version of the stepped wedge design that does not assume the randomized timing of implementation while retaining the method’s analytic advantages and applying to a broader set of evaluations. To test the feasibility of a nonrandomized stepped wedge design, we developed simulated data on patient care experiences and on QII implementation that had the structures and features of the expected data from a planned QII. We then applied the design in anticipation of performing an actual QII evaluation. Methods We used simulated data on 108,000 patients to model nonrandomized stepped wedge results from QII implementation across nine primary care sites over 12 quarters. The outcome we simulated was change in a single self-administered question on access to care used by Veterans Health Administration (VA), based in the United States, as part of its quarterly patient ratings of quality of care. Our main predictors were QII exposure and time. Based on study hypotheses, we assigned values of 4 to 11 % for improvement in access when sites were first exposed to implementation and 1 to 3 % improvement in each ensuing time period thereafter when sites continued with implementation. We included site-level (practice size) and respondent-level (gender, race/ethnicity) characteristics that might account for nonrandomized timing in site implementation of the QII. We analyzed the resulting data as a repeated cross-sectional model using HLM 7 with a three-level hierarchical data structure and an ordinal outcome. Levels in the data structure included patient ratings, timing of adoption of the QII, and primary care site. Results We were able to demonstrate a statistically significant improvement in adoption of the QII, as postulated in our simulation. The linear time trend while sites were in the control state was not significant, also as expected in the real life scenario of the example QII. Conclusions We concluded that the nonrandomized stepped wedge design was feasible within the parameters of our planned QII with its data structure and content. Our statistical approach may be applicable to similar evaluations.

Background Meta-analyses show collaborative care models (CCMs) with nurse care management are effective for improving primary care for depression. This study aimed to develop CCM approaches that could be sustained and spread within Veterans Affairs (VA). Evidence-based quality improvement (EBQI) uses QI approaches within a research/clinical partnership to redesign care. The study used EBQI methods for CCM redesign, tested the effectiveness of the locally adapted model as implemented, and assessed the contextual factors shaping intervention effectiveness. Methods The study intervention is EBQI as applied to CCM implementation. The study uses a cluster randomized design as a formative evaluation tool to test and improve the effectiveness of the redesign process, with seven intervention and three non-intervention VA primary care practices in five different states. The primary study outcome is patient antidepressant use. The context evaluation is descriptive and uses subgroup analysis. The primary context evaluation measure is naturalistic primary care clinician (PCC) predilection to adopt CCM. For the randomized evaluation, trained telephone research interviewers enrolled consecutive primary care patients with major depression in the evaluation, referred enrolled patients in intervention practices to the implemented CCM, and re-surveyed at seven months. Results Interviewers enrolled 288 CCM site and 258 non-CCM site patients. Enrolled intervention site patients were more likely to receive appropriate antidepressant care (66% versus 43%, p = 0.01), but showed no significant difference in symptom improvement compared to usual care. In terms of context, only 40% of enrolled patients received complete care management per protocol. PCC predilection to adopt CCM had substantial effects on patient participation, with patients belonging to early adopter clinicians completing adequate care manager follow-up significantly more often than patients of clinicians with low predilection to adopt CCM (74% versus 48%%, p = 0.003). Conclusions Depression CCM designed and implemented by primary care practices using EBQI improved antidepressant initiation. Combining QI methods with a randomized evaluation proved challenging, but enabled new insights into the process of translating research-based CCM into practice. Future research on the effects of PCC attitudes and skills on CCM results, as well as on enhancing the link between improved antidepressant use and symptom outcomes, is needed. Trial Registration ClinicalTrials.gov: NCT00105820

Purpose – The purpose of this paper is to provide evidence based guidance to researchers and practice personnel about forming and carrying out effective research partnerships. Design/methodology/approach – A review of the literature, interviews and discussions with colleagues in both research and practice roles, and a review of the authors' personal experiences as researchers in partnership research. Findings – Partnership research is, in some respects, a distinct “approach” to research, but there are many different versions. An analysis of research publications and of their research experience led the authors to develop a framework for planning and assessing the partnership research process, which includes defining expected outcomes for the partners, their roles, and steps in the research process. Practical implications – This review and analysis provides guidance that may reduce commonly-reported misunderstandings and help to plan more successful partnerships and projects. It also identifies future research which is needed to define more precisely the questions and purposes for which partnership research is most appropriate, and methods and designs for specific types of partnership research. Originality/value – As more research moves towards increased participation of practitioners and patients in the research process, more precise and differentiated understanding of the different partnership approaches is required, and when each is most suitable. This article describes research approaches that have the potential to reduce “the research-practice gap”. It gives evidence- and experience-based guidance for choosing and establishing a partnership research process, so as to improve partnership relationship-building and more actionable research.