Lengths of Stay and Costs Associated With Children's Hospitals

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Lengths of Stay and Costs Associated With Children’s Hospitals

Dan Merenstein, MD*; Brian Egleston, MPP‡; and Marie Diener-West, PhD‡

ABSTRACT. Objective. Because of the unique mis-sion of freestanding children’s hospitals, higher costs have generally been accepted; however, increasing health care costs and the impetus for outcomes data demand more accountability. For common diagnoses, with respect to quality care indicators, length of stay (LOS), and total charges, we propose to compare freestanding children’s hospitals and other hospitals. Our hypothesis is that, for similar diagnoses, freestanding children hospitals will have longer LOSs and higher costs than other hospitals.

Methods. Data were analyzed from the Healthcare Cost and Utilization Project Kids’ Inpatient Database 2000. Encounters qualified for evaluation when 1 of the top 3 discharge codes was consistent with pneumonia, gastroenteritis, respiratory syncytial virus, dehydration, or asthma. Our outcomes were LOS and total charges per hospital admission; hospitals were categorized as chil-dren’s hospitals and nonchilchil-dren’s hospitals. We ad-justed for the following potential confounders: number of diagnoses, insurance information, patient age in years, race of patient, admission source, procedures, teaching status of hospital, and hospital location. Because of the right skew of the outcomes, our primary analyses con-sisted of robust median regression; to support our final models, we also performed sensitivity analyses.

Results. Of 252 262 total inpatient encounters, 24 322 met the inclusion criteria. There were 3408 encounters from 23 different freestanding children’s hospitals and 20 914 encounters from 1749 nonchildren’s hospitals. Freestanding children’s hospitals provided care to a higher risk population with more children transferred from other hospitals, a higher percentage of minorities, increased number of co-diagnoses, and a higher percent-age on Medicaid. There was no statistically significant difference in LOS by hospital type. However, there was a significant difference in total costs, with the median cost of an admission at freestanding children’s hospitals $1294 more per hospitalization than at nonchildren’s hos-pitals, after adjusting for confounders.

Conclusion. We found no significant difference in median LOS among freestanding children’s hospitals and nonchildren’s hospitals, but freestanding children’s hospitals had higher total charges per admission, even after adjusting for differences in population characteris-tics. Additional studies are needed to elucidate whether these increased costs result in better health outcomes or are simply attributable to other characteristics of

chil-dren’s hospitals, in which not all patients may benefit.

Pediatrics 2005;115:839–844;hospital performance, length of stay.

ABBREVIATIONS. NACHRI, National Association of Children’s Hospitals and Related Institutions; HCUP, Healthcare Cost and Utilization Project; The KID, Kids’ Inpatient Database 2000; AHRQ, Agency for Healthcare Research and Quality; ICD-9-CM,

International Classification of Diseases, Ninth Revision, Clinical Mod-ifications; CI, confidence interval.

T

he National Association of Children’s Hospi-tals and Related Institutions (NACHRI) has cited that “all children need children’s hospi-tals.”1 _{For some patients and certain procedures,}

such as subspecialty surgery, special-needs children, oncology regimens, and rare problems, hospitals with higher volumes, which are generally freestand-ing children’s hospitals, are likely much better equipped than other hospitals.2–6_{However, for more}

common admissions such as asthma, dehydration, pneumonia, and diarrhea, it is not known whether children’s hospitals are superior to other hospitals in providing care. Recently there has been an impetus, from both the private sector and the government, for hospitals to provide data on length of stay (LOS), total charges, and other patient outcomes to facilitate evidence-based or quality-of-care decisions with re-gard to which hospitals truly provide superior care.7,8

Advocates of children’s hospitals claim that access to more subspecialists, laboratories, radiology equip-ment, and ancillary services that are designed for children, coupled with the general composition of children’s hospitals, makes them more appropriate places for children to be treated. With adults, it has been shown that access to more subspecialty-ori-ented care results in higher costs, move invasive procedures, and more tests but does not guarantee improved outcomes.9–11_{Similarly, it is possible that}

children’s hospitals may feel obliged to order more computed topography scans or keep children in the ICU longer for conditions such as asthma and pneu-monia; although more readily available, these prac-tices may not improve care. One recent study dem-onstrated that ventilated children who were treated outside the ICU faired just as well, in cost and clinical outcome, as those who were treated inside the ICU.12

In 2000, children’s hospital admissions accounted for 18% of the total US admissions, ⬃6.3 million visits.13 _{Although freestanding children’s hospitals}

comprise only 1% of all US hospitals, they account for 39% of child admissions, 49% of inpatient days, From the *Johns Hopkins School of Medicine, Baltimore, Maryland; and

‡Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

Accepted for publication Sep 1, 2004. doi:10.1542/peds.2004-1622 No conflict of interest declared.

Address correspondence to Dan Merenstein, MD, Johns Hopkins Hospital, 600 N Wolfe St, Carnegie 291, Baltimore, MD 21287. E-mail: dmerenstein@ jhu.edu

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and 59% of costs at $10 billion a year.1_{In addition,}

governmental funding for general medical education at children’s hospitals rose from $38 million in 2000 to $221 million in 2001.14_{These high societal costs, in}

both patient care and dollars, exemplify the impor-tance that freestanding children’s hospitals play in our health care system.

We propose to compare children’s care in free-standing children’s hospitals with that of other hos-pitals, which treat children with common diagnoses, with respect to LOS and total charges. Our hypoth-esis is that children with similar diagnoses at free-standing children’s hospitals will have longer LOSs and higher costs than children at other hospitals.

METHODS

Data on patient encounters were analyzed from the Healthcare Cost and Utilization Project (HCUP) Kids’ Inpatient Database 2000 (The KID).15_{The KID is a hospital administrative data set,} spon-sored by the Agency for Healthcare Research and Quality (AHRQ) in partnership with state data organizations, that includes hospital discharge abstracts on⬎2.5 million hospitalizations from 27 re-gionally diverse states in individuals younger than 20 years, dur-ing 2000. Institutional Review Board exemption was obtained from the Johns Hopkins Bloomberg School of Public Health before analyses.

All diagnoses were selected using theInternational Classification of Diseases, Ninth Revision, Clinical Modifications(ICD-9-CM). Our inclusion criteria were all diagnosis of pneumonia, ICD-9-CM codes 480 to 486, gastroenteritis 558.9 or 009, respiratory syncytial virus 079, dehydration 276.5, and asthma 493. Patient records were included when any of these diagnoses were coded as the primary or secondary reason for the hospitalization.

In The KID data set, each hospital is categorized as a nonchil-dren’s hospital, chilnonchil-dren’s general hospital, chilnonchil-dren’s specialty hospital, or children’s unit in a general hospital, as defined by NACHRI. We excluded the last category to allow a comparison of freestanding children’s hospitals (either children’s general hospi-tal or children’s specialty hospihospi-tal) versus nonchildren’s hospihospi-tals. However, as expected as a result of our ICD-9-CM inclusion criteria, no children’s specialty hospitals were included in the analysis.

Our dependent variables were LOS and total charges. LOS was measured in days; a value of 0 was possible when a child was discharged on the same day as admission. Total charges were measured in US dollars.

Statistical Analysis

All statistical analysis was conducted using Stata 8.2 statistical software.16_{Because The KID is not a random sample of states, all} of our primary analyses were performed using the HCUP sample weights, enabling us to produce national estimates. Because total charge data for the state of Texas were available for only half of the year, total charge-weighted data do not include Texas. Multiple encounters per child were possible but not distinguishable in the data set.

Initially, basic descriptive statistics were used to compare the characteristics of children in the 2 groups, children’s hospitals and nonchildren’s hospitals. To compare baseline characteristics be-tween the 2 types of hospital groups, we used pairedttests for continuous variables and the␹2_{statistic for ordinal variables.}

The potential confounders included number of diagnoses, in-surance type, patient age in years, race of patient, admission source, performance of procedure, teaching status of hospital, and hospital location. The number of diagnoses was provided as a continuous variable, taking values 1 to 25; however, 90% of the encounters were associated with 5 or fewer diagnoses. We cate-gorized this variable as 1, 2, 3, 4, and 5 or more diagnoses; 1 diagnosis served as the reference group. Insurance information was categorized, with Medicaid as the reference group. Age was recorded in years, and ages for patients who were younger than 1 year were converted to fractions; for example, a 6-month-old was considered 0.5 years. Race was examined as white, black, His-panic, and other, which included Asians, Pacific Islanders, and

Native Americans. Admission source was categorized with the emergency department as the reference category. Nonteaching hospitals were the reference group for the dichotomous variable of teaching status. Location of hospital was a dichotomous variable, with rural as the reference category. When total charges were examined, LOS was also used as a continuous variable. In addi-tion, variance inflation factors were obtained to check for multi-collinearity between variables.

Bivariate relationships between the outcomes and covariates with hospital type were explored using ordinary least squares linear regression analysis. Both of the outcome variables LOS and total charges were extremely skewed to the right, and Shapiro-Wilk tests confirmed that these variables were not normally dis-tributed. Differences in outcomes by bivariate analyses were as-sessed using nonparametric tests (Wilcoxon rank sum and Kruskal-Wallis tests). Median regression analyses were performed for multivariable analyses to attenuate the influence of outliers on results.17 _{In addition, we bootstrapped our models to provide} more accurate estimated SDs and confidence intervals (CIs). To check the performance of our models, we ran different sensitivity analyses: logistic regression, robust bootstrap logistic regression, multiple linear regression using log LOS, and multiple linear regression using log total charges.16_{Analyses were also repeated} after deleting total charges⬎$100 000, $14 077, and $7466, respec-tively, and categorizing age using different cutoffs. Finally, to assess whether there was clustering among hospitals, we fit a random effects model, using generalized estimating equations with a uniform working correlation matrix.18

Because of the large number of encounters, we analyzed a simple random sample of 10% of the visits, leaving us with 252 262 inpatient encounters. To generate a subsample of the data set, we randomly assigned to each study participant a number between 0 and 1 generated from a uniform distribution. We excluded from this study all participants whose numbers were⬎0.10. The statis-tics presented in this article were estimated using cases with complete covariate data. None of the covariates had⬎3% missing values, with the exception of age (9%).

RESULTS

There are⬎2.5 million inpatient visits in The KID 2000. After applying our inclusion criteria, we had 24 322 encounters with complete LOS data and 21 366 encounters with complete total charges data. In these totals, 119 encounters were excluded from hospitals that were also coded as both nonteaching hospitals and freestanding children’s hospitals. Al-though it is possible that such hospitals exist, they are contrary to expectation and have very different characteristics from the majority of children’s hospi-tals in our analysis. We also excluded 1 encounter from the total charge analysis, as it seemed to be an error that resulted in an exorbitant cost for an ex-tremely short LOS with no reasonable explanation. In multivariable analyses, numbers of encounters varied slightly, because complete data were not available for all covariates.

General Characteristics

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Covariates

We investigated multiple variables for case-mix adjustment. Children’s hospitals had a much higher percentage of patients with 5 or more diagnoses (16%) as compared with nonchildren’s hospitals (7%). Another measure that suggested that children’s hospitals are taking care of much sicker children is the transfer rate from other hospitals: 7% for chil-dren’s hospitals versus 1% for nonchilchil-dren’s hospi-tals. In addition, children’s hospitals took care of a much higher percentage of minorities (62%) than nonchildren’s hospitals (48%) as well as a higher percentage of patients with Medicaid (46%) than nonchildren’s hospitals (41%). These data support the assumption that children’s hospitals have a much sicker patient population than do nonchildren’s hos-pitals. In addition, visits to children’s hospitals re-sulted in more procedures being performed per visit, with an average of 34% of the visits having at least 1 procedure in children’s hospitals compared with 17% in nonchildren’s hospitals.

It is not possible to adjust for hospital location or teaching status of hospital, because as shown in Ta-ble 1, all-freestanding children’s hospitals had 100% teaching status and urban location. Unadjusted

dif-ferences in total charges by hospital type for all co-variates are shown in Table 2.

LOS

Table 3 depicts the wide variation and right skew in the distribution of LOS by hospital type. Unad-justed mean (median) LOS for children’s hospitals was 4.03 (2.0) as compared with 2.82 (2.0) for non-children’s hospitals. In non-children’s hospitals, 90% of encounters were⬍8 days; 60 visits were longer than 20 days. Similarly, in nonchildren’s hospitals, 90% of encounters were⬍5 days; 109 visits were longer than 20 days.

Both unadjusted and adjusted median regression analyses for LOS were performed. Even after adjust-ment for confounders, there was no clinically signif-icant difference in the median LOS between hospital types. Because days were reported only as integers, rather than fractions of days, the adjusted difference in median LOS for most of the covariates, as well as their associated 95% CIs, were estimated at ⬃0, as a result of the large sample size. After adjusting for hospital type, insurance status, patient age, patient race, and admission source, the only statistically sig-nificant differences in median LOS were observed TABLE 1. Distribution of Patient and Hospital Characteristics by Hospital Type*

Characteristic Children’s Hospitals Nonchildren’s Hospitals

n % n %

Insurance status

Medicaid 1826 46.5 8346 40.9

Private

Insurance 1885 48.0 10 264 50.3

Self-pay 106 2.7 1071 5.2

Other† 112 2.8 711 3.5

Race

White 1305 38.3 10 841 51.8

Black 829 24.3 3623 17.3

Hispanic 997 29.2 5005 23.9

Other‡ 277 8.1 1448 6.9

Admission source

Emergency department 2377 61.9 9889 50.0

Another hospital 274 7.1 268 1.4

Another health facility 31 0.8 146 0.7

Other§ 1161 30.2 9388 47.7

Hospital location

Urban 3929 100 15 591 76.4

Rural 0 4802 23.6

Teaching status

Teaching 3929 100 6602 32.4

Nonteaching 0 0 13 791 67.6

Age

6 mo or less 335 8.5 1968 9.6

3 y or less 1915 48.8 9959 48.8

10 y or more 1123 28.6 6646 32.6

Procedures储 1354 34.5 3427 16.8

No. of diagnoses

1 744 18.9 3666 18.0

2 1151 29.3 7248 35.5

3 888 22.6 5432 26.6

4 516 13.2 2712 13.3

5 or more 630 16.0 1335 6.6

Total no. of encounters 3408 20 914

* Total numbers differ per characteristic as a result of missing data. † Medicare, no charge, and other.

‡ Asian, Pacific Islander, Native American, or other. § Routine birth, court, and outpatient facility.

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when comparing encounters with 1 or more proce-dures versus none (increase in LOS of 1 day in free-standing children’s hospitals) or encounters with 5 or more diagnoses versus 1 diagnosis (increase of LOS of 2 days in freestanding children’s hospitals).

Numerous sensitivity analyses were performed to support the conclusion from our final model. Be-cause 50% of the encounters were 2 days or less, we dichotomized LOS as ⬎2 days and 2 days or less.

Multiple logistic regression analysis indicated that the estimated adjusted odds of a longer LOS were 3% higher in children’s hospitals but not statistically significant (95% CI: 0.95–1.13; P ⫽ .451). Multiple linear regression analysis of the log LOS resulted in an adjusted coefficient of 0.05 (95% CI: 0.023– 0.079;P

⬍.0001). Nonweighted bootstrap median regression resulted in similar findings to our weighted median regression results. Using generalized estimating TABLE 2. Adjusted Versus Unadjusted Differences in Median Total Charges, in Dollars

Unadjusted Difference in Total Charges, 95% CI

Adjusted* Difference in Total Charges, 95% CI

Hospital type

Nonchildren’s hospital Reference Reference

Children’s hospital 2199 (2020 to 2377) 1294 (1181 to 1408)

LOS

Per day 2113 (2102 to 2123) 1952 (1942 to 1963)

Insurance status

Medicare Reference Reference

Private

Insurance ⫺21 (⫺358 to 316) 409 (178 to 640)

Self-pay ⫺558 (⫺682 to⫺433) 213 (122 to 304)

Other† 35 (⫺254 to 325) 260 (60 to 460)

Race

White Reference Reference

Black 1147 (991 to 1303) 266 (152 to 380)

Hispanic 2193 (2044 to 2342) 1176 (1068 to 1284)

Other‡ 1238 (1004 to 1471) 478 (317 to 639)

Admission source

Emergency department Reference Reference

Another hospital 1671 (1257 to 2084) 448 (163 to 734)

Another health facility ⫺1311 (⫺1942 to⫺680) ⫺472 (⫺899 to⫺45)

Other§ ⫺1093 (⫺1217 to⫺968) ⫺696 (⫺785 to 608)

Hospital location

Rural Reference Reference

Urban 1814 (1654 to 1973) –

Teaching status

Nonteaching Reference Reference

Teaching 1399 (1280 to 1518) –

Age

Per year 88 (77 to 98) 42 (35 to 49)

Procedures

0 Reference Reference

1 or more 4045 (3911 to 4179) 1511 (1406 to 1616)

No. of diagnoses

1 Reference Reference

2 ⫺561 (⫺738 to⫺384) ⫺112 (⫺230 to 7)

3 ⫺256 (⫺444 to⫺68) ⫺150 (⫺277 to⫺24)

4 481 (253 to 709) ⫺56 (⫺210 to 98)

5 6282 (6019 to 6545) 1203 (1018 to 1389)

* For hospital type, LOS, insurance status, race, admission source, age in years, procedures, and diagnoses. † Medicare, no charge, and other.

‡ Asian, Pacific Islander, Native American, or other. § Routine birth, court, and outpatient facility.

TABLE 3. Distribution of LOS and Total Charges by Hospital Type

Children’s Hospitals

Nonchildren’s Hospitals

LOS, d

Mean (SD) 4.03 (6.20) 2.82 (3.35)

Median 2 2

Range 0–106 0–131

Interquartile range (25th–75th percentiles) 2–4 1–3

Total no. of encounters 3408 20 914

Total charges, $

Mean (SD) 12 952 (25 909) 6476 (15 973)

Median 5843 3644

Range 904–368 227 26–879 156

Interquartile range (25th–75th percentiles) 3471–11 692 2212–6351

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equations to adjust for potential correlation of out-comes within hospitals showed a statistically signif-icant but small increase in LOS of 0.51 days for children’s hospitals (95% CI: 0.20 – 0.83; P ⫽ .001). The last 2 procedures could not be performed incor-porating the sample weights. However, the results of our weighted and unweighted analyses seemed ro-bust. Thus, each of these analyses provided little evidence of a clinically significant difference in LOS by hospital type.

Total Charges

Table 3 also displays the distribution of total charges by hospital type. Unadjusted mean (median) total charges in children’s hospitals were $12 952 ($5843), whereas they were $6476 ($3644) in nonchil-dren’s hospitals. For chilnonchil-dren’s hospitals, 90% of total charges were⬍$27 000; however, 44 encounters had charges⬎$100 000. For nonchildren’s hospitals, 90% of encounters were ⬍$13 000; however, 67 encoun-ters had costs⬎$100 000.

Table 2 displays both the unadjusted and adjusted differences in median total charges by hospital type and patient characteristics. Higher total charges were associated with increased LOS, Medicare insurance status, minority race, transfer from another hospital, urban location, teaching hospitals, increased age of patient, 1 or more procedure, and 4 or 5 diagnoses. The unadjusted median total charges for children’s hospitals were $2199 more than nonchildren’s hospi-tals. After adjustment for LOS and statistically sig-nificant confounders, the difference in median total charges decreased to $1294 (95% CI: $1181–$1408;P

⬍ .0001; Table 2).

Additional sensitivity analyses were performed to confirm our results. A multiple linear regression analysis of the log total charges yielded a statistically significant difference by hospital type (adjusted dif-ference⫽0.25; 95% CI: 0.23– 0.28;P⬍.0001). We also repeated the regression analysis after excluding out-liers defined as total charges ⬎$100 000, and the results remained robust. As additional sensitivity analyses, we performed the analysis excluding the top 10th percentile (⬎$14 077) and 25th percentile (⬎$7466) of total charges, respectively; the differ-ences remained statistically significant, although slightly decreasing in magnitude. Thus, each of these analyses revealed statistically significantly higher to-tal charges observed in the children’s hospito-tals.

DISCUSSION

To evaluate indirect indicators of quality of care provided to children who are admitted to the hospi-tal, we compared encounters in children’s hospitals versus nonchildren’s hospitals with respect to LOS and total charges for common admission diagnoses: pneumonia, gastroenteritis, respiratory syncytial vi-rus, dehydration, and asthma. Although our findings are not similar for LOS and total charges, the differ-ences by hospital type were not as large as we had anticipated. We did not find clinically important dif-ferences in adjusted LOS between freestanding chil-dren’s hospitals and nonchilchil-dren’s hospitals.

How-ever, there was an adjusted increase in median total charges in children’s hospitals of $1294.

Previous studies have found differing results, some showing an increase in LOS among teaching hospitals versus nonteaching hospitals, whereas oth-ers have found similar LOS among hospital types.19–21 _{Although our hypothesis regarding}

in-creased LOS in children’s hospitals could not be supported, we believe that our study provides a more definitive answer when examining freestand-ing children’s hospitals and nonchildren’s hospitals with respect to LOS. Our study has the advantage of national scope, ability to case-adjust for multiple fac-tors, weighted data, and a very large sample size. In addition, we performed multiple different sensitivity analyses under varying assumptions, and no mean-ingful differences in LOS were observed by hospital type.

Alternatively, our other hypothesis was supported in that total charges were statistically significantly higher among freestanding children’s hospitals than nonchildren’s hospitals. This is consistent with pre-vious observations regarding total charges for adult patients who were admitted to tertiary hospitals.22

We postulated that total charges would increase in children’s hospitals because subspecialists, with ad-ditional technology more readily available, likely contributed to more of the care. In fact, in our anal-yses, 34% of encounters at children’s hospitals had at least 1 procedure performed compared with 17% in nonchildren’s hospitals. However, these greater costs and increased procedures fortunately did not result in longer LOS for children who were admitted to freestanding children’s hospitals.

An important caveat to our results is that although we tested very important outcomes, LOS and total charges, data on direct health outcomes were not available. Thus, it is possible that these additional tests and costs resulted in lower readmission rates, better patient and caregiver education, and overall improved health. One study of childbirth demon-strated superior outcomes at academic centers with higher costs.23_{In addition, we were unable to}

exam-ine whether the nurse-to-patient ratio was higher at freestanding children’s hospitals; this has been shown to improve patient outcomes and might also explain the higher costs.24,25 _{For this investigation,}

we chose common, generally benign conditions. If the increased costs in children’s hospitals resulted in better care, then that is commendable, but if they simply resulted in more tests and procedures, then freestanding children’s hospitals must examine the care that they provide.

Our analysis is based on coding of selected ICD-9-CM codes. There are clear limitations to the accu-racy of this type of data collection, but the profes-sional coding used by The KID strengthens our investigation.26–29 _{Also, we used multiple variables}

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it is available only for adult patients; in addition, NACHRI’s case-mix adjustment is not publicly avail-able.1,30–32_{Finally costs and charges are not identical,}

with costs generally near 50% of actual charges. Cur-rently, formulas are being developed by AHRQ to provide better estimates of total costs and collections. A senior economist at AHRQ told us that, in general, freestanding children’s hospital’s costs are roughly 42% whereas other hospitals are 46% on the dollar (C. Steiner, MD, MPH, written communication, June 2004). This does not affect the LOS data; furthermore, the differences in total charges are large enough to remain robust.

We have demonstrated that on at least 1 important indicator of quality of care, LOS, freestanding chil-dren’s hospitals are on par with nonchilchil-dren’s hos-pitals. What is most striking is that they are clearly providing care to a more vulnerable population, with much higher percentages of patients who qualify as minorities, more patients transferred from other hos-pitals, patients with more diagnoses, and more Med-icaid patients. Although the increased total charges for freestanding children’s hospitals need additional examination, it is possible that these increased costs result in better health outcomes and reduced costs in the long term. These associations must be under-stood before market forces, patients, physicians, and insurers make uninformed decisions for themselves.

ACKNOWLEDGMENT

We thank Claudia Steiner, MD, MPH, for thoughtful input in reviewing the manuscript.

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DOI: 10.1542/peds.2004-1622

2005;115;839

Pediatrics

Dan Merenstein, Brian Egleston and Marie Diener-West