Capturing Patient Value in an Economic Evaluation.

OBJECTIVE: Economic evaluations predominantly use generic outcomes, such as the Euro Quality of Life-5 Dimension (EQ-5D), to assess health status. However, because of the generic nature, they are less suitable to capture the quality of life of patients with specific conditions. Given the transition to patient-centered (remote) care delivery, this study aims to evaluate the possibility of using disease-specific measures in a cost-effectiveness analysis. METHODS: A real-life cohort from Maasstad Hospital (2020-2021) in the Netherlands, with 772 patients with rheumatoid arthritis (RA), was used to assess the cost-effectiveness of electronic consultations (e-consultations) compared with face-to-face consultations. The Incremental Cost-Effectiveness Ratio (ICER), based on the generic EQ-5D, was compared with ICER's based on RA-specific measures: the Rheumatoid Arthritis Impact of Disease (RAID) and Health Assessment Questionnaire-Disability Index (HAQ-DI). To compare the cost-effectiveness of these different measures, HAQ-DI and RAID were expressed in quality-adjusted life-years (QALYs) via estimated conversion equations. RESULTS: Disease-specific patient-reported outcome measures (PROMs) offer a promising alternative for traditional measures in economic evaluations, capturing patient-relevant domains more comprehensively. Because PROMs are increasingly applied in clinical practice, the next step entails modeling of an RA patient-wide conversion equation to implement PROMs in economic evaluations. CONCLUSION: The conventional ICER (eg, EQ-5D) indicates that e-consultations are cost-effective with cost savings of -€161,000 per QALY gained for a prevalent RA cohort treated in a secondary trainee hospital. RA-specific measures show similar results, with ICERs of -€163,000 per HAQ-DI (QALY) and -€223,000 per RAID (QALY) gained. RA-specific measures capture patient-relevant domains and offer the opportunity to improve the assessment and treatment of the disease impact.

Cost-utility analysis of tapering strategies of biologicals in rheumatoid arthritis patients in the Netherlands.

OBJECTIVES: Current guidelines recommend tapering biological disease-modifying antirheumatoid drugs (bDMARDs) in rheumatoid arthritis (RA) if the disease is under control. However, guidelines on tapering are lacking. Assessing cost-effectiveness of different tapering strategies might provide broader input for creating guidelines on how to taper bDMARDs in patients with RA. The aim of this study is to evaluate the long-term cost-effectiveness from a societal perspective of bDMARD tapering strategies in Dutch patients with RA, namely 50% dose reduction (tapering), discontinuation and a 50% dose reduction followed by discontinuation (de-escalation). METHODS: Using a societal perspective, a Markov model with a life-time horizon of 30 years was used to simulate 3-monthly transitions between Disease Activity 28 (DAS28)-defined health states of remission (<2.6), low disease activity (2.63.2). Transition probabilities were estimated through literature search and random effects pooling. Incremental costs, incremental quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs) and incremental net monetary benefits for each tapering strategy were compared with continuation. Deterministic, probabilistic sensitivity analyses and multiple scenario analyses were performed. RESULTS: After 30 years, the ICERs were €115 157/QALY lost, €74 226/QALY lost and €67 137/QALY lost for tapering, de-escalation and discontinuation, respectively; mainly driven by bDMARD cost savings and a 72.8% probability of a loss in quality of life. This corresponds to a 76.1%, 64.3% and 60.1% probability of tapering, de-escalation and discontinuation being cost-effective, provided a willingness-to-accept threshold of €50 000/QALY lost. CONCLUSIONS: Based on these analyses, the 50% tapering approach saved the highest cost per QALY lost.

Dealing with Time Estimates in Hospital Cost Accounting: Integrating Fuzzy Logic into Time-Driven Activity-Based Costing.

BACKGROUND: Time-driven activity-based costing (TDABC) can support value-based healthcare (VBHC) programs by providing insights into the actual relationships between time spent by the medical staff and the costs associated with specific care cycles. However, the robustness of time estimates (time variation) as well as the effort required to obtain these estimates are major challenges of the TDABC methodology, given the heterogeneity in patients' needs and the presence of (multi)morbidity. To allow for the variation in time estimates in an efficient manner, this study uses fuzzy logic (FL) to estimate the TDABC model parameters (FL-TDABC). METHODS: A standardized care path was used to calculate the annual costs (per patient) and cost drivers of the Rheumatoid arthritis (RA) care cycle following the FL-TDABC methodology. Cost information (2018) was derived from hospital reports concerning financial, human resource and business intelligence data from a Dutch top clinical research hospital, Maasstad Hospital. Time estimates of procedures were obtained by interviewing the medical staff and relevant care activities were extracted from electronic health records. For analytical and validation purposes, FL-TDABC estimates were compared with TDABC and ABC cost estimates. RESULTS: The RA care cycle annual costs totaled €1497 per patient (2018 prices) based on the FL-TDABC methodology. Maximum RA cycle costs (€1684) were some 22% higher than minimum costs (€1317) observed from FL-TDABC. Cost drivers explaining the cost variation are predominantly the number of consultations with rheumatologists and pharmacy costs related to RA. Based on TDABC and ABC, annual costs per patient were €1609 and €1604, respectively. CONCLUSIONS: The FL-TDABC methodology offers a more precise and efficient estimate of care cycle costs, allowing for the subjective (fuzzy) nature of healthcare time estimates made by the medical staff. As a result, the FL-TDABC provides insight into the practice variation, and hence it can promote the transition from a volume-based system to a VBHC system.

Multimorbidity status and annual healthcare expenditures of rheumatoid arthritis patients: a Dutch hospital-centered versus population-based comparison.

The prevalence of multimorbidity among rheumatoid arthritis (RA) patients is increasing and associated with worse outcomes. Therefore, management of multimorbid patients requires a multidisciplinary approach. However, healthcare systems consist of mono-disciplinary subsystems, which limits collaboration across subsystems. To study the importance of a multidisciplinary, integrated approach, associations between expenditures and multimorbidity are assessed in real-life data. Retrospective data on RA patients from a Dutch single-hospital are analyzed and compared to the Dutch RA population data. The Elixhauser index is used to measure the multimorbidity prevalence. Regression analyses were conducted to derive the relationship between multimorbidity, healthcare costs and self-reported quality of life (e.g. EQ-5D). When analyzing the impact of multimorbidity within RA patients in context of a single-hospital context, multimorbidity is only partially captured: 13% prevalence versus 24% of the Dutch population. Multimorbidity is associated with higher care expenditures. Depending on the type of multimorbidity, expenditures are €43-€5821 higher in a single-hospital and from €2259-€9648 in population data. Finally, medication use associated with chronic diseases and self-reported aspects of well-being are associated with similar increases in healthcare expenditures as multimorbidity based on hospital care. Within RA, a single-hospital approach underestimates the association between multimorbidity and healthcare expenditures as 43% of healthcare utilization and expenditures are missed. To overcome a single-provider perspective in healthcare and efficiently coordinate multimorbid patients, besides providing holistic care, professionals also need to use data providing comprehensive pictures of patients.

Meta-Analyses on the Effects of Disease-Modifying Antirheumatic Drugs on the Most Relevant Patient-Reported Outcome Domains in Rheumatoid Arthritis.

OBJECTIVE: Whereas in the treatment of rheumatoid arthritis much evidence exists on the effects of current pharmacologic treatment on clinical outcomes, little is known about the effects on patient-reported outcomes. This systematic review aims to evaluate the effects of disease-modifying antirheumatic drugs (DMARDs) on the patient-relevant domains of pain, fatigue, activity limitation, overall emotional and physical health impact, and work/school/housework ability and productivity. METHODS: A literature search was conducted to identify randomized controlled trials wherein registered DMARDs were compared with placebo or methotrexate and reported the effects on patient-reported outcomes included in the International Consortium of Health Outcomes Measurement standard set for inflammatory arthritis. Random effects meta-analyses using the standardized mean differences of change scores as the effect measure were performed for the domains of pain, fatigue, and activity limitation, comparing DMARDs with placebo and methotrexate. The other 2 domains were presented narratively. RESULTS: Across the 5 domains, 69 records belonging to 52 studies were identified. All meta-analyses showed a decrease of burden when DMARDs were compared with placebo (standardized mean differences [95% confidence interval] in pain -0.80 [-0.99, -0.61], fatigue -0.48 [-0.64, -0.32], and activity limitation -0.56 [- 0.63, -0.49]) and when compared with methotrexate (-0.55 [-0.70, -0.41), -0.44 [-0.55, -0.33], and - 0.37 [-0.44, -0.30], respectively). CONCLUSION: DMARDs decrease the burden in all the domains that are relevant to patients. Effect sizes may be influenced by DMARD type. Therefore, in the decision for rheumatoid arthritis treatment, patient-reported outcomes should be taken into account.

Defining the care delivery value chain and mapping the patient journey in rheumatoid arthritis.

Rheumatoid Arthritis (RA) is a chronic disease that impacts patients' quality of life. Sophisticated organization of care delivery drives quality improvement. Therefore, the study objective was establishing a validated process map of the care cycle for RA patients. Hence, increasing transparency and optimizing care delivery and identifying areas of improvement. To map the RA care cycle, the care delivery value chain (CDVC) approach was used as framework to document activities and resources systematically. A mixed method study was conducted where quantitative data on activities were collected from health records and unstructured interviews with medical staff were held. Consequently, the process map was separately validated in a consensus meeting with a delegation of the medical staff and patient advisory board. At the start of the care cycle, the focus is predominantly on defining the treat-to-target strategy and examining disease activity. Towards the monitoring phase, tapering medication and managing the disease through patient-reported outcome measures are becoming increasingly important. Although patient's functioning, quality of care and patient's evaluation of received care are monitored, reflection of CDVC and engaging patients in the evaluation process resulted in improvement actions on outcome and process level. Mapping the RA care cycle following a systematic approach, provides insight and transparency in delivered activities, involved resources and the engagement of patients and caregivers at multiple levels, contributing to a system facilitating value-based care delivery. The CDVC framework and applied methodology is recommended in other conditions. Future research will focus at assigning outcomes and costs to activities and evaluating interventions to explore patient value.

Barriers and facilitators for implementation of a digital referral algorithm for inflammatory arthritis - a qualitative assessment in patients and caregivers.

PURPOSE: Difficulty to recognize inflammatory rheumatic diseases (IRD) in a primary care setting leads to late referral to secondary care. An evidence-based digital referral algorithm can support early referral, yet implementation in daily practice only succeeds with support of end users. We aim to understand the context of implementing a digital referral algorithm and explore the potential barriers and facilitators to implementation. METHODS: This qualitative study comprised focus groups and an online survey. Focus groups were performed with patients from outpatient rheumatology clinics. Surveys were sent out to general practitioners and rheumatologists distributed over The Netherlands. The presented digital referral algorithm originates from the JOINT referral study. Thematic analysis was used with inductive and deductive approaches. RESULTS: In total 26 patients participated distributed over three focus groups, and 215 caregivers (104 rheumatologists, 111 general practitioners) filled out the survey. Both patients and caregivers endorse the need for early referral, and recognize the perceived benefit of the digital algorithm. Potential barriers include the complexity of currently included questions, and the outcome lacking information on what to do with no risk of IRD. In order for implementation to be successful, the inclusivity, accessibility, content and outcome of the algorithm are considered important themes. CONCLUSION: Successful implementation of a digital referral algorithm needs a systematic multi-facetted approach, considering the barriers and facilitators for implementation as discussed. Since the majority of identified barriers and facilitators was overlapping between all stakeholders, findings from this study can reliably inform further decision strategies for successful implementation.

Diagnostic Performance and Clinical Utility of Referral Rules to Identify Primary Care Patients at Risk of an Inflammatory Rheumatic Disease.

OBJECTIVE: To determine the diagnostic performance and clinical utility of the Rotterdam Early Arthritis Cohort (REACH) and the Clinical Arthritis Rule (CARE) referral rules in an independent population of unselected patients from primary care. METHODS: This study consisted of adults who were suspected of the need for referral to a rheumatologist by their general practitioner. Diagnostic accuracy measures and a net benefit approach were used to compare both rules to usual care for recognizing inflammatory arthritis and inflammatory rheumatic diseases (IRDs). Using the least absolute shrinkage and selection operator method and cross-validation we created an optimal prediction rule for IRD. RESULTS: This study consisted of 250 patients, of whom 42 (17%) were diagnosed with inflammatory arthritis and 55 (22%) with an IRD 3 months after referral. Considering inflammatory arthritis, the area under the receiver operating characteristic curve (AUC) was 0.72 (95% confidence interval [95% CI] 0.64-0.80) for REACH and 0.82 (95% CI 0.75-0.88) for CARE. Considering IRD, the AUC was 0.66 (95% CI 0.58-0.74) for REACH and 0.76 (95% CI 0.69-0.83) for CARE. CARE was of highest clinical value when compared to usual care. The composite referral rule for IRD of 10 parameters included sex, age, joint features, acute onset of symptoms, physical limitations, and duration of symptoms (AUC 0.82 [95% CI 0.75-0.88]). CONCLUSION: Both validated rules have a net benefit in recognizing inflammatory arthritis as well as IRD compared to usual care, but CARE shows superiority over REACH. Although the composite referral rule indicates a greater diagnostic performance, external validation is needed.

The susceptibility of attaining and maintaining DMARD-free remission in different (rheumatoid) arthritis phenotypes.

OBJECTIVES: To compare (sustained) DMARD-free remission rates((S)DFR), defined as respectively ≥6 months and >1 year, after 2 and 5 years between three clinical arthritis phenotypes; undifferentiated arthritis(UA), autoantibody-negative(RA-) and positive rheumatoid arthritis(RA+). METHODS: All UA(n = 130), RA-(n = 176) and RA + (n = 331) patients from the tREACH trial, a stratified single-blinded trial with a treat-to-target approach, were used. (S)DFR comparisons between phenotypes after 2 and 5 years were performed with Logistic regression. Medication use and early and late flares(DAS ≥ 2.4), respectively defined as < 12 and >12 months after reaching DFR, were also compared. Cox proportional hazard models were used to evaluate potential predictors for (S)DFR. RESULTS: Within 2 and 5 years less DFR was seen in RA + (17.2-25.7%), followed by RA-(28.4-42.1%) and UA patients(43.1-58.5%). This also applied for SDFR within 2 and 5 years (respectively 7.6% and 21.4%; 20.5% and 38.1%; and 35.4% and 55.4%). A flare during tapering was seen in 22.7% of patients. Of the patients in DFR 7.5% had an early flare and 3.4% a late flare. Also more treatment intensifications occurred in RA+ compared with RA- and UA. We found that higher baseline DAS, ACPA positivity, BMI and smoking were negatively associated with (S)DFR, while clinical phenotype(reference RA+), short symptom duration(<6 months) and remission within 6 months were positively associated. CONCLUSIONS: (Long-term) clinical outcomes differ between undifferentiated arthritis, autoantibody-negative and positive rheumatoid arthritis(RA). These data reconfirm that RA can be subdivided into aforementioned clinical phenotypes and that treatment might be stratified upon these phenotypes, although validation is needed. TRIAL REGISTRATION: ISRCTN, https://www.isrctn.com/, ISRCTN26791028.