Dynamic hospital competition under rationing by waiting times

Does hospital competition improve the quality of outpatient care? - empirical evidence from a quasi-experiment in a Chinese city

BACKGROUND

Although countries worldwide have launched a series of pro-competition reforms, the literature on the impacts of hospital competition has produced a complex and contradictory picture. This study examined whether hospital competition contributed to an increase in the quality of outpatient care.

METHODS

The dataset comprises encounter data on 406,664 outpatients with influenza between 2015 and 2019 in China. Competition was measured using the Herfindahl-Hirschman index (HHI). Whether patients had 14-day follow-up encounter for influenza at any healthcare facility, outpatient facility, and hospital outpatient department were the three quality outcomes assessed. Binary regression models with crossed random intercepts were constructed to estimate the impacts of the HHI on the quality of outpatient care. The intensity of nighttime lights was employed as an instrumental variable to address the endogenous relationship between the HHI and the quality of outpatient care.

RESULTS

We demonstrated that an increase in the degree of hospital competition was associated with improved quality of outpatient care. For each 1% increase in the degree of hospital competition, an individual's risk of having a 14-day follow-up encounter for influenza at any healthcare facility, outpatient facility, and hospital outpatient department fell by 34.9%, 18.3%, and 20.8%, respectively. The impacts of hospital competition on improving the quality of outpatient care were more substantial among females, individuals who used the Urban and Rural Residents Basic Medical Insurance to pay for their medical costs, individuals who visited accredited hospitals, and adults aged 25 to 64 years when compared with their counterparts.

CONCLUSION

This study demonstrated that hospital competition contributed to better quality of outpatient care under a regime with a regulated ceiling price. Competition is suggested to be promoted in the outpatient care market where hospitals have control over quality and government sets a limit on the prices that hospitals may charge.

Intended and unintended consequences of strategies to meet performance benchmarks for rheumatologist referrals in a centralized intake system

RATIONALE

Timely assessment of a chronic condition is critical to prevent long-term irreversible consequences. Patients with inflammatory arthritis (IA) symptoms require diagnosis by a rheumatologist and intervention initiation to minimize potential joint damage. With limited rheumatologist capacity, meeting urgency wait time benchmarks can be challenging. We investigate the impact of the maximum wait time guarantee (MWTG) policy and referral volume changes in a rheumatology central intake (CI) system on meeting this challenge.

METHODS

We applied a system simulation approach to model a high-volume CI rheumatology clinic. Model parameters were based on the referral and triage data from the CI and clinic appointment data. We compare the wait time performance of the current distribution policy MWTG and when referral volumes change.

RESULTS

The MWTG policy ensures 100% of new patients see a rheumatologist within their urgency wait time benchmark. However, the average wait time for new patients increased by 51% (178-269 days). A 10% decrease in referrals resulted in a 76% decrease on average wait times (178-43 days) for new patients and an increase in the number of patients seen by a rheumatologist within 1 year of the initial visit.

CONCLUSION

An MWTG policy can result in intended and unintended consequences-ensuring that all patients meet the wait time benchmarks but increasing wait times overall. Relatively small changes in referral volume significantly impact wait times. These relationships can assist clinic managers and policymakers decide on the best approach to manage referrals for better system performance.

On the bright side of market concentration in a mixed-oligopoly healthcare industry

We describe the healthcare industry as a mixed oligopoly, where a public and two private providers compete, and examine the effects of a merger between the two private healthcare providers on prices, quality, and welfare. When the price and (eventually) quality of the public provider are regulated, the cost synergies required for the merger to increase consumer welfare are less significant than in a setting with only profit-maximizing providers. When, instead, the public provider can adjust its policy to the rivals' behavior and maximizes a weighted sum of profits and consumer surplus (i.e., it has 'semi-altruistic' preferences), the merger is consumer surplus increasing if the public provider is sufficiently altruist, in some cases even absent efficiencies. These results suggest that ignoring the role and objectives of the public sector in the healthcare industry may lead agencies to reject mergers that, while would decrease consumer welfare in fully privatized industries, would increase it in mixed oligopolies.

"Shopping around" for treatment is not a solution to cancer backlog

Ajay Aggarwal and colleagues argue that relying on patient choice to cut waiting times is oversimplistic and likely to widen inequalities

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

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

Measuring quality effects in equilibrium

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

Physician-Customized Strategies for Reducing Outpatient Waiting Time in South Korea Using Queueing Theory and Probabilistic Metamodels

The time a patient spends waiting to be seen by a healthcare professional is an important determinant of patient satisfaction in outpatient care. Hence, it is crucial to identify parameters that affect the waiting time and optimize it accordingly. First, statistical analysis was used to validate the effective parameters. However, no parameters were found to have significant effects with respect to the entire outpatient department or to each department. Therefore, we studied the improvement of patient waiting times by analyzing and optimizing effective parameters for each physician. Queueing theory was used to calculate the probability that patients would wait for more than 30 min for a consultation session. Using this result, we built metamodels for each physician, formulated an effective method to optimize the problem, and found a solution to minimize waiting time using a non-dominated sorting genetic algorithm (NSGA-II). On average, we obtained a 30% decrease in the probability that patients would wait for a long period. This study shows the importance of customized improvement strategies for each physician.

Patients' free choice of physicians is not always good

We present a model of learning in healthcare markets. Hospitals have junior physicians with low and senior physicians with high ability. Junior physicians turn senior if they treat enough patients. Patients face heterogeneous costs for waiting if a physician's capacity is utilized. Hospitals choose to either allocate patients to physicians randomly or let patients choose their physicians. In a monopolistic market, the hospital always chooses the welfare-maximizing allocation system. In a competitive market, inefficiencies may arise due to two externalities. If patients are free to choose their physician, the marginal patient neither internalizes her impact on other patients' waiting costs nor the learning of junior physicians.

Hospital competition in a national health service: Evidence from a patient choice reform

We study the impact of exposing hospitals in a National Health Service (NHS) to non-price competition by exploiting a patient choice reform in Norway in 2001. The reform facilitates a difference-in-difference approach due to plausibly exogenous (geographical) variation in pre-reform market structure. Employing rich, administrative data, covering the universe of hospital admissions from 1998 to 2005, we estimate models with hospital and treatment (DRG) fixed-effects and use only emergency admissions to limit patient selection issues. The results show that hospitals in more competitive areas have a sharper reduction in AMI mortality but no effect on stroke mortality. We also find that exposure to competition reduces all-cause mortality, shortens length of stay, but increases readmissions, though the effects are small in magnitude. In years with high (DRG) prices, the negative effect on readmissions almost vanishes. Finally, exposure to competition tends to reduce waiting times and increase admissions, but the effects must be interpreted with care as the outcomes include elective treatments.

A note on the trade-off between waiting times and quality in a constrained hospital market

While aging population and technological innovation are expected to increase healthcare demand in the future, increase in healthcare spending is not likely to be sustainable in times of fiscal constraint. This might lead to a tightening of hospital capacity and, potentially, to higher patient waiting times. This paper studies waiting times and quality in a healthcare market where semi-altruistic hospitals operate at full capacity. We show that in this context a trade-off between waiting times and quality emerges which, if hospitals dislike patients to wait, decreases the incentive for the quality of care. We also show that, when hospitals operate at full capacity, standard waiting time policies involving targets and penalties (e.g., "Targets and Terror" in England) can meet the target at the expense of a lower quality of care, with relevant implications for the empirical evaluation of waiting time policy.