Hospital recruitment for a pragmatic cluster-randomized clinical trial: Lessons learned from the COMPASS study

Qualitative study of challenges with recruitment of hospitals into a cluster controlled trial of clinical decision support in Australia

OBJECTIVE

To identify barriers to hospital participation in controlled cluster trials of clinical decision support (CDS) and potential strategies for addressing barriers.

DESIGN

Qualitative descriptive design comprising semistructured interviews.

SETTING

Five hospitals in New South Wales and one hospital in Queensland, Australia.

PARTICIPANTS

Senior hospital staff, including department directors, chief information officers and those working in health informatics teams.

RESULTS

20 senior hospital staff took part. Barriers to hospital-level recruitment primarily related to perceptions of risk associated with not implementing CDS as a control site. Perceived risks included reductions in patient safety, reputational risk and increased likelihood that benefits would not be achieved following electronic medical record (EMR) implementation without CDS alerts in place. Senior staff recommended clear communication of trial information to all relevant stakeholders as a key strategy for boosting hospital-level participation in trials.

CONCLUSION

Hospital participation in controlled cluster trials of CDS is hindered by perceptions that adopting an EMR without CDS is risky for both patients and organisations. The improvements in safety expected to follow CDS implementation makes it challenging and counterintuitive for hospitals to implement EMR without incorporating CDS alerts for the purposes of a research trial. To counteract these barriers, clear communication regarding the evidence base and rationale for a controlled trial is needed.

Referral to Community-Based Rehabilitation Following Acute Stroke: Findings From the COMPASS Pragmatic Trial

BACKGROUND

Few studies on care transitions following acute stroke have evaluated whether referral to community-based rehabilitation occurred as part of discharge planning. Our objectives were to describe the extent to which patients discharged home were referred to community-based rehabilitation and identify the patient, hospital, and community-level predictors of referral.

METHODS

We examined data from 40 North Carolina hospitals that participated in the COMPASS (Comprehensive Post-Acute Stroke Services) cluster-randomized trial. Participants included adults discharged home following stroke or transient ischemic attack (N=10  702). In this observational analysis, COMPASS data were supplemented with hospital-level and county-level data from various sources. The primary outcome was referral to community-based rehabilitation (physical, occupational, or speech therapy) at discharge. Predictor variables included patient (demographic, stroke-related, medical history), hospital (structure, process), and community (therapist supply) measures. We used generalized linear mixed models with a hospital random effect and hierarchical backward model selection procedures to identify predictors of therapy referral.

RESULTS

Approximately, one-third (36%) of stroke survivors (mean age, 66.8 [SD, 14.0] years; 49% female, 72% White race) were referred to community-based rehabilitation. Rates of referral to physical, occupational, and speech therapists were 31%, 18%, and 10%, respectively. Referral rates by hospital ranged from 3% to 78% with a median of 35%. Patient-level predictors included higher stroke severity, presence of medical comorbidities, and older age. Female sex (odds ratio, 1.24 [95% CI, 1.12-1.38]), non-White race (2.20 [2.01-2.44]), and having Medicare insurance (1.12 [1.02-1.23]) were also predictors of referral. Referral was higher for patients living in counties with greater physical therapist supply. Much of the variation in referral across hospitals remained unexplained.

CONCLUSIONS

One-third of stroke survivors were referred to community-based rehabilitation. Patient-level factors predominated as predictors. Variation across hospitals was notable and presents an opportunity for further evaluation and possible targets for improved poststroke rehabilitative care.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02588664.

Assessing the representativeness of cluster randomized trials: Evidence from two large pragmatic trials in United States nursing homes

BACKGROUND/AIMS

When the randomized clusters in a cluster randomized trial are selected based on characteristics that influence treatment effectiveness, results from the trial may not be directly applicable to the target population. We used data from two large nursing home-based pragmatic cluster randomized trials to compare nursing home and resident characteristics in randomized facilities to eligible non-randomized and ineligible facilities.

METHODS

We linked data from the high-dose influenza vaccine trial and the Music & Memory Pragmatic TRIal for Nursing Home Residents with ALzheimer's Disease (METRICaL) to nursing home assessments and Medicare fee-for-service claims. The target population for the high-dose trial comprised Medicare-certified nursing homes; the target population for the METRICaL trial comprised nursing homes in one of four US-based nursing home chains. We used standardized mean differences to compare facility and individual characteristics across the three groups and logistic regression to model the probability of nursing home trial participation.

RESULTS

In the high-dose trial, 4476 (29%) of the 15,502 nursing homes in the target population were eligible for the trial, of which 818 (18%) were randomized. Of the 1,361,122 residents, 91,179 (6.7%) were residents of randomized facilities, 463,703 (34.0%) of eligible non-randomized facilities, and 806,205 (59.3%) of ineligible facilities. In the METRICaL trial, 160 (59%) of the 270 nursing homes in the target population were eligible for the trial, of which 80 (50%) were randomized. Of the 20,262 residents, 973 (34.4%) were residents of randomized facilities, 7431 (36.7%) of eligible non-randomized facilities, and 5858 (28.9%) of ineligible facilities. In the high-dose trial, randomized facilities differed from eligible non-randomized and ineligible facilities by the number of beds (132.5 vs 145.9 and 91.9, respectively), for-profit status (91.8% vs 66.8% and 68.8%), belonging to a nursing home chain (85.8% vs 49.9% and 54.7%), and presence of a special care unit (19.8% vs 25.9% and 14.4%). In the METRICaL trial randomized facilities differed from eligible non-randomized and ineligible facilities by the number of beds (103.7 vs 110.5 and 67.0), resource-poor status (4.6% vs 10.0% and 18.8%), and presence of a special care unit (26.3% vs 33.8% and 10.9%). In both trials, the characteristics of residents in randomized facilities were similar across the three groups.

CONCLUSION

In both trials, facility-level characteristics of randomized nursing homes differed considerably from those of eligible non-randomized and ineligible facilities, while there was little difference in resident-level characteristics across the three groups. Investigators should assess the characteristics of clusters that participate in cluster randomized trials, not just the individuals within the clusters, when examining the applicability of trial results beyond participating clusters.

Post-acute Ambulatory Care Service Use Among Patients Discharged Home After Stroke or TIA: The Cluster-randomized COMPASS Study

BACKGROUND AND OBJECTIVES

We examined transitional care management within 90 days and 1 year following discharge home among acute stroke and transient ischemic attack patients from the Comprehensive Post-Acute Stroke Services (COMPASS) Study, a cluster-randomized pragmatic trial of early supported discharge conducted in 41 hospitals (40 hospital units) in North Carolina, United States.

METHODS

Data for 2262 of the total 6024 (37.6%; 1069 intervention and 1193 usual care) COMPASS patients were linked with the Centers for Medicare and Medicaid Services fee-for-service Medicare claims. Time to the first ambulatory care visit was examined using Cox proportional hazard models adjusted for patient characteristics not included in the randomization protocol.

RESULTS

Only 6% of the patients [mean (SD) age 74.9 (10.2) years, 52.1% women, 80.3% White)] did not have an ambulatory care visit within 90 days postdischarge. Mean time (SD) to first ambulatory care visit was 12.0 (26.0) and 16.3 (35.1) days in intervention and usual care arms, respectively, with the majority of visits in both study arms to primary care providers. The COMPASS intervention resulted in a 27% greater use of ambulatory care services within 1 year postdischarge, relative to usual care [HR=1.27 (95% CI: 1.14-1.41)]. The use of transitional care billing codes was significantly greater in the intervention arm as compared with usual care [OR=1.87 (95% CI: 1.54-2.27)].

DISCUSSION

The COMPASS intervention, which was aimed at improving stroke post-acute care, was associated with an increase in the use of ambulatory care services by stroke and transient ischemic attack patients discharged home and an increased use of transitional care billing codes by ambulatory providers.

Hospital Readmissions and Mortality Among Fee-for-Service Medicare Patients With Minor Stroke or Transient Ischemic Attack: Findings From the COMPASS Cluster-Randomized Pragmatic Trial

Background Mortality and hospital readmission rates may reflect the quality of acute and postacute stroke care. Our aim was to investigate if, compared with usual care (UC), the COMPASS-TC (Comprehensive Post-Acute Stroke Services Transitional Care) intervention (INV) resulted in lower all-cause and stroke-specific readmissions and mortality among patients with minor stroke and transient ischemic attack discharged from 40 diverse North Carolina hospitals from 2016 to 2018. Methods and Results Using Medicare fee-for-service claims linked with COMPASS cluster-randomized trial data, we performed intention-to-treat analyses for 30-day, 90-day, and 1-year unplanned all-cause and stroke-specific readmissions and all-cause mortality between INV and UC groups, with 90-day unplanned all-cause readmissions as the primary outcome. Effect estimates were determined via mixed logistic or Cox proportional hazards regression models adjusted for age, sex, race, stroke severity, stroke diagnosis, and documented history of stroke. The final analysis cohort included 1069 INV and 1193 UC patients (median age 74 years, 80% White, 52% women, 40% with transient ischemic attack) with median length of hospital stay of 2 days. The risk of unplanned all-cause readmission was similar between INV versus UC at 30 (9.9% versus 8.7%) and 90 days (19.9% versus 18.9%), respectively. No significant differences between randomization groups were seen in 1-year all-cause readmissions, stroke-specific readmissions, or mortality. Conclusions In this pragmatic trial of patients with complex minor stroke/transient ischemic attack, there was no difference in the risk of readmission or mortality with COMPASS-TC relative to UC. Our study could not conclusively determine the reason for the lack of effectiveness of the INV. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02588664.

Effectiveness of knowledge brokering and recommendation dissemination for influencing healthcare resource allocation decisions: A cluster randomised controlled implementation trial

BACKGROUND

Implementing evidence into clinical practice is a key focus of healthcare improvements to reduce unwarranted variation. Dissemination of evidence-based recommendations and knowledge brokering have emerged as potential strategies to achieve evidence implementation by influencing resource allocation decisions. The aim of this study was to determine the effectiveness of these two research implementation strategies to facilitate evidence-informed healthcare management decisions for the provision of inpatient weekend allied health services.

METHODS AND FINDINGS

This multicentre, single-blinded (data collection and analysis), three-group parallel cluster randomised controlled trial with concealed allocation was conducted in Australian and New Zealand hospitals between February 2018 and January 2020. Clustering and randomisation took place at the organisation level where weekend allied health staffing decisions were made (e.g., network of hospitals or single hospital). Hospital wards were nested within these decision-making structures. Three conditions were compared over a 12-month period: (1) usual practice waitlist control; (2) dissemination of written evidence-based practice recommendations; and (3) access to a webinar-based knowledge broker in addition to the recommendations. The primary outcome was the alignment of weekend allied health provision with practice recommendations at the cluster and ward levels, addressing the adoption, penetration, and fidelity to the recommendations. The secondary outcome was mean hospital length of stay at the ward level. Outcomes were collected at baseline and 12 months later. A total of 45 clusters (n = 833 wards) were randomised to either control (n = 15), recommendation (n = 16), or knowledge broker (n = 14) conditions. Four (9%) did not provide follow-up data, and no adverse events were recorded. No significant effect was found with either implementation strategy for the primary outcome at the cluster level (recommendation versus control β 18.11 [95% CI -8,721.81 to 8,758.02] p = 0.997; knowledge broker versus control β 1.24 [95% CI -6,992.60 to 6,995.07] p = 1.000; recommendation versus knowledge broker β -9.12 [95% CI -3,878.39 to 3,860.16] p = 0.996) or ward level (recommendation versus control β 0.01 [95% CI 0.74 to 0.75] p = 0.983; knowledge broker versus control β -0.12 [95% CI -0.54 to 0.30] p = 0.581; recommendation versus knowledge broker β -0.19 [-1.04 to 0.65] p = 0.651). There was no significant effect between strategies for the secondary outcome at ward level (recommendation versus control β 2.19 [95% CI -1.36 to 5.74] p = 0.219; knowledge broker versus control β -0.55 [95% CI -1.16 to 0.06] p = 0.075; recommendation versus knowledge broker β -3.75 [95% CI -8.33 to 0.82] p = 0.102). None of the control or knowledge broker clusters transitioned to partial or full alignment with the recommendations. Three (20%) of the clusters who only received the written recommendations transitioned from nonalignment to partial alignment. Limitations include underpowering at the cluster level sample due to the grouping of multiple geographically distinct hospitals to avoid contamination.

CONCLUSIONS

Owing to a lack of power at the cluster level, this trial was unable to identify a difference between the knowledge broker strategy and dissemination of recommendations compared with usual practice for the promotion of evidence-informed resource allocation to inpatient weekend allied health services. Future research is needed to determine the interactions between different implementation strategies and healthcare contexts when translating evidence into healthcare practice.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12618000029291.

Rationale for a Clinical Trial That Compares Acute Stroke Rehabilitation at Inpatient Rehabilitation Facilities to Skilled Nursing Facilities: Challenges and Opportunities

In the United States, approximately 400,000 patients with acute stroke are discharged annually to inpatient rehabilitation facilities (IRFs) or skilled nursing facilities (SNFs). Typically, IRFs provide time-intensive therapy for an average of 2-3 weeks, whereas SNFs provide more moderately intensive therapy for 4-5 weeks. The factors that influence discharge to an IRF or SNF are multifactorial and poorly understood. The complexity of these factors in combination with subjective clinical indications contributes to large variations in the use of IRFs and SNFs. This has significant financial implications for health care expenditure, given that stroke rehabilitation at IRFs costs approximately double that at SNFs. To control health care spending without compromising outcomes, the Institute of Medicine has stated that policy reforms that promote more efficient use of IRFs and SNFs are critically needed. A major barrier to the formulation of such policies is the highly variable and low-quality evidence for the comparative effectiveness of IRF- vs SNF-based stroke rehabilitation. The current evidence is limited by the inability of observational data to control for residual confounding, which contributes to substantial uncertainty around any magnitude of benefit for IRF- vs SNF-based care. Furthermore, it is unclear which specific patients would receive the most benefit from each setting. A randomized controlled trial addresses these issues, because random treatment allocation facilitates an equitable distribution of measured and unmeasured confounders. We discuss several measurement, practical, and ethical issues of a trial and provide our rationale for design suggestions that overcome some of these issues.

Methodological Challenges and Statistical Approaches in the COMprehensive Post-Acute Stroke Services Study

BACKGROUND

The COMprehensive Post-Acute Stroke Services study was a cluster-randomized pragmatic trial designed to evaluate a comprehensive care transitions model versus usual care. The data collected during this trial were complex and analysis methodology was required that could simultaneously account for the cluster-randomized design, missing patient-level covariates, outcome nonresponse, and substantial nonadherence to the intervention.

OBJECTIVE

The objective of this study was to discuss an array of complementary statistical methods to evaluate treatment effectiveness that appropriately addressed the challenges presented by the complex data arising from this pragmatic trial.

METHODS

We utilized multiple imputation combined with inverse probability weighting to account for missing covariate and outcome data in the estimation of intention-to-treat effects (ITT). The ITT estimand reflects the effectiveness of assignment to the COMprehensive Post-Acute Stroke Services intervention compared with usual care (ie, it does not take into account intervention adherence). Per-protocol analyses provide complementary information about the effect of treatment, and therefore are relevant for patients to inform their decision-making. We describe estimation of the complier average causal effect using an instrumental variables approach through 2-stage least squares estimation. For all preplanned analyses, we also discuss additional sensitivity analyses.

DISCUSSION

Pragmatic trials are well suited to inform clinical practice. Care should be taken to proactively identify the appropriate balance between control and pragmatism in trial design. Valid estimation of ITT and per-protocol effects in the presence of complex data requires application of appropriate statistical methods and concerted efforts to ensure high-quality data are collected.

Recruiting hard-to-reach pregnant women at high psychosocial risk: strategies and costs from a randomised controlled trial

BACKGROUND

Recruiting participants to randomised controlled trials (RCTs) is often challenging, particularly when working with socially disadvantaged populations who are often termed 'hard-to-reach' in research. Here we report the recruitment strategies and costs for the Trial for Healthy Relationship Initiatives in the Very Early years (THRIVE), an RCT evaluating two group-based parenting interventions for pregnant women.

METHODS

THRIVE aimed to recruit 500 pregnant women with additional health and social care needs in Scotland between 2014 and 2018. Three recruitment strategies were employed: (1) referrals from a health or social care practitioner or voluntary/community organisation (practitioner-led referral), (2) direct engagement with potential participants by research staff (researcher-led recruitment) and (3) self-referral in response to study advertising (self-referral). The number of referrals and recruited participants from each strategy is reported along with the overall cost of recruitment. The impact of recruitment activities and the changes in maternity policy/context on recruitment throughout the study are examined.

RESULTS

THRIVE received 973 referrals: 684 (70%) from practitioners (mainly specialist and general midwives), 273 (28%) from research nurses and 16 (2%) self-referrals. The time spent in antenatal clinics by research nurses each month was positively correlated with the number of referrals received (r = 0.57; p < 0.001). Changes in maternity policies and contexts were reflected in the number of referrals received each month, with both positive and negative impacts throughout the trial. Overall, 50% of referred women were recruited to the trial. Women referred via self-referral, THRIVE research nurses and specialist midwives were most likely to go on to be recruited (81%, 58% and 57%, respectively). Key contributors to recruitment included engaging key groups of referrers, establishing a large flexible workforce to enable recruitment activities to adapt to changes in context throughout the study and identifying the most appropriate setting to engage with potential participants. The overall cost of recruitment was £377 per randomised participant.

CONCLUSIONS

Recruitment resulted from a combination of all three strategies. Our reflections on the successes and challenges of these strategies highlight the need for recruitment strategies to be flexible to adapt to complex interventions and real-world challenges. These findings will inform future research in similar hard-to-reach populations.

TRIAL REGISTRATION

International Standard Randomised Controlled Trials Number Registry ISRCTN21656568 . Retrospectively registered on 28 February 2014.

Strategies for facilitating the delivery of cluster randomized trials in hospitals: A study informed by the CFIR-ERIC matching tool

BACKGROUND

Recruitment and engagement of clusters in a cluster randomized controlled trial can sometimes prove challenging. Identification of successful or unsuccessful strategies may be beneficial in guiding future researchers in conducting their cluster randomized controlled trial. This study aimed to identify strategies that could be used to facilitate the delivery of cluster randomized controlled trials in hospitals.

METHODS

The study employed the Consolidated Framework for Implementation Research-Expert Recommendations for Implementing Change matching tool. The barriers and enablers to cluster randomized controlled trial conduct identified in our previously conducted studies served as a means of determinant identification for the conduct of cluster randomized controlled trials. These determinants were mapped to Consolidated Framework for Implementation Research constructs and then matched to Expert Recommendations for Implementing Change compilation strategies using the Consolidated Framework for Implementation Research-Expert Recommendations for Implementing Change matching tool.

RESULTS

The Expert Recommendations for Implementing Change strategies matched to at least one determinant Consolidated Framework for Implementation Research construct were as follows: (1) 'Identify and prepare champions', (2) 'Conduct local needs assessment', (3) 'Conduct educational meetings', (4) 'Inform local opinion leaders', (5) 'Build a coalition', (6) 'Promote adaptability', (7) 'Develop a formal implementation blueprint', (8) 'Involve patients/consumers and family members', (9) 'Obtain and use patients/consumers and family feedback', (10) 'Develop educational materials', (11) 'Promote network weaving', (12) 'Distribute educational materials', (13) 'Access new funding' and (14) 'Develop academic partnerships'.

CONCLUSION

This study was intended as a step in the research agenda aimed at facilitating cluster randomized controlled trial delivery in hospitals and can act as a resource for future researchers when planning their cluster randomized controlled trial, with the expectation that the strategies identified here will be tailored to each context.

Partnering with healthcare facilities to understand psychosocial distress screening practices among cancer survivors: pilot study implications for study design, recruitment, and data collection

BACKGROUND

We sought to understand barriers and facilitators to implementing distress screening (DS) of cancer patients to inform and promote uptake in cancer treatment facilities. We describe the recruitment and data collection challenges and recommendations for assessing DS in oncology treatment facilities.

METHODS

We recruited CoC-accredited facilities and collected data from each facility's electronic health record (EHR). Collected data included cancer diagnosis and demographics, details on DS, and other relevant patient health data. Data were collected by external study staff who were given access to the facility's EHR system, or by facility staff working locally within their own EHR system. Analyses are based on a pilot study of 9 facilities.

RESULTS

Challenges stemmed from being a multi-facility-based study and local institutional review board (IRB) approval, facility review and approval processes, and issues associated with EHR systems and the lack of DS data standards. Facilities that provided study staff remote-access took longer for recruitment; facilities that performed their own extraction/abstraction took longer to complete data collection.

CONCLUSION

Examining DS practices and follow-up among cancer survivors necessitated recruiting and working directly with multiple healthcare systems and facilities. There were a number of lessons learned related to recruitment, enrollment, and data collection. Using the facilitators described in this manuscript offers increased potential for working successfully with various cancer centers and insight into partnering with facilities collecting non-standardized DS clinical data.

Implementation of a Transitional Care Model for Stroke: Perspectives From Frontline Clinicians, Administrators, and COMPASS-TC Implementation Staff

BACKGROUND AND OBJECTIVES

Stroke is a chronic, complex condition that disproportionally affects older adults. Health systems are evaluating innovative transitional care (TC) models to improve outcomes in these patients. The Comprehensive Post-Acute Stroke Services (COMPASS) Study, a large cluster-randomized pragmatic trial, tested a TC model for patients with stroke or transient ischemic attack discharged home from the hospital. The implementation of COMPASS-TC in complex real-world settings was evaluated to identify successes and challenges with integration into the clinical workflow.

RESEARCH DESIGN AND METHODS

We conducted a concurrent process evaluation of COMPASS-TC implementation during the first year of the trial. Qualitative data were collected from 4 sources across 19 intervention hospitals. We analyzed transcripts from 43 conference calls with hospital clinicians, individual and group interviews with leaders and clinicians from 9 hospitals, and 2 interviews with the COMPASS-TC Director of Implementation using iterative thematic analysis. Themes were compared to the domains of the RE-AIM framework.

RESULTS

Organizational, individual, and community factors related to Reach, Adoption, and Implementation were identified. Organizational readiness was an additional key factor to successful implementation, in that hospitals that were not "organizationally ready" had more difficulty addressing implementation challenges.

DISCUSSION AND IMPLICATIONS

Multifaceted TC models are challenging to implement. Facilitators of implementation were organizational commitment and capacity, prioritizing implementation of innovative delivery models to provide comprehensive care, being able to address challenges quickly, implementing systems for tracking patients throughout the intervention, providing clinicians with autonomy and support to address challenges, and adequately resourcing the intervention.

CLINICAL TRIAL REGISTRATION

NCT02588664.

Randomized Pragmatic Trial of Stroke Transitional Care: The COMPASS Study

Background The objectives of this study were to develop and test in real-world clinical practice the effectiveness of a comprehensive postacute stroke transitional care (TC) management program. Methods and Results The COMPASS study (Comprehensive Post-Acute Stroke Services) was a pragmatic cluster-randomized trial where the hospital was the unit of randomization. The intervention (COMPASS-TC) was initiated at 20 hospitals, and 20 hospitals provided their usual care. Hospital staff enrolled 6024 adult stroke and transient ischemic attack patients discharged home between 2016 and 2018. COMPASS-TC was patient-centered and assessed social and functional determinates of health to inform individualized care plans. Ninety-day outcomes were evaluated by blinded telephone interviewers. The primary outcome was functional status (Stroke Impact Scale-16); secondary outcomes were mortality, disability, medication adherence, depression, cognition, self-rated health, fatigue, care satisfaction, home blood pressure monitoring, and falls. The primary analysis was intention to treat. Of intervention hospitals, 58% had uninterrupted intervention delivery. Thirty-five percent of patients at intervention hospitals attended a COMPASS clinic visit. The primary outcome was measured for 59% of patients and was not significantly influenced by the intervention. Mean Stroke Impact Scale-16 (±SD) was 80.6±21.1 in TC versus 79.9±21.4 in usual care. Home blood pressure monitoring was self-reported by 72% of intervention patients versus 64% of usual care patients (adjusted odds ratio, 1.43 [95% CI, 1.21-1.70]). No other secondary outcomes differed. Conclusions Although designed according to the best available evidence with input from various stakeholders and consistent with Centers for Medicare and Medicaid Services TC policies, the COMPASS model of TC was not consistently incorporated into real-world health care. We found no significant effect of the intervention on functional status at 90 days post-discharge. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02588664.

Barriers and enablers to conducting cluster randomized control trials in hospitals: A theory-informed scoping review

BACKGROUND

Cluster randomized control trials (cRCTs) have unique challenges compared to single site trials with regards to conduct of the trial, and it is important to understand these barriers. The aim of this scoping review was to describe the current literature surrounding the implementation of the cRCTs in hospitals.

METHODS

The search strategy was designed to identify literature relevant to conduct of cRCTs, with hospitals as the unit of randomization. Data was extracted and was mapped using the Consolidated Framework for Implementation Research (CFIR) as a codebook, which contains 39 constructs organized into five domains.

RESULTS

Twenty-two articles met inclusion criteria and were included. 18 of 39 constructs of the CFIR were identified in coding, spanning four of the five domains. Barriers to the conduct of the trial were rarely reported as the main outcome of the study, and few details were included in the identified literature.

CONCLUSIONS

The review can provide guidance to future researchers planning cRCTs in hospitals. It also identified a large gap in reporting of conduct of these trials, demonstrating the need for a research agenda that further explores the barriers and facilitators, with the aim of garnering knowledge for improved guidance in the implementation.

Implementation of a billable transitional care model for stroke patients: the COMPASS study

Background

The COMprehensive Post-Acute Stroke Services (COMPASS) pragmatic trial compared the effectiveness of comprehensive transitional care (COMPASS-TC) versus usual care among stroke and transient ischemic attack (TIA) patients discharged home from North Carolina hospitals. We evaluated implementation of COMPASS-TC in 20 hospitals randomized to the intervention using the RE-AIM framework.

Methods

We evaluated hospital-level Adoption of COMPASS-TC; patient Reach (meeting transitional care management requirements of timely telephone and face-to-face follow-up); Implementation using hospital quality measures (concurrent enrollment, two-day telephone follow-up, 14-day clinic visit scheduling); and hospital-level sustainability (Maintenance). Effectiveness compared 90-day physical function (Stroke Impact Scale-16), between patients receiving COMPASS-TC versus not. Associations between hospital and patient characteristics with Implementation and Reach measures were estimated with mixed logistic regression models.

Results

Adoption: Of 95 eligible hospitals, 41 (43%) participated in the trial. Of the 20 hospitals randomized to the intervention, 19 (95%) initiated COMPASS-TC.

Reach: A total of 24% (656/2751) of patients enrolled received a billable TC intervention, ranging from 6 to 66% across hospitals.

Implementation: Of eligible patients enrolled, 75.9% received two-day calls (or two attempts) and 77.5% were scheduled/offered clinic visits. Most completed visits (78% of 975) occurred within 14 days.

Effectiveness: Physical function was better among patients who attended a 14-day visit versus those who did not (adjusted mean difference: 3.84, 95% CI 1.42–6.27, p = 0.002).

Maintenance: Of the 19 adopting hospitals, 14 (74%) sustained COMPASS-TC.

Conclusions

COMPASS-TC implementation varied widely. The greatest challenge was reaching patients because of system difficulties maintaining consistent delivery of follow-up visits and patient preferences to pursue alternate post-acute care. Receiving COMPASS-TC was associated with better functional status.

Trial registration

ClinicalTrials.gov number: NCT02588664. Registered 28 October 2015.

Recruitment challenges in stroke neurorecovery clinical trials

There are multiple available treatments to enhance stroke rehabilitation, although few interventions have confirmed significant clinical improvements on motor function in pivotal Randomized Clinical Trials. Development of large Randomized Clinical Trials is limited by several barriers and low enrollment rate is considered an important factor. Consequently, most of the evidence comes from small sample size studies, often leading to limited conclusions. According to the National Institute of Health (NIH), about 80% of clinical trials in the United States do not achieve their timelines, increasing research costs and postponing regulatory approval of new therapies. Given that the success of a Randomized Clinical Trial is dependent on enrolling an adequate number of subjects, effective strategies to enhance recruitment rates are highly desirable. In addition, given the resources and time limitations, it is important to understand which strategies are most cost-effective. In this manuscript, we summarize and discuss nine recruitment strategies used in an NIH R21 sponsored clinical trial, including medical records review and online advertising, among others. In addition, we developed an index to compare the time spent benefit of each approach and guide the allocation of the recruitment efforts. For this trial, online advertising and referral from health care professionals other than physicians were the strategies with greater time-benefit, leading to the largest number of stroke subjects enrolled.

Telephone interventions, delivered by healthcare professionals, for providing education and psychosocial support for informal caregivers of adults with diagnosed illnesses

BACKGROUND

Maintaining care for ill persons in the community is heavily dependent on support from unpaid caregivers. Many caregivers, however, find themselves in a caring role for which they are ill prepared and may require professional support. The telephone is an easily accessible method of providing support irrespective of geographical location.

OBJECTIVES

The objective of this review was to evaluate the effectiveness of telephone support interventions, delivered by healthcare professionals, when compared to usual care or non-telephone-based support interventions for providing education and psychosocial support for informal caregivers of people with acute and chronic diagnosed illnesses, and to evaluate the cost-effectiveness of telephone interventions in this population.

SEARCH METHODS

We searched the following databases from inception to 16 November 2018: the Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; Embase; PsycINFO; ProQuest Dissertations and Theses A&I; and CINAHL Complete. We also searched 11 caregiver-specific websites, three conference links, and two clinical trial registries.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) (including cluster-RCTs) and quasi-RCTs. We excluded cross-over trials because of the high risk of carry-over effects from one intervention to another.

DATA COLLECTION AND ANALYSIS

Two authors independently screened citations against the review's inclusion criteria, extracted data, and assessed the included studies using the Cochrane 'Risk of bias' tool. The review's prespecified primary (quality of life and burden) and secondary outcomes (skill acquisition, psychological health, knowledge, health status and well-being, family functioning, satisfaction, and economic outcomes), where reported, were assessed at the end of intervention delivery and at short-term (≤ 3 months), medium-term (> 3 to ≤ 6 months) and longer-term time points (> 6 to 12 months) following the intervention. Where possible, meta-analyses were conducted, otherwise results were reported narratively.

MAIN RESULTS

We included 21 randomised studies involving 1,690 caregivers; 19 studies compared telephone support interventions and usual care, of which 18 contributed data to the analyses. Two studies compared telephone and non-telephone professional support interventions. Caregiver ages ranged from 19 years to 87 years across studies. The majority of participants were female (> 70.53%), with two trials including females only. Most caregivers were family members, educated beyond secondary or high school level or had the equivalent in years of education. All caregivers were based in the community. Overall risk of bias was high for most studies.The results demonstrated that there is probably little or no difference between telephone support interventions and usual care for the primary outcome of quality of life at the end of intervention (SMD -0.02, 95% CI -0.24 to 0.19, 4 studies, 364 caregivers) (moderate-certainty evidence) or burden at the end of intervention (SMD -0.11, 95% CI -0.30 to 0.07, 9 studies, 788 caregivers) (low-certainty evidence). For one study where quality of life at the end of intervention was reported narratively, the findings indicated that a telephone support intervention may result in slightly higher quality of life, compared with usual care. Two further studies on caregiver burden were reported narratively; one reported that telephone support interventions may decrease burden, the other reported no change in the intervention group, compared with usual care.We are uncertain about the effects of telephone support interventions on caregiver depression at the end of intervention (SMD -0.37, 95% CI -0.70 to -0.05, 9 studies, 792 caregivers) due to very low-certainty evidence for this outcome. Depression was reported narratively for three studies. One reported that the intervention may reduce caregiver depression at the end of intervention, but this effect was not sustained at short-term follow-up. The other two studies reported there may be little or no difference between telephone support and usual care for depression at the end of intervention. Six studies measured satisfaction with the intervention but did not report comparative data. All six reported high satisfaction scores with the intervention. No adverse events, including suicide or suicide ideation, were measured or reported by any of the included studies.Our analysis indicated that caregiver anxiety may be slightly reduced (MD -6.0, 95% CI -11.68 to -0.32, 1 study, 61 caregivers) and preparedness to care slightly improved (SMD 0.37, 95% CI 0.09 to 0.64, 2 studies, 208 caregivers) at the end of intervention, following telephone-only support interventions compared to usual care. Findings indicated there may be little or no difference between telephone support interventions and usual care for all of the following outcomes at the end of intervention: problem-solving, social activity, caregiver competence, coping, stress, knowledge, physical health, self-efficacy, family functioning, and satisfaction with supports (practical or social). There may also be little or no effect of telephone support interventions for quality of life and burden at short-term follow-up or for burden and depression at medium-term follow-up.Litttle or no difference was found between groups for any of the reported outcomes in studies comparing telephone and non-telephone professional support interventions. We are uncertain as to the effects of telephone support interventions compared to non-telephone support interventions for caregiver burden and depression at the end of intervention. No study reported on quality of life or satisfaction with the intervention and no adverse events were reported or noted in the two studies reporting on this comparison.

AUTHORS' CONCLUSIONS

Although our review indicated slight benefit may exist for telephone support interventions on some outcomes (e.g. anxiety and preparedness to care at the end of intervention), for most outcomes, including the primary outcomes, telephone-only interventions may have little or no effect on caregiver outcomes compared to usual care. The findings of the review were mainly based on studies with overall high risk of bias, and few participants. Further high-quality trials, with larger sample sizes are required.

Meeting Medicare requirements for transitional care: Do stroke care and policy align?

OBJECTIVE

This study (1) describes transitional care for stroke patients discharged home from hospitals, (2) compares hospitals' standards of transitional care with core transitional care management (TCM) components recognized by Medicare, and (3) examines the association of policy and hospital specialty designations with TCM implementation.

METHODS

Hospitals participating in the Comprehensive Post-Acute Stroke Services (COMPASS) Study provided data on their hospital, stroke patient population, and standards of transitional care. Hospital-reported transitional care strategies were compared with the federal TCM definition (2-day follow-up, 14-day visit, non-face-to-face services). We examined the associations of TCM billing, stroke center certification, and Magnet nursing excellence designation with TCM implementation.

RESULTS

Transitional care varied widely among 41 hospitals in North Carolina and no one strategy was universally applied or provided across hospitals. One third of hospitals met the TCM definition (37% provided telephone follow-up, 76% provided face-to-face provider follow-up, all provided a type of non-face-to-face support). There were no differences between groups (TCM met/not met) in hospital characteristics or transitional care resources and processes. Stroke center certification, Magnet designation, and use of TCM billing codes were not different for hospitals that did and did not meet the TCM definition.

CONCLUSIONS

There was substantial variation in the provision of strategies supporting stroke patients' transition home from the hospital. Supportive stroke care transitions are essential when more than 50% of stroke patients are discharged home and more than half experience moderate to severe strokes. More research is needed to identify drivers of TCM uptake.

CLINICALTRIALSGOV IDENTIFIER

NCT02588664.

Challenges of conducting research in long-term care facilities: a systematic review

Background

The aim of this review is to describe the challenges and barriers to conducting research in long-term care facilities.

Methods

A literature search was conducted in Ovid MEDLINE, Embase, Cochrane Central, PsycINFO and CINAHL. Keywords used included “long term care”, “nursing home”, “research”, “trial”, “challenge” and “barrier”, etc. Resulting references were screened in order to identify relevant studies that reported on challenges derived from first-hand experience of empirical research studies. Challenges were summarized and synthesized.

Results

Of 1723 references, 39 articles were selected for inclusion. To facilitate understanding we proposed a classification framework of 8 main themes to categorize the research challenges presented in the 39 studies, relating to the characteristics of facility/owner/administrator, resident, staff caregiver, family caregiver, investigator, ethical or legal concerns, methodology, and budgetary considerations.

Conclusions

Conducting research in long-term care facilities is full of challenges which can be categorized into 8 main themes. Investigators should be aware of all these challenges and specifically address them when planning their studies. Stakeholders should be involved from an early stage and flexibility should be built into both the methodology and research budget.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0934-9) contains supplementary material, which is available to authorized users.

A Person-Centered Approach to Poststroke Care: The COMprehensive Post-Acute Stroke Services Model

Many individuals who have had a stroke leave the hospital without postacute care services in place. Despite high risks of complications and readmission, there is no standard in the United States for postacute stroke care after discharge home. We describe the rationale and methods for the development of the COMprehensive Post-Acute Stroke Services (COMPASS) care model and the structure and quality metrics used for implementation. COMPASS, an innovative, comprehensive extension of the TRAnsition Coaching for Stroke (TRACS) program, is a clinician-led quality improvement model providing early supported discharge and transitional care for individuals who have had a stroke and have been discharged home. The effectiveness of the COMPASS model is being assessed in a cluster-randomized pragmatic trial in 41 sites across North Carolina, with a recruitment goal of 6,000 participants. The COMPASS model is evidence based, person centered, and stakeholder driven. It involves identification and education of eligible individuals in the hospital; telephone follow-up 2, 30, and 60 days after discharge; and a clinic visit within 14 days conducted by a nurse and advanced practice provider. Patient and caregiver self-reported assessments of functional and social determinants of health are captured during the clinic visit using a web-based application. Embedded algorithms immediately construct an individualized care plan. The COMPASS model's pragmatic design and quality metrics may support measurable best practices for postacute stroke care.