Research Papers CanRad Other Sources

Utilization Patterns of Disease-Modifying Antirheumatic Drugs for the Treatment of Rheumatoid Arthritis: Rationale for Improving the Harmonization of Coverage Criteria

Executive Summary
Background/Issue: Rheumatoid arthritis (RA) is a chronic and debilitating disease associated with significant comorbidities and higher risk of mortality for Canadians, with a prevalence of approximately 1.2% of adults living with RA. The first line of treatment for RA is usually conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), but for patients with inadequate response to csDMARDs, the next phase of therapy is typically biologic disease-modifying antirheumatic drugs (bDMARDs). The use of these medications in the treatment of RA is likely to differ across public drug plans because of variations in prescribing patterns and coverage criteria.

Objective: This analysis examined utilization patterns of csDMARDs and bDMARDs for the treatment of RA across public drug plans in Canada over the past several years to identify the rationale for improving coverage criteria harmonization.

Approach: Claims data related to the treatment of RA were extracted for all provincial drug plans (except Quebec) and Yukon from 2015 to 2020 and a descriptive analysis was performed to assess the utilization patterns of csDMARDs, the time to initiate bDMARDs, and the utilization patterns of bDMARDs. The proportion and number of csDMARDs used, the mean time from the initiation of csDMARDs to the initiation of bDMARDs, the persistence of utilization of bDMARDs 6 months after initiation, the changes in proportion and cost per patient of bDMARDs, and the uptake of biosimilars were assessed.

Implications for Policy-Makers: These findings provide a rationale for the harmonization of coverage criteria and reimbursement processes for public drug plans; coverage criteria for csDMARDs can be harmonized to include 3 lines of therapy for all jurisdictions. This could provide modest cost savings to some jurisdictions without impacting health outcomes. Costs per patient for bDMARDs can be reduced through greater uptake of biosimilars and implementation of formulary management strategies such as tiering frameworks (e.g., as in Manitoba).

Launch of a checklist for reporting longitudinal observational drug studies in rheumatology: a EULAR extension of STROBE guidelines based on experience from biologics registries

The advent and increased use of targeted therapies in rheumatology have stimulated the establishment of clinical drug registers. Such registers have evaluated a broad spectrum of outcomes in patients exposed to these uniquely designed, potent and expensive drugs.1–8 Although the main focus of most drug registers in rheumatology is drug safety, other important issues include drug usage, real-life effectiveness and economic consequences.

Accuracy of administrative data for surveillance of healthcare-associated infections: a systematic review

ABSTRACT
Objective: Measuring the incidence of healthcare associated infections (HAI) is of increasing importance in current healthcare delivery systems.
Administrative data algorithms, including (combinations of ) diagnosis codes, are commonly used to determine the occurrence of HAI, either to support within-hospital surveillance programmes or as free-standing quality indicators. We conducted a systematic review evaluating the diagnostic accuracy of administrative data for the detection of HAI.
Methods: Systematic search of Medline, Embase, CINAHL and Cochrane for relevant studies (1995–2013). Methodological quality assessment was performed using QUADAS-2 criteria; diagnostic accuracy estimates were stratified by HAI type and key study characteristics.
Results: 57 studies were included, the majority aiming to detect surgical site or bloodstream infections. Study designs were very diverse regarding the specification of their administrative data algorithm (code selections, follow-up) and definitions of HAI
presence. One-third of studies had important methodological limitations including differential or incomplete HAI ascertainment or lack of blinding of assessors. Observed sensitivity and positive predictive values of administrative data algorithms for HAI detection were very heterogeneous and generally modest at best, both for within-hospital algorithms and for formal quality indicators; accuracy was particularly poor for the identification of device-associated HAI such as central line associated bloodstream infections. The large heterogeneity in study designs across the included studies precluded formal calculation of summary diagnostic accuracy estimates in most instances.
Conclusions: Administrative data had limited and highly variable accuracy for the detection of HAI, and their judicious use for internal surveillance efforts and external quality assessment is recommended. If hospitals and policymakers choose to rely on administrative data for HAI surveillance, continued improvements to existing algorithms and their robust validation are imperative.

The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement

Routinely collected health data, obtained for administrative and clinical purposes without specific a priori research goals, are increasingly used for research. The rapid evolution and availability of these data have revealed issues not addressed by existing reporting guidelines, such as Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). The REporting of studies Conducted using Observational Routinely collected health Data (RECORD) statement was created to fill these gaps. RECORD was created as an extension to the STROBE statement to address reporting items specific to observational studies using routinely collected health data. RECORD consists of a checklist of 13 items related to the title, abstract, introduction, methods, results, and discussion section of articles, and other information required for inclusion in such research reports. This document contains the checklist and explanatory and elaboration information to enhance the use of the checklist. Examples of good reporting for each RECORD checklist item are also included herein. This document, as well as the accompanying website and message board (http://www.record-statement.org), will enhance the implementation and understanding of RECORD. Through implementation of RECORD, authors, journals editors, and peer reviewers can encourage transparency of research reporting.

Simulation modeling with system dynamics (SD) to plan osteoarthritis care delivery in Alberta

Purpose: Currently, there are no reliable and validated tools that health service decision-makers can use to inform system level policy decisions. To address this need, we worked with health administrators, clinicians and researchers to create and validate a decision-support tool that service planners can use to achieve a sustainable, integrated care system for hip and knee osteoarthritis (OA).

Methods: The tool is based on a system dynamics (SD) model of patient flow across the continuum of care, including self-directed, primary, rheumatologic and orthopaedic specialist, acute, and surgical follow-up care. The model was developed in four phases: phase 1 focused on demand and flow rates, phase 2 on resource use and costs, phase 3 on geographical stratification, and phase 4 on adding feedback loops. We populated the model with data from several sources, including Alberta Health & Wellness (e.g. physician claims, inpatient, and ambulatory data), Statistics Canada (e.g. the Survey of Living with Chronic Diseases in Canada and population projections), and the Alberta Bone and Joint Health Institute (clinical/surgical data). Using established principles of SD modeling and an iterative, integrated knowledge translation process involving multiple workshops with front-line clinical staff and administrators, we defined the problem, determined the care process, modeled the system as a series of stock and flows, tested, validated and calibrated the model.

Results: We have developed the full SD model, for two key applications. First, it can help identify flow, resource use and cost variations in current practice, which may benefit from further exploration. For example, variations in practice patterns, particularly surgery rates and resource use, were observed among the health zones reflecting regional differences. Second, it can be used to explore the effects of various ‘what if’ scenarios that can demonstrate system wide and long-term effects that may result from changes in care processes. For example, two scenarios examined were: “What would happen if 1) primary care providers could manage more patients medically, ultimately referring fewer patients to specialists; and 2) primary care providers in all health zones adopted one zone’s rheumatologist referral patterns for OA patients?” Such scenarios change the pathways through which simulated patients flow, the results of which can provide insight into intended and unintended effects on resource use and costs across the continuum of care over a lengthy time horizon.

Conclusions: Our SD model can be used as a decision-support tool to estimate changes in health care demands, resource requirements and costs over time and as a result of ‘what if’ scenarios. It is critically important to involve clinicians and decision-makers in the development of such tools to ensure they are appropriate representations of the system and to facilitate their adoption and continued use to inform decision making.

What could the future hold? Simulating the demand for osteoarthritis (OA) care in Alberta to plan a sustainable OA care system

Purpose: The prevalence of osteoarthritis (OA) is increasing with the aging population; correspondingly, the demand for OA care, including hip and knee replacement surgery, is increasing. Simultaneously, combined with patients seeking surgery at younger ages and more revision surgeries, there is an increasing burden on the healthcare system. In systems with limited surgical capacity, such as Canada’s, this is raising concerns about lengthy surgical wait times. Policy makers are being called upon to identify means of managing these anticipated future demands in order to meet benchmark targets in a way that is sustainable.

Symptom onset, diagnosis and management of osteoarthritis

Abstract
Background
The time between symptom onset and physician diagnosis is a period when people with osteoarthritis can make lifestyle changes to reduce pain, improve function and delay disability.
Data and methods
This study analyses data for a nationally representative sample of 4,565 Canadians aged 20 or older who responded to the Arthritis component of the 2009 Survey on Living with Chronic Diseases in Canada. Descriptive statistics are used to report the prevalence of hip and knee osteoarthritis; the mean age of symptom onset and diagnosis; medication use; and contacts with health professionals during the previous year.
Results
Among people with a physician diagnosis of arthritis, 37% reported osteoarthritis. Of these, 70% experienced pain in the hip(s), knee(s), or hip(s) and knee(s). Close to half (48%) of these people experienced symptoms the same year they were diagnosed; 42% experienced symptoms at least a year before the diagnosis; and 10% experienced
symptoms after the diagnosis. Among those who had symptoms before diagnosis, the average time between symptom onset and diagnosis was 7.7 years.
Interpretation
Individuals with osteoarthritis may experience symptoms for several years before they obtain a physician diagnosis.

Attributable Risk Estimation in Cohort Studies

Population attributable risk (PAR) or etiologic fraction is the proportion of a disease that could be prevented by elimination of a causal risk factor from the population. PAR is likely to be a function of time because both the prevalence of a risk factor and its effect on exposed individuals may change over time, as may the underlying risk of disease. In cohort studies with a wide range of follow-up, it may be important to account for this time dependency. Estimating the full PAR curve on some time scale of interest (e.g. age or time on study) can be more informative than considering a single value. Time-specific PAR can be estimated based on cumulative incidence adjusted for the competing risk of death. Cox models with time-dependent covariates can be used to obtain PAR estimates adjusted for confounders. The unique value of this approach is illustrated with examples that arose from our studies of heart failure in rheumatoid arthritis.

Modelling the complete continuum of care using system dynamics: the case of osteoarthritis in Alberta

Estimating how many patients will require care, the nature of the care they require, and when and where they will require it, is critical when planning resources for a sustainable health-care system. Resource planning must consider how quickly patients move among stages of care, the various different pathways they may take and the resources required at each stage. This research presents a preliminary long-term, population-driven system dynamics simulation developed to support resource planning and policy development relating to osteoarthritis care. The simulation models osteoarthritis patients as they transition through the continuum of care from disease onset through end-stage care, and provides insight into the size and characteristics of the patient population, their resource requirements and associated health-care costs. Although the model presented is specific to the osteoarthritis care system in the Province of Alberta, Canada, similar methods could be applied to develop simulations relating to other chronic conditions.

Health services research in rheumatology: a great deal accomplished, a great deal left to do

Although rheumatology has been on the cutting edge of health services research for decades, there are many unresolved issues for patients, clinicians, insurers, and policy makers. This article explore three areas in which methodologic controversies present tradeoffs to a health care system that is grappling with larger issues around cost and access to care. Specifically, we examine issues around the use of large databases, the appropriate instruments for measuring patient-centered outcomes, and the questions that are raised from cost effectiveness studies of new treatments for rheumatoid arthritis (RA). The issues are presented in the context of a need to provide better information to those who are providing care and those who are paying for it.