Analysis of Crash Data Using Quantile Regression for Counts

Effects of private health insurance on medical expenditure and health service utilization in South Korea: a quantile regression analysis

BACKGROUND

Despite universal health insurance, South Korea has seen a sharp increase in the number of people enrolled in supplemental private health insurance (PHI) during the last decade. This study examined how private health insurance enrollment affects medical expenditure and health service utilization.

METHODS

Unbalanced panel data for adults aged 19 and older were constructed using the 2016-2018 Korea Health Panel Survey. Quantile regression for medical cost, and quantile count regression for health service utilization were utilized using propensity score-matched data. We included 17 variables representing demographic, socioeconomic, and health information, as well as medical costs and use of outpatient and inpatient care.

RESULTS

We discovered that PHI enrollees' socioeconomic and health status is more likely to be better than PHI non-enrollees'. Results showed that private health insurance had a greater effect on the lower quantiles of the conditional distribution of outpatient costs (coefficient 0.149 at the 10th quantile and 0.121 at the 25th quantile) and higher quantiles of inpaitent care utilization (coefficient 0.321 at the 90th quantile for days of hospitalization and 0.076 at the 90th quantile for number of inpatient visits).

CONCLUSIONS

PHI enrollment is positively correlated with outpatient costs and inpatient care utilization. Government policies should consider these heterogeneous distributional effects of private health insurance.

A Spatial Autoregressive Quantile Regression to Examine Quantile Effects of Regional Factors on Crash Rates

Spatial autocorrelation and skewed distribution are the most frequent issues in crash rate modelling analysis. Previous studies commonly focus on the spatial autocorrelation between adjacent regions or the relationships between crash rate and potentially risky factors across different quantiles of crash rate distribution, but rarely both. To overcome the research gap, this study utilizes the spatial autoregressive quantile (SARQ) model to estimate how contributing factors influence the total and fatal-plus-injury crash rates and how modelling relationships change across the distribution of crash rates considering the effects of spatial autocorrelation. Three types of explanatory variables, i.e., demographic, traffic networks and volumes, and land-use patterns, were considered. Using data collected in New York City from 2017 to 2019, the results show that: (1) the SARQ model outperforms the traditional quantile regression model in prediction and fitting performance; (2) the effects of variables vary with the quantiles, mainly classifying three types: increasing, unchanged, and U-shaped; (3) at the high tail of crash rate distribution, the effects commonly have sudden increases/decrease. The findings are expected to provide strategies for reducing the crash rate and improving road traffic safety.

Spatial heterogeneity analysis of macro-level crashes using geographically weighted Poisson quantile regression

In recent years, globally quantile-based model (e.g. quantile regression) and spatially conditional mean models (e.g. geographically weighted regression) have been widely and commonly employed in macro-level safety analysis. The former ones assume that the model coefficients are fixed over space, while the latter ones only represent the entire distribution of variable effects by a single concentrated trend. However, the influence of crash related factors on the distribution of crash frequency is observed to vary over space and across different quantiles. Therefore, a geographically weighted Poisson quantile regression (GWPQR) model is employed to investigate the spatial heterogeneity of variable effects crossing different quantiles. Five categories, including exposure, socio-economic, transportation, network and land use were selected to estimate the spatial effects on crash frequency. In the case study, vehicle related crashes collected in New York City were used to validate the predicted performance of the proposed models. The results show that the GWPQR outperforms the NB, QR and GWNBR for modeling the skewed distribution, reconstructing the crash distribution and capturing the unobserved spatial heterogeneity. Additionally, the significant coefficients are further used to classify all 21 variables into key, important and general parts. Then we discuss how these factors affects the regional crashes over space and distribution of crash frequency. This study confirms that the influencing factors have varying effects on different quantiles of distribution and on different regions, which could be helpful to provide support for making safety countermeasures and policies at urban regional level.

Discharge destination following hip fracture in Canada among previously community-dwelling older adults, 2004-2012: database study

Little is known about post-acute care following hip fracture surgery. We investigated discharge destinations from surgical hospitals for nine Canadian provinces. We identified significant heterogeneity in discharge patterns across provinces suggesting different post-acute recovery pathways. Further work is required to determine the impact on patient outcomes and health system costs.

INTRODUCTION

To examine discharge destinations by provinces in Canada, adjusting for patient, injury, and care characteristics.

METHODS

We analyzed population-based hospital discharge abstracts from a national administrative database for community-dwelling patients who underwent hip fracture surgery between 2004 and 2012 in Canada. Discharge destination was categorized as rehabilitation, home, acute care, and continuing care. Multinomial logistic regression modeling compared proportions of discharge to rehabilitation, acute care, and continuing care versus home between each province and Ontario. Adjusted risk differences and risk ratios were estimated.

RESULTS

Of 111,952 previously community-dwelling patients aged 65 years or older, 22.5% were discharged to rehabilitation, 31.6% to home, 27.0% to acute care, and 18.2% to continuing care, with significant variation across provinces (p < 0.001). The proportion of discharge to rehabilitation ranged from 2.4% in British Columbia to 41.0% in Ontario while the proportion discharged home ranged from 20.3% in Prince Edward Island to 52.2% in British Columbia. The proportion of discharge to acute care ranged from 15.2% in Ontario to 58.8% in Saskatchewan while the proportion discharged to continuing care ranged from 9.3% in Manitoba and Prince Edward Island to 22.9% in New Brunswick. Adjusting for hospital type changed the direction of the provincial effect on discharge to continuing care in two provinces, but statistical significance remained consistent with the primary analysis.

CONCLUSIONS

Discharge destination from the surgical hospital after hip fracture is highly variable across nine Canadian provinces. Further work is required to determine the impact of this heterogeneity on patient outcomes and health system costs.

Identifying the safety factors over traffic signs in state roads using a panel quantile regression approach

OBJECTIVE

This study intended to investigate the interactions between accident rate and traffic signs on state roads located in Croatia and accommodate the heterogeneity attributed to unobserved factors. Data from 130 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia's Ministry of the Interior.

METHODS

To address the heterogeneity, a panel quantile regression model was proposed, in which a quantile regression model offers a more complete view and a highly comprehensive analysis of the relationship between accident rate and traffic signs, and the panel data model accommodates the heterogeneity attributed to unobserved factors.

RESULTS

Results revealed that (1) low visibility of material damage (MD) and death or injury (DI) increased the accident rate; (2) the number of mandatory signs and the number of warning signs were more likely to reduce the accident rate; (3) the average speed limit and the number of invalid traffic signs per kilometer exhibited a high accident rate.

CONCLUSIONS

To our knowledge, this study is the first attempt to analyze the interactions between accident consequences and traffic signs by employing a panel quantile regression model; by including visibility, the present study demonstrates that low visibility causes a relatively higher risk of MD and DI. It is noteworthy that average speed limit positively corresponds with accident rate; the number of mandatory signs and the number of warning signs are more likely to reduce the accident rate; and the number of invalid traffic signs per kilometer is significant for the accident rate; thus, regular maintenance should be performed for a safer roadway environment.

Time to surgery after hip fracture across Canada by timing of admission

The extent of Canadian provincial variation in hip fracture surgical timing is unclear. Provinces performed a similar proportion of surgeries within three inpatient days after adjustment. Time to surgery varied by timing of admission across provinces. This may reflect different approaches to providing access to hip fracture surgery.

INTRODUCTION

The aim of this study was to compare whether time to surgery after hip fracture varies across Canadian provinces for surgically fit patients and their subgroups defined by timing of admission.

METHODS

We retrieved hospitalization records for 140,235 patients 65 years and older, treated surgically for hip fracture between 2004 and 2012 in Canada (excluding Quebec). We studied the proportion of surgeries on admission day and within 3 inpatient days, and times required for 33%, 66%, and 90% of surgeries across provinces and by subgroups defined by timing of admission. Differences were adjusted for patient, injury, and care characteristics.

RESULTS

Overall, provinces performed similar proportions of surgeries within the recommended three inpatient days, with all provinces requiring one additional day to perform the recommended 90% of surgeries. Prince Edward Island performed 7.0% more surgeries on admission day than Ontario irrespective of timing of admission (difference = 7.0; 95% CI 4.0, 9.9). The proportion of surgeries on admission day was 6.3% lower in Manitoba (difference = - 6.3; 95% CI - 12.1, - 0.6), and 7.7% lower in Saskatchewan (difference = - 7.7; 95% CI - 12.7, - 2.8) compared to Ontario. These differences persisted for late weekday and weekend admissions. The time required for 33%, 66%, and 90% of surgeries ranged from 1 to 2, 2-3, and 3-4 days, respectively, across provinces by timing of admission.

CONCLUSIONS

Provinces performed similarly with respect to recommended time for hip fracture surgery. The proportion of surgeries on admission day, and time required to complete 33% and 66% of surgeries, varied across provinces and by timing of admission. This may reflect different provincial approaches to providing access to hip fracture surgery.