Health Care Spending Effectiveness: Estimates Suggest That Spending Improved US Health From 1996 To 2016

Systematic review of the impact of health care expenditure on health outcome measures: implications for cost-effectiveness thresholds

OBJECTIVE

Empirical estimates of the impact of healthcare expenditure on health outcome measures may inform the cost-effectiveness threshold (CET) for guiding funding decisions. This study aims to systematically review studies that estimated this, summarize and compare the estimates by country income level.

METHODS

We searched PubMed, Scopus, York Research database, and [anonymized] for Reviews and Dissemination database from inception to 1 August 2023. For inclusion, a study had to be an original article, estimating the impact of healthcare expenditure on health outcome measures at a country level, and presented estimates, in terms of cost per quality-adjusted life year (QALY) or disability-adjusted life year (DALY).

RESULTS

We included 18 studies with 385 estimates. The median (range) estimates were PPP$ 11,224 (PPP$ 223 - PPP$ 288,816) per QALY gained and PPP$ 5,963 (PPP$ 71 - PPP$ 165,629) per DALY averted. As ratios of Gross Domestic Product per capita (GDPPC), these estimates were 0.376 (0.041-182.840) and 0.318 (0.004-37.315) times of GDPPC, respectively.

CONCLUSIONS

The commonly used CET of GDPPC seems to be too high for all countries, but especially low-to-middle-income countries where the potential health losses from misallocation of the same money are greater.

REGISTRATION

The review protocol was published and registered in PROSPERO (CRD42020147276).

Economic Burden of Sanfilippo Syndrome in the United States

Introduction

Sanfilippo syndrome is a rare disease and fatal genetic disorder with no FDA-approved treatment in the United States (US), and no comprehensive assessment of economic disease burden is available.

Objectives

To develop a model to estimate the economic burden associated with Sanfilippo syndrome in the US using direct costs, indirect costs and valued intangibles (disability-adjusted life years, or DALYs) from 2023 onward.

Design and Setting

A multistage comorbidity model was generated based on Sanfilippo syndrome symptoms, and disability weights from the 2010 Global Burden of Disease Study. Attributable increase in caregiver mental health burden were estimated using data from the CDC National Comorbidity Survey and retrospective studies on caregiver burden. Direct costs were approximated from the 2019 EveryLife Foundation survey, and indirect costs were estimated from Federal income data. Monetary valuations were adjusted to USD 2023 and given a 3% discount rate from 2023 onward.

Main Outcome Measures

Incidence of Sanfilippo syndrome was calculated for each year, and year-over-year DALYs due to patient years lived with disability (YLDs) and years life lost (YLLs) were calculated by comparing to the health-adjusted life expectancy (HALE) in the US. Direct and indirect costs were calculated for each simulated patient from onset of symptoms to death.

Results

From 2023-2043, overall economic burden in the US attributable to Sanfilippo syndrome was estimated to be $2.04 billion USD present value (2023) with current standard of care. The burden to individual families exceeded $8 million present value from time of birth per child born with Sanfilippo syndrome.

Conclusion

Sanfilippo syndrome is a rare lysosomal storage disease, however the severe burden associated with the disease for individual families demonstrates a considerable cumulative impact. Our model represents the first disease burden value estimate associated with Sanfilippo syndrome, and underscores the substantial morbidity and mortality burden of Sanfilippo syndrome.

What drives health care spending in Switzerland? Findings from a decomposition by disease, health service, sex, and age

BACKGROUND

High and increasing spending dominates the public discussion on healthcare in Switzerland. However, the drivers of the spending increase are poorly understood. This study decomposes health care spending by diseases and other perspectives and estimates the contribution of single cost drivers to overall healthcare spending growth in Switzerland between 2012 and 2017.

METHODS

We decompose total healthcare spending according to National Health Accounts by 48 major diseases, injuries, and other conditions, 20 health services, 21 age groups, and sex of patients. This decomposition is based on micro-data from a multitude of data sources such as the hospital inpatient registry, health and accident insurance claims data, and population surveys. We identify the contribution of four main drivers of spending: population growth, change in population structure (age/sex distribution), changes in disease prevalence, and changes in spending per prevalent patient.

RESULTS

Mental disorders were the most expensive major disease group in both 2012 and 2017, followed by musculoskeletal disorders and neurological disorders. Total health care spending increased by 19.7% between 2012 and 2017. An increase in spending per prevalent patient was the most important spending driver (43.5% of total increase), followed by changes in population size (29.8%), in population structure (14.5%), and in disease prevalence (12.2%).

CONCLUSIONS

A large part of the recent health care spending growth in Switzerland was associated with increases in spending per patient. This may indicate an increase in the treatment intensity. Future research should show if the spending increases were cost-effective.