Associations of the COVID-19 pandemic with older individuals’ healthcare utilization and self-reported health status: a longitudinal analysis from Singapore

Background The COVID–19 pandemic has challenged the capacity of healthcare systems around the world and can potentially compromise healthcare utilization and health outcomes among non-COVID–19 patients. Objectives To examine the associations of the COVID-19 pandemic with healthcare utilization, out-of-pocket medical costs, and perceived health among middle-aged and older individuals in Singapore. Method Utilizing data collected from a monthly panel survey, a difference-in-differences approach was used to characterize monthly changes of healthcare use and spending and estimate the probability of being diagnosed with a chronic condition and self-reported health status before and during the COVID-19 outbreak in 2020. Subjects Data were analyzed from 7569 nationally representative individuals from 2019 January and 2020 December. Measures Healthcare utilization and healthcare spending by medical service categories as well as self-reported health status. Results Between January and April 2020 (the first peak period of COVID-19 in Singapore), doctor visits decreased by 30%, and out-of-pocket medical spending decreased by 23%, mostly driven by reductions in inpatient and outpatient care. As a result, the probability of any diagnosis of chronic conditions decreased by 19% in April 2020. The decreased healthcare utilization and spending recovered after lifting the national lockdown in June, 2020 and remained similar to the pre-pandemic level through the rest of 2020. Conclusions Middle-aged and older Singaporeans’ healthcare utilization and the diagnosis of chronic conditions substantially decreased during the first peak period of the COVID-19 outbreak. Further studies to track the longer-term health effect of the pandemic among non-COVID-19 patients are warranted.

A magánkiadások hatása a hazai egészségügyi diagnosztikai szolgáltatók pénzügyi helyzetére : The Impact of Private Healthcare Spending on the Hungarian Medical Diagnostic Companies

A magánfinanszírozás modellje a kilencvenes évek kezdete óta része a hazai egészségügynek. A 2000-es évektől azonban komolyan előtérbe kerültek ezek a csatornák, különösen a képalkotó diagnosztika és laborszolgáltatások területén, ami az itt szolgáltató vállalkozások közelebbi vizsgálatát teszi szükségessé. Elsőként az Ohlson-féle O csődkockázati mutatók által adott jelzéseket vizsgáljuk meg egy öt vállalkozásból álló mintán 2006 és 2017 között. Ezt követően az Ohlson-féle O csődkockázati mutató változásának magyarázhatóságát vizsgáljuk az egészségügyi finanszírozási környezet, a tőkepiaci helyzet és a technológiai környezetet lefedő modellek keretében, panelregressziós eljárásokkal. Megállapítható, hogy az egészségügyi finanszírozás GDP-arányos változása, illetve a kórházi ágyszám változásai gyakorolták a legkomolyabb hatást a mintában szereplő vállalatok pénzügyi helyzetének alakulására. The Hungarian healthcare services are partially financed on private basis since the 1990s. This channel gained increasing popularity in the 2000s especially on the fields of medical imaging and labour diagnostics – what motivates a deeper corporate analysis on annual report data between 2006 and 2017. Financial conditions were studied with the assumption of the Ohlson O bankruptcy ratio, and their changes were monitored trough three different panel regression models: one focused on general and public healthcare spending and hospital capacities, while the second contained the financial market-related variables as the third referred on the technological environment. The changes of healthcare funding to GDP ratios and hospital bed numbers surpassed all other variables on the financial conditions of the sample companies.

Risk and Health Policy Preferences: Evidence from the UK COVID-19 Crisis

The onset of the COVID-19 pandemic constituted a large shock to the risk of acquiring a disease that represents a meaningful threat to health. We investigate whether individuals subject to larger increases in objective health risk -- operationalised by occupation-based measures of proximity to other people -- became more supportive of increased government healthcare spending during the crisis. Using panel data which tracks UK individuals before and after the outbreak of the pandemic, we implement a fixed-effect design which was pre-registered before the key treatment variable was available to us. While individuals in high-risk occupations were more worried about their personal risk of infection, and had higher COVID death rates, there is no evidence that increased health risks during COVID-19 shifted attitudes on government spending on healthcare, nor broader attitudes relating to redistribution. Our findings are consistent with recent research demonstrating the limited effects of the pandemic on political attitudes.

Characteristics and resource utilization of high-cost users in the intensive care unit: a population-based cohort study

Background Healthcare expenditure within the intensive care unit (ICU) is costly. A cost reduction strategy may be to target patients accounting for a disproportionate amount of healthcare spending, or high-cost users. This study aims to describe high-cost users in the ICU, including health outcomes and cost patterns. Methods We conducted a population-based retrospective cohort study of patients with ICU admissions in Ontario from 2011 to 2018. Patients with total healthcare costs in the year following ICU admission (including the admission itself) in the upper 10th percentile were defined as high-cost users. We compared characteristics and outcomes including length of stay, mortality, disposition, and costs between groups. Results Among 370,061 patients included, 37,006 were high-cost users. High-cost users were 64.2 years old, 58.3% male, and had more comorbidities (41.2% had ≥3) when likened to non-high cost users (66.1 years old, 57.2% male, 27.9% had ≥3 comorbidities). ICU length of stay was four times greater for high-cost users compared to non-high cost users (22.4 days, 95% confidence interval [CI] 22.0–22.7 days vs. 5.56 days, 95% CI 5.54–5.57 days). High-cost users had lower in-hospital mortality (10.0% vs.14.2%), but increased dispositioning outside of home (77.4% vs. 42.2%) compared to non-high-cost users. Total healthcare costs were five-fold higher for high-cost users ($238,231, 95% CI $237,020–$239,442) compared to non-high-cost users ($45,155, 95% CI $45,046–$45,264). High-cost users accounted for 37.0% of total healthcare costs. Conclusion High-cost users have increased length of stay, lower in-hospital mortality, and higher total healthcare costs when compared to non-high-cost users. Further studies into cost patterns and predictors of high-cost users are necessary to identify methods of decreasing healthcare expenditure.

The role of European health system characteristics in affecting Covid 19 lethality during the early days of the pandemic

This article examines the main factors affecting COVID-19 lethality across 16 European Countries with a focus on the role of health system characteristics during the first phase of the diffusion of the virus. Specifically, we investigate the leading causes of lethality at 10, 20, 30, 40 days in the first hit of the pandemic. Using a random forest regression (ML), with lethality as outcome variable, we show that the percentage of people older than 65 years (with two or more chronic diseases) is the main predictor variable of lethality by COVID-19, followed by the number of hospital intensive care unit beds, investments in healthcare spending compared to GDP, number of nurses and doctors. Moreover, the variable of general practitioners has little but significant predicting quality. These findings contribute to provide evidence for the prediction of lethality caused by COVID-19 in Europe and open the discussion on health policy and management of health care and ICU beds during a severe epidemic.

An Integrated Medical-Psychological Approach in the Routine Care of Patients with Type 2 Diabetes: A Pilot Study to Explore the Clinical and Economic Sustainability of the Healthcare Intervention

The economic burden of Type 2 Diabetes Mellitus (T2DM) is a challenge for sustainability. Psychological factors, healthy behaviors, and stressful conditions are predictive and prognostic factors for T2DM. Focusing on psychological factors can reduce costs and help ensure the sustainability of diabetes care. The study aimed to support an integrated medical-psychological approach in the care of patients with T2DM. A group of patients undergoing usual healthcare treatment was compared to patients who received a psychotherapeutic intervention in addition to standard treatment. The study’s outcomes were: physical health (blood glucose, glycated hemoglobin, blood lipids, blood pressure); lifestyle (cigarettes, alcoholic drinks, physical activity, body mass index); mental health (anxiety, depression, stress, coping styles, alexithymia, emotion regulation, locus of control); costs (number of referrals to a specialist, standard cost of each visit). We examined the change from baseline to 24-week follow-up. Compared to the Standard Group, the Integrated Group reported a reduction in blood lipids and triglycerides, chronic depressive and anxious mood states, patient emotional coping, and the number of specialist visits and diagnostic tests. Close collaboration between diabetologists and psychologists is feasible, and it is worth considering integrated care as an option to contain and make healthcare spending more sustainable.

Healthcare spending in U.S. emergency departments by health condition, 2006–2016

Background Healthcare spending in the emergency department (ED) setting has received intense focus from policymakers in the United States (U.S.). Relatively few studies have systematically evaluated ED spending over time or disaggregated ED spending by policy-relevant groups, including health condition, age, sex, and payer to inform these discussions. This study’s objective is to estimate ED spending trends in the U.S. from 2006 to 2016, by age, sex, payer, and across 154 health conditions and assess ED spending per visit over time. Methods and findings This observational study utilized the National Emergency Department Sample, a nationally representative sample of hospital-based ED visits in the U.S. to measure healthcare spending for ED care. All spending estimates were adjusted for inflation and presented in 2016 U.S. Dollars. Overall ED spending was $79.2 billion (CI, $79.2 billion-$79.2 billion) in 2006 and grew to $136.6 billion (CI, $136.6 billion-$136.6 billion) in 2016, representing a population-adjusted annualized rate of change of 4.4% (CI, 4.4%-4.5%) as compared to total healthcare spending (1.4% [CI, 1.4%-1.4%]) during that same ten-year period. The percentage of U.S. health spending attributable to the ED has increased from 3.9% (CI, 3.9%-3.9%) in 2006 to 5.0% (CI, 5.0%-5.0%) in 2016. Nearly equal parts of ED spending in 2016 was paid by private payers (49.3% [CI, 49.3%-49.3%]) and public payers (46.9% [CI, 46.9%-46.9%]), with the remainder attributable to out-of-pocket spending (3.9% [CI, 3.9%-3.9%]). In terms of key groups, the majority of ED spending was allocated among females (versus males) and treat-and-release patients (versus those hospitalized); those between age 20–44 accounted for a plurality of ED spending. Road injuries, falls, and urinary diseases witnessed the highest levels of ED spending, accounting for 14.1% (CI, 13.1%-15.1%) of total ED spending in 2016. ED spending per visit also increased over time from $660.0 (CI, $655.1-$665.2) in 2006 to $943.2 (CI, $934.3-$951.6) in 2016, or at an annualized rate of 3.4% (CI, 3.3%-3.4%). Conclusions Though ED spending accounts for a relatively small portion of total health system spending in the U.S., ED spending is sizable and growing. Understanding which diseases are driving this spending is helpful for informing value-based reforms that can impact overall health care costs.

The Morbidity Costs of Air Pollution through the Lens of Health Spending in China

This study offers one of the first causal evidence on the morbidity costs of fine particulates (PM2.5) for all age cohorts in a developing country, using individual-level healthcare spending data from the basic medical insurance program in Wuhan, China. Our instrumental variable (IV) approach uses thermal inversion to address potential endogeneity in PM2.5 concentrations and shows that PM2.5 imposes a significant impact on medical expenditures. The IV estimate suggests that a 10 μg/m3 reduction in monthly average PM2.5 leads to a 2.79% decrease in the value of health spending and a 0.70% decline in the number of transactions in pharmacies and health facilities. The effect is more salient for males, children, and older adults. Moreover, our estimates provide a lower bound of people's willingness-to-pay, which amounts to CNY 51.85 (or USD 8.38) per capita per year for a 10 μg/m3 reduction in PM2.5.

Falsified and Substandard Medicines in Developing Countries: Seeking for The Sampling Procedure to Find them

Falsified and substandard medicines is a very important issue, especially in developing countries including Indonesia. World Health Organization (WHO) stated that 1 in 10 medicines in developing countries are substandard or falsified. It is result in risks for patients and health systems relating to ineffective drugs, prolong treatment times, possible side effects, increased healthcare spending, even the risk of serious illness and death. There are many factors responsible for this situation, namely the effectiveness of government control, public drug procurement policies, market and economic competition, the depletion of entry barriers driven by free and online trade, availability of raw materials, and mastery of technology on pharmaceuticals. The problem is how to find falsified and substandard medicines amidst so many kinds of medicines in market. If the sampling is done randomly on all types of medicines in all market, it will be less likely to find them. In addition, this kind of sampling technique will be expensive because it requires a lot of resources. Therefore, a risk-based systematic mechanism is needed to guide sampling procedure. This research was aimed to design a model that could be used as a reference. Using the system thinking method, we mapped out relationships between various factors and phenomena surrounding the issue. Then, the system dynamics modelling was developed with a focus on sentinel groups that were most at risk of drug counterfeiting cases. All relevant variables were discussed, and some recommendations were provided in this paper. We hope, using this recommendation, the sampling procedure becomes faster, more efficient, and more likely to find cases. It is because the more effective the way to control falsified and substandard medicines, the higher the protection that consumers or patients may get.