Health care utilization after hospitalization following a road traffic accident.

Purpose: In recent years, there has been an increasing interest in measuring and modeling health care utilization. However, only limited research has been performed in the field of health care utilization following road traffic accidents. This article aims to measure the incremental health care utilization after hospital discharge after a road traffic accident and explore the association between socio-demographic and injury-related variables and health care utilization.Material and methods: Generalized linear models with negative binomial distribution and log-link were executed per type of health care provider (general practitioner, medical specialists, rehabilitation services and outpatient nursing care) and per type of discharge location (discharged to home, discharged to in-hospital rehabilitation). Health care utilization of the 6 months after discharge was compared with the 6 months before the accident (baseline care).Results: Health care utilization six months after discharge is significantly higher than baseline care, except for outpatient nursing care and general practitioners in in-hospital rehabilitation. The increase in visits to medical specialists ranged on average between 1 and 2.2 visits. For general practitioner, there was an increase of 0.4 visits and 0.8 in outpatient nursing care for those who returned home after acute hospitalization. The average increase in rehabilitation services ranged between 3.6 and 20. Associated influential factors differ per health care provider and discharge destination.Conclusion: Evidence of this study suggests higher health care utilization during the first 6 months following hospitalization due to a road traffic injury, compared with baseline care. Associated variables differ per type of health care provider and discharge-destination. More in-depth research on subgroups is needed.Implications for rehabilitationHealth care utilization varies across different patient characteristics and type of injuries which should be considered in the communication with patients on their care trajectory post-discharge.General descriptions of health care utilization in traffic victims at the population level are lacking. Output similar to our study could serve as a reference for post-discharge care planning.The research output can be a starting point for future research on quality indicators of the expected quantity of care.Efforts must be made to estimate suchlike reference tables on post-discharge services in other patient groups and secondary data are a suitable data-source for those analyses.

The Incremental Hospitalization Cost of Significant Transport-Related Traumatic Brain Injury.

AIM: This study aims to determine the incremental cost of acute hospitalization for traumatic brain injury (TBI) compared with matched controls. A second purpose is to identify the factors contributing to this hospital costs. METHODOLOGY: Analyses were performed on administrative data for injured patients, hospitalized in Belgium between 2009 and 2011 following a road traffic accident. Cases were matched to a control with similar injuries but without TBI. The incremental hospitalization cost of TBI and the factors contributing to the hospital costs were determined using multivariable regression modeling with gamma distribution and log link. RESULTS: A descriptive comparison of cases and controls shows clear differences in healthcare utilization and costs. The presence of a TBI increases the cost by a factor between 1.66 (95% confidence interval: 1.52-1.82) and 2.08 (95% confidence interval: 1.72-2.51). Regarding healthcare utilization, the most important determinants of hospital costs are surgical complexity, use of magnetic resonance imaging, intensive care unit admission, and mechanical ventilation. DISCUSSION: To our knowledge, this is the first matched-control study calculating the incremental hospitalization cost of TBI. The insights provided by this study are relevant in the context of prospective payments and can be an incentive for investments in prevention policies and extramural care.

The incremental cost of traumatic brain injury during the first year after a road traffic accident.

This study aims to determine the incremental cost of TBI during the first year after a traffic accident, compared to other patients with similar non-TBI injuries. Secondly, identification of factors associated with medical costs of TBI is pursued. Analyses were performed on administrative data for traffic victims hospitalised in Belgium between 2009 and 2011. Medical costs attributable to the accident are estimated over one year post-injury. Cases with TBI were matched to controls with similar non-TBI injuries to determine the incremental cost of TBI. Both aims of this research were assessed using regression analysis. The incremental cost of TBI is estimated to range between € 10 042 (95%CI [€8198; €11 887]) and €21 715 (95%CI [€13 5889; €29 540]). Age, problems with self-reliance, survival status, the occurrence of acute events and severity of TBI are significant predictors of medical costs. As to healthcare utilisation, MRI usage, inpatient rehabilitation facilities, nursing homes and readmissions to acute hospital stand out as having most influence on costs. This study reveals a considerable incremental cost of TBI. Policy-making bodies should be made aware of this phenomenon and a diversified policy should be considered when financing programs are discussed.

Time Gain Needed for In-Ambulance Telemedicine: Cost-Utility Model.

BACKGROUND: Stroke is a very time-sensitive pathology, and many new solutions target the optimization of prehospital stroke care to improve the stroke management process. In-ambulance telemedicine, defined by live bidirectional audio-video between a patient and a neurologist in a moving ambulance and the automated transfer of vital parameters, is a promising new approach to speed up and improve the quality of acute stroke care. Currently, no evidence exists on the cost effectiveness of in-ambulance telemedicine. OBJECTIVE: We aim to develop a first cost effectiveness model for in-ambulance telemedicine and use this model to estimate the time savings needed before in-ambulance telemedicine becomes cost effective. METHODS: Current standard stroke care is compared with current standard stroke care supplemented with in-ambulance telemedicine using a cost-utility model measuring costs and quality-adjusted life-years (QALYs) from a health care perspective. We combine a decision tree with a Markov model. Data from the UZ Brussel Stroke Registry (2282 stroke patients) and linked hospital claims data at individual level are combined with literature data to populate the model. A 2-way sensitivity analysis varying both implementation costs and time gain is performed to map the different cost-effective combinations and identify the time gain needed for cost effectiveness and dominance. For several modeled time gains, the cost-effectiveness acceptability curve is calculated and mapped in 1 figure. RESULTS: Under the base-case scenario (implementation cost of US $159,425) and taking a lifetime horizon into account, in-ambulance telemedicine is a cost-effective strategy compared to standard stroke care alone starting from a time gain of 6 minutes. After 12 minutes, in-ambulance telemedicine becomes dominant, and this results in a mean decrease of costs by US -$30 (95% CI -$32 to -$29) per patient with 0.00456 (95% CI 0.00448 to 0.00463) QALYs on average gained per patient. In over 82% of all probabilistic simulations, in-ambulance telemedicine remains under the cost-effectiveness threshold of US $47,747. CONCLUSIONS: Our model suggests that in-ambulance telemedicine can be cost effective starting from a time gain of 6 minutes and becomes a dominant strategy after approximately 15 minutes. This indicates that in-ambulance telemedicine has the potential to become a cost-effective intervention assuming time gains in clinical implementations are realized in the future.

Variations in hospital costs after traffic injuries: The importance of sociodemographic aspects and comorbidities.

OBJECTIVE: The impact of sociodemographic aspects and comorbidities on the inpatient hospital care costs of traffic victims are not clear. The main goal of this study is to provide insights into the sociodemographic characteristics and clinical conditions (including comorbidities) of the victims that result in higher hospital costs. PARTICIPANTS: For the period 2009-2011, people admitted to a hospital as a result of a road traffic crash (N=64,304) were identified in the national Minimal Hospital Dataset, after which they were linked to their respective claims data from the sickness funds. METHODS: A generalized linear model was used to analyse hospital costs controlling for roadway user categories, demographics (gender, age, individual socioeconomic status (SES)), and clinical factors (the nature, location, and severity of injury, and comorbidities). RESULTS: The median hospital cost was € 2801 (IQR € 1510-€ 7175, 2015 Euros). There was no significant difference between gender. Low SES inpatients incurred 16% (95% CI: 14%-18%) higher hospital costs than inpatients of high SES. The presence of comorbidities was associated with an increased hospital cost, however with varying magnitude. For example traffic victims suffering from dementia incur significantly higher hospital costs than those who were not (49% higher, 95% CI: 44%-53%), whereas diabetes was associated with a smaller increase in costs compared to non-diabetics (13%, 95% CI: 10%-16%). CONCLUSION: Comorbidities and low SES are associated with higher hospital costs for traffic victims, notwithstanding their age, and the nature and the severity of their injury. The broad variability of hospital costs among trauma inpatients should be accounted for when reconsidering financing models. Furthermore, the strong predictive value of some comorbidities and SES on hospital costs should be considered when projections of future health care utilisation in traffic safety scenarios are prepared.

Long-term impact of stroke on patients' health-related quality of life.

PURPOSE: This international study aims to examine the size and determinants of the impact of stroke on five-year survivors' health-related quality of life (HRQoL) in four different European countries. METHOD: Patients were recruited consecutively in four European rehabilitation centers. Five years after stroke, the EuroQol-visual analog scale (EQ-VAS) was administered in 226 first-ever stroke patients. Impact of stroke was determined by calculating EQ-VAS z-norm scores (= deviation - expressed in SD - of patients' EQ-VAS level relative to their age-and gender-matched national population norms). Determinants of EQ-VAS z-norm scores were identified using multivariate linear regression analysis. RESULTS: Five years post-stroke, patients' mean EQ-VAS was 63.74 (SD = 19.33). Mean EQ-VAS z-norm score was -0.57 [95%CI: (-0.70)-(-0.42)]. Forty percent of the patients had an EQ-VAS z-norm score <-0.75 SD; 52% had an EQ-VAS z-norm score between -0.75 and +0.75 SD, only 8% scored >+0.75 SD. Higher patients' levels of depression, anxiety and disability were associated with increasingly negative EQ-VAS z-norm scores (adjusted R2 = 0.392). CONCLUSIONS: Five years after stroke, mean HRQoL of stroke survivors showed large variability and was more than ½ SD below population norm. Forty percent had a HRQoL level below, 52% on, and 8% above population norm. The variability could only partially be explained by the variables considered in this study. Longitudinal studies are needed to increase our understanding of the size and determinants of the impact of stroke on the HRQoL of long-term stroke survivors. Implications for rehabilitation The current European concept of stroke rehabilitation is focused on the acute and sub-acute rehabilitation phase, i.e., in the first months after stroke. The results of this study show that at five years after stroke, the mean level of HRQoL of stroke survivors remains below the healthy population level. This finding shows the need for continuation of rehabilitation in the chronic phase. At five years after stroke, higher patients' levels of depression, anxiety and disability were associated with lower scores for HRQoL. This finding implicates that chronic rehabilitation programs should be multi-faceted in order to increase long-term survivors' psychosocial outcomes.

Effect of the shape of the exposure-response function on estimated hospital costs in a study on non-elective pneumonia hospitalizations related to particulate matter.

OBJECTIVE: We used log-linear and log-log exposure-response (E-R) functions to model the association between PM2.5 exposure and non-elective hospitalizations for pneumonia, and estimated the attributable hospital costs by using the effect estimates obtained from both functions. METHODS: We used hospital discharge data on 3519 non-elective pneumonia admissions from UZ Brussels between 2007 and 2012 and we combined a case-crossover design with distributed lag models. The annual averted pneumonia hospitalization costs for a reduction in PM2.5 exposure from the mean (21.4µg/m(3)) to the WHO guideline for annual mean PM2.5 (10µg/m(3)) were estimated and extrapolated for Belgium. RESULTS: Non-elective hospitalizations for pneumonia were significantly associated with PM2.5 exposure in both models. Using a log-linear E-R function, the estimated risk reduction for pneumonia hospitalization associated with a decrease in mean PM2.5 exposure to 10µg/m(3) was 4.9%. The corresponding estimate for the log-log model was 10.7%. These estimates translate to an annual pneumonia hospital cost saving in Belgium of €15.5 million and almost €34 million for the log-linear and log-log E-R function, respectively. DISCUSSION: Although further research is required to assess the shape of the association between PM2.5 exposure and pneumonia hospitalizations, we demonstrated that estimates for health effects and associated costs heavily depend on the assumed E-R function. These results are important for policy making, as supra-linear E-R associations imply that significant health benefits may still be obtained from additional pollution control measures in areas where PM levels have already been reduced.

Direct cost saving potential in medication costs due to a reduction in outdoor air pollution for the Brussels Capital Region.

INTRODUCTION: The adverse health effects of exposure to air pollution have been well-established and include mortality, hospital admissions, emergency department visits, etc, but also less severe outcomes such as medication use and purchase. The economic impact, an additional motivator for policy, has been studied primarily for the more severe outcomes. METHODS: Purchase data of reimbursed medications typically prescribed for asthma and chronic obstructive pulmonary disease, were obtained through the mandatory Belgian health insurance system. A time series analyses approach was used to model daily sales on daily air pollution concentrations (NO2, PM10 and PM2.5) for residents of the Brussels Capital Region as a whole. In addition, a higher geographical resolution of both sales and pollutant concentrations allowed for a multi-sector approach. Annual savings were estimated for the scenario of a 10% reduction in each of the pollutants. RESULTS: Medication purchase was significantly associated with NO2 concentrations, leading to an annual cost saving potential of € 107,845 [95%CI: € 71,483-€ 143,823] in R03 sales (WHO classification for drugs of obstructive airway diseases). Saving potentials of PM10 and PM2.5 were not significant. Estimates were not sensitive to the geographical resolution, however, higher precision can be obtained with higher resolution data, subject to the condition that the number of sales is sufficiently large.

Predicting in-hospital mortality of traffic victims: A comparison between AIS-and ICD-9-CM-related injury severity scales when only ICD-9-CM is reported.

BACKGROUND AND AIM: Injury severity scores are important in the context of developing European and national goals on traffic safety, health-care benchmarking and improving patient communication. Various severity scores are available and are mostly based on Abbreviated Injury Scale (AIS) or International Classification of Diseases (ICD). The aim of this paper is to compare the predictive value for in-hospital mortality between the various severity scores if only International Classification of Diseases, 9th revision, Clinical Modification ICD-9-CM is reported. METHODOLOGY: To estimate severity scores based on the AIS lexicon, ICD-9-CM codes were converted with ICD Programmes for Injury Categorization (ICDPIC) and four AIS-based severity scores were derived: Maximum AIS (MaxAIS), Injury Severity Score (ISS), New Injury Severity Score (NISS) and Exponential Injury Severity Score (EISS). Based on ICD-9-CM, six severity scores were calculated. Determined by the number of injuries taken into account and the means by which survival risk ratios (SRRs) were calculated, four different approaches were used to calculate the ICD-9-based Injury Severity Scores (ICISS). The Trauma Mortality Prediction Model (TMPM) was calculated with the ICD-9-CM-based model averaged regression coefficients (MARC) for both the single worst injury and multiple injuries. Severity scores were compared via model discrimination and calibration. Model comparisons were performed separately for the severity scores based on the single worst injury and multiple injuries. RESULTS: For ICD-9-based scales, estimation of area under the receiver operating characteristic curve (AUROC) ranges between 0.94 and 0.96, while AIS-based scales range between 0.72 and 0.76, respectively. The intercept in the calibration plots is not significantly different from 0 for MaxAIS, ICISS and TMPM. DISCUSSION: When only ICD-9-CM codes are reported, ICD-9-CM-based severity scores perform better than severity scores based on the conversion to AIS.

Cost saving potential in cardiovascular hospital costs due to reduction in air pollution.

OBJECTIVE: We describe a methodological framework to estimate potential cost savings in Belgium for a decrease in cardiovascular emergency admissions (ischemic heart disease (IHD), heart rhythm disturbances (HRD), and heart failure) due to a reduction in air pollution. METHODS: Hospital discharge data on emergency admissions from an academic hospital were used to identify cases, derive risk functions, and estimate hospital costs. Risk functions were derived with case-crossover analyses with weekly average PM10, PM2.5, and NO2 exposures. The risk functions were subsequently used in a micro-costing analysis approach. Annual hospital cost savings for Belgium were estimated for two scenarios on the decrease of air pollution: 1) 10% reduction in each of the pollutants and 2) reduction towards annual WHO guidelines. RESULTS: Emergency admissions for IHD and HRD were significantly associated with PM10, PM2.5, and NO2 exposures the week before admission. The estimated risk reduction for IHD admissions was 2.44% [95% confidence interval (CI): 0.33%-4.50%], 2.34% [95% CI: 0.62%-4.03%], and 3.93% [95% CI: 1.14%-6.65%] for a 10% reduction in PM10, PM2.5, and NO2 respectively. For Belgium, the associated annual cost savings were estimated at € 5.2 million, € 5.0 million, and € 8.4 million respectively. For HRD, admission risk could be reduced by 2.16% [95% CI: 0.14%-4.15%], 2.08% [95% CI: 0.42%-3.70%], and 3.46% [95% CI: 0.84%-6.01%] for a 10% reduction in PM10, PM2.5, and NO2 respectively. This corresponds with a potential annual hospital cost saving in Belgium of € 3.7 million, € 3.6 million, and € 5.9 million respectively. If WHO annual guidelines for PM10 and PM2.5 are met, more than triple these amounts would be saved. DISCUSSION: This study demonstrates that a model chain of case-crossover and micro-costing analyses can be applied in order to obtain estimates on the impact of air pollution on hospital costs.