Changes in patterns of multimorbidity and associated with medical costs among Chinese middle-aged and older adults from 2013 to 2023: an analysis of repeated cross-sectional surveys in Xiangyang, China.

Background: Multimorbidity has become a major public health problem among Chinese middle-aged and older adults, and the most costly to the health care system. However, most previous population-based studies of multimorbidity have focused on a limited number of chronic diseases, and diagnosis was based on participants' self-report, which may oversimplify the problem. At the same time, there were few reports on the relationship between multimorbidity patterns and health care costs. This study analyzed the multimorbidity patterns and changes among middle-aged and older people in China over the past decade, and their association with medical costs, based on representative hospital electronic medical record data. Methods: Two cross-sectional surveys based on representative hospital data were used to obtain adults aged 45 years and older in Xiangyang in 2013 (n = 20,218) and 2023 (n = 63,517). Latent Class Analysis was used to analyze changes in the patterns of multimorbidity, gray correlation analysis and ordered logistics model were used to assess the association of multimorbidity patterns with medical expenses. The diagnosis and classification of chronic diseases were based on the International Classification of Diseases, Tenth Revision codes (ICD-10). Results: The detection rate of chronic disease multimorbidity has increased (70.74 vs. 76.63%, p < 0.001), and multimorbidity patterns have increased from 6 to 9 (2013: Malignant tumors pattern, non-specific multimorbidity pattern, ischemic heart disease + hypertension pattern, cerebral infarction + hypertension pattern, kidney disease + hypertension pattern, lens disease + hypertension pattern; new in 2023: Nutritional metabolism disorders + hypertension pattern, chronic lower respiratory diseases + malignant tumors pattern, and gastrointestinal diseases pattern) in China. The medical cost of all multimorbidity patients have been reduced between 2013 and 2023 (RMB: 8216.74 vs. 7247.96, IQR: 5802.28-15,737 vs. 5014.63-15434.06). The top three specific multimorbidity patterns in both surveys were malignancy tumor pattern, ischemic heart disease + hypertension pattern, and cerebral infarction + hypertension pattern. Hypertension and type 2 diabetes are important components of multimorbidity patterns. Compared with patients with a single disease, only lens disorders + hypertension pattern were at risk of higher medical costs in 2013 (aOR:1.23, 95% CI: 1.03, 1.47), whereas all multimorbidity patterns were significantly associated with increased medical costs in 2023, except for lens disorders + hypertension (aOR:0.35, 95% CI: 0.32, 0.39). Moreover, the odds of higher medical costs were not consistent across multimorbidity patterns. Among them, ischemic heart disease + hypertension pattern [adjusted odds ratio (aOR):4.66, 95%CI: 4.31, 5.05] and cerebral infarction + hypertension pattern (aOR: 3.63, 95% CI: 3.35, 3.92) were the two patterns with the highest risk. Meanwhile, men (aOR:1.12, 95CI:1.09, 1.16), no spouse (aOR:1.09, 95CI: 1.03, 1.16) had a positive effect on medical costs, while patients with total self-pay (aOR: 0.45, 95CI: 0.29, 0.70), no surgery (aOR: 0.05, 95CI: 0.05, 0.05), rural residence (aOR: 0.92, 95CI: 0.89, 0.95), hospitalization days 1-5 (aOR: 0.04, 95CI: 0.04, 0.04), and hospitalization days 6-9 (aOR: 0.15, 95CI: 0.15, 0.16) had a negative impact on medical costs. Conclusion: Multimorbidity patterns among middle-aged and older adults in China have diversified over the past decade and are associated with rising health care costs in China. Smart, decisive and comprehensive policy and care interventions are needed to effectively manage NCDS and their risk factors and to reduce the economic burden of multimorbidity on patients and the country.

Impact of the Home-Based Medical Integrated Program on Health Outcomes and Medical Resource Utilization in Home Healthcare Patients in Taiwan.

Purpose: The home-based medical integrated program (HMIP) is a novel model for home healthcare (HHC) in Taiwan, initiated in 2016 to enhance care quality. However, the outcomes of this program on health outcomes and medical resource utilization in HHC patients remain unclear. Thus, we conducted this study to clarify it. Patients and Methods: The authors utilized the Taiwan National Health Insurance Research Database to identify HHC patients who received HMIP and those who did not between January 2015 and December 2017. A retrospective cohort study design was used. Convenience sampling was employed to select patients who met the inclusion criteria: being part of the HHC program and having complete data for analysis. Results: A total of 4982 HHC patients in the HMIP group and 10,447 patients in the non-HMIP group were identified for this study. The mean age in the HMIP group and non-HMIP group was 77.6 years and 76.1 years, respectively. Compared with the non-HMIP group, the HMIP group had lower total medical costs for HHC, fewer outpatient department visits and lower medical costs, lower medical costs for emergency department visits, fewer hospitalizations, and a lower mortality rate (34.6% vs 41.2%, p<0.001). Conclusion: The HMIP is a promising model for improving care quality and reducing medical resource utilization in HHC patients. While this suggests that the non-HMIP model should be replaced, it's important to note that both non-HMIP and HMIP models currently coexist. The HMIP may serve as an important reference for other nations seeking to improve care quality and reduce medical resource utilization in their own HHC systems.

Lipid Control and Medical Costs Among Patients With and Without Established Atherosclerotic Cardiovascular Disease Followed in a Brazilian Private Healthcare System.

Background: There is limited real-world data of lipid control and healthcare costs among patients with and without Atherosclerotic Cardiovascular Disease (ASCVD) in Latin America. Methods: A retrospective cohort study including patients with LDL-cholesterol (LDL-C) assessment from 2015 to 2017 was performed in a health insurance database. Patient characteristics, comorbidities and laboratory data were collected, and International Classification of Diseases (ICD) codes were used to identify a subcohort of patients with ASCVD (secondary prevention) and assess the proportion of these patients with LDL-C controlled. Lipid control among patients without ASCVD (primary prevention) and healthcare costs in one year in the overall population were also assessed. Results: From the 17,434 patients selected, 5,208 (29.8%) had ASCVD. The mean age of these patients in secondary prevention was 68.9 (±12.3) years and 47.8% were male patients. LDL-C < 70 mg/dL was identified in 19.1% of the ASCVD population and only 4.1% had an LDL-C < 50 mg/dL. LDL control was worse in women compared to men (13.1% vs. 25.7%; P < 0.01). The average cost in one year was 3,591 American dollars (USD) per patient in primary prevention compared to 8,210 dollars per year for patients in secondary prevention (P < 0.01). While outpatient costs accounted for 59.8% of the total cost in the primary prevention group, the main cost of the secondary prevention population was related to hospital costs (54.1%). Conclusion: Despite the favorable evidence for intensive cholesterol reduction, the evaluation of large real-world database with more than 17,000 individuals showed that the targets of guideline recommendations have not yet been adequately incorporated into clinical practice. Average annual cost per patient in secondary prevention is more than twice compared to primary prevention. Hospital expenses account for most of the cost in the secondary prevention group, while outpatient costs predominate in primary prevention.

Direct healthcare expenditure on Alzheimer's disease from healthcare providers' perspective in Malaysia: a micro-costing approach.

Alzheimer's disease (AD) is an important geriatric disease that creates challenges in health policy planning. There is no previous attempt to quantify the actual direct healthcare cost of AD among older adults in Malaysia. This retrospective observational study with bottom-up micro-costing approach aimed to evaluate the direct healthcare expenditure on AD along with its potential predictors from healthcare providers' perspective, conducted across six tertiary hospitals in Malaysia. AD patients aged 65 and above who received AD treatment between 1 January 2016 and 31 December 2021 were included. Direct healthcare cost (DHC) of AD was estimated by extracting one-year follow-up information from patient medical records. As a result, 333 AD patients were included in the study. The mean DHC of AD was estimated RM2641.30 (USD 572.45) per patient per year (PPPY) from the healthcare payer's perspective. Laboratory investigations accounted for 37.2% of total DHC, followed by clinic care (31.5%) and prescription medicine (24.9%). As disease severity increases, annual DHC increases from RM2459.04 (mild), RM 2642.27 (moderate), to RM3087.61 (severe) PPPY. Patients aged 81 and above recorded significantly higher annual DHC (p = 0.003). Such real-world estimates are important in assisting the process of formulating healthcare policies in geriatric care.

Comparative analysis of financial toxicity between SARS-CoV-2 infection and common comorbidities.

Financial toxicity is common in individuals with COVID-19 and Long COVID. However, the extent of financial toxicity experienced, in comparison to other common comorbidities, is uncertain. Contributing factors exacerbating financial challenges in Long COVID are also unclear. These knowledge gaps are addressed via a cross-sectional analysis utilizing data from the 2022 National Health Interview Survey (NHIS), a representative sample drawn from the United States. COVID-19 cases were identified through self-reported positive testing or physician diagnoses. Long COVID was defined as experiencing COVID-19-related symptoms for more than three months. Comorbidity was assessed based on self-reported diagnoses of ten doctor-diagnosed conditions (Yes/No). Financial toxicity was defined as having difficulty paying medical bills, cost-related medication nonadherence, delaying healthcare due to cost, and/or not obtained healthcare due to cost. A total of 27,492 NHIS 2022 respondents were included in our analysis, representing 253 million U.S. adults. In multivariable logistic regression models, adults with Long COVID (excluding respondents with COVID-19 but not Long COVID), showed increased financial toxicity compared to those with other comorbidities, such as epilepsy (OR [95% CI]: 1.69 [1.22, 2.33]), dementia (1.51 [1.01, 2.25]), cancer (1.43 [1.19, 1.71]) or respiratory/cardiovascular conditions (1.18 [1.00, 1.40]/1.23 [1.02, 1.47]). Long COVID-related financial toxicity was associated with female sex, age <65 years, lack of medical insurance, current paid employment, residence region, food insecurity, fatigue, mild to severe depression symptoms experienced during the survey completion, visits to hospital emergency rooms, presence of arthritis, cardiovascular or respiratory conditions, and social activity limitations. In conclusion, American adults with Long COVID, but not those who had prior COVID-19 infection without Long COVID, exhibited a higher prevalence of financial toxicity compared to individuals with common comorbidities. Vulnerable populations were at greater risk for financial toxicity. These findings emphasize the importance of evaluating strategies to reduce economic burden and increase awareness of the effect of Long COVID-related financial toxicity on patient's healthcare and health status.

The Risk Of Perpetuating Health Disparities Through Cost-Effectiveness Analyses.

Cost-effectiveness analyses are commonly used to inform health care and public health policy decisions. However, standard approaches may systematically disadvantage marginalized groups by incorporating assumptions of persisting health inequities. We examined how competing risks, baseline health care costs, and indirect costs can differentially affect cost-effectiveness analyses for racial and ethnic minority populations. We illustrate that these structural factors can reduce estimated quality-adjusted life-years and cost savings for disadvantaged groups, making interventions focused on disadvantaged populations appear less cost-effective. For example, analyses of a sugar-sweetened beverage tax may estimate higher costs per quality-adjusted life-year gained for Black versus White populations because of differences in competing risks and insurance status that manifest in higher health care cost savings from averted disease among White people. To ensure that cost-effectiveness assessments do not perpetuate inequities, alternative approaches are needed that account for the impact of structural factors on different groups and that consider scenarios in which health inequities are reduced. Sensitivity analyses focusing on health equity could help advance interventions that disproportionately benefit disadvantaged communities.

A real-world data analysis of electronic health records to investigate the associations of predominant negative symptoms with healthcare resource utilisation, costs and treatment patterns among patients with schizophrenia.

OBJECTIVES: Negative symptoms in schizophrenia are associated with significant illness burden. We sought to investigate clinical outcomes for patients with schizophrenia who present with predominant negative symptoms (PNS) vs without PNS. DESIGN: Retrospective analysis of electronic health record (EHR) data. SETTING: 25 US providers of mental healthcare. PARTICIPANTS: 4444 adults with schizophrenia receiving care between 1999 and 2020. EXPOSURE: PNS defined as ≥3 negative symptoms and ≤3 positive symptoms recorded in EHR data at the time of the first recorded schizophrenia diagnosis (index date). Symptom data were ascertained using natural language processing applied to semistructured free text records documenting the mental state examination. A matched sample (1:1) of patients without PNS was used to compare outcomes. Follow-up data were obtained up to 12 months following the index date. PRIMARY OUTCOME MEASURE: Mean number of psychiatric hospital admissions. SECONDARY OUTCOME MEASURES: Mean number of outpatient visits, estimated treatment costs, Clinical Global Impression - Severity score and antipsychotic treatments (12 months before and after index date). RESULTS: 360 (8%) patients had PNS and 4084 (92%) did not have PNS. Patients with PNS were younger (36.4 vs 39.7 years, p<0.001) with a greater prevalence of psychiatric comorbidities (schizoaffective disorders: 25.0 vs 18.4%, p=0.003; major depressive disorder: 17.8 vs 9.8%, p<0.001). During follow-up, patients with PNS had fewer days with an antipsychotic prescription (mean=111.8 vs 140.9 days, p<0.001). Compared with matched patients without PNS, patients with PNS were more likely to have a psychiatric inpatient hospitalisation (76.1% vs 59.7%, p<0.001) and had greater estimated inpatient costs ($16 893 vs $13 732, p=0.04). CONCLUSIONS: Patients with PNS were younger and presented with greater illness severity and more psychiatric comorbidities compared with patients without PNS. Our findings highlight an unmet need for novel therapeutic approaches to address negative symptoms to improve clinical outcomes.

Assessing economic investment required to scale up bariatric surgery capacity in England: a health economic modelling analysis.

OBJECTIVES: To quantify the economic investment required to increase bariatric surgery (BaS) capacity in National Health Service (NHS) England considering the growing obesity prevalence and low provision of BaS in England despite its high clinical effectiveness. DESIGN: Data were included for the patients with obesity who were eligible for BaS. We used a decision-tree approach including four distinct steps of the patient pathway to capture all associated resource use. We estimated total costs according to the current capacity (current scenario) and three BaS scaling up strategies over a time horizon of 20 years (projected scenario): maximising NHS capacity (strategy 1), maximising NHS and private sector capacity (strategy 2) and adding infrastructure to NHS capacity to cover the entire prevalent and incident obesity populations (strategy 3). SETTING: BaS centres based in NHS and private sector hospitals in England. MAIN OUTCOME MEASURES: Number of BaS procedures (including revision surgery), cost (GBP) and resource utilisation over 20 years. RESULTS: At current capacity, the number of BaS procedures and the total cost over 20 years were estimated to be 140 220 and £1.4 billion, respectively. For strategy 1, these values were projected to increase to 157 760 and £1.7 billion, respectively. For strategy 2, the values were projected to increase to 232 760 and £2.5 billion, respectively. Strategy 3 showed the highest increase to 564 784 and £6.4 billion, respectively, with an additional 4081 personnel and 49 facilities required over 20 years. CONCLUSIONS: The expansion of BaS capacity in England beyond a small proportion of the eligible population will likely be challenging given the significant upfront economic investment and additional requirement of personnel and infrastructure.

Health-economic evaluation of orthogeriatric co-management for patients with pelvic or vertebral fragility fractures.

BACKGROUND: Orthogeriatric co-management (OGCM) addresses the special needs of geriatric fracture patients. Most of the research on OGCM focused on hip fractures while results concerning other severe fractures are rare. We conducted a health-economic evaluation of OGCM for pelvic and vertebral fractures. METHODS: In this retrospective cohort study, we used German health and long-term care insurance claims data and included cases of geriatric patients aged 80 years or older treated in an OGCM (OGCM group) or a non-OGCM hospital (non-OGCM group) due to pelvic or vertebral fractures in 2014-2018. We analyzed life years gained, fracture-free life years gained, healthcare costs, and cost-effectiveness within 1 year. We applied entropy balancing, weighted gamma and two-part models. We calculated incremental cost-effectiveness ratios and cost-effectiveness acceptability curves. RESULTS: We included 21,036 cases with pelvic (71.2% in the OGCM, 28.8% in the non-OGCM group) and 33,827 with vertebral fractures (72.8% OGCM, 27.2% non-OGCM group). 4.5-5.9% of the pelvic and 31.8-33.8% of the vertebral fracture cases were treated surgically. Total healthcare costs were significantly higher after treatment in OGCM compared to non-OGCM hospitals for both fracture cohorts. For both fracture cohorts, a 95% probability of cost-effectiveness was not exceeded for a willingness-to-pay of up to €150,000 per life year or €150,000 per fracture-free life year gained. CONCLUSION: We did not obtain distinct benefits of treatment in an OGCM hospital. Assigning cases to OGCM or non-OGCM group on hospital level might have underestimated the effect of OGCM as not all patients in the OGCM group have received OGCM.

Multilevel medical insurance mitigate health cost inequality due to air pollution: Evidence from China.

BACKGROUND: Air pollution affects residents' health to varying extents according to differences in socioeconomic status. However, there has been a lack of research on whether air pollution contributes to unfair health costs. METHODS: In this research, data from the China Labour Force Dynamics Survey are matched with data on PM2.5 average concentration and precipitation, and the influence of air pollution on the health expenditures of residents is analysed with econometric methods involving a two-part model, instrument variables and moderating effects. RESULTS: The findings reveal that air pollution significantly impacts Chinese residents' health costs and leads to low-income people face health inequality. Specifcally, the empirical evidence shows that air pollution has no significant influence on the probability of residents' health costs (ß = 0.021, p = 0.770) but that it increases the amount of residents' total outpatient costs (ß = 0.379, p < 0.006), reimbursed outpatient cost (ß = 0.453, p < 0.044) and out-of-pocket outpatient cost (ß = 0.362, p < 0.048). The heterogeneity analysis of income indicates that low-income people face inequality due to health cost inflation caused by air pollution, their total and out-of-pocket outpatient cost significantly increase with PM2.5 (ß = 0.417, p = 0.013; ß = 0.491, p = 0.020). Further analysis reveals that social basic medical insurance does not have a remarkable positive moderating effect on the influence of air pollution on individual health inflation (ß = 0.021, p = 0.292), but supplementary medical insurance for employees could reduce the effect of air pollution on low-income residents' reimbursed and out-of-pocket outpatient cost (ß=-1.331, p = 0.096; ß=-2.211, p = 0.014). CONCLUSION: The study concludes that air pollution increases the amount of Chinese residents' outpatient cost and has no significant effect on the incidence of outpatient cost. However, air pollution has more significant impact on the low-income residents than the high-income residents, which indicates that air pollution leads to the inequity of medical cost. Additionally, the supplementary medical insurance reduces the inequity of medical cost caused by air pollution for the low-income employees.

Economic Burden of Healthcare Services on Cancer Survivors in Bangladesh.

BACKGROUND: Cancer is a critical public health issue that imposes a considerable economic burden, especially in low-resource countries. In Bangladesh, there has been a noticeable lack of research focusing on the economic burden associated with cancer. AIMS: This study aimed to examine the economic burden of cancer care and the contributing factors. METHODS: This cross-sectional study included 623 cancer patients. Data were collected between January and May 2022. The magnitude of the economic burden (no burden to extreme burden) was the outcome variable. A logistic regression model was performed to determine the associated factors of the economic burden of cancer. RESULTS: Overall, 34% of cancer survivors experienced extreme economic burden due to treatment costs. Patients with prostate (relative risk ratio, RRR = 23.24; 95% confidence interval, CI: 1.97, 273.70), bone (RRR = 5.85; 95% CI: 1.10, 31.04), and liver cancer (RRR = 4.94; 95% CI: 1.29, 18.9) reported significantly higher extreme economic burden compared to patients with other cancers. The economic burden was significantly higher for patients diagnosed with Stage III (RRR = 38.69; 95% CI: 6.17, 242.72) and Stage IV (RRR = 24.74; 95% CI: 3.22, 190.11) compared to Stage 0. Patients from low-income households suffered from nine times more extreme burden (RRR = 8.85; 95% CI: 4.05, 19.36) compared with those from high-income households. CONCLUSION: Our study found a disproportionately high economic burden among patients with cancer, across disease sites, stages, and income quintiles. The burden was significantly higher among patients with prostate, bone, and liver cancer, and those diagnosed with advanced stage. The findings underscore the importance of early cancer detection before metastasis which may lead to more efficient treatment, avoid disease progression, lower disease management costs, and better health outcomes. Patients from low-income households experience an extreme economic burden due to cancer, highlighting the need for affordable healthcare services, financial support, and healthcare subsidies.

Cost-sharing and associated factors in the Peruvian private health care system.

BACKGROUND: The costs associated with healthcare are of critical importance to both decision-makers and users, given the limited resources allocated to the health sector. However, the available scientific evidence on healthcare costs in low- and middle-income countries, such as Peru, is scarce. In the Peruvian context, the health system is fragmented, and the private health insurance and its financing models have received less research attention. We aimed to analyse user cost-sharing and associated factors within the private healthcare system. METHODS: Our study was cross-sectional, using open data from the Electronic Transaction Model of Standardized Billing Data-TEDEF-SUSALUD, between 2021-2022. Our unit of analysis is the user's medical bills. We considered the total amount of cost-sharing, proportion of total payments as cost-sharing, and cost-sharing as a proportion of minimum salaries. We use a multiple regression model to perform the analyses. RESULTS: Our study included 5,286,556 health services provided to users of the private health insurance in Peru. We found a significant difference was observed in the cost-sharing for hospitalization-related services, with an average of 419.64 soles per day (95% CI: 413.44 to 425.85). Also, we identified that for hospitalization-related services per day is, on average, 0.41 (95% CI: 0.41 to 0.41) minimum salaries more expensive than outpatient care, although cost-sharing per day of hospitalization represent on average only 14% of the total amount submitted. CONCLUSIONS: Our study provides a detailed overview of cost-sharing in the private healthcare system in Peru and the factors associated with them. Policymakers can use the study's finding that higher cost-sharing for inpatient hospitalization compared to outpatient care in private insurance can create inequities in access to healthcare to design policies aimed at reducing these costs and promoting a more equitable and accessible healthcare system in Peru.

Subgroups of High-Cost Patients and Their Preventable Inpatient Cost in Rural China.

BACKGROUND: High-cost patients account for most healthcare costs and are highly heterogeneous. This study aims to classify high-cost patients into clinically homogeneous subgroups, describe healthcare utilization patterns of subgroups, and identify subgroups with relatively high preventable inpatient cost (PIC) in rural China. METHODS: A population-based retrospective study was performed using claims data in Xi county, Henan province. 32 108 high-cost patients, representing the top 10% of individuals with the highest total spending, were identified. A density-based clustering algorithm combined with expert opinions were used to group high-cost patients. Healthcare utilization (including admissions, length of stay, and outpatient visits) and spending characteristics (including total spending, and the proportion of PIC, inpatient and out-of-pocket spending on total spending) were described among subgroups. PIC was calculated based on potentially preventable hospitalizations (PPHs) which were identified according to the Agency for Healthcare Research and Quality Prevention Quality Indicators algorithm. RESULTS: High-cost patients were more likely to be older (Mean=51.87, SD=22.28), male (49.03%) and from poverty-stricken families (37.67%) than non-high-cost patients, with 2.49 (SD=2.47) admissions and 3.25 (SD=4.52) outpatient visits annually. Fourteen subgroups of high-cost patients were identified: chronic disease, non-trauma diseases which need surgery, female disease, cancer, eye disease, respiratory infection/inflammation, skin disease, fracture, liver disease, vertigo syndrome and cerebral infarction, mental disease, arthritis, renal failure, and other neurological disorders. The annual admissions ranged from 1.83 (SD=1.23, fracture) to 12.21 (SD=9.26, renal failure), and the average length of stay ranged from 6.61 (SD=10.00, eye disease) to 32.11 (SD=28.78, mental disease) days among subgroups. The chronic disease subgroup showed the largest proportion of PIC on total spending (10.57%). CONCLUSION: High-cost patients were classified into 14 clinically distinct subgroups which had different healthcare utilization and spending characteristics. Different targeted strategies may be needed for subgroups to reduce preventable hospitalizations. Priority should be given to high-cost patients with chronic diseases.

Estimation of Attributable Risk and Direct Medical and Non-Medical Costs of Major Mental Disorders Associated With Air Pollution Exposures Among Children and Adolescents in the Republic of Korea, 2011-2019.

BACKGROUND: Recent studies have reported the burden of attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], and depressive disorder. Also, there is mounting evidence on the effects of environmental factors, such as ambient air pollution, on these disorders among children and adolescents. However, few studies have evaluated the burden of mental disorders attributable to air pollution exposure in children and adolescents. METHODS: We estimated the risk ratios of major mental disorders (ADHD, ASD, and depressive disorder) associated with air pollutants among children and adolescents using time-series data (2011-2019) obtained from a nationwide air pollution monitoring network and healthcare utilization claims data in the Republic of Korea. Based on the estimated risk ratios, we determined the population attributable fraction (PAF) and calculated the medical costs of major mental disorders attributable to air pollution. RESULTS: A total of 33,598 patients were diagnosed with major mental disorders during 9 years. The PAFs for all the major mental disorders were estimated at 6.9% (particulate matter < 10 µm [PM10]), 3.7% (PM2.5), and 2.2% (sulfur dioxide [SO2]). The PAF of PM10 was highest for depressive disorder (9.2%), followed by ASD (8.4%) and ADHD (5.2%). The direct medical costs of all major mental disorders attributable to PM10 and SO2 decreased during the study period. CONCLUSION: This study assessed the burden of major mental disorders attributable to air pollution exposure in children and adolescents. We found that PM10, PM2.5, and SO2 attributed 7%, 4%, and 2% respectively, to the risk of major mental disorders among children and adolescents.

Costs of Health Registries: An Exploration for Health Services Research.

Health registries are an established methodology in health services research. Regarded as cheap bidder for observation studies in earlier times, many registries now benefit from an appropriate funding. However, reference figures for costs of registries in health services research are missing. Based on literature data as well as figures from a German funding initiative, the relationship between costs per newly recruited case and the annual sample size was analyzed. One can assume that a standard multicenter registry in health services research with 1,000 new patients each year will be appropriately financed with 1.1 to 2.2 million Euro in a period of five years. So smaller the sample size, so higher the costs for a newly recruited patient. The cost model of health registries should be further elaborated taking into account specifics of individual registries and differences in the level of case money.