Mauro Laudicella

This study measures the increment of health care expenditure (HCE) that can be attributed to technological progress and change in medical practice by using a residual approach and microdata. We examine repeated cross‐sections of individuals experiencing an initial health shock at different point in time over a 10‐year window and capture the impact of unobservable technology and medical practice to which they are exposed after allowing for differences in health and socioeconomic characteristics. We decompose the residual increment in the part that is due to the effect of delaying time to death, that is, individuals surviving longer after a health shock and thus contributing longer to the demand of care, and the part that is due to increasing intensity of resource use, that is, the basket of services becoming more expensive to allow for the cost of innovation. We use data from the Danish National Health System that offers universal coverage and is free of charge at the point of access. We find that technological progress and change in medical practice can explain about 60% of the increment of HCE, in line with macroeconomic studies that traditionally investigate this subject.

Summary: This paper develops an extension of the class of finite mixture models for longitudinal count data to the bivariate case by using a hidden Markov chain approach. The model allows for disentangling unobservable time‐varying heterogeneity from the dynamic effect of utilisation of primary and secondary care and measuring their potential substitution effect. Three points of supports adequately describe the distribution of the latent states suggesting the existence of three profiles of low, medium and high users who shows persistency in their behaviour, but not permanence as some switch to their neighbour's profile.

Studies on alternative routes to diagnosis stimulated successful policy interventions reducing the number of emergency diagnoses and associated mortality risk. A dearth of evidence on the costs of such interventions might prevent new policies from achieving more ambitious targets. We conducted a retrospective cohort study on the population of colorectal (88,051), breast (90,387), prostate (96,219), and lung (97,696) cancer patients diagnosed after a GP referral or an emergency presentation and reported in the Cancer Registry of England. Resource use and survival were compared 1 year before and 5 years after diagnosis (3 years for lung), including the costs of GP referrals not converted into a positive diagnosis. Risk-adjusted statistical models were used to calculate the effect of rerouting patient’ diagnoses from emergency presentation to GP referral. Rerouting a cancer diagnosis results in a relatively small additional costs to the National Health System against additional years of life saved to the patient. The cost per year of life saved is £6456 in colorectal, £1057 in breast, −£662 in prostate (savings), and £819 in lung cancer. Reducing the overall prevalence of emergency presentations to the level achieved by the 20% of Clinical Commissioning Groups with the lowest prevalence would result in £11,481,948 against 1863 years of life saved for Colorectal, £847,750 against 889 years for breast, −£943,434 (cost savings) against 1195 years for prostate, and £609,938 against 1011 years for lung cancer. Redirecting diagnoses from emergency presentation to GP referral appears an achievable target that can produce large benefits to patients against modest additional costs to the National Health System.

Objectives: To measure the impact of the improvement in hospital survival rates on patients’ subsequent utilization of unplanned (emergency) admissions.Data Sources/Study Setting: Unplanned admissions occurring in all acute hospitals of the National Health Service in England between 2000 and 2009, including 286,027 hip fractures, 375,880 AMI, 387,761 strokes, and 9,966,246 any cause admissions.Study Design: Population‐based retrospective cohort study. Unplanned admissions experienced by patients within 28 days, 1 year, and 2 years of discharge from the index admission are modeled as a function of hospital risk‐adjusted survival rates using patient‐level probit and negative binomial models. Identification is also supported by an instrumental variable approach and placebo test.Principal Findings: The improvement in hospital survival rates that occurred between 2000 and 2009 explains 37.3 percent of the total increment in unplanned admissions observed over the same period. One extra patient surviving increases the expected number of subsequent admissions occurring within 1 year from discharge by 1.9 admissions for every 100 index admissions (0.019 per admission, 95% CI, 0.016–0.022). Similar results in hip fracture (0.006[0.004–0.007]), AMI (0.006[0.04–0.007]), and stroke (0.004(0.003–0.005)).Conclusions: The success of hospitals in improving survival from unplanned admissions can be an important contributory factor to the increase in subsequent admissions.

In universal health care systems such as the English National Health Service, equality of access is a core principle, and health care is free at the point of delivery. However, even within a universal system, disparities in care and costs exist along a socioeconomic gradient. Little is known about socioeconomic disparities at the end of life and how they affect health care costs. This study examines disparities in end-of-life treatment costs for cancer patients in England. Analyzing data on over 250,000 colorectal, breast, prostate, and lung cancer patients from multiple national databases, we found evidence illustrating that disparities are driven largely by the greater use of emergency inpatient care among patients of lower socioeconomic status. Even within a system with free health care, differences in the use of care create disparities in cancer costs. While further studies of these barriers is required, our research suggests that disparities may be reduced through better management of needs through the use of less expensive and more effective health care settings and treatments.

Objective Laparoscopy is increasingly being used as an alternative to open surgery in the treatment of patients with colon cancer. The study objective is to estimate the difference in hospital costs between laparoscopic and open colon cancer surgery. Design Population-based retrospective cohort study. Settings All acute hospitals of the National Health System in England. Population A total of 55 358 patients aged 30 and over with a primary diagnosis of colon cancer admitted for planned (elective) open or laparoscopic major resection between April 2006 and March 2013. Primary outcomes Inpatient hospital costs during index admission and after 30 and 90 days following the index admission. Results Propensity score matching was used to create comparable exposed and control groups. The hospital cost of an index admission was estimated to be £1933 (95% CI 1834 to 2027; pConclusions Laparoscopy is associated with lower hospital costs than open surgery in elective patients with colon cancer suitable for both interventions.

Background: Inequalities in health-care access and outcomes raise concerns about quality of care and justice, and the NHS has a statutory duty to consider reducing them.Objectives: The objectives were to (1) develop indicators of socioeconomic inequality in health-care access and outcomes at different stages of the patient pathway; (2) develop methods for monitoring local NHS equity performance in tackling socioeconomic health-care inequalities; (3) track the evolution of socioeconomic health-care inequalities in the 2000s; and (4) develop ‘equity dashboards’ for communicating equity findings to decision-makers in a clear and concise format.Design: Longitudinal whole-population study at the small-area level.Setting: England from 2001/2 to 2011/12.Participants: A total of 32,482 small-area neighbourhoods (lower-layer super output areas) of approximately 1500 people.Main outcome measures: Slope index of inequality gaps between the most and least deprived neighbourhoods in England, adjusted for need or risk, for (1) patients per family doctor, (2) primary care quality, (3) inpatient hospital waiting time, (4) emergency hospitalisation for chronic ambulatory care-sensitive conditions, (5) repeat emergency hospitalisation in the same year, (6) dying in hospital, (7) mortality amenable to health care and (8) overall mortality.Data sources: Practice-level workforce data from the general practice census (indicator 1), practice-level Quality and Outcomes Framework data (indicator 2), inpatient hospital data from Hospital Episode Statistics (indicators 3–6) and mortality data from the Office for National Statistics (indicators 6–8).Results: Between 2004/5 and 2011/12, more deprived neighbourhoods gained larger absolute improvements on all indicators except waiting time, repeat hospitalisation and dying in hospital. In 2011/12, there was little measurable inequality in primary care supply and quality, but inequality was associated with 171,119 preventable hospitalisations and 41,123 deaths amenable to health care. In 2011/12, > 20% of Clinical Commissioning Groups performed statistically significantly better or worse than the England equity benchmark.Limitations: General practitioner supply is a limited measure of primary care access, need in deprived neighbourhoods may be underestimated because of a lack of data on multimorbidity, and the quality and outcomes indicators capture only one aspect of primary care quality. Health-care outcomes are adjusted for age and sex but not for other risk factors that contribute to unequal health-care outcomes and may be outside the control of the NHS, so they overestimate the extent of inequality for which the NHS can reasonably be held responsible.Conclusions: NHS actions can have a measurable impact on socioeconomic inequality in both health-care access and outcomes. Reducing inequality in health-care outcomes is more challenging than reducing inequality of access to health care. Local health-care equity monitoring against a national benchmark can be performed using any administrative geography comprising ≥ 100,000 people.Future work: Exploration of quality improvement lessons from local areas performing well and badly on health-care equity, improved methods including better measures of need and risk and measures of health-care inequality over the life-course, and monitoring of other dimensions of equity. These indicators can also be used to evaluate the health-care equity impacts of interventions and make international health-care equity comparisons.Funding: The National Institute for Health Research Health Services and Delivery Research programme.