Future Health Care Costs Research Articles

Temperature, morbidity, and behavior in milder climates

Since climate change is expected to lead to an increase in extreme weather events, several studies have considered the effects of temperature on human health, especially in countries with hotter climates. We extended this literature by modeling the relationship between temperature and morbidity in a country with a temperate maritime climate, and by considering the role of behavioral responses. Using weekly data on accident and emergency (A&E) attendances at 429 hospitals across England from 2010 to 2015, we found that while cold weather was associated with an initial reduction in A&E attendances, it appears to be a result of postponements to subsequent weeks. However, for hotter temperatures, we found substantial increases in overall attendances, which were not offset by subsequent reductions. Our results show clear effects of temperature on morbidity, even in relatively milder climates, with implications for future healthcare demand and the overall cost of climate change. • Effects of temperature on morbidity and behavior in milder climates are unclear. • We model the relationship between temperature and A&E attendances in England. • Colder temperatures lead to postponement of A&E attendances to subsequent weeks. • Hotter temperatures result in significant increases in overall A&E attendances. • Effects have implications for future healthcare demand and cost of climate change.

Healthcare costs attributable to e-cigarette use and subsequent uptake of cigarette smoking by Australians who have never smoked.

Objective New legislation to curb the rapid increase in e-cigarette use among youth is underway. We estimated the future healthcare costs for chronic diseases from e-cigarette use among never smokers who transition to tobacco smoking. Methods Using population-attributable fractions, we estimated the health expenditure attributable to e-cigarettes based on the prevalence of e-cigarette use, uptake of tobacco smoking, and risk of smoking on developing chronic disease. Data for men and women were derived from published reports on e-cigarette use prevalence, risk of smoking-related disease and addiction, and health expenditure for 25 diseases. Sensitivity analyses were undertaken to address data input variation. Results Future healthcare costs attributed to new e-cigarette-initiated smokers were conservatively estimated to be (in Australian dollars) $179.6 million annually. Collectively, the estimated costs were highest for respiratory diseases ($102.2 million; 57% of total costs), malignant cancers ($49.6 million; 28%), and cardiovascular disease ($27.7 million; 15%). The uptake rate of e-cigarettes was more important in driving healthcare costs than the proportion moving from e-cigarettes to cigarette smoking. Conclusion High avoidable health system costs are predicted for the treatment of chronic conditions created by e-cigarette-initiated smoking. These costs exclude the immediate and direct healthcare harms of e-cigarette-related poisoning, lung injury, and respiratory problems, and costs associated with the unknown health harms of e-cigarette use alone. The proposed regulations to curb recreational e-cigarette use in Australia are set to prevent expensive health care arising sometime in the future from new cigarette smokers.

Measuring the geographic disparity of comorbidity in commercially insured individuals compared to the distribution of physicians in South Africa

BackgroundMeasuring and addressing the disparity between access to healthcare resources and underlying health needs of populations is a prominent focus in health policy development. More recently, the fair distribution of healthcare resources among population subgroups have become an important indication of health inequities. Single disease outcomes are commonly used for healthcare resource allocations; however, leveraging population-level comorbidity measures for health disparity research has been limited. This study compares the geographical distribution of comorbidity and associated healthcare utilization among commercially insured individuals in South Africa (SA) relative to the distribution of physicians.MethodsA retrospective, cross-sectional analysis was performed comparing the geographical distribution of comorbidity and physicians for 2.6 million commercially insured individuals over 2016–2017, stratified by geographical districts and population groups in SA. We applied the Johns Hopkins ACG® System across the claims data of a large health plan administrator to measure a comorbidity risk score for each individual. By aggregating individual scores, we determined the average healthcare resource need of individuals per district, known as the comorbidity index (CMI), to describe the disease burden per district. Linear regression models were constructed to test the relationship between CMI, age, gender, population group, and population density against physician density.ResultsOur results showed a tendency for physicians to practice in geographic areas with more insurance enrollees and not necessarily where disease burden may be highest. This was confirmed by a negative relationship between physician density and CMI for the overall population and for three of the four major population groups. Among the population groups, the Black African population had, on average, access to fewer physicians per capita than other population groups, before and after adjusting for confounding factors.ConclusionCMI is a novel measure for healthcare disparities research that considers both acute and chronic conditions contributing to current and future healthcare costs. Our study linked and compared the population-level geographical distribution of CMI to the distribution of physicians using routinely collected data. Our results could provide vital information towards the more equitable distribution of healthcare providers across population groups in SA, and to meet the healthcare needs of disadvantaged communities.

Social Determinants of Health Influence Future Health Care Costs in the Medicaid Cohort of the District of Columbia Study.

Social determinants of health are an important predictor of future health care costs but little is known about their impact on Medicaid spending. This study analyzes the role of social determinants of health (SDH) in predicting future health care costs for adult Medicaid beneficiaries with similar past morbidity burdens and past costs. We enrolled into a prospective cohort study 8,892 adult Medicaid beneficiaries who presented for treatment at an emergency department or clinic affiliated with two hospitals in Washington, DC, between September 2017 and December 31, 2018. We used SDH information measured at enrollment to categorize our participants into four social risk classes of increasing severity. We used Medicaid claims for a 2-year period; 12 months pre- and post-study enrollment to measure past and future morbidity burden according to the Adjusted Clinical Groups system. We also used the Medicaid claims data to characterize total annual Medicaid costs one year prior to and one year after study enrollment. The 8,892 participants were primarily female (66%) and Black (91%). For persons with similar past morbidity burdens and past costs (p < 0.01), the future morbidity burden was significantly higher in the upper two social risk classes (1.15 and 2.04, respectively) compared with the lowest one. Mean future health care spending was significantly higher in the upper social risk classes compared with the lowest one ($2,713, $11,010, and $17,710, respectively) and remained significantly higher for the two highest social risk classes ($1,426 and $3,581, respectively), given past morbidity burden and past costs (p < 0.01). When we controlled for future morbidity burden (measured concurrently with future costs), social risk class was no longer a significant predictor of future health care costs. SDH are statistically significant predictors of future morbidity burden and future costs controlling for past morbidity burden and past costs. Further research is needed to determine whether current payment systems adequately account for differences in the care needs of highly medically and socially complex patients.

Cost analysis and cost-effectiveness of open versus laparoscopic versus robot-assisted versus transanal total mesorectal excision in patients with rectal cancer: a protocol for a systematic review

IntroductionNowadays, most rectal tumours are treated open or minimally invasive, using laparoscopic, robot-assisted or transanal total mesorectal excision. However, insight into the total costs of these techniques is limited. Since...

The future health and economic burden of obesity-attributable type 2 diabetes and liver disease among the working-age population in Saudi Arabia.

BackgroundObesity and type 2 diabetes (T2DM) are increasing in Saudi Arabia (SA). Among other conditions, these risk factors increase the likelihood of non-alcoholic fatty liver disease (NAFLD), which in turn increases risks for advanced liver diseases, such as non-alcoholic steatohepatitis (NASH), cirrhosis and cancer. The goal of this study was to quantify the health and economic burden of obesity-attributable T2DM and liver disease in SA.MethodsWe developed a microsimulation of the SA population to quantify the future incidence and direct health care costs of obesity-attributable T2DM and liver disease, including liver cancer. Model inputs included population demographics, body mass index, incidence, mortality and direct health care costs of T2DM and liver disease and relative risks of each condition as a function of BMI category. Model outputs included age- and sex-disaggregated incidence of obesity-attributable T2DM and liver disease and their direct health care costs for SA’s working-age population (20–59 years) between 2020 and 2040.ResultsBetween 2020 and 2040, the available data predicts 1,976,593 [± 1834] new cases of T2DM, 285,346 [±874] new cases of chronic liver diseases, and 2,101 [± 150] new cases of liver cancer attributable to obesity, amongst working-age people. By 2040, the direct health care costs of these obesity-attributable diseases are predicted to be 127,956,508,540 [± 51,882,446] USD.ConclusionsThe increase in obesity-associated T2DM and liver disease emphasises the urgent need for obesity interventions and strategies to meaningfully reduce the future health and economic burden of T2DM, chronic liver diseases and liver cancer in SA.

Costs and health impact of delayed implementation of a national hepatitis B treatment program in China.

BackgroundHepatitis B virus (HBV) infection is a leading public health problem in China. COVID-19 pandemic has interrupted the delivery of health care interventions worldwide, including HBV infection control.MethodsIn this study, we used a Markov model to quantify the costs and population health impact of HBV treatment in China for the following scenarios: 1) current practice with only 17% of treatment eligible HBV infected adults receiving antiviral treatment; 2) reaching the World Health Organization (WHO) treatment target of 80% by 2030 with a steady increase in treatment rate beginning in 2022; and 3) the effect of a 1-5-year delay in meeting the 2030 WHO treatment target. A one-way as well as a probabilistic sensitivity analysis were conducted.ResultsWithout increasing antiviral treatment for treatment eligible HBV infected adults, the life-time health care costs for the estimated 89.2 million adults living with HBV in China is US$1305 billion and 10.8 million (12%) will die from HBV-related liver disease. Increasing treatment to achieve the WHO 80% target by 2030 would save US$472 billion and prevent 3.3 million HBV-related deaths. We estimated that a 1-year delay beyond 2030 in reaching the WHO 80% treatment target would likely lead to US$55 billion increase in future health care costs, and an additional 334 000 future deaths from HBV-related liver disease or cancer.ConclusionsReaching the WHO 2030 with minimal delays would have an immense health and economic benefit. Implementing a national treatment program for HBV in China should be a key priority for policymakers.

Lifestyle taxes in the presence of profit shifting

The consumption of unhealthy products generates significant externalities in terms of increased future health care costs to society. Lifestyle taxes are attracting increasing attention as a measure by which to discourage over-consumption and correct such externalities. This paper focuses on the trade-off that governments face in setting a lifestyle tax when the producer of the taxed good is a multinational which may engage in profit-shifting activities. In the absence of profit shifting, if governments do care about corporate tax revenue, the optimal lifestyle tax is always lower than the marginal health care cost. We show that, by shrinking the corporate tax base, profit shifting has the interesting side effect of helping to close the gap between the lifestyle tax and the marginal health care cost.

The future costs of cancer attributable to excess body weight in Brazil, 2030-2040

BackgroundExcess body weight (EBW), herein defined as body mass index (BMI) ≥25 kg/m2, is a well-known modifiable risk factor for cancer and a pivotal vector for growing healthcare costs. We estimated the future (2030) federal direct healthcare costs of cancer in the Brazilian Unified Health System (SUS) attributable to EBW. We also projected direct healthcare costs of cancer that could be potentially saved in 2040, considering counterfactual (alternative) scenarios of population-wide reductions in the BMI to be achievedin 2030.MethodsWe developed a macrosimulation model by sex using self-reported BMI data in adults ≥ 20 years who relied exclusively on the public health system from the Brazilian National Health Survey (PNS) 2019; relative risks for 12 types of cancer from the World Cancer Research Fund/American Institute Cancer Research (WCRF/AICR) meta-analysis; and nationwide registries of federal direct healthcare costs of inpatient and outpatient procedures in adults ≥30 years with cancer from 2008-2019. We calculated the attributable costs of cancer via comparative risk assessment, assuming a 10-year lag between exposure and outcome. We used the potential impact fraction (PIF) equation and the Monte Carlo simulation method to estimate the attributable costs and 95% uncertainty intervals, considering the theoretical-minimum-risk exposure and other counterfactual (alternative) scenarios of the EBW prevalence. We assessed the cancer costs attributable to EBW, multiplying PIF by the direct healthcare costs of cancer.ResultsIn 2030, 2.4% or US$ 62.8 million in direct healthcare costs of cancer may be attributable to EBW. We projected potential savings of approximately US$ 10.3 to 26.6 million in 2040 by reducing the prevalence of EBW in 2030.ConclusionsWe estimated high future costs of cancer attributable to EBW in Brazil. Our findings may support interventions and policies focused on the primary prevention of EBW and cancer.

Patient expenditure prediction using deep learning framework

Measurement of patient expenditure in healthcare is a critical task that has a variety of applications, including provider profiling, accountable care management, and capitated medical payment adjustment. Currently available methods rely on manually built features and linear regression-based models, both of which need a significant amount of medical domain expertise. and have low prediction accuracy. This study develops a multi-view deep learning system for forecasting future healthcare costs at the individual level based on prior claims data. Our multi-view technique efficiently models heterogeneous data such patient demographics, medical codes, medication usages, and facility usage. To execute spending forecasting tasks, we employed a real-world paediatric dataset with approximately 450,000 patients. According to the empirical data, our proposed technique beats all baselines for predicting medical cost. In the sphere of healthcare, these insights help to improve preventative and responsible care.

Health State Risk Categorization: A Machine Learning Clustering Approach Using Health and Retirement Study Data

For countries such as the United States, which lacks a universal health care system, future health care costs can create significant uncertainty that a retirement investment strategy must be built to manage. One of the most important factors determining health care costs is the individual’s health status. Hence, categorizing individuals into meaningful health risk types is an essential task. The conventional approach is to use individuals’ self-rated health state categorization. In this work, the authors provide an objective and data-driven machine learning (ML)–based approach to categorize heath state risk by using the most widely used US household surveys on older Americans, the Health and Retirement Study (HRS). The authors propose an approach of employing the K-modes clustering method to algorithmically cluster on an exhaustive list of categorical health-related variables in the HRS. The resulting clusters are shown to provide an objective, interpretable, and practical health state risk categorization. The authors then compare and contrast the ML-based and self-rated health state categorizations and discuss the implications of the differences. They also illustrate the difficulty in predicting out-of-pocket costs based on self-rated health status and how ML-based categorizations can generate more-accurate health care cost estimates for personalized retirement planning. The results in this article open different avenues of research, including behavioral science analysis for health and retirement study.

Relationship of COPD Exacerbation Severity and Frequency on Risks for Future Events and Economic Burden in the Medicare Fee-For-Service Population.

PurposeTo quantify the effects of moderate and/or severe chronic obstructive pulmonary disease (COPD) exacerbations on future exacerbations and healthcare costs in Medicare Fee-For-Service beneficiaries.Patients and MethodsA retrospective cohort study of patients ≥40 years of age, with continuous enrollment from 2015 to 2018, with an index COPD diagnosis defined as first hospitalization, emergency department visit, or first of two outpatient visits (≥30 days apart) in 2015 with a claim for chronic bronchitis, emphysema, or chronic airway obstruction. Patients were stratified by baseline exacerbation categories in year one (YR1) and subsequently evaluated in YR2 and YR3: (A) none; (B) 1 moderate; (C) ≥2 moderate; (D) 1 severe; and (E) ≥2, one being severe. Moderate exacerbations were defined as COPD-related outpatient/ED visits with a corticosteroid/antibiotic claim within ±7 days of the visit and severe exacerbations as hospitalizations with a primary COPD diagnosis. Total all-cause costs for Categories B-E were compared to reference Category A using generalized linear models and inflation adjusted to 2019 dollars.ResultsA total of 1,492,108 patients met study criteria with a mean (±SD) age of 70.9±10.9. In YR1, nearly 40% of patients experienced ≥1 moderate and/or severe exacerbations. Patients having multiple exacerbations, regardless of severity were 2–4 times more likely to experience an exacerbation during YR2 and YR3. Adjusted costs ranged between $24,000 and $26,600 for all categories for YR2 and YR3. Adjusted YR2 costs for Category D and E were $1421 and $1548 higher than those without an exacerbation (Category A YR2 $25,084, YR3 $24,282; p<0.0001). The respective YR3 adjusted costs were $2062 and $2117 higher than those without an exacerbation (Category A; p<0.0001), representing an increase of 6–8% and 8–9% for YR2 and YR3.ConclusionMedicare patients with recent moderate or severe exacerbations, or at least two exacerbations per year are at significant risk for future exacerbations and incur higher all-cause costs.

Value appropriation in hepatitis C

BackgroundIn 2015, the Swedish government in an unprecedented move decided to allocate 150 million € to provide funding for new drugs for hepatitis C. This was triggered by the introduction of the first second generation of direct-acting antivirals (DAAs) promising higher cure rates and reduced side effects. The drugs were cost-effective but had a prohibitive budget impact. Subsequently, additional products have entered the market leading to reduction in prices and expansions of the eligible patient base.MethodsWe estimated the social surplus generated by the new DAAs in Stockholm, Sweden, for the years 2014–2019. The actual use and cost of the drugs was based on registry data. Effects on future health care costs, indirect costs and QALY gains were estimated using a Markov model based primarily on Swedish data and using previous generations of interferon-based therapies as the counterfactual.ResultsA considerable social surplus was generated, 15% of which was appropriated by the producers whose share fell rapidly over time as prices fell. Most of the consumer surplus was generated by QALY gains, although 10% was from reduced indirect costs. QALY gains increased less rapidly than the number of treated patients as the eligibility criteria was loosened.ConclusionsThe transfer of funds from the government to the regions helped generate substantial surplus for both consumers and producers with indirect costs playing an important role. The funding model may serve as a model for the financing of innovative treatments in the future.

The cost-effectiveness of pharmacist-physician collaborative care models vs usual care on time in target systolic blood pressure range in patients with hypertension: a payer perspective.

BACKGROUND: Hypertension is highly prevalent in the United States, affecting nearly half of all adults (43%). Studies have shown that pharmacist-physician collaborative care models (PPCCMs) for hypertension management significantly improve blood pressure (BP) control rates and provide consistent control of BP. Time in target range (TTR) for systolic BP is a novel measure of BP control consistency that is independently associated with decreased cardiovascular risk. There is no evidence that observed improvement in TTR for systolic BP with a PPCCM is cost-effective. OBJECTIVE: To compare the cost-effectiveness of a PPCCM with usual care for the management of hypertension from the payer perspective. METHODS: We used a decision analytic model with a 3-year time horizon based on published literature and publicly available data. The population consisted of adult patients who had a previous diagnosis of high BP (defined as office-based BP ≥ 140/90 mmHg) or were receiving antihypertensive medications. Effectiveness data were drawn from 2 published studies evaluating the effect of PPCCMs (vs usual care) on TTR for systolic BP and the impact of TTR for systolic BP on 4 cardiovascular outcomes (nonfatal myocardial infarction [MI], stroke, heart failure [HF], and cardiovascular disease [CVD] death). The model incorporated direct medical costs, including both programmatic costs (ie, direct costs for provider time) and downstream health care utilization associated with acute cardiovascular events. One-way sensitivity and threshold analyses examined model robustness. RESULTS: In base-case analyses, PPCCM hypertension management was associated with lower downstream medical expenditures (difference: -$162.86) and lower total program costs (difference: -$108.00) when compared with usual care. PPCCM was associated with lower downstream medical expenditures across all parameter ranges tested in the deterministic sensitivity analysis. For every 10,000 hypertension patients managed with PPCCM vs usual care over a 3-year time horizon, approximately 27 CVD deaths, 29 strokes, 21 nonfatal MIs, and 12 incident HF diagnoses are expected to be averted. CONCLUSIONS: This is the first study to evaluate the cost-effectiveness of PPCCM compared to usual care on TTR for systolic BP in adults with hypertension. PPCCM was less costly to administer and resulted in downstream health care savings and fewer acute cardiovascular events relative to usual care. Although further research is needed to evaluate the long-term costs and outcomes of PPCCM, payer coverage of PPCCM services may prevent future health care costs and improve patient cardiovascular outcomes. DISCLOSURES: No funding was received for the completion of this research. The authors have nothing to disclose. Study results were presented as an abstract at the AMCP 2021 Virtual, April 12-16, 2021.

Estimating the late-life effects of social and emotional skills in childhood using midlife mediators

Social and emotional skills are known to affect health and non-health outcomes, but there is limited evidence on whether these skills in childhood affect late life outcomes because of a shortage of long-running datasets containing this information. We develop a three-stage procedure and use it to estimate the effect of childhood social and emotional skills on health and labour market outcomes in late-life. This procedure makes use of mediators in midlife which are shown to be predicted by childhood skills in one dataset and to predict late-life outcomes in another dataset. We use this method to combine estimates from the National Child Development Survey and the British Household Panel Survey. We find that childhood skills predict marital status, education, home ownership, income and health at age 46 years and these midlife variables predict levels of quality-adjusted life years and labour income accumulated by age 63 years. The combined estimates suggest a standard deviation increase in average Bristol Social Adjustment Guide total score at ages 7 and 11 is associated with 4.2% (standard error = 0.6%) additional quality-adjusted life years and more than 9.9% (£14,539, standard error = £2072) additional accumulated pre-tax earnings by age 63 years. Therefore, childhood interventions to increase social and emotional skills would be expected to reduce future healthcare costs and increase wealth. Our three-stage methodology can be used to predict the life-course effects of investments in childhood skills by combining results from datasets across population cohorts.

The Relevance of Including Future Healthcare Costs in Cost-Effectiveness Threshold Calculations for the UK NHS.

Background and ObjectiveThe supply-side threshold for the UK National Health Service has been empirically estimated as the marginal returns to healthcare spending on health outcomes. These estimates implicitly exclude future healthcare costs, which is inconsistent with the objective of making the most efficient use of healthcare resources. This paper illustrates how empirical estimates of the threshold within healthcare can be adjusted to account for future healthcare costs.MethodsUsing cause-deleted life tables and previous work on future costs in England and Wales, we illustrate how such estimates can be adjusted.ResultsWhile the effect of including future healthcare costs can have substantial effects on incremental cost-effectiveness ratios of specific life-extending interventions, we find that including future costs has relatively little impact (an increase of £743 per quality-adjusted life-year) on the threshold estimate.ConclusionsFor some life-extending interventions the impact of including future costs on whether an intervention is deemed cost effective may be considerable.

DIR reform, supply chain security, and more

DIR reform, supply chain security, and more

411 EFFICACY OF CDSS IN IMPROVING ANTI-RESORPTIVE BONE PROTECTIVE THERAPY AMONGST ORTHOGERIATRIC INPATIENTS: A COMPARISON STUDY

Abstract Background Hip fractures have a mortality rate of 20% in the year following the fracture. Therefore, patients presenting with hip fractures should be assessed and prescribed anti-resorptive bone protective therapy (ABPT) to reduce the risk of further fractures. In our institution, this decision is undertaken by a specialist only. Purpose: The objective of this study is to compare the proportion of patients commenced on ABPT by surgical interns following the introduction of a Clinical Decision Support System (CDSS) in January 2020 to support appropriate ABPT prescribing amongst non-specialists. Methods The study compares the orthogeriatric patient cohort before and after CDSS introduction within the same time period (Jan 1st to June 30th) in 2019 and 2020. Data were extracted from the Irish Hip Fracture Database and statistically analyzed using SPSS. The Mann–Whitney two-tailed test was employed to calculate statistical significance. Results In 2019, 31% (55/178) of patients admitted during the study period (n = 178) did not receive orthogeriatric specialist input and only 27% (15/55) of these had ABPT prescribed during their admission. In 2020, 17% (32/185) of patients admitted during the study period (n = 185) did not receive specialist input; however, 44% (14/32) of these were commenced on ABPT. Overall, more patients were prescribed ABPT in 2020 (78%;146/185), as compared to 55% (98/178) in 2019 (z-score 6.57069; p-value &amp;lt;0.01). The number of patients awaiting specialist outpatient appointments before being prescribed ABPT also dropped from 40% (71/178) in 2019 to 13% (24/185) in 2020 (p-value &amp;lt;0.01). Conclusion This study highlighted the significance of a CDSS to improve inpatient ABPT prescribing by non-specialists and to reduce outpatient specialist appointments. This could have a major impact on the long-term reduction of mortality rates amongst orthogeriatric patients and the reduction of future healthcare costs.

False Economies: Myths about Public Health Spending

Coronavirus has raised questions about the use of public health resources in Britain. It has been argued that the government’s response was weakened by public health budget cuts and that public health expenditure saves money in the long run by reducing future healthcare costs. In reality, there has been no cut in Public Health England’s budget for infectious disease prevention. Between 2014 and 2019, its budget for protection from infectious diseases rose from £52 million to £86.9 million. Cutting the public health budget has been described as a false economy, but this is a misrepresentation. Most public health interventions are cost-effective if a quality-adjusted year of life is valued at £20,000, but only 20% of interventions save money or produce a cash return. More than a third of public health interventions would not be approved if they were NHS treatments because they are not cost-effective. It is not possible to tell from the available data whether England’s public health budget is too small, too large or about right, but many of the arguments made for increased spending on public health are based on a misunderstanding of economics and human behaviour.

Emergency department visits and associated healthcare costs attributable to increasing temperature in the context of climate change in Perth, Western Australia, 2012–2019

Increasing temperature and its impact on population health is an emerging significant public health issue in the context of climate change in Australia. While previous studies have primarily focused on risk assessment, very few studies have evaluated heat-attributable emergency department (ED) visits and associated healthcare costs, or projected future health and economic burdens. This study used a distributed lag non-linear model to estimate heat attributable ED visits and associated healthcare costs from 13 hospitals in Perth, Western Australia, and to project the future healthcare costs in 2030s and 2050s under three climate change scenarios—Representative Concentration Pathways (RCPs)2.6, RCP4.5 and RCP8.5. There were 3697 ED visits attributable to heat (temperatures above 20.5 °C) over the study period 2012–2019, accounting for 4.6% of the total ED visits. This resulted in AU$ 2.9 million in heat-attributable healthcare costs. The number of ED visits projected to occur in the 2030s and 2050s ranges from 5707 to 9421 under different climate change scenarios, which would equate to AU$ 4.6–7.6 million in heat associated healthcare costs. The heat attributable fraction for ED visits and associated healthcare costs would increase from 4.6% and 4.1% in 2010s to 5.0%–6.3% and 4.4%–5.6% in 2030s and 2050s, respectively. Future heat attributable ED visits and associated costs will increase in Perth due to climate change. Excess heat will generate a substantial population health challenge and economic burdens on the healthcare system if there is insufficient heat adaptation. It is vital to reduce greenhouse gas emissions, develop heat-related health interventions and optimize healthcare resources to mitigate the negative impact on the healthcare system and population health in the face of climate change.