Significant Gains in Rheumatoid Arthritis Quality Measures Among RISE Registry Practices

Development and application of Breadth-Depth-Context (BDC), a conceptual framework for measuring technology engagement with a qualified clinical data registry

Objectives

Despite the proliferation of dashboards that display performance data derived from Qualified Clinical Data Registries (QCDR), the degree to which clinicians and practices engage with such dashboards has not been well described. We aimed to develop a conceptual framework for assessing user engagement with dashboard technology and to demonstrate its application to a rheumatology QCDR.

Materials and Methods

We developed the BDC (Breadth-Depth-Context) framework, which included concepts of breadth (derived from dashboard sessions), depth (derived from dashboard actions), and context (derived from practice characteristics). We demonstrated its application via user log data from the American College of Rheumatology's Rheumatology Informatics System for Effectiveness (RISE) registry to define engagement profiles and characterize practice-level factors associated with different profiles.

Results

We applied the BDC framework to 213 ambulatory practices from the RISE registry in 2020-2021, and classified practices into 4 engagement profiles: not engaged (8%), minimally engaged (39%), moderately engaged (34%), and most engaged (19%). Practices with more patients and with specific electronic health record vendors (eClinicalWorks and eMDs) had a higher likelihood of being in the most engaged group, even after adjusting for other factors.

Discussion

We developed the BDC framework to characterize user engagement with a registry dashboard and demonstrated its use in a specialty QCDR. The application of the BDC framework revealed a wide range of breadth and depth of use and that specific contextual factors were associated with nature of engagement.

Conclusion

Going forward, the BDC framework can be used to study engagement with similar dashboards.

Latent Tuberculosis Screening Among New Users of a Biologic or Targeted Synthetic Disease-Modifying Antirheumatic Drug: Gaps in Screening Overall and Among Janus Kinase Inhibitors

OBJECTIVE

We combined claims and electronic health record (EHR) data to provide contemporary and accurate estimates of latent tuberculosis (TB) screening among new users of a biologic or targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) and assess potential gaps in testing by drug type, patient characteristics, and practice.

METHODS

Our denominator population was patients in the Rheumatology Informatics System for Effectiveness (RISE) registry and Medicare using a b/tsDMARD in 2018 without a claim or prescription in the year prior. TB screening was assessed in both Medicare and RISE 1 and 3 years before the medication start date. We calculated the proportion screened overall, by medication class, and by practice. We tested for demographic differences in screening using logistic regression.

RESULTS

In the year before drug starts, 65.6% of patients had any TB screening; in a 3-year window, 72.9% had any TB screening. Rates of screening within 1 year by drug type were greater or equal to the overall screening rate for most drugs except for JAK inhibitors (JAKis) (46%) and interleukin-17 inhibitors (IL-17is) (11.5%). A lower proportion of Hispanic and Asian patients were screened compared with White patients. Practice screening rates ranged from 20.0% to 92.9% of patients within 1 year.

CONCLUSION

We report higher screening rates than have previously been published because of combining claims and EHR data. However, important safety gaps remain, namely, reduced screening among new users of a JAKi or IL-17i and among Asian and Hispanic patients, as well as low-performing practices. Educational initiatives, team-based care delivery, task shifting, and technological interventions to address observed gaps in patient safety procedures are needed.

Implementation of a Best Practice Advisory to Improve Infection Screening Prior to New Prescriptions of Biologics and Targeted Synthetic Drugs

OBJECTIVE

Use of biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) in patients with preexisting tuberculosis (TB), hepatitis B virus (HBV), or hepatitis C virus (HCV) infection can have serious consequences. Although various society guidelines recommend routine screening for these infections before initiating certain b/tsDMARDs, adherence to these recommendations varies widely. This quality improvement initiative evaluated local compliance with screening and assessed whether an automated computerized decision support system in the form of a best practice advisory (BPA) in the electronic health record could improve patient screening.

METHODS

Established patients with autoimmune rheumatic disease (ARD) aged 18 years or older with at least one visit to our rheumatology practice between October 1, 2017, and March 3, 2022, were included. When prescribing a new b/tsDMARD, clinicians were alerted via a BPA that showed the most recent results for TB, HBV, and HCV. Screening proportions for TB, HBV, and HCV before BPA initiation were compared with those of eligible patients after the BPA implementation.

RESULTS

A total of 711 patients pre-BPA and 257 patients post-BPA implementation were included in the study. The BPA implementation was associated with statistically significant improvement in screening for TB from 66% to 82% (P ≤ 0.001), HCV from 60% to 79% (P ≤ 0.001), hepatitis B core antibody 32% to 51% (P ≤ 0.001), and hepatitis B surface antigen from 51% to 70% (P ≤ 0.001).

CONCLUSION

Implementation of a BPA can improve infectious disease screening for patients with ARD who are started on b/tsDMARDs and has potential to improve patient safety.

An Electronic Dashboard to Improve Dosing of Hydroxychloroquine Within the Veterans Health Care System: Time Series Analysis

BACKGROUND

Hydroxychloroquine (HCQ) is commonly used for patients with autoimmune conditions. Long-term use of HCQ can cause retinal toxicity, but this risk can be reduced if high doses are avoided.

OBJECTIVE

We developed and piloted an electronic health record-based dashboard to improve the safe prescribing of HCQ within the Veterans Health Administration (VHA). We observed pilot facilities over a 1-year period to determine whether they were able to improve the proportion of patients receiving inappropriate doses of HCQ.

METHODS

Patients receiving HCQ were identified from the VHA corporate data warehouse. Using PowerBI (Microsoft Corp), we constructed a dashboard to display patient identifiers and the most recent HCQ dose and weight (flagged if ≥5.2 mg/kg/day). Six VHA pilot facilities were enlisted to test the dashboard and invited to participate in monthly webinars. We performed an interrupted time series analysis using synthetic controls to assess changes in the proportion of patients receiving HCQ ≥5.2 mg/kg/day between October 2020 and November 2021.

RESULTS

At the start of the study period, we identified 18,525 total users of HCQ nationwide at 128 facilities in the VHA, including 1365 patients at the 6 pilot facilities. Nationwide, at baseline, 19.8% (3671/18,525) of patients were receiving high doses of HCQ. We observed significant improvements in the proportion of HCQ prescribed at doses ≥5.2 mg/kg/day among pilot facilities after the dashboard was deployed (-0.06; 95% CI -0.08 to -0.04). The difference in the postintervention linear trend for pilot versus synthetic controls was also significant (-0.06; 95% CI -0.08 to -0.05).

CONCLUSIONS

The use of an electronic health record-based dashboard reduced the proportion of patients receiving higher than recommended doses of HCQ and significantly improved performance at 6 VHA facilities. National roll-out of the dashboard will enable further improvements in the safe prescribing of HCQ.

Researchers in rheumatology should avoid categorization of continuous predictor variables

BACKGROUND

Rheumatology researchers often categorize continuous predictor variables. We aimed to show how this practice may alter results from observational studies in rheumatology.

METHODS

We conducted and compared the results of two analyses of the association between our predictor variable (percentage change in body mass index [BMI] from baseline to four years) and two outcome variable domains of structure and pain in knee and hip osteoarthritis. These two outcome variable domains covered 26 different outcomes for knee and hip combined. In the first analysis (categorical analysis), percentage change in BMI was categorized as ≥ 5% decrease in BMI, < 5% change in BMI, and ≥ 5% increase in BMI, while in the second analysis (continuous analysis), it was left as a continuous variable. In both analyses (categorical and continuous), we used generalized estimating equations with a logistic link function to investigate the association between the percentage change in BMI and the outcomes.

RESULTS

For eight of the 26 investigated outcomes (31%), the results from the categorical analyses were different from the results from the continuous analyses. These differences were of three types: 1) for six of these eight outcomes, while the continuous analyses revealed associations in both directions (i.e., a decrease in BMI had one effect, while an increase in BMI had the opposite effect), the categorical analyses showed associations only in one direction of BMI change, not both; 2) for another one of these eight outcomes, the categorical analyses suggested an association with change in BMI, while this association was not shown in the continuous analyses (this is potentially a false positive association); 3) for the last of the eight outcomes, the continuous analyses suggested an association of change in BMI, while this association was not shown in the categorical analyses (this is potentially a false negative association).

CONCLUSIONS

Categorization of continuous predictor variables alters the results of analyses and could lead to different conclusions; therefore, researchers in rheumatology should avoid it.

Screening for Latent Infections Among Users of High-Risk Immunosuppressants: A Cross-Sectional Analysis From the Veterans Health Administration Healthcare System

OBJECTIVES

Guidelines recommend screening for latent hepatitis B virus (HBV), hepatitis C virus (HCV), and tuberculosis (TB) before initiating biologics or targeted synthetic disease-modifying antirheumatic drugs (b/ts DMARDs) to avoid reactivation of life-threatening infections. The extent to which such screening occurs in the national Veterans Health Administration (VA) healthcare system is unknown.

METHODS

Using data from the Veterans Affairs' (VA) Corporate Data Warehouse, we performed a cross-sectional analysis of veterans receiving b/ts DMARDs between October 1, 2017, and September 30, 2019. We calculated the proportion of patients with screening completed for latent HBV, HCV, and TB between October 1, 1999 and September 30, 2019. Patient characteristics associated with complete screening were evaluated using mixed-effects multivariate logistic regression models. We also examined facility-level factors associated with high versus lower performance.

RESULTS

A total of 51,764 unique patients from 129 VA facilities received b/ts DMARDs from 2017 to 2019. Of these, 63% had complete screening. Among the 11,006 patients identified as new users, 64% had complete screening. Higher screening rates were observed among Hispanic/Latinx and Black/African American patients, users of B-cell therapies, and patients who had seen oncology subspecialists. Substantial variation was observed across facilities, with complete screening ranging from 13% to 98% of patients. Higher screening rates were associated with highly complex, urban, and higher-volume facilities.

CONCLUSIONS

Approximately two-thirds of veterans taking b/ts DMARDs have received guideline-recommended screening for HBV, HCV, and TB, but substantial facility variation was observed. Performance measures, robust multidisciplinary workflows, and electronic health record-based tools to feed information back to providers may improve screening rates for low-performing facilities.

The Relationship Between Electronic Health Record System and Performance on Quality Measures in the American College of Rheumatology's Rheumatology Informatics System for Effectiveness (RISE) Registry: Observational Study

BACKGROUND

Routine collection of disease activity (DA) and patient-reported outcomes (PROs) in rheumatoid arthritis (RA) are nationally endorsed quality measures and critical components of a treat-to-target approach. However, little is known about the role electronic health record (EHR) systems play in facilitating performance on these measures.

OBJECTIVE

Using the American College Rheumatology's (ACR's) RISE registry, we analyzed the relationship between EHR system and performance on DA and functional status (FS) quality measures.

METHODS

We analyzed data collected in 2018 from practices enrolled in RISE. We assessed practice-level performance on quality measures that require DA and FS documentation. Multivariable linear regression and zero-inflated negative binomial models were used to examine the independent effect of EHR system on practice-level quality measure performance, adjusting for practice characteristics and patient case-mix.

RESULTS

In total, 220 included practices cared for 314,793 patients with RA. NextGen was the most commonly used EHR system (34.1%). We found wide variation in performance on DA and FS quality measures by EHR system (median 30.1, IQR 0-74.8, and median 9.0, IQR 0-74.2), respectively). Even after adjustment, NextGen practices performed significantly better than Allscripts on the DA measure (51.4% vs 5.0%; P<.05) and significantly better than eClinicalWorks and eMDs on the FS measure (49.3% vs 29.0% and 10.9%; P<.05).

CONCLUSIONS

Performance on national RA quality measures was associated with the EHR system, even after adjusting for practice and patient characteristics. These findings suggest that future efforts to improve quality of care in RA should focus not only on provider performance reporting but also on developing and implementing rheumatology-specific standards across EHRs.

A narrative review on the validity of electronic health record-based research in epidemiology

Electronic health records (EHRs) are widely used in epidemiological research, but the validity of the results is dependent upon the assumptions made about the healthcare system, the patient, and the provider. In this review, we identify four overarching challenges in using EHR-based data for epidemiological analysis, with a particular emphasis on threats to validity. These challenges include representativeness of the EHR to a target population, the availability and interpretability of clinical and non-clinical data, and missing data at both the variable and observation levels. Each challenge reveals layers of assumptions that the epidemiologist is required to make, from the point of patient entry into the healthcare system, to the provider documenting the results of the clinical exam and follow-up of the patient longitudinally; all with the potential to bias the results of analysis of these data. Understanding the extent of as well as remediating potential biases requires a variety of methodological approaches, from traditional sensitivity analyses and validation studies, to newer techniques such as natural language processing. Beyond methods to address these challenges, it will remain crucial for epidemiologists to engage with clinicians and informaticians at their institutions to ensure data quality and accessibility by forming multidisciplinary teams around specific research projects.

Strategies for developing and implementing a rheumatoid arthritis healthcare quality framework: a thematic analysis of perspectives from arthritis stakeholders

OBJECTIVES

To obtain stakeholder perspectives to inform the development and implementation of a rheumatoid arthritis (RA) healthcare quality measurement framework.

DESIGN

Qualitative study using thematic analysis of focus groups and interviews.

SETTING

Arthritis stakeholders from across Canada including healthcare providers, persons living with RA, clinic managers and policy leaders were recruited for the focus groups and interviews.

PARTICIPANTS

Fifty-four stakeholders from nine provinces.

INTERVENTIONS

Qualitative researchers led each focus group/interview using a semistructured guide; the digitally recorded data were transcribed verbatim. Two teams of two coders independently analysed the transcripts using thematic analysis.

RESULTS

Perspectives on the use of different types of measurement frameworks in healthcare were obtained. In particular, stakeholders advocated for the use of existing healthcare frameworks over frameworks developed in the business world and adapted for healthcare. Persons living with RA were less familiar with specific measurement frameworks, however, they had used existing online public forums for rating their experience and quality of healthcare provided. They viewed a standardised framework as potentially useful for assisting with monitoring the care provided to them individually. Nine guiding principles for framework development and 13 measurement themes were identified. Perceived barriers identified included access to data and concerns about how measures in the framework were developed and used. Effective approaches to framework implementation included having sound knowledge translation strategies and involving stakeholders throughout the measurement development and reporting process. Clinical models of care and health policies conducive to outcome measurement were highlighted as drivers of successful measurement initiatives.

CONCLUSION

These important perspectives will be used to inform a healthcare quality measurement framework for RA.