Thesis Thursday: Francesco Longo

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Francesco Longo who has a PhD from the University of York. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Essays on hospital performance in England
Luigi Siciliani
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What do you mean by ‘hospital performance’, and how is it measured?

The concept of performance in the healthcare sector covers a number of dimensions including responsiveness, affordability, accessibility, quality, and efficiency. A PhD does not normally provide enough time to investigate all these aspects and, hence, my thesis mostly focuses on quality and efficiency in the hospital sector. The concept of quality or efficiency of a hospital is also surprisingly broad and, as a consequence, perfect quality and efficiency measures do not exist. For example, mortality and readmissions are good clinical quality measures but the majority of hospital patients do not die and are not readmitted. How well does the hospital treat these patients? Similarly for efficiency: knowing that a hospital is more efficient because it now has lower costs is essential, but how is that hospital actually reducing costs? My thesis tries to answer also these questions by analysing various quality and efficiency indicators. For example, Chapter 3 uses quality measures such as overall and condition-specific mortality, overall readmissions, and patient-reported outcomes for hip replacement. It also uses efficiency indicators such as bed occupancy, cancelled elective operations, and cost indexes. Chapter 4 analyses additional efficiency indicators, such as admissions per bed, the proportion of day cases, and proportion of untouched meals.

You dedicated a lot of effort to comparing specialist and general hospitals. Why is this important?

The first part of my thesis focuses on specialisation, i.e. an organisational form which is supposed to generate greater efficiency, quality, and responsiveness but not necessarily lower costs. Some evidence from the US suggests that orthopaedic and surgical hospitals had 20 percent higher inpatient costs because of, for example, higher staffing levels and better quality of care. In the English NHS, specialist hospitals play an important role because they deliver high proportions of specialised services, commonly low-volume but high-cost treatments for patients with complex and rare conditions. Specialist hospitals, therefore, allow the achievement of a critical mass of clinical expertise to ensure patients receive specialised treatments that produce better health outcomes. More precisely, my thesis focuses on specialist orthopaedic hospitals which, for instance, provide 90% of bone and soft tissue sarcomas surgeries, and 50% of scoliosis treatments. It is therefore important to investigate the financial viability of specialist orthopaedic hospitals relative to general hospitals that undertake similar activities, under the current payment system. The thesis implements weighted least square regressions to compare profit margins between specialist and general hospitals. Specialist orthopaedic hospitals are found to have lower profit margins, which are explained by patient characteristics such as age and severity. This means that, under the current payment system, providers that generally attract more complex patients such as specialist orthopaedic hospitals may be financially disadvantaged.

In what way is your analysis of competition in the NHS distinct from that of previous studies?

The second part of my thesis investigates the effect of competition on quality and efficiency under two different perspectives. First, it explores whether under competitive pressures neighbouring hospitals strategically interact in quality and efficiency, i.e. whether a hospital’s quality and efficiency respond to neighbouring hospitals’ quality and efficiency. Previous studies on English hospitals analyse strategic interactions only in quality and they employ cross-sectional spatial econometric models. Instead, my thesis uses panel spatial econometric models and a cross-sectional IV model in order to make causal statements about the existence of strategic interactions among rival hospitals. Second, the thesis examines the direct effect of hospital competition on efficiency. The previous empirical literature has studied this topic by focusing on two measures of efficiency such as unit costs and length of stay measured at the aggregate level or for a specific procedure (hip and knee replacement). My thesis provides a richer analysis by examining a wider range of efficiency dimensions. It combines a difference-in-difference strategy, commonly used in the literature, with Seemingly Unrelated Regression models to estimate the effect of competition on efficiency and enhance the precision of the estimates. Moreover, the thesis tests whether the effect of competition varies for more or less efficient hospitals using an unconditional quantile regression approach.

Where should researchers turn next to help policymakers understand hospital performance?

Hospitals are complex organisations and the idea of performance within this context is multifaceted. Even when we focus on a single performance dimension such as quality or efficiency, it is difficult to identify a measure that could work as a comprehensive proxy. It is therefore important to decompose as much as possible the analysis by exploring indicators capturing complementary aspects of the performance dimension of interest. This practice is likely to generate findings that are readily interpretable by policymakers. For instance, some results from my thesis suggest that hospital competition improves efficiency by reducing admissions per bed. Such an effect is driven by a reduction in the number of beds rather than an increase in the number of admissions. In addition, competition improves efficiency by pushing hospitals to increase the proportion of day cases. These findings may help to explain why other studies in the literature find that competition decreases length of stay: hospitals may replace elective patients, who occupy hospital beds for one or more nights, with day case patients, who are instead likely to be discharged the same day of admission.

Sam Watson’s journal round-up for 12th February 2018

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Tuskegee and the health of black men. The Quarterly Journal of Economics [RePEc] Published February 2018

In 1932, a study often considered the most infamous and potentially most unethical in U.S. medical history began. Researchers in Alabama enrolled impoverished black men in a research program designed to examine the effects of syphilis under the guise of receiving government-funded health care. The study was known as the Tuskegee syphilis experiment. For 40 years the research subjects were not informed they had syphilis nor were they treated, even after penicillin was shown to be effective. The study was terminated in 1972 after its details were leaked to the press; numerous men died, 40 wives contracted syphilis, and a number of children were born with congenital syphilis. It is no surprise then that there is distrust among African Americans in the medical system. The aim of this article is to examine whether the distrust engendered by the Tuskegee study could have contributed to the significant differences in health outcomes between black males and other groups. To derive a causal estimate the study makes use of a number of differences: black vs non-black, for obvious reasons; male vs female, since the study targeted males, and also since women were more likely to have had contact with and hence higher trust in the medical system; before vs after; and geographic differences, since proximity to the location of the study may be informative about trust in the local health care facilities. A wide variety of further checks reinforce the conclusions that the study led to a reduction in health care utilisation among black men of around 20%. The effect is particularly pronounced in those with low education and income. Beyond elucidating the indirect harms caused by this most heinous of studies, it illustrates the importance of trust in mediating the effectiveness of public institutions. Poor reputations caused by negligence and malpractice can spread far and wide – the mid-Staffordshire hospital scandal may be just such an example.

The economic consequences of hospital admissions. American Economic Review [RePEcPublished February 2018

That this paper’s title recalls that of Keynes’s book The Economic Consequences of the Peace is to my mind no mistake. Keynes argued that a generous and equitable post-war settlement was required to ensure peace and economic well-being in Europe. The slow ‘economic privation’ driven by the punitive measures and imposed austerity of the Treaty of Versailles would lead to crisis. Keynes was evidently highly critical of the conference that led to the Treaty and resigned in protest before its end. But what does this have to do with hospital admissions? Using an ‘event study’ approach – in essence regressing the outcome of interest on covariates including indicators of time relative to an event – the paper examines the impact hospital admissions have on a range of economic outcomes. The authors find that for insured non-elderly adults “hospital admissions increase out-of-pocket medical spending, unpaid medical bills, and bankruptcy, and reduce earnings, income, access to credit, and consumer borrowing.” Similarly, they estimate that hospital admissions among this same group are responsible for around 4% of bankruptcies annually. These losses are often not insured, but they note that in a number of European countries the social welfare system does provide assistance for lost wages in the event of hospital admission. Certainly, this could be construed as economic privation brought about by a lack of generosity of the state. Nevertheless, it also reinforces the fact that negative health shocks can have adverse consequences through a person’s life beyond those directly caused by the need for medical care.

Is health care infected by Baumol’s cost disease? Test of a new model. Health Economics [PubMed] [RePEcPublished 9th February 2018

A few years ago we discussed Baumol’s theory of the ‘cost disease’ and an empirical study trying to identify it. In brief, the theory supposes that spending on health care (and other labour-intensive or creative industries) as a proportion of GDP increases, at least in part, because these sectors experience the least productivity growth. Productivity increases the fastest in sectors like manufacturing and remuneration increases as a result. However, this would lead to wages in the most productive sectors outstripping those in the ‘stagnant’ sectors. For example, salaries for doctors would end up being less than those for low-skilled factory work. Wages, therefore, increase in the stagnant sectors despite a lack of productivity growth. The consequence of all this is that as GDP grows, the proportion spent on stagnant sectors increases, but importantly the absolute amount spent on the productive sectors does not decrease. The share of the pie gets bigger but the pie is growing at least as fast, as it were. To test this, this article starts with a theoretic two-sector model to develop some testable predictions. In particular, the authors posit that the cost disease implies: (i) productivity is related to the share of labour in the health sector, and (ii) productivity is related to the ratio of prices in the health and non-health sectors. Using data from 28 OECD countries between 1995 and 2016 as well as further data on US industry group, they find no evidence to support these predictions, nor others generated by their model. One reason for this could be that wages in the last ten years or more have not risen in line with productivity in manufacturing or other ‘productive’ sectors, or that productivity has indeed increased as fast as the rest of the economy in the health care sector. Indeed, we have discussed productivity growth in the health sector in England and Wales previously. The cost disease may well then not be a cause of rising health care costs – nevertheless, health care need is rising and we should still expect costs to rise concordantly.


Sam Watson’s journal round-up for 11th December 2017

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Can incentives improve survey data quality in developing countries?: results from a field experiment in India. Journal of the Royal Statistical Society: Series A Published 17th November 2017

I must admit a keen interest in the topic of this paper. As part of a large project looking at the availability of health services in slums and informal settlements around the world, we are designing a household survey. Much like the Demographic and Health Surveys, which are perhaps the Gold standard of household surveys in low-income countries, interviewers will go door to door to sampled households to complete surveys. One of the issues with household surveys is that they take a long time, and so non-response can be an issue. A potential solution is to offer respondents incentives, cash or otherwise, either before the survey or conditionally on completing it. But any change in survey response as a result of an incentive might create suspicion around data quality. Work in high-income countries suggests incentives to participate have little or no effect on data quality. But there is little evidence about these effects in low-income countries. We might suspect the consequences of survey incentives to differ in poorer settings. For a start, many surveys are conducted on behalf of the government or an NGO, and respondents may misrepresent themselves if they believe further investment in their area might be forthcoming if they are sufficiently badly-off. There may also be larger differences between the interviewer and interviewee in terms of education or cultural background. And finally, incentives can affect the balance between a respondent’s so-called intrinsic and extrinsic motivations for doing something. This study presents the results of a randomised trial where the ‘treatment’ was a small conditional payment for completing a survey, and the ‘control’ was no incentive. In both arms, the response rate was very high (>96%), but it was higher in the treatment arm. More importantly, the authors compare responses to a broad range of socioeconomic and demographic questions between the study arms. Aside from the frequent criticism that statistical significance is interpreted here as the existence of a difference, there are some interesting results. The key observed difference is that in the incentive arm respondents reported having lower wealth consistently across a number of categories. This may result from any of the aforementioned effects of incentives, but may be evidence that incentives can affect data quality and should be used with caution.

Association of US state implementation of newborn screening policies for critical congenital heart disease with early infant cardiac deaths. JAMA [PubMedPublished 5th December 2017

Writing these journal round-ups obviously requires reading the papers that you choose. This can be quite an undertaking for papers published in economics journals, which are often very long, but they provide substantial detail allowing for a thorough appraisal. The opposite is true for articles in medical journals. They are pleasingly concise, but often at the expense of including detail or additional analyses. This paper falls into the latter camp. Using detailed panel data on infant deaths by cause by year and by state in the US, it estimates the effect of mandated screening policies for infant congenital heart defects on deaths from this condition. Given these data and more space, one might expect to see more flexible models than the differences in differences type analysis presented here, such as allowing for state-level correlated time trends. The results seem clear and robust – the policies were associated with a reduction in death from congenital heart conditions by around a third. Given this, one might ask: if it’s so effective, why weren’t doctors doing it anyway? Additional analyses reveal little to no association of the policies with death from other conditions, which may suggest that doctors didn’t have to reallocate their time from other beneficial functions. Perhaps then the screening bore other costs. In the discussion, the authors mention that a previous economic evaluation showed that universal screening was relatively costly (approximately $40,000 per life year saved), but that this may be an overestimate in light of these new results. Certainly then an updated economic evaluation is warranted. However, the models used in the paper may lead one to be cautious about causal interpretations and hence using the estimates in an evaluation. Given some more space the authors may have added additional analyses, but then I might not have read it…

Subsidies and structure: the lasting impact of the Hill-Burton program on the hospital industry. Review of Economics and Statistics [RePEcPublished 29th November 2017

As part of the Hospital Survey and Construction Act of 1946 in the United States, the Hill-Burton program was enacted. As a reaction to the perceived lack of health care services for workers during World War 2, the program provided subsidies of up to a third for building nonprofit and local hospitals. Poorer areas were prioritised. This article examines the consequences of this subsidy program on the structure of the hospital market and health care utilisation. The main result is that the program had the consequence of increasing hospital beds per capita and that this increase was lasting. More specific analyses are presented. Firstly, the increase in beds took a number of years to materialise and showed a dose-response; higher-funded counties had bigger increases. Secondly, the funding reduced private hospital bed capacity. The net effect on overall hospital beds was positive, so the program affected the composition of the hospital sector. Although this would be expected given that it substantially affected the relative costs of different types of hospital bed. And thirdly, hospital utilisation increased in line with the increases in capacity, indicating a previously unmet need for health care. Again, this was expected given the motivation for the program in the first place. It isn’t often that results turn out as neatly as this – the effects are exactly as one would expect and are large in magnitude. If only all research projects turned out this way.