Implementation Support for a Social Risk Screening and Referral Process in Community Health Centers.

Evidence is needed about how to effectively support health care providers in implementing screening for social risks (adverse social determinants of health) and providing related referrals meant to address identified social risks. This need is greatest in underresourced care settings. The authors tested whether an implementation support intervention (6 months of technical assistance and coaching study clinics through a five-step implementation process) improved adoption of social risk activities in community health centers (CHCs). Thirty-one CHC clinics were block-randomized to six wedges that occurred sequentially. Over the 45-month study period from March 2018 to December 2021, data were collected for 6 or more months preintervention, the 6-month intervention period, and 6 or more months postintervention. The authors calculated clinic-level monthly rates of social risk screening results that were entered at in-person encounters and rates of social risk-related referrals. Secondary analyses measured impacts on diabetes-related outcomes. Intervention impact was assessed by comparing clinic performance based on whether they had versus had not yet received the intervention in the preintervention period compared with the intervention and postintervention periods. In assessing the results, the authors note that five clinics withdrew from the study for various bandwidth-related reasons. Of the remaining 26, a total of 19 fully or partially completed all 5 implementation steps, and 7 fully or partially completed at least the first 3 steps. Social risk screening was 2.45 times (95% confidence interval [CI], 1.32-4.39) higher during the intervention period compared with the preintervention period; this impact was not sustained postintervention (rate ratio, 2.16; 95% CI, 0.64-7.27). No significant difference was seen in social risk referral rates during the intervention or postintervention periods. The intervention was associated with greater blood pressure control among patients with diabetes and lower rates of diabetes biomarker screening postintervention. All results must be interpreted considering that the Covid-19 pandemic began midway through the trial, which affected care delivery generally and patients at CHCs particularly. Finally, the study results show that adaptive implementation support was effective at temporarily increasing social risk screening. It is possible that the intervention did not adequately address barriers to sustained implementation or that 6 months was not long enough to cement this change. Underresourced clinics may struggle to participate in support activities over longer periods without adequate resources, even if lengthier support is needed. As policies start requiring documentation of social risk activities, safety-net clinics may be unable to meet these requirements without adequate financial and coaching/technical support.

Effect of Clinical Decision Support at Community Health Centers on the Risk of Cardiovascular Disease: A Cluster Randomized Clinical Trial.

Importance: Management of cardiovascular disease (CVD) risk in socioeconomically vulnerable patients is suboptimal; better risk factor control could improve CVD outcomes. Objective: To evaluate the impact of a clinical decision support system (CDSS) targeting CVD risk in community health centers (CHCs). Design, Setting, and Participants: This cluster randomized clinical trial included 70 CHC clinics randomized to an intervention group (42 clinics; 8 organizations) or a control group that received no intervention (28 clinics; 7 organizations) from September 20, 2018, to March 15, 2020. Randomization was by CHC organization accounting for organization size. Patients aged 40 to 75 years with (1) diabetes or atherosclerotic CVD and at least 1 uncontrolled major risk factor for CVD or (2) total reversible CVD risk of at least 10% were the population targeted by the CDSS intervention. Interventions: A point-of-care CDSS displaying real-time CVD risk factor control data and personalized, prioritized evidence-based care recommendations. Main Outcomes and Measures: One-year change in total CVD risk and reversible CVD risk (ie, the reduction in 10-year CVD risk that was considered achievable if 6 key risk factors reached evidence-based levels of control). Results: Among the 18 578 eligible patients (9490 [51.1%] women; mean [SD] age, 58.7 [8.8] years), patients seen in control clinics (n = 7419) had higher mean (SD) baseline CVD risk (16.6% [12.8%]) than patients seen in intervention clinics (n = 11 159) (15.6% [12.3%]; P < .001); baseline reversible CVD risk was similarly higher among patients seen in control clinics. The CDSS was used at 19.8% of 91 988 eligible intervention clinic encounters. No population-level reduction in CVD risk was seen in patients in control or intervention clinics; mean reversible risk improved significantly more among patients in control (-0.1% [95% CI, -0.3% to -0.02%]) than intervention clinics (0.4% [95% CI, 0.3% to 0.5%]; P < .001). However, when the CDSS was used, both risk measures decreased more among patients with high baseline risk in intervention than control clinics; notably, mean reversible risk decreased by an absolute 4.4% (95% CI, -5.2% to -3.7%) among patients in intervention clinics compared with 2.7% (95% CI, -3.4% to -1.9%) among patients in control clinics (P = .001). Conclusions and Relevance: The CDSS had low use rates and failed to improve CVD risk in the overall population but appeared to have a benefit on CVD risk when it was consistently used for patients with high baseline risk treated in CHCs. Despite some limitations, these results provide preliminary evidence that this technology has the potential to improve clinical care in socioeconomically vulnerable patients with high CVD risk. Trial Registration: ClinicalTrials.gov Identifier: NCT03001713.

Applying a scoping review approach for identifying effective implementation strategies in oral health settings.

Dental service providers have limited capacity to identify strategies to implement evidence-based practices (EBPs). We developed a rigorous yet parsimonious scoping review approach to identify, select, and rate implementation strategies based on an oral health system context. From 153 strategies identified, we selected the top 11 strategies, which had a moderate level of support of evidence and where managers were the main actors. The main actions were to educate, remind, structure, and influence. Targets included dentists, dental hygienists, and assistants and managers from a large prepaid dental care delivery system. This approach responds to calls for rapid and innovative methods to implement EBPs in oral health.

Using Electronic Health Record-Based Clinical Decision Support to Provide Social Risk-Informed Care in Community Health Centers: Protocol for the Design and Assessment of a Clinical Decision Support Tool.

BACKGROUND: Consistent and compelling evidence demonstrates that social and economic adversity has an impact on health outcomes. In response, many health care professional organizations recommend screening patients for experiences of social and economic adversity or social risks-for example, food, housing, and transportation insecurity-in the context of care. Guidance on how health care providers can act on documented social risk data to improve health outcomes is nascent. A strategy recommended by the National Academy of Medicine involves using social risk data to adapt care plans in ways that accommodate patients' social risks. OBJECTIVE: This study's aims are to develop electronic health record (EHR)-based clinical decision support (CDS) tools that suggest social risk-informed care plan adaptations for patients with diabetes or hypertension, assess tool adoption and its impact on selected clinical quality measures in community health centers, and examine perceptions of tool usability and impact on care quality. METHODS: A systematic scoping review and several stakeholder activities will be conducted to inform development of the CDS tools. The tools will be pilot-tested to obtain user input, and their content and form will be revised based on this input. A randomized quasi-experimental design will then be used to assess the impact of the revised tools. Eligible clinics will be randomized to a control group or potential intervention group; clinics will be recruited from the potential intervention group in random order until 6 are enrolled in the study. Intervention clinics will have access to the CDS tools in their EHR, will receive minimal implementation support, and will be followed for 18 months to evaluate tool adoption and the impact of tool use on patient blood pressure and glucose control. RESULTS: This study was funded in January 2020 by the National Institute on Minority Health and Health Disparities of the National Institutes of Health. Formative activities will take place from April 2020 to July 2021, the CDS tools will be developed between May 2021 and November 2022, the pilot study will be conducted from August 2021 to July 2022, and the main trial will occur from December 2022 to May 2024. Study data will be analyzed, and the results will be disseminated in 2024. CONCLUSIONS: Patients' social risk information must be presented to care teams in a way that facilitates social risk-informed care. To our knowledge, this study is the first to develop and test EHR-embedded CDS tools designed to support the provision of social risk-informed care. The study results will add a needed understanding of how to use social risk data to improve health outcomes and reduce disparities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/31733.

Study protocol: A stepped-wedge, cluster-randomized trial of the effectiveness of a deliberative loop in identifying implementation strategies for the adoption of a dental sealant guideline in dental clinics.

BACKGROUND: The American Dental Association (ADA) recommends dental providers apply dental sealants to the occlusal surfaces of permanent molars for the prevention or treatment of non-cavitated dental caries. Despite the evidence-based support for this guideline, adherence among general dentists is low, ranging from less than 5 to 38.5%. Thus, an evidence-to-practice gap exists, and it is unclear which implementation strategies would best support providers in adopting and implementing the evidence-based practice. One potential approach to selecting and tailoring implementation strategies is a deliberative loop process, a stakeholder-engaged approach to decision-making. This trial aims to test the acceptability, feasibility, and effectiveness of using a deliberative loop intervention with stakeholders (i.e., providers and staff) to enable managers to select implementation strategies that facilitate the adoption of an evidence-based dental practice. METHODS: Sixteen dental clinics within Kaiser Permanente Northwest Dental will be cluster randomized to determine the timing of receiving the intervention in this stepped-wedge trial. In the three-part deliberative loop intervention, clinic stakeholders engage in the following activities: (1) receive background information, (2) participate in facilitated small-group discussions designed to promote learning from each other's lived experiences and develop informed opinions about effective clinic-level implementation strategies, and (3) share their informed opinions with clinic leaders, who may then choose to select and deploy implementation strategies based on the stakeholders' informed opinions. The primary outcome of Reach will be defined as patient-level receipt of guideline-concordant care. Secondary outcomes will include the cost-effectiveness, acceptability, and feasibility of the deliberative loop process. Implementation strategies deployed will be catalogued over time. DISCUSSION: These results will establish the extent to which the deliberative loop process can help leaders select and tailor implementation strategies with the goal of improving guideline-concordant dental care. TRIAL REGISTRATION: This project is registered at ClinicalTrials.gov with ID NCT04682730. The trial was first registered on 12/18/2020. https://clinicaltrials.gov/ct2/show/NCT04682730.

Study protocol: a pragmatic, stepped-wedge trial of tailored support for implementing social determinants of health documentation/action in community health centers, with realist evaluation.

BACKGROUND: National leaders recommend documenting social determinants of health and actions taken to address social determinants of health in electronic health records, and a growing body of evidence suggests the health benefits of doing so. However, little evidence exists to guide implementation of social determinants of health documentation/action. METHODS: This paper describes a 5-year, mixed-methods, stepped-wedge trial with realist evaluation, designed to test the impact of providing 30 community health centers with step-by-step guidance on implementing electronic health record-based social determinants of health documentation. This guidance will entail 6 months of tailored support from an interdisciplinary team, including training and technical assistance. We will report on tailored support provided at each of five implementation steps; impact of tailored implementation support; a method for tracking such tailoring; and context-specific pathways through which these tailored strategies effect change. We will track the competencies and resources needed to support the study clinics' implementation efforts. DISCUSSION: Results will inform how to tailor implementation strategies to meet local needs in real-world practice settings. Secondary analyses will assess impacts of social determinants of health documentation and referral-making on diabetes outcomes. By learning whether and how scalable, tailored implementation strategies help community health centers adopt social determinants of health documentation and action, this study will yield timely guidance to primary care providers. We are not aware of previous studies exploring implementation strategies that support adoption of social determinants of action using electronic health and interventions, despite the pressing need for such guidance. TRIAL REGISTRATION: clinicaltrials.gov, NCT03607617 , registration date: 7/31/2018-retrospectively registered.