The growth in cost per case explains far more of US health spending increases than rising disease prevalence

Cost of postoperative complications of lower anterior resection for rectal cancer: a nationwide registry study of 15,187 patients

PURPOSE

To assess the increase in hospital costs associated with postoperative complications after lower anterior resection (LAR) for rectal cancer.

METHODS

The subjects of this retrospective analysis were patients who underwent elective LAR surgery between April, 2015 and March, 2017, collected from a Japanese nationwide gastroenterological surgery registry linked to hospital-based claims data. We evaluated total and category-specific hospitalization costs based on the level of postoperative complications categorized using the Clavien-Dindo (CD) classification. We assessed the relative increase in hospital costs, adjusting for preoperative factors and hospital case volume.

RESULTS

We identified 15,187 patients (mean age 66.8) treated at 884 hospitals. Overall, 71.8% had no recorded complications, whereas 7.6%, 10.8%, 9.0%, 0.6%, and 0.2% had postoperative complications of CD grades I-V, respectively. The median (25th-75th percentiles) hospital costs were $17.3 K (16.1-19.3) for the no-complications group, and $19.1 K (17.3-22.2), $21.0 K (18.5-25.0), $27.4 K (22.4-33.9), $41.8 K (291-618), and $22.7 K (183-421) for the CD grades I-V complication groups, respectively. The multivariable model identified that complications of CD grades I-V were associated with 11%, 21%, 61%, 142%, and 70% increases in in-hospital costs compared with no complications.

CONCLUSIONS

Postoperative complications and their severity are strongly associated with increased hospital costs and health-care resource utilization. Implementing strategies to prevent postoperative complications will improve patients' clinical outcomes and reduce hospital care costs substantially.

What is the major driver of China's hospital medical expenditure growth? A decomposing analysis

OBJECTIVES

This study aimed to quantify increases in the medical expenditures of public hospitals associated with changes in service use and prices, which could inform policy efforts to curb the future growth of hospital medical expenditures.

DESIGN

Nationwide and provincial data regarding service volume, service price and intensity of public hospitals' outpatient and inpatient care from 2008 to 2018 were extracted from the China Health Statistical Yearbooks, and population size data were obtained from the 2019 China Statistical Yearbook.

METHODS

A decomposition analysis was performed to measure the relative effects of changes in service use (volume or its subcomponent factors) and service price and intensity on the increase in the inpatient and outpatient total medical expenditures of public hospitals from 2008 to 2018.

RESULTS

After adjusting for price inflation, the total medical expenditure of public hospitals increased by approximately threefold from 2008 to 2018. During this period, the increase in service volume was associated with 67.4% of the observed increase in the total medical expenditures in the inpatient sector and 57.2% of the observed increase in the total medical expenditures in the outpatient sector. Most of the service volume effect is due to an increase in the hospital utilisation rate. The growth in the utilisation rate was associated with 73.7% of the observed growth in the total medical expenditures in the inpatient sector and 60.3% of the observed growth in the total medical expenditures in the outpatient sector.

CONCLUSION

Service use, rather than price, appears to be the major driver of increases in medical expenditures in Chinese hospitals. An important policy implication for China and other countries with similar drivers is that the effect of controlling price and intensity growth on containing medical costs could be limited and controlling service utilisation growth could be essential.

Decomposition of outpatient health care spending by disease - a novel approach using insurance claims data

Background

Decomposing health care spending by disease, type of care, age, and sex can lead to a better understanding of the drivers of health care spending. But the lack of diagnostic coding in outpatient care often precludes a decomposition by disease. Yet, health insurance claims data hold a variety of diagnostic clues that may be used to identify diseases.

Methods

In this study, we decompose total outpatient care spending in Switzerland by age, sex, service type, and 42 exhaustive and mutually exclusive diseases according to the Global Burden of Disease classification. Using data of a large health insurance provider, we identify diseases based on diagnostic clues. These clues include type of medication, inpatient treatment, physician specialization, and disease specific outpatient treatments and examinations. We determine disease-specific spending by direct (clues-based) and indirect (regression-based) spending assignment.

Results

Our results suggest a high precision of disease identification for many diseases. Overall, 81% of outpatient spending can be assigned to diseases, mostly based on indirect assignment using regression. Outpatient spending is highest for musculoskeletal disorders (19.2%), followed by mental and substance use disorders (12.0%), sense organ diseases (8.7%) and cardiovascular diseases (8.6%). Neoplasms account for 7.3% of outpatient spending.

Conclusions

Our study shows the potential of health insurance claims data in identifying diseases when no diagnostic coding is available. These disease-specific spending estimates may inform Swiss health policies in cost containment and priority setting.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07262-x.

What has driven acute public hospital expenditure growth in South Australia? An analysis of the relative importance of major expenditure drivers between 2006-07 and 2017-18

ObjectiveThe aim of this study was to investigate whether increasing costs of delivering care have driven real growth in acute public hospital expenditure in South Australia (SA) and what has contributed to these real cost increases.MethodsUsing published time-series data, we decomposed inflation-adjusted growth in per capita total acute public hospital recurrent expenditure into its major utilisation and cost components to evaluate their relative contribution over the 12 years to 2017-18.ResultsReal per capita total acute public hospital recurrent expenditure grew by AU$667 (45.2%) over the 12-year period; of this, 86.0% was from real growth in input costs per weighted activity unit, with real growth in the average salaries of hospital staff accounting for AU$247 or 37.0%. Hospital utilisation rates contributed a minor 14.0%.ConclusionOver the 12 years to 2017-18, real growth in average clinical salaries was a more important driver of real growth in per capita total acute public hospital expenditure than rates of hospital utilisation. This would be facilitated by improvements in the scope, accuracy, quality and consistency of published national hospital data.What is known about the topic?Public hospital expenditure is one of the largest and fastest growing areas of government expenditure in Australia. Policy narratives often centre around demand pressures from an increasingly older, overweight, and chronically ill population. Comparatively little attention has been paid to the influence of increases in real input costs within the Australian context.What does this paper add?Real salary growth has been a major driver of acute public hospital recurrent expenditure growth in SA, whereas hospital utilisation rates have played a minor role.What are the implications for practitioners?A clearer understanding of the main drivers of acute public hospital expenditure growth and the resulting benefits to population health is needed to guide the efficient and sustainable use of scarce healthcare resources.

Factors related to the change in Swiss inpatient costs by disease: a 6-factor decomposition

There is currently little systematic knowledge about the contribution of different factors to the increase in health care spending in high-income countries such as Switzerland. The aim of this paper is to decompose inpatient care costs in the Swiss canton of Zurich by 100 diseases and 42 age/sex groups and to assess the contribution of six factors to the change in aggregate costs between 2013 and 2017. These six factors are population size, age and sex structure, inpatient treated prevalence, utilization in terms of stays per patient, length of stay per case, and costs per treatment day. Using detailed inpatient cost data at the case level, we find that the most important contributor to the change in disease-specific costs was a rise in costs per treatment day. For most conditions, this effect was partly offset by a reduction in the average length of stay. Changes in population size accounted for one third of the total increase, but population structure had only a small positive association with costs. The most expensive cases accounted for the largest part of the increase in costs, but the magnitude of this effect differed across diseases. A better understanding of the factors related to cost changes at the disease level over time is essential for the design of targeted health policies aiming at an affordable health care system.

Economic Burden and Healthcare Resource Use for Thoracic Aortic Dissections and Thoracic Aortic Aneurysms-A Population-Based Cost-of-Illness Analysis

Background

Thoracic aortic dissections (TADs) and thoracic aortic aneurysms (TAAs) are resource intensive. We sought to determine economic burden and healthcare resource use to guide health policy.

Methods and Results

Using universal healthcare coverage data for Ontario, Canada, from 2003 to 2016, a cost‐of‐illness analysis was performed. From a single‐payer's perspective, direct costs (hospitalization, reinterventions, readmissions, rehabilitation, extended care, home care, prescription drugs, and imaging) were assessed in 2017 Canadian dollars. Controls without TADs or TAAs were matched 10:1 on age, sex, and socioeconomic status to cases with TADs or TAAs to compare posthospital service use to the general population. Linear and spline regression were used for cost trends. Total hospital costs increased from $9 M to $20.7 M for TADs (P<0.0001) and $13 M to $18 M for TAAs (P<0.001). Costs cumulated to $587 M for 17 113 cases. Median hospital costs for TADs were $11 525 ($6102 medical, $26 896 endograft, and $30 372 surgery) with an increase over time (P=0.04). For TAAs, median costs were $16 683 ($7247 medical, $11 679 endograft, and $22 949 surgery) with a decrease over time (P=0.03). Home care was the most used posthospital service (TADs 44%, TAAs 38%), but rehabilitation had the highest median cost (TADs $11.9 M, TAAs $11 M). Men had increased median costs for indexed hospitalizations relative to women, yet women used more posthospital services with higher service costs.

Conclusions

Total yearly costs have increased for TADs and TAAs. Median hospital costs have increased for TADs yet decreased for TAAs. Women use posthospital healthcare services more often than men.

Stanford's Biodesign Innovation program: Teaching opportunities for value-driven innovation in surgery

The Stanford Biodesign Innovation process, which identifies meaningful clinical needs, develops solutions to meet those needs, and plans for subsequent implementation in clinical practice, is an effective training approach for new generations of healthcare innovators. Continued success of this process hinges on its evolution in response to changes in healthcare delivery and an ever-increasing demand for economically viable solutions. In this article, we provide perspective on opportunities for value-driven innovation in surgery and relate these to value-related teaching elements currently integrated in the Stanford Biodesign process.

Secular trends in cognitive trajectories of diverse older adults

INTRODUCTION

This study aimed to determine if later birth year influences trajectory of age-related cognitive decline across racial/ethnic groups and to test whether years of school, childhood socioeconomic status, and cardiovascular disease burden explain such secular trends.

METHODS

We compared cognitive trajectories of global cognition and subdomains in two successive racially/ethnically and educationally diverse birth cohorts of a prospective cohort study.

RESULTS

Later birth year was associated with higher initial cognitive levels for Whites and Blacks, but not Hispanics. Later birth year was also associated with less rapid rate of decline in all three racial/ethnic groups. More years of education, higher childhood socioeconomic status, and, to a smaller extent, greater cardiovascular disease burden accounted for higher intercepts in the later-born cohort, but did not account for attenuated slope of cognitive decline.

DISCUSSION

Later birth year is related to a slower rate of age-related decline in some cognitive domains in some racial/ethnic groups. Our analyses suggest that racial/ethnic and social inequalities are part of the mechanisms driving secular trends in cognitive aging and dementia.

Relative contribution of overweight and obesity to rising public hospital in-patient expenditure in South Australia

Objective Arguments to fund obesity prevention have often focused on the growing hospital costs of associated diseases. However, the relative contribution of overweight and obesity to public hospital expenditure growth is not well understood. This paper examines the effect of overweight and obesity on acute public hospital in-patient expenditure in South Australia over time compared with other expenditure drivers. Methods Annual inflation-adjusted acute public admitted expenditure attributable to a high body mass index was estimated for 2007-08 and 2011-12 and compared with other expenditure drivers. Results Expenditure attributable to overweight and obesity increased by A$45million, from 4.7% to 5.4% of total acute public in-patient expenditure. This increase accounted for 7.8% of the A$583million total expenditure growth, whereas the largest component of total growth (62.4%) was a real increase in the average cost per separation. Conclusions The relatively minor contribution of overweight and obesity to expenditure growth over the time period examined invites reflection on arguments to boost preventive spending that centre upon reducing hospital costs. These arguments may inadvertently detract attention from the considerable health and social burdens of overweight and obesity and from unrelated sources of expenditure growth that reduce opportunities for state governments to fund obesity prevention programs despite their comparative benefits to population health. What is known about the topic? Stand-alone estimates suggest that overweight and obesity are placing a considerable financial burden on the Australian public healthcare system. What does this paper add? Our findings challenge common perceptions about the relative importance of overweight and obesity in the context of rising public in-patient expenditure in Australia. What are the implications for practitioners? Consistent serial estimates of overweight- and obesity-attributable expenditure enable its tracking and comparison with other potentially controllable expenditure drivers that may also warrant attention. Explicit consideration of population health trade-offs in expenditure-related decisions, including in enterprise bargaining, would enhance transparency in priority setting.

Decomposing changes in the growth of U.S. prescription drug use and expenditures, 1999-2016

OBJECTIVE

To analyze factors associated with changes in prescription drug use and expenditures in the United States from 1999 to 2016, a period of rapid growth, deceleration, and resumed above-average growth.

DATA SOURCES/STUDY SETTING

The Medical Expenditure Panel Survey (MEPS), containing household and pharmacy information on over five million prescription drug fills.

STUDY DESIGN

We use nonparametric decomposition to analyze drug use, average payment per fill, and per capita expenditure, tracking the contributions over time of socioeconomic characteristics, health status and treated conditions, insurance coverage, and market factors surrounding the patent cycle.

DATA COLLECTION/EXTRACTION METHODS

Medical Expenditure Panel Survey data were combined with information on drug approval dates and patent status.

PRINCIPAL FINDINGS

Per capita utilization increased by nearly half during 1999-2016, with changes in health status and treated conditions accounting for four-fifths of the increase. In contrast, per capita expenditures more than doubled, with individual characteristics only explaining one-third of the change. Other drivers of spending during this period include the changing pipeline of new drugs, drugs losing exclusivity, and changes in generic competition.

CONCLUSIONS

Long-term trends in treated conditions were the fundamental drivers of medication use, whereas factors involving the patent cycle accelerated and decelerated spending growth relative to trends in use.

How much does the treatment of each major disease cost? A decomposition of Swiss National Health Accounts

In most countries, surprisingly little is known on how national healthcare spending is distributed across diseases. Single-disease cost-of-illness studies cover only a few of the diseases affecting a population and in some cases lead to untenably large estimates. The objective of this study was to decompose healthcare spending in 2011, according to Swiss National Health Accounts, into 21 collectively exhaustive and mutually exclusive major disease categories. Diseases were classified following the Global Burden of Disease Study. We first assigned the expenditures directly mapping from National Health Accounts to the 21 diseases. The remaining expenditures were assigned based on diagnostic codes and clues contained in a variety of microdata sources. Expenditures were dominated by non-communicable diseases with a share of 79.4%. Cardiovascular diseases stood out with 15.6% of total spending, followed by musculoskeletal disorders (13.4%), and mental and substance use disorders (10.6%). Neoplasms (6.0% of the total) ranked only sixth, although they are the leading cause of premature death in Switzerland. These results may be useful for the design of health policies, as they illustrate how healthcare spending is influenced by the epidemiological transition and increasing life expectancy. They also provide a plausibility check for single cost-of-illness studies. Our study may serve as a starting point for further research on the drivers of the constant growth of healthcare spending.

Understanding Trends in Medicare Spending, 2007-2014

OBJECTIVES

To analyze the sources of per-beneficiary Medicare spending growth between 2007 and 2014, including the role of demographic characteristics, attributes of Medicare coverage, and chronic conditions.

DATA SOURCES

Individual-level Medicare spending and enrollment data.

STUDY DESIGN

Using an Oaxaca-Blinder decomposition model, we analyzed whether changes in price-standardized, per-beneficiary Medicare Part A and B spending reflected changes in the composition of the Medicare population or changes in relative spending levels per person.

DATA EXTRACTION METHODS

We identified a 5 percent sample of fee-for-service Medicare beneficiaries age 65 and above from years 2007 to 2014.

RESULTS

Mean payment-adjusted Medicare per-beneficiary spending decreased by $180 between the 2007-2010 and 2011-2014 time periods. This decline was almost entirely attributable to lower spending levels for beneficiaries. Notably, declines in marginal spending levels for beneficiaries with chronic conditions were associated with a $175 reduction in per-beneficiary spending. The decline was partially offset by the increasing prevalence of certain chronic diseases. Still, we are unable to attribute a large share of the decline in spending levels to observable beneficiary characteristics or chronic conditions.

CONCLUSIONS

Declines in spending levels for Medicare beneficiaries with chronic conditions suggest that changing patterns of care use may be moderating spending growth.

Public Health Spending and Medicare Resource Use: A Longitudinal Analysis of U.S. Communities

OBJECTIVE

To examine whether local expenditures for public health activities influence area-level medical spending for Medicare beneficiaries.

DATA SOURCES AND SETTING

Six census surveys of the nation's 2,900 local public health agencies were conducted between 1993 and 2013, linked with contemporaneous information on population demographics, socioeconomic characteristics, and area-level Medicare spending estimates from the Dartmouth Atlas of Health Care.

DATA COLLECTION/EXTRACTION

Measures derive from agency survey data and aggregated Medicare claims.

STUDY DESIGN

A longitudinal cohort design follows the geographic areas served by local public health agencies. Multivariate, fixed-effects, and instrumental-variables regression models estimate how area-level Medicare spending changes in response to shifts in local public health spending, controlling for observed and unmeasured confounders.

PRINCIPAL FINDINGS

A 10 percent increase in local public health spending per capita was associated with 0.8 percent reduction in adjusted Medicare expenditures per person after 1 year (p < .01) and a 1.1 percent reduction after 5 years (p < .05). Estimated Medicare spending offsets were larger in communities with higher rates of poverty, lower health insurance coverage, and health professional shortages.

CONCLUSIONS

Expanded financing for public health activities may provide an effective way of constraining Medicare spending, particularly in low-resource communities.

Factors Associated With Increases in US Health Care Spending, 1996-2013

IMPORTANCE

Health care spending in the United States increased substantially from 1995 to 2015 and comprised 17.8% of the economy in 2015. Understanding the relationship between known factors and spending increases over time could inform policy efforts to contain future spending growth.

OBJECTIVE

To quantify changes in spending associated with 5 fundamental factors related to health care spending in the United States: population size, population age structure, disease prevalence or incidence, service utilization, and service price and intensity.

DESIGN AND SETTING

Data on the 5 factors from 1996 through 2013 were extracted for 155 health conditions, 36 age and sex groups, and 6 types of care from the Global Burden of Disease 2015 study and the Institute for Health Metrics and Evaluation's US Disease Expenditure 2013 project. Decomposition analysis was performed to estimate the association between changes in these factors and changes in health care spending and to estimate the variability across health conditions and types of care.

EXPOSURES

Change in population size, population aging, disease prevalence or incidence, service utilization, or service price and intensity.

MAIN OUTCOMES AND MEASURES

Change in health care spending from 1996 through 2013.

RESULTS

After adjustments for price inflation, annual health care spending on inpatient, ambulatory, retail pharmaceutical, nursing facility, emergency department, and dental care increased by $933.5 billion between 1996 and 2013, from $1.2 trillion to $2.1 trillion. Increases in US population size were associated with a 23.1% (uncertainty interval [UI], 23.1%-23.1%), or $269.5 (UI, $269.0-$270.0) billion, spending increase; aging of the population was associated with an 11.6% (UI, 11.4%-11.8%), or $135.7 (UI, $133.3-$137.7) billion, spending increase. Changes in disease prevalence or incidence were associated with spending reductions of 2.4% (UI, 0.9%-3.8%), or $28.2 (UI, $10.5-$44.4) billion, whereas changes in service utilization were not associated with a statistically significant change in spending. Changes in service price and intensity were associated with a 50.0% (UI, 45.0%-55.0%), or $583.5 (UI, $525.2-$641.4) billion, spending increase. The influence of these 5 factors varied by health condition and type of care. For example, the increase in annual diabetes spending between 1996 and 2013 was $64.4 (UI, $57.9-$70.6) billion; $44.4 (UI, $38.7-$49.6) billion of this increase was pharmaceutical spending.

CONCLUSIONS AND RELEVANCE

Increases in US health care spending from 1996 through 2013 were largely related to increases in health care service price and intensity but were also positively associated with population growth and aging and negatively associated with disease prevalence or incidence. Understanding these factors and their variability across health conditions and types of care may inform policy efforts to contain health care spending.

Health Care Spending Slowdown From 2000 To 2010 Was Driven By Lower Growth In Cost Per Case, According To A New Data Source

In 2015 the Bureau of Economic Analysis released an experimental set of measures referred to as the Health Care Satellite Account, which tracks national health care spending by medical condition. These statistics improve the understanding of the health care sector by blending medical claims data and survey data to present measures of national spending and cost of treatment by condition. This article introduces key aspects of the new account and uses it to study the health spending slowdown that occurred in the period 2000-10. Our analysis of the account reveals that the slowdown was driven by a reduction of growth in cost per case but that spending trends varied greatly across conditions and differentially affected the slowdown. More than half of the overall slowdown was accounted for by a slowdown in spending on circulatory conditions. However, there were more dramatic slowdowns in spending on categories such as endocrine system and musculoskeletal conditions than in spending on other categories, such as cancers.

US Spending on Personal Health Care and Public Health, 1996-2013

Importance

US health care spending has continued to increase, and now accounts for more than 17% of the US economy. Despite the size and growth of this spending, little is known about how spending on each condition varies by age and across time.

Objective

To systematically and comprehensively estimate US spending on personal health care and public health, according to condition, age and sex group, and type of care.

Design and Setting

Government budgets, insurance claims, facility surveys, household surveys, and official US records from 1996 through 2013 were collected and combined. In total, 183 sources of data were used to estimate spending for 155 conditions (including cancer, which was disaggregated into 29 conditions). For each record, spending was extracted, along with the age and sex of the patient, and the type of care. Spending was adjusted to reflect the health condition treated, rather than the primary diagnosis.

Exposures

Encounter with US health care system.

Main Outcomes and Measures

National spending estimates stratified by condition, age and sex group, and type of care.

Results

From 1996 through 2013, $30.1 trillion of personal health care spending was disaggregated by 155 conditions, age and sex group, and type of care. Among these 155 conditions, diabetes had the highest health care spending in 2013, with an estimated $101.4 billion (uncertainty interval [UI], $96.7 billion-$106.5 billion) in spending, including 57.6% (UI, 53.8%-62.1%) spent on pharmaceuticals and 23.5% (UI, 21.7%-25.7%) spent on ambulatory care. Ischemic heart disease accounted for the second-highest amount of health care spending in 2013, with estimated spending of $88.1 billion (UI, $82.7 billion-$92.9 billion), and low back and neck pain accounted for the third-highest amount, with estimated health care spending of $87.6 billion (UI, $67.5 billion-$94.1 billion). The conditions with the highest spending levels varied by age, sex, type of care, and year. Personal health care spending increased for 143 of the 155 conditions from 1996 through 2013. Spending on low back and neck pain and on diabetes increased the most over the 18 years, by an estimated $57.2 billion (UI, $47.4 billion-$64.4 billion) and $64.4 billion (UI, $57.8 billion-$70.7 billion), respectively. From 1996 through 2013, spending on emergency care and retail pharmaceuticals increased at the fastest rates (6.4% [UI, 6.4%-6.4%] and 5.6% [UI, 5.6%-5.6%] annual growth rate, respectively), which were higher than annual rates for spending on inpatient care (2.8% [UI, 2.8%-2.8%] and nursing facility care (2.5% [UI, 2.5%-2.5%]).

Conclusions and Relevance

Modeled estimates of US spending on personal health care and public health showed substantial increases from 1996 through 2013; with spending on diabetes, ischemic heart disease, and low back and neck pain accounting for the highest amounts of spending by disease category. The rate of change in annual spending varied considerably among different conditions and types of care. This information may have implications for efforts to control US health care spending.

Adjusting Health Expenditures for Inflation: A Review of Measures for Health Services Research in the United States

OBJECTIVE

To provide guidance on selecting the most appropriate price index for adjusting health expenditures or costs for inflation.

DATA SOURCES

Major price index series produced by federal statistical agencies.

STUDY DESIGN

We compare the key characteristics of each index and develop suggestions on specific indexes to use in many common situations and general guidance in others.

DATA COLLECTION/EXTRACTION METHODS

Price series and methodological documentation were downloaded from federal websites and supplemented with literature scans.

PRINCIPAL FINDINGS

The gross domestic product implicit price deflator or the overall Personal Consumption Expenditures (PCE) index is preferable to the Consumer Price Index (CPI-U) to adjust for general inflation, in most cases. The Personal Health Care (PHC) index or the PCE health-by-function index is generally preferred to adjust total medical expenditures for inflation. The CPI medical care index is preferred for the adjustment of consumer out-of-pocket expenditures for inflation. A new, experimental disease-specific Medical Care Expenditure Index is now available to adjust payments for disease treatment episodes.

CONCLUSIONS

There is no single gold standard for adjusting health expenditures for inflation. Our discussion of best practices can help researchers select the index best suited to their study.

Mental Disorders Top The List Of The Most Costly Conditions In The United States: $201 Billion

Estimates of annual health spending for a comprehensive set of medical conditions are presented for the entire US population and with totals benchmarked to the National Health Expenditure Accounts. In 2013 mental disorders topped the list of most costly conditions, with spending at $201 billion.

Guidelines for Measuring Disease Episodes: An Analysis of the Effects on the Components of Expenditure Growth

OBJECTIVE

To provide guidelines to researchers measuring health expenditures by disease and compare these methodologies' implied inflation estimates.

DATA SOURCE

A convenience sample of commercially insured individuals over the 2003 to 2007 period from Truven Health. Population weights are applied, based on age, sex, and region, to make the sample of over 4 million enrollees representative of the entire commercially insured population.

STUDY DESIGN

Different methods are used to allocate medical-care expenditures to distinct condition categories. We compare the estimates of disease-price inflation by method.

PRINCIPAL FINDINGS

Across a variety of methods, the compound annual growth rate stays within the range 3.1 to 3.9 percentage points. Disease-specific inflation measures are more sensitive to the selected methodology.

CONCLUSION

The selected allocation method impacts aggregate inflation rates, but considering the variety of methods applied, the differences appear small. Future research is necessary to better understand these differences in other population samples and to connect disease expenditures to measures of quality.

Explaining the Growth in US Health Care Spending Using State-Level Variation in Income, Insurance, and Provider Market Dynamics

The slowed growth in national health care spending over the past decade has led analysts to question the extent to which this recent slowdown can be explained by predictable factors such as the Great Recession or must be driven by some unpredictable structural change in the health care sector. To help address this question, we first estimate a regression model for state personal health care spending for 1991-2009, with an emphasis on the explanatory power of income, insurance, and provider market characteristics. We then use the results from this simple predictive model to produce state-level projections of health care spending for 2010-2013 to subsequently compare those average projected state values with actual national spending for 2010-2013, finding that at least 70% of the recent slowdown in health care spending can likely be explained by long-standing patterns. We also use the results from this predictive model to both examine the Great Recession's likely reduction in health care spending and project the Affordable Care Act's insurance expansion's likely increase in health care spending.

Decomposing growth in spending finds annual cost of treatment contributed most to spending growth, 1980-2006

Researchers have disagreed about factors driving up health care spending since the 1980s. One camp, led by Kenneth Thorpe, identifies rising numbers of people being treated for chronic diseases as a major factor. Charles Roehrig and David Rousseau reach the opposite conclusion: that three-quarters of growth in average spending reflects the rising costs of treating given diseases. We reexamined sources of spending growth using data from four nationally representative surveys. We found that rising costs of treatment accounted for 70 percent of growth in real average health care spending from 1980 to 2006. The contribution of shares of the population treated for given diseases increased in 1997-2006, but even then it accounted for only one-third of spending growth. We highlight the fact that Thorpe's inclusion of population growth as part of disease prevalence explains the appreciable difference in results. An important policy implication is that programs to better manage chronic diseases may only modestly reduce average spending growth.

Change in medical spending attributable to diabetes: national data from 1987 to 2011

OBJECTIVE

Diabetes care has changed substantially in the past 2 decades. We examined the change in medical spending and use related to diabetes between 1987 and 2011.

RESEARCH DESIGN AND METHODS

Using the 1987 National Medical Expenditure Survey and the Medical Expenditure Panel Surveys in 2000-2001 and 2010-2011, we compared per person medical expenditures and uses among adults ≥ 18 years of age with or without diabetes at the three time points. Types of medical services included inpatient care, emergency room (ER) visits, outpatient visits, prescription drugs, and others. We also examined the changes in unit cost, defined by the expenditure per encounter for medical services.

RESULTS

The excess medical spending attributed to diabetes was $2,588 (95% CI, $2,265 to $3,104), $4,205 ($3,746 to $4,920), and $5,378 ($5,129 to $5,688) per person, respectively, in 1987, 2000-2001, and 2010-2011. Of the $2,790 increase, prescription medication accounted for 55%; inpatient visits accounted for 24%; outpatient visits accounted for 15%; and ER visits and other medical spending accounted for 6%. The growth in prescription medication spending was due to the increase in both the volume of use and unit cost, whereas the increase in outpatient expenditure was almost entirely driven by more visits. In contrast, the increase in inpatient and ER expenditures was caused by the rise of unit costs.

CONCLUSIONS

In the past 2 decades, managing diabetes has become more expensive, mostly due to the higher spending on drugs. Further studies are needed to assess the cost-effectiveness of increased spending on drugs.

Framing the issue of ageing and health care spending in Canada, the United Kingdom and the United States

Political debates about the affordability of health care programmes in high-income countries often point to population ageing as a threat to sustainability. Debates in the United States, in particular, highlight concerns about intergenerational equity, whereby spending on older people is perceived as a threat to spending on the young. This paper compares how the problem of health spending is defined in Canada, the United Kingdom and the United States by presenting the results of a content analysis of print media during the period 2005-2010. We found that population ageing was cited as an important source of health care cost increases in all three countries but was cited less frequently in Canadian newspapers than in the UK or US papers. Direct claims about intergenerational equity are infrequent among the articles we coded, but newspaper articles in the United States were more likely than those in Canada and the United Kingdom to claim that of high health care spending on older people takes resources away from younger people. In Canada a much larger percentage of articles in our sample either claimed that high health care spending is crowding out other types of government expenditure. Finally, we found that almost no articles in the United States challenged the view that population ageing causes health care spending, whereas in both Canada and the United Kingdom a small, but steady stream of articles challenged the idea that population ageing is to blame for health care spending increases.

Treated disease prevalence and spending per treated case drove most of the growth in health care spending in 1987-2009

Analysis of data from the National Medical Expenditure Survey and the Medical Expenditure Panel Surveys from 1987-2009 reinforces previous observations that increased prevalence of treated disease has become the main driver of increased spending on health care in the United States. Higher treated disease prevalence and higher spending per treated case were associated with 50.8 percent and 39.0 percent, respectively, of the spending increase seen in the population ages eighteen and older, while their joint effect accounts for the remaining 10.2 percent. The proportion of increased spending attributable to increased treated prevalence alone is particularly high in the Medicare population: 77.7 percent, compared to 33.5 percent among the privately insured. Moreover, the current findings reveal a substantial contribution to the increase in total spending (10.4 percent) from a doubling of the share of the population considered to be obese and from increases in treatment intensity, a component of spending per treated case (11.9 percent), in 1987-2009. Constraining the cost of health care will require policy options focused on reducing the incidence of disease, as well as improved understanding of the extent to which more aggressive treatments for chronic conditions do, or do not, result in lower morbidity and mortality.

Effectiveness of Financial Incentives in a Worksite Diabetes Prevention Program

Purpose

To evaluate the effect of financial incentive in a diabetes prevention weight loss program at worksites.

Design

Group-level randomized intervention study.

Setting

Four long-term care facilities, randomly assigned to “incentive-IG” or “non incentive-NIG” groups.

Participants

Ninety-nine employees, all overweight or obese (BMI= mean 34.8±7.4 kg/m²) and at risk for type 2 diabetes.

Intervention

A 16 week weight loss program (diabetes prevention program) with a 3 month follow up. IG could either choose a "standard incentive" to receive cash award when achieving the projected weight loss or to participate in a "standard plus deposit incentive" to get additional money matched with their deposit for projected weight loss. All of the participants received a one-hour consultation for a healthy weight loss at the beginning.

Measures

Weight-loss, diabetes risk score (DRS), and cardiovascular risk outcomes.

Analyses

Linear and logistic regressions for completed cases with adjustments for clustering effect at group level.

Results

IG lost on average more pounds (p=0.027), reduced BMI (p=0.04), and reduced in DRS (p=0.011) compared to NIG at week 16. At the 12-week follow-up period, those in IG plus deposit subgroup had twice the odds (OR=2.2, p=0.042) and those in the standard IG had three times the odds of achieving weight loss goals than NIG; those in the IG plus deposit group reduced DRS by 0.4 (p=0.045).

Conclusion

Monetary incentives appear to be effective in reducing weight and diabetes risk.

Geographic variation in commercial medical-care expenditures: a framework for decomposing price and utilization

This study introduces a new framework for measuring and analyzing medical-care expenditures. The framework focuses on expenditures at the disease level that are decomposed between price and utilization. We find that both price and utilization differences are important contributors to expenditure differences across commercial markets. Further examination shows that for some diseases utilization drives variation while for others price is more important. Finally, when disease-specific measures are aggregated across diseases, much of the important disease-specific variation is masked, leading to much smaller measures of aggregate variation.

The worldwide environment of cardiovascular disease: prevalence, diagnosis, therapy, and policy issues: a report from the American College of Cardiology

The environment in which the field of cardiology finds itself has been rapidly changing. This supplement, an expansion of a report created for the Board of Trustees, is intended to provide a timely snapshot of the socio-economic, political, and scientific aspects of this environment as it applies to practice both in the United States and internationally. This publication should assist healthcare professionals looking for the most recent statistics on cardiovascular disease and the risk factors that contribute to it, drug and device trends affecting the industry, and how the practice of cardiology is changing in the United States.

Lessons from game theory about healthcare system price inflation: evidence from a community-level case study

BACKGROUND

Game theory is useful for identifying conditions under which individual stakeholders in a collective action problem interact in ways that are more cooperative and in the best interest of the collective. The literature applying game theory to healthcare markets predicts that when providers set prices for services autonomously and in a noncooperative fashion, the market will be susceptible to ongoing price inflation.

OBJECTIVES

We compare the traditional fee-for-service pricing framework with an alternative framework involving modified doctor, hospital and insurer pricing and incentive strategies. While the fee-for-service framework generally allows providers to set prices autonomously, the alternative framework constrains providers to interact more cooperatively.

METHODS

We use community-level provider and insurer data to compare provider and insurer costs and patient wellness under the traditional and modified pricing frameworks. The alternative pricing framework assumes (i) providers agree to manage all outpatient claims; (ii) the insurer agrees to manage all inpatient clams; and (iii) insurance premiums are tied to patients' healthy behaviours.

RESULTS AND CONCLUSIONS

Consistent with game theory predictions, the more cooperative alternative pricing framework benefits all parties by producing substantially lower administrative costs along with higher profit margins for the providers and the insurer. With insurance premiums tied to consumers' risk-reducing behaviours, the cost of insurance likewise decreases for both the consumer and the insurer.

Growth of spinal interventional pain management techniques: analysis of utilization trends and Medicare expenditures 2000 to 2008

STUDY DESIGN

Analysis of the growth, utilization trends, and Medicare expenditures of spinal interventional pain management techniques from 2000 through 2008.

OBJECTIVE

To evaluate the use of epidural steroid injections, facet joint interventions, and sacroiliac joint interventions, and to analyze the trends of Medicare utilization and expenditures in multiple settings-namely, hospital outpatient departments, ambulatory surgery centers, and physician offices.

SUMMARY OF BACKGROUND DATA

There has been an explosive growth of many invasive and noninvasive modalities designed to manage chronic spinal pain. Commonly used interventional techniques include epidural steroid injections, facet joint interventions, and sacroiliac joint interventions. However, their effectiveness and the appropriateness of their application continue to be debated.

METHODS

The present article provides an analysis of the growth of spinal interventional techniques, as described earlier, for managing the chronic spinal pain of Medicare beneficiaries from 2000 through 2008. The standard 5% national sample of the Centers for Medicare and Medicaid Services carrier claims that record data from 2000 through 2008 were utilized. Current procedural terminology codes from 2000 through 2008 were used to identify the number of procedures performed each year, as well as trends and expenditures.

RESULTS

Medicare recipients receiving spinal interventional techniques increased 107.8% from 2000 through 2008, with an annual average increase of 9.6%, whereas spinal interventional techniques increased 186.8%, an annual average increase of 14.1% per 100,000 beneficiaries.

CONCLUSION

The study suggests explosive increases in spinal interventional techniques from 2000 to 2008, with some slowing of growth in later years.

The medicalization of chronic disease and costs

U.S. health care spending has increased dramatically in the past several decades, consuming 17.6% percent ($2.6 trillion) of GDP in 2010. Although historical spending drivers do not account for this recent increase, two major changes in population health--the rise in obesity and obesity-related chronic disease--provide a likely explanation. This article reviews the contribution that rising treated obesity-related chronic disease prevalence and its associated treatment (spending per treated case) has made to the growth in health care spending. We discuss trends in the clinical incidence of obesity and chronic disease as well as timely advancements in disease detection, treatment, and management. Evidence shows that rising obesity rates are influencing spending largely by increasing the treated prevalence of obesity-related chronic disease. Therefore, preventing individuals from becoming treated cases in the first place is one key way that our country can cut health care spending moving forward.