Chris Sampson’s journal round-up for 4th June 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.

A qualitative investigation of the health economic impacts of bariatric surgery for obesity and implications for improved practice in health economics. Health Economics [PubMed] Published 1st June 2018

Few would question the ‘economic’ nature of the challenge of obesity. Bariatric surgery is widely recommended for severe cases but, in many countries, the supply is not sufficient to satisfy the demand. In this context, this study explores the value of qualitative research in informing economic evaluation. The authors assert that previous economic evaluations have adopted a relatively narrow focus and thus might underestimate the expected value of bariatric surgery. But rather than going and finding data on what they think might be additional dimensions of value, the authors ask patients. Emotional capital, ‘societal’ (i.e. non-health) impacts, and externalities are identified as theories for the types of value that might be derived from bariatric surgery. These theories were used to guide the development of questions and prompts that were used in a series of 10 semi-structured focus groups. Thematic analysis identified the importance of emotional costs and benefits as part of the ‘socioemotional personal journey’ associated with bariatric surgery. Out-of-pocket costs were also identified as being important, with self-funding being a challenge for some respondents. The information seems useful in a variety of ways. It helps us understand the value of bariatric surgery and how individuals make decisions in this context. This information could be used to determine the structure of economic evaluations or the data that are collected and used. The authors suggest that an EQ-5D bolt-on should be developed for ’emotional capital’ but, given that this ‘theory’ was predefined by the authors and does not arise from the qualitative research as being an important dimension of value alongside the existing EQ-5D dimensions, that’s a stretch.

Developing accessible, pictorial versions of health-related quality-of-life instruments suitable for economic evaluation: a report of preliminary studies conducted in Canada and the United Kingdom. PharmacoEconomics – Open [PubMed] Published 25th May 2018

I’ve been telling people about this study for ages (apologies, authors, if that isn’t something you wanted to read!). In my experience, the need for more (cognitively / communicatively) accessible outcome measures is widely recognised by health researchers working in contexts where this is relevant, such as stroke. If people can’t read or understand the text-based descriptors that make up (for example) the EQ-5D, then we need some alternative format. You could develop an entirely new measure. Or, as the work described in this paper set out to do, you could modify existing measures. There are three descriptive systems described in this study: i) a pictorial EQ-5D-3L by the Canadian team, ii) a pictorial EQ-5D-3L by the UK team, and iii) a pictorial EQ-5D-5L by the UK team. Each uses images to represent the different levels of the different dimensions. For example, the mobility dimension might show somebody walking around unaided, walking with aids, or in bed. I’m not going to try and describe what they all look like, so I’ll just encourage you to take a look at the Supplementary Material (click here to download it). All are described as ‘pilot’ instruments and shouldn’t be picked up and used at this stage. Different approaches were used in the development of the measures, and there are differences between the measures in terms of the images selected and the ways in which they’re presented. But each process referred to conventions in aphasia research, used input from clinicians, and consulted people with aphasia and/or their carers. The authors set out several remaining questions and avenues for future research. The most interesting possibility to most readers will be the notion that we could have a ‘generic’ pictorial format for the EQ-5D, which isn’t aphasia-specific. This will require continued development of the pictorial descriptive systems, and ultimately their validation.

QALYs in 2018—advantages and concerns. JAMA [PubMed] Published 24th May 2018

It’s difficult not to feel sorry for the authors of this article – and indeed all US-based purveyors of economic evaluation in health care. With respect to social judgments about the value of health technologies, the US’s proverbial head remains well and truly buried in the sand. This article serves as a primer and an enticement for the use of QALYs. The ‘concerns’ cited relate almost exclusively to decision rules applied to QALYs, rather than the underlying principles of QALYs, presumably because the authors didn’t feel they could ignore the points made by QALY opponents (even if those arguments are vacuous). What it boils down to is this: trade-offs are necessary, and QALYs can be used to promote value in those trade-offs, so unless you offer some meaningful alternative then QALYs are here to stay. Thankfully, the Institute for Clinical and Economic Review (ICER) has recently added some clout to the undeniable good sense of QALYs, so the future is looking a little brighter. Suck it up, America!

The impact of hospital costing methods on cost-effectiveness analysis: a case study. PharmacoEconomics [PubMed] Published 22nd May 2018

Plugging different cost estimates into your cost-effectiveness model could alter the headline results of your evaluation. That might seems obvious, but there are a variety of ways in which the selection of unit costs might be somewhat arbitrary or taken for granted. This study considers three alternative sources of information for hospital-based unit costs for hip fractures in England: (a) spell-level tariffs, (b) finished consultant episode (FCE) reference costs, and (c) spell-level reference costs. Source (b) provides, in theory, a more granular version of (a), describing individual episodes within a person’s hospital stay. Reference costs are estimated on the basis of hospital activity, while tariffs are prices estimated on the basis of historic reference costs. The authors use a previously reported cohort state transition model to evaluate different models of care for hip fracture and explore how the use of the different cost figures affects their results. FCE-level reference costs produced the highest total first-year hospital care costs (£14,440), and spell-level tariffs the lowest (£10,749). The more FCEs within a spell, the greater the discrepancy. This difference in costs affected ICERs, such that the net-benefit-optimising decision would change. The study makes an important point – that selection of unit costs matters. But it isn’t clear why the difference exists. It could just be due to a lack of precision in reference costs in this context (rather than a lack of accuracy, per se), or it could be that reference costs misestimate the true cost of care across the board. Without clear guidance on how to select the most appropriate source of unit costs, these different costing methodologies represent another source of uncertainty in modelling, which analysts should consider and explore.

Credits

Thesis Thursday: Sarah Zheng

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 Sarah Zheng who has a PhD from Boston University. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Design for performance: studies on cost and quality in U.S. health care
Supervisors
Z. Justin Ren, Kimberley H. Geissler, Janelle Heineke, Anita Tucker
Repository link
https://open.bu.edu/handle/2144/23312

In the context of your PhD research, what does ‘design for performance’ mean?

“Design for performance” is a further step in managing healthcare from “pay for performance”, on which there has been decades of attention paid among practitioners and academics. Despite the long effort on “pay for performance”, the core challenge remains how to properly incentivize patients, clinicians and staff to align their behaviors with optimal, safe and cost-effective, patient-centric care. This dissertation suggests an important set of issues to consider around “design for performance” at the system and process levels.

At the system level, under what conditions does cost-sharing lead to lower total costs without reducing quality of care? Previous literature has studied contract theory and mechanism design in varied industry settings (Guajardo et al. 2012), yet very few are studied in the healthcare domain where insurance plans are offered to patients under different contract arrangements. It remains unclear whether certain contract design at such settings may lead to desired outcomes (e.g., low healthcare spending). At the process level, under what conditions and to what extent does excellent internal supply operations result in superior hospital performance? Industrial studies suggest that reliable, efficient internal supply chains that are integrated with production yield better financial and quality performance for manufacturing companies (Droge et al. 2004, Flynn et al. 2010). However, there is scant quantitative research on the impact of support departments in hospitals (Tucker et al. 2008, Fredendall et al. 2009). Studies are needed to understand the extent to which support departments impact patient care outcomes, such as adverse events.

How was quality captured in the data that you used in your analyses?

In Chapter 3 of my thesis, I studied the impact of internal service quality on one particular quality performance metric: adverse events. Specifically, it is a rate variable that is calculated by the sum of adverse events (i.e., patient falls with injury and pressure ulcers) on the unit that month divided by the number of patient days on the unit that month, which is then multiplied by 1,000. The hospital collects these data monthly. The adverse event data come from both patient record reviews and incident reports in the hospital’s safety reporting system, as is typical of this type of data (Lake and Cheung 2006). The error event data are audited internally as well as reported to CMS (Zheng et al. 2017).

This is a unique opportunity to study quality as most healthcare operations research has relied on publicly available, hospital-level quality data, such as patient mortality (e.g., Senot et al. 2015, KC and Terwiesch 2011)—which is a blunt measure of quality—or process of care measures (e.g., Boyer et al. 2012, Gardner et al. 2015, Senot et al. 2015), which have been criticized in the healthcare literature for their weak connection to clinical outcomes (Patterson et al. 2010).

You complemented your quantitative analysis with some qualitative interviews – was this a valuable exercise?

Yes, definitely. To understand further the role patients (and the patient-physician dyad) play in deciding the usage of imaging studies, I conducted in-depth conversations with both physicians and patients. Specifically, I interviewed three physicians (i.e., hospitalist, primary care provider) and one imaging technician with the average conversation time of 70 mins. I also interviewed six patients with the average conversation time of 20 mins.

I found that patients did play a role in deciding the usage of imaging studies in the way that high-deductible health plan (HDHP) patients are less likely to demand imaging studies than non-HDHP patients. However, as patients cannot distinguish low-value care from high-value care, HDHP patients avoid patient care in general. This is consistent with previous literature on patient cost-sharing and HDHPs where patients indiscriminately reduce medical care (Hibbard et al. 2008, Lohr et al. 1986). It further suggests that HDHP may be a blunt instrument, reducing all diagnostic imaging, rather than helping physicians and patients choose high-value imaging.

Did any of your findings about high-deductible health plans stand out as different from previous studies?

I wouldn’t say different but more like complementary. Previous studies found HDHPs have different impacts depending on the site and type of care (Haviland et al. 2015, Wharam et al. 2013, Bundorf 2012, Nair et al. 2009, Waters et al. 2011, Hibbard et al. 2008, Busch et al. 2006, Rowe et al. 2008, Parente et al. 2004). By explicitly testing associations between HDHP enrollment and diagnostic imaging, we provide a more complete picture for policymakers in making guidelines related to HDHP plans. Our results suggest that increases in HDHP enrollment may contribute to a slow in the growth of diagnostic imaging utilization. However, increased cost-sharing may not allow patients to differentiate between high-value and low-value utilization, and better patient awareness and education should be a crucial part of any reductions in diagnostic imaging utilization (Zheng et al. 2016).

‘Internal service quality’ is a term that doesn’t often appear in health economics journals – should researchers be dedicating more attention to this?

Yes. In our study we find improved internal service quality to be a particularly novel driver of reduced adverse events because it is not obvious a priori that support departments—most of which are not clinical in nature—could have a significant impact on clinical outcomes. In particular, we find that improving the overall average internal service quality received by a nursing unit by 0.1 on a 5-point scale is associated with a 38% reduction in adverse events per nursing unit, which has roughly the same benefit for reducing adverse events as increasing staffing on that unit by nearly one full-time equivalent nurse. In the hospital that we study, the average salary of a support service technician is lower than the average salary of a nurse. Thus, hospitals might be able to improve quality of care at a lower cost by increasing support staff to relieve the burden on nurses (Zheng et al. 2017). More studies are needed in this area to explore further internal service quality as a viable and cost-effective means to improve clinical performance.

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.

Title
Essays on hospital performance in England
Supervisor
Luigi Siciliani
Repository link
http://etheses.whiterose.ac.uk/18975/

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.