Steering them softly with a quality label? A case study analysis of a patient channelling strategy without financial incentives.

Steering patients to lower priced and/or higher quality providers can increase the value of a healthcare system. In a managed care setting, health insurers may use financial incentives for this purpose. However, introducing cost-sharing differences among providers may cause enrolee discontent, which may result in disenrollment. Simply informing and guiding enrolees to preferred providers without financial incentives may therefore be an attractive alternative for insurers. But the effectiveness of such a soft channelling strategy is unclear. This paper investigates whether a Dutch health insurer's strategy of designating preferred hospitals for breast cancer surgery and for inguinal hernia repair affected its enrolees' hospital choices. In October 2008, preferred hospitals received a quality label ('TopCare') because of their high-quality performances in previous years. The insurer recommended these hospitals to enrolees without a financial incentive. Individual patient-level claims data from the insurer over a 5-year period (2006-2010) and a conditional logit choice model was used. Our study samples for breast cancer surgery and inguinal hernia repair included 7985 and 17,292 patients, respectively. It is found that for both procedures, patients ex ante already had a certain preference for the hospitals designated by the insurer as top-quality providers, even when considering possible additional travel time. Also, for both procedures, patient choice did not differ significantly before and after the launch of the TopCare label. The quality label did not increase patient demand for preferred hospitals. Thus, the insurer's strategy to steer patients to preferred hospital alternatives without a financial incentive was not effective.

Health service planning to assess the expected impact of centralising specialist cancer services on travel times, equity, and outcomes: a national population-based modelling study.

BACKGROUND: Centralisation of specialist cancer services is occurring in many countries, often without evaluating the potential impact before implementation. We developed a health service planning model that can estimate the expected impacts of different centralisation scenarios on travel time, equity in access to services, patient outcomes, and hospital workload, using rectal cancer surgery as an example. METHODS: For this population-based modelling study, we used routinely collected individual patient-level data from the National Cancer Registration and Analysis Service (NCRAS) and linked to the NHS Hospital Episode Statistics (HES) database for 11 888 patients who had been diagnosed with rectal cancer between April 1, 2016, and Dec 31, 2018, and who subsequently underwent a major rectal cancer resection in 163 National Health Service (NHS) hospitals providing rectal cancer surgery in England. Five centralisation scenarios were considered: closure of lower-volume centres (scenario A); closure of non-comprehensive cancer centres (scenario B); closure of centres with a net loss of patients to other centres (scenario C); closure of centres meeting all three criteria in scenarios A, B, and C (scenario D); and closure of centres with high readmission rates (scenario E). We used conditional logistic regression to predict probabilities of affected patients moving to each of the remaining centres and the expected changes in travel time, multilevel logistic regression to predict 30-day emergency readmission rates, and linear regression to analyse associations between the expected extra travel time for patients whose centre is closed and five patient characteristics, including age, sex, socioeconomic deprivation, comorbidity, and rurality of the patients' residential areas (rural, urban [non-London], or London). We also quantified additional workload, defined as the number of extra patients reallocated to remaining centres. FINDINGS: Of the 11 888 patients, 4130 (34·7%) were women, 5249 (44·2%) were aged 70 years and older, and 5005 (42·1%) had at least one comorbidity. Scenario A resulted in closures of 43 (26%) of the 163 rectal cancer surgery centres, affecting 1599 (13·5%) patients; scenario B resulted in closures of 112 (69%) centres, affecting 7029 (59·1%) patients; scenario C resulted in closures of 56 (34%) centres, affecting 3142 (26·4%) patients; scenario D resulted in closures of 24 (15%) centres, affecting 874 (7·4%) patients; and scenario E resulted in closures of 16 (10%) centres, affecting 1000 (8·4%) patients. For each scenario, there was at least a two-times increase in predicted travel time for re-allocated patients with a mean increase in travel time of 23 min; however, the extra travel time did not disproportionately affect vulnerable patient groups. All scenarios resulted in significant reductions in 30-day readmission rates (range 4-48%). Three hospitals in scenario A, 41 hospitals in in scenario B, 13 hospitals in scenario C, no hospitals in scenario D, and two hospitals in scenario E had to manage at least 20 extra patients annually. INTERPRETATION: This health service planning model can be used to to guide complex decisions about the closure of centres and inform mitigation strategies. The approach could be applied across different country or regional health-care systems for patients with cancer and other complex health conditons. FUNDING: National Institute for Health Research.

Financing COVID-19-related health care costs in the Dutch competitive health system during 2020 and 2021: Overall experiences and policy recommendations for improving health system resilience.

The Dutch health system is based on the principles of managed (or regulated) competition, meaning that competing risk bearing insurers and providers negotiate contracts on the price, quantity and quality of care. The COVID-19 pandemic caused a huge external shock to the health system which potentially distorted the conditions required for fair competition. Therefore, an important question is to what extent was the competitive Dutch health system resilient to the financial shock caused by the pandemic? Overall, the Dutch competitive health system proved to be sufficiently flexible and resilient at absorbing the financial shock caused by the COVID-19 pandemic in 2020 and 2021 due to an effective combination of regulatory and self-regulatory measures. However, based on the overall experiences in the Netherlands, from the health policy perspective improvements are needed aimed at (i) refining the catastrophic costs clause included in the Health Insurance Act, (ii) reducing the vulnerability of the Dutch risk equalisation system to distortions due to unforeseen catastrophic health care costs, and (iii) establishing more equal financial risk sharing between health insurers and health care providers. These improvements are also relevant for other countries with a health system based on the principles of managed (or regulated) competition.

Assessing hospital competition when prices don't matter to patients: the use of time-elasticities.

Health care reforms in several European countries provide health insurers with incentives and tools to become prudent purchasers of health care. The potential success of this strategy crucially depends on insurers' bargaining leverage vis-à-vis health care providers. An important determinant of insurers' bargaining power is the willingness of consumers to consider alternative providers. In this paper we examine to what extent consumers are willing to switch hospitals when they are fully covered for hospital services, which is typical for many European countries. Since prices do not matter to these patients, we estimate time-elasticities to assess hospital substitutability. Using data from a large Dutch health insurer on non-emergency neurosurgical outpatient hospital visits in 2003, we estimate a conditional logit model of patient hospital choice taking both patient heterogeneity and hospital characteristics into account. We use the parameter estimates to simulate the demand effect of an artificial increase in travel time by 10% for every patient, holding all other hospital attributes constant. Overall, the resulting point estimates of hospitals' time-elasticities are fairly high, although variation is substantial (-2.6 to -1.4). Sensitivity tests reveal that these estimates are very robust and differ significantly across individual hospitals. This implies that all hospitals in our study sample have at least one close substitute which is an important precondition for effective hospital competition.

Simulating the impact of centralization of prostate cancer surgery services on travel burden and equity in the English National Health Service: A national population based model for health service re-design.

INTRODUCTION: There is limited evidence on the impact of centralization of cancer treatment services on patient travel burden and access to treatment. Using prostate cancer surgery as an example, this national study analysis aims to simulate the effect of different centralization scenarios on the number of center closures, patient travel times, and equity in access. METHODS: We used patient-level data on all men (n = 19,256) undergoing radical prostatectomy in the English National Health Service between January 1, 2010 and December 31, 2014, and considered three scenarios for centralization of prostate cancer surgery services A: procedure volume, B: availability of specialized services, and C: optimization of capacity. The probability of patients travelling to each of the remaining centers in the choice set was predicted using a conditional logit model, based on preferences revealed through actual hospital selections. Multivariable linear regression analysed the impact on travel time according to patient characteristics. RESULTS: Scenarios A, B, and C resulted in the closure of 28, 24, and 37 of the 65 radical prostatectomy centers, respectively, affecting 3993 (21%), 5763 (30%), and 7896 (41%) of the men in the study. Despite similar numbers of center closures the expected average increase on travel time was very different for scenario B (+15 minutes) and A (+28 minutes). A distance minimization approach, assigning patients to their next nearest center, with patient preferences not considered, estimated a lower impact on travel burden in all scenarios. The additional travel burden on older, sicker, less affluent patients was evident, but where significant, the absolute difference was very small. CONCLUSION: The study provides an innovative simulation approach using national patient-level datasets, patient preferences based on actual hospital selections, and personal characteristics to inform health service planning. With this approach, we demonstrated for prostate cancer surgery that three different centralization scenarios would lead to similar number of center closures but to different increases in patient travel time, whilst all having a minimal impact on equity.

Patient responsiveness to a differential deductible: empirical results from The Netherlands.

Health insurers may use financial incentives to encourage their enrollees to choose preferred providers for medical treatment. Empirical evidence whether differences in cost-sharing rates across providers affects patient choice behavior is, especially from Europe, limited. This paper examines the effect of a differential deductible to steer patient provider choice in a Dutch regional market for varicose veins treatment. Using individual patients' choice data and information about their out-of-pocket payments covering the year of the experiment and 1 year before, we estimate a conditional logit model that explicitly controls for pre-existing patient preferences. Our results suggest that in this natural experiment designating preferred providers and waiving the deductible for enrollees using these providers significantly influenced patient choice. The average cross-price elasticity of demand is found to be 0.02, indicating that patient responsiveness to the cost-sharing differential itself was low. Unlike fixed cost-sharing differences, the deductible exemption was conditional on the patient's other medical expenses occurring in the policy year. The differential deductible did, therefore, not result in a financial benefit for patients with annual costs exceeding their total deductible.

Why do patients bypass the nearest hospital? An empirical analysis for orthopaedic care and neurosurgery in the Netherlands.

Using data for 2003, we find that both for non-emergency orthopaedic care (38%) and neurosurgery (54%) numerous Dutch patients did not visit the nearest hospital. Our estimation results show that extra travel time negatively influences the probability of hospital bypassing. Good waiting time performance by the nearest hospital also significantly decreases the likelihood of a bypass decision. Patients seem to place a lower negative value on extra travel time for orthopaedic care than for neurosurgery. The valuation of shorter waiting time also varies between these two types of hospital care. A good performance of the nearest hospital on waiting time decreases the likelihood of a bypass decision most for neurosurgery. In both samples, patients are more likely to bypass the nearest hospital when it is a university medical centre or a tertiary teaching hospital. Patient attributes, such as age and social status, are also found to significantly affect hospital bypassing. From our analysis it follows that both patient and hospital care heterogeneity should be taken into account when assessing the substitutability of hospitals.

Using the deductible for patient channeling: did preferred providers gain patient volume?

In market-based health care systems, channeling patients to designated preferred providers can increase payer's bargaining clout, other things being equal. In the unique setting of the new Dutch health care system with regulated competition, this paper evaluates the impact of a 1-year natural experiment with patient channeling on providers' market shares. In 2009 a large regional Dutch health insurer designated preferred providers for two different procedures (cataract surgery and varicose veins treatment) and gave its enrollees a positive financial incentive for choosing them. That is, patients were exempted from paying their deductible when they went to a preferred provider. Using claims data over the period 2007-2009, we apply a difference-in-difference approach to study the impact of this channeling strategy on the allocation of patients across individual providers. Our estimation results show that, in the year of the experiment, preferred providers of varicose veins treatment on average experienced a significant increase in patient volume relative to non-preferred providers. However, for cataract surgery no significant effect is found. Possible explanations for the observed difference between both procedures may be the insurer's selection of preferred providers and the design of the channeling incentive resulting in different expected financial benefits for both patient groups.

Do patients choose hospitals with high quality ratings? Empirical evidence from the market for angioplasty in the Netherlands.

A necessary condition for competition to promote quality in hospital markets is that patients are sensitive to differences in hospital quality. In this paper we examine the relationship between hospital quality, as measured by publicly available quality ratings, and patient hospital choice for angioplasty using individual claims data from a large health insurer. We find that Dutch patients have a high propensity to choose hospitals with a good reputation, both overall and for cardiology, and a low readmission rate after treatment for heart failure. Relative to a mean readmission rate of 8.5% we find that a 1%-point lower readmission rate is associated with a 12% increase in hospital demand. Since readmission rates are not adjusted for case-mix they may not provide a correct signal of hospital quality. Insofar patients base their hospital choice on such imperfect quality information, this may result in suboptimal choices and risk selection by hospitals.

Pharmaceutical policy in the Netherlands: from price regulation towards managed competition.

PURPOSE: To analyse the development of pharmaceutical policy in the Dutch market for outpatient prescription drugs since the early 1990s. METHODOLOGY: A literature review and document analysis is performed to examine the effects of pharmaceutical policy on the performance of the Dutch market for outpatient prescription drugs since the early 1990s. FINDINGS: Government efforts to control prices of pharmaceuticals were effective in constraining prices of in-patent drugs, but had an opposite effect on the prices of generic drugs. The gradual transition towards managed competition--that particularly gained momentum after the introduction of the new universal health insurance scheme in 2006--appears to be more effective in constraining prices of generic drugs than earlier government efforts to control these prices. ORIGINALITY: Comparative analysis of the impact of price regulation and managed competition on generic drug prices in the Netherlands. IMPLICATIONS: Implications of the changing role of health insurers are discussed for the future market for prescription drugs and role of pharmacies in the Netherlands.