Prognostic model for overall survival of head and neck cancer patients in the palliative phase.

BACKGROUND: Patients with head and neck squamous cell carcinoma (HNSCC) enter the palliative phase when cure is no longer possible or when they refuse curative treatment. The mean survival is five months, with a range of days until years. Realistic prognostic counseling enables patients to make well-considered end-of-life choices. However, physicians tend to overestimate survival. The aim of this study was to develop a prognostic model that calculates the overall survival (OS) probability of palliative HNSCC patients. METHODS: Patients diagnosed with incurable HNSCC or patients who refused curative treatment for HNSCC between January 1st 2006 and June 3rd 2019 were included (n = 659). Three patients were lost to follow-up. Patients were considered to have incurable HNSCC due to tumor factors (e.g. inoperability with no other curative treatment options, distant metastasis) or patient factors (e.g. the presence of severe comorbidity and/or poor performance status).Tumor and patients factors accounted for 574 patients. An additional 82 patients refused curative treatment and were also considered palliative. The effect of 17 candidate predictors was estimated in the univariable cox proportional hazard regression model. Using backwards selection with a cut-off P-value < 0.10 resulted in a final multivariable prediction model. The C-statistic was calculated to determine the discriminative performance of the model. The final model was internally validated using bootstrapping techniques. RESULTS: A total of 647 patients (98.6%) died during follow-up. Median OS time was 15.0 weeks (95% CI: 13.5;16.6). Of the 17 candidate predictors, seven were included in the final model: the reason for entering the palliative phase, the number of previous HNSCC, cT, cN, cM, weight loss in the 6 months before diagnosis, and the WHO performance status. The internally validated C-statistic was 0.66 indicating moderate discriminative ability. The model showed some optimism, with a shrinkage factor of 0.89. CONCLUSION: This study enabled the development and internal validation of a prognostic model that predicts the OS probability in HNSCC patients in the palliative phase. This model facilitates personalized prognostic counseling in the palliative phase. External validation and qualitative research are necessary before widespread use in patient counseling and end-of-life care.

Standardized mortality ratios for regionalized acute cardiovascular care.

BACKGROUND: Standardized Mortality Ratios (SMRs) are case-mix adjusted mortality rates per hospital and are used to evaluate quality of care. However, acute care is increasingly organized on a regional level, with more severe patients admitted to specialized hospitals. We hypothesize that the current case-mix adjustment insufficiently captures differences in case-mix between non-specialized and specialized hospitals. We aim to improve the SMR by adding proxies of disease severity to the model and by calculating a regional SMR (RSMR) for acute cerebrovascular disease (CVD) and myocardial infarction (MI). METHODS: We used data from the Dutch National Basic Registration of Hospital Care. We selected all admissions from 2016 to 2018. SMRs and RSMRs were calculated by dividing the observed in-hospital mortality by the expected in-hospital mortality. The expected in-hospital mortality was calculated using logistic regression with adjustment for age, sex, socioeconomic status, severity of main diagnosis, urgency of admission, Charlson comorbidity index, place of residence before admission, month/year of admission, and in-hospital mortality as outcome. RESULTS: The IQR of hospital SMRs of CVD was 0.85-1.10, median 0.94, with higher SMRs for specialized hospitals (median 1.12, IQR 1.00-1.28, 71%-SMR > 1) than for non-specialized hospitals (median 0.92, IQR 0.82-1.07, 32%-SMR > 1). The IQR of RSMRs was 0.92-1.09, median 1.00. The IQR of hospital SMRs of MI was 0.76-1.14, median 0.98, with higher SMRs for specialized hospitals (median 1.00, IQR 0.89-1.25, 50%-SMR > 1 versus median 0.94, IQR 0.74-1.11, 44%-SMR > 1). The IQR of RSMRs was 0.90-1.08, median 1.00. Adjustment for proxies of disease severity mostly led to lower SMRs of specialized hospitals. CONCLUSION: SMRs of acute regionally organized diseases do not only measure differences in quality of care between hospitals, but merely measure differences in case-mix between hospitals. Although the addition of proxies of disease severity improves the model to calculate SMRs, real disease severity scores would be preferred. However, such scores are not available in administrative data. As a consequence, the usefulness of the current SMR as quality indicator is very limited. RSMRs are potentially more useful, since they fit regional organization and might be a more valid representation of quality of care.

Estimation of treatment effects in observational stroke care data: comparison of statistical approaches.

INTRODUCTION: Various statistical approaches can be used to deal with unmeasured confounding when estimating treatment effects in observational studies, each with its own pros and cons. This study aimed to compare treatment effects as estimated by different statistical approaches for two interventions in observational stroke care data. PATIENTS AND METHODS: We used prospectively collected data from the MR CLEAN registry including all patients (n = 3279) with ischemic stroke who underwent endovascular treatment (EVT) from 2014 to 2017 in 17 Dutch hospitals. Treatment effects of two interventions - i.e., receiving an intravenous thrombolytic (IVT) and undergoing general anesthesia (GA) before EVT - on good functional outcome (modified Rankin Scale ≤2) were estimated. We used three statistical regression-based approaches that vary in assumptions regarding the source of unmeasured confounding: individual-level (two subtypes), ecological, and instrumental variable analyses. In the latter, the preference for using the interventions in each hospital was used as an instrument. RESULTS: Use of IVT (range 66-87%) and GA (range 0-93%) varied substantially between hospitals. For IVT, the individual-level (OR ~ 1.33) resulted in significant positive effect estimates whereas in instrumental variable analysis no significant treatment effect was found (OR 1.11; 95% CI 0.58-1.56). The ecological analysis indicated no statistically significant different likelihood (ß = - 0.002%; P = 0.99) of good functional outcome at hospitals using IVT 1% more frequently. For GA, we found non-significant opposite directions of points estimates the treatment effect in the individual-level (ORs ~ 0.60) versus the instrumental variable approach (OR = 1.04). The ecological analysis also resulted in a non-significant negative association (0.03% lower probability). DISCUSSION AND CONCLUSION: Both magnitude and direction of the estimated treatment effects for both interventions depend strongly on the statistical approach and thus on the source of (unmeasured) confounding. These issues should be understood concerning the specific characteristics of data, before applying an approach and interpreting the results. Instrumental variable analysis might be considered when unobserved confounding and practice variation is expected in observational multicenter studies.

Can We Cluster ICU Treatment Strategies for Traumatic Brain Injury by Hospital Treatment Preferences?

BACKGROUND: In traumatic brain injury (TBI), large between-center differences in treatment and outcome for patients managed in the intensive care unit (ICU) have been shown. The aim of this study is to explore if European neurotrauma centers can be clustered, based on their treatment preference in different domains of TBI care in the ICU. METHODS: Provider profiles of centers participating in the Collaborative European Neurotrauma Effectiveness Research in TBI study were used to assess correlations within and between the predefined domains: intracranial pressure monitoring, coagulation and transfusion, surgery, prophylactic antibiotics, and more general ICU treatment policies. Hierarchical clustering using Ward's minimum variance method was applied to group data with the highest similarity. Heat maps were used to visualize whether hospitals could be grouped to uncover types of hospitals adhering to certain treatment strategies. RESULTS: Provider profiles were available from 66 centers in 20 different countries in Europe and Israel. Correlations within most of the predefined domains varied from low to high correlations (mean correlation coefficients 0.2-0.7). Correlations between domains were lower, with mean correlation coefficients of 0.2. Cluster analysis showed that policies could be grouped, but hospitals could not be grouped based on their preference. CONCLUSIONS: Although correlations between treatment policies within domains were found, the failure to cluster hospitals indicates that a specific treatment choice within a domain is not a proxy for other treatment choices within or outside the domain. These results imply that studying the effects of specific TBI interventions on outcome can be based on between-center variation without being substantially confounded by other treatments. TRIAL REGISTRATION: We do not report the results of a health care intervention.

Rasch Analysis of Patient- and Parent-Reported Outcome Measures in the International Consortium for Health Outcomes Measurement Standard Set for Cleft Lip and Palate.

OBJECTIVES: The aim of this study was to evaluate the psychometric performance of the patient- and parent-reported measures in the International Consortium for Health Outcomes Measurement (ICHOM) Standard Set for Cleft Care, and to identify ways of improving concept coverage. METHODS: Data from 714 patients with cleft lip and/or palate, aged 8 to 9, 10 to 12.5, and 22 years were collected between November 2015 and April 2019 at Erasmus University Medical Center, Boston Children's Hospital, Duke Children's Hospital, and from participating sites in the CLEFT-Q Phase 3 study. The Standard Set includes 9 CLEFT-Q scales, the Nasal Obstruction Symptom Evaluation (NOSE) questionnaire, the Child Oral Health Impact Profile-Oral Symptoms Scale (COHIP-OSS), and the Intelligibility in Context Scale (ICS). Targeting, item-fit statistics, thresholds for item responses, and measurement precision (PSI) were analyzed using Rasch measurement theory. RESULTS: The proportion of the sample to score within each instruments range of measurement varied from 69% (ICS) to 92% (CLEFT-Q teeth and COHIP-OSS). Specific problems with individual items within the NOSE and COHIP-OSS questionnaires were noted, such as poor item fit to the Rasch model and disordered thresholds (6 of 10). Reliability measured with PSI was above 0.82 for the ICS and all but one CLEFT-Q scale (speech distress). PSIs were lowest for the COHIP-OSS (0.43) and NOSE questionnaire (0.35). CONCLUSION: The patient- and parent-reported components within the facial appearance, psychosocial function, and speech domains are valid measures; however, the facial function and oral health domains are not sufficiently covered by the CLEFT-Q eating and drinking, NOSE, and COHIP-OSS, and these questionnaires may not be accurate enough to stratify cleft-related outcomes.

Improving quality of stroke care through benchmarking center performance: why focusing on outcomes is not enough.

BACKGROUND: Between-center variation in outcome may offer opportunities to identify variation in quality of care. By intervening on these quality differences, patient outcomes may be improved. However, whether observed differences in outcome reflect the true quality improvement potential is not known for many diseases. Therefore, we aimed to analyze the effect of differences in performance on structure and processes of care, and case-mix on between-center differences in outcome after endovascular treatment (EVT) for ischemic stroke. METHODS: In this observational cohort study, ischemic stroke patients who received EVT between 2014 and 2017 in all 17 Dutch EVT-centers were included. Primary outcome was the modified Rankin Scale, ranging from 0 (no symptoms) to 6 (death), at 90 days. We used random effect proportional odds regression modelling, to analyze the effect of differences in structure indicators (center volume and year of admission), process indicators (time to treatment and use of general anesthesia) and case-mix, by tracking changes in tau2, which represents the amount of between-center variation in outcome. RESULTS: Three thousand two hundred seventy-nine patients were included. Performance on structure and process indicators varied significantly between EVT-centers (P < 0.001). Predicted probability of good functional outcome (modified Rankin Scale 0-2 at 90 days), which can be interpreted as an overall measure of a center's case-mix, varied significantly between 17 and 50% across centers. The amount of between-center variation (tau2) was estimated at 0.040 in a model only accounting for random variation. This estimate more than doubled after adding case-mix variables (tau2: 0.086) to the model, while a small amount of between-center variation was explained by variation in performance on structure and process indicators (tau2: 0.081 and 0.089, respectively). This indicates that variation in case-mix affects the differences in outcome to a much larger extent. CONCLUSIONS: Between-center variation in outcome of ischemic stroke patients mostly reflects differences in case-mix, rather than differences in structure or process of care. Since the latter two capture the real quality improvement potential, these should be used as indicators for comparing center performance. Especially when a strong association exists between those indicators and outcome, as is the case for time to treatment in ischemic stroke.

Value-based healthcare in ischemic stroke care: case-mix adjustment models for clinical and patient-reported outcomes.

BACKGROUND: Patient-Reported Outcome Measures (PROMs) have been proposed for benchmarking health care quality across hospitals, which requires extensive case-mix adjustment. The current study's aim was to develop and compare case-mix models for mortality, a functional outcome, and a patient-reported outcome measure (PROM) in ischemic stroke care. METHODS: Data from ischemic stroke patients, admitted to four stroke centers in the Netherlands between 2014 and 2016 with available outcome information (N = 1022), was analyzed. Case-mix adjustment models were developed for mortality, modified Rankin Scale (mRS) scores and EQ-5D index scores with respectively binary logistic, proportional odds and linear regression models with stepwise backward selection. Predictive ability of these models was determined with R-squared (R2) and area-under-the-receiver-operating-characteristic-curve (AUC) statistics. RESULTS: Age, NIHSS score on admission, and heart failure were the only common predictors across all three case-mix adjustment models. Specific predictors for the EQ-5D index score were sex (ß = 0.041), socio-economic status (ß = - 0.019) and nationality (ß = - 0.074). R2-values for the regression models for mortality (5 predictors), mRS score (9 predictors) and EQ-5D utility score (12 predictors), were respectively R2 = 0.44, R2 = 0.42 and R2 = 0.37. CONCLUSIONS: The set of case-mix adjustment variables for the EQ-5D at three months differed considerably from the set for clinical outcomes in stroke care. The case-mix adjustment variables that were specific to this PROM were sex, socio-economic status and nationality. These variables should be considered in future attempts to risk-adjust for PROMs during benchmarking of hospitals.

Regression Discontinuity Design: Simulation and Application in Two Cardiovascular Trials with Continuous Outcomes.

In epidemiology, the regression discontinuity design has received increasing attention recently and might be an alternative to randomized controlled trials (RCTs) to evaluate treatment effects. In regression discontinuity, treatment is assigned above a certain threshold of an assignment variable for which the treatment effect is adjusted in the analysis. We performed simulations and a validation study in which we used treatment effect estimates from an RCT as the reference for a prospectively performed regression discontinuity study. We estimated the treatment effect using linear regression adjusting for the assignment variable both as linear terms and restricted cubic spline and using local linear regression models. In the first validation study, the estimated treatment effect from a cardiovascular RCT was -4.0 mmHg blood pressure (95% confidence interval: -5.4, -2.6) at 2 years after inclusion. The estimated effect in regression discontinuity was -5.9 mmHg (95% confidence interval: -10.8, -1.0) with restricted cubic spline adjustment. Regression discontinuity showed different, local effects when analyzed with local linear regression. In the second RCT, regression discontinuity treatment effect estimates on total cholesterol level at 3 months after inclusion were similar to RCT estimates, but at least six times less precise. In conclusion, regression discontinuity may provide similar estimates of treatment effects to RCT estimates, but requires the assumption of a global treatment effect over the range of the assignment variable. In addition to a risk of bias due to wrong assumptions, researchers need to weigh better recruitment against the substantial loss in precision when considering a study with regression discontinuity versus RCT design.

Health-related quality of life in Guillain-Barré syndrome patients: a systematic review.

Guillain-Barré syndrome (GBS) encompasses a broad spectrum of health-related quality of life (HRQL) determinants, including mobility, fatigue, pain, and depression. We systematically reviewed the literature on functional outcome domains in which GBS patients experience limitations in the short and long terms and evaluated determinants of HRQL in GBS patients. MEDLINE and EMBASE were systematically searched by two independent reviewers for articles covering HRQL data of GBS patients. Of 730 abstracts screened, 17 articles covering data of 14 studies matched the selection criteria. The included articles showed that many GBS patients experienced physical limitations, even years after the acute phase of the disease, while results were inconsistent for perceived levels of pain, fatigue, and general mental well-being. Only three papers covered HRQL assessments at more than one time point, generally showing large improvements in HRQL in the first year after GBS onset, but not thereafter. We appraised the methodological quality of included studies using a 13-item checklist; none of the articles fulfilled all items and only seven articles presented data on correlations between HRQL and determinants. In conclusion, the majority of studies on HRQL in GBS patients are cross-sectional and of low methodological quality. This paper provides guidance for much needed high-quality studies on patterns of patient-perceived recovery after GBS onset.

Between-hospital variation in indicators of quality of care: a systematic review.

BACKGROUND: Efforts to mitigate unwarranted variation in the quality of care require insight into the 'level' (eg, patient, physician, ward, hospital) at which observed variation exists. This systematic literature review aims to synthesise the results of studies that quantify the extent to which hospitals contribute to variation in quality indicator scores. METHODS: Embase, Medline, Web of Science, Cochrane and Google Scholar were systematically searched from 2010 to November 2023. We included studies that reported a measure of between-hospital variation in quality indicator scores relative to total variation, typically expressed as a variance partition coefficient (VPC). The results were analysed by disease category and quality indicator type. RESULTS: In total, 8373 studies were reviewed, of which 44 met the inclusion criteria. Casemix adjusted variation was studied for multiple disease categories using 144 indicators, divided over 5 types: intermediate clinical outcomes (n=81), final clinical outcomes (n=35), processes (n=10), patient-reported experiences (n=15) and patient-reported outcomes (n=3). In addition to an analysis of between-hospital variation, eight studies also reported physician-level variation (n=54 estimates). In general, variation that could be attributed to hospitals was limited (median VPC=3%, IQR=1%-9%). Between-hospital variation was highest for process indicators (17.4%, 10.8%-33.5%) and lowest for final clinical outcomes (1.4%, 0.6%-4.2%) and patient-reported outcomes (1.0%, 0.9%-1.5%). No clear pattern could be identified in the degree of between-hospital variation by disease category. Furthermore, the studies exhibited limited attention to the reliability of observed differences in indicator scores. CONCLUSION: Hospital-level variation in quality indicator scores is generally small relative to residual variation. However, meaningful variation between hospitals does exist for multiple indicators, especially for care processes which can be directly influenced by hospital policy. Quality improvement strategies are likely to generate more impact if preceded by level-specific and indicator-specific analyses of variation, and when absolute variation is also considered. PROSPERO REGISTRATION NUMBER: CRD42022315850.

Value-Based Integrated Care: A Systematic Literature Review.

BACKGROUND: Healthcare services worldwide are transforming themselves into value-based organizations. Integrated care is an important aspect of value-based healthcare (VBHC), but practical evidence-based recommendations for the successful implementation of integrated care within a VBHC context are lacking. This systematic review aims to identify how value-based integrated care (VBIC) is defined in literature, and to summarize the literature regarding the effects of VBIC, and the facilitators and barriers for its implementation. METHODS: Embase, Medline ALL, Web of Science Core Collection, and Cochrane Central Register of Controlled Trails databases were searched from inception until January 2022. Empirical studies that implemented and evaluated an integrated care intervention within a VBHC context were included. Non-empirical studies were included if they described either a definition of VBIC or facilitators and barriers for its implementation. Theoretical articles and articles without an available full text were excluded. All included articles were analysed qualitatively. The Rainbow Model of Integrated Care (RMIC) was used to analyse the VBIC interventions. The quality of the articles was assessed using the Mixed Methods Appraisal Tool (MMAT). RESULTS: After screening 1328 titles/abstract and 485 full-text articles, 24 articles were included. No articles were excluded based on quality. One article provided a definition of VBIC. Eleven studies reported-mostly positive- effects of VBIC, on clinical outcomes, patient-reported outcomes, and healthcare utilization. Nineteen studies reported facilitators and barriers for the implementation of VBIC; factors related to reimbursement and information technology (IT) infrastructure were reported most frequently. CONCLUSION: The concept of VBIC is not well defined. The effect of VBIC seems promising, but the exact interpretation of effect evaluations is challenged by the precedence of multicomponent interventions, multiple testing and generalizability issues. For successful implementation of VBIC, it is imperative that healthcare organizations consider investing in adequate IT infrastructure and new reimbursement models. Systematic Review Registration: PROSPERO (CRD42021259025).

Variation Between Hospitals in Outcomes and Costs of IBD Care: Results From the IBD Value Study.

BACKGROUND: Data on variation in outcomes and costs of the treatment of inflammatory bowel disease (IBD) can be used to identify areas for cost and quality improvement. It can also help healthcare providers learn from each other and strive for equity in care. We aimed to assess the variation in outcomes and costs of IBD care between hospitals. METHODS: We conducted a 12-month cohort study in 8 hospitals in the Netherlands. Patients with IBD who were treated with biologics and new small molecules were included. The percentage of variation in outcomes (following the International Consortium for Health Outcomes Measurement standard set) and costs attributable to the treating hospital were analyzed with intraclass correlation coefficients (ICCs) from case mix-adjusted (generalized) linear mixed models. RESULTS: We included 1010 patients (median age 45 years, 55% female). Clinicians reported high remission rates (83%), while patient-reported rates were lower (40%). During the 12-month follow-up, 5.2% of patients used prednisolone for more than 3 months. Hospital costs (outpatient, inpatient, and medication costs) were substantial (median: €8323 per 6 months), mainly attributed to advanced therapies (€6611). Most of the variation in outcomes and costs among patients could not be attributed to the treating hospitals, with ICCs typically between 0% and 2%. Instead, patient-level characteristics, often with ICCs above 50%, accounted for these variations. CONCLUSIONS: Variation in outcomes and costs cannot be used to differentiate between hospitals for quality of care. Future quality improvement initiatives should look at differences in structure and process measures of care and implement patient-level interventions to improve quality of IBD care. TRIAL REGISTRATION NUMBER: NL8276.

Variation in outcomes and costs cannot be used to differentiate between hospitals for quality of inflammatory bowel disease care. Future quality improvement initiatives should look at differences in structure and process measures and implement patient-level interventions to improve quality of inflammatory bowel disease care.

Optimizing the Psychosocial Function Measures in the International Consortium for Health Outcomes Measurement Standard Set for Cleft.

BACKGROUND: To ensure the feasibility of implementing PROMs in clinical practice, they must be continually appraised for undue burden placed on patients and clinicians and their usefulness for decision-making. This study assesses correlations between the CLEFT-Q psychosocial scales in the International Consortium for Health Outcomes Measurement Standard Set for cleft and explores their associations with patient characteristics and psychosocial care referral. METHODS: Spearman correlation coefficients were calculated for CLEFT-Q psychological function, social function, school function, face, speech function, and speech-related distress scales. Logistic regressions were used to assess the association of cleft phenotype, syndrome, sex, and adoption status on scale scores and clinical referral to psychosocial care for further evaluation and management. RESULTS: Data were obtained from 3067 patients with cleft lip and/or palate at three centers. Strong correlations were observed between social function and psychological function (r > 0.69) and school function (r > 0.78) scales. Correlation between school function and psychological function scales was lower (r = 0.59 to 0.68). Genetic syndrome (OR, 2.37; 95% CI, 1.04 to 5.41), psychological function (OR, 0.92; 95% CI, 0.88 to 0.97), school function (OR, 0.94; 95% CI, 0.90 to 0.98), and face (OR, 0.96; 95% CI, 0.94 to 0.98) were significant predictors for referral to psychosocial care. CONCLUSIONS: Because social function as measured by the CLEFT-Q showed strong correlations with both school and psychological function, its additional value for measuring psychosocial function within the Standard Set is limited, and it is reasonable to consider removing this scale from the International Consortium for Health Outcomes Measurement Standard Set for cleft.

Validity of the self-administered comorbidity questionnaire in patients with inflammatory bowel disease.

Background: The International Consortium for Health Outcomes Measurement has selected the self-administered comorbidity questionnaire (SCQ) to adjust case-mix when comparing outcomes of inflammatory bowel disease (IBD) treatment between healthcare providers. However, the SCQ has not been validated for use in IBD patients. Objectives: We assessed the validity of the SCQ for measuring comorbidities in IBD patients. Design: Cohort study. Methods: We assessed the criterion validity of the SCQ for IBD patients by comparing patient-reported and clinician-reported comorbidities (as noted in the electronic health record) of the 13 diseases of the SCQ using Cohen's kappa. Construct validity was assessed using the Spearman correlation coefficient between the SCQ and the Charlson Comorbidity Index (CCI), clinician-reported SCQ, quality of life, IBD-related healthcare and productivity costs, prevalence of disability, and IBD disease activity. We assessed responsiveness by correlating changes in the SCQ with changes in healthcare costs, productivity costs, quality of life, and disease activity after 15 months. Results: We included 613 patients. At least fair agreement (κ > 0.20) was found for most comorbidities, but the agreement was slight (κ < 0.20) for stomach disease [κ = 0.19, 95% CI (-0.03; 0.41)], blood disease [κ = 0.02, 95% CI (-0.06; 0.11)], and back pain [κ = 0.18, 95% CI (0.11; 0.25)]. Correlations were found between the SCQ and the clinician-reported SCQ [ρ = 0.60, 95% CI (0.55; 0.66)], CCI [ρ = 0.39, 95% CI (0.31; 0.45)], the prevalence of disability [ρ = 0.23, 95% CI (0.15; 0.32)], and quality of life [ρ = -0.30, 95% CI (-0.37; -0.22)], but not between the SCQ and healthcare or productivity costs or disease activity (|ρ| ⩽ 0.2). A change in the SCQ after 15 months was not correlated with a change in any of the outcomes. Conclusion: The SCQ is a valid tool for measuring comorbidity in IBD patients, but face and content validity should be improved before being used to correct case-mix differences.

Disentangling the Association Between Neurologic Deficits, Patient-Reported Impairments, and Quality of Life After Ischemic Stroke.

BACKGROUND AND OBJECTIVES: The EuroQol Group 5-Dimension Self-Reported Questionnaire (EQ-5D) is a well-established instrument to assess quality of life and generates generic utility values for health states reported by patients, derived from assessments by the general public. We hypothesized that language problems and other nonmotor deficits are not captured as well as motor deficits by this system. We aimed to quantify the association between disabling neurologic deficits and the EQ-5D dimension scores and the utility score in patients with ischemic stroke. METHODS: We used data of the Interventional Management of Stroke III trial. Missing data were imputed by multiple imputation. The association between neurologic deficits (individual NIH Stroke Scale [NIHSS] item scores) and the EQ-5D-3L (5 three-level dimension scores and utility score) at 90 days was assessed with ordinal logistic regression and Tobit regression, respectively. The explained variance of each model was estimated with Nagelkerke pseudo-R2 or R2. RESULTS: In total, 525 surviving patients were included. Complete data on both the NIHSS and EQ-5D were available for 481/525 (91.6%) patients. At 90 days, 161/491 (32.8%) patients had aphasia and 226/491 (46.0%) patients had paresis of at least 1 limb. Limb paresis, facial palsy, sensory loss, and dysarthria explained most of the variance in all EQ-5D dimension scores and the utility score. In the utility score, 8.9% of the variance was explained by neglect, 10.0% by aphasia, 10.8% by hemianopia, and 17.5%-24.1% by limb paresis. DISCUSSION: The impact of neurologic deficits on the EQ-5D in patients with ischemic stroke is mostly due to limb paresis, while the EQ-5D is less sensitive to other nonmotor deficits such as hemianopia, aphasia, and neglect. This may lead to overestimation of quality of life and, consequently, underestimation of the (cost-)effectiveness of treatments and interventions. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov. Unique identifier: NCT00359424.

Intramural Healthcare Consumption and Costs After Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study.

Traumatic brain injury (TBI) is a global public health problem and a leading cause of mortality, morbidity, and disability. The increasing incidence combined with the heterogeneity and complexity of TBI will inevitably place a substantial burden on health systems. These findings emphasize the importance of obtaining accurate and timely insights into healthcare consumption and costs on a multi-national scale. This study aimed to describe intramural healthcare consumption and costs across the full spectrum of TBI in Europe. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) core study is a prospective observational study conducted in 18 countries across Europe and in Israel. The baseline Glasgow Coma Scale (GCS) was used to differentiate patients by brain injury severity in mild (GCS 13-15), moderate (GCS 9-12), or severe (GCS ≤8) TBI. We analyzed seven main cost categories: pre-hospital care, hospital admission, surgical interventions, imaging, laboratory, blood products, and rehabilitation. Costs were estimated based on Dutch reference prices and converted to country-specific unit prices using gross domestic product (GDP)-purchasing power parity (PPP) adjustment. Mixed linear regression was used to identify between-country differences in length of stay (LOS), as a parameter of healthcare consumption. Mixed generalized linear models with gamma distribution and log link function quantified associations of patient characteristics with higher total costs. We included 4349 patients, of whom 2854 (66%) had mild, 371 (9%) had moderate, and 962 (22%) had severe TBI. Hospitalization accounted for the largest part of the intramural consumption and costs (60%). In the total study population, the mean LOS was 5.1 days at the intensive care unit (ICU) and 6.3 days at the ward. For mild, moderate, and severe TBI, mean LOS was, respectively, 1.8, 8.9, and 13.5 days at the ICU and 4.5, 10.1, and 10.3 days at the ward. Other large contributors to the total costs were rehabilitation (19%) and intracranial surgeries (8%). Total costs increased with higher age and greater trauma severity (mild; €3,800 [IQR €1,400-14,000], moderate; €37,800 [IQR €14,900-€74,200], severe; €60,400 [IQR €24,400-€112,700]). The adjusted analysis showed that female patients had lower costs than male patients (odds ratio (OR) 0.80 [CI 0.75-1.85]). Increasing TBI severity was associated with higher costs, OR 1.46 (confidence interval [CI] 1.31-1.63) and OR 1.67 [CI 1.52-1.84] for moderate and severe patients, respectively. A worse pre-morbid overall health state, increasing age and more severe systemic trauma, expressed in the Injury Severity Score (ISS), were also significantly associated with higher costs. Intramural costs of TBI are significant and are profoundly driven by hospitalization. Costs increased with trauma severity and age, and male patients incurred higher costs. Reducing LOS could be targeted with advanced care planning, in order to provide cost-effective care.

Handling missing values in the analysis of between-hospital differences in ordinal and dichotomous outcomes: a simulation study.

Missing data are frequently encountered in registries that are used to compare performance across hospitals. The most appropriate method for handling missing data when analysing differences in outcomes between hospitals with a generalised linear mixed model is unclear. We aimed to compare methods for handling missing data when comparing hospitals on ordinal and dichotomous outcomes. We performed a simulation study using data from the Multicentre Randomised Controlled Trial of Endovascular Treatment for Acute Ischaemic Stroke in the Netherlands (MR CLEAN) Registry, a prospective cohort study in 17 hospitals performing endovascular therapy for ischaemic stroke in the Netherlands. The investigated methods for handling missing data, both case-mix adjustment variables and outcomes, were complete case analysis, single imputation, multiple imputation, single imputation with deletion of imputed outcomes and multiple imputation with deletion of imputed outcomes. Data were generated as missing completely at random (MCAR), missing at random and missing not at random (MNAR) in three scenarios: (1) 10% missing data in case-mix and outcome; (2) 40% missing data in case-mix and outcome; and (3) 40% missing data in case-mix and outcome with varying degree of missing data among hospitals. Bias and reliability of the methods were compared on the mean squared error (MSE, a summary measure combining bias and reliability) relative to the hospital effect estimates from the complete reference data set. For both the ordinal outcome (ie, the modified Rankin Scale) and a common dichotomised version thereof, all methods of handling missing data were biased, likely due to shrinkage of the random effects. The MSE of all methods was on average lowest under MCAR and with fewer missing data, and highest with more missing data and under MNAR. The 'multiple imputation, then deletion' method had the lowest MSE for both outcomes under all simulated patterns of missing data. Thus, when estimating hospital effects on ordinal and dichotomous outcomes in the presence of missing data, the least biased and most reliable method to handle these missing data is 'multiple imputation, then deletion'.

Validity of Early Outcomes as Indicators for Comparing Hospitals on Quality of Stroke Care.

Background Insight into outcome variation between hospitals could help to improve quality of care. We aimed to assess the validity of early outcomes as quality indicators for acute ischemic stroke care for patients treated with endovascular therapy (EVT). Methods and Results We used data from the MR CLEAN (Multicenter Randomized Controlled Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) Registry, a large multicenter prospective cohort study including 3279 patients with acute ischemic stroke undergoing EVT. Random effect linear and proportional odds regression were used to analyze the effect of case mix on between-hospital differences in 2 early outcomes: the National Institutes of Health Stroke Scale (NIHSS) score at 24 to 48 hours and the expanded thrombolysis in cerebral infarction score. Between-hospital variation in outcomes was assessed using the variance of random hospital effects (tau2). In addition, we estimated the correlation between hospitals' EVT-patient volume and (case-mix-adjusted) outcomes. Both early outcomes and case-mix characteristics varied significantly across hospitals. Between-hospital variation in the expanded thrombolysis in cerebral infarction score was not influenced by case-mix adjustment (tau 2=0.17 in both models). In contrast, for the NIHSS score at 24 to 48 hours, case-mix adjustment led to a decrease in variation between hospitals (tau 2 decreases from 0.19 to 0.17). Hospitals' EVT-patient volume was strongly correlated with higher expanded thrombolysis in cerebral infarction scores (r=0.48) and weakly with lower NIHSS score at 24 to 48 hours (r=0.15). Conclusions Between-hospital variation in NIHSS score at 24 to 48 hours is significantly influenced by case-mix but not by patient volume. In contrast, between-hospital variation in expanded thrombolysis in cerebral infarction score is strongly influenced by EVT-patient volume but not by case-mix. Both outcomes may be suitable for comparing hospitals on quality of care, provided that adequate adjustment for case-mix is applied for NIHSS score.

Effect of Treatment in a Specialized Pediatric Hemato-Oncology Setting on 5-Year Survival in Acute Lymphoblastic Leukemia: A Quasi-Experimental Study.

Survival rates of adolescents and young adults (AYAs) with acute lymphoblastic leukemia (ALL) are inferior to those of pediatric ALL patients. In part, this may be caused by differences in treatment setting. Generally, children are treated in specialized pediatric hemato-oncology settings, whereas AYAs are treated in adult hemato-oncology settings. Since 2005, adult treatment protocols have included pediatric-inspired chemotherapy, which has been the standard of care for AYAs from 2008 onwards. This study aims to assess whether, despite protocols in both settings having become more similar, there remains an effect of treatment in specialized pediatric hemato-oncology settings on 5-year survival for ALL patients in the Netherlands. We used nationwide registry data (2004-2013) on 472 ALL patients aged between 10 and 30 years old. A fuzzy regression discontinuity design was applied to estimate the treatment effect using two-stage least squares regression with the treatment threshold at 17 years and 7 months of age, adjusting for sex, age at diagnosis, and immunophenotype. We found a risk difference of 0.419 (p = 0.092; 95% CI = -0.0686; 0.907), meaning a 41.9 percentage point greater probability of surviving five years after diagnosis for ALL patients treated in specialized pediatric hemato-oncology settings. Our results suggest that ALL patients around the threshold could benefit from increased collaboration between pediatric and adult hemato-oncology in terms of survival.