Physician clinical decision support system prompts and administration of subsequent doses of HPV vaccine: A randomized clinical trial

EMR-Based Interventions on HPV Vaccination Initiation, Completion, and Receiving the Next Dose: A Meta-Analytic Review

Despite the acknowledged importance of Human Papillomavirus (HPV) vaccination in reducing HPV-related diseases, the influence of electronic medical records (EMR) on HPV vaccination uptake (HVU) remains underexplored. This study aimed to evaluate the efficacy of EMR-based interventions on HVU. A systematic review and meta-analysis of randomized controlled trials were performed, focusing on studies that primarily used EMR-based interventions to measure initiation rates, completion rates, and receipt of the next required vaccine dose. Subgroup analyses were conducted to assess the differential effects of supplementary strategies, provider feedback, and parental education or reminders on these outcomes. The results of the comprehensive analysis provided robust evidence for the significant role of EMR interventions, demonstrating an average increase of 4.7% in vaccine initiation, 6.6% in vaccine completion, and 7.2% in receipt of the next HPV vaccine dose. Additionally, the subgroup analyses indicated that provider feedback and parental education could further enhance the effectiveness of EMR-based interventions. These findings support the broader adoption of digital health technologies in vaccination programs, offering vital insights for healthcare providers, policymakers, and researchers, and emphasizing the need for continued technological innovation to improve public health outcomes.

Clinician Prompts for Human Papillomavirus Vaccination: A Cluster Randomized Trial

OBJECTIVE

We assessed the impact of an online intervention using clinician prompts for human papillomavirus (HPV) vaccination with a cluster randomized controlled trial.

METHODS

The randomized trial occurred July 2021-January 2022 in 48 primary care pediatric practices (24 intervention, 24 control) across the US. We trained clinicians via two online learning modules, plus weekly ''quick tips'' delivered via text or email. The training taught practices to implement a staff prompt to the clinician (e.g., printed reminders placed on the keyboard) plus electronic health record (EHR) prompts (if not already done) at well and acute/chronic visits for initial and subsequent HPV vaccination. We assessed missed opportunities for HPV vaccination using logistic regression models accounting for clustering by practice on an intent to treat basis. Surveys assessed facilitators and barriers to using prompts.

RESULTS

During the 6-month intervention, missed opportunities for HPV vaccination increased (worsened) in both intervention and control groups. However, at well child care visits, missed opportunities for the initial HPV vaccine increased by 4.5 (95% CI: -9.0%, -0.1%) percentage points less in intervention versus control practices. Change in missed opportunities for subsequent doses at well child care and non-well child care visits did not differ between trial groups. An end-of trial survey found understaffing as a common challenge.

CONCLUSIONS

Clinician prompts reduced missed opportunities for HPV vaccination at well child care visits. Understaffing related to the COVID-19 pandemic may have led to worsening missed opportunities for both groups and likely impeded practices in fully implementing changes.

Using Technology to Overcome Vaccine Hesitancy

Technology holds great potential to address many vaccine hesitancy determinants and support vaccine uptake given its ability to amplify positive messages, support knowledge, and enhance providers' recommendations. Modalities previously implemented with variable success have included automated reminder systems, decision support for clinicians, online education programs, social media campaigns, and virtual reality curricula. Further research is needed to identify the optimal uses of technology at the patient/parent and provider levels to overcome vaccine hesitancy. The most effective interventions will likely be multipronged providing patients, parents, and providers with information related to vaccine status.

Human Papillomavirus vaccination clinical decision support for young adults in an upper midwestern healthcare system: a clinic cluster-randomized control trial

INTRODUCTION

Human papillomavirus (HPV) vaccination rates are low in young adults. Clinical decision support (CDS) in primary care may increase HPV vaccination. We tested the treatment effect of algorithm-driven, web-based, and electronic health record-linked CDS with or without shared decision-making tools (SDMT) on HPV vaccination rates compared to usual care (UC).

METHODS

In a clinic cluster-randomized control trial conducted in a healthcare system serving a largely rural population, we randomized 34 primary care clinic clusters (with three clinics sharing clinicians randomized together) to: CDS; CDS+SDMT; UC. The sample included young adults aged 18-26 due for HPV vaccination with a study index visit from 08/01/2018-03/15/2019 in a study clinic. Generalized linear mixed models tested differences in HPV vaccination status 12 months after index visits by study arm.

RESULTS

Among 10,253 patients, 6,876 (65.2%) were due for HPV vaccination, and 5,054 met study eligibility criteria. In adjusted analyses, the HPV vaccination series was completed by 12 months in 2.3% (95% CI: 1.6%-3.2%) of CDS, 1.6% (95% CI: 1.1%-2.3%) of CDS+SDMT, and 2.2% (95% CI: 1.6%-3.0%) of UC patients, and at least one HPV vaccine was received by 12 months in 13.1% (95% CI: 10.6%-16.1%) of CDS, 9.2% (95% CI: 7.3%-11.6%) of CDS+SDMT, and 11.2% (95% CI: 9.1%-13.7%) of UC patients. Differences were not significant between arms. Females, those with prior HPV vaccinations, and those seen at urban clinics had significantly higher odds of HPV vaccination in adjusted models.

DISCUSSION

CDS may require optimization for young adults to significantly impact HPV vaccination.

TRIAL REGISTRATION

clinicaltrials.gov NCT02986230, 12/6/2016.

Interventions to Improve Immunization Coverage Among Children and Adolescents: A Meta-analysis

BACKGROUND AND OBJECTIVES

Vaccinations are recognized as a feasible, cost-effective public health intervention for reducing the burden and associated mortality of many infectious diseases. The purpose of this study was to evaluate the effectiveness of potential interventions to improve the uptake of vaccines among children and adolescents.

METHODS

We performed a literature search until December 2020. Eligible studies were identified using Cochrane Central Register of Controlled Trials, MEDLINE, PubMed, and other sources. We included studies conducted on children and adolescents aged 5 to 19 years. Studies comprised of hospitalized children and those with comorbid conditions were excluded. Two authors independently performed the meta-analysis.

RESULTS

Findings from 120 studies (123 articles), of which 95 were meta-analyzed, reveal that vaccination education may increase overall vaccination coverage by 19% (risk ratio [RR], 1.19; 95% confidence interval [CI], 1.12-1.26), reminders by 15% (RR, 1.15; 95% CI, 1.11-1.18), interventions for providers by 13% (RR, 1.13; 95% CI, 1.07-1.19), financial incentives by 67% (RR, 1.67; 95% CI, 1.40-1.99), and multilevel interventions by 25% (RR, 1.25; 95% CI, 1.10-1.41). The impact of school-based clinics and policy and legislation on overall vaccination coverage is still uncertain, and no impact of a multicomponent intervention on overall vaccination coverage was found.

CONCLUSIONS

Educational interventions, reminders, provider-directed interventions, financial incentives, and multilevel interventions may improve vaccination coverage among school-aged children and adolescents.

Clinical Decision Support Systems

BACKGROUND

By combining up-to-date medical knowledge and steadily increasing patient data, a new level of medical care can emerge.

SUMMARY AND KEY MESSAGES

Clinical decision support systems (CDSSs) are an arising solution to handling rich data and providing them to health care providers in order to improve diagnosis and treatment. However, despite promising examples in many areas, substantial evidence for a thorough benefit of these support solutions is lacking. This may be due to a lack of general frameworks and diverse health systems around the globe. We therefore summarize the current status of CDSSs in medicine but also discuss potential limitations that need to be overcome in order to further foster future development and acceptance.

A Systematic Review of Interventions to Improve HPV Vaccination Coverage

Human papillomavirus (HPV) infection is the most common sexually transmitted infection worldwide. Although most HPV infections are transient and asymptomatic, persistent infection with high-risk HPV types may results in diseases. Although there are currently three effective and safe prophylactic HPV vaccines that are used across the world, HPV vaccination coverage remains low. This review evaluates the effects of the interventions to improve HPV vaccination coverage. We searched the Cochrane Central Register of Controlled Trials, PubMed, Web of Science, Scopus, and the World Health Organization International Clinical Trials Registry Platform and checked the reference lists of relevant articles for eligible studies. Thirty-five studies met inclusion criteria. Our review found that various evaluated interventions have improved HPV vaccination coverage, including narrative education, outreach plus reminders, reminders, financial incentives plus reminders, brief motivational behavioral interventions, provider prompts, training, training plus assessment and feedback, consultation, funding, and multicomponent interventions. However, the evaluation of these intervention was conducted in high-income countries, mainly the United States of America. There is, therefore, a need for studies to evaluate the effect of these interventions in low-and middle-income countries, where there is a high burden of HPV and limited HPV vaccination programs.

Prioritizing and implementing HPV vaccination quality improvement programs in healthcare systems: the perspective of quality improvement leaders

Human papillomavirus (HPV) vaccination could prevent most of the ~34,000 HPV-attributable cancers diagnosed annually in the US, but uptake remains suboptimal. Healthcare systems are key partners in implementing HPV vaccination quality improvement (QI) programs. To inform future system-level HPV vaccine initiatives, we sought to understand HPV vaccine QI from the perspective of QI program leaders in healthcare systems. We conducted telephone interviews with a multi-state sample of 17 QI leaders in 15 systems. We analyzed data qualitatively via thematic analysis to describe QI leaders' perspectives on prioritizing and implementing HPV vaccine QI. All QI leaders endorsed HPV vaccination as beneficial, and some had already prioritized increasing uptake to improve adolescent health and meet payor reimbursement standards. Those not prioritizing HPV vaccination cited concerns including the relatively small size of adolescent patient populations, lack of buy-in among providers, and the need to focus on health services perceived as more profitable or urgent. When implementing HPV vaccine QI programs, QI leaders reported key barriers to be the lack of robust data systems and acceptable QI metrics, limited time, and pressures of a fee-for-service clinical environment. Facilitators included automation and standardization in QI efforts and passionate vaccine champions. Almost all QI leaders reported future plans to implement HPV vaccine QI projects. Findings suggest that many healthcare systems are motivated to improve HPV vaccination. However, resistance to guideline-consistent quality metrics, the narrow target of one vaccine in the adolescent patient population, payment structures, and constrained time of providers are key barriers to practice improvements.

Contemporary use of real-world data for clinical trial conduct in the United States: a scoping review

OBJECTIVE

Real-world data (RWD), defined as routinely collected healthcare data, can be a potential catalyst for addressing challenges faced in clinical trials. We performed a scoping review of database-specific RWD applications within clinical trial contexts, synthesizing prominent uses and themes.

MATERIALS AND METHODS

Querying 3 biomedical literature databases, research articles using electronic health records, administrative claims databases, or clinical registries either within a clinical trial or in tandem with methodology related to clinical trials were included. Articles were required to use at least 1 US RWD source. All abstract screening, full-text screening, and data extraction was performed by 1 reviewer. Two reviewers independently verified all decisions.

RESULTS

Of 2020 screened articles, 89 qualified: 59 articles used electronic health records, 29 used administrative claims, and 26 used registries. Our synthesis was driven by the general life cycle of a clinical trial, culminating into 3 major themes: trial process tasks (51 articles); dissemination strategies (6); and generalizability assessments (34). Despite a diverse set of diseases studied, <10% of trials using RWD for trial process tasks evaluated medications or procedures (5/51). All articles highlighted data-related challenges, such as missing values.

DISCUSSION

Database-specific RWD have been occasionally leveraged for various clinical trial tasks. We observed underuse of RWD within conducted medication or procedure trials, though it is subject to the confounder of implicit report of RWD use.

CONCLUSION

Enhanced incorporation of RWD should be further explored for medication or procedure trials, including better understanding of how to handle related data quality issues to facilitate RWD use.

Can Big Data guide prognosis and clinical decisions in epilepsy?

Big Data is no longer a novel concept in health care. Its promise of positive impact is not only undiminished, but daily enhanced by seemingly endless possibilities. Epilepsy is a disorder with wide heterogeneity in both clinical and research domains, and thus lends itself to Big Data concepts and techniques. It is therefore inevitable that Big Data will enable multimodal research, integrating various aspects of "-omics" domains, such as phenome, genome, microbiome, metabolome, and proteome. This scope and granularity have the potential to change our understanding of prognosis and mortality in epilepsy. The scale of new discovery is unprecedented due to the possibilities promised by advances in machine learning, in particular deep learning. The subsequent possibilities of personalized patient care through clinical decision support systems that are evidence-based, adaptive, and iterative seem to be within reach. A major objective is not only to inform decision-making, but also to reduce uncertainty in outcomes. Although the adoption of electronic health record (EHR) systems is near universal in the United States, for example, advanced clinical decision support in or ancillary to EHRs remains sporadic. In this review, we discuss the role of Big Data in the development of clinical decision support systems for epilepsy care, prognostication, and discovery.