Location, quality and choice of hospital: Evidence from England 2002-2013

Quantifying the impact of hospital catchment area definitions on hospital admissions forecasts: COVID-19 in England, September 2020-April 2021

BACKGROUND

Defining healthcare facility catchment areas is a key step in predicting future healthcare demand in epidemic settings. Forecasts of hospitalisations can be informed by leading indicators measured at the community level. However, this relies on the definition of so-called catchment areas or the geographies whose populations make up the patients admitted to a given hospital, which are often not well-defined. Little work has been done to quantify the impact of hospital catchment area definitions on healthcare demand forecasting.

METHODS

We made forecasts of local-level hospital admissions using a scaled convolution of local cases (as defined by the hospital catchment area) and delay distribution. Hospital catchment area definitions were derived from either simple heuristics (in which people are admitted to their nearest hospital or any nearby hospital) or historical admissions data (all emergency or elective admissions in 2019, or COVID-19 admissions), plus a marginal baseline definition based on the distribution of all hospital admissions. We evaluated predictive performance using each hospital catchment area definition using the weighted interval score and considered how this changed by the length of the predictive horizon, the date on which the forecast was made, and by location. We also considered the change, if any, in the relative performance of each definition in retrospective vs. real-time settings, or at different spatial scales.

RESULTS

The choice of hospital catchment area definition affected the accuracy of hospital admission forecasts. The definition based on COVID-19 admissions data resulted in the most accurate forecasts at both a 7- and 14-day horizon and was one of the top two best-performing definitions across forecast dates and locations. The "nearby" heuristic also performed well, but less consistently than the COVID-19 data definition. The marginal distribution baseline, which did not include any spatial information, was the lowest-ranked definition. The relative performance of the definitions was larger when using case forecasts compared to future observed cases. All results were consistent across spatial scales of the catchment area definitions.

CONCLUSIONS

Using catchment area definitions derived from context-specific data can improve local-level hospital admission forecasts. Where context-specific data is not available, using catchment areas defined by carefully chosen heuristics is a sufficiently good substitute. There is clear value in understanding what drives local admissions patterns, and further research is needed to understand the impact of different catchment area definitions on forecast performance where case trends are more heterogeneous.

The Effects of Distance, Time, and Nonspatial Factors on Hemodialysis Access in Qatar

Background A long distance and time spent traveling to a hemodialysis (HD) center and other factors, such as comorbidities, can significantly impact HD patient compliance, satisfaction, and cost. Uncertainty about HD-dependent patients' geographical location may lead to inappropriate distribution of HD centers. The present study investigates travel time, distance, and nonspatial factors affecting HD center accessibility within a 30-km radius in the State of Qatar. Materials and methods The study included all HD-dependent patients residing in Qatar between March 1, 2020, and December 31, 2021. There were 921 patients dialyzed in six HD centers across Qatar. Our methodology incorporated descriptive and analytical cross-sectional designs to accurately identify the shortest routes and quickest travel times. We used two applications (Maptive {Vancouver, WA: BatchGeo LLC} and Google Maps {Mountain View, CA: Google LLC}) and marked a driving distance of 30 km as the main assessment scale and measurement standard, allowing optimum spatial accessibility determination. Results On average, patients traveled approximately 19±4.2 km, requiring almost 17.6±3.4 minutes to reach the assigned HD center three times per week. Based on geographic-spatial accessibility analysis, patients living in Umm Salal drove 31.4±3.5 km in 32.4±4.7 minutes, Al Daayen patients drove 30.2 km in 25.3 minutes, and others even drove more than 70 km to access HD sessions. Approximately 37.8% of Qatar's municipalities had no HD centers within their boundaries, but nearly 47% of HD-dependent patients lived in those municipalities. Additionally, some municipalities had HD centers; however, their general population density was less than 100 inhabitants/km2, and they had relatively few patients requiring regular HD. We noted a statistically significant correlation between the patients' residences and the locations of HD centers, whether they were located within or outside municipalities. Also, nonspatial factors may have affected the likelihood of reaching a hemodialysis center within a 30-km distance, including two or more comorbid conditions, having HD for at least five years, living in a municipality with more than 1,000 inhabitants/km2, being female, and attending dialysis centers that are more than 30 km away. Conclusion Although the available HD centers were sufficient for the present number of patients requiring HD, HD center locations did not match the patients' distribution, leading to difficulties for some patients. Understanding the impact of this geographic mismatch, population density, and other spatial factors helps significantly improve patient care and satisfaction at minimal cost. Furthermore, considering all these factors is crucial when planning new centers to achieve higher satisfaction and compliance as well as better health care.

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.

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.

Outcomes of Veterans Treated in Veterans Affairs Hospitals vs Non-Veterans Affairs Hospitals

Importance

Many veterans enrolled in the Veterans Affairs (VA) health care system have access to non-VA care through insurance and VA-purchased community care. Prior comparisons of VA and non-VA hospital outcomes have been limited to subpopulations.

Objective

To compare outcomes for 6 acute conditions in VA and non-VA hospitals for younger and older veterans using VA and all-payer discharge data.

Design, Setting, and Participants

This cohort study used a repeated cross-sectional analysis of hospitalization records for acute myocardial infarction (AMI), coronary artery bypass graft (CABG), gastrointestinal (GI) hemorrhage, heart failure (HF), pneumonia, and stroke. Participants included VA enrollees from 11 states at VA and non-VA hospitals from 2012 to 2017. Analysis was conducted from July 1, 2022, to October 18, 2023.

Exposures

Treatment in VA or non-VA hospital.

Main Outcome and Measures

Thirty-day mortality, 30-day readmission, length of stay (LOS), and costs. Average treatment outcomes of VA hospitals were estimated using inverse probability weighted regression adjustment to account for selection into hospitals. Models were stratified by veterans' age (aged less than 65 years and aged 65 years and older).

Results

There was a total of 593 578 hospitalizations and 414 861 patients with mean (SD) age 75 (12) years, 405 602 males (98%), 442 297 hospitalizations of non-Hispanic White individuals (75%) and 73 155 hospitalizations of non-Hispanic Black individuals (12%) overall. VA hospitalizations had a lower probability of 30-day mortality for HF (age ≥65 years, -0.02 [95% CI, -0.03 to -0.01]) and stroke (age <65 years, -0.03 [95% CI, -0.05 to -0.02]; age ≥65 years, -0.05 [95% CI, -0.07 to -0.03]). VA hospitalizations had a lower probability of 30-day readmission for CABG (age <65 years, -0.04 [95% CI, -0.06 to -0.01]; age ≥65 years, -0.05 [95% CI, -0.07 to -0.02]), GI hemorrhage (age <65 years, -0.04 [95% CI, -0.06 to -0.03]), HF (age <65 years, -0.05 [95% CI, -0.07 to -0.03]), pneumonia (age <65 years, -0.04 [95% CI, -0.06 to -0.03]; age ≥65 years, -0.03 [95% CI, -0.04 to -0.02]), and stroke (age <65 years, -0.11 [95% CI, -0.13 to -0.09]; age ≥65 years, -0.13 [95% CI, -0.16 to -0.10]) but higher probability of readmission for AMI (age <65 years, 0.04 [95% CI, 0.01 to 0.06]). VA hospitalizations had a longer mean LOS and higher costs for all conditions, except AMI and stroke in younger patients.

Conclusions and Relevance

In this cohort study of veterans, VA hospitalizations had lower mortality for HF and stroke and lower readmissions, longer LOS, and higher costs for most conditions compared with non-VA hospitalizations with differences by condition and age group. There were tradeoffs between better outcomes and higher resource use in VA hospitals for some conditions.

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.

Identifying the Drivers of Inter-Regional Patients' Mobility: An Analysis on Hospital Beds Endowment

BACKGROUND

In a Beveridgean decentralized healthcare system, like the Italian one, where regions are responsible for their own health planning and financing, the analysis of patients' mobility appears very interesting as it has economic and social implications. The study aims to analyze both patients' mobility for hospital rehabilitation and if the beds endowment is a driver for these flows; Methods: From 2011 to 2019, admissions data were collected from the Hospital Discharge Cards database of the Italian Ministry of Health, population data from the Italian National Institute of Statistics and data on beds endowment from the Italian Ministry of Health website. To evaluate patients' mobility, we used Gandy's Nomogram, while to assess if beds endowments are mobility drivers, we created two matrices, one with attraction indexes (AI) and one with escape indexes (EI). The beds endowment, for each Italian region, was correlated with AI and EI. Spearman's test was carried out through STATA software; Results: Gandy's Nomogram showed that only some northern regions had good hospital planning for rehabilitation. A statistically significant correlation between beds endowment and AI was found for four regions and with EI for eight regions; Conclusions: Only some northern regions appear able to satisfy the care needs of their residents, with a positive attractions minus escapes epidemiological balance. The beds endowment seems to be a driver of patients' mobility, mainly for escapes. Certainly, the search for mobility drivers needs further investigation given the situation in Molise and Basilicata.

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.

Evaluation of medical services from the perspective of COVID-19 vaccine demand satisfaction in Hangzhou, China

The outbreak of COVID-19 has had a huge global impact, and it continues to test the resilience of medical services to emergencies worldwide. In the current post-epidemic era, vaccination has become a highly effective strategy to prevent the spread of COVID-19. However, using conventional mathematical models to evaluate the spatial distribution of medical resources, including vaccination, ignore people's behaviors and choices and make simplifications to the real world. In this study, we use an enhanced model based on the Theory of People Behavior (TPB) to perform a macro analysis of the satisfaction ability of medical resources for vaccination in Hangzhou, China, and attribute the city to a three-level structure. According to the allocation, the supply capacity of vaccination sites is calculated and divided into four categories (good, normal, not bad, and bad). Meanwhile, we raise an assumption based on the result and the general development law of the city and analyze the reasons for the impact of personal behavior on the spatial distribution of medical resources, as well as the relationship between the demand distribution and spatial distribution of medical resources and future development strategies. It is considered that the overall medical resources, especially vaccination in Hangzhou, feature the situation of central supply overflow, and are found to hardly meet the needs of population points in surrounding areas, requiring a more flexible strategy to allocate facilities in these areas.

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.

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.

Relationship between continuity of care and clinical outcomes in patients with dyslipidemia in Korea: a real world claims database study

Dyslipidemia is a risk factor for atherosclerotic cardiovascular disease and requires proactive management. This study aimed to investigate the association between care continuity and the outcomes of patients with dyslipidemia. We conducted a retrospective cohort study on patients with dyslipidemia by employing the Korea National Health Insurance claims database during the period 2007–2018. The Continuity of Care Index (COCI) was used to measure continuity of care. We considered incidence of atherosclerotic cardiovascular disease as a primary outcome. A Cox's proportional hazards regression model was used to quantify risks of primary outcome. There were 236,486 patients newly diagnosed with dyslipidemia in 2008 who were categorized into the high and low COC groups depending on their COCI. The adjusted hazard ratio for the primary outcome was 1.09 times higher (95% confidence interval: 1.06–1.12) in the low COC group than in the high COC group. The study shows that improved continuity of care for newly-diagnosed dyslipidemic patients might reduce the risk of atherosclerotic cardiovascular disease.

Hospital volume allocation: integrating decision maker and patient perspectives

Planning problems in healthcare systems have received greater attention in the last decade, especially because of the concerns recently raised about the scattering of surgical interventions among a wide number of different facilities that can undermine the quality of the outcome due to the volume-outcome association. In this paper, an approach to plan the amount of surgical interventions that a facility has to perform to assure a low adjusted mortality rate is proposed. The approach explicitly takes into account the existing interaction among patients’ choices and decision makers’ planning decisions. The first objective of the proposed approach is to find a solution able to reach quality in health outcomes and patients’ adherence. The second objective is to investigate the difference among solutions that are identified as optimal by either only one of the actors’ perspective, i.e., decision makers and patients, or by considering both the perspectives simultaneously. Following these objectives, the proposed approach is applied to a case study on Italian colon cancer interventions performed in 2014. Results confirm a variation in the hospital planned volumes when considering patients’ behaviour together with the policy maker plan, especially due to personal preferences and lack of information about hospital quality.

Data analysis of ambient intelligence in a healthcare simulation system: a pilot study in high-end health screening process improvement

Background

This study aimed to reduce the total waiting time for high-end health screening processes.

Method

The subjects of this study were recruited from a health screening center in a tertiary hospital in northern Taiwan from September 2016 to February 2017, where a total of 2342 high-end customers participated. Three policies were adopted for the simulation.

Results

The first policy presented a predetermined proportion of customer types, in which the total waiting time was increased from 72.29 to 83.04 mins. The second policy was based on increased bottleneck resources, which provided significant improvement, decreasing the total waiting time from 72.29 to 28.39 mins. However, this policy also dramatically increased the cost while lowering the utilization of this health screening center. The third policy was adjusting customer arrival times, which significantly reduced the waiting time—with the total waiting time reduced from 72.29 to 55.02 mins. Although the waiting time of this policy was slightly longer than that of the second policy, the additional cost was much lower.

Conclusions

Scheduled arrival intervals could help reduce customer waiting time in the health screening department based on the “first in, first out” rule. The simulation model of this study could be utilized, and the parameters could be modified to comply with different health screening centers to improve processes and service quality.

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.

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.

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.

Evaluating the effect of hierarchical medical system on health seeking behavior: A difference-in-differences analysis in China

The unbalanced allocation of healthcare resources and the underutilization of primary care facilities are the core problems that restrict the current healthcare reforms in China. In order to encourage residents to go to primary care facilities, China implemented the Hierarchical Medical System (HMS) in 2015. This study aims to evaluate the effect of HMS on health seeking behavior in China using panel data. Statistics for the study were derived from China Family Panel Studies (CFPS) 2012, 2014, 2016 and 2018, and China health and family planning statistical yearbook 2012, 2014, 2016 and 2018. We employed the difference-in-differences (DID) model with multiple periods. In total, 61,932 residents were incorporated for a final sample covered 25 provinces. The results indicated that the implementation of HMS had a significantly positive effect on the probability of urban residents going to primary care facilities for contact. However, the effect of HMS was not significant for rural residents. Basic health insurance was a significant factor for directing residents to primary care facilities. Self-assessed health, chronic disease, economic level and educational status were also found to be focal factors of health seeking behavior. In conclusion, the introduction of HMS has led to improved health seeking behavior and is worth putting more effort into. For policy makers, basic medical insurance is still an important health policy that enables systematic health seeking behavior. Initiatives to continue to expand the adjustment range of economic incentives should be adopted to promote the implementation of HMS. However, the effect of HMS in chronic disease is poor and efforts to formulate chronic disease as a breakthrough to HMS should be carried out. Moreover, the government should increase the publicity of HMS.

Does price deregulation in a competitive hospital market damage quality?

Regulators may be hesitant to permit price competition in healthcare markets because of its potential to damage quality. We assess whether this fear is well founded by examining a reform that permitted Dutch health insurers to freely negotiate prices with hospitals. Unlike previous research on hospital competition that has relied on quality indicators for urgent treatments, we take advantage of a plausible absence of selection bias to identify the effect on the quality of elective procedures that should be more price responsive. Using data on all admissions for hip replacements to Dutch hospitals and a difference-in-differences comparison between more and less concentrated markets, we find no evidence that price deregulation in a competitive environment reduces quality measured by hip replacement readmission rates.

Is there scope for mixed markets in the provision of hospital care?

Market oriented reforms in hospital care have produced a variety of quasi markets that differ for the type of providers that are allowed to compete. Mixed markets, where public hospitals compete alongside private ones, are increasingly common, but the literature does not agree on their performances and their desirability. We review the contributions in this field by proposing a common framework which allows to account for the different approaches proposed to model public hospitals. In this paper we show under which conditions mixed markets perform better in terms of average quality, and we review the empirical literature to determine whether these conditions are met. In general, pure forms (private or public competition) are superior to mixed markets, unless patients interpret public hospitals as reference suppliers, and quality of care is important. The empirical evidence on these key questions shows that public hospitals behave differently from private organisations, but they are not necessarily less efficient. Research into patients choices seems to suggest that ownership is a value, but the empirical literature is still rather scant. From a policy point of view, our review suggests that there does not seem to be a clear answer to whether this market form should be used. Local conditions are going to play an important role.

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.

Primary health institutions preference by hypertensive patients: effect of distance, trust and quality of management in the rural Heilongjiang province of China

Background

Traditional “inverted triangle” healthcare resources allocation model in China has wasted a lot of health resources. The Chinese health reform began to strengthens the role of the primary health institutions in delivering primary health care especially in rural areas in the background of large development gap between urban-rural health and rapid growth in the incidence of chronic diseases in rural. We take hypertensive patients as an example, to verify the effect of policy implementation through distribution characteristics of rural primary health institutions preference of hypertensive patients and explore the influencing factor that promoting rationalized use of medical care for patients with chronic disease as well as rational allocation of health resources in rural areas.

Methods

A cross-sectional survey was conducted in Heilongjiang, a province in northeastern China by using a self-designed questionnaire. Stratified cluster sampling was used to choose 484 hypertensive patients from two villages in Heilongjiang province in 2010.

Results

About 88.4% of respondents reported preferred primary health institutions (83.5% preferred village clinics and 4.9% preferred township hospitals), 49.4% of respondents knew hypertension management administered by primary health institutions, 53.5% received hypertension education from primary care physicians, more than half of respondents reported that they didn’t receive telephone interviews and family visits from primary care physicians over the past 6 months. Residence closer to the primary health institutions (OR = 10.360), trust in village doctors (OR = 7.323), elders (OR = 3.001), and asked for return visits by primary health physicians (OR = 2.073) promote preferences for primary health institutions.

Conclusions: Accessibility to primary healthcare and doctor-patient trust stimulate patients to choose the primary health institutions. Primary health institutions should improve general approach to hypertension management and enhance the ability of providing basic public health services.

Electronic supplementary material

The online version of this article (10.1186/s12913-019-4465-7) contains supplementary material, which is available to authorized users.

Identification of Factors Influencing Out-of-county Hospitalizations in the New Cooperative Medical Scheme

Throughout the duration of the New Cooperative Medical Scheme (NCMS), it was found that an increasing number of rural patients were seeking out-of-county medical treatment, which posed a great burden on the NCMS fund. Our study was conducted to examine the prevalence of out-of-county hospitalizations and its related factors, and to provide a scientific basis for follow-up health insurance policies. A total of 215 counties in central and western China from 2008 to 2016 were selected. The total out-of-county hospitalization rate in nine years was 16.95%, which increased from 12.37% in 2008 to 19.21% in 2016 with an average annual growth rate of 5.66%. Its related expenses and compensations were shown to increase each year, with those in the central region being higher than those in the western region. Stepwise logistic regression reveals that the increase in out-of-county hospitalization rate was associated with region (X1), rural population (X2), per capita per year net income (X3), per capita gross domestic product (GDP) (X4), per capita funding amount of NCMS (X5), compensation ratio of out-of-county hospitalization cost (X6), per time average in-county (X7) and out-of-county hospitalization cost (X8). According to Bayesian network (BN), the marginal probability of high out-of-county hospitalization rate was as high as 81.7%. Out-of-county hospitalizations were directly related to X8, X3, X4 and X6. The probability of high out-of-county hospitalization obtained based on hospitalization expenses factors, economy factors, regional characteristics and NCMS policy factors was 95.7%, 91.1%, 93.0% and 88.8%, respectively. And how these factors affect out-of-county hospitalization and their interrelationships were found out. Our findings suggest that more attention should be paid to the influence mechanism of these factors on out-of-county hospitalizations, and the increase of hospitalizations outside the county should be reasonably supervised and controlled and our results will be used to help guide the formulation of proper intervention policies.

Bypassing health facilities in rural Mozambique: spatial, institutional, and individual determinants

BACKGROUND

Access to sexual and reproductive health (SRH) services is critical for such outcomes as pregnancy and birth, prenatal and neonatal mortality, maternal morbidity and mortality, and prevention of vertical transmission of infections like HIV. Health facilities are typically set up where they can efficiently serve the nearby targeted population. However, the actual utilization of health care can be complicated as people sometimes bypass the closest or nearby facilities for various reasons such as service quality. A better understanding of how people actually utilize health services can benefit future health resource allocation as well as health program planning.

METHODS

In this study, we use prenatal care as an example of a basic, widely available service to investigate women's choice and bypassing of SRH facilities as well as potential influencing factors at the geographic, clinic, household, and individual levels. The data come from a population-based survey of women of reproductive age in rural Mozambique. The spatial pattern of utilization of health clinics for prenatal care is explored by geographical information system (GIS)-based spatial analysis. Logistic regression is fitted to test the hypotheses regarding the effect of distance, service quality, and household/individual-level factors on the bypassing of the nearest clinic.

RESULTS

The results indicate that most women living near clinics tend to utilize the closest facilities for prenatal care and those who travel farther mainly do so to seek better services. Further, for women who live far from a clinic (> 5.5 km), service quality still plays an important role in the facility bypassing while the effect of distance is no longer significant. The bypassing of nearest facility is also affected by individual characteristics such as age, HIV status, and household economic conditions.

CONCLUSIONS

The findings help to better understand health facility choice and bypassing in developing settings, in general, and in resource-limited Sub-Saharan settings, in particular. They offer valuable guidance for future health resource allocation and health service planning.

Spatial Equilibrium Allocation of Urban Large Public General Hospitals Based on the Welfare Maximization Principle: A Case Study of Nanjing, China

This study aims to utilize the new gravity P-median model to conduct an empirical study for the spatial equilibrium layout of general hospitals in the urban area of Nanjing City, based on multiple requirements for spatial equilibrium, involving spatial equity-efficiency, service utility fairness, and utilization efficiency. The major results are as follows: (1) the new layout can achieve the goal of obtaining a proximate, high-quality medical service in 30 min even for those who reside on the outskirts, which is less than the current 65.6 min. Moreover, the new layout corresponds better to the population distribution and traffic network layout. (2) When compared with several typical characteristics of accessibility to hospitals, including severe gradient variation, five high-value centers, and the efficiency orientation in the current layout, the new demonstrates distinctive ones: comparatively moderate accessibility variation; more relatively high-value areas scattered in different parts of the city; more convenient accessibility on the outskirts; a better balance of the equitable appeal from the inhabitants residing in different areas. (3) The new layout can attain spatial equilibrium at a higher level, the representative indices to measure spatial equity, spatial efficiency, chance fairness, and utilization efficiency have been ameliorated by 54%, 13%, 63%, 14%, respectively. The study reveals that: (1) The new gravity P-median model has the validity and practicability in solving facility location and scale configuration problems with high time complexity, under complicated situations due to multiple targets and multi-agent competition. (2) The model can be applied to decision making related to public infrastructure planning in different types of development areas, by setting concerning parameters or making some minor adjustments to the model in different scenarios. Such research can provide some reference for the location-allocation problem of high-grade facilities in metropolises, and support the decision-making basis for urban infrastructure planning.

Cost-Effectiveness of Robot-assisted Radical Cystectomy Using a Propensity-matched Cohort

BACKGROUND

Health-related quality of life is important for patients undergoing radical cystectomy (RC).

OBJECTIVE

To determine the cost-effectiveness of robotic-assisted RC (RARC) compared to open cystectomy (OC) for bladder cancer and factors that contribute to cost-effectiveness.

DESIGN, SETTING, AND PARTICIPANTS

A decision analytic model was used to compare health-related quality of life and medical costs for RARCs with intracorporeal urinary diversion and OCs performed between 2007 and 2015.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Propensity matching was performed among 1322 cases to yield a final cohort of 100 RARC and 96 ORC cases. Probabilities were obtained from the clinical study data, while quality-adjusted life years (QALYs) and health utility values were derived from the literature. A complication, readmission, or transfusion was included in the 90-d time horizon model.

RESULTS AND LIMITATIONS

There were no differences between the groups in patient demographics, pathologic staging, or length of stay. Multivariable analysis revealed that the RARC group had fewer transfusions and complications compared to the OC group. The incremental cost-effectiveness ratio was $2969. RARC cost $2969 less per QALY when compared to OC. While RARC was $17000 more expensive, it also associated with an increase of 0.32 QALYs. One-way sensitivity analysis identified RARC as the preferred strategy if a complication can be prevented 74% of the time. RARC is preferred as long as it is 70% effective in preventing a transfusion. Two-way sensitivity analysis showed that as long as RARC can prevent complications and transfusions, it is the preferred cost-effective treatment when compared to OC. The study is limited by the omission of a societal perspective and the lack of health utility values for RC.

CONCLUSIONS

RARC is cost-effective compared to OC when the rates of complications and transfusions are significantly lower.

PATIENT SUMMARY

Bladder removal via a robotic approach is more expensive, but it improves health-related quality of life. Robotic surgery is cost-effective compared to an open approach for bladder removal if there are low rates of complications and blood transfusion.

Women's Preferences for Birthing Hospital in Denmark: A Discrete Choice Experiment

BACKGROUND

Free choice of hospital has been introduced in many healthcare systems to accommodate patient preferences and incentivize hospitals to compete; however, little is known about what patients actually prefer.

OBJECTIVES

This study assessed women's preferences for birthing hospital in Denmark by quantifying the utility and trade-offs of hospital attributes.

METHODS

We conducted a discrete-choice experiment survey with 12 hypothetical scenarios in which women had to choose between three hospitals characterized by five attributes: continuity of midwifery care, availability of a neonatal intensive care unit (NICU), hospital services offered, level of specialization to handle rare events, and travel time. A random parameter logit model was used to estimate the utility and marginal willingness to travel (WTT) for improvements in other hospital attributes.

RESULTS

A total of 517 women completed the survey. Significant preferences were expressed for all attributes (p < 0.01), with the availability of a NICU being the most important driver of women's preferences; women were willing to travel 30 more minutes (95% confidence interval 28-32) to reach a hospital with a highly specialized NICU. The subgroup analyses revealed differences in WTT, with substantial heterogeneity due to prior experience with giving birth and regarding risk attitude and health literacy.

CONCLUSION

A high specialization level was the most influential factor for women without previous birth experience and for risk-averse individuals but not for women with a high health literacy score. Hence, more information about the woman's risk profile and services required could play a role in affecting hospital choice.

Managing imperfect competition by pay for performance and reference pricing

I study a managed health service market where differentiated providers compete for consumers by choosing multiple service qualities, and where copayments that consumers pay and payments that providers receive for services are set by a payer. The optimal regulation scheme is two-sided. On the demand side, it justifies and clarifies value-based reference pricing. On the supply side, it prescribes pay for performance when consumers misperceive service benefits or providers have intrinsic quality incentives. The optimal bonuses are expressed in terms of demand elasticities, service technology, and provider characteristics. However, pay for performance may not outperform prospective payment when consumers are rational and providers are profit maximizing, or when one of the service qualities is not contractible.

Socioeconomic inequality of access to healthcare: Does choice explain the gradient?

Equity of access is a key policy objective in publicly-funded healthcare systems. However, observed inequalities of access by socioeconomic status may result from differences in patients' choices. Using data on non-emergency coronary revascularisation procedures in the English National Health Service, we found substantive differences in waiting times within public hospitals between patients with different socioeconomic status: up to 35% difference, or 43 days, between the most and least deprived population quintile groups. Using selection models with differential distances as identification variables, we estimated that only up to 12% of these waiting time inequalities can be attributed to patients' choices of hospital and type of treatment (heart bypass versus stent). Residual inequality, after allowing for choice, was economically significant: patients in the least deprived quintile group benefited from shorter waiting times and the associated health benefits were worth up to £850 per person.