Adjusting for comorbidities in cost of illness studies

Net costs of breast cancer in Colombia: a cost-of-illness study based on administrative claims databases

BACKGROUND

Breast Cancer (BC) is associated with substantial costs of healthcare; however, real-world data regarding these costs in Colombia is scarce. The contributory regime provides healthcare services to formal workers and their dependents and covers almost half of the population in Colombia. This study aims to describe the net costs of healthcare in women with BC covered by the contributory regime in Colombia in 2019 from the perspective of the Colombian Health System.

METHODS

The main data source was the Capitation Sufficiency Database, an administrative database that contains patient-level data on consumption of services included in the National Formulary (PBS, in Spanish Plan de Beneficios en Salud). Data on consumption of services not included in the PBS (non-PBS) were calculated using aggregated data from MIPRES database. All direct costs incurred by prevalent cases of BC, from January 1 to December 31, 2019, were included in the analysis. The net costs of the disease were estimated by multiplying the marginal cost and the expected number of cases with BC by region and age group. Marginal costs were defined as the costs of services delivered to patients with BC after subtracting the expected costs of health services due to age, comorbidity burden or region of residence. To calculate these costs, we used Propensity Score Matching in the main analysis. All costs were expressed in 2019 international dollars. Productivity losses, transportation expenses, and caregiving costs were not included.

RESULTS

A total of 46,148 patients with BC were identified. Total net costs were $387 million (95% CI $377 to $396 million), 60% associated with non-PBS services. Marginal costs were $8,366 (95% Confidence Interval $8,170 to $8,573), with substantial variations between regions age groups (from $3,919 for older patients in the Amazonia region to $10,070 for younger patients in the Pacific region). The costs for PBS services were higher for ambulatory services and for patients who died during 2020.

CONCLUSIONS

BC imposes a substantial economic burden for the Colombian Health System with important variations in net costs between regions and age groups. Patients near death and ambulatory services were associated with higher costs of healthcare.

Understanding health behavior change by motivation and reward mechanisms: a review of the literature

The global rise of lifestyle-related chronic diseases has engendered growing interest among various stakeholders including policymakers, scientists, healthcare professionals, and patients, regarding the effective management of health behavior change and the development of interventions that facilitate lifestyle modification. Consequently, a plethora of health behavior change theories has been developed with the intention of elucidating the mechanisms underlying health behavior change and identifying key domains that enhance the likelihood of successful outcomes. Until now, only few studies have taken into account neurobiological correlates underlying health behavior change processes. Recent progress in the neuroscience of motivation and reward systems has provided further insights into the relevance of such domains. The aim of this contribution is to review the latest explanations of health behavior change initiation and maintenance based on novel insights into motivation and reward mechanisms. Based on a systematic literature search in PubMed, PsycInfo, and Google Scholar, four articles were reviewed. As a result, a description of motivation and reward systems (approach/wanting = pleasure; aversion/avoiding = relief; assertion/non-wanting = quiescence) and their role in health behavior change processes is presented. Three central findings are discussed: (1) motivation and reward processes allow to distinguish between goal-oriented and stimulus-driven behavior, (2) approach motivation is the key driver of the individual process of behavior change until a new behavior is maintained and assertion motivation takes over, (3) behavior change techniques can be clustered based on motivation and reward processes according to their functional mechanisms into facilitating (= providing external resources), boosting (= strengthening internal reflective resources) and nudging (= activating internal affective resources). The strengths and limitations of these advances for intervention planning are highlighted and an agenda for testing the models as well as future research is proposed.

Estimating health spending associated with chronic multimorbidity in 2018: An observational study among adults in the United States

BACKGROUND

The rise in health spending in the United States and the prevalence of multimorbidity-having more than one chronic condition-are interlinked but not well understood. Multimorbidity is believed to have an impact on an individual's health spending, but how having one specific additional condition impacts spending is not well established. Moreover, most studies estimating spending for single diseases rarely adjust for multimorbidity. Having more accurate estimates of spending associated with each disease and different combinations could aid policymakers in designing prevention policies to more effectively reduce national health spending. This study explores the relationship between multimorbidity and spending from two distinct perspectives: (1) quantifying spending on different disease combinations; and (2) assessing how spending on a single diseases changes when we consider the contribution of multimorbidity (i.e., additional/reduced spending that could be attributed in the presence of other chronic conditions).

METHODS AND FINDINGS

We used data on private claims from Truven Health MarketScan Research Database, with 16,288,894 unique enrollees ages 18 to 64 from the US, and their annual inpatient and outpatient diagnoses and spending from 2018. We selected conditions that have an average duration of greater than one year among all Global Burden of Disease causes. We used penalized linear regression with stochastic gradient descent approach to assess relationship between spending and multimorbidity, including all possible disease combinations with two or three different conditions (dyads and triads) and for each condition after multimorbidity adjustment. We decomposed the change in multimorbidity-adjusted spending by the type of combination (single, dyads, and triads) and multimorbidity disease category. We defined 63 chronic conditions and observed that 56.2% of the study population had at least two chronic conditions. Approximately 60.1% of disease combinations had super-additive spending (e.g., spending for the combination was significantly greater than the sum of the individual diseases), 15.7% had additive spending, and 23.6% had sub-additive spending (e.g., spending for the combination was significantly less than the sum of the individual diseases). Relatively frequent disease combinations (higher observed prevalence) with high estimated spending were combinations that included endocrine, metabolic, blood, and immune disorders (EMBI disorders), chronic kidney disease, anemias, and blood cancers. When looking at multimorbidity-adjusted spending for single diseases, the following had the highest spending per treated patient and were among those with high observed prevalence: chronic kidney disease ($14,376 [12,291,16,670]), cirrhosis ($6,465 [6,090,6,930]), ischemic heart disease (IHD)-related heart conditions ($6,029 [5,529,6,529]), and inflammatory bowel disease ($4,697 [4,594,4,813]). Relative to unadjusted single-disease spending estimates, 50 conditions had higher spending after adjusting for multimorbidity, 7 had less than 5% difference, and 6 had lower spending after adjustment.

CONCLUSIONS

We consistently found chronic kidney disease and IHD to be associated with high spending per treated case, high observed prevalence, and contributing the most to spending when in combination with other chronic conditions. In the midst of a surging health spending globally, and especially in the US, pinpointing high-prevalence, high-spending conditions and disease combinations, as especially conditions that are associated with larger super-additive spending, could help policymakers, insurers, and providers prioritize and design interventions to improve treatment effectiveness and reduce spending.

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.

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.

The excess economic burden of mental disorders: findings from a cross-sectional prevalence survey in Austria

Information about the scope of mental disorders (MDs), resource use patterns in health and social care sectors and economic cost is crucial for adequate mental healthcare planning. This study provides the first representative estimates about the overall utilisation of resources by people with MDs and the excess healthcare and productivity loss costs associated with MDs in Austria. Data were collected in a cross-sectional survey conducted on a representative sample (n = 1008) between June 2015 and June 2016. Information on mental health diagnoses, 12-month health and social care use, medication use, comorbidities, informal care, early retirement, sick leave and unemployment was collected via face-to-face interviews. Generalised linear model was used to assess the excess cost of MDs. The healthcare cost was 37% higher (p = 0.06) and the total cost was twice as high (p < 0.001) for the respondents with MDs compared to those without MDs. Lost productivity cost was over 2.5-times higher (p < 0.001) for those with MDs. Participants with severe MDs had over 2.5-times higher health and social care cost (p < 0.001) and 9-times higher mental health services cost (p < 0.001), compared to those with non-severe MDs. The presence of two or more physical comorbidities was a statistically significant determinant of the total cost. Findings suggest that the overall excess economic burden on health and social care depends on the severity of MDs and the number of comorbidities. Both non-severe and severe MDs contribute to substantially higher loss productivity costs compared to no MDs. Future resource allocation and service planning should take this into consideration.

Heterogeneous health classes for older adults and their regional disparities in China: based on multidimensional health

OBJECTIVES

China is currently facing an unprecedented complex health demand from a rapidly aging population. Based on multidimensional health, this study aimed to identify heterogeneous latent health classes for older Chinese people, and assess regional disparities and associated sociodemographic factors.

STUDY DESIGN

Chinese Longitudinal Healthy Longevity Survey in 2014 was adopted.

METHODS

For 2886 participants aged 65 years and more without missing health indicators in physical, psychological, and social dimensions, latent class analysis was used to identify heterogeneous health. For 2128 participants with complete information, logistic regressions were used to examine how regional divisions and sociodemographic factors impact each identified class.

RESULTS

Four classes were identified and labeled as 'Lacking Socialization' (17.4%), 'High Comorbidity' (13.7%), 'Functional Impairment' (7.1%), and 'Relative Health' (61.8%). When the Relative Health class was the reference, the likelihoods of the High Comorbidity and Functional Impairment classes were higher for older adults in eastern and central regions than in western regions. Those in eastern regions also tended to be in the Lacking Socialization class than in western regions. The effects of regional divisions on the different classes were significantly impacted by sociodemographic characteristics.

CONCLUSIONS

Four health classes identified by multidimensional health have enhanced our understanding of heterogeneity among older Chinese people. By examining regional disparities in China, our study provided evidence for health policies addressing the issue of aging with respect to regional disparities.

Incremental direct healthcare expenditures of valvular heart disease in the USA

Aim: To quantify the healthcare expenditures for valvular heart disease (VHD) in the USA. Patients & methods: Direct annual incremental healthcare expenditures were estimated using multiple logistic and linear regression models. Results were stratified by age cohorts (18–64 years, ≥65 and ≥75 years) and disease status: symptomatic aortic valve disease (AVD), asymptomatic AVD, symptomatic mitral valve disease (MVD) and asymptomatic MVD. Results: A total of 1463 VHD patients were identified. The overall aggregated incremental direct expenditures were $56.62 billion ($26.48 billion for patients ≥75 years). Individuals ≥75 years with symptomatic AVD had the largest incremental effect on annual, per-patient healthcare expenditure of $30,949. The annualized incremental costs of VHD were greatest for individuals ≥75 years with AVD. Conclusion: Identification of VHD at an earlier stage may reduce the economic burden.

Hospital costs associated with intraoperative hypotension among non-cardiac surgical patients in the US: a simulation model

Objective: Recent studies indicate intraoperative hypotension, common in non-cardiac surgical patients, is associated with myocardial injury, acute kidney injury, and mortality. This study extends on these findings by quantifying the association between intraoperative hypotension and hospital expenditures in the US. Methods: Monte Carlo simulations (10,000 trial per simulation) based on current epidemiological and cost outcomes literature were developed for both acute kidney injury (AKI) and myocardial injury in non-cardiac surgery (MINS). For AKI, three models with different epidemiological assumptions (two models based on observational studies and one model based on a randomized control trial [RCT]) estimate the marginal probability of AKI conditional on intraoperative hypotension status. Similar models are also developed for MINS (except for the RCT case). Marginal probabilities of AKI and MINS sequelae (myocardial infarction, congestive heart failure, stroke, cardiac catheterization, and percutaneous coronary intervention) are multiplied by marginal cost estimates for each outcome to evaluate costs associated with intraoperative hypotension. Results: The unadjusted (adjusted) model found hypotension control lowers the absolute probability of AKI by 2.2% (0.7%). Multiplying these probabilities by the marginal cost of AKI, the unadjusted (adjusted) AKI model estimated a cost reduction of $272 [95% CI = $223-$321] ($86 [95% CI = $47-$127]) per patient. The AKI model based on relative risks from the RCT had a mean cost reduction estimate of $281 (95% CI = -$346-$750). The unadjusted (adjusted) MINS model yielded a cost reduction of $186 [95% CI = $73-$393] ($33 [95% CI = $10-$77]) per patient. Conclusions: The model results suggest improved intraoperative hypotension control in a hospital with an annual volume of 10,000 non-cardiac surgical patients is associated with mean cost reductions ranging from $1.2-$4.6 million per year. Since the magnitude of the RCT mean estimate is similar to the unadjusted observational model, the institutional costs are likely at the upper end of this range.

The extra cost of comorbidity: multiple illnesses and the economic burden of non-communicable diseases

BACKGROUND

The literature offers competing estimates of disease costs, with each study having its own data and methods. In 2007, the Dutch Center for Public Health Forecasting of the National Institute for Public Health and the Environment provided guidelines that can be used to set up cost-of-illness (COI) studies, emphasising that most COI analyses have trouble accounting for comorbidity in their cost estimations. When a patient has more than one chronic condition, the conditions may interact such that the patient's healthcare costs are greater than the sum of the costs for the individual diseases. The main objective of this work was to estimate the costs of 10 non-communicable diseases when their co-occurrence is acknowledged and properly assessed.

METHODS

The French Echantillon Généraliste de Bénéficiaires (EGB) database was used to assign all healthcare expenses for a representative sample of the population covered by the National Health Insurance. COIs were estimated in a bottom-up approach, through regressions on individuals' healthcare expenditure. Two-way interactions between the 10 chronic disease variables were included in the expenditure model to account for possible effect modification in the presence of comorbidity(ies).

RESULTS

The costs of the 10 selected chronic diseases were substantially higher for individuals with comorbidity, demonstrating the pattern of super-additive costs in cases of diseases interaction. For instance, the cost associated with diabetes for people without comorbidity was estimated at 1776 €, whereas this was 2634 € for people with heart disease as a comorbidity. Overall, we detected 41 cases of super-additivity over 45 possible comorbidities. When simulating a preventive action on diabetes, our results showed that significant monetary savings could be achieved not only for diabetes itself, but also for the chronic diseases frequently associated with diabetes.

CONCLUSIONS

When comorbidity exists and where super-additivity is involved, a given preventive policy leads to greater monetary savings than the costs associated with the single diagnosis, meaning that the returns from the action are generally underestimated.

Adjusting health spending for the presence of comorbidities: an application to United States national inpatient data

BACKGROUND

One of the major challenges in estimating health care spending spent on each cause of illness is allocating spending for a health care event to a single cause of illness in the presence of comorbidities. Comorbidities, the secondary diagnoses, are common across many causes of illness and often correlate with worse health outcomes and more expensive health care. In this study, we propose a method for measuring the average spending for each cause of illness with and without comorbidities.

METHODS

Our strategy for measuring cause of illness-specific spending and adjusting for the presence of comorbidities uses a regression-based framework to estimate excess spending due to comorbidities. We consider multiple causes simultaneously, allowing causes of illness to appear as either a primary diagnosis or a comorbidity. Our adjustment method distributes excess spending away from primary diagnoses (outflows), exaggerated due to the presence of comorbidities, and allocates that spending towards causes of illness that appear as comorbidities (inflows). We apply this framework for spending adjustment to the National Inpatient Survey data in the United States for years 1996-2012 to generate comorbidity-adjusted health care spending estimates for 154 causes of illness by age and sex.

RESULTS

The primary diagnoses with the greatest number of comorbidities in the NIS dataset were acute renal failure, septicemia, and endocarditis. Hypertension, diabetes, and ischemic heart disease were the most common comorbidities across all age groups. After adjusting for comorbidities, chronic kidney diseases, atrial fibrillation and flutter, and chronic obstructive pulmonary disease increased by 74.1%, 40.9%, and 21.0%, respectively, while pancreatitis, lower respiratory infections, and septicemia decreased by 21.3%, 17.2%, and 16.0%. For many diseases, comorbidity adjustments had varying effects on spending for different age groups.

CONCLUSIONS

Our methodology takes a unified approach to account for excess spending caused by the presence of comorbidities. Adjusting for comorbidities provides a substantially altered, more accurate estimate of the spending attributed to specific cause of illness. Making these adjustments supports improved resource tracking, accountability, and planning for future resource allocation.

Hyperlipidemia and Medical Expenditures by Cardiovascular Disease Status in US Adults

BACKGROUND

Hyperlipidemia is a major risk factor for cardiovascular disease (CVD), affecting 73.5 million American adults. Information about health care expenditures associated with hyperlipidemia by CVD status is needed to evaluate the economic benefit of primary and secondary prevention programs for CVD.

METHODS

The study sample includes 48,050 men and nonpregnant women ≥18 from 2010 to 2012 Medical Expenditure Panel Survey. A 2-part econometric model was used to estimate annual hyperlipidemia-associated medical expenditures by CVD status. The estimation results from the 2-part model were used to calculate per-capita and national medical expenditures associated with hyperlipidemia. We adjusted the medical expenditures into 2012 dollars.

RESULTS

Among those with CVD, per person hyperlipidemia-associated expenditures were $1105 [95% confidence interval (CI), $877-$1661] per year, leading to an annual national expenditure of $15.47 billion (95% CI, $5.23-$27.75 billion). Among people without CVD, per person hyperlipidemia-associated expenditures were $856 (95% CI, $596-$1211) per year, resulting in an annual national expenditure of $23.11 billion (95% CI, $16.09-$32.71 billion). Hyperlipidemia-associated expenditures were attributable mostly to the costs of prescription medication (59%-90%). Among people without CVD, medication expenditures associated with hyperlipidemia were $13.72 billion (95% CI, $10.55-$15.74 billion), higher in men than in women.

CONCLUSIONS

Hyperlipidemia significantly increased medical expenditures and the increase was higher in people with CVD than without. The information on estimated expenditures could be used to evaluate and develop effective programs for CVD prevention.

Multimorbidity in chronic disease: impact on health care resources and costs

Effective and resource-efficient long-term management of multimorbidity is one of the greatest health-related challenges facing patients, health professionals, and society more broadly. The purpose of this review was to provide a synthesis of literature examining multimorbidity and resource utilization, including implications for cost-effectiveness estimates and resource allocation decision making. In summary, previous literature has reported substantially greater, near exponential, increases in health care costs and resource utilization when additional chronic comorbid conditions are present. Increased health care costs have been linked to elevated rates of primary care and specialist physician occasions of service, medication use, emergency department presentations, and hospital admissions (both frequency of admissions and bed days occupied). There is currently a paucity of cost-effectiveness information for chronic disease interventions originating from patient samples with multimorbidity. The scarcity of robust economic evaluations in the field represents a considerable challenge for resource allocation decision making intended to reduce the burden of multimorbidity in resource-constrained health care systems. Nonetheless, the few cost-effectiveness studies that are available provide valuable insight into the potential positive and cost-effective impact that interventions may have among patients with multiple comorbidities. These studies also highlight some of the pragmatic and methodological challenges underlying the conduct of economic evaluations among people who may have advanced age, frailty, and disadvantageous socioeconomic circumstances, and where long-term follow-up may be required to directly observe sustained and measurable health and quality of life benefits. Research in the field has indicated that the impact of multimorbidity on health care costs and resources will likely differ across health systems, regions, disease combinations, and person-specific factors (including social disadvantage and age), which represent important considerations for health service planning. Important priorities for research include economic evaluations of interventions, services, or health system approaches that can remediate the burden of multimorbidity in safe and cost-effective ways.

Annual direct health care expenditures and employee absenteeism costs in high-risk, low-income mothers with major depression

BACKGROUND

To determine the health care and labor productivity costs associated with major depressive disorder in high-risk, low-income mothers.

METHODS

This study was conducted using the 1996-2011 Medical Expenditure Panel Survey (MEPS). The MEPS is a nationally-representative database that includes information on health care utilization and expenditures for the civilian, non-institutionalized population in the United States. High-risk mothers were between the ages of 18-35 years, and either unmarried, receiving Medicaid, or with incomes less than 300% of the Federal Poverty Level. Mothers were categorized as being depressed if they had an ICD-9 diagnosis code of 296 or 311 (N=2310) or not depressed (N=18,221). Insurer expenditures, out-of-pocket (OOP) expenses, and lost wage earnings were calculated.

RESULTS

After controlling for comorbidities, demographics, region, and year, high-risk depressed mothers were more likely to incur insurer (0.84 vs. 0.79) and OOP expenses (0.84 vs. 0.81) and to have higher insurer ($4448 vs. $3072) and OOP expenses ($794 vs. $523). Depression significantly increased the likelihood of missing work days (OR=1.40; p<0.01). Depression increased overall direct health care expenditures by $1.89 billion (range=$1.28-$2.60 billion) and indirect costs by $523 million annually, with a range of $353-$719 million.

CONCLUSIONS

In this high-risk population, the direct and indirect aggregate costs of depression-related to health care expenditures and lost work productivity were substantial. These findings establish a quantifiable cost for policy makers and highlight the need to target this population for prevention and treatment efforts.

Excess costs of comorbidities in chronic obstructive pulmonary disease: a systematic review

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. Comorbidities are often reported in patients with COPD and may influence the cost of care. Yet, the extent by which comorbidities affect costs remains to be determined.

OBJECTIVES

To review, quantify and evaluate excess costs of comorbidities in COPD.

METHODS

Using a systematic review approach, Pubmed and Embase were searched for studies analyzing excess costs of comorbidities in COPD. Resulting studies were evaluated according to study characteristics, comorbidity measurement and cost indicators. Mark-up factors were calculated for respective excess costs. Furthermore, a checklist of quality criteria was applied.

RESULTS

Twelve studies were included. Nine evaluated comorbidity specific costs; three examined index-based results. Pneumonia, cardiovascular disease and diabetes were associated with the highest excess costs. The mark-up factors for respective excess costs ranged between 1.5 and 2.5 in the majority of cases. On average the factors constituted a doubling of respective costs in the comorbid case. The main cost driver, among all studies, was inpatient cost. Indirect costs were not accounted for by the majority of studies. Study heterogeneity was high.

CONCLUSIONS

The reviewed studies clearly show that comorbidities are associated with significant excess costs in COPD. The inclusion of comorbid costs and effects in future health economic evaluations of preventive or therapeutic COPD interventions seems highly advisable.