The effect of waiting time and distance on hospital choice for English cataract patients

The Relationship Between Static Characteristics of Physicians and Patient Consultation Volume in Internet Hospitals: Quantitative Analysis

BACKGROUND

Internet medical treatment, also known as telemedicine, represents a paradigm shift in health care delivery. This contactless model allows patients to seek medical advice remotely, often before they physically visit a doctor's clinic. Herein, physicians are in a relatively passive position, as patients browse and choose their health care providers. Although a wealth of experience is undoubtedly a draw for many patients, it remains unclear which specific facets of a doctor's credentials and accomplishments patients prioritize during their selection process.

OBJECTIVE

Our primary aim is to delve deeper into the correlation between physicians' static characteristics-such as their qualifications, experiences, and profiles on the internet-and the number of patient visits they receive. We seek to achieve this by analyzing comprehensive internet hospital data from public hospitals. Furthermore, we aim to offer insights into how doctors can present themselves more effectively on web-based platforms, thereby attracting more patients and improving overall patient satisfaction.

METHODS

We retrospectively gathered web-based diagnosis and treatment data from the First Affiliated Hospital of Guangxi Medical University in 2023. These data underwent rigorous analysis, encompassing basic descriptive statistics, correlation analyses between key factors in doctors' internet-based introductions, and the number of patient consultation visits. Additionally, we conducted subgroup analyses to ascertain the independence of these vital factors. To further distill the essence from these data, we used nonnegative matrix factorization to identify crucial demographic characteristics that significantly impact patient choice.

RESULTS

The statistical results suggested that there were significant differences in the distribution of consultation volume (P<.001), and the correlation analysis results suggested that there was a strong correlation between the two groups of data (ρ=0.93; P<.001). There was a correlation between the richness of a profile and popularity (P<.001). Patients were more interested in physicians with advanced titles, doctoral degrees, social activities, and scientific achievements (P<.001) as well as other institutional visit experiences (P=.003). More prosperous social activities, scientific achievements, experiences of other institutional visits, and awards were more common among people with advanced professional titles. Doctoral degrees remained attractive to patients when data were limited to senior physicians (P<.001). Patients trusted the medical staff with advanced titles, social activities, scientific achievements, and doctoral degrees (P<.001).

CONCLUSIONS

Patient preferences for choosing a health care provider differed significantly between free and paid consultations. Notably, patients tended to trust doctors with advanced professional titles more and were more likely to seek out those with doctoral qualifications over other professional ranks. Additionally, physicians who actively participated in social events and scientific endeavors often had an advantage in attracting new patients. Given these insights, doctors who invest in enhancing their personal and professional experiences within these domains are likely to see increased popularity and patient satisfaction.

Who responds to longer wait times? The effects of predicted emergency wait times on the health and volume of patients who present for care

Healthcare is often free at the point-of-care so that price does not deter patients. However, the dis-utility from waiting for care that often occurs could also lead to deterrence. I investigate responses in the volume and types of patients that demand emergency care when predicted waiting times quasi-randomly change. I leverage a discontinuity to compare emergency sites with similar predicted wait times but with different apparent wait times displayed to patients. I use impulse response functions estimated by local projections to estimate effects of predicted wait times on patient demand for care. An additional thirty minutes of predicted wait time results in 15% fewer waiting patients at urgent cares and 2% fewer waiting patients at emergency departments within three hours of display. Patients that stop using emergency care are also triaged as healthier. However, at very high predicted wait times, there are reductions in demand for all patients including sicker patients.

Social Medical Insurances, Choices of Medical Institutions and the 'Siphon Effect' in the Health Service Market: Evidence from 2021 Yangtze River Delta Region of China

Purpose

The siphon effect in the health service market is notably pronounced in many countries. How to measure and identify the determinants contributing to the siphon effect presents a substantial challenge. This study aimed to analyse the effect of two different social medical insurances, the Basic Medical Insurance System for Urban Employees (BMISUE), and the Basic Medical Insurance System for Urban and Rural Residents (BMISURR), on the siphon effect in the health services market.

Methods

The data used in this study were from the 2021 Health Life Satisfaction Survey of Yangtze River Delta (HLSSYRD) conducted by Shanghai Jiao Tong University. The logistic model was used to evaluate the association between social medical insurances and individual choices of medical institutions, and the Propensity Score Matching method (PSM) was used to check the robustness of basic results.

Results

Residents covered by BMISUE were more likely to choose a general hospital when they first sought medical treatment (OR = 5.377, 95% CI: 4.887, 5.915) relative to those insured by BMISURR. Further analysis showed that BMISUE would accelerate the siphon effect of general hospitals, people insured by BMISUE were still more likely to choose general hospitals despite being close to primary hospitals compared to those insured by BMISURR (OR = 3.240, 95% CI: 2.945, 3.565). Heterogeneity analysis indicated BMISUE had a greater impact on residents aged 15-59 years and those with high income compared to older people and individuals with low income.

Conclusion

Different social medical insurances can substantially affect residents' first choice of medical institutions. BMISUE with higher benefits level could exacerbate the siphon effect in the health service market. More equitable medical security system should be strengthened to bridge the benefits gap between BMISUE and BMISURR.

Separating the wheat from the chaff: How to measure hospital quality in routine data?

OBJECTIVE

To measure hospital quality based on routine data available in many health care systems including the United States, Germany, the United Kingdom, Scandinavia, and Switzerland.

DATA SOURCES AND STUDY SETTING

We use the Swiss Medical Statistics of Hospitals, an administrative hospital dataset of all inpatient stays in acute care hospitals in Switzerland for the years 2017-2019.

STUDY DESIGN

We study hospital quality based on quality indicators used by leading agencies in five countries (the United States, the United Kingdom, Germany, Austria, and Switzerland) for two high-volume elective procedures: inguinal hernia repair and hip replacement surgery. We assess how least absolute shrinkage and selection operator (LASSO), a supervised machine learning technique for variable selection, and Mundlak corrections that account for unobserved heterogeneity between hospitals can be used to improve risk adjustment and correct for imbalances in patient risks across hospitals.

DATA COLLECTION/EXTRACTION METHODS

The Swiss Federal Statistical Office collects annual data on all acute care inpatient stays including basic socio-demographic patient attributes and case-level diagnosis and procedure codes.

PRINCIPAL FINDINGS

We find that LASSO-selected and Mundlak-corrected hospital random effects logit models outperform common practice logistic regression models used for risk adjustment. Besides the more favorable statistical properties, they have superior in- and out-of-sample explanatory power. Moreover, we find that Mundlak-corrected logits and the more complex LASSO-selected models identify the same hospitals as high or low-quality offering public health authorities a valuable alternative to standard logistic regression models. Our analysis shows that hospitals vary considerably in the quality they provide to patients.

CONCLUSION

We find that routine hospital data can be used to measure clinically relevant quality indicators that help patients make informed hospital choices.

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.

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.

The effect of hospital spending on waiting times

Long waiting times have been a persistent policy issue in the United Kingdom that the COVID-19 pandemic has exacerbated. This study analyses the causal effect of hospital spending on waiting times in England using a first-differences panel approach and an instrumental variable strategy to deal with residual concerns for endogeneity. We use data from 2014 to 2019 on waiting times from general practitioner referral to treatment (RTT) measured at the level of local purchasers (known as Clinical Commissioning Groups). We find that increases in hospital spending by local purchasers of 1% reduce median RTT waiting time for patients whose pathway ends with a hospital admission (admitted pathway) by 0.6 days but the effect is not statistically significant at 5% level (only at the 10% level). We also find that higher hospital spending does not affect the RTT waiting time for patients whose pathway ends with a specialist consultation (non-admitted pathway). Nor does higher spending have a statistically significant effect on the volume of elective activity for either pathway. Our findings suggest that higher spending is no guarantee of higher volumes and lower waiting times, and that additional mechanisms need to be put in place to ensure that increased spending benefits elective patients.

Patient Travel Distance to Neurologist Visits

BACKGROUND AND OBJECTIVES

The density of neurologists within a given geographic region varies greatly across the United States. We aimed to measure patient travel distance and travel time to neurologist visits, across neurologic conditions and subspecialties. Our secondary goal was to identify factors associated with long-distance travel for neurologic care.

METHODS

We performed a cross-sectional analysis using a 2018 Medicare sample of patients with at least 1 outpatient neurologist visit. Long-distance travel was defined as driving distance ≥50 miles 1-way to the visit. Travel time was measured as driving time in minutes. Multilevel generalized linear mixed models with logistic link function, which accounted for clustering of patients within hospital referral region and allowed modeling of region-specific random effects, were used to determine the association of patient and regional characteristics with long-distance travel.

RESULTS

We identified 563,216 Medicare beneficiaries with a neurologist visit in 2018. Of them, 96,213 (17%) traveled long distance for care. The median driving distance and time were 81.3 (interquartile range [IQR]: 59.9-144.2) miles and 90 (IQR: 69-149) minutes for patients with long-distance travel compared with 13.2 (IQR: 6.5-23) miles and 22 (IQR: 14-33) minutes for patients without long-distance travel. Comparing across neurologic conditions, long-distance travel was most common for nervous system cancer care (39.6%), amyotrophic lateral sclerosis [ALS] (32.1%), and MS (22.8%). Many factors were associated with long-distance travel, most notably low neurologist density (first quintile: OR 3.04 [95% CI 2.41-3.83] vs fifth quintile), rural setting (4.89 [4.79-4.99]), long-distance travel to primary care physician visit (3.6 [3.51-3.69]), and visits for ALS and nervous system cancer care (3.41 [3.14-3.69] and 5.27 [4.72-5.89], respectively). Nearly one-third of patients bypassed the nearest neurologist by 20+ miles, and 7.3% of patients crossed state lines for neurologist care.

DISCUSSION

We found that nearly 1 in 5 Medicare beneficiaries who saw a neurologist traveled ≥50 miles 1-way for care, and travel burden was most common for lower-prevalence neurologic conditions that required coordinated multidisciplinary care. Important potentially addressable predictors of long-distance travel were low neurologist density and rural location, suggesting interventions to improve access to care such as telemedicine or neurologic subspecialist support to local neurologists. Future work should evaluate differences in clinical outcomes between patients with long-distance travel and those without.

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.

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.

Regional practice variation in pelvic organ prolapse surgery in Tuscany, Italy: a retrospective cohort study on administrative health data

OBJECTIVES

To explore determinants of practice variation in both access, and quality and efficiency of surgical care for pelvic organ prolapse (POP).

DESIGN AND SETTING

A retrospective cohort study employing administrative health data from the Tuscany region, Italy.

PARTICIPANTS

All women over 40 years hospitalised for apical/multicompartmental POP reconstructive surgery (excluding anterior/posterior colporrhaphy without concomitant hysterectomy) from January 2017 to December 2019.

OUTCOMES

We first computed treatment rates just for women residing in Tuscany (n=2819) and calculated the Systematic Component of Variation (SCV) to explore variation in access to care among health districts. Then, using the full cohort (n=2959), we ran multilevel models for the average length of stay and reoperations, readmissions and complications, and computed the intraclass correlation coefficient to assess the individual and hospital determinants of efficiency and quality of care provided by hospitals.

RESULTS

The 5.4-fold variation between the lowest-rate (56/100 000 inhabitants) and the highest-rate (302/100 000) districts and the SCV over 10% confirmed high systematic variation in the access to care. Higher treatment rates were driven by greater provisions of robotic and/or laparoscopic interventions, which showed highly variable usage rates. Both individual and hospital factors influenced quality and efficiency provided by hospitals, but just low proportions of variation were explained by hospital and patient characteristics.

CONCLUSIONS

We found high and systematic variation in the access to POP surgical care in Tuscany and in quality and efficiency provided by hospitals. Such a variation may be mainly explained by user and provider preferences, which should be further explored. Also, supply-side factors may be involved, suggesting that wider and more uniform dissemination of robotic/laparoscopic procedures may reduce variation.

Provider supply and access to primary care

Resource-constrained delivery systems often have access issues, causing patients to wait a long time to see a provider. We develop theoretical and empirical models of wait times and apply them to primary care delivery by the U.S. Veterans Health Administration (VHA). Using instrumental variables to handle simultaneity issues, we estimate the effect of clinician supply on new patient wait times. We find that it has a sizable impact. A 10% increase in capacity reduces wait times by 2.1%. Wait times are also associated with clinician productivity, scheduling protocols, and patient access to alternative sources of care. The VHA has adopted our models to identify underserved areas as specified by the MISSION Act of 2018.

Effect of hospital attributes on patient preference among outpatient attendants in Wolaita Zone, Southern Ethiopia: discrete choice experiment study

BACKGROUND

Patient preference has preceded the use of health care services, and it has been affected by different hospital attributes. Meanwhile, the number of patients receiving vital health intervention is particularly low in Ethiopia. Therefore, this study aimed to determine the effect of hospital attributes on patient preference for outpatients in the Wolaita area in September 2020.

METHODS

A discrete choice experimental study was applied to determine the effect of hospital attributes on patient preference with a sample size of 1077. The experimental survey was conducted among outpatient attendants selected through a systematic random sampling approach. Six key attributes (competence of healthcare providers; availability of medical equipment and supplies; cost of service; wait time; distance; and hospital reputation) deduced from various hospital attributes were used to elicit the patient preferences. The data was collected from participants through the Open Data Kit application. A random effect probit model with marginal willingness to pay measure and partially log-likelihood analysis was applied to extract important attributes. We used STATA version 15 software for analysis, and the fitness of the model was verified by the calculated p-value for the Wald chi-square with a cut-point value of 0.05.

RESULT

One thousand forty-five patients who received outpatient care participated in the study. The random effect probit results have shown that all hospital attributes included in the study were significantly valued by patients while choosing the hospital (p-value < 0.001). Meanwhile, based on marginal willingness to pay and partial log-likelihood analysis, the competence of health care providers was identified as the most important attribute followed by the availability of medical equipment and supplies in hospitals.

CONCLUSION AND RECOMMENDATION

The results suggested that the quality of health care providers and availability of medical equipment and supply in hospitals would be primary interventional points for improving the patient preference of hospitals. Assessment, education, and training are recommended for enhancing the quality of health care providers. And stock balance checks, inspections, and accreditation are believed to be valuable for improving the availability of equipment and supply in hospitals.

Using Discrete Choice Methodology to Explore the Impact of Patient Room Window Design on Hospital Choice

Evidence-based design has been fundamental to designing healthcare environments for patient outcomes and experience, yet few studies have studied how design factors drive patient choice. 652 patients who recently received care at hospitals across the United States were administered an online discrete choice survey to investigate the factors playing into their choice between hypothetical hospitals. Discrete choice models are widely used to model patient preferences among treatment alternatives, but few studies have utilized this approach to investigate healthcare design alternatives. In the current study, respondents were asked to choose between hypothetical hospitals that differed in patient room design, window features of the room, appointment availability, distance from home, insurance coverage, and HCAHPS ratings. The results demonstrate that patient room design that allowed unobscured access to daylight and views through windows, in-network insurance coverage, closer distance from home, and one-star higher patient experience rating increased the likelihood of a patient's hospital choice. The study broadly explores discrete choice model's applicability to healthcare design and its ability to quantify patient perceptions with a metric meaningful for hospital administrators.

Does Internet Use Affect Medical Decisions among Older Adults in China? Evidence from CHARLS

Background: The rapid growth of the elderly population poses a huge challenge for people to access medical services. The key to get rid of the dilemma is for patients to go firstly to primary medical institutions. Existing studies have identified numerous factors that can affect patients’ health institution choice. However, we currently know little about the role of Internet use in the patients’ medical decisions. The objective of this study is to explore health-seeking behavior and institution choice under the background of the Internet era from the perspective of older adults, and to analyze whether the Internet could guide patients to the appropriate medical institution so as to accomplish hierarchical treatment. Methods: The dataset comprises 9416 people aged 45 or above from the China Health and Retirement Longitudinal Survey (CHARLS), which, through multistage cluster sampling, was conducted in 2011, 2013, and 2015. Logistic regression, PSM, and FE model are used to estimate the influence of Internet use on the health care decision-making behavior. Results: Internet use has a significant positive impact on the self-treatment of common diseases (β = 0.05, p < 0.05). In terms of medical institution choices, those who use Internet are more inclined to choose top-level hospitals than community health service institutions to treat common diseases (β = 0.06, p < 0.01). Conclusions: The Internet has lowered the obstacles to learning about common ailments, resulting in a substitution impact of self-treatment for hospital care. However, Internet use may aggravate older adults’ perception of the risk of disease, which exacerbates the tendency of going to higher-level medical institutions for medical treatment. The finding of the study is useful for further rational planning and utilization of the Internet in order to guide patients to appropriate medical institution, which helps to improve the efficiency of the overall medical and health services.

Whether Public Hospital Reform Affects the Hospital Choices of Patients in Urban Areas: New Evidence from Smart Card Data

The effects of public hospital reforms on spatial and temporal patterns of health-seeking behavior have received little attention due to small sample sizes and low spatiotemporal resolution of survey data. Without such information, however, health planners might be unable to adjust interventions in a timely manner, and they devise less-effective interventions. Recently, massive electronic trip records have been widely used to infer people's health-seeking trips. With health-seeking trips inferred from smart card data, this paper mainly answers two questions: (i) how do public hospital reforms affect the hospital choices of patients? (ii) What are the spatial differences of the effects of public hospital reforms? To achieve these goals, tertiary hospital preferences, hospital bypass, and the efficiency of the health-seeking behaviors of patients, before and after Beijing's public hospital reform in 2017, were compared. The results demonstrate that the effects of this reform on the hospital choices of patients were spatially different. In subdistricts with (or near) hospitals, the reform exerted the opposite impact on tertiary hospital preference compared with core and periphery areas. However, the reform had no significant effect on the tertiary hospital preference and hospital bypass in subdistricts without (or far away from) hospitals. Regarding the efficiency of the health-seeking behaviors of patients, the reform positively affected patient travel time, time of stay at hospitals, and arrival time. This study presents a time-efficient method to evaluate the effects of the recent public hospital reform in Beijing on a fine scale.

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.

Patient satisfaction with outpatient care in China: a comparison of public secondary and tertiary hospitals

OBJECTIVE

The aims of this study were to investigate and compare patient satisfaction with outpatient care in public secondary and tertiary hospitals in China and to explore the factors affecting patient satisfaction for improving the quality of outpatient care in public hospitals.

METHODS

This cross-sectional study comprised a sample survey of 11 097 adults in 31 provincial cities in China from February to April 2018. A pretested structured questionnaire was used to collect outpatient experience data through a computer-assisted telephone interviewing system. Patient satisfaction was assessed using nine questions answered on a 4-point Likert scale. Multivariate regression models were employed to examine the relationships of patient satisfaction with outpatient services and healthcare provider level and to identify the factors associated with satisfaction.

RESULTS

Patient's overall satisfaction score with outpatient care was 27.3 (SD = 3.8), with lower scores observed in tertiary hospitals than in secondary hospitals (27.3 vs. 27.6, P < 0.05). The domain with the highest satisfaction was 'consulting environment', and the domain with the lowest satisfaction was 'patient waiting time in the hospital'. Patients who went to tertiary hospitals reported lower satisfaction in 'patient waiting time in the hospital', 'medical expenses', 'patient length of treatment time' and 'attitudes of other health workers' than patients who went to secondary hospitals (P < 0.05). In secondary hospitals, no significant difference in patient satisfaction was observed between different sociodemographic categories (P > 0.05). In tertiary hospitals, female and single respondents were more likely to have higher satisfaction (P < 0.05), whereas respondents with high school or junior college degrees were more likely to have lower satisfaction (P < 0.05).

CONCLUSION

The aforementioned results suggested that tertiary hospitals face larger challenges in patient satisfaction with outpatient care than secondary hospitals. Measures must be adopted to improve patient satisfaction with outpatient care in future healthcare reforms. Patient waiting time, medical expenses and treatment duration especially require improvements in tertiary hospitals.

Optimal hospital payment rules under rationing by waiting

We derive optimal rules for paying hospitals for non-emergency care when providers choose quality and capacity, and patient demand is rationed by waiting time. Waiting for treatment is costly for patients, so that hospital payment rules should take account of their effect on waiting time as well as on quality. Since deterministic waiting time models imply that profit maximising hospitals will never choose to have both positive quality and positive waiting time, we develop a stochastic model of rationing by waiting in which both quality and expected waiting are positive in equilibrium. We use it to show that, although a prospective output price gives hospitals an incentive to attract patients by raising quality and reducing waiting times, it must be supplemented by a price attached to hospital decisions on quality or capacity or to a performance indicator which depends on those decisions (such as average waiting time, or average length of stay). A prospective output price by itself can support the optimal quality and waiting time distribution only if the welfare function respects patient preferences over quality and waiting time, if patients' marginal rates of substitution between quality and waiting time are independent of income, and if waiting for treatment does not reduce the productivity of patients. If these conditions do not hold, supplementing the output price with a reward linked to the hospital's cost can increase welfare, though it is possible that costs should be taxed rather than subsidised.

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.

Dynamic hospital competition under rationing by waiting times

We develop a dynamic model of hospital competition where (i) waiting times increase if demand exceeds supply; (ii) patients choose a hospital based in part on waiting times; and (iii) hospitals incur waiting time penalties. We show that, whereas policies based on penalties will lead to lower waiting times, policies that promote patient choice will instead lead to higher waiting times. These results are robust to different game-theoretic solution concepts, designs of the hospital penalty structure, and patient utility specifications. Furthermore, waiting time penalties are likely to be more effective in reducing waiting times if they are designed with a linear penalty structure, but the counterproductive effect of patient choice policies is smaller when penalties are convex. These conclusions are partly derived by calibration of our model based on waiting times and elasticities observed in the English NHS for a common treatment (cataract surgery).

Factors associated with the choice of primary care facilities for initial treatment among rural and urban residents in Southwestern China

Objective

To explore influential factors contributing to the choice of primary care facilities (PCFs) for the initial treatment among rural and urban residents in Southwestern China.

Methods

A face-to-face survey was conducted on a multistage stratified random sample of 456 rural and 459 urban residents in Sichuan Province from January to August in 2014. A structured questionnaire was used to collect data on residents’ characteristics, provider of initial treatment and principal reason for the choice. Multivariate logistic regression was performed to identify factors associated with choosing PCFs for the initial treatment.

Results

The result showed that 65.4% of the rural residents and 50.5% of the urban residents chose PCFs as their initial contact for medical care. Among both rural and urban residents, the principal reason for choosing medical institutions for the initial treatment was convenience (42.3% versus 40.5%, respectively), followed by high quality of medical care (26.5% versus 29.4%, respectively). Compared to rural residents, urban residents were more likely to value trust in doctors and high quality of medical care but were less likely to value the insurance designation status of the facilities. Logistic regression analysis showed that both rural and urban residents were less likely to choose PCFs for the initial treatment if they lived more than 15 minutes (by walk) from the nearest facilities (rural: OR = 0.15, 95%CI = 0.09–0.26; urban: OR = 0.19, 95%CI = 0.10–0.36), had fair (rural: OR = 0.49, 95%CI = 0.26–0.92; urban: OR = 0.31, 95%CI = 0.15–0.64) or poor (rural: OR = 0.14, 95%CI = 0.07–0.30; urban: OR = 0.22, 95%CI = 0.11–0.44) self-reported health status. Among rural residents, attending college or higher education (OR = 0.21, 95%CI = 0.08–0.59), being retired (OR = 0.90, 95%CI = 0.44–1.84) and earning a per capita annual income of household of 10,000–29,999 (OR = 0.24, 95%CI = 0.11–0.52) and 30,000–49,999 (OR = 0.26, 95%CI = 0.07–0.92) were associated with lower rates of seeking care at PCFs.

Conclusion

Efforts should be made to improve the accessibility of PCFs and to upgrade the services capability of PCFs both in rural and urban areas in China. At the same time, resources should be prioritized to residents with poorer self-reported health status, and rural residents who retire or have better education and higher income levels should be taken into account.

To "vape" or smoke? Experimental evidence on adult smokers

A growing share of the United States population uses e-cigarettes but the optimal regulation of these controversial products remains an open question. We conduct a discrete choice experiment to investigate how adult tobacco cigarette smokers' demand for e-cigarettes and tobacco cigarettes varies by four attributes: (i) whether e-cigarettes are considered healthier than tobacco cigarettes, (ii) the effectiveness of e-cigarettes as a cessation device, (iii) bans on use in public places, and (iv) price. We find that adult smokers' demand for e-cigarettes is motivated more by health concerns than by the desire to avoid smoking bans or higher prices.

Hospital Choice for Cataract Treatments: The Winner Takes Most

Background: Transparency in quality of care is an increasingly important issue in healthcare. In many international healthcare systems, transparency in quality is crucial for health insurers when purchasing care on behalf of their consumers, for providers to improve the quality of care (if necessary), and for consumers to choose their provider in case treatment is needed. Conscious consumer choices incentivize healthcare providers to deliver better quality of care. This paper studies the impact of quality on patient volume and hospital choice, and more specifically whether high quality providers are able to attract more patients.

Methods: The dataset covers the period 2006-2011 and includes all patients who underwent a cataract treatment in the Netherlands. We first estimate the impact of quality on volume using a simple ordinary least squares (OLS), second we use a mixed logit to determine how patients make trade-offs between quality, distance and waiting time in provider choice.

Results: At the aggregate-level we find that, a one-point quality increase, on a scale of one to a hundred, raises patient volume for the average hospital by 2-4 percent. This effect is mainly driven by the hospital with the highest quality score: the effect halves after excluding this hospital from the dataset. Also at the individual-level, all else being equal, patients have a stronger preference for the hospital with the highest quality score, and appear indifferent between the remaining hospitals.

Conclusion: Our results suggest that the top performing hospital is able to attract significantly more patients than the remaining hospitals. We find some evidence that a small share of consumers may respond to quality differences, thereby contributing to incentives for providers to invest in quality and for insurers to take quality into account in the purchasing strategy.

Proximity and waiting times in choice models for outpatient cardiological visits in Italy

We apply mixed logit regression to investigate patients' choice of non-emergency outpatient cardiovascular specialists in Tuscany, Italy. We focused on the effects of travel time and waiting time. Results reveal that patients prefer clinics nearby and with shorter waiting times. Differences in patient choice depend on age and socioeconomic conditions, thus confirming equity concerns in the access of non-acute services. Our results could be used to optimize the allocation of resources, reduce inequities and increase the efficiency and responsiveness of outpatient systems considering patient preferences.

Choice in the presence of experts: The role of general practitioners in patients' hospital choice

This paper considers the micro-econometric analysis of patients' hospital choice for elective medical procedures when their choice set is pre-selected by a general practitioner (GP). GPs have a dual role with regard to elective referrals in the English NHS, advising patients and at the same time taking account of the financial implications of referral decisions on local health budgets. The paper proposes a two-stage choice model that encompasses both patient and GP level optimization. It demonstrates that estimators that do not take account of strategic pre-selection of choice sets may be biased and inconsistent. We find that GPs as patients' agents select choice options based on quality, but as agents of health authorities also consider financial implications of referrals. When considering these choice options, patients focus on tangible hospital attributes, like amenities.

Should I stay or should I go? Hospital emergency department waiting times and demand

In the absence of the price mechanism, hospital emergency departments rely on waiting times, alongside prioritisation mechanisms, to restrain demand and clear the market. This paper estimates by how much the number of treatments demanded is reduced by a higher waiting time. I use variation in waiting times for low-urgency patients caused by rare and resource-intensive high-urgency patients to estimate the relationship. I find that when waiting times are higher, more low-urgency patients are deterred from treatment and leave the hospital during the waiting period without being treated. The waiting time elasticity of demand for low-urgency patients is approximately -0.25 and is highest for the lowest-urgency patients.

Investigation of attributes which guide choice in cataract surgery services in urban Sydney, Australia

BACKGROUND

It is critical to consult patients to develop patient-centred cataract surgery care. We aimed to identify attributes patients consider when making decisions about cataract surgery in an Australian context, where both publicly and privately funded surgery are available. This is the first step in investigating how decisions are made about cataract surgery services.

METHODS

This observational qualitative study was undertaken in two public hospitals and one private practice in Sydney, Australia. The study involved 19 women and men with age-related cataracts and no previous cataract surgery, aged > 18 years, able to speak conversational English or Mandarin. A multi-stage attribute development process was followed, including: literature review, semi-structured interviews with surgery candidates in three eye clinics, and review by an expert panel. The main outcome measures were primary attributes for making choices about cataract surgery.

RESULTS

Wait time, cost, institutional reputation, surgeon experience and travel time were identified as principal attributes; lower value was placed on consultation length and accessibility. Non-English speaking participants indicated greater interest in pre-operative information than English speakers, but expressed trust in the Australian healthcare system.

CONCLUSIONS

Findings suggest individuals prioritise attributes which consume time or incur costs when accessing care (wait time, cost and travel time). They also consider factors associated with the outcome of their cataract surgery (surgeon experience and institutional reputation). Similar to other decision-making processes, patients are likely to trade between these different attributes depending on their personal preferences and circumstances.

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.

Pregnant women's choice of birthing hospital: A qualitative study on individuals' preferences

OBJECTIVE

To investigate pregnant women's decision making in relation to their choice of birthing hospital and, in particular, their priorities regarding hospital characteristics.

METHODS

The focus of this study was the choice of birthing hospital among pregnant women. A qualitative interview design was used and women were recruited during their first pregnancy-related visit to a general practitioner. The interviews were conducted using a semi-structured interview guide, and a thematic analysis of the data was carried out.

RESULTS

Women made their hospital choice decision independently and they relied extensively on their own or peers' experiences. Travel distance played a role, but some women were willing to incur longer travel times to give birth at a specialized hospital in order to try to reduce the risks (in case of unexpected events). The women associated the presence of specialized services and staff that were more qualified and experienced with increased safety. Other priorities included continuity of care (i.e., being seen by the same midwife) as well as service availability, which in this case referred to the possibility of a water birth and postnatal hoteling services.

CONCLUSIONS

The choice of hospital provider appears to be strongly influenced by experience, whether personal experience or the experience of peers. However, there appears to be room for more information to be provided on safety and service attributes as an instrument for making an informed decision.

Financial incentives to discontinue long-term benzodiazepine use: a discrete choice experiment investigating patient preferences and willingness to participate

OBJECTIVES

Investigate the acceptability of financial incentives for initiating a medically supervised benzodiazepine discontinuation programme among people with long-term benzodiazepine use and to identify programme features that influence willingness to participate.

METHODS

We conducted a discrete choice experiment in which we presented a variety of incentive-based programs to a sample of older adults with long-term benzodiazepine use identified using the outpatient electronic health record of a university-owned health system. We studied four programme variables: incentive amount for initiating the programme, incentive amount for successful benzodiazepine discontinuation, lottery versus certain payment and whether partial payment was given for dose reduction. Respondents reported their willingness to participate in the programmes and additional information was collected on demographics, history of use and anxiety symptoms.

RESULTS

The overall response rate was 28.4%. Among the 126 respondents, all four programme variables influenced stated preferences. Respondents strongly preferred guaranteed cash-based incentives as opposed to a lottery, and the dollar amount of both the starting and conditional incentives had a substantial impact on choice. Willingness to participate increased with the amount of conditional incentive. Programme participation also varied by gender, duration of use and income.

CONCLUSIONS

Participation in an incentive-based benzodiazepine discontinuation programme might be relatively low, but is modifiable by programme variables including incentive amounts. These results will be helpful to inform the design of future trials of benzodiazepine discontinuation programmes. Further research is needed to assess the financial viability and potential cost-effectiveness of such economic incentives.

Do hospitals respond to rivals' quality and efficiency? A spatial panel econometric analysis

We investigate whether hospitals in the English National Health Service change their quality or efficiency in response to changes in quality or efficiency of neighbouring hospitals. We first provide a theoretical model that predicts that a hospital will not respond to changes in the efficiency of its rivals but may change its quality or efficiency in response to changes in the quality of rivals, though the direction of the response is ambiguous. We use data on eight quality measures (including mortality, emergency readmissions, patient reported outcome, and patient satisfaction) and six efficiency measures (including bed occupancy, cancelled operations, and costs) for public hospitals between 2010/11 and 2013/14 to estimate both spatial cross-sectional and spatial fixed- and random-effects panel data models. We find that although quality and efficiency measures are unconditionally spatially correlated, the spatial regression models suggest that a hospital's quality or efficiency does not respond to its rivals' quality or efficiency, except for a hospital's overall mortality that is positively associated with that of its rivals. The results are robust to allowing for spatially correlated covariates and errors and to instrumenting rivals' quality and efficiency.

Patient choice modelling: how do patients choose their hospitals?

As an aid to predicting future hospital admissions, we compare use of the Multinomial Logit and the Utility Maximising Nested Logit models to describe how patients choose their hospitals. The models are fitted to real data from Derbyshire, United Kingdom, which lists the postcodes of more than 200,000 admissions to six different local hospitals. Both elective and emergency admissions are analysed for this mixed urban/rural area. For characteristics that may affect a patient's choice of hospital, we consider the distance of the patient from the hospital, the number of beds at the hospital and the number of car parking spaces available at the hospital, as well as several statistics publicly available on National Health Service (NHS) websites: an average waiting time, the patient survey score for ward cleanliness, the patient safety score and the inpatient survey score for overall care. The Multinomial Logit model is successfully fitted to the data. Results obtained with the Utility Maximising Nested Logit model show that nesting according to city or town may be invalid for these data; in other words, the choice of hospital does not appear to be preceded by choice of city. In all of the analysis carried out, distance appears to be one of the main influences on a patient's choice of hospital rather than statistics available on the Internet.

Does Quality Affect Patients' Choice of Doctor? Evidence from England

Reforms giving users of public services choice of provider aim to improve quality. But such reforms will work only if quality affects choice of provider. We test this crucial prerequisite in the English health care market by examining the choice of 3.4 million individuals of family doctor. Family doctor practices provide primary care and control access to non-emergency hospital care, the quality of their clinical care is measured and published and care is free. In this setting, clinical quality should affect choice. We find that a 1 standard deviation increase in clinical quality would increase practice size by around 17%.

Choice of hospital: Which type of quality matters?

The implications of hospital quality competition depend on what type of quality affects choice of hospital. Previous studies of quality and choice of hospitals have used crude measures of quality such as mortality and readmission rates rather than measures of the health gain from specific treatments. We estimate multinomial logit models of hospital choice by patients undergoing hip replacement surgery in the English NHS to test whether hospital demand responds to quality as measured by detailed patient reports of health before and after hip replacement. We find that a one standard deviation increase in average health gain increases demand by up to 10%. The more traditional measures of hospital quality are less important in determining hospital choice.

A Theory of Waiting Time Reporting and Quality Signaling

We develop a theoretical model to study a policy that publicly reports hospital waiting times. We characterize two effects of such a policy: the 'competition effect' that drives hospitals to compete for patients by increasing service rates and reducing waiting times and the 'signaling effect' that allows patients to distinguish a high-quality hospital from a low-quality one. While for a low-quality hospital both effects help reduce waiting time, for a high-quality hospital, they act in opposite directions. We show that the competition effect will outweigh the signaling effect for the high-quality hospital, and consequently, both hospitals' waiting times will be reduced by the introduction of the policy. This result holds in a policy environment where maximum waiting time targets are not binding. Copyright © 2015 John Wiley & Sons, Ltd.

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

We investigate (a) how patient choice of hospital for elective hip replacement is influenced by distance, quality and waiting times, (b) differences in choices between patients in urban and rural locations, (c) the relationship between hospitals' elasticities of demand to quality and the number of local rivals, and how these changed after relaxation of constraints on hospital choice in England in 2006. Using a data set on over 500,000 elective hip replacement patients over the period 2002 to 2013 we find that patients became more likely to travel to a provider with higher quality or lower waiting times, the proportion of patients bypassing their nearest provider increased from 25% to almost 50%, and hospital elasticity of demand with respect to own quality increased. By 2013 average hospital demand elasticity with respect to readmission rates and waiting times were - 0.2 and - 0.04. Providers facing more rivals had demand that was more elastic with respect to quality and waiting times. Patients from rural areas have smaller disutility from distance.

Patient Mobility for Elective Secondary Health Care Services in Response to Patient Choice Policies: A Systematic Review

Our review establishes the empirical evidence for patient mobility for elective secondary care services in countries that allow patients to choose their health care provider. PubMed and Embase were searched for relevant articles between 1990 and 2015. Of 5,994 titles/abstracts reviewed, 26 studies were included. The studies used three main methodological models to establish mobility. Variation in the extent of patient mobility was observed across the studies. Mobility was positively associated with lower waiting times, indicators of better service quality, and access to advanced technology. It was negatively associated with advanced age or lower socioeconomic backgrounds. From a policy perspective we demonstrate that a significant proportion of patients are prepared to travel beyond their nearest provider for elective services. As a consequence, some providers are likely to be “winners” and others “losers,” which could result in overall decreased provider capacity or inefficient utilization of existing services. Equity also remains a key concern.

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

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

The relationship between educational attainment and waiting time among the elderly in Norway

We investigate whether educational attainment affects waiting time of elderly patients in somatic hospitals. We consider three distinct pathways; that patients with different educational attainment have different disease patterns, that patients with different levels of education receive treatments at different hospitals, and that patient choice and supply of local health services within hospital catchment areas explain unequal waiting time of different educational groups. We find evidence of an educational gradient in waiting time for male patients, but not for female patients. Conditional on age, male patients with tertiary education wait 45% shorter than male patients with secondary or primary education. The first pathway is not quantitatively important as controlling for disease patters has little effect on relative waiting times. The second pathway is important. Relative to patients with primary education, variation in waiting time and education level across local hospitals contributes to higher waiting time for male patients with secondary education and female patients with secondary or tertiary education and lower waiting time for male patients with tertiary education. These effects are in the order of 15-20%. The third pathway is also quantitatively important. The educational gradients within catchment areas disappear when we control for travel distance and supply of private specialists.

Hospital sector choice and support for public hospital care in New Zealand: Results from a labeled discrete choice survey

This study uses a discrete choice experiment (DCE) to measure patients' preferences for public and private hospital care in New Zealand. A labeled DCE was administered to 583 members of the general public, with the choice between a public and private hospital for a non-urgent surgery. The results suggest that cost of surgery, waiting times for surgery, option to select a surgeon, convenience, and conditions of the hospital ward are important considerations for patients. The most important determinant of hospital choice was whether it was a public or private hospital, with respondents far more likely to choose a public hospital than a private hospital. The results have implications for government policy toward using private hospitals to clear waiting lists in public hospitals, with these results suggesting the public might not be indifferent to policies that treat private hospitals as substitutes for public hospitals.

Patient hospital choice for hip replacement: empirical evidence from the Netherlands

In the Dutch health care system, hospitals are expected to compete. A necessary condition for competition among hospitals is that patients do not automatically choose the nearest hospital, but are-at least to some extent-sensitive to differences in hospital quality. In this study, an analysis is performed on the underlying features of patient hospital choice in a setting where prices do not matter for patients as a result of health insurance coverage. Using claims data from all Dutch hospitals over the years 2008-2010, a conditional logit model examines the relationship between patient characteristics (age, gender and reoperations) and hospital attributes (hospital quality information, waiting times on treatments and travel time for patients to the hospitals) in the market for general non-emergency hip replacement treatments. The results show that travel time is the most important determinant in patient hospital choice. From our analysis, however, it follows that publicly available hospital quality ratings and waiting times also have a significant impact on patient hospital choice. The panel data used for this study (2008-2010) is rather short, which may explain why no coherent and persistent changes in patient hospital choice behaviour over time are found.

Impact of specialization in gynecology and obstetrics departments on pregnant women's choice of maternity institutions

In April 2008, specialization in gynecology and obstetrics departments was introduced in the Sennan area of Osaka prefecture in Japan that aimed at solving the problems of regional provisions of obstetrics services (e.g., shortage of obstetricians, overworking of obstetricians, and provision of specialist maternity services for high-risk pregnancies). Under this specialization, the gynecology and obstetrics departments in two city hospitals were combined and reconstructed into two centers, i.e., the gynecological care center in Kaizuka City Hospital and the prenatal care center in Izumisano City Hospital. This paper investigates to what extent and how this specialization affected pregnant women's choices of the prenatal care center and other maternity institutions. We used birth certificate data of 15,927 newborns from the Sennan area between April 1, 2007 and March 30, 2010, for Before and After Analysis to examine changes in pregnant women's choices of maternity institutions before and after the specialization was instituted. Our results indicated that this specialization scheme was, to some extent, successful on the basis of providing maternity services for high-risk pregnancies at the prenatal care center (i.e., Izumisano City Hospital) and having created a positive effect by pregnant women to other facilities in the nearby area.

Recognition of physiotherapists' expertise in Parkinson's disease

BACKGROUND

Publicly available information comparing performance across quality and costs has proliferated in recent years, both about individual healthcare professionals and hospitals. This type of information is now becoming increasingly available for physiotherapists with expertise in Parkinson's disease (PD). Our study aimed to explore the ability of people with Parkinson's disease to recognise expertise, and to what extent respondents selectively choose such expert physiotherapists.

METHODS

We used claim data from the period 2009-2010 to select customers with PD who claimed physiotherapy. A random sample of 500 eligible respondents received a paper-based survey. We used descriptive statistics to compare the respondent characteristics, a qualitative programme to analyse the qualitative items, and univariate and multivariate regression.

RESULTS

Most respondents (89%) took their referring physician's advice when selecting a physiotherapist, although this advice rarely was supported with arguments. The remaining respondents (11%) searched for comparative performance information about physiotherapists. Respondents who recognised the added value of PD expertise among physiotherapists were 3.28 times as likely to search for comparative performance information as those who did not understand. Respondents were willing to switch to an expert physiotherapist (68%), and this willingness increased if they recognised the value of PD expertise (p < .001).

CONCLUSION

The participants were able to recognise certain aspects of expertise. Though they showed relatively few signs of selectively choice behaviour for expert physiotherapists. Both respondents and referring professionals need more understanding about the added value of an expert physiotherapist, to foster selective provider choice.