Choice of hospital: Which type of quality matters?

Freedom of choice for specialized consultation in Portugal: An observational analysis of response to hospital quality

BACKGROUND

Portugal introduced freedom of choice for initial specialist consultations in 2016 to boost quality via competition. However, for tangible benefits, specialized care demand must be quality-elastic. This research probes the relation between choosing hospital out the residence area and their quality traits.

METHODS

We used data for all primary consultation requests from primary care centres to hospitals from 1/1/2017 to 31/12/2018 (n = 3,346,335). We modelled the choice of a hospital as a function of its quality characteristics, adjusting for area-based socioeconomic variables using logistic regressions.

RESULTS

Results indicate that patients and their general practitioners consider quality indicators when choosing a hospital. Higher mortality, longer waiting times and higher readmission rates at the hospital of origin were positively associated with the patient's choice. Freedom of choice is less used when the distance to the hospital of origin increases. Similar patterns were observed for larger hospitals and those with academic status.

DISCUSSION

This study underscores the relevance of quality considerations in hospital selection by both patients and their general practitioners (GPs). The implications are two-fold. Firstly, improving quality appears as a factor to increase attractiveness, so that hospital competition may lead to improved health outcomes. Secondly, it highlights that hospital financing should include an activity dimension in which "money follows the patient", otherwise no financial incentive exists to improve quality. Hence, the current hospital financing model and the limited possibility to choose in certain areas limit the potential of quality improvement based on enhanced attractivity. Decision makers should be aware that quality is a driver of patient choice, as our study demonstrates, and adapt the system to take advantage of this reality.

Hospital competition when patients learn through experience

We study competing hospitals' incentives for quality provision in a dynamic setting where healthcare is an experience good. In our model, the utility a patient derives from choosing a particular provider depends on a subjective component specific to the match between the patient and the provider, which can only be learned through experience. We find that the experience-good nature of healthcare can either reinforce or dampen the demand responsiveness to quality and the hospitals' incentives for quality provision, depending on two key factors: the shape of the distribution of match-specific utilities and the cost relationship between quality provision and treatment volume. We establish conditions under which ignoring the experience dimension of healthcare leads to inaccurate assessments of the competitiveness of hospital markets.

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.

Analysing the intra and interregional components of spatial accessibility gravity model to capture the level of equity in the distribution of hospital services in Italy: do they influence patient mobility?

BACKGROUND

An equal distribution of hospital structures represents an important factor to achieve Universal Health Coverage. Generally, the most diffused approach to measure the potential availability to healthcare is the provider-to-population ratio based on the number of beds or professionals. However, this approach considers only the availability of resources provided at regional or local level ignoring the spatial accessibility of interregional facilities that are particularly accessed by patients living at the borders. Aim of this study is to outline the distribution of the intra and interregional services in Italy to capture the level of equity across the country. Moreover, it explores the impact of the accessibility to these resources on interregional patient's mobility to receive care.

METHODS

To compute spatial accessibility, we propose an alternative approach that applies the enhanced two-step floating catchment area (ESFCA) to capture the level of attraction of intra and interregional hospitals to a given population. Moreover, the adoption of process and outcome indices captured to what extent the quality of structures influenced patients in choosing services located inside or outside their region of residence.

RESULTS

The study confirms that there is an unequal distribution of high-quality resources at regional and national level with a high level of inequality in the availability and accessibility of quality resources between the north and south part of Italy. This is particularly true considering the accessibility of intraregional resources in the southern part of the country that clearly influences patient choice and contribute to a significant cross border passive mobility to northern regions. This is confirmed by an econometric model that showed a significant effect of spatial accessibility with the propensity of patients of travel from the region of residence to receive care.

CONCLUSIONS

The analysis of intra and interregional components of spatial accessibility may contribute to identify to what extent patients are willing to travel outside their region of residence to access to care services. Moreover, it can contribute to gain a deeper understanding of the allocation of health resources providing input for policy makers on the basis of the principles of service accessibility in order to contain patient mobility.

The elicitation of patient and physician preferences for calculating consumer-based composite measures on hospital report cards: results of two discrete choice experiments

PURPOSE

The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information METHODS: Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients' and referring physicians' preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models RESULTS: Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, "Postoperative complication rate" (20.6%; level range of 1.164) was rated highest, followed by "Mobility at hospital discharge" (19.9%; level range of 1.127), and ''The number of cases treated" (18.5%; level range of 1.045). In contrast, referring physicians valued most the ''One-year revision surgery rate'' (30.4%; level range of 1.989), followed by "The number of cases treated" (21.0%; level range of 1.372), and "Postoperative complication rate" (17.2%; level range of 1.123) CONCLUSION: We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting.

Choosing a maternity hospital: a matter of travel distance or quality of care?

BACKGROUND

The choice of a hospital should be based on individual need and accessibility. For maternity hospitals, this includes known or expected risk factors, the geographic accessibility and level of care provided by the hospital. This study aims to identify factors influencing hospital choice with the aim to analyze if and how many deliveries are conducted in a risk-appropriate and accessible setting in Bavaria, Germany.

METHODS

This is a cross-sectional secondary data analysis based on all first births in Bavaria (2015-18) provided by the Bavarian Quality Assurance Institute for Medical Care. Information on the mother and on the hospital were included. The Bavarian Index of Multiple Deprivation 2010 was used to account for area-level socioeconomic differences. Multiple logistic regression models were used to estimate the strength of association of the predicting factors and to adjust for confounding.

RESULTS

We included 195,087 births. Distances to perinatal centers were longer than to other hospitals (16 km vs. 12 km). 10% of women with documented risk pregnancies did not deliver in a perinatal center. Regressions showed that higher age (OR 1.03; 1.02-1.03 95%-CI) and risk pregnancy (OR 1.44; 1.41-1.47 95%-CI) were associated with choosing a perinatal center. The distances travelled show high regional variation with a strong urban-rural divide.

CONCLUSION

In a health system with free choice of hospitals, many women chose a hospital close to home and/or according to their risks. However, this is not the case for 10% of mothers, a group that would benefit from more coordinated care.

Patient outcomes, efficiency, and adverse events for elective hip and knee replacement in private and NHS hospitals: a population-based cohort study in England

Background

Since the early 2000s, the National Health Service (NHS) in England has expanded provision of publicly funded care in private hospitals as a strategy to meet growing demand for elective care. This study aims to compare patient outcomes, efficiency and adverse events in private and NHS hospitals when providing elective hip and knee replacement.

Methods

We conducted a population-based cohort study including patients ≥18 years, undergoing a publicly funded elective hip or knee replacement in private and NHS hospitals in England between January 1st 2016 and March 31st 2019. Comparative probability was estimated for three patient outcome measures (in-hospital mortality, emergency readmissions with 28 days, hospital transfers), two efficiency measures (pre-operative length of stay (LOS) >0 day and post-operative LOS >2 days), and four adverse events (hospital-associated infection, adverse drug reactions, pressure ulcers, venous thromboembolism). Probit regression was used to adjust for observable confounding followed by instrumental variable (IV) analyses to also account for unobserved confounding at the patient-level. Propensity score matching was then used as a robustness check.

Findings

Our study sample included 169,232 patients in private hospitals, and 262,659 patients in NHS hospitals. Estimates from probit regression indicated that treatment in private hospital was associated with reduced probability of in-hospital mortality (-0.0009, 95% CI -0.0010, -0.0007), emergency readmissions (-0.0181, 95% CI -0.0191, -0.0172), hospital transfers (-0.0076, 95% CI -0.0084, -0.0068), prolonged post-operative LOS (-0.1174, 95% CI -0.1547, -0.0801), hospital-associated infection (-0.0115, 95% CI -0.0123, -0.0107), adverse drug reactions (-0.0051, 95% CI -0.0056, -0.0046), pressure ulcers (-0.0017, 95% CI -0.0019, -0.0014), and venous thromboembolism (-0.0027, 95% CI -0.0031, -0.0022). IV analyses produced no significant differences between private and NHS hospitals, except for lower probability in private hospitals of hospital-associated infection (-0.0057, 95% CI -0.0081, -0.0032), and greater probability in private hospitals of prolonged post-operative LOS (0.2653, 95% CI 0.1833, 0.3472). Propensity score matching produced similar results to probit regression.

Interpretation

Our findings indicate there is potentially important unobservable confounding at the patient-level between private and NHS hospitals not adjusted for when using probit regression or propensity score matching.

Funding

This research did not receive any dedicated funding.

Referring physicians' intention to use hospital report cards for hospital referral purposes in the presence or absence of patient-reported outcomes: a randomized trial

PURPOSE

This study aims to determine the intention to use hospital report cards (HRCs) for hospital referral purposes in the presence or absence of patient-reported outcomes (PROs) as well as to explore the relevance of publicly available hospital performance information from the perspective of referring physicians.

METHODS

We identified the most relevant information for hospital referral purposes based on a literature review and qualitative research. Primary survey data were collected (May-June 2021) on a sample of 591 referring orthopedists in Germany and analyzed using structural equation modeling. Participating orthopedists were recruited using a sequential mixed-mode strategy and randomly allocated to work with HRCs in the presence (intervention) or absence (control) of PROs.

RESULTS

Overall, 420 orthopedists (mean age 53.48, SD 8.04) were included in the analysis. The presence of PROs on HRCs was not associated with an increased intention to use HRCs (p = 0.316). Performance expectancy was shown to be the most important determinant for using HRCs (path coefficient: 0.387, p < .001). However, referring physicians have doubts as to whether HRCs can help them. We identified "complication rate" and "the number of cases treated" as most important for the hospital referral decision making; PROs were rated slightly less important.

CONCLUSIONS

This study underpins the purpose of HRCs, namely to support referring physicians in searching for a hospital. Nevertheless, only a minority would support the use of HRCs for the next hospital search in its current form. We showed that presenting relevant information on HRCs did not increase their use intention.

Hospital and Patient Factors Affecting Veterans' Hospital Choice

Veterans enrolled in the Veterans Affairs (VA) health care system gained greater access to non-VA care beginning in 2014. We examined hospital and Veteran characteristics associated with hospital choice. We conducted a longitudinal study of elective hospitalizations 2011 to 2017 in 11 states and modeled patients' choice of VA hospital, large non-VA hospital, or small non-VA hospital in conditional logit models. Patients had higher odds of choosing a hospital with an academic affiliation, better patient experience rating, location closer to them, and a more common hospital type. Patients who were male, racial/ethnic minorities, had higher VA enrollment priority, and had a mental health comorbidity were more likely than other patients to choose a VA hospital than a non-VA hospital. Our findings suggest that patients respond to certain hospital attributes. VA hospitals may need to maintain or achieve high levels of quality and patient experience to attract or retain patients in the future.

Driving time drives the hospital choice: choice models for pelvic organ prolapse surgery in Italy

OBJECTIVE

The Italian healthcare jurisdiction promotes patient mobility, which is a major determinant of practice variation, thus being related to the equity of access to health services. We aimed to explore how travel times, waiting times, and other efficiency- and quality-related hospital attributes influenced the hospital choice of women needing pelvic organ prolapse (POP) surgery in Tuscany, Italy.

METHODS

We obtained the study population from Hospital Discharge Records. We duplicated individual observations (n = 2533) for the number of Tuscan hospitals that provided more than 30 POP interventions from 2017 to 2019 (n = 22) and merged them with the hospitals' list. We generated the dichotomous variable "hospital choice" assuming the value one when hospitals where patients underwent surgery coincided with one of the 22 hospitals. We performed mixed logit models to explore between-hospital patient choice, gradually adding the women's features as interactions.

RESULTS

Patient choice was influenced by travel more than waiting times. A general preference for hospitals delivering higher volumes of interventions emerged. Interaction analyses showed that poorly educated women were less likely to choose distant hospitals and hospitals providing greater volumes of interventions compared to their counterpart. Women with multiple comorbidities more frequently chose hospitals with shorter average length of stay.

CONCLUSION

Travel times were the main determinants of hospital choice. Other quality- and efficiency-related hospital attributes influenced hospital choice as well. However, the effect depended on the socioeconomic and clinical background of women. Managers and policymakers should consider these findings to understand how women behave in choosing providers and thus mitigate equity gaps.

The sorting effect in healthcare access: Those left behind

Many governments have sought to enhance patient choice in hospital by intensifying competitive pressure on hospital administrations that is expected to improve efficiency, quality, and innovation. However, there is mixed evidence on whether patients travel past their local hospitals to seek better quality care and whether higher-income patients are those most sensitive to respond to competitive pressures. Using detailed data from 17 million inpatient stays admitted in France during 2019, this paper explores patients' choice of provider where for-profit, non-profit, research hospital and local hospitals are allowed to compete with each other. We estimate the extent to which deprivation gradient plays on patient's choice of provider. We found that, in general, patients travel for their care, with just one-quarter of them going to the nearest hospital. In fact, the most vulnerable patients (i.e., those socio-economically deprived, and very aged) are mostly treated in local public hospitals with the lowest quality service level, and with large variability in quality as well, while those with less socio-economic deprivation seek care at higher-quality for-profit hospitals. Our counterfactual simulations show that admission to university hospitals attenuates existing inequalities. However, whether it delays the healthcare access sought by this population remains an open question.

How to direct patients to high-volume hospitals: exploring the influencing drivers

BACKGROUND

During the last decade, planning concentration policies have been applied in healthcare systems. Among them, attention has been given to guiding patients towards high-volume hospitals that perform better, acccording to the volume-outcome association. This paper analyses which factors drive patients to choose big or small hospitals (with respect to the international standards of volumes of activity).

METHODS

We examined colon cancer surgeries performed in Piedmont (Italy) between 2004 and 2018. We categorised the patient choice of the hospital as big/small, and we used this outcome as main dependent variable of descriptive statistics, tests and logistic regression models. As independent variables, we included (i) patient characteristics, (ii) characteristics of the closest big hospital (which should be perceived as the most immediate to be chosen), and (iii) territorial characteristics (i.e., characteristics of the set of hospitals among which the patient can choose). We also considered interactions among variables to examine which factors influence all or a subset of patients.

RESULTS

Our results confirm that patient personal characteristics (such as age) and hospital characteristics (such as distance) play a primary role in the patient decision process. The findings seem to support the importance of closing small hospitals when they are close to big hospitals, although differences emerge between rural and urban areas. Other interesting insights are provided by examining the interactions between factors, e.g., patients affected by comorbidities are more responsive to hospital quality even though they are distant.

CONCLUSIONS

Reorganising healthcare services to concentrate them in high-volume hospitals emerged as a crucial issue more than forty years ago. Evidence suggests that concentration strategies guarantee better clinical performance. However, in healthcare systems in which patients are free to choose where to be treated, understanding patients' behaviour and what drives them towards the most effective choice is of paramount importance. Our study builds on previous research that has already analysed factors influencing patients' choices, and takes a step further to enlighten which factors drive patients to choose between a small or a big hospital (in terms of volume). The results could be used by decision makers to design the best concentration strategy.

A composite measure for patient-reported outcomes in orthopedic care: design principles and validity checks

BACKGROUND

The complex, multidimensional nature of healthcare quality makes provider and treatment decisions based on quality difficult. Patient-reported outcome (PRO) measures can enhance patient centricity and involvement. The proliferation of PRO measures, however, requires a simplification to improve comprehensibility. Composite measures can simplify complex data without sacrificing the underlying information.

OBJECTIVE AND METHODS

We propose a five-step development approach to combine different PRO into one composite measure (PRO-CM): (i) theoretical framework and metric selection, (ii) initial data analysis, (iii) rescaling, (iv) weighting and aggregation, and (v) sensitivity and uncertainty analysis. We evaluate different rescaling, weighting, and aggregation methods by utilizing data of 3145 hip and 2605 knee replacement patients, to identify the most advantageous development approach for a PRO-CM that reflects quality variations from a patient perspective.

RESULTS

The comparison of different methods within steps (iii) and (iv) reveals the following methods as most advantageous: (iii) rescaling via z-score standardization and (iv) applying differential weights and additive aggregation. The resulting PRO-CM is most sensitive to variations in physical health. Changing weighting schemes impacts the PRO-CM most directly, while it proves more robust towards different rescaling and aggregation approaches.

CONCLUSION

Combining multiple PRO provides a holistic picture of patients' health improvement. The PRO-CM can enhance patient understanding and simplify reporting and monitoring of PRO. However, the development methodology of a PRO-CM needs to be justified and transparent to ensure that it is comprehensible and replicable. This is essential to address the well-known problems associated with composites, such as misinterpretation and lack of trust.

Robotic-assisted surgery for prostatectomy - does the diffusion of robotic systems contribute to treatment centralization and influence patients' hospital choice?

BACKGROUND

Between 2008 and 2018, the share of robotic-assisted surgeries (RAS) for radical prostatectomies (RPEs) has increased from 3 to 46% in Germany. Firstly, we investigate if this diffusion of RAS has contributed to RPE treatment centralization. Secondly, we analyze if a hospital's use of an RAS system influenced patients' hospital choice.

METHODS

To analyze RPE treatment centralization, we use (bi-) annual hospital data from 2006 to 2018 for all German hospitals in a panel-data fixed effect model. For investigating RAS systems' influence on patients' hospital choice, we use patient level data of 4614 RPE patients treated in 2015. Employing a random utility choice model, we estimate the influence of RAS as well as specialization and quality on patients' marginal utilities and their according willingness to travel.

RESULTS

Despite a slight decrease in RPEs between 2006 and 2018, hospitals that invested in an RAS system could increase their case volumes significantly (+ 82% compared to hospitals that did not invest) contributing to treatment centralization. Moreover, patients are willing to travel longer for hospitals offering RAS (+ 22% than average travel time) and for specialization (+ 13% for certified prostate cancer treatment centers, + 9% for higher procedure volume). The influence of outcome quality and service quality on patients' hospital choice is insignificant or negligible.

CONCLUSIONS

In conclusion, centralization is partly driven by (very) high-volume hospitals' investment in RAS systems and patient preferences. While outcome quality might improve due to centralization and according specialization, evidence for a direct positive influence of RAS on RPE outcomes still is ambiguous. Patients have been voting with their feet, but research yet has to catch up.

Women's choices of hospital for breast cancer surgery in Italy: Quality and equity implications

This paper employs mixed logit regression to investigate the effects of providers characteristics on women's choice of hospital for breast surgery. Patient level data are used to model choices in Tuscany region, Italy. In particular, we focus on the effects of travel time and hospital quality indicators including quality standard (volumes of breast surgery), measurement of process (waiting times) and quality of surgical procedures. Variation in preferences related to individual characteristics such as age, education and travel distance from the hospital are also considered. Findings show that, on average, women prefer closer hospital with longer waiting times and higher quality (high volumes of interventions). We found preference heterogeneity associated to education: travel distance affects choice especially among less educated women (regardless of age), while among younger women (<65 years), less educated ones prefer shorter waiting times. These results could be used to optimize the allocation of resources toward breast cancer units that meet quality and efficacy standards to increase the efficiency and responsiveness of breast cancer care.

Health service behaviors of migrants: A conceptual framework

Universal health coverage is vital to the World Health Organization's (WHO's) efforts to ensure access to health as a human right. However, it has been reported that migrants, including both international immigrants and internal migrants, underuse health services. Establishing a conceptual framework to facilitate research on the health service behaviors (HSB) of migrants is particularly important. Many theoretical frameworks explaining the general population's HSB have been published; however, most theoretical frameworks on migrants' HSB only focus on international immigrants without the inclusion of internal migrants. Of note, internal migrants are much more abundant than immigrants, and this group faces similar barriers to HSB as immigrants do. Based on theoretical frameworks of immigrants' HSB and Anderson's behavior model, the author proposes a new conceptual framework of migrants' HSB that includes both immigrants and internal migrants. The new conceptual framework divides the determinants into macro-structural or contextual factors, health delivery system characteristics, and characteristics of the population at risk and describes subgroup-specific factors. The author added some variables and reclassified variables in some dimensions, including characteristics of health delivery systems and access to healthcare. The characteristics of health delivery systems comprise the volume, organization, quality, and cost of the health delivery system, while the characteristics of access to healthcare include time accessibility, geographic accessibility, and information accessibility. The outcomes of HSB have been expanded, and relationships between them have been reported. The mediating effects of some variables have also been described. This conceptual framework can facilitate a deep and comprehensive understanding of the HSB determination process for migrants, including internal migrants.

Can competition improve hospital quality of care? A difference-in-differences approach to evaluate the effect of increasing quality transparency on hospital quality

Public reporting on the quality of care is intended to guide patients to the provider with the highest quality and to stimulate a fair competition on quality. We apply a difference-in-differences design to test whether hospital quality has improved more in markets that are more competitive after the first public release of performance data in Germany in 2008. Panel data from 947 hospitals from 2006 to 2010 are used. Due to the high complexity of the treatment of stroke patients, we approximate general hospital quality by the 30-day risk-adjusted mortality rate for stroke treatment. Market structure is measured (comparatively) by the Herfindahl-Hirschman index (HHI) and by the number of hospitals in the relevant market. Predicted market shares based on exogenous variables only are used to compute the HHI to allow a causal interpretation of the reform effect. A homogenous positive effect of competition on quality of care is found. This effect is mainly driven by the response of non-profit hospitals that have a narrow range of services and private for-profit hospitals with a medium range of services. The results highlight the relevance of outcome transparency to enhance hospital quality competition.

Consumer choice and public-private providers: The role of perceived prices

Governments often encourage health service providers to improve quality of care and reduce prices through competition. The efficacy of competition hinges on the assumption that consumers demand high quality care at low prices for any given health condition. In this paper, we examine this assumption by investigating the role of perceived price and quality on consumer choice for four different health conditions across public and private providers. We use a nationally representative survey in Malaysia to elicit respondents' perception on prices and quality, and their preferred choice of provider. We estimate a mixed logit model and show that consumers value different dimensions of quality depending on the health condition. Furthermore, increasing perceived prices for private providers reduces demand for minor, more frequent health conditions such as flu fever or cough, but increases demand for more complex, severe conditions such as coronary artery bypass graft. These findings provide empirical support for price regulation which differentiates the severity of underlying health conditions.

Defining minimum volume thresholds to increase quality of care: a new patient-oriented approach using mixed integer programming

A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume-outcome relationship into minimum volume regulation (MVR) to increase the quality of care-yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accordingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure's complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR's intended benefit: concentrating treatment delivery to improve the quality of care.

Doctors’ Preferences in the Selection of Patients in Online Medical Consultations: An Empirical Study with Doctor–Patient Consultation Data

Online medical consultation (OMC) allows doctors and patients to communicate with each other in an online synchronous or asynchronous setting. Unlike face-to-face consultations in which doctors are only passively chosen by patients with appointments, doctors engaging in voluntary online consultation have the option of choosing patients they hope to treat when faced with a large number of online questions from patients. It is necessary to characterize doctors’ preferences for patient selection in OMC, which can contribute to their more active participation in OMC services. We proposed to exploit a bipartite graph to describe the doctor–patient interaction and use an exponential random graph model (ERGM) to analyze the doctors’ preferences for patient selection. A total of 1404 doctor–patient consultation data retrieved from an online medical platform in China were used for empirical analysis. It was found that first, mildly ill patients will be prioritized by doctors, but the doctors with more professional experience may be more likely to prefer more severely ill patients. Second, doctors appear to be more willing to provide consultation services to patients from urban areas, but the doctors with more professional experience or from higher-quality hospitals give higher priority to patients from rural and medically underserved areas. Finally, doctors generally prefer asynchronous communication methods such as picture/text consultation, while the doctors with more professional experience may be more willing to communicate with patients via synchronous communication methods, such as voice consultation or video consultation.

Effects of competition and bundled payment on the performance of hip replacement surgery in Stockholm, Sweden: results from a quasi-experimental study

OBJECTIVE

To evaluate the effects of competition and a bundled payment model on the performance of hip replacement surgery.

DESIGN

A quasi-experimental study where a difference-in-differences analytical framework is applied to analyse routinely collected patient-level data from multiple registers.

SETTING

Hospitals providing hip replacement surgery in Sweden.

PARTICIPANTS

The study included patients who underwent elective primary total hip replacement due to osteoarthritis from 2005 to 2012. The final study sample consisted of 85 275 hip replacement surgeries, where the exposure group consisted of 14 570 surgeries (n=6380 prereform and n=8190 postreform) and the control group consisted of 70 705 surgeries (n=32 799 prereform and n=37 906 postreform).

INTERVENTION

A reform involving patient choice, free entry of new providers and a bundled payment model for hip replacement surgery, which came into force in 2009 in Region Stockholm, Sweden.

OUTCOME MEASURES

Performance is measured as length of stay of the surgical admission, adverse event rate within 90 days following surgery and patient satisfaction 1 year postsurgery.

RESULTS

The reform successfully improved the adverse event rate (1.6 percentage reduction, p<0.05). Length of stay decreased less in the more competitive market than in the control group (0.7 days lower, p<0.01). These effects were mainly driven by university and central hospitals. No effects of the reform on patient satisfaction were found (no significance).

CONCLUSIONS

The study concludes that the incentives of the reform focusing on avoidance of adverse events have a predictable impact. Since the payment for providers is fixed per case, the impact on resource use is limited. Our findings contribute to the general knowledge about the effects of financial incentives and market-oriented reforms.

3D Differential Equation Model for Patients' Choice of Hospital in China

The number of patients in a hospital is a direct indicator of patients' choice of hospital, which is a complex process affected by many factors. Based on the national medical system and patients' preference for high-grade hospitals in China, this study establishes a three-dimensional differential equation model for calculating the time variation of the number of visits to three grades of hospitals. We performed a qualitative analysis of the system. We carried out a subsequent numerical simulation to analyze the impact on the system when the rate of leapfrog treatment and the maximum capacity of doctors and treatments changed. The results show that the sustainability of China's three levels of hospitals mainly depends on the level of hospital development. The strength of comprehensive health improvement at specific levels is the key to increasing the service efficiency of medical resources.

Measuring quality effects in equilibrium

Unlike demand studies in other industries, models of provider demand in health care often must omit a price, or any other factor that equilibrates the market such as a waiting time. Estimates of the consumer response to quality may consequently be attenuated, if the limited capacity of individual physicians prevents some consumers from obtaining higher quality. We propose a tractable method to address this problem by adding a congestion effect to standard discrete-choice models. We show analytically how this can improve forecasts of the consumer response to quality. We then apply this method to the market for heart surgery, and find that the attenuation bias in estimated quality effects can be important empirically.

Resilient managed competition during pandemics: lessons from the Italian experience during COVID-19

In the last decades, several European health systems have abandoned their vertically integrated health care in favour of some form of managed competition (MC), either in a centralised or decentralised format. However, during a pandemic, MC may put health systems under additional strain as they are designed to follow some form of 'organisational self-interest', and hence face reduced incentives for both provider coordination (e.g. temporary hospital close down, change in the case-mix), and information sharing. We illustrate our argument using evidence for the Covid-19 pandemic outbreak in Italy during March and April 2020, which calls for the development of 'coordination mechanisms' at times of a health emergency.

Investment and quality competition in healthcare markets

We study the strategic relationship between hospital investment and provision of service quality. We use a spatial competition framework and allow investment and quality to be complements or substitutes in patient benefit and provider cost. We assume that each hospital commits to a certain investment before deciding on service quality, and that investment is observable and contractible while quality is observable but not contractible. We show that, under a fixed DRG-pricing system, providers' lack of ability to commit to quality leads to under- or overinvestment, relative to the first-best solution. Underinvestment arises when the price-cost margin is positive, and quality and investments are strategic complements, which has implications for optimal contracting. Differently from the simultaneous-move case, the regulator must complement the payment with one more instrument to address under/overinvestment. We also analyse the welfare effects of different policy options (separate payment for investment, higher per-treatment prices, or DRG-refinement policies).

Comparing the Impact of Online Ratings and Report Cards on Patient Choice of Cardiac Surgeon: Large Observational Study

Background

Patients may use two information sources about a health care provider’s quality: online physician reviews, which are written by patients to reflect their subjective experience, and report cards, which are based on objective health outcomes.

Objective

The aim of this study was to examine the impact of online ratings on patient choice of cardiac surgeon compared to that of report cards.

Methods

We obtained ratings from a leading physician review platform, Vitals; report card scores from Pennsylvania Cardiac Surgery Reports; and information about patients’ choices of surgeons from inpatient records on coronary artery bypass graft (CABG) surgeries done in Pennsylvania from 2008 to 2017. We scraped all reviews posted on Vitals for surgeons who performed CABG surgeries in Pennsylvania during our study period. We linked the average overall rating and the most recent report card score at the time of a patient’s surgery to the patient’s record based on the surgeon’s name, focusing on fee-for-service patients to avoid impacts of insurance networks on patient choices. We used random coefficient logit models with surgeon fixed effects to examine the impact of receiving a high online rating and a high report card score on patient choice of surgeon for CABG surgeries.

Results

We found that a high online rating had positive and significant effects on patient utility, with limited variation in preferences across individuals, while the impact of a high report card score on patient choice was trivial and insignificant. About 70.13% of patients considered no information on Vitals better than a low rating; the corresponding figure was 26.66% for report card scores. The findings were robust to alternative choice set definitions and were not explained by surgeon attrition, referral effect, or admission status. Our results also show that the interaction effect of rating information and a time trend was positive and significant for online ratings, but small and insignificant for report cards.

Conclusions

A patient’s choice of surgeon is affected by both types of rating information; however, over the past decade, online ratings have become more influential, while the effect of report cards has remained trivial. Our findings call for information provision strategies that incorporate the advantages of both online ratings and report cards.

Simply the best? The impact of quality on choice of primary healthcare provider in Sweden

OBJECTIVE

One of the more important objectives with the patient choice reform, introducing non-price competition in Swedish primary healthcare, was to improve performance and quality of care. However, in order for choice to lead to quality improvements, citizens need to consider quality aspects in their choices of provider. We hypothesize that quality of care influences choice of provider and the objective of this study is to investigate if citizens are willing to make a trade-off between distance to chosen provider and quality of care.

METHODS

We use conditional logit models to analyse if quality and other provider attributes influence choice of provider. The study population includes all citizens of Region Stockholm with at least one primary healthcare contact (N ~1.4 million).

RESULTS

The results show that distance is the most important factor in choosing a primary healthcare provider but that there seems to be a willingness to make a trade-off between distance and quality measures. However, other provider attributes, such as the Care Need Index of the registered population, seem to influence choice to a greater extent than quality.

CONCLUSION

The results point in the same direction as the arguments behind the patient choice reform. However, the effects are marginal. To enhance quality competition, policy makers should consider making quality information at the provider level more accessible.

Choice, quality and patients' experience: evidence from a Finnish physiotherapy service

We study the relationship between patient choices and provider quality in a rehabilitation service for disabled patients who receive the service frequently but do not have access to quality information. Previous research has found a positive relationship between patient choices and provider quality in health services that patients typically do not have previous experience or use frequently. We contribute by examining choices of new patients and experienced patients who were either forced to switch or actively switched their provider. In the analysis, we combine register data on patients' choices and switches with provider quality data from a competitive bidding, and estimate conditional logit choice models. The results show that all patients prefer high-quality providers within short distances. We find that the willingness to travel for quality is highest among new patients and active switchers. These results suggest that new patients and active switchers compare different alternatives more thoroughly, whereas forced switchers choose their new provider in limited time leading into poorer choices.

The effects of competition and bundled payment on patient reported outcome measures after hip replacement surgery

BACKGROUND

Competition-promoting reforms and economic incentives are increasingly being introduced worldwide to improve the performance of healthcare delivery. This study considers such a reform which was initiated in 2009 for elective hip replacement surgery in Stockholm, Sweden. The reform involved patient choice of provider, free establishment of new providers and a bundled payment model. The study aimed to examine its effects on hip replacement surgery quality as captured by patient reported outcome measures (PROMs) of health gain (as indicated by the EQ-5D index and a visual analogue scale (VAS)), pain reduction (VAS) and patient satisfaction (VAS) one and six years after the surgery.

METHODS

Using patient-level data collected from multiple national registers, we applied a quasi-experimental research design. Data were collected for elective primary total hip replacements that were carried out between 2008 and 2012, and contain information on patient demography, the surgery and PROMs at baseline and at one- and six-years follow-up. In total, 36,627 observations were included in the analysis. First, entropy balancing was applied in order to reduce differences in observable characteristics between treatment groups. Second, difference-in-difference analyses were conducted to eliminate unobserved time-invariant differences between treatment groups and to estimate the causal treatment effects.

RESULTS

The entropy balancing was successful in creating balance in all covariates between treatment groups. No significant effects of the reform were found on any of the included PROMs at one- and six-years follow-up. The sensitivity analyses showed that the results were robust.

CONCLUSIONS

Competition and bundled payment had no effects on the quality of hip replacement surgery as captured by post-surgery PROMs of health gain, pain reduction and patient satisfaction. The study provides important insights to the limited knowledge on the effects of competition and economic incentives on PROMs.

Predicting Hospital Overall Quality Star Ratings in the USA

The U.S. Centers for Medicare and Medicaid Services (CMS) assigns quality star ratings to hospitals upon assessing their performance across 57 measures. Ratings can be used by healthcare consumers for hospital selection and hospitals for quality improvement. We provide a simpler, more intuitive modeling approach, aligned with recent criticism by stakeholders. An ordered logistic regression approach is proposed to assess associations between performance measures and ratings across eligible (n = 4519) U.S. hospitals. Covariate selection reduces the double counting of information from highly correlated measures. Multiple imputation allows for inference of star ratings when information on all measures is not available. Twenty performance measures were found to contain all the relevant information to formulate star rating predictions upon accounting for performance measure correlation. Hospitals can focus their efforts on a subset of model-identified measures, while healthcare consumers can predict quality star ratings for hospitals ineligible under CMS criteria.

Divided by choice? For-profit providers, patient choice and mechanisms of patient sorting in the English National Health Service

This paper studies patient choice of provider following government reforms in the 2000s, which allowed for-profit surgical centers to compete with existing public National Health Service (NHS) hospitals in England. For-profit providers offer significant benefits, notably shorter waiting times. We estimate the extent to which different types of patients benefit from the reforms, and we investigate mechanisms that cause differential benefits. Our counterfactual simulations show that, in terms of the value of access, entry of for-profit providers benefitted the richest patients twice as much as the poorest, and white patients six times as much as ethnic minority patients. Half of these differences is explained by healthcare geography and patient health, while primary care referral practice plays a lesser, though non-negligible role. We also show that, with capitated reimbursement, different compositions of patient risks between for-profit surgical centers and existing public hospitals put public hospitals at a competitive disadvantage.

Economic Analysis of Portuguese Public Hospitals Through the Construction of Quality, Efficiency, Access, and Financial Related Composite Indicators

Hospitals consume most of the health systems' financial resources. In Portugal, for instance, public hospitals represent more than half of the National Health Service debt and are decisive in their financial insufficiency. Although profit is not the primary goal of hospitals, it is essential to guarantee their financial sustainability to ensure users' health care and the necessary resources. An analysis of the existing literature shows that researches focus mainly on the hospital's technical efficiency. The literature has paid little or even no attention to the use of composite indicators in hospital benchmarking studies. This study uses the Benefit of Doubt methodology alongside recent data about Portuguese public hospitals (2013-2017) to understand the factors that contribute to low performance and high indebtedness levels. Our results suggest that hospitals perform better in terms of access (average score: 0.982). The group of criteria with the lowest performance was efficiency and productivity (average score: 0.919), suggesting resources waste. Financial performance is, in general, higher than quality, raising social concerns about the way that public hospitals have been managed. Findings bring relevant implications. For example, the way hospitals are currently financed should consider efficiency, productivity, quality, and access. Regulators should ensure that minimum performance levels are fulfilled, applying preventive and corrective measures to avoid future low-performance levels. We suggest that hospital managers introduce satisfaction inquiries to improve quality. These improvements can attract more patients in the medium- or long-term; thus, our results are useful to citizens to make a better choice.

The impact of quality on hospital choice. Which information affects patients' behavior for colorectal resection or knee replacement?

Quality competition among hospitals, induced by patients freely choosing their hospital in a price regulated market, can only be realized if quality differences between hospitals are transparent, understandable, and thus influence patients' hospital choice. We use data from ~145,000 German patients and ~ 900 hospitals for colorectal resections and knee replacements to investigate whether patients value quality and specialization when choosing their hospital. Using a random utility choice model, we estimate patients' marginal utilities, willingness to travel and change in hospital demand for quality improvements. Patients respond to service quality and specialization and thus, quality competition seems to be present. Colorectal resection patients are willing to travel longer for more specialized hospitals (+9% for procedure volume, +9% for certification). Knee replacement patients travel longer for hospitals with better service quality (+6%) and higher procedure volume (+12%). However, clinical quality indicators, often difficult to access and interpret, barely play a role in patients' hospital choice. Furthermore, we find that competition on quality for colorectal resection is rather local, whereas for knee replacement we observe regional competition patterns.

The effects of expanded social health insurance on young mothers: Lessons from a pro-choice reform in Uruguay

With the implementation of the National Integrated Health System in 2007, the Uruguayan government extended social health insurance (SHI) to groups of individuals previously covered by the public safety net (PSN) or that paid for private insurance out-of-pocket. The policy allowed new beneficiaries to choose care from a set of private providers. In this study, we focus on the extension of SHI to adolescent mothers previously covered by the PSN. Exploiting the gradual incorporation of children of formal workers during the 2008-2013 period, and the geographic variation in the intensity of the reform, we find suggestive evidence that the increase in choice associated to the expansion of SHI decreased adolescent fertility, improved prenatal care and birthweight, and decreased first year mortality among low birthweight infants. These effects were only observed in the medium run, suggesting initial choice frictions and input shortage. We provide evidence that families increased their choice of private providers and that market concentration decreased in certain areas of the country, supporting the hypothesis that choice, and possibly competition, were the main mechanisms behind the findings.

Rumor has it: How do patients respond to patient-generated physician ratings?

This paper studies the impact of patient-generated ratings of primary care physicians in Norway. Norway has a universal health care system, with no available objective quality indicators. In May 2012, an online review platform that allows patients to rate their physician was launched. Relying on a difference-in-differences approach we show that higher-rated physicians see an increase in demand relative to lower-rated physicians. The effect is primarily driven by females and patients with high socioeconomic status. We find no indications that physicians change their practice style or supply of patient capacity in response to the ratings.

Funnel plots of patient-reported outcomes to evaluate health-care quality: Basic principles, pitfalls and considerations

A funnel plot is a graphical method to evaluate health-care quality by comparing hospital performances on certain outcomes. So far, in nephrology, this method has been applied to clinical outcomes like mortality and complications. However, patient-reported outcomes (PROs; eg, health-related quality of life [HRQOL]) are becoming increasingly important and should be incorporated into this quality assessment. Using funnel plots has several advantages, including clearly visualized precision, detection of volume-effects, discouragement of ranking hospitals and easy interpretation of results. However, without sufficient knowledge of underlying methods, it is easy to stumble into pitfalls, such as overinterpretation of standardized scores, incorrect direct comparisons of hospitals and assuming a hospital to be in-control (ie, to perform as expected) based on underpowered comparisons. Furthermore, application of funnel plots to PROs is accompanied by additional challenges related to the multidimensional nature of PROs and difficulties with measuring PROs. Before using funnel plots for PROs, high and consistent response rates, adequate case mix correction and high-quality PRO measures are required. In this article, we aim to provide insight into the use and interpretation of funnel plots by presenting an overview of the basic principles, pitfalls and considerations when applied to PROs, using examples from Dutch routine dialysis care.

Do small hospitals have lower quality? Evidence from the English NHS

We investigate the extent to which small hospitals are associated with lower quality. We first take a patient perspective, and test if, controlling for casemix, patients admitted to small hospitals receive lower quality than those admitted to larger hospitals. We then investigate if differences in quality between large and small hospitals can be explained by hospital characteristics such as hospital type and staffing. We use a range of quality measures including hospital mortality rates (overall and for specific conditions), hospital acquired infection rates, waiting times for emergency patients, and patient perceptions of the care they receive. We find that small hospitals, with fewer than 400 beds, are generally not associated with lower quality before or after controlling for hospital characteristics. The only exception is heart attack mortality, which is generally higher in small hospitals.

Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability

OBJECTIVES

The growth of COVID-19 infections in England raises questions about system vulnerability. Several factors that vary across geographies, such as age, existing disease prevalence, medical resource availability and deprivation, can trigger adverse effects on the National Health System during a pandemic. In this paper, we present data on these factors and combine them to create an index to show which areas are more exposed. This technique can help policy makers to moderate the impact of similar pandemics.

DESIGN

We combine several sources of data, which describe specific risk factors linked with the outbreak of a respiratory pathogen, that could leave local areas vulnerable to the harmful consequences of large-scale outbreaks of contagious diseases. We combine these measures to generate an index of community-level vulnerability.

SETTING

91 Clinical Commissioning Groups (CCGs) in England.

MAIN OUTCOME MEASURES

We merge 15 measures spatially to generate an index of community-level vulnerability. These measures cover prevalence rates of high-risk diseases; proxies for the at-risk population density; availability of staff and quality of healthcare facilities.

RESULTS

We find that 80% of CCGs that score in the highest quartile of vulnerability are located in the North of England (24 out of 30). Here, vulnerability stems from a faster rate of population ageing and from the widespread presence of underlying at-risk diseases. These same areas, especially the North-East Coast areas of Lancashire, also appear vulnerable to adverse shocks to healthcare supply due to tighter labour markets for healthcare personnel. Importantly, our index correlates with a measure of social deprivation, indicating that these communities suffer from long-standing lack of economic opportunities and are characterised by low public and private resource endowments.

CONCLUSIONS

Evidence-based policy is crucial to mitigate the health impact of pandemics such as COVID-19. While current attention focuses on curbing rates of contagion, we introduce a vulnerability index combining data that can help policy makers identify the most vulnerable communities. We find that this index is positively correlated with COVID-19 deaths and it can thus be used to guide targeted capacity building. These results suggest that a stronger focus on deprived and vulnerable communities is needed to tackle future threats from emerging and re-emerging infectious disease.

Determinants of nursing home choice: Does reported quality matter?

Quality report cards addressing information asymmetry in the health care market have become a popular strategy used by policymakers to improve the quality of care for older people. Using individual level data from the largest German sickness fund merged with institutional level data, we examine the relationship between reported nursing home quality, as measured by recently introduced report cards, nursing home prices, nursing home's location, and the individual choice of nursing homes. Report cards were stepwise introduced as of 2009, and we use a sample of 2010 that includes both homes that had been evaluated at that time and that had not yet been. Thus, we can distinguish between institutions with above and below average ratings as well as nonrated nursing homes. We find that the probability of choosing a nursing home decreases in distance and price. However, we find no economically significant effect of reported quality on individuals' choice of nursing homes.

Using EQ-5D Data to Measure Hospital Performance: Are General Population Values Distorting Patients' Choices?

Background. The English National Health Service publishes hospital performance indicators based on average postoperative EQ-5D index scores after hip replacement surgery to inform prospective patients' choices of hospital. Unidimensional index scores are derived from multidimensional health-related quality-of-life data using preference weights estimated from a sample of the UK general population. This raises normative concerns if general population preferences differ from those of the patients who are to be informed. This study explores how the source of valuation affects hospital performance estimates. Methods. Four different value sets reflecting source of valuation (general population v. patients), valuation technique (visual analog scale [VAS] v. time tradeoff [TTO]), and experience with health states (currently experienced vs. experimentally estimated) were used to derive and compare performance estimates for 243 hospitals. Two value sets were newly estimated from EQ-5D-3L data on 122,921 hip replacement patients and 3381 members of the UK general public. Changes in hospital ranking (nationally) and performance outlier status (nationally; among patients' 5 closest hospitals) were compared across valuations. Results. National rankings were stable under different valuations (rank correlations >0.92). Twenty-three (9.5%) hospitals changed outlier status when using patient VAS valuations instead of general population TTO valuations, the current approach. Outlier status also changed substantially at the local level. This was explained mostly by the valuation technique, not the source of valuations or experience with the health states. Limitations. No patient TTO valuations were available. The effect of value set characteristics could be established only through indirect comparisons. Conclusion. Different value sets may lead to prospective patients choosing different hospitals. Normative concerns about the use of general population valuations are not supported by empirical evidence based on VAS valuations.

Low risk, high reward? Repeated competitive biddings with multiple winners in health care

We study physiotherapy providers' prices in repeated competitive biddings where multiple providers are accepted in geographical districts. Historically, only very few districts have rejected any providers. We show that this practice increased prices and analyze the effects the risk of rejection has on prices. Our data are derived from three subsequent competitive biddings. The results show that rejecting at least one provider decreased prices by more than 5% in the next procurement round. The results also indicate that providers have learned to calculate their optimal bids, which has also increased prices. Further, we perform counterfactual policy analysis of a capacity-rule of acceptance. The analysis shows that implementing a systematic acceptance rule results in a trade-off between direct cost savings and service continuity at patients' usual providers.

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.

The use of digitally collected patient-reported outcome measures for newly operated patients with total knee and hip replacements to improve post-treatment recovery: study protocol for a randomized controlled trial

Background

The number of total knee replacements (TKRs) and total hip replacements (THRs) has been increasing noticeably in high-income countries, such as Germany. In particular, the number of revisions is expected to rise because of higher life expectancy and procedures performed on younger patients, impacting the budgets of health-care systems. Quality transparency is the basis of holistic patient pathway optimization. Nevertheless, a nation-wide cross-sectoral assessment of quality from a patient perspective does not yet exist. Several studies have shown that the use of patient-reported outcome measures (PROMs) is effective for measuring quality and monitoring post-treatment recovery. For the first time in Germany, we test whether early detection of critical recovery paths using PROMs after TKR/THR improves the quality of care in a cost-effective way and can be recommended for implementation into standard care.

Methods/design

The study is a two-arm multi-center patient-level randomized controlled trial. Patients from nine hospitals are included in the study. Patient-centered questionnaires are employed to regularly measure digitized PROMs of TKR/THR patients from the time of hospital admission until 12 months post-discharge. An expert consortium has defined PROM alert thresholds at 1, 3, and 6 months to signal critical recovery paths after TKR/THR. An algorithm alerts study assistants if patients are not recovering in line with expected recovery paths. The study assistants contact patients and their physicians to investigate and, if needed, adjust the post-treatment protocol. When sickness funds’ claims data are added, the cost-effectiveness of the intervention can be analyzed.

Discussion

The study is expected to deliver an important contribution to test PROMs as an intervention tool and examine the determinants of high-quality endoprosthetic care. Depending on a positive and cost-effective impact, the goal is to transfer the study design into standard care. During the trial design phase, several insights have been discovered, and there were opportunities for efficient digital monitoring limited by existing legacy care models. Digitalization in hospital processes and the implementation of digital tools still represent challenges for hospital personnel and patients. Furthermore, data privacy regulations and the separation between the in- and outpatient sector are roadblocks to effectively monitor and assess quality along the full patient pathway.

Trial registration

German Clinical Trials Register: DRKS00019916. Registered November 26, 2019 – retrospectively registered.

Hospital and Surgeon Variation in Patient-reported Functional Outcomes After Lumbar Spine Fusion: A Statewide Evaluation

STUDY DESIGN

Statewide retrospective cohort study using prospectively collected data from the Spine Care and Outcomes Assessment Program, capturing ∼75% of the state's spine fusion procedures.

OBJECTIVE

The aim of this study was to estimate the variation in patient-reported outcomes (PROs) 1 year after elective lumbar fusion surgery across surgeons and hospitals; and to discuss the potential impact of guiding patient selection using a PRO prediction tool.

SUMMARY OF BACKGROUND DATA

Despite an increasing interest in incorporating PROs as part of the move toward value-based payment and to improve quality, limited evidence exists on how PROs vary across hospitals and surgeons, a key aspect of using these metrics for quality profiling.

METHODS

We examined patient-reported functional improvement (≥15-point reduction in the Oswestry Disability Index [ODI]) and minimal disability (reaching ≤22 on the ODI) 1 year after surgery in 17 hospitals and 58 surgeons between 2012 and 2017. Outcomes were risk-adjusted for patient characteristics with multiple logistic regressions and reliability-adjusted using hierarchical models.

RESULTS

Of the 737 patients who underwent lumbar fusion (mean [SD] age, 63 [12] years; 60% female; 84% had stenosis; 70% had spondylolisthesis), 58.7% achieved functional improvement and 42.5% reached minimal disability status at 1 year. After adjusting for patient factors, there was little variation between hospitals and surgeons (maximum interclass correlation was 3.5%), and this variation became statistically insignificant after further reliability adjustment. Avoiding operation on patients with <50% chance of functional improvement may reduce current surgical volume by 63%.

CONCLUSION

Variations in PROs across hospitals and surgeons were mainly driven by differences in patient populations undergoing lumbar fusion, suggesting that PROs may not be useful indicators of hospital or surgeon quality. Careful patient selection using validated prediction tools may decrease differences in outcomes across hospitals and providers and improve overall quality, but would significantly reduce surgical volumes.

LEVEL OF EVIDENCE

3.

Subjective and objective quality and choice of hospital: Evidence from maternal care services in Germany

We study patient choice of healthcare provider based on both objective and subjective quality measures in the context of maternal care hospital services in Germany. Objective measures are obtained from publicly reported clinical indicators, while subjective measures are based on satisfaction scores from a large and nationwide patient survey. We merge both quality metrics to detailed hospital discharge records and quantify the additional distance expectant mothers are willing to travel to give birth in maternity clinics with higher reported quality. Our results reveal that patients are on average willing to travel 0.1-2.7 additional kilometers for a one standard deviation increase in quality. Patients respond to both objective and subjective quality measures, suggesting that patient satisfaction scores may constitute important complements to clinical indicators when choosing provider.

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.