Cardiovascular care guideline implementation in community health centers in Oregon: a mixed-methods analysis of real-world barriers and challenges

Evidence-Based Quality Improvement: a Scoping Review of the Literature

BACKGROUND

Quality improvement (QI) initiatives often reflect approaches based on anecdotal evidence, but it is unclear how initiatives can best incorporate scientific literature and methods into the QI process. Review of studies of QI initiatives that aim to systematically incorporate evidence review (termed evidence-based quality improvement (EBQI)) may provide a basis for further methodological development.

METHODS

In this scoping review (registration: https://osf.io/hr5bj ) of EBQI, we searched the databases PubMed, CINAHL, and SCOPUS. The review addressed three central questions: How is EBQI defined? How is evidence used to inform evidence-informed QI initiatives? What is the effectiveness of EBQI?

RESULTS

We identified 211 publications meeting inclusion criteria. In total, 170 publications explicitly used the term "EBQI." Published definitions emphasized relying on evidence throughout the QI process. We reviewed a subset of 67 evaluations of QI initiatives in primary care, including both studies that used the term "EBQI" with those that described an evidence-based initiative without using EBQI terminology. The most frequently reported EBQI components included use of evidence to identify previously tested effective QI interventions; engaging stakeholders; iterative intervention development; partnering with frontline clinicians; and data-driven evaluation of the QI intervention. Effectiveness estimates were positive but varied in size in ten studies that provided data on patient health outcomes.

CONCLUSIONS

EBQI is a promising strategy for integrating relevant prior scientific findings and methods systematically in the QI process, from the initial developmental phase of the IQ initiative through to its evaluation. Future QI researchers and practitioners can use these findings as the basis for further development of QI initiatives.

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.

Improving management of the genitourinary syndrome of menopause: evaluation of a health system-based, cluster-randomized intervention

BACKGROUND

Genitourinary symptoms are common in postmenopausal women and adversely affect the quality of life. National surveys and data collected from our healthcare system indicate that postmenopausal women with the genitourinary syndrome of menopause often fail to receive appropriate diagnosis or treatment.

OBJECTIVE

To promote greater detection and treatment of the genitourinary syndrome of menopause, we created and tested a clinician-focused health system intervention that included clinician education sessions and a suite of evidence-based electronic health record tools.

STUDY DESIGN

Using a cluster-randomized design, we allocated primary care (16) and gynecology (6) clinics to the intervention or control group. From September to November 2014, we provided training about the diagnosis and treatment of genitourinary syndrome of menopause in face-to-face presentations at each intervention clinic and in an online video. We developed clinical decision support tools in the electronic health record that contained an evidence-based, point-of-care knowledge resource, a standardized order set, and a checklist of patient education materials for the patient's after visit summary. The tools aimed to facilitate accurate diagnostic coding and prescribing (SmartSet, SmartRx) along with relevant patient information (SmartText). Clinicians who only performed visits at control clinics received no training or notification about the tools. Our primary outcome was vulvovaginal diagnoses made at well visits for women at the age of 55 years and older from November 15, 2014 to November 15, 2015. We also assessed urinary diagnoses, vaginal estrogen prescriptions, and use of the electronic tools. There was departmental support for the intervention but no prioritization within the healthcare system to incentivize change.

RESULTS

In the 1-year period, 386 clinicians performed 14,921 well visits for women at the age of 55 years and older. Among the 190 clinicians who performed well visits in the intervention clinics, 109 (57.4%) completed either in-person or online educational training. The proportion of visits that included a vulvovaginal (7.2% vs 5.8%; odds ratio, 1.27; 95% confidence interval, 0.65-2.51) or urinary diagnosis (2.5% vs 3.1%; odds ratio, 0.79; 95% confidence interval, 0.55-1.13) or vaginal estrogen prescription (4.5% vs 3.7%; odds ratio, 1.24; 95% confidence interval, 0.63-2.46) did not differ between study arms. There was a significant interaction for primary care and gynecology, which revealed more vulvovaginal diagnoses by gynecology but not primary care intervention clinics (odds ratio, 1.63; 95% confidence interval, 1.15-2.31), but there was no significant interaction for prescriptions. Clinicians in the intervention clinics were more likely to use decision support tools than those in control clinics-SmartSet (22.2% vs 1.5%; odds ratio, 18.8; 95% confidence interval, 5.5-63.8) and SmartText for patient information (38.0% vs 24.4%; odds ratio, 1.91; 95% confidence interval, 1.10-3.34). A per-protocol analysis revealed similar findings.

CONCLUSION

Overall, the intervention did not lead to more diagnoses or prescription therapy for postmenopausal genitourinary symptoms but did result in greater distribution of patient information. Gynecology clinicians were more likely to address genitourinary symptoms generally and were more likely to make a vulvovaginal diagnosis after the intervention. Further efforts for improving care should consider ongoing clinician education beginning with enhanced menopause curricula in residency training. Additional interventions to consider include greater access for postmenopausal women to gynecologic care, addressing treatment barriers, and development of national performance metrics.

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.

A Practice-Based Research Network (PBRN) Roadmap for Evaluating COVID-19 in Community Health Centers: A Report From the OCHIN PBRN

BACKGROUND

Primary care practice-based research networks (PBRNs) are critical laboratories for generating evidence from real-world settings, including studying natural experiments. Primary care's response to the novel coronavirus-19 (COVID-19) pandemic is arguably the most impactful natural experiment in our lifetime. EVALUATING THE IMPACT OF COVID-19: We briefly describe the OCHIN PBRN of community health centers (CHCs), its partnership with implementation scientists, and how we are leveraging this infrastructure and expertise to create a rapid research response evaluating how CHCs across the country responded to the COVID-19 pandemic. COVID-19 RESEARCH ROADMAP: Our research agenda focuses on asking: How has care delivery in CHCs changed due to COVID-19? What impact has COVID-19 had on the delivery of preventive services in CHCs? Which PBRN services (e.g., data surveillance, training, evidence synthesis) are most impactful to real-world practices? What decision-making strategies were used in the PBRN and its practices to make real-time changes in response to the pandemic? What critical factors in successfully and sustainably transforming primary care are illuminated by pandemic-driven changes?

DISCUSSION AND CONCLUSIONS

PBRNs enable real-world evaluation of practice change and natural experiments, and thus are ideal laboratories for implementation science research. We present a real-time example of how a PBRN Implementation Laboratory activated a response to study a historic natural experiment, to help other PBRNs charting a course through this pandemic.

Development of an algorithm to link electronic health record prescriptions with pharmacy dispense claims

Objective

Medication adherence is an important aspect of chronic disease management. Electronic health record (EHR) data are often not linked to dispensing data, limiting clinicians' understanding of which of their patients fill their medications, and how to tailor care appropriately. We aimed to develop an algorithm to link EHR prescribing to claims-based dispensing data and use the results to quantify how often patients with diabetes filled prescribed chronic disease medications.

Materials and Methods

We developed an algorithm linking EHR prescribing data (RxNorm terminology) to claims-based dispensing data (NDC terminology), within sample of adult (19-64) community health center (CHC) patients with diabetes from a network of CHCs across 12 states. We demonstrate an application of the method by calculating dispense rates for a set of commonly prescribed diabetes and cardio-protective medications. To further inform clinical care, we computed adjusted odds ratios of dispense by patient-, encounter-, and clinic-level characteristics.

Results

Seventy-six percent of cardio-protective medication prescriptions and 74% of diabetes medications were linked to a dispensing record. Age, income, ethnicity, insurance, assigned primary care provider, comorbidity, time on EHR, and clinic size were significantly associated with odds of dispensing.

Discussion

EHR prescriptions and pharmacy dispense data can be linked at the record level across different terminologies. Dispensing rates in this low-income population with diabetes were similar to other populations.

Conclusion

Record linkage resulted in the finding that CHC patients with diabetes largely had their chronic disease medications dispensed. Understanding factors associated with dispensing rates highlight barriers and opportunities for optimal disease management.