Abstract
Background:
More children with spina bifida (SB) are surviving into adulthood. Unfortunately, little data exist regarding the economic implications of modern SB care.
Objective:
We examined economic data from two national databases to estimate the annual nationwide hospital and emergency charges of SB from 2006–14.
Methods:
We analyzed the 2006–2014 Nationwide Inpatient Sample (NIS) and Nationwide Emergency Department Sample (NEDS). SB patients were defined using ICD-9-CM codes. Demographic and charge data were obtained from each database. Multiple imputation was used to estimate missing data (1.6% for NIS and 22% in NEDS). The principal outcomes were mean, median, and total charges for encounters each year.
Results:
There were 725,646 encounters for individuals with SB between 2006 and 2014. The average age of captured SB patients who were admitted to a hospital or seen in an ER was 29 years. In 2014, the median charge for inpatient encounters was $31,071 (IQR: $15,947, $63,063) and for ER encounters was $2407.02 (IQR: $1321.91, $4211.35). In total, the sum of charges from all SB-related admissions in 2014 was $1,862,016,217 (95% CI: $1.69 billion, $2.03 billion), while the sum of charges of all SB-related ER encounters in 2014 was $176,843,522 (95% CI: $158 million, $196 million). There was a steady increase in charges over the study period.
Conclusion:
Charges for SB-related inpatient and emergency care in the US in 2014 was in excess of $2 billion in contrast to $1.2 billion in 2006, after adjusting for inflation; this is an impressively high figure for a relatively small number of patients.
Keywords: Spina bifida, Pediatrics, Spinal dysraphism
Spina bifida (SB) is the most common survivable, permanently disabling congenital anomaly, occurring in approximately 3/10,000 live births.1–4 This disease has a wide range of presentations, but the underlying pathophysiology is due to the incomplete closure of the caudal neural tube during the first two weeks of embryonic development. While folic acid supplementation and prenatal screening have decreased the incidence of spina bifida, SB remains the most common permanently disabling birth defect in the United States. Furthermore, SB patients are increasingly surviving into adulthood as a result of medical advancements and improvements in practice patterns.5,6 With more SB patients surviving into adulthood, there has been a focus on the lifetime cost of the disease since SB patients are high users of medical care for their many medical problems. Understanding the charges would aid in determining the economic impact of these interventions on society.
Numerous groups have studied medical expenditures or lifetime costs of SB. Dicianno and Wilson abstracted data from the 2004–2005 Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) and reported that the national estimated sample size of approximately 37,000 SB inpatients had mean total charges of $28,918, or a total of $1.08 billion in 2005.7 Ouyang et al. analyzed data from the 2001–2003 Marketscan database on paid medical and prescription drug claims; their cohort had average inpatient and outpatient medical expenditures of $15,911 in 2003. Furthermore, they estimated lifetime medical expenditures for an average SB patient to be approximately $319,000.8 A more recent analysis of data from the National Birth Defects Prevention Network using inpatient and outpatient cost data from other studies estimated the lifetime direct costs of a live-born child with spina bifida in 2014 to be $791,900.9
In this study, we sought to describe current SB-associated charges using a large cohort drawn from updated data from both emergency and inpatient settings. To perform this, we used two national databases, one of inpatient admissions (NIS) and another following emergency department (ED) encounters (Nationwide Emergency Department Sample (NEDS)).
Methods
Data source
The 2006 to 2014 NIS and NEDS databases from the Healthcare Cost and Utilization Project (HCUP) were used. All analyses utilized HCUP data distributed by CD-ROM or digital download. The NIS approximates a 20-percent stratified sample of all discharges from U.S. community hospitals, excluding rehabilitation and long-term acute care hospitals. Weights are applied to the sample to make national level inferences.10 NEDS approximates a 20% sample of hospital-based EDs in the US. All ED visits are retained from each sampled hospital. Similar to the NIS, weights are applied to make national level inferences.11
Selection of patients and covariates
We identified all patients encountered in either NIS or NEDS between 2006 and 2014 with an International Classification of Disease (ICD)-9 code for SB (756.17, 741.0, 741.9, 741.00, 741.01, 741.02, 741.03, 741.90, 741.91, 741.92, 741.93). Patients identified with ICD-9 codes for bladder exstrophy, congenital spondylolysis, and non-scoliosis spine malformations (753.5, 756.13, and 756.11) were excluded. Covariates included basic patient demographics (age, gender), insurance payer (public vs. private), inpatient length of stay, year of admission or ED encounter, encounter outcomes, and Van Walraven comorbidity index (VWI; used to measure a patient’s comorbidity level).
The VWI is a modification of the Elixhauser comorbidity score. The Elixhauser score includes 30 dichotomous disease variables instead of an overall index score. To overcome this limitation, Van Walraven et al. derived weights to summarize the 30 variables into a single score. The score can range from −19 to 89 and is susceptible to coding bias.12
Outcomes
Our primary outcome was total charges of hospital discharge in either the inpatient or emergency department care setting. We examined this variable by calculating the mean and median charge per year, then summed the total charges of all encounters associated with SB within a given year and care setting. We adjusted for inflation at the 2017-dollar value using the Consumer Price Index-All Urban Consumers (Appendix 1). The CPI standard index was chosen over medical specific CPI as it more accurately accounts for technological improvement, quality change, and improved health outcomes.13,14
Statistical analysis
Weighted descriptive statistics were used to describe the demographics of each cohort as per HCUP recommendations.15 Due to the NIS redesign in 2012, the revised trend weight was applied to years prior to 2012 (2006–2011) as HCUP recommends.16 Multiple imputations were utilized to estimate missing charge data in both the NIS and NEDS since 1.6% and 22% of inpatient and ED discharges, respectively, were missing charge data. This was performed using a full conditional model, which allows for imputation across different variable types. To impute charge, we first had to impute missing covariates that would be used in our imputation model. Age was missing for 0.07% of encounters in the NIS and 0.02% of encounters in the NEDS, gender was missing for 0.08% of encounters in the NIS and 0.03% of encounters in the NEDS, insurance was missing for 0.14% of encounters in the NIS and 0.1% of encounters in the NEDS and length of stay was missing for 0.01% of encounters in the NIS. Regression imputation was used for continuous variables (age, length of stay and charge), logistic imputation was used for binary variables (gender), and discriminate imputation was used for categorical variables (insurance). The charge imputation model used gender, insurance, length of stay, age, HCUP Stratum, and year. Length of stay was excluded from NEDS since that information is not collected specifically for ED admissions. Race was excluded as this variable is not collected in NEDS.17 Year and HCUP stratum were utilized to impute missing covariates. The exception was for insurance payer, since only continuous variables can be used while fitting a discriminate imputation model in SAS 9.4; thus, both age and year of admission were used. Twenty imputed data sets were generated. With each data set, the mean, median, quartiles and sum of charges were reported. The final estimate for each of the four statistics was defined as the average of the twenty estimates generated from each imputed data set. Confidence intervals for the reported statistics were calculated using the Rubin method.18
In many cases, the inclusion of imputed values can improve statistical inference.19 Imputed values were compared to non-missing values and were empirically determined to be reasonable. As a sensitivity analysis, we took a random sample of 1500 observations from the non-missing charges and treated them as missing. We then used our multiple imputation model, using the observations with non-missing charges only, to estimate these 1500 observations. The mean of these estimates was compared to the mean of the true values. We also compared the demographic characteristics of the missing to the non-missing cases. This was done in both care settings. SAS 9.4 was used for all analyses with Proc MI and Proc MIANALYZE specifically for calculating imputations and assessing them respectively.[17–21]
Results
Demographics
There were 725,646 encounters for individuals with SB identified in NIS and NEDS between 2006 and 2014, with 430,530 (59.3%) being ED encounters (Table 1). The mean age of both inpatient (29 years; 95% CI: 28.3, 29.7) and ED (29 years; 95% CI: 28.6, 29.8) encounters were similar. The rate of females in either setting was approximately 57%. Public insurance (63.2% in NIS vs 66.4% NEDS) was the most common payer type. Q1 (29.3% in NIS vs 30.5% in NEDS) and Q2 (27.3% in NIS vs 28.6% in NEDS) were the most common reported Median Income by quartiles in both care settings.
Table 1.
Demographics of spina bifida patients captured from 2006 to 2014 in the NIS and NEDS databases.
| Variable | Inpatient (n = 295116) | ED (n = 430530) |
|---|---|---|
| Age (years) | ||
| Mean (95% CI) | 29 (28.3, 29.7) | 29 (28.6, 29.8) |
| Min, Max | 0, 97 | 0, 100 |
| Gender | ||
| Female | 167428 (56.7%) | 246431 (57.2%) |
| Missing | 235 (0.08%) | 137 (0.03%) |
| Insurance | ||
| Public | 186323 (63.2%) | 285708 (66.4%) |
| Private | 89352 (30.3%) | 102212 (23.8%) |
| Other | 18954 (6.4%) | 41989 (9.8%) |
| Missing | 410 (0.14%) | 428 (0.1%) |
| Median Income by Quartiles | ||
| Q1 | 86419 (29.3%) | 131267 (30.5%) |
| Q2 | 80436 (27.3%) | 122995 (28.6%) |
| Q3 | 69557 (23.6%) | 100653 (23.4%) |
| Q4 | 51866 (17.6%) | 66951 (15.6%) |
| Missing | 6839 (2.3%) | 8663 (2%) |
| Year | ||
| 2006 | 30942 (10.5%) | 38546 (9%) |
| 2007 | 31134 (10.5%) | 42997 (10%) |
| 2008 | 32545 (11%) | 48251 (11.2%) |
| 2009 | 33467 (11.3%) | 47299 (11%) |
| 2010 | 35058 (11.9%) | 49029 (11.4%) |
| 2011 | 33791 (11.5%) | 50256 (11.7%) |
| 2012 | 33075 (11.2%) | 50521 (11.7%) |
| 2013 | 32445 (11%) | 52142 (12.1%) |
| 2014 | 32660 (11.1%) | 51489 (12%) |
| Life Status | ||
| Died | 3229 (1%) | 378 (0.09%) |
| Missing | 124 (0.04%) | 3897 (0.9%) |
| Van Walraven Score | ||
| ≤−1 | 35924 (12.2%) | 36077 (8.4%) |
| 0 | 120224 (40.7%) | 241451 (56.1%) |
| 1 | 3611 (1.2%) | 3438 (0.8%) |
| 2 | 4331 (1.5%) | 4229 (1%) |
| 3 | 19931 (6.8%) | 27687 (6.4%) |
| 4 | 5182 (1.8%) | 4778 (1.1%) |
| 5 | 20763 (7%) | 22484 (5.2%) |
| ≥6 | 85151 (28.9%) | 90387 (21%) |
Data Source: HCUP NIS and NEDS 2006–2014.
The number of encounters for individuals with SB in the NIS setting ranged between 30,000 and 35,000 per year and was consistent across the years. In contrast, the number of SB encounters in the NEDS ranged between 38,000 and 52,000 with a steady increase in the number admissions from the ED between 2006 and 2014.
One percent of encounters in the NIS and only 0.09% of NEDS encounters resulted in a death. 47% of NIS encounters had a Van Walraven comorbidity score greater than zero. In contrast, only 35.5% of NEDS encounters had a Van Walraven score greater than zero (at least one co-morbid condition).
There were differences observed in the demographic features between non-missing and missing charges in particular with age, insurance type and year of encounter (Appendix 2). This indicated that the data was not missing completely at random.
Annual mean inpatient and ED charges
Table 2 lists the annual mean inpatient and ED charges per encounter, after adjusting for inflation (Appendix 1). Mean charges associated with SB encounters in the NIS steadily increased from $36,560 (95% CI: $33,240.52, $39,878.77) in 2006 to $57,012 (95% CI: $54,088.98, $59,935.31) in 2014. In the NEDS, mean charges steadily increased from $1751.82 (95% CI: $1639.42, $1864.22) in 2006 to $3434.61 (95% CI: $3272.12, $3597.10) in 2014.
Table 2.
Mean charges per spina bifida inpatient and emergency department encounter by year from 2006 to 2014 per NIS and NEDS databases.
| Inpatient Mean Charges |
ED Mean Charges |
|||||
|---|---|---|---|---|---|---|
| Mean | 95%CI | Mean | 95% CI | |||
| 2006 | $36,560 | $33,240.52 | $39,878.77 | $1751.82 | $1639.42 | $1864.22 |
| 2007 | $39,464 | $36,586.03 | $42,342.88 | $1814.26 | $1716.23 | $1912.30 |
| 2008 | $41,242 | $37,201.85 | $45,281.73 | $2100.59 | $1955.54 | $2245.65 |
| 2009 | $45,254 | $41,251.31 | $49,257.26 | $2374.05 | $2233.46 | $2514.64 |
| 2010 | $44,379 | $44,379 | $44,379 | $2546.27 | $2377.51 | $2715.02 |
| 2011 | $46,778 | $42,954.12 | $50,602.49 | $2534.24 | $2379.95 | $2688.53 |
| 2012 | $53,164 | $50,130.47 | $56,198.48 | $2912.38 | $2767.90 | $3056.86 |
| 2013 | $55,766 | $52,203.81 | $59,328.79 | $3175.57 | $2989.24 | $3361.91 |
| 2014 | $57,012 | $54,088.98 | $59,935.31 | $3434.61 | $3272.12 | $3597.10 |
Data Source: HCUP NIS and NEDS 2006–2014.
Median annual charges in inpatient and ED encounters
Due to the inherent skewness of the charge data, median charges in the NIS and NEDS were examined (Table 3). After adjusting for inflation (see Appendix 1), median charges associated with SB encounters in the NIS steadily increased from $19,211 (IQR: $9638.59, $38,278) in 2006 to $31,071 (IQR: $15,947, $63,063) in 2014. In the NEDS, median charges steadily increased from $1215.82 (IQR: $608.77, $2344.34) in 2006 to $2407.02 (IQR: $1321.91, $4211.35) in 2014 (see Table 4).
Table 3.
Median charges per spina bifida inpatient and emergency department encounter by year from 2006 to 2014 per NIS and NEDS databases.
| Inpatient Median (IQR) Charges |
ED Median (IQR) Charges |
|||||
|---|---|---|---|---|---|---|
| Median | IQR | Median | IQR | |||
| 2006 | $19,211 | $9638.59 | $38,278 | $1215.82 | $608.77 | $2344.34 |
| 2007 | $20,986 | $10,462 | $42,702 | $1266.46 | $612.63 | $2433.19 |
| 2008 | $22,460 | $11,390 | $44,653 | $1410.32 | $727.94 | $2757.99 |
| 2009 | $23,913 | $12,280 | $50,094 | $1591.35 | $801.03 | $3011.89 |
| 2010 | $24,879 | $12,621 | $49,851 | $1711.00 | $895.28 | $3169.44 |
| 2011 | $25,989 | $13,173 | $54,010 | $1694.12 | $912.71 | $3055.95 |
| 2012 | $27,750 | $14,590 | $56,246 | $1977.59 | $1077.25 | $3603.19 |
| 2013 | $29,470 | $15,011 | $59,193 | $2117.42 | $1125.99 | $3833.84 |
| 2014 | $31,071 | $15,947 | $63,063 | $2407.02 | $1321.91 | $4211.35 |
Data Source: HCUP NIS and NEDS 2006–2014.
Table 4.
Total charges for all spina bifida inpatient and emergency department encounters by year from 2006 to 2014 per NIS and NEDS databases.
| Inpatient Sum of Charges |
ED Sum of Charges |
|||||
|---|---|---|---|---|---|---|
| Sum | 95%CI | Sum | 95% CI | |||
| 2006 | $1,131,228,362 | $9.09 × 108 | $1.35 × 109 | $67,524,725 | $5.7 × 107 | $7.8 × 107 |
| 2007 | $1,228,667,128 | $1.02 × 109 | $1.43 × 109 | $78,007,044 | $6.7 × 107 | $8.9 × 107 |
| 2008 | $1,342,213,656 | $1.08 × 109 | $1.61 × 109 | $101,356,129 | $8.8 × 107 | $1.15 × 108 |
| 2009 | $1,514,506,016 | $1.25 × 109 | $1.78 × 109 | $112,290,526 | $9.8 × 107 | $1.26 × 108 |
| 2010 | $1,555,813,834 | $1.29 × 109 | $1.83 × 109 | $124,841,950 | $1.08 × 108 | $1.42 × 108 |
| 2011 | $1,580,697,706 | $1.29 × 109 | $1.87 × 109 | $127,285,091 | $1.14 × 108 | $1.41 × 108 |
| 2012 | $1,758,415,242 | $1.59 × 109 | $1.92 × 109 | $146,992,772 | $1.30 × 108 | $1.64 × 108 |
| 2013 | $1,809,335,673 | $1.63 × 109 | $1.99 × 109 | $165,581,881 | $1.47 × 108 | $1.84 × 108 |
| 2014 | $1,862,016,217 | $1.69 × 109 | $2.03 × 109 | $176,843,522 | $1.58 × 108 | $1.96 × 108 |
Data Source: HCUP NIS and NEDS 2006–2014.
Total annual charges in inpatient and ED encounters
The sum of charges from all SB-related encounters in 2014 NIS was $1,862,016,217 (95% CI: 1.69 × 109, $2.03 × 109), while the sum of charges of all SB-related ER encounters in 2014 NEDS was $176,843,522 (95% CI: $1.58 × 108, $1.96 × 108). We observed a steady increase in total charges of all SB-related encounters in both the NIS and NEDS from 2006 to 2014.
Sensitivity analyses
Due to patterns of miss data, we investigated the model with imputed values. To assess the performance of the imputation, a random sample of 1500 observations from the non-missing charges were treated as missing. The multiple imputation model was used to estimate these 1500 values. The mean of these estimates was compared to the mean of the true values. For each of the years in the study (2006–2014), the 95% confidence intervals of these two means overlapped (Appendix 3 and 4). This empirical evidence suggests that the multiple imputation models were reasonable. We investigated the model with and without imputed values. We found that our calculated means from the complete cases only had similar results to our imputed findings, implying that they could be added to increase statistical inference (Appendix 5).
Discussion
To our knowledge, this study represents the most comprehensive inpatient and emergency department-based assessment of the economic impact of SB in the United States to date. Dicianno and Wilson (2010) reported a mean inpatient charge of $28,918 and a total sum of $1.08 billion for inpatient admissions in 2005. Our study attempted to build off this finding by documenting the trend of hospital and ED charges over time while also imputing values to improve statistical inference. For our data set, the mean and total charges associated with SB inpatient encounters in 2006, without adjusting for inflation, were found to be $35,154 (95% CI: $31,962.04, $38,344.97) and $1.09 billion (95% CI: $8.74 × 108, $1.30 × 109) respectively. These estimates are close to Dicianno’s estimated values in 2005. With inflation and the addition of ED encounters, our estimate of $2.04 billion between inpatient and emergency departments for 2014 is a large economic burden for a small number of patients. Furthermore, these charges may be an under-estimate of the economic impact of SB, as it excludes non-ER outpatient SB management, co-morbidities due to SB (that may have been coded for during encounters that excluded SB as a diagnosis), and additional costs related to the diagnosis such as durable medical equipment (e.g. wheelchairs and braces), and societal costs (such as patient/parental missed time from school/work, transportation to health care facilities).
While the annual number of inpatient encounters remained stable through the study period, there was an increase in the annual number of ED encounters over the same time period. Previous studies have suggested that approximately 1/3 of inpatient admissions are for preventable complications,7 and so this represents an opportunity for significant cost savings. Considering the mean age was 29 (95% CI: 28.6, 29.8) years for patients visiting the ED, an effort to expand transitional care for SB patients could yield positive financial dividends by keeping these patients out of the emergency room.22 Unfortunately, due to the nature of the NIS and NEDS, we were unable to parse out the granularity of the reason for each encounter, just that the patient had a diagnosis of spina bifida. Future investigations into the reasons for encounters could inform a strategy to manage these patients in a less expensive outpatient setting.
Our findings must be interpreted in the context of our study’s limitations. First, while the NIS contains cost-charge-ratio files that allow for an estimate of cost, NEDS data only contains charge data. Due to this, we presented all our findings as charges, not costs. Still, our concluded figure of total hospital charges for SB could be an under-estimate of the true economic burden of SB, as previously described. Another approach to calculating total cost for visits is to calculate costs using cost-to-charge (CCR) information. While HCUP does not publish CCR values that can be used for NEDS, it is of interest in future work to identify if this CCR information could be appropriately applied to this dataset.23
Another limitation is that the NIS and NEDS databases are derived from stratified sampled data. Although HCUP has included more hospitals and states with time, these data sets are not wholly representative of all hospitals and regions in the United States. While we did not focus on pediatric hospitals, as would be provided by using the Pediatric Health Information System database, the HCUP databases allowed us to capture SB patients, regardless of age, with a larger sample size to increase our power. Still, due to the lower prevalence of SB, our reported results may not be generalizable to encounters not in the sample pool. It may be of future interest to investigate if there is any potential bias in estimating costs. Further, NIS and NEDS are large, retrospective administrative databases that may be affected by inaccurate or incomplete coding. Notably, we impute 1.6% and 22% of total charges within the NIS and NEDS databases, respectively. The sensitivity analysis of the imputations indicated that this was appropriate. However, some of these missing values could be due to transfers from ED to inpatient. If this is the case, there is a potential for some of these imputed ED encounters to be also represented by inpatient encounters. We examined the variable in NIS that reports if an encounter has ED related billing codes and found 45.3% of our NIS encounters potential overlapped with the NEDS. This could result in overestimating of inpatient charges. In addition, our analysis relies on the accuracy of the diagnostic and procedure codes in the databases, and it is possible that at least some portion of our cohort may have been incorrectly coded.
Lastly, because NIS and NEDS represent encounter-based data rather than patient-based data, it is impossible to track a given patient across time. We could not assess any accrued charge estimation beyond each encounter, whether a couple of very comorbid patients drove up the charges, or whether patients may have been accounted for multiple times. However, since we focused on charges associated with SB-encounters and not with individual patients, we did not expect this to impact our results. A single patient admitted twice, or two patients who were each admitted once, would not change the total charges across all SB encounters.
Conclusion
Based on this inpatient and ER data, hospital charges for management of SB was estimated to be $2.04 billion in 2014 alone in contrast to $1.2 billion in 2006. This figure may be an under-estimate of the economic burden of SB, as it excludes non-ER outpatient SB management and societal costs.
Supplementary Material
Acknowledgments
Funding source
None.
Abbreviations
- CCR
Cost-to-charge ratio
- ED
Emergency Department
- HCUP
Healthcare Cost and Utilization Project
- ICD
International Classification of Disease
- NIS
Nationwide Inpatient Sample
- NEDS
Nationwide Emergency Department Sample
- SB
Spina bifida
- VWI
Van Walraven comorbidity index
Appendix 1.
Inflation points
| Year | Inflation Adjustment |
|---|---|
| 2006 | 4% |
| 2007 | 4.4% |
| 2008 | 3.7% |
| 2009 | 3.2% |
| 2010 | 3.4% |
| 2011 | 3% |
| 2012 | 3.7% |
| 2013 | 2.5% |
| 2014 | 2.4% |
Appendix 2.
Comparison of demographics between missing and complete charges
| Variable | Complete Charges (n = 290303) | Missing Charges (n = 4737) | Complete Charges (n = 335577) | Missing Charges (n = 94953) |
|---|---|---|---|---|
| Age | ||||
| Mean (95% CI) | 26.4 (23, 29.8) | 29 (28.6, 29.8) | 29.5 (29, 30) | 28.2 (26.6, 29.8) |
| Min, Max | 0, 90 | 0, 100 | 0, 100 | 0, 97 |
| Gender | ||||
| Female | 164689 (56.7%) | 352 (57.8%) | 193971 (57.8%) | 52460 (55.2%) |
| Missing | 213 (0.07%) | <1%* | 137 (0.04%) | |
| Insurance | ||||
| Public | 184449 (63.5%) | 1874 (39.6%) | 219722 (65.5%) | 65986 (69.5%) |
| Private | 86928 (29.9%) | 2424 (51.2%) | 82104 (24.5%) | 20108 (21.2%) |
| Other | 18528 (6.4%) | 426 (9%) | 33182 (9.9%) | 8807 (9.2%) |
| Missing | 398 (0.2%) | <1%* | 404 (0.1%) | 24 (0.1%) |
| Year | ||||
| 2006 | 30459 (10.5%) | 483 (10.2%) | 27638 (8.2%) | 10907 (11.5%) |
| 2007 | 30764 (10.6%) | 369 (7.8%) | 31375 (9.3%) | 11621 (12.2%) |
| 2008 | 31884 (11%) | 661 (14%) | 35824 (10.7%) | 12427 (13.1%) |
| 2009 | 33243 (11.4%) | 224 (4.7%) | 36420 (10.9%) | 10880 (11.5%) |
| 2010 | 34572 (11.9%) | 486 (10.3%) | 39848 (11.9%) | 9182 (9.7%) |
| 2011 | 32846 (11.3%) | 945 (20%) | 42034 (12.5%) | 8222 (8.7%) |
| 2012 | 32550 (11.2%) | 525 (11.1%) | 39575 (11.8%) | 10946 (11.5%) |
| 2013 | 31920 (11%) | 525 (11%) | 42383 (12.6%) | 9759 (10.3%) |
| 2014 | 32140 (11.1%) | 520 (11%) | 40481 (12.1%) | 11008 (11.6%) |
| Life Status | ||||
| Died | 3148 (1.1%) | 81 (1.7%) | ||
| Died in ED | 325 (0.1%) | 51 (0.05%) | ||
| Died in Hospital | 1361 (0.4%) | 644 (0.7%) | ||
| Missing | 124 (0.04%) | 1736 (0.5%) | 156 (0.2%) | |
| Van Walraven Score (VWS) | ||||
| ≤−1 | 35314 (12.2%) | 610 (12.9%) | 27199 (8.1%) | 8878 (9.4%) |
| 0 | 118079 (40.7%) | 2144 (45.3%) | 193765 (57.7%) | 47686 (50.2%) |
| 1 | 3532 (1.2%) | 79 (1.7%) | 2551 (0.8%) | 886 (0.9%) |
| 2 | 4274 (1.5%) | 57 (1.2%) | 3076 (0.9%) | 1153 (1.2%) |
| 3 | 19688 (6.8%) | 244 (5.1%) | 22070 (6.6%) | 5618 (5.9%) |
| 4 | 5127 (1.8%) | 55 (1.2%) | 3600 (1.1%) | 1178 (1.2%) |
| 5 | 20564 (7.1%) | 199 (4.2%) | 16549 (4.9%) | 5935 (6.3%) |
| ≥6 | 83802 (28.9%) | 1348 (28.5%) | 66768 (19.9%) | 23619 (24.9%) |
Appendix 3.
Sensitivity analysis in NIS
| Year | Real Charge Data Mean (95%CI) | Imputed Charge data Mean (95%CI) |
|---|---|---|
| Overall Charges (between 2006 and 2014) | 41210 (38128.84, 44290.50) | 41630 (38541.20, 44718.50) |
| 2006 | 25759 (21138.14, 30380.82) | 27310 (18626.74, 35992.79) |
| 2007 | 31250 (24406.30, 38092.83) | 31823 (22445.90, 41199.62) |
| 2008 | 38819 (29671.53, 47966.80) | 35545 (25526.05, 45563.63) |
| 2009 | 38378 (31047.26, 45709.01) | 44294 (35103.95, 53484.85) |
| 2010 | 43230 (32307.50, 54153.03) | 38488 (29508.96, 47467.53) |
| 2011 | 46660 (36326.50, 56992.96) | 41450 (32649.05, 50251.28) |
| 2012 | 51923 (38674.74, 65171.47) | 49837 (39879.50, 59793.97) |
| 2013 | 47844 (39231.47, 56455.96) | 55589 (44472.98, 66704.84) |
| 2014 | 48018 (39596.76, 56439.79) | 51396 (42689.28, 60103.16) |
Appendix 4.
Sensitivity analysis in NEDS
| Year | Real Charge Data Mean (95%CI) | Imputed Charge data Mean (95%CI) |
|---|---|---|
| Overall Charges (between 2006 and 2014) | 2461.27 (2280.74, 2641.80) | 2436.90 (2307.28, 2566.51) |
| 2006 | 1879.66 (1518.03, 2241.29) | 1578.36 (1162.59, 1994.13) |
| 2007 | 1704.60 (1395.94, 2013.26) | 1651.22 (1301.97, 2000.48) |
| 2008 | 2028.90 (1303.11, 2754.68) | 1966.93 (1567.04, 2366.81) |
| 2009 | 2126.84 (1746.29, 2507.39) | 2165.42 (1713.84, 2617.00) |
| 2010 | 2402.05 (2001.99, 2802.12) | 2449.99 (2078.52, 2821.47) |
| 2011 | 2127.03 (1777.14, 2476.92) | 2444.35 (2052.66, 2836.04) |
| 2012 | 2726.00 (2239.54, 3212.47) | 2760.22 (2378.27, 3142.16) |
| 2013 | 3085.19 (2551.83, 3618.56) | 3126.34 (2781.94, 3470.73) |
| 2014 | 3737.19 (2832.85, 4641.52) | 3361.06 (3008.41,3713.71) |
Appendix 5.
Complete case only means
| Inpatient Mean Charges |
ED Mean Charges |
|||||
|---|---|---|---|---|---|---|
| Mean | 95%CI | Mean | 95% CI | |||
| 2006 | $36,151 | $32868.09 | $39434.11 | $,1695.36 | $1547.18 | $1843.54 |
| 2007 | $39,461 | $36547.97 | $42374.77 | $1748.40 | $1627.77 | $1869.03 |
| 2008 | $41,013 | $36866.94 | $45159.90 | $2026.45 | $1843.45 | $2209.44 |
| 2009 | $45,261 | $41257.64 | $49264.21 | $2306.15 | $2123.54 | $2488.77 |
| 2010 | $44,319 | $40753.20 | $47884.15 | $2510.88 | $2310.81 | $2710.95 |
| 2011 | $46,172 | $42221.48 | $50123.50 | $2534.61 | $2351.46 | $2717.76 |
| 2012 | $53,049 | $49951.49 | $56145.90 | $2892.60 | $2713.63 | $3071.57 |
| 2013 | $55,753 | $52116.33 | $59389.00 | $3161.22 | $2931.72 | $3390.72 |
| 2014 | $56,841 | $53849.04 | $59833.82 | $3404.22 | $3201.45 | $3606.99 |
Footnotes
Conflicts of interests
None.
Disclosure
Third World Congress of Spina Bifida in San Diego, CA on March 16, 2017.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.dhjo.2019.01.007.
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