Implementation of Health IT for Cancer Screening in US Primary Care: Scoping Review

BACKGROUND

A substantial percentage of the US population is not up to date on guideline-recommended cancer screenings. Identifying interventions that effectively improve screening rates would enhance the delivery of such screening. Interventions involving health IT (HIT) show promise, but much remains unknown about how HIT is optimized to support cancer screening in primary care.

OBJECTIVE

This scoping review aims to identify (1) HIT-based interventions that effectively support guideline concordance in breast, cervical, and colorectal cancer screening provision and follow-up in the primary care setting and (2) barriers or facilitators to the implementation of effective HIT in this setting.

METHODS

Following scoping review guidelines, we searched MEDLINE, CINAHL Plus, Web of Science, and IEEE Xplore databases for US-based studies from 2015 to 2021 that featured HIT targeting breast, colorectal, and cervical cancer screening in primary care. Studies were dual screened using a review criteria checklist. Data extraction was guided by the following implementation science frameworks: the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework; the Expert Recommendations for Implementing Change taxonomy; and implementation strategy reporting domains. It was also guided by the Integrated Technology Implementation Model that incorporates theories of both implementation science and technology adoption. Reporting was guided by PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews).

RESULTS

A total of 101 studies met the inclusion criteria. Most studies (85/101, 84.2%) involved electronic health record-based HIT interventions. The most common HIT function was clinical decision support, primarily used for panel management or at the point of care. Most studies related to HIT targeting colorectal cancer screening (83/101, 82.2%), followed by studies related to breast cancer screening (28/101, 27.7%), and cervical cancer screening (19/101, 18.8%). Improvements in cancer screening were associated with HIT-based interventions in most studies (36/54, 67% of colorectal cancer-relevant studies; 9/14, 64% of breast cancer-relevant studies; and 7/10, 70% of cervical cancer-relevant studies). Most studies (79/101, 78.2%) reported on the reach of certain interventions, while 17.8% (18/101) of the included studies reported on the adoption or maintenance. Reported barriers and facilitators to HIT adoption primarily related to inner context factors of primary care settings (eg, staffing and organizational policies that support or hinder HIT adoption). Implementation strategies for HIT adoption were reported in 23.8% (24/101) of the included studies.

CONCLUSIONS

There are substantial evidence gaps regarding the effectiveness of HIT-based interventions, especially those targeting guideline-concordant breast and colorectal cancer screening in primary care. Even less is known about how to enhance the adoption of technologies that have been proven effective in supporting breast, colorectal, or cervical cancer screening. Research is needed to ensure that the potential benefits of effective HIT-based interventions equitably reach diverse primary care populations.

Pandemic-related practice changes and CVD risk management in community clinics

OBJECTIVES

Understanding how the COVID-19 pandemic affected cardiovascular disease (CVD) risk monitoring in primary care may inform new approaches for addressing modifiable CVD risks. This study examined how pandemic-driven changes in primary care delivery affected CVD risk management processes.

STUDY DESIGN

This retrospective study used electronic health record data from patients at 70 primary care community clinics with scheduled appointments from September 1, 2018, to September 30, 2021.

METHODS

Analyses examined associations between appointment type and select care process measures: appointment completion rates, time to appointment, and up-to-date documentation for blood pressure (BP) and hemoglobin A1c (HbA1c).

RESULTS

Of 1,179,542 eligible scheduled primary care appointments, completion rates were higher for virtual care (VC) vs in-person appointments (10.7 percentage points [PP]; 95% CI, 10.5-11.0; P < .001). Time to appointment was shorter for VC vs in-person appointments (-3.9 days; 95% CI, -4.1 to -3.7; P < .001). BP documentation was higher for appointments completed pre- vs post pandemic onset (16.2 PP; 95% CI, 16.0-16.5; P < .001) and for appointments completed in person vs VC (54.9 PP; 95% CI, 54.6-55.2; P < .001). HbA1c documentation was higher for completed appointments after pandemic onset vs before (5.9 PP; 95% CI, 5.1-6.7; P < .001) and for completed VC appointments vs in-person appointments (3.9 PP; 95% CI, 3.0-4.7; P < .001).

CONCLUSIONS

After pandemic onset, appointment completion rates were higher, time to appointment was shorter, HbA1c documentation increased, and BP documentation decreased. Future research should explore the advantages of using VC for CVD risk management while continuing to monitor for unintended consequences.

Cardiovascular disease risk management during COVID-19: in-person vs virtual visits

OBJECTIVES

Limited research has assessed how virtual care (VC) affects cardiovascular disease (CVD) risk management, especially in community clinic settings. This study assessed change in community clinic patients' CVD risk management during the COVID-19 pandemic and CVD risk factor control among patients who had primarily in-person or primarily VC visits.

STUDY DESIGN

Retrospective interrupted time-series analysis.

METHODS

Data came from an electronic health record shared by 52 community clinics for index (March 1, 2019, to February 29, 2020) and follow-up (July 1, 2020, to February 28, 2022) periods. Analyses compared follow-up period changes in slope and level of population monthly means of 10-year reversible CVD risk score, blood pressure (BP), and hemoglobin A1c (HbA1c) among patients whose completed follow-up period visits were primarily in person vs primarily VC. Propensity score weighting minimized confounding.

RESULTS

There were 10,028 in-person and 6593 VC patients in CVD risk analyses, 9874 in-person and 5390 VC patients in BP analyses, and 8221 in-person and 4937 VC patients in HbA1c analyses. The VC group was more commonly younger, female, White, and urban. Mean reversible CVD risk, mean systolic BP, and percentage of BP measurements that were 140/90 mm Hg or higher increased significantly from index to follow-up periods in both groups. Rate of change between these periods was the same for all outcomes in both groups, regardless of care modality.

CONCLUSIONS

Among community clinic patients with CVD risk, receiving a majority of care in person vs a majority of care via VC was not significantly associated with longitudinal trends in reversible CVD risk score or key CVD risk factors.

Area-level social determinants of health and individual-level social risks: Assessing predictive ability and biases in social risk screening

Introduction

Area-level social determinants of health (SDoH) and individual-level social risks are different, yet area-level measures are frequently used as proxies for individual-level social risks. This study assessed whether demographic factors were associated with patients being screened for individual-level social risks, the percentage who screened positive for social risks, and the association between SDoH and patient-reported social risks in a nationwide network of community-based health centers.

Methods

Electronic health record data from 1,330,201 patients with health center visits in 2021 were analyzed using multilevel logistic regression. Associations between patient characteristics, screening receipt, and screening positive for social risks (e.g., food insecurity, housing instability, transportation insecurity) were assessed. The predictive ability of three commonly used SDoH measures (Area Deprivation Index, Social Deprivation Index, Material Community Deprivation Index) in identifying individual-level social risks was also evaluated.

Results

Of 244,155 (18%) patients screened for social risks, 61,414 (25.2%) screened positive. Sex, race/ethnicity, language preference, and payer were associated with both social risk screening and positivity. Significant health system-level variation in both screening and positivity was observed, with an intraclass correlation coefficient of 0.55 for social risk screening and 0.38 for positivity. The three area-level SDoH measures had low accuracy, sensitivity, and area under the curve when used to predict individual social needs.

Conclusion

Area-level SDoH measures may provide valuable information about the communities where patients live. However, policymakers, healthcare administrators, and researchers should exercise caution when using area-level adverse SDoH measures to identify individual-level social risks.

Finding meaning: a realist-informed perspective on social risk screening and relationships as mechanisms of change

Background

Social risk screening rates in many US primary care settings remain low. This realist-informed evaluation explored the mechanisms through which a tailored coaching and technical training intervention impacted social risk screening uptake in 26 community clinics across the United States.

Methods

Evaluation data sources included the documented content of interactions between the clinics and implementation support team and electronic health record (EHR) data. Following the realist approach, analysis was composed of iterative cycles of developing, testing and refining program theories about how the intervention did-or didn't-work, for whom, under what circumstances. Normalization Process Theory was applied to the realist program theories to enhance the explanatory power and transferability of the results.

Results

Analysis identified three overarching realist program theories. First, clinic staff perceptions about the role of standardized social risk screening in person-centered care-considered "good" care and highly valued-strongly impacted receptivity to the intervention. Second, the physicality of the intervention materials facilitated collaboration and impacted clinic leaders' perception of the legitimacy of the social risk screening implementation work. Third, positive relationships between the implementation support team members, between the support team and clinic champions, and between clinic champions and staff motivated and inspired clinic staff to engage with the intervention and to tailor workflows to their settings' needs. Study clinics did not always exhibit the social risk screening patterns anticipated by the program theories due to discrepant definitions of success between clinic staff (improved ability to provide contextualized, person-centered care) and the trial (increased rates of EHR-documented social risk screening). Aligning the realist program theories with Normalization Process Theory constructs clarified that the intervention as implemented emphasized preparation over operationalization and appraisal, providing insight into why the intervention did not successfully embed sustained systematic social risk screening in participating clinics.

Conclusion

The realist program theories highlighted the effectiveness and importance of intervention components and implementation strategies that support trusting relationships as mechanisms of change. This may be particularly important in social determinants of health work, which requires commitment and humility from health care providers and vulnerability on the part of patients.

Implementation of Social Isolation Screening and an Integrated Community Resource Referral Platform

BACKGROUND

Screening and referral programs for social isolation and loneliness in older patients increased during the COVID-19 pandemic in primary care settings to mitigate associated adverse health outcomes. This study explores community health centers' experiences implementing a social isolation and loneliness screening program involving a community resource referral platform integrated into the electronic health record to support referrals.

METHODS

A formative mixed methods evaluation in 4 community health centers. Semistructured interviews, observation of implementation meetings, facilitated group discussions, surveys, and utilization data extracted from the electronic health record and community resource referral platform were collected and analyzed concurrently.

RESULTS

Screening for social isolation and loneliness can heighten health center staff knowledge and prioritization of socially isolated older patients. Participants indicate using an integrated community resource referral platform may only be useful in certain circumstances, particularly for those located outside urban areas. The experiences of these health centers indicate that when implementing interventions to mitigate patients' social isolation and loneliness, it is necessary to consider other resource directories, needed adjustments to referral and documentation workflows, and potential impacts on patients and care teams.

CONCLUSION

Screening older patients for social isolation could increase care team awareness of social risk; assistance related referral options should be considered carefully.

Does Clinical Decision Support Increase Appropriate Medication Prescribing for Cardiovascular Risk Reduction?

PURPOSE

To assess the impact of a clinical decision support (CDS) system's recommendations on prescribing patterns targeting cardiovascular disease (CVD) when the recommendations are prioritized in order from greatest to least benefit toward overall CVD risk reduction.

METHODS

Secondary analysis of trial data from September 20, 2018, to March 15, 2020, where 70 community health center clinics were cluster-randomized to the CDS intervention (42 clinics; 8 organizations) or control group (28 clinics; 7 organizations). Included patients were medication-naïve and aged 40 to 75 years with ≥1 uncontrolled cardiovascular disease risk factor, with known diabetes or cardiovascular disease, or ≥10% 10-year reversible CVD risk.

RESULTS

Among eligible encounters with 29,771 patients, the probability of prescribing a medication targeting hypertension was greater at intervention clinic encounters when CDS was used (34.9% [95% CI, 31.5 to 38.3]) versus dismissed (29.6% [95% CI, 26.7 to 32.6]; P < .001), but not when compared with control clinic encounters (34.9% [95% CI, 31.1 to 38.7]; P = .998). Prescribing for dyslipidemia was significantly higher at intervention encounters where the CDS system was used (11.3% [95% CI, 9.3 to 13.3]) compared with dismissed (7.7% [95% CI, 6.1 to 9.3]; P = .003) and to control encounters (8.7% [95% CI, 7.0 to 10.4]; P = .044); smoking cessation medication showed a similar pattern. Except for dyslipidemia, prescribing rates increased according to their prioritization.

CONCLUSIONS

Use of this CDS system was associated with significantly higher prescribing targeting most cardiovascular risk factors. These results highlight how displaying prioritized actions to reduce reversible CVD risk could improve risk management.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03001713, https://clinicaltrials.gov/.

Food Insecurity Screening in Primary Care: Patterns During the COVID-19 Pandemic by Encounter Modality

INTRODUCTION

Screening for food insecurity in clinical settings is recommended, but implementation varies widely. This study evaluated the prevalence of screening for food insecurity and other social risks in telehealth versus in-person encounters during the COVID-19 pandemic and changes in screening before versus after widespread COVID-19 vaccine availability.

METHODS

These cross-sectional analyses used electronic health record and ancillary clinic data from a national network of 400+ community health centers with a shared electronic health record. Food insecurity screening was characterized in 2022 in a sample of 275,465 first encounters for routine primary care at any network clinic during March 11, 2020-December 31, 2021. An adjusted multivariate multilevel probit model estimated screening prevalence on the basis of encounter mode (in-person versus telehealth) and time period (initial pandemic versus after vaccine availability) in a random subsample of 11,000 encounters.

RESULTS

Encounter mode was related to food insecurity screening (p<0.0001), with an estimated 9.2% screening rate during in-person encounters, compared with 5.1% at telehealth encounters. There was an interaction between time period and encounter mode (p<0.0001), with higher screening prevalence at in-person versus telehealth encounters after COVID-19 vaccines were available (11.7% vs 4.9%) than before vaccines were available (7.8% vs 5.2%).

CONCLUSIONS

Food insecurity screening in first primary care encounters is low overall, with lower rates during telehealth visits and the earlier phase of the COVID-19 pandemic. Future research should explore the methods for enhancing social risk screening in telehealth encounters.

Social Risk Screening and Response Equity: Assessment by Race, Ethnicity, and Language in Community Health Centers

INTRODUCTION

Little has previously been reported about the implementation of social risk screening across racial/ethnic/language groups. To address this knowledge gap, the associations between race/ethnicity/language, social risk screening, and patient-reported social risks were examined among adult patients at community health centers.

METHODS

Patient- and encounter-level data from 2016 to 2020 from 651 community health centers in 21 U.S. states were used; data were extracted from a shared Epic electronic health record and analyzed between December 2020 and February 2022. In adjusted logistic regression analyses stratified by language, robust sandwich variance SE estimators were applied with clustering on patient's primary care facility.

RESULTS

Social risk screening occurred at 30% of health centers; 11% of eligible adult patients were screened. Screening and reported needs varied significantly by race/ethnicity/language. Black Hispanic and Black non-Hispanic patients were approximately twice as likely to be screened, and Hispanic White patients were 28% less likely to be screened than non-Hispanic White patients. Hispanic Black patients were 87% less likely to report social risks than non-Hispanic White patients. Among patients who preferred a language other than English or Spanish, Black Hispanic patients were 90% less likely to report social needs than non-Hispanic White patients.

CONCLUSIONS

Social risk screening documentation and patient reports of social risks differed by race/ethnicity/language in community health centers. Although social care initiatives are intended to promote health equity, inequitable screening practices could inadvertently undermine this goal. Future implementation research should explore strategies for equitable screening and related interventions.

Uptake of a Cervical Cancer Clinical Decision Support Tool: A Mixed-Methods Study

OBJECTIVES

Clinical decision support (CDS) tools that provide point-of-care reminders of patients' care needs may improve rates of guideline-concordant cervical cancer screening. However, uptake of such electronic health record (EHR)-based tools in primary care practices is often low. This study describes the frequency of factors associated with, and barriers and facilitators to adoption of a cervical cancer screening CDS tool (CC-tool) implemented in a network of community health centers.

METHODS

This mixed-methods sequential explanatory study reports on CC-tool use among 480 community-based clinics, located across 18 states. Adoption of the CC-tool was measured as any instance of tool use (i.e., entry of cervical cancer screening results or follow-up plan) and as monthly tool use rates from November 1, 2018 (tool release date) to December 31, 2020. Adjusted odds and rates of tool use were evaluated using logistic and negative-binomial regression. Feedback from nine clinic staff representing six clinics during user-centered design sessions and semi-structured interviews with eight clinic staff from two additional clinics were conducted to assess barriers and facilitators to tool adoption.

RESULTS

The CC-tool was used ≥1 time in 41% of study clinics during the analysis period. Clinics that ever used the tool and those with greater monthly tool use had, on average, more encounters, more patients from households at >138% federal poverty level, fewer pediatric encounters, higher up-to-date cervical cancer screening rates, and higher rates of abnormal cervical cancer screening results. Qualitative data indicated barriers to tool adoption, including lack of knowledge of the tool's existence, understanding of its functionalities, and training on its use.

CONCLUSION

Without effective systems for informing users about new EHR functions, new or updated EHR tools are unlikely to be widely adopted, reducing their potential to improve health care quality and outcomes.

Partner-developed electronic health record tools to facilitate social risk-informed care planning

OBJECTIVE

Increased social risk data collection in health care settings presents new opportunities to apply this information to improve patient outcomes. Clinical decision support (CDS) tools can support these applications. We conducted a participatory engagement process to develop electronic health record (EHR)-based CDS tools to facilitate social risk-informed care plan adjustments in community health centers (CHCs).

MATERIALS AND METHODS

We identified potential care plan adaptations through systematic reviews of hypertension and diabetes clinical guidelines. The results were used to inform an engagement process in which CHC staff and patients provided feedback on potential adjustments identified in the guideline reviews and on tool form and functions that could help CHC teams implement these suggested adjustments for patients with social risks.

RESULTS

Partners universally prioritized tools for social risk screening and documentation. Additional high-priority content included adjusting medication costs and changing follow-up plans based on reported social risks. Most content recommendations reflected partners' interests in encouraging provider-patient dialogue about care plan adaptations specific to patients' social needs. Partners recommended CDS tool functions such as alerts and shortcuts to facilitate and efficiently document social risk-informed care plan adjustments.

DISCUSSION AND CONCLUSION

CDS tools were designed to support CHC providers and staff to more consistently tailor care based on information about patients' social context and thereby enhance patients' ability to adhere to care plans. While such adjustments occur on an ad hoc basis in many care settings, these are among the first tools designed both to systematize and document these activities.

Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers

Objective

Electronic health record (EHR)-based shared decision-making (SDM) and clinical decision support (CDS) systems can improve cardiovascular disease (CVD) care quality and risk factor management. Use of the CV Wizard system showed a beneficial effect on high-risk community health center (CHC) patients' CVD risk within an effectiveness trial, but system adoption was low overall. We assessed which multi-level characteristics were associated with system use.

Materials and Methods

Analyses included 80 195 encounters with 17 931 patients with high CVD risk and/or uncontrolled risk factors at 42 clinics in September 2018-March 2020. Data came from the CV Wizard repository and EHR data, and a survey of 44 clinic providers. Adjusted, mixed-effects multivariate Poisson regression analyses assessed factors associated with system use. We included clinic- and provider-level clustering as random effects to account for nested data.

Results

Likelihood of system use was significantly higher in encounters with patients with higher CVD risk and at longer encounters, and lower when providers were >10 minutes behind schedule, among other factors. Survey participants reported generally high satisfaction with the system but were less likely to use it when there were time constraints or when rooming staff did not print the system output for the provider.

Discussion

CHC providers prioritize using this system for patients with the greatest CVD risk, when time permits, and when rooming staff make the information readily available. CHCs' financial constraints create substantial challenges to addressing barriers to improved system use, with health equity implications.

Conclusion

Research is needed on improving SDM and CDS adoption in CHCs.

Trial Registration

ClinicalTrials.gov, NCT03001713, https://clinicaltrials.gov/.

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.

Patient-Reported Social Risks and Clinician Decision Making: Results of a Clinician Survey in Primary Care Community Health Centers

PURPOSE

To assess the extent that patients' social determinants of health (SDOH) influence safety-net primary care clinicians' decisions at the point of care; examine how that information comes to the clinician's attention; and analyze clinician, patient, and encounter characteristics associated with the use of SDOH data in clinical decision making.

METHODS

Thirty-eight clinicians working in 21 clinics were prompted to complete 2 short card surveys embedded in the electronic health record (EHR) daily for 3 weeks. Survey data were matched with clinician-, encounter-, and patient-level variables from the EHR. Descriptive statistics and generalized estimating equation models were used to assess relationships between the variables and the clinician reported use of SDOH data to inform care.

RESULTS

Social determinants of health were reported to influence care in 35% of surveyed encounters. The most common sources of information on patients' SDOH were conversations with patients (76%), prior knowledge (64%), and the EHR (46%). Social determinants of health were significantly more likely to influence care among male and non-English-speaking patients, and those with discrete SDOH screening data documented in the EHR.

CONCLUSIONS

Electronic health records present an opportunity to support clinicians integrating information about patients' social and economic circumstances into care planning. Study findings suggest that SDOH information from standardized screening documented in the EHR, combined with patient-clinician conversations, may enable social risk-adjusted care. Electronic health record tools and clinic workflows could be used to support both documentation and conversations. Study results also identified factors that may cue clinicians to include SDOH information in point-of-care decision-making. Future research should explore this topic further.

Creating research-ready partnerships: the initial development of seven implementation laboratories to advance cancer control

BACKGROUND

In 2019-2020, with National Cancer Institute funding, seven implementation laboratory (I-Lab) partnerships between scientists and stakeholders in 'real-world' settings working to implement evidence-based interventions were developed within the Implementation Science Centers in Cancer Control (ISC3) consortium. This paper describes and compares approaches to the initial development of seven I-Labs in order to gain an understanding of the development of research partnerships representing various implementation science designs.

METHODS

In April-June 2021, members of the ISC3 Implementation Laboratories workgroup interviewed research teams involved in I-Lab development in each center. This cross-sectional study used semi-structured interviews and case-study-based methods to collect and analyze data about I-Lab designs and activities. Interview notes were analyzed to identify a set of comparable domains across sites. These domains served as the framework for seven case descriptions summarizing design decisions and partnership elements across sites.

RESULTS

Domains identified from interviews as comparable across sites included engagement of community and clinical I-Lab members in research activities, data sources, engagement methods, dissemination strategies, and health equity. The I-Labs use a variety of research partnership designs to support engagement including participatory research, community-engaged research, and learning health systems of embedded research. Regarding data, I-Labs in which members use common electronic health records (EHRs) leverage these both as a data source and a digital implementation strategy. I-Labs without a shared EHR among partners also leverage other sources for research or surveillance, most commonly qualitative data, surveys, and public health data systems. All seven I-Labs use advisory boards or partnership meetings to engage with members; six use stakeholder interviews and regular communications. Most (70%) tools or methods used to engage I-Lab members such as advisory groups, coalitions, or regular communications, were pre-existing. Think tanks, which two I-Labs developed, represented novel engagement approaches. To disseminate research results, all centers developed web-based products, and most (n = 6) use publications, learning collaboratives, and community forums. Important variations emerged in approaches to health equity, ranging from partnering with members serving historically marginalized populations to the development of novel methods.

CONCLUSIONS

The development of the ISC3 implementation laboratories, which represented a variety of research partnership designs, offers the opportunity to advance understanding of how researchers developed and built partnerships to effectively engage stakeholders throughout the cancer control research lifecycle. In future years, we will be able to share lessons learned for the development and sustainment of implementation laboratories.

Precision Ecologic Medicine: Tailoring Care to Mitigate Impacts of Climate Change

As recent extreme weather events demonstrate, climate change presents unprecedented and increasing health risks, disproportionately so for disadvantaged communities in the U.S. already experiencing health disparities. As patients in these frontline communities live through extreme weather events, socioeconomic and health stressors are compounded; thus, their healthcare teams will need tools to provide precision ecologic medicine approaches to their care. Many primary care teams are taking actionable steps to bring community-level socioeconomic data ("community vital signs") into electronic medical records, to facilitate tailoring care based on a given patient's circumstances. This work can be extended to include environmental risk data, thus equipping healthcare teams with an awareness of clinical and community vital signs and making them better positioned to mitigate climate impacts on health. For example, if healthcare teams can easily identify patients who have multiple chronic conditions and live in an urban heat island, they can proactively arrange to "prescribe" an air conditioner, heat pump, and/or air purifier. Or, when a severe storm/heat event/poor air quality event is predicted, they can take preemptive steps to get help to patients at high medical and socioeconomic risk, rather than waiting for them to arrive in the emergency department. Advances in health information technologies now make it technically feasible to integrate a wealth of publicly-available community-level data into EMRs. Efforts to bring this contextual data into clinical settings must be accelerated to equip healthcare teams to provide precision ecologic medicine interventions to their patients.

Adjusting for Patient Economic/Access Issues in a Hypertension Quality Measure

INTRODUCTION

The American Heart Association and American College of Cardiology have proposed adjusting hypertension-related care quality measures by excluding patients with economic/access issues from the denominator of rate calculations. No research to date has explored the methods to operationalize this recommendation or how to measure economic/access issues. This study applied and compared different approaches to populating these denominator exceptions.

METHODS

Electronic health record data from 2019 were used in 2021 to calculate hypertension control rates in 84 community health centers. A total of 10 different indicators of patient economic/access barriers to care were used as denominator exclusions to calculate and then compare adjusted quality measure performance. Data came from a nonprofit health center‒controlled network that hosts a shared electronic health record for community health centers located in 22 states.

RESULTS

A total of 5 of 10 measures yielded an increase in adjusted hypertension control rates in ≥50% of clinics (average rate increases of 0.7-3.71 percentage points). A total of 3 of 10 measures yielded a decrease in adjusted hypertension control rates in >50% of clinics (average rate decreases of 1.33-13.82 percentage points). A total of 5 measures resulted in excluding >50% of the clinic's patient population from quality measure assessments.

CONCLUSIONS

Changes in clinic-level hypertension control rates after adjustment differed depending on the measure of economic/access issue. Regardless of the exclusion method, changes between baseline and adjusted rates were small. Removing community health center patients experiencing economic/access barriers from a hypertension control quality measure resulted in excluding a large proportion of patients, raising concerns about whether this calculation can be a meaningful measure of clinical performance.

Social Care Recommendations in National Diabetes Treatment Guidelines

PURPOSE OF REVIEW

An expanding body of research documents associations between socioeconomic circumstances and health outcomes, which has led health care institutions to invest in new activities to identify and address patients' social circumstances in the context of care delivery. Despite growing national investment in these "social care" initiatives, the extent to which social care activities are routinely incorporated into care for patients with type II diabetes mellitus (T2D), specifically, is unknown. We conducted a scoping review of existing T2D treatment and management guidelines to explore whether and how these guidelines incorporate recommendations that reflect social care practice categories.

RECENT FINDINGS

We applied search terms to locate all T2D treatment and management guidelines for adults published in the US from 1977 to 2021. The search captured 158 national guidelines. We subsequently applied the National Academies of Science, Engineering, and Medicine framework to search each guideline for recommendations related to five social care activities: Awareness, Adjustment, Assistance, Advocacy, and Alignment. The majority of guidelines (122; 77%) did not recommend any social care activities. The remainder (36; 23%) referred to one or more social care activities. In the guidelines that referred to at least one type of social care activity, adjustments to medical treatment based on social risk were most common [34/36 (94%)]. Recommended adjustments included decreasing medication costs to accommodate financial strain, changing literacy level or language of handouts, and providing virtual visits to accommodate transportation insecurity. Ensuring that practice guidelines more consistently reflect social care best practices may improve outcomes for patients living with T2D.

Cross-Sectional Associations: Social Risks and Diabetes Care Quality, Outcomes

INTRODUCTION

Social risks (e.g., food/transportation insecurity) can hamper type 2 diabetes mellitus (T2DM) self-management, leading to poor outcomes. To determine the extent to which high-quality care can overcome social risks' health impacts, this study assessed the associations between reported social risks, receipt of guideline-based T2DM care, and T2DM outcomes when care is up to date among community health center patients.

METHODS

A cross-sectional study of adults aged ≥18 years (N=73,484) seen at 186 community health centers, with T2DM and ≥1 year of observation between July 2016 and February 2020. Measures of T2DM care included up-to-date HbA1c, microalbuminuria, low-density lipoprotein screening, and foot examination, and active statin prescription when indicated. Measures of T2DM outcomes among patients with up-to-date care included blood pressure, HbA1c, and low-density lipoprotein control on or within 6‒12 months of an index encounter. Analyses were conducted in 2021.

RESULTS

Individuals reporting transportation or housing insecurity were less likely to have up-to-date low-density lipoprotein screening; no other associations were seen between social risks and clinical care quality. Among individuals with up-to-date care, food insecurity was associated with lower adjusted rates of controlled HbA1c (79% vs 75%, p<0.001), and transportation insecurity was associated with lower rates of controlled HbA1c (79% vs 74%, p=0.005), blood pressure (74% vs 72%, p=0.025), and low-density lipoprotein (61% vs 57%, p=0.009) than among those with no reported need.

CONCLUSIONS

Community health center patients received similar care regardless of the presence of social risks. However, even among those up to date on care, social risks were associated with worse T2DM control. Future research should identify strategies for improving HbA1c control for individuals with social risks.

TRIAL REGISTRATION

This study is registered at www.

CLINICALTRIALS

gov NCT03607617.

Designing and Implementing an Electronic Health Record-Embedded Card Study in Primary Care: Methods and Considerations

Card studies-short surveys about the circumstances within which patients receive care-are traditionally completed on physical cards. We report on the development of an electronic health record (EHR)-embedded card study intended to decrease logistical challenges inherent to paper-based approaches, including distributing, tracking, and transferring the physical cards, as well as data entry and respondent prompts, while simultaneously decreasing the complexity for participants and facilitating rich analyses by linking to clinical and demographic data found in the EHR. Developing the EHR-based programming and data extraction was time consuming, required specialized expertise, and necessitated iteration to rectify issues encountered during implementation. Nonetheless, future EHR-embedded card studies will be able to replicate many of the same processes as informed by these results. Once built, the EHR-embedded card study simplified survey implementation for both the research team and clinic staff, resulting in research-quality data, the ability to link survey responses to relevant EHR data, and a 79% response rate. This detailed accounting of the development and implementation process, including issues encountered and addressed, might guide others in conducting EHR-embedded card studies.

114 Effect of siponimod on cognitive processing speed in SPMS patients with active and non-active disease

Background

Siponimod significantly reduced the relative risk of 3-month (m) confirmed disability progression (CDP) by 21% and 6mCDP by 26% versus placebo in the EXPAND core study and showed significant benefits on cognitive processing speed (CPS) using the Symbol Digit Modalities Test (SDMT).

Objectives

To evaluate the effect of siponimod on CPS in active (aSPMS) and non-active (naSPMS) patients from EXPAND core study.

Methods

This subgroup analysis included aSPMS patients (siponimod, n=516; placebo, n=263) and naSPMS patients (siponimod, n=557; placebo, n=270). Change in SDMT score; time to 6m confirmed ≥4-points cognitive worsening/improvement (6mCW/6mCI) on SDMT and the proportion of patients with worsened, stable and improved SDMT scores at M24 were analysed.

Results

Change in SDMT (95% Cl) versus placebo from baseline to M24 in aSPMS and naSPMS groups was

2.34 (0.66; 4.02) and 2.44 (0.67; 4.22), respectively, consistent with overall EXPAND core population. In aSPMS patients, siponimod reduced risk of 6mCW by 27% (p=0.06) and improved chances of 6mCI by 62% (p=0.007) versus placebo. Corresponding values in the naSPMS group were: 6mCW, 24% (p=ns) and 6mCI, 19% (p=ns).

Conclusions

Siponimod was associated with relevant benefits in CPS as measured by change in SDMT in patients with active and non-active SPMS.

teresa

sawtell@novartis.com

82

115 Impact of siponimod on myelination across SPMS subgroups: post-hoc analysis from EXPAND MRI substudy

Background

Changes in magnetization transfer ratio (MTR) are a marker of changes in myelin density and brain tissue integrity. Siponimod improved lesional MTR recovery in the overall EXPAND secondary progressive multiple sclerosis (SPMS) population.

Objectives

Investigate the effect of siponimod on MTR changes in SPMS subgroups.

Methods

This prospective sub-study assessed the effect of siponimod versus placebo on median nor- malized MTR (nMTR) in normal appearing brain tissue (NABT), cortical Grey Matter (cGM) and normal appearing white matter (NAWM). Subgroups were defined by: disease history, severity and duration, EDSS score, Symbol Digit Modalities Test score, and inflammatory disease activity.

Results

There was an attenuation in median nMTR decrease versus placebo across all subgroups (all p<0.05 except EDSS≥6 subgroup, p=0.064). In the active SPMS subgroup, siponimod attenuated median nMTR decrease across NABT, cGM and NAWM by 91–109% (p<0.01 all); and in the non-active SPMS subgroup by 170– 198% (p=0.0151 for NAWM, p>0.05 for NABT, cGM).

Conclusions

Over 24 months, siponimod attenuated the decrease in median nMTR in brain tissues across patient subgroups characterized by disease activity and severity, with most pronounced effects in NAWM. This supports preclinical studies, showing beneficial CNS effects on myelination.

teresa.sawtell@novartis.com

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.

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

"I didn't know you could do that": A Pilot Assessment of EHR Optimization Training

BACKGROUND

Informatics tools within electronic health records (EHRs)-for example, data rosters and clinical reminders-can help disseminate care guidelines into clinical practice. Such tools' adoption varies widely, however, possibly because many primary care providers receive minimal training in even basic EHR functions.

OBJECTIVES

This mixed-methods evaluation of a pilot training program sought to identify factors to consider when providing EHR use optimization training in community health centers (CHCs) as a step toward supporting CHC providers' adoption of EHR tools.

METHODS

In spring 2018, we offered 10 CHCs a 2-day, 16-hour training in EHR use optimization, provided by clinician trainers, and customized to each CHC's needs. We surveyed trainees pre- and immediately post-training and again 3 months later. We conducted post-training interviews with selected clinic staff, and conducted a focus group with the trainers, to assess satisfaction with the training, and perceptions of how it impacted subsequent EHR use.

RESULTS

Six CHCs accepted and received the training; 122 clinic staff members registered to attend, and most who completed the post-training survey reported high satisfaction. Three months post-training, 80% of survey respondents said the training had changed their daily EHR use somewhat or significantly.

CONCLUSION

Factors to consider when planning EHR use optimization training in CHCs include: CHCs may face barriers to taking part in such training; it may be necessary to customize training to a given clinic's needs and to different trainees' clinic roles; identifying trainees' skill level a priori would help but is challenging; in-person training may be preferable; and inclusion of a practice coach may be helpful. Additional research is needed to identify how to provide such training most effectively.

Strengthening methods for tracking adaptations and modifications to implementation strategies

BACKGROUND

Developing effective implementation strategies requires adequate tracking and reporting on their application. Guidelines exist for defining and reporting on implementation strategy characteristics, but not for describing how strategies are adapted and modified in practice. We built on existing implementation science methods to provide novel methods for tracking strategy modifications.

METHODS

These methods were developed within a stepped-wedge trial of an implementation strategy package designed to help community clinics adopt social determinants of health-related activities: in brief, an 'Implementation Support Team' supports clinics through a multi-step process. These methods involve five components: 1) describe planned strategy; 2) track its use; 3) monitor barriers; 4) describe modifications; and 5) identify / describe new strategies. We used the Expert Recommendations for Implementing Change taxonomy to categorize strategies, Proctor et al.'s reporting framework to describe them, the Consolidated Framework for Implementation Research to code barriers / contextual factors necessitating modifications, and elements of the Framework for Reporting Adaptations and Modifications-Enhanced to describe strategy modifications.

RESULTS

We present three examples of the use of these methods: 1) modifications made to a facilitation-focused strategy (clinics reported that certain meetings were too frequent, so their frequency was reduced in subsequent wedges); 2) a clinic-level strategy addition which involved connecting one study clinic seeking help with community health worker-related workflows to another that already had such a workflow in place; 3) a study-level strategy addition which involved providing assistance in overcoming previously encountered (rather than de novo) challenges.

CONCLUSIONS

These methods for tracking modifications made to implementation strategies build on existing methods, frameworks, and guidelines; however, as none of these were a perfect fit, we made additions to several frameworks as indicated, and used certain frameworks' components selectively. While these methods are time-intensive, and more work is needed to streamline them, they are among the first such methods presented to implementation science. As such, they may be used in research on assessing effective strategy modifications and for replication and scale-up of effective strategies. We present these methods to guide others seeking to document implementation strategies and modifications to their studies.

TRIAL REGISTRATION

clinicaltrials.gov ID: NCT03607617 (first posted 31/07/2018).

Strengthening methods for tracking adaptations and modifications to implementation strategies

BACKGROUND

Developing effective implementation strategies requires adequate tracking and reporting on their application. Guidelines exist for defining and reporting on implementation strategy characteristics, but not for describing how strategies are adapted and modified in practice. We built on existing implementation science methods to provide novel methods for tracking strategy modifications.

METHODS

These methods were developed within a stepped-wedge trial of an implementation strategy package designed to help community clinics adopt social determinants of health-related activities: in brief, an 'Implementation Support Team' supports clinics through a multi-step process. These methods involve five components: 1) describe planned strategy; 2) track its use; 3) monitor barriers; 4) describe modifications; and 5) identify / describe new strategies. We used the Expert Recommendations for Implementing Change taxonomy to categorize strategies, Proctor et al.'s reporting framework to describe them, the Consolidated Framework for Implementation Research to code barriers / contextual factors necessitating modifications, and elements of the Framework for Reporting Adaptations and Modifications-Enhanced to describe strategy modifications.

RESULTS

We present three examples of the use of these methods: 1) modifications made to a facilitation-focused strategy (clinics reported that certain meetings were too frequent, so their frequency was reduced in subsequent wedges); 2) a clinic-level strategy addition which involved connecting one study clinic seeking help with community health worker-related workflows to another that already had such a workflow in place; 3) a study-level strategy addition which involved providing assistance in overcoming previously encountered (rather than de novo) challenges.

CONCLUSIONS

These methods for tracking modifications made to implementation strategies build on existing methods, frameworks, and guidelines; however, as none of these were a perfect fit, we made additions to several frameworks as indicated, and used certain frameworks' components selectively. While these methods are time-intensive, and more work is needed to streamline them, they are among the first such methods presented to implementation science. As such, they may be used in research on assessing effective strategy modifications and for replication and scale-up of effective strategies. We present these methods to guide others seeking to document implementation strategies and modifications to their studies.

TRIAL REGISTRATION

clinicaltrials.gov ID: NCT03607617 (first posted 31/07/2018).

POS0584 ULTRASONOGRAPHY OF THE MEDIAN NERVE IN PATIENTS WITH RHEUMATOID ARTHRITIS UNDER SUSPICION OF CARPAL TUNNEL SYNDROME

Background:

Carpal tunnel syndrome (CTS) is the most common nerve compression syndrome and a common extra-articular manifestation of rheumatoid arthritis (RA). Different causes of CTS are known, among them inflammatory and non-inflammatory pathologies. Electroneurography (ENG) of the median nerve, the method of choice to diagnose CTS, measures impairment of nerve conduction velocity without explaining its underlying cause. However, because the electrical stimulation is often not well tolerated, ENG results may come out inconclusive. Using greyscale ultrasonography (GS-US) provides anatomic information including a structural representation of the carpal tunnel.

Objectives:

To investigate the performance of nerve GS-US in the diagnosis of CTS in patients with RA.

Methods:

Consecutive patients with active RA under suspicion of CTS presenting to a large rheumatologic center were included. Both hands were examined by an experienced neurologist including ENG and a GS-US (ML linear probe with 6-15 Hz) of the median nerve. An established grading system for ENG (1), and an established system for GS-US based on cut-offs for the nerve cross sectional area (CSA) [mild: 0,11-0,13cm2, moderate: 0,14-0,15 cm2, severe: > 0,15 cm2 CTS (2)] were used. In addition, the Boston Carpal Tunnel Syndrome Questionnaire (BCTSQ) was used to assess CTS symptoms (3).

Results:

Both hands of 58 patients with active RA (n=116) and clinical suspicion of CTS (in 38 cases bilaterally) were included. After clinical examination, CTS was suspicious in 96 hands (82.8%), and 59 of all hands had a final diagnosis of CTS (50.9%). Of the latter, 43 hands (72.9%) had a positive ENG and 16 (27.1%) a positive GS-US finding only, while 30 hands (50.8%) were positive in both examinations.

There was a good correlation of the cross-sectional area (CSA) as well as the CSA-ratio to the ENG findings: the larger the CSA, the more severe was the CTS as assessed by ENG (Spearman’s rho=0.554; p<0.001). The more severe the GS-US findings of CTS were, the more definite were the distal motor latency (Spearman’s rho=0.554; p<0.001) and sensible nerve conduction velocity of the median nerve (Spearman’s rho=-0.5411; p<0.001).

In the 46 hands positive in GS-US, tenosynovial hypertrophy of the flexor tendons was detected in 19 hands (41.3%), 7 of which (36.8%) also showed an additional cystic mass. In these 19 patients, clinical complains were more severely present than in patients with non-inflammatory CTS, as assessed by the BCTSQ with a total score of 68.8±13.4 vs. 59.3±13.7, respectively (p=0.007).

Conclusion:

In patients with active RA and clinical complains of CTS, ultrasound examinations provide additional information about inflammation which is helpful for a diagnosis of CTS. Thus, ENG and nerve GS-US should be used complementary for a diagnostic workup of CTS in RA patients with a suspicion of CTS. Power-Doppler may further improve the diagnostic performance of GS-US.

References:

[1]Padua L et al. Acta Neurol Scand 1997; 96:211–217

[2]El Miedany et al., Rheumatology (Oxford). 2004 Jul; 43(7):887-895

[3]Levine DW et al. J Bone Joint Surg Am 1993; 75: 1585-1592

Figure 1.

BCTSQ scores in patients with diagnosis of CTS and absence or presence of RA-related tenosynovial hypertrophy

Disclosure of Interests:

None declared

Health insurance coverage and self-employment

BACKGROUND

Self-employed workers are 10% of the US labor force, with growth projected over the next decade. Whether existing policy mechanisms are sufficient to ensure health insurance coverage for self-employed workers, who do not have access to employer-sponsored coverage, is unclear.

OBJECTIVE

To determine whether self-employment is associated with lack of health insurance coverage.

DATA SOURCES

Secondary analysis of Medical Expenditure Panel Survey (MEPS) data collected 2014-2017.

STUDY DESIGN

Participants were working age (18-64 years), employed, civilian noninstitutionalized US adults with two years of Medical Expenditure Panel Survey (MEPS) participation in 2014-2017. We compared those who were employees vs those who were self-employed. Key outcomes were self-report of health insurance coverage, and of delaying needed medical care.

DATA EXTRACTION METHODS

Longitudinal design among individuals who were employees during study year 1, comparing health insurance coverage among those who did vs did not transition to self-employment in year 2.

PRINCIPAL FINDINGS

16 335 individuals, representing 121 473 345 working-age adults, met inclusion criteria; of these, 147, representing 1 097 582 individuals, transitioned to self-employment. In unadjusted analyses, 25.7% of those who became self-employed were uninsured in year 2, vs 8.1% of those who remained employees (P < .0001). In adjusted models, self-employment was associated with greater risk of being uninsured (26.1% vs 8.0%, risk difference 18.0%, 95% confidence interval [CI] 9.2% to 26.9%, P = .0001). A time-by-employment type product term suggests that 10.0 percentage points (95%CI 0.3 to 19.7 percentage points, P = .04) of the risk difference may be attributable to the change to self-employment. Self-employment was also associated with delaying needed medical care (12.0% vs 3.1%, risk difference: 8.9%, 95% CI 3.1% to 14.6%, P = .003).

CONCLUSIONS

One in four self-employed workers lack health insurance coverage. Given the rise in self-employment, it is imperative to identify ways to improve health care insurance access for self-employed working-age US adults.

The impact of a nationwide hands-on workshop on the diagnostic rates and management of obstetrical anal sphincter Injuries in Israel

AIM

The aim was to evaluate the influence of a half day, hands-on, workshop on the detection and repair of obstetric anal sphincter injuries (OASIs).

METHOD

Starting in February 2011, hands-on workshops for the diagnosis and repair of OASIs were delivered by trained urogynaecologists in departments of tertiary medical centres in Israel. The structure of the hands-on workshop resembles the workshop organized at the International Urogynecological Association annual conferences. Participants included medical staff, midwives and surgical residents from each medical centre. We collected data regarding the rate of OASIs, 1 year before and 1 year following the workshop, in 11 medical centres. The study population was composed of parturients with the following inclusion criteria: singleton pregnancy, vertex presentation and vaginal delivery. Pre-viable preterm gestations (< 24 weeks), birth weight < 500 g, stillborn, and those with major congenital anomalies, multifoetal pregnancies, breech presentations and caesarean deliveries were excluded from the analysis.

RESULTS

In the reviewed centres, 70 663 (49.3%) women delivered prior to the workshop (pre-workshop group) and 72 616 (50.7%) women delivered following the workshop (post-workshop group). Third- or fourth-degree perineal tears occurred in 248 women (0.35%) before the workshop, and in 328 (0.45%) following the workshop, a significant increase of 28.7% (P = 0.002). The increase in diagnosis was significant also in women with third-degree tears alone, 226 women (0.32%) before the workshop and 298 (0.41%) following the workshop, an increase of 28.3% (P = 0.005).

CONCLUSION

The detection rate of OASIs has significantly increased following the hands-on workshop. The implementation of such programmes is crucial for increasing awareness and detection rates of OASI following vaginal deliveries.

SARS-CoV-2 Testing and Changes in Primary Care Services in a Multistate Network of Community Health Centers During the COVID-19 Pandemic

This study uses electronic health record data to describe primary care services offered by US community health centers in March through May 2020, including SARS-CoV-2 testing, well-child visits, HbA_1c testing, and cancer screening.

Comparison of Community-Level and Patient-Level Social Risk Data in a Network of Community Health Centers

IMPORTANCE

Responding to the substantial research on the relationship between social risk factors and health, enthusiasm has grown around social risk screening in health care settings, and numerous US health systems are experimenting with social risk screening initiatives. In the absence of standard social risk screening recommendations, some health systems are exploring using publicly available community-level data to identify patients who live in the most vulnerable communities as a way to characterize patient social and economic contexts, identify patients with potential social risks, and/or to target social risk screening efforts.

OBJECTIVE

To explore the utility of community-level data for accurately identifying patients with social risks by comparing the social deprivation index score for the census tract where a patient lives with patient-level social risk screening data.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional study using patient-level social risk screening data from the electronic health records of a national network of community health centers between June 24, 2016, and November 15, 2018, linked to geocoded community-level data from publicly available sources. Eligible patients were those with a recorded response to social risk screening questions about food, housing, and/or financial resource strain, and a valid address of sufficient quality for geocoding.

EXPOSURES

Social risk screening documented in the electronic health record.

MAIN OUTCOMES AND MEASURES

Community-level social risk was assessed using census tract-level social deprivation index score stratified by quartile. Patient-level social risks were identified using food insecurity, housing insecurity, and financial resource strain screening responses.

RESULTS

The final study sample included 36 578 patients from 13 US states; 22 113 (60.5%) received public insurance, 21 181 (57.9%) were female, 17 578 (48.1%) were White, and 10 918 (29.8%) were Black. Although 6516 (60.0%) of those with at least 1 social risk factor were in the most deprived quartile of census tracts, patients with social risk factors lived in all census tracts. Overall, the accuracy of the community-level data for identifying patients with and without social risks was 48.0%.

CONCLUSIONS AND RELEVANCE

Although there is overlap, patient-level and community-level approaches for assessing patient social risks are not equivalent. Using community-level data to guide patient-level activities may mean that some patients who could benefit from targeted interventions or care adjustments would not be identified.

Lessons learned about the effective operationalization of champions as an implementation strategy: results from a qualitative process evaluation of a pragmatic trial

BACKGROUND

Though the knowledge base on implementation strategies is growing, much remains unknown about how to most effectively operationalize these strategies in diverse contexts. For example, while evidence shows that champions can effectively support implementation efforts in some circumstances, little has been reported on how to operationalize this role optimally in different settings, or on the specific pathways through which champions enact change.

METHODS

This is a secondary analysis of data from a pragmatic trial comparing implementation strategies supporting the adoption of guideline-concordant cardioprotective prescribing in community health centers in the USA. Quantitative data came from the community health centers' shared electronic health record; qualitative data sources included community health center staff interviews over 3 years. Using a convergent mixed-methods design, data were collected concurrently and merged for interpretation to identify factors associated with improved outcomes. Qualitative analysis was guided by the constant comparative method. As results from the quantitative and initial qualitative analyses indicated the essential role that champions played in promoting guideline-concordant prescribing, we conducted multiple immersion-crystallization cycles to better understand this finding.

RESULTS

Five community health centers demonstrated statistically significant increases in guideline-concordant cardioprotective prescribing. A combination of factors appeared key to their successful practice change: (1) A clinician champion who demonstrated a sustained commitment to implementation activities and exhibited engagement, influence, credibility, and capacity; and (2) organizational support for the intervention. In contrast, the seven community health centers that did not show improved outcomes lacked a champion with the necessary characteristics, and/or organizational support. Case studies illustrate the diverse, context-specific pathways that enabled or prevented study implementers from advancing practice change.

CONCLUSION

This analysis confirms the important role of champions in implementation efforts and offers insight into the context-specific mechanisms through which champions enact practice change. The results also highlight the potential impact of misaligned implementation support and key modifiable barriers and facilitators on implementation outcomes. Here, unexamined assumptions and a lack of evidence-based guidance on how best to identify and prepare effective champions led to implementation support that failed to address important barriers to intervention success.

TRIAL REGISTRATION

ClinicalTrials.gov , NCT02325531 . Registered 15 December 2014.

Pathological spontaneous activity as a prognostic marker in chronic inflammatory demyelinating polyneuropathy

BACKGROUND AND PURPOSE

Monitoring of the disease course of patients with chronic inflammatory demyelinating polyneuropathy (CIDP) remains challenging because nerve conduction studies do not adequately correlate with functional disability. The prognostic value of pathological spontaneous activity (PSA) in needle electromyography (EMG) in different CIDP subgroups in a longitudinal context has, to date, not been analysed. We aimed to determine whether PSA was a prognostic marker or a marker of disease activity in a cohort of patients with CIDP.

METHODS

A total of 127 patients with CIDP spectrum disorder were retrospectively analysed over 57 ± 47 months regarding the occurrence of PSA (fibrillations and positive sharp waves). The presence of PSA at diagnosis, newly occurring PSA, and continuously present PSA were longitudinally correlated with clinical disability using the Inflammatory Neuropathy Cause and Treatment Overall Disability Sum Score (INCAT-ODSS) and CIDP subtype.

RESULTS

Pathological spontaneous activity occurred in 49.6% of all CIDP patients at first diagnosis. More frequent evidence of PSA was significantly associated with a higher INCAT-ODSS at the last follow-up. Continuous and new occurrence of PSA were associated with higher degree of disability at the last follow-up. The majority of patients with sustained evidence of PSA were characterized by an atypical phenotype, higher degree of disability, and the need for escalation of treatment.

CONCLUSIONS

Pathological spontaneous activity was associated with a higher degree of disability and occurred more frequently in atypical CIDP variants according to the longitudinal data of a large cohort of patients with CIDP. Our results showed that EMG examination was an adequate marker for disease progression and should be evaluated during the disease course.

Longitudinal Remote Coaching for Implementation of Perinatal Collaborative Care: A Mixed-Methods Analysis

The collaborative care model (CoCM) is a multicomponent, team-based integrated behavioral health framework. Its effectiveness in the treatment of perinatal depression is established, but implementation has been limited. The authors used longitudinal remote coaching (LRC) as a novel implementation strategy to support systematic case review in a multistate cluster-randomized trial of CoCM for perinatal depression. They describe LRC for perinatal CoCM in three clinics and use of a mixed-methods analysis of data from LRC feedback forms and interviews with participants. LRC is a scalable implementation strategy with potential to support complex models of integrated behavioral health, such as perinatal CoCM.

Unmet information needs of clinical teams delivering care to complex patients and design strategies to address those needs

OBJECTIVES

To identify the unmet information needs of clinical teams delivering care to patients with complex medical, social, and economic needs; and to propose principles for redesigning electronic health records (EHR) to address these needs.

MATERIALS AND METHODS

In this observational study, we interviewed and observed care teams in 9 community health centers in Oregon and Washington to understand their use of the EHR when caring for patients with complex medical and socioeconomic needs. Data were analyzed using a comparative approach to identify EHR users' information needs, which were then used to produce EHR design principles.

RESULTS

Analyses of > 300 hours of observations and 51 interviews identified 4 major categories of information needs related to: consistency of social determinants of health (SDH) documentation; SDH information prioritization and changes to this prioritization; initiation and follow-up of community resource referrals; and timely communication of SDH information. Within these categories were 10 unmet information needs to be addressed by EHR designers. We propose the following EHR design principles to address these needs: enhance the flexibility of EHR documentation workflows; expand the ability to exchange information within teams and between systems; balance innovation and standardization of health information technology systems; organize and simplify information displays; and prioritize and reduce information.

CONCLUSION

Developing EHR tools that are simple, accessible, easy to use, and able to be updated by a range of professionals is critical. The identified information needs and design principles should inform developers and implementers working in community health centers and other settings where complex patients receive care.

Initiating and Implementing Social Determinants of Health Data Collection in Community Health Centers

Successfully incorporating social determinants of health (SDH) screening into clinic workflows can help care teams provide targeted care, appropriate referrals, and other interventions to address patients' social risk factors. However, integrating SDH screening into clinical routines is known to be challenging. To achieve widespread adoption of SDH screening, we need to better understand the factors that can facilitate or hinder implementation of effective, sustainable SDH processes. The authors interviewed 43 health care staff and professionals at 8 safety net community health center (CHC) organizations in 5 states across the United States; these CHCs had adopted electronic health record (EHR)-based SDH screening without any external implementation support. Interviewees included staff in administrative, quality improvement, informatics, front desk, and clinical roles (providers, nurses, behavioral health staff), and community health workers. Interviews focused on how each organization integrated EHR-based SDH screening into clinic workflows, and factors that affected adoption of this practice change. Factors that facilitated effective integration of EHR-based SDH screening were: (1) external incentives and motivators that prompted introduction of this screening (eg, grant requirements, encouragement from professional associations); (2) presence of an SDH screening advocate; and (3) maintaining flexibility with regard to workflow approaches to optimally align them with clinic needs, interests, and resources. Results suggest that it is possible to purposefully create an environment conducive to successfully implementing EHR-based SDH screening. Approaching the task of implementing SDH screening into clinic workflows as understanding the interplay of context-dependent factors, rather than following a step-by-step process, may be critical to success in primary care settings.

Atrophy of optic nerve detected by transorbital sonography in patients with demyelinating diseases of the central nervous system

BACKGROUND AND PURPOSE

Transorbital sonography (TOS) has emerged as promising imaging method for the diagnosis and follow-up of acute optic neuritis (ON). Available studies report an increase in the optic nerve diameter (OND) and the optic nerve sheath diameter (ONSD) in the case of a first episode of ON in the affected eye compared to either the contralateral unaffected eye or controls. However, the utility of TOS in the case of recurrent episodes of ON has never been assessed.

METHODS

In our prospective cohort study, the diagnostic utility of TOS in patients with demyelinating diseases of the central nervous system was assessed, and the association between TOS, optical coherence tomography (OCT) and visual evoked potentials was examined further.

RESULTS

Seventy-eight patients with a history of demyelinating disorders of the central nervous system (mean age 38.2 ± 14.2 years; 24% with acute ON) were included. No differences in the OND (3.2 ± 0.5 mm vs. 3.2 ± 0.4 mm) and ONSD (5.1 ± 0.8 mm vs. 5.1 ± 0.7 mm) measurements were found between patients with and without acute ON. Papillary swelling was more frequent in patients with acute ON (14.2% vs. 1.5%, P = 0.002). Patients with a history of previous ON were found to have lower OND (P < 0.001) and ONSD (P = 0.007) compared to patients without a history of previous ON. TOS measurements were inversely associated with disease duration and positively correlated with OCT findings. No association with visual evoked potential measurements was found.

CONCLUSION

No evidence was found for TOS-sensitive differences in the OND and ONSD of patients with demyelinating diseases, according to the presence of acute ON. The association between TOS and OCT measurements deserves further investigation.

Does increased implementation support improve community clinics' guideline-concordant care? Results of a mixed methods, pragmatic comparative effectiveness trial

Background

Disseminating care guidelines into clinical practice remains challenging, partly due to inadequate evidence on how best to help clinics incorporate new guidelines into routine care. This is particularly true in safety net community health centers (CHCs).

Methods

This pragmatic comparative effectiveness trial used a parallel mixed methods design. Twenty-nine CHC clinics were randomized to receive increasingly intensive implementation support (implementation toolkit (arm 1); toolkit + in-person training + training webinars (arm 2); toolkit + training + webinars + offered practice facilitation (arm 3)) targeting uptake of electronic health record (EHR) tools focused on guideline-concordant cardioprotective prescribing for patients with diabetes. Outcomes were compared across study arms, to test whether increased support yielded additive improvements, and with 137 non-study CHCs that share the same EHR as the study clinics. Quantitative data from the CHCs’ EHR were used to compare the magnitude of change in guideline-concordant ACE/ARB and statin prescribing, using adjusted Poisson regressions. Qualitative data collected using diverse methods (e.g., interviews, observations) identified factors influencing the quantitative outcomes.

Results

Outcomes at CHCs receiving higher-intensity support did not improve in an additive pattern. ACE/ARB prescribing did not improve in any CHC group. Statin prescribing improved overall and was significantly greater only in the arm 1 and arm 2 CHCs compared with the non-study CHCs. Factors influencing the finding of no additive impact included: aspects of the EHR tools that reduced their utility, barriers to providing the intended implementation support, and study design elements, e.g., inability to adapt the provided support. Factors influencing overall improvements in statin outcomes likely included a secular trend in awareness of statin prescribing guidelines, selection bias where motivated clinics volunteered for the study, and study participation focusing clinic staff on the targeted outcomes.

Conclusions

Efforts to implement care guidelines should: ensure adaptability when providing implementation support and conduct formative evaluations to determine the optimal form of such support for a given clinic; consider how study data collection influences adoption; and consider barriers to clinics’ ability to use/accept implementation support as planned. More research is needed on supporting change implementation in under-resourced settings like CHCs.

Trial registration

ClinicalTrials.gov, NCT02325531. Registered 15 December 2014.

Variation in Electronic Health Record Documentation of Social Determinants of Health Across a National Network of Community Health Centers

INTRODUCTION

This paper describes the adoption of an electronic health record-based social determinants of health screening tool in a national network of more than 100 community health centers.

METHODS

In 2016, a screening tool with questions on 7 social determinants of health domains was developed and deployed in the electronic health record, with technical instructions on how to use the tool and suggested clinical workflows. To understand adoption patterns, the study team extracted electronic health record data for any patient with a community health center visit between June 2016 and May 2018. Patients were considered "screened" if a response to at least 1 social determinants of health domain was documented in the electronic health record tool.

RESULTS

A total of 31,549 patients (2% of those with a visit in the study period) had a documented social determinants of health screening. The number of screenings increased over time, time; 71 community health centers (67%) conducted at least one screening, but almost 50% took place in only 4 community health centers. Over half (55%) of screenings only included responses for only 1 domain. Screening was most likely to occur during an office visit with an established patient and documented in the electronic health record by a medical assistant.

CONCLUSIONS

Screening documentation patterns varied widely across the network of community health centers. Despite the growing national emphasis on the importance of screening for social determinants of health, these findings suggest that simply activating electronic health record tools for social determinants of health screening does not lead to widespread adoption. Potential barriers to screening adoption and implementation should be explored further.

SUPPLEMENT INFORMATION

This article is part of a supplement entitled Identifying and Intervening on Social Needs in Clinical Settings: Evidence and Evidence Gaps, which is sponsored by the Agency for Healthcare Research and Quality of the U.S. Department of Health and Human Services, Kaiser Permanente, and the Robert Wood Johnson Foundation.

Early Multidisciplinary Intensive-care Therapy can Improve Outcome of Severe Anti-NMDA-receptor Encephalitis Presenting with Extreme Delta Brush

Anti-N-methyl-D-aspartate receptor encephalitis (Anti-NMDARE) is a synaptic autoimmune encephalitis syndrome mainly affecting young females. An underlying tumor, most commonly ovarian teratomas in young females, may indicate a paraneoplastic syndrome. Prognostic factors of the clinical course of disease and outcome play a central role in view of early administration of second-line immunotherapy and intensive-care therapy. We report a case of severe Anti-NMDARE associated with unfavorable predictors including an extreme delta brush (EDB) electroencephalographic-pattern and high anti-NMDAR-antibody titers in the cerebral spinal fluid (CSF), which necessitated the admission to an intensive care unit. In spite of the poor prognosis, the patient completely recovered; we attribute this to an early escalation to second-line immunotherapy with rituximab and multidisciplinary intensive-care therapy. The present case underlines the relevance of multidisciplinary management for individuals with Anti-NMDARE.