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.

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'.

Factors Influencing the Introduction of Value-Based Payment in Integrated Stroke Care: Evidence from a Qualitative Case Study.

Background: To address issues related to suboptimal insight in outcomes, fragmentation, and increasing costs, stakeholders are experimenting with value-based payment (VBP) models, aiming to facilitate high-value integrated care. However, insight in how, why and under what circumstances such models can be successful is limited. Drawing upon realist evaluation principles, this study identifies context factors and associated mechanisms influencing the introduction of VBP in stroke care. Methods: Existing knowledge on context-mechanism relations impacting the introduction of VBP programs (in real-world settings) was summarized from literature. These relations were then tested, refined, and expanded based on a case study comprising interviews with representatives from organizations involved in the introduction of a VBP model for integrated stroke care in Rotterdam, the Netherlands. Results: Facilitating factors were pre-existing trust-based relations, shared dissatisfaction with the status quo, regulatory compatibility and simplicity of the payment contract, gradual introduction of down-side risk for providers, and involvement of a trusted third party for data management. Yet to be addressed barriers included friction between short- and long-term goals within and among organizations, unwillingness to forgo professional and organizational autonomy, discontinuity in resources, and limited access to real-time data for improving care delivery processes. Conclusions: Successful payment and delivery system reform require long-term commitment from all stakeholders stretching beyond the mere introduction of new models. Careful consideration of creating the 'right' contextual circumstances remains crucially important, which includes willingness among all involved providers to bear shared financial and clinical responsibility for the entire care chain, regardless of where care is provided.

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.

Predictable profits and losses in a health insurance market with risk equalization: A multiple-contract period perspective.

Many social health insurance systems rely on 'regulated competition' among insurers to improve efficiency. In the presence of community-rated premiums, risk equalization is an important regulatory feature to mitigate risk-selection incentives in such systems. Empirical studies evaluating selection incentives have typically quantified group-level (un)profitability for one contract period. However, due to switching barriers, a multiple contract period perspective might be more relevant. In this paper, using data from a large health survey (N≈380k) we identify subgroups of chronically ill and healthy individuals in year t and follow these groups over three consecutive years. Using administrative data covering the entire Dutch population (N≈17m), we then simulate the mean per person predictable profits and losses (i.e. spending predicted by a sophisticated risk-equalization model minus actual spending) of these groups over the three follow-up years. We find that most of the groups of chronically ill are persistently unprofitable on average, while the healthy group is persistently profitable. This implies that selection incentives might be stronger than initially thought, underscoring the necessity of eliminating predictable profits and losses for the adequate functioning of competitive social health insurance markets.

Continuous vital sign monitoring in patients after elective abdominal surgery: a retrospective study on clinical outcomes and costs.

Aim: To assess changes in outcomes and costs upon implementation of continuous vital sign monitoring in postsurgical patients. Materials & methods: Retrospective analysis of clinical outcomes and in-hospital costs compared with a control period. Results: During the intervention period patients were less frequently admitted to the intensive care unit (ICU) (p = 0.004), had shorter length of stay (p < 0.001) and lower costs (p < 0.001). The intervention was associated with a lower odds of ICU admission (odds ratio: 0.422; p = 0.007) and ICU related costs (odds ratio: -662.4; p = 0.083). Conclusion: Continuous vital sign monitoring may have contributed to fewer ICU admissions and lower ICU costs in postsurgical patients.

Financial risk allocation and provider incentives in hospital-insurer contracts in The Netherlands.

In healthcare systems with a purchaser-provider split, contracts are an important tool to define the conditions for the provision of healthcare services. Financial risk allocation can be used in contracts as a mechanism to influence provider behavior and stimulate providers to provide efficient and high-quality care. In this paper, we provide new insights into financial risk allocation between insurers and hospitals in a changing contracting environment. We used unique nationwide data from 901 hospital-insurer contracts in The Netherlands over the years 2013, 2016, and 2018. Based on descriptive and regression analyses, we find that hospitals were exposed to more financial risk over time, although this increase was somewhat counteracted by an increasing use of risk-mitigating measures between 2016 and 2018. It is likely that this trend was heavily influenced by national cost control agreements. In addition, alternative payment models to incentivize value-based health care were rarely used and thus seemingly of lower priority, despite national policies being explicitly directed at this goal. Finally, our analysis shows that hospital and insurer market power were both negatively associated with financial risk for hospitals. This effect becomes stronger if both hospital and insurer have strong market power, which in this case may indicate a greater need to reduce (financial) uncertainties and to create more cooperative relationships.

Between-Hospital and Between-Physician Variation in Outcomes and Costs in High- and Low-Complex Surgery: A Nationwide Multilevel Analysis.

OBJECTIVES: Clinicians and policy makers are increasingly exploring strategies to reduce unwarranted variation in outcomes and costs. Adequately accounting for case mix and better insight into the levels at which variation exists is crucial for such strategies. This nationwide study investigates variation in surgical outcomes and costs at the level of hospitals and individual physicians and evaluates whether these can be reliably compared on performance. METHODS: Variation was analyzed using 92 330 patient records collected from 62 Dutch hospitals who underwent surgery for colorectal cancer (n = 6640), urinary bladder cancer (n = 14 030), myocardial infarction (n = 31 870), or knee osteoarthritis (n = 39 790) in the period 2018 to 2019. Multilevel regression modeling with and without case-mix adjustment was used to partition variation in between-hospital and between-physician components for in-hospital mortality, intensive care unit admission, length of stay, 30-day readmission, 30-day reintervention, and in-hospital costs. Reliability was calculated for each treatment-outcome combination at both levels. RESULTS: Across outcomes, hospital-level variation relative to total variation ranged between ≤ 1% and 15%, and given the high caseloads, this typically yielded high reliability (> 0.9). In contrast, physician-level variation components were typically ≤ 1%, with limited opportunities to make reliable comparisons. The impact of case-mix adjustment was limited, but nonnegligible. CONCLUSIONS: It is not typically possible to make reliable comparisons among physicians due to limited partitioned variation and low caseloads. Nevertheless, for hospitals, the opposite often holds. Although variation-reduction efforts directed at hospitals are thus more likely to be successful, this should be approached cautiously, partly because level-specific variation and the impact of case mix vary considerably across treatments and outcomes.

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.

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.

Prediction Models for Future High-Need High-Cost Healthcare Use: a Systematic Review.

BACKGROUND: In an effort to improve both quality of care and cost-effectiveness, various care-management programmes have been developed for high-need high-cost (HNHC) patients. Early identification of patients at risk of becoming HNHC (i.e. case finding) is crucial to a programme's success. We aim to systematically identify prediction models predicting future HNHC healthcare use in adults, to describe their predictive performance and to assess their applicability. METHODS: Ovid MEDLINE® All, EMBASE, CINAHL, Web of Science and Google Scholar were systematically searched from inception through January 31, 2021. Risk of bias and methodological quality assessment was performed through the Prediction model Risk Of Bias Assessment Tool (PROBAST). RESULTS: Of 5890 studies, 60 studies met inclusion criteria. Within these studies, 313 unique models were presented using a median development cohort size of 20,248 patients (IQR 5601-174,242). Predictors were derived from a combination of data sources, most often claims data (n = 37; 62%) and patient survey data (n = 29; 48%). Most studies (n = 36; 60%) estimated patients' risk to become part of some top percentage of the cost distribution (top-1-20%) within a mean time horizon of 16 months (range 12-60). Five studies (8%) predicted HNHC persistence over multiple years. Model validation was performed in 45 studies (76%). Model performance in terms of both calibration and discrimination was reported in 14 studies (23%). Overall risk of bias was rated as 'high' in 40 studies (67%), mostly due to a 'high' risk of bias in the subdomain 'Analysis' (n = 37; 62%). DISCUSSION: This is the first systematic review (PROSPERO CRD42020164734) of non-proprietary prognostic models predicting HNHC healthcare use. Meta-analysis was not possible due to heterogeneity. Most identified models estimated a patient's risk to incur high healthcare expenditure during the subsequent year. However, case-finding strategies for HNHC care-management programmes are best informed by a model predicting HNHC persistence. Therefore, future studies should not only focus on validating and extending existing models, but also concentrate on clinical usefulness.

Performance feedback on the quality of care in hospitals performing thrombectomy for ischemic stroke (PERFEQTOS): protocol of a stepped wedge cluster randomized trial.

BACKGROUND: Although the provision of performance feedback to healthcare professionals based on data from quality registries is common practice in many fields of medicine, observational studies of its effect on the quality of care have shown mixed results. The objective of this study is to evaluate the effect of performance feedback on the quality of care for acute ischemic stroke. METHODS: PERFEQTOS is a stepped wedge cluster randomized trial in 13 hospitals in the Netherlands providing endovascular thrombectomy for ischemic stroke. The primary outcome is the hospital's door-to-groin time. The study starts with a 6-month period in which none of the hospitals receives the performance feedback intervention. Subsequently, every 6 months, three or four hospitals are randomized to cross over from the control to the intervention conditions, until all hospitals receive the feedback intervention. The feedback intervention consists of a dashboard with quarterly reports on patient characteristics, structure, process, and outcome indicators related to patients with ischemic stroke treated with endovascular thrombectomy. Hospitals can compare their present performance with their own performance in the past and with other hospitals. The performance feedback is provided to local quality improvement teams in each hospital, who define their own targets on specific indicators and develop performance improvement plans. The impact of the performance feedback and improvement plans will be evaluated by comparing the primary outcome before and after the intervention. DISCUSSION: This study will provide evidence on the effectiveness of performance feedback to healthcare providers. The results will be actively disseminated through peer-reviewed journals, conference presentations, and various stakeholder engagement activities. TRIAL REGISTRATION: Netherlands Trial Register NL9090 . Registered on December 3, 2020.

Facilitators and barriers for implementing patient-reported outcome measures in clinical care: An academic center's initial experience.

Objectives The aim of this study was to explore the perspectives of healthcare providers and researchers in a large academic hospital on facilitators and barriers for implementing patient-reported outcome measures (PROMs) in clinical care. Methods A customized web-based questionnaire was developed and disseminated to healthcare providers and researchers across multiple medical departments involved in a value-based health care initiative in the hospital. Questionnaire statements were rated using a 5-point Likert scale ranging from "strongly agree" to "strongly disagree". In addition, 8 open-ended questions were included allowing respondents to mention additional facilitators and barriers for implementing PROMs. Descriptive statistics were used to summarize the results. Results In total, 61 participants from both surgical and non-surgical departments completed the survey. Most respondents (51%) were medical specialists and the median employment duration was 14 years. Frequently reported facilitators were the presence of a PROM coordinator in the (outpatient) clinic (85%), the integration of PROMs in the electronic health record (81%), and the intrinsic motivation of members involved in the implementation (N=9 open responses). Commonly reported barriers were language barriers (76%), IT issues (N=17 open responses), and time constraints (N=14 open responses). Conclusions For the successful implementation of PROMs in clinical practice, it is imperative that healthcare organizations consider supporting motivated healthcare professionals, involving PROMs coordinators, and investing in an adequate IT infrastructure, and removal of language barriers.

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.

Selection Incentives for Health Insurers in the Presence of Sophisticated Risk Adjustment.

This article analyzes selection incentives for insurers in the Dutch basic health insurance market, which operates with community-rated premiums and sophisticated risk adjustment. Selection incentives result from the interplay of three market characteristics: possible actions by insurers, consumer response to these actions, and predictable variation in profitability of insurance contracts. After a qualitative analysis of the first two characteristics our primary objective is to identify the third. Using a combination of claims data (N = 16.8 million) and survey information (N = 387,195), we find substantial predictable variation in profitability. On average, people in good health are profitable, while those in poor health are unprofitable. We conclude that Dutch insurers indeed face selection incentives. A complete measure of selection incentives, however, captures the correlation between individual-level profitability and consumer response to insurer-actions. Obtaining insight in this correlation is an important direction for further research.

Value-Based Provider Payment Initiatives Combining Global Payments With Explicit Quality Incentives: A Systematic Review.

An essential element in the pursuit of value-based health care is provider payment reform. This article aims to identify and analyze payment initiatives comprising a specific manifestation of value-based payment reform that can be expected to contribute to value in a broad sense: (a) global base payments combined with (b) explicit quality incentives. We conducted a systematic review of the literature, consulting four scientific bibliographic databases, reference lists, the Internet, and experts. We included and compared 18 initiatives described in 111 articles/documents on key design features and impact on value. The initiatives are heterogeneous regarding the operationalization of the two payment components and associated design features. Main commonalities between initiatives are a strong emphasis on primary care, the use of "virtual" spending targets, and the application of risk adjustment and other risk-mitigating measures. Evaluated initiatives generally show promising results in terms of lower spending growth with equal or improved quality.

Value-based provider payment: towards a theoretically preferred design.

Worldwide, policymakers and purchasers are exploring innovative provider payment strategies promoting value in health care, known as value-based payments (VBP). What is meant by 'value', however, is often unclear and the relationship between value and the payment design is not explicated. This paper aims at: (1) identifying value dimensions that are ideally stimulated by VBP and (2) constructing a framework of a theoretically preferred VBP design. Based on a synthesis of both theoretical and empirical studies on payment incentives, we conclude that VBP should consist of two components: a relatively large base payment that implicitly stimulates value and a relatively small payment that explicitly rewards measurable aspects of value (pay-for-performance). Being the largest component, the base payment design is essential, but often neglected when it comes to VBP reform. We explain that this base payment ideally (1) is paid to a multidisciplinary provider group (2) for a cohesive set of care activities for a predefined population, (3) is fixed, (4) is adjusted for the population's risk profile and (5) includes risk-mitigating measures. Finally, some important trade-offs in the practical operationalisation of VBP are discussed.

Risk equalization in competitive health insurance markets: Identifying healthy individuals on the basis of multiple-year low spending.

OBJECTIVE: To study the extent to which risk equalization (RE) in competitive health insurance markets can be improved by including an indicator for being healthy. STUDY SETTING/DATA SOURCES: This study is conducted in the context of the Dutch individual health insurance market. Administrative data on spending and risk characteristics (2011-2014) for the entire population (N = 16.6 m) as well as health survey data from a large sample (N = 387 k) are used. STUDY DESIGN: The indicator for being healthy is low spending in three consecutive prior years. "Low spending" is defined in three ways: belonging to the bottom 60%, 70%, or 80% of the annual spending distribution. Versions of the Dutch RE model 2017 with and without the indicator are compared on individual-level payment fit and, using the survey data, group-level payment fit. PRINCIPAL FINDINGS: All three alternative models outperform the Dutch RE model 2017. However, significant unpriced risk heterogeneity remains. Compared with the 60% threshold, the 80% threshold comes with a larger improvement in fit but identifies a less selective group. CONCLUSIONS: The performance of the RE model can be improved by adding an indicator for being healthy based on multiple-year low spending. However, risk-selection potential remains, warranting high priority to further improvement of RE.

Improving risk equalization using information on physiotherapy diagnoses.

BACKGROUND: Worldwide, risk-equalization (RE) models in competitive health insurance markets have evolved from simple demographic models to sophisticated models containing diagnosis and pharmacy-based indicators of health. However, these models still have important imperfections; adding information on (diagnoses of) physiotherapy treatment may further improve RE-models. Therefore, a new risk-adjuster based on physiotherapy costs in the prior year was introduced in the Dutch RE-model of 2016. METHODS: Physiotherapy claims-data (2012) and administrative data on costs and risk-characteristics (2013) for 94% of the Dutch population (N = 15.8 million) are used to evaluate the current risk-adjuster based on physiotherapy costs and to assess the effects of replacing it by different modalities of a risk-adjuster based on physiotherapy diagnoses. Of the 89 diagnoses in the claims-data, 62 are dropped because they relate to temporary health problems. The 27 retained diagnoses are added to the Dutch model in 4 modalities: 27 separate risk-classes, 9 diagnosis-clusters based on main pathology category, 4 diagnosis-clusters based on residual costs, and the 4 clusters of modality 3 interacted with age. RESULTS: Although the cost-based risk-adjuster improves the model's predictive power and removes the average undercompensation (€919) for enrollees with physiotherapy costs in the prior year, it is outperformed by all 4 diagnosis-based modalities. Of these modalities, modality 3 is preferred based on its simplicity and comparable predictive power. CONCLUSIONS: Adding information on physiotherapy can further improve the performance of sophisticated RE-models. Regarding the Dutch model, a risk-adjuster containing 4 risk-classes for clustered diagnoses based on residual costs is the preferred modality.

Diagnosis-based Cost Groups in the Dutch Risk-equalization Model: Effects of Clustering Diagnoses and of Allowing Patients to be Classified into Multiple Risk-classes.

BACKGROUND: The risk-equalization (RE) model in the Dutch health insurance market has evolved to a sophisticated model containing direct proxies for health. However, it still has important imperfections, leaving incentives for risk selection. This paper focuses on refining an important health-based risk-adjuster in this model: the diagnosis-based costs groups (DCGs). The current (2017) DCGs are calibrated on "old" data of 2011/2012, are mutually exclusive, and are essentially clusters of about 200 diagnosis-groups ("dxgroups"). METHODS: Hospital claims data (2013), administrative data (2014) on costs and risk-characteristics for the entire Dutch population (N≈16.9 million), and health survey data (2012, N≈387,000) are used. The survey data are used to identify subgroups of individuals in poor or in good health. The claims and administrative data are used to develop alternative DCG-modalities to examine the impact on individual-level and group-level fit of recalibrating the DCGs based on new data, of allowing patients to be classified in multiple DCGs, and of refraining from clustering. RESULTS: Recalibrating the DCGs and allowing enrolees to be classified into multiple DCGs lead to nontrivial improvements in individual-level and group-level fit (especially for cancer patients and people with comorbid conditions). The improvement resulting from refraining from clustering does not seem to justify the increase in model complexity this would entail. CONCLUSIONS: The performance of the sophisticated Dutch RE-model can be improved by allowing classification in multiple (clustered) DCGs and using new data. Irrespective of the modality used, however, various subgroups remain significantly undercompensated. Further improvement of the RE-model merits high priority.