Women's prepregnancy underweight as a risk factor for preterm birth: a retrospective study

OBJECTIVE

To investigate the distribution of known factors for preterm birth (PTB) by severity of maternal underweight; to investigate the risk-adjusted relation between severity of underweight and PTB, and to assess whether the relation differed by gestational age.

DESIGN

Retrospective cohort study.

SETTING

State of California, USA.

METHODS

Maternally linked hospital and birth certificate records of 950 356 California deliveries in 2007-2010 were analysed. Singleton live births of women whose prepregnancy body mass index (BMI) was underweight (<18.5 kg/m² ) or normal (18.50-24.99 kg/m² ) were analysed. Underweight BMI was further categorised as: severe (<16.00), moderate (16.00-16.99) or mild (17.00-18.49). PTB was grouped as 22-27, 28-31, 32-36 or <37 weeks (compared with 37-41 weeks). Adjusted multivariable Poisson regression modeling was used to estimate relative risk for PTB.

MAIN OUTCOME MEASURES

Risk of PTB.

RESULTS

About 72 686 (7.6%) women were underweight. Increasing severity of underweight was associated with increasing percent PTB: 7.8% (n = 4421) in mild, 9.0% (n = 1001) in moderate and 10.2% (475) in severe underweight. The adjusted relative risk of PTB also significantly increased: adjusted relative risk (aRR) = 1.22 (95% CI 1.19-1.26) in mild, aRR = 1.41 (95% CI 1.32-1.50) in moderate and aRR = 1.61 (95% CI 1.47-1.76) in severe underweight. These findings were similar in spontaneous PTB, medically indicated PTB, and the gestational age groupings.

CONCLUSION

Increasing severity of maternal prepregnancy underweight BMI was associated with increasing risk-adjusted PTB at <37 weeks. This increasing risk was of similar magnitude in spontaneous and medically indicated births and in preterm delivery at 28-31 and at 32-36 weeks of gestation.

TWEETABLE ABSTRACT

Increasing severity of maternal underweight BMI was associated with increasing risk of preterm birth.

Examining the effect of hospital-level factors on mortality of very low birth weight infants using multilevel modeling

OBJECTIVE

The objective of this study was to examine the effect of hospital-level factors on mortality of very low birth weight infants using multilevel modeling.

STUDY DESIGN

This is a secondary data analysis of California maternal-infant hospital discharge data from 1997 to 2002. The study population was limited to singleton, non-anomalous, very low birth weight infants, who delivered in hospitals providing neonatal intensive care services (level-2 and higher). Hierarchical generalized linear modeling, also known as multilevel modeling, was used to adjust for individual-level confounders.

RESULT

In a multilevel model, increasing hospital volume of very low birth weight deliveries was associated with lower odds of very low birth weight mortality. Characteristics of a particular hospital's obstetrical and neonatal services (the presence of residency and fellowship training programs and the availability of perinatal and neonatal services) had no independent effect.

CONCLUSION

Using multilevel modeling, hospital volume of very low birth weight deliveries appears to be the primary driver of reduced mortality among very low birth weight infants.

Predictors of medical service utilization among individuals with co-occurring HIV infection and substance abuse disorders

This study examined factors affecting medical service use among HIV-infected persons with a substance abuse disorder. The sample comprised 190 participants enrolled in a randomized trial of a case management intervention. Participants were interviewed about their backgrounds, housing status, income, alcohol and drug use problems, health status and depressive symptoms at study entry. Electronic medical records were used to assess medical service use. Poisson regression models were tested to determine the effects of need, enabling and predisposing factors on the dependent variables of emergency department visits, inpatient admissions and ambulatory care visits. During a two-year period, 71% were treated in the emergency department, 64% had been hospitalized and the sample averaged 12.9 ambulatory care visits. Homelessness was associated with higher utilization of emergency department and inpatient services; drug use severity was associated with higher inpatient and ambulatory care service use; and alcohol use severity was associated with greater use of emergency medical services. Homelessness and substance abuse exacerbate the health care needs of HIV-infected persons and result in increased use of emergency department and inpatient services. Interventions are needed that target HIV-infected persons with substance abuse disorders, particularly those that increase entry and retention in outpatient health care and thus decrease reliance on acute hospital-based services.

Is travel distance a barrier to veterans' use of VA hospitals for medical surgical care?

Lengthy travel distances may explain why relatively few veterans in the United States use VA hospitals for inpatient medical/surgical care. We used two approaches to distinguish the effect of distance on VA use from other factors such as access to alternatives and veterans' characteristics. The first approach describes how disparities in travel distance to the VA are related to other characteristics of geographic areas. The second approach involved a multivariate analysis of VA use in postal zip code areas (ZCAs). We used several sources of data to estimate the number of veterans who had priority access to the VA so that use rates could be estimated. Access to hospitals was characterized by estimated travel distance to inpatient providers that typically serve each ZCA. The results demonstrate that travel distance to the VA is variable, with veterans in rural areas traveling much farther for VA care than veterans in areas of high population density. However, Medicare recipients also travel farther in areas of low population density. In some areas veterans must travel lengthy distances for VA care because VA hospitals which were built over the past few decades are not located close to areas in which veterans reside in the 1990s. The disparities in travel distance suggest inequitable access to the VA. Use of the VA decreases with increases in travel distance only up to about 15 miles, after which use is relatively insensitive to further increases in distance. The multivariate analyses indicate that those over 65 are less sensitive to distance than younger veterans, even though those over 65 are Medicare eligible and therefore have inexpensive access to alternatives. The results suggest that proximity to a VA hospital is only one of many factors determining VA use. Further research is indicated to develop an appropriate response to the needs of the small but apparently dedicated group of VA users who are traveling very long distances to obtain VA care.

Short-term health and economic benefits of smoking cessation: low birth weight

OBJECTIVES

To estimate excess direct medical costs of low birth weight from maternal smoking and short-term cost savings from smoking cessation programs before or during the first trimester of pregnancy.

METHODS

Simulations using data on neonatal costs per live birth. Outcome measures are mean US excess direct medical cost per live birth, total excess direct medical cost, reductions in low birth weight, and savings in medical costs from an annual 1 percentage point drop in smoking prevalence among pregnant women.

RESULTS

Mean average excess direct medical cost per live birth for each pregnant smoker (in 1995 dollars) was $511; total cost was $263 million. An annual drop of 1 percentage point in smoking prevalence would prevent 1300 low birth weight live births and save $21 million in direct medical costs in the first year of the program; it would prevent 57,200 low birth weight infants and save $572 million in direct medical costs in 7 years.

CONCLUSIONS

Smoking cessation before the end of the first trimester produces significant cost savings from the prevention of low birth weight.

The hospital cost of congenital syphilis

OBJECTIVE

To determine the hospital cost of caring for newborn infants with congenital syphilis.

STUDY POPULATION

All live-born singleton neonates with birth weight greater than 500 gm at an inner-city municipal hospital in New York City in 1989.

METHODS

We compared the characteristics of 114 infants with case-compatible congenital syphilis with those of 2906 infants without syphilis. Cost estimates were based on New York State newborn diagnosis-related groups (DRG) reimbursements adjusted for length of stay, birth weight, preterm delivery, and selected maternal risk factors, including infection with the human immunodeficiency virus, cocaine use during pregnancy, and history of injected drug use.

RESULTS

For infants with congenital syphilis, the unadjusted mean cost ($11,031) and the median cost ($4961) were more than three times larger than those for infants without syphilis (p < 0.01). After adjustment, congenital syphilis was associated with an additional length of hospitalization of 7 1/2 days and an additional cost of $4690 (both p < 0.01) above mean study population values (7.13 days, $3473).

CONCLUSIONS

Based on the number of reported cases (1991 to 1994), the average annual national cost of treating infants with congenital syphilis is approximately $18.4 million (1995 dollars). This estimate provides a benchmark to assess the cost-effectiveness of strategies to prevent, diagnose, and treat the disease.

Does case mix matter for substance abuse treatment? A comparison of observed and case mix-adjusted readmission rates for inpatient substance abuse treatment in the Department of Veterans Affairs

OBJECTIVE

To develop a case mix model for inpatient substance abuse treatment to assess the effect of case mix on readmission across Veterans Affairs Medical Centers (VAMCs).

DATA SOURCES/STUDY SETTING

The computerized patient records from the 116 VAMCs with inpatient substance abuse treatment programs between 1987 and 1992.

STUDY DESIGN

Logistic regression was used on patient data to model the effect of demographic, psychiatric, medical, and substance abuse factors on readmission to VAMCs for substance abuse treatment within six months of discharge. The model predictions were aggregated for each VAMC to produce an expected number of readmissions. The observed number of readmissions for each VAMC was divided by its expected number to create a measure of facility performance. Confidence intervals and rankings were used to examine how case mix adjustment changed relative performance among VAMCs.

DATA COLLECTION/EXTRACTION METHODS

Ward where care was provided and ICD-9-CM diagnosis codes were used to identify patients receiving treatment for substance abuse (N = 313,886).

PRINCIPAL FINDINGS

The case mix model explains 36 percent of the observed facility level variation in readmission. Over half of the VAMCs had numbers of readmissions that were significantly different than expected. There were also noticeable differences between the rankings based on actual and case mix-adjusted readmissions.

CONCLUSIONS

Secondary data can be used to build a reasonably stable case mix model for substance abuse treatment that will identify meaningful variation across facilities. Further, case mix has a large effect on facility level readmission rates for substance abuse treatment. Uncontrolled facility comparisons can be misleading. Case mix models are potentially useful for quality assurance efforts.

The effects of patient volume and level of care at the hospital of birth on neonatal mortality

OBJECTIVE

To examine the effects of neonatal intensive care unit (NICU) patient volume and the level of NICU care available at the hospital of birth on neonatal mortality.

DESIGN

Birth certificate data linked to infant death certificates and to infant discharge abstracts were used in a logistic regression model to control for differences in each patient's clinical and demographic risks. Hospitals were classified by the level of NICU care available (no NICU: level I; intermediate NICU: level II; expanded intermediate NICU: level II+: tertiary NICU: level III) and by the average patient census in the NICU.

SETTING

All nonfederal hospitals in California with maternity services.

PATIENTS

All births in nonfederal hospitals in California in 1990 (N=594104), 473209 (singletons only) of which were successfully linked with discharge abstracts. Of these infants, 53229 were classified as likely NICU admissions.

MAIN OUTCOME MEASURES

Death within the first 28 days of life, or within the first year of life, if continuously hospitalized.

RESULTS

Patient volume and level of NICU care at the hospital of birth both had significant effects on mortality. Compared with hospitals without an NICU, infants born in a hospital with a level III NICU with an average NICU census of at least 15 patients per day had significantly lower risk-adjusted neonatal mortality (odds ratio, 0.62; 95% confidence interval, 0.47-0.82; P=.002). Risk-adjusted neonatal mortality for infants born in smaller level III NICUs, and in level II+ and level II NICUs, regardless of size, was not significantly different from hospitals without an NICU, and was significantly higher than hospitals with large level III NICUS.

CONCLUSIONS

Risk-adjusted neonatal mortality was significantly lower for births that occurred in hospitals with large (average census, >15 patients per day) level III NICUs. Despite the differences in outcomes, costs for the birth of infants born at hospitals with large level III NICUs were not more than those for infants born at other hospitals with NICUs. Concentration of high-risk deliveries in urban areas in a smaller number of hospitals that could provide level III NICU care has the potential to decrease neonatal mortality without increasing costs.

Correlation of travel time on roads versus straight line distance

Studies of hospital demand and choice of hospital have used straight line distance from a patient's home to hospitals as a measure of geographic access, but there is the potential for bias if straight line distance does not accurately reflect travel time. Travel times for unimpeded travel between major intersections in upstate New York were compared with distances between these points. The correlation between distance and travel time was 0.987 for all observations and 0.826 for distances less than 15 miles. These very high correlations indicate that straight line distance is a reasonable proxy for travel time in most hospital demand or choice models, especially those with large numbers of hospitals. The authors' outlier analyses show some exceptions, however, so this relationship may not hold for studies focusing on specific hospitals, very small numbers of hospitals, or studies in dense urban areas with high congestion and reliance on surface streets.

Inpatient treatment for substance abuse patients with psychiatric disorders: a national study of determinants of readmission

This study examined the patient case mix and program determinants of 6-month readmission rates and early treatment dropout for 7,711 VA inpatients with both substance abuse and major psychiatric disorders treated in one of 104 substance abuse programs. Patients were treated in one of three types of inpatient programs: explicitly designed dual diagnosis specialty programs, substance abuse programs with a dual diagnosis psychotherapy group or standard substance abuse programs. Dual diagnosis specialty programs differed from regular substance abuse programs in that they had a more severe case mix, a higher 180-day readmission rate, greater dual diagnosis treatment orientation, used more psychotropic medication, had longer lengths of stay, had greater tolerance of relapse and medication noncompliance, and a higher rate of psychiatric aftercare in the 30 days after discharged. Programs with less severe case mix, longer intended and actual length of stay, lower 7-day dropout rates, greater tolerance of problem behavior, 12-step groups, and higher immediate postdischarge utilization of outpatient mental health treatment lower 180-day readmission rates. Programs with less severe patient case mix, more use of psychotropic medications but less of methadone and antabuse, less varied and diverse treatment activities, and low use of patient-led groups had lower dropout rates.

Determinants of readmission following inpatient substance abuse treatment: a national study of VA programs

This study examines program determinants of one aspect of VA inpatient substance abuse treatment program performance. Performance was measured by the ratio of a program's readmission rate to the expected rate for programs with similar patients. Six-month readmission rates in 101 VA treatment programs were analyzed. Preliminary analyses indicated that patient differences across programs accounted for 36% of the variance in readmission rates. Program differences accounted for 47% of the variance in case-mix-adjusted readmission rate. Among program factors selected through a literature review, better than expected readmission performance was associated with having fewer early discharges, a longer intended treatment duration, more patient participation in aftercare, more family or friend assessment interviews, and treating more patients on a compulsory basis. Performance was not related to stress management training, patient attendance at more self-help meetings during treatment, staff characteristics, or average staff costs per patient day. The findings indicate that treatment retention, duration, and increased aftercare may be targeted to reduce high readmission rates. Last, there were only small differences in the model over 30, 60, 90, and 365 day follow-up intervals, suggesting substantial stability of the findings.

Prenatal care needs assessment comparing service use and outcomes in Fresno, CA

The authors performed a prenatal care needs assessment for Fresno County, CA, using data from a sample of 11,878 birth certificates for the county for 1989. Birth records, patterns of prenatal care utilization, and low birth weight outcomes in the county were compared with those in a random sample of 11,826 certificates derived from births in the remainder of the State. Bivariate techniques were used in calculating care utilization rates. Multivariate logistic regression analysis was used in associating rates of prenatal care visits and gestational month of initiation of prenatal care with low weight birth outcomes. County women entered prenatal care as early as women in the remainder of the State, but did not return as often for prenatal care visits. Their rate of return for followup visits was 29.9 percent, compared with 24.8 percent for women in all other counties (P < 0.001). County women with the lowest rates of visits had 1.4 to 1.9 times the risk of having a low weight birth than other county women with higher rates of visits, and a significantly higher risk than for women of all other counties. An intensive visit schedule for high-risk care was provided 28.9 percent of county women, compared with 33.0 percent of women in all other counties (P < 0.001). County women who received a high-risk intensive visit schedule were 2.5 times more likely to have a low weight birth than county women who did not receive the schedule. For all other women in the State, the comparable risk was 2.1 times. Improvements in the number and content of prenatal care visits were shown to have a high likelihood of substantially improving birth weight outcomes for pregnancies among Fresno County women.

Cost effects of surfactant therapy for neonatal respiratory distress syndrome

OBJECTIVE

To examine the cost effects of a single dose (5 ml/kg) of a protein-free synthetic surfactant (Exosurf) as therapy for neonatal respiratory distress syndrome, for both rescue and prophylactic therapy.

RESEARCH DESIGN

Nonblinded, randomized clinical trials of both rescue and prophylactic therapy. Regression analyses were used to control for the independent effects of sex, multiple birth, delivery method, birth weight, and surfactant therapy.

SETTING

The prophylactic trial was conducted at a university medical center only; the rescue trial also included a tertiary community hospital.

PATIENTS

Prophylaxis was administered immediately after birth to 36 infants (38 control subjects) with birth weights between 700 and 1350 gm. Rescue therapy was administered at 4 to 24 hours of age to 53 infants (51 control subjects) with established respiratory distress syndrome and birth weights > or = 650 gm (no upper limit). Infants in the prophylactic trial were not eligible for the rescue trial.

RESULTS

For the rescue trial, there was a $16,600 reduction in average hospital costs (p = 0.18), which was larger than the cost of the surfactant ($450 to $900), yielding a probable net savings. For the prophylactic trial, hospital costs were larger for treated infants versus control subjects who weighed less than about 1100 gm at birth and lower for treated infants versus control subjects who weighed more than 1100 gm at birth (p < 0.05). For the prophylactic sample, the result was an average cost per life saved of $71,500.

CONCLUSIONS

Single-dose rescue surfactant therapy is probably a cost-effective therapy because it produced a lower mortality rate for the same (and probably lower) expenditure. Single-dose prophylactic therapy for smaller infants (< or = 1350 gm) appeared to yield a reduction in mortality rate for a small additional cost. The use of multiple-dose therapy in infants who do not respond to initial therapy may alter the effects described above to either increase or decrease the observed cost-effectiveness of surfactant therapy. Regardless, surfactant therapy will remain a cost-effective method of reducing mortality rates, relative to other commonly used health care interventions.

A variable-radius measure of local hospital market structure

OBJECTIVE

To provide a radius measure of the structure of local hospital markets that varies with hospital characteristics and is available for all hospitals in the United States.

DATA SOURCES

1982 American Hospital Association (AHA) Survey of Hospitals, 1982 Area Resource File (ARF), and 1983 California Office of Statewide Health Planning and Development (OSHPD) discharge abstracts.

STUDY DESIGN

The OSHPD data were used to measure the radii necessary to capture 75 percent and 90 percent of each hospital's admissions. These radii were used as the dependent variables in regression models in which the independent variables were from the AHA and ARF. To estimate predicted market radii, the estimated parameters from the California models were applied to all nonfederal, short-term, general hospitals in the continental United States. These radii were used to define each hospital's service area, and all other hospitals within the calculated radii were considered potential competitors. Using this definition, we calculated two measures of local market structure: the number of other hospitals within the radius and a Herfindahl-Hirschman Index based on the distribution of hospital bed shares in the market.

DATA EXTRACTION METHODS

These measures were calculated for all nonfederal, short-term, acute care hospitals in the continental United States for whom complete data were available (N = 4,884).

CONCLUSIONS

These measures are available from the authors on computer-readable diskette, matched to hospital identifiers.

Choice of hospital for delivery: a comparison of high-risk and low-risk women

OBJECTIVE

This article tests whether or not the factors that affect hospital choice differ for selected subgroups of the population.

DATA SOURCES

1985 California Office of Statewide Health Planning and Development (OSHPD) discharge abstracts and hospital financial data were used.

STUDY DESIGN

Models for hospital choice were estimated using McFadden's conditional logit model. Separate models were estimated for high-risk and low-risk patients, and for high-risk and low-risk women covered either by private insurance or by California Medicaid. The model included independent variables to control for quality, price, ownership, and distance to the hospital.

DATA EXTRACTION

Data covered all maternal deliveries in the San Francisco Bay Area in 1985 (N = 61,436). ICD-9 codes were used to classify patients as high-risk or low-risk. The expected payment code on the discharge abstract was used to identify insurance status.

PRINCIPAL FINDINGS

The results strongly reject the hypothesis that high-risk and low-risk women have the same choice process. Hospital quality tended to be more important for high-risk than low-risk women. These results also reject the hypothesis that factors influencing choice of hospital are the same for women covered by private insurance as for those covered by Medicaid. Further, high-risk women covered by Medicaid were less likely than high-risk women covered by private insurance to deliver in hospitals with newborn intensive care units.

CONCLUSIONS

The results show that the choice factors vary across several broadly defined subgroups of patients with a specific condition. Thus, estimates aggregating all patients may be misleading. Specifically, such estimates will understate actual patient response to quality of care indicators, since patient sensitivity to quality of care varies with the patients' risk status.

Birth weight and illness severity: independent predictors of neonatal mortality

BACKGROUND

Low birth weight is a major determinant of neonatal mortality. Yet birth weight, even in conjunction with other demographic markers, is inadequate to explain the large variations in neonatal mortality between intensive care units. This variation probably reflects differences in admission severity. The authors have recently developed the Score for Neonatal Acute Physiology (SNAP), an illness severity index specific for neonatal intensive care, and demonstrated illness severity to be a major determinant of neonatal mortality.

OBJECTIVE

To define the relative contributions of birth weight and illness severity to the risk of neonatal mortality and to identify other significant independent risk factors.

METHODS

Logistic regression was used to analyze data from a cohort of 1621 consecutive admissions to three neonatal intensive care units (92 deaths), to test six alternative predictive models. The best logistic model was then used to develop a simple additive clinical score, the SNAP Perinatal Extension (SNAP-PE).

RESULTS

These analyses demonstrated that birth weight and illness severity are powerful independent predictors across a broad range of birth weights and that their effects are additive. Below 750 g, there is an interaction between birth weight and SNAP. Other factors that showed independent predictive power were low Apgar score at 5 minutes and small size for gestational age. Separate derivation and test samples were used to demonstrate that the SNAP-PE is comparable to the best logistic model and has a sensitivity and specificity superior to either birth weight or SNAP alone (receiver-operator characteristic area .92 +/- .02) as well as excellent goodness of fit.

CONCLUSION

This simplified clinical score provides accurate mortality risk estimates for application in a broad array of clinical and research settings.

Back transporting infants from neonatal intensive care units to community hospitals for recovery care: effect on total hospital charges

Many neonates are referred to neonatal intensive care units (NICUs) for specialized care far from their parents' residence. This distance can add to the stress of the parents and reduce the contact of the parents with their newborn. Small studies have found that back transporting these neonates to hospitals closer to their homes is safe and cost-effective. Despite these findings, the reluctance of many insurers to pay for back transports prevents or delays many back transports. Insurers may not consider the findings of the previous studies to be conclusive, given that the comparisons were between small numbers of neonates back transported and neonates who remained in tertiary care, and the potential for differences in severity of illness between the groups is significant. In this study the effect on hospital charges of back transports was examined by comparing the charges for care in community hospitals with what these charges would have been in a tertiary care center. The advantage of this method is that it avoids case-mix differences between the groups and thus minimizes the potential for small-sample bias. Data were collected for all back transports from a NICU to non-tertiary care centers (n = 90) for a 9-month period. We were able to obtain the itemized bills for the care at community hospitals for 42 of these patients. Each bill was recalculated using the charges for the NICU to determine potential for savings. The average charges for recovery care were about $6200 lower at the community hospital than they would have been at the NICU.(ABSTRACT TRUNCATED AT 250 WORDS)

Prevention: the cost-effectiveness of the California Diabetes and Pregnancy Program

BACKGROUND

The California Diabetes and Pregnancy Program is a new preventive approach to improving pregnancy outcomes through intensive diabetes management preconception and early in pregnancy.

METHODS

Hospital charges and length of stay data were collected on 102 program enrollees and 218 control cases. Ninety program enrollees and 90 control cases were matched on mother's age. White's classification, and race. Regression models controlled for these variables in addition to MediCal status, birth weight, and enrollment in the program.

RESULTS

Hospital charges were about 30% less for program participants and days in the hospital were roughly 25% less. The program effects were larger for women that enrolled before 8 weeks gestation. More serious diabetics were also found to have larger reductions in charges and days.

CONCLUSION

After adjusting for inflation and differences in charges across hospitals, $5.19 is saved for every dollar spent on the program.

The neonatal costs of maternal cocaine use

OBJECTIVE

--To examine the added neonatal cost and length of hospital stay associated with fetal cocaine exposure.

DESIGN

--All cocaine-exposed infants in the study population (n = 355) were compared with a random sample of unexposed infants (n = 199). Regression analysis was used to control for the independent effects of maternal age, smoking, alcohol consumption, prenatal care, race, gravidity, and sex of the infant.

SETTING

--A large, public, inner-city hospital studied from 1985 to 1986.

PATIENTS

--All infants were routinely tested for illicit substances, records were reviewed for maternal histories of substance abuse, and all known cocaine-exposed singleton infants were included.

MAIN OUTCOME MEASURES

--Cost and length of stay until each infant was medically cleared for hospital discharge and cost and length of stay until each infant was actually discharged from the hospital.

RESULTS

--Neonatal hospital costs until medically cleared for discharge were $5200 more for cocaine-exposed infants than for unexposed infants (a difference of $7957 vs $2757 [P = .003]). The costs of infants remaining in the nursery while awaiting home and social evaluation or foster care placement increased this difference by more than $3500 (P less than .0001). Compared with other forms of cocaine, fetal exposure to crack was associated with much larger cost increases ($6735 vs $1226). Exposure to other illicit substances in addition to cocaine was also associated with much larger cost increases ($8450 vs $1283).

CONCLUSIONS

--At the national level, we estimate that these individual medical costs add up to about $500 million. The large magnitude of these costs indicates that effective treatment programs for maternal cocaine abusers could yield savings within their first year of operation.

Modeling the effect of hospital charges and quality on choice

The authors apply a conditional choice model to simulate the results of patient and physician choices of hospitals for a specific surgical procedure in response to improvements in quality or changes in charges. The model includes all zip code areas and relevant hospitals in a large metropolitan area and estimates the impact on admissions at each hospital. It can be used to estimate both the impact of decisions by a given hospital and the potential responses of competitors, as well as the effects of selective contracting with hospitals by certain payors.

Initial clinical trial of EXOSURF, a protein-free synthetic surfactant, for the prophylaxis and early treatment of hyaline membrane disease

EXOSURF is a protein-free surfactant composed of 85% dipalmitoylphosphatidylcholine, 9% hexadecanol, and 6% tyloxapol by weight. A single dose of 5 mL of EXOSURF per kilogram body weight, which gave 67 mg of dipalmitoylphosphatidylcholine per kilogram body weight, or 5 mL/kg air was given intratracheally in each of two controlled trials: at birth to neonates 700 through 1350 g (the prophylactic trial, n = 74) or at 4 to 24 hours after birth to neonates greater than 650 g who had hyaline membrane disease severe enough to require mechanical ventilation (the rescue trial, n = 104). In both studies, time-averaged inspired oxygen concentrations and mean airway pressures during the 72 hours after entry decreased significantly (P less than .05) in the treated neonates when compared with control neonates. Thirty-six percent of the treated neonates in the rescue study had an incomplete response to treatment or relapsed within 24 hours, suggesting the need for retreatment in some neonates. In the rescue trial, risk-adjusted survival increased significantly in the treated group. There were no significant differences in intracranial hemorrhages, chronic lung disease, or symptomatic patent ductus arteriosus between control and treated infants in either trial.

Explaining resource consumption among non-normal neonates

The adoption by Medicare in 1983 of prospective payment using diagnosis-related groups (DRGs) has stimulated research to develop case-mix grouping schemes that more accurately predict resource consumption by patients. In this article, the authors explore a new method designed to improve case-mix classification for newborns through the use of birth weight in combination with DRGs to adjust the unexplained case-mix severity. Although the findings are developmental in nature, they reveal that the model significantly improves our ability to explain resource use.

Does quality influence choice of hospital?

In recent years, much information has been provided to the public and to physicians about hospital quality measured in terms of patient outcomes. To examine if, before these public data releases, quality influenced the attractiveness of a hospital to referring or admitting physicians and to patients, we estimated the influences of quality, charges, ownership, and distance on the choice of hospitals for patients with seven surgical procedures and five medical diagnoses in hospitals in three geographic areas in California in 1983. Greater distance and public or proprietary ownership consistently reduced the likelihood of selection while medical school affiliation increased the likelihood of selection. For five of seven surgical procedures and two of five medical diagnoses, hospitals with poorer than expected outcomes attracted significantly fewer admissions. The reverse held for two surgical procedures and one medical diagnosis. The results suggest that quality played an important role in choices among hospitals even before explicit data were widely available.

The sensitivity of conditional choice models for hospital care to estimation technique

It is plausible that distance, quality, and hospital charges all influence which hospital patients (and their referring physicians) choose. Several researchers have estimated conditional choice models that explicitly incorporate the existence of competing hospitals. To be useful for hospital administrators, health planners and insurers, however, estimates must be made for specific types of patients and include entire market areas. Data sets meeting these requirements have many combinations of hospitals and locations with zero patients. This raises computational difficulties with the linear estimation techniques used previously. In this paper, we use data on patients undergoing cardiac catheterization in several market areas to assess alternative estimation techniques. First, we estimate the conditional choice model with the two techniques used previously to transform the non-linear choice model. These involve using as a reference (1) a single hospital, or (2) the geometric mean of all the hospitals in the market. When there are many zeros, these techniques require extensive adjustments to the data which may lead to biased estimators. We then compare these results with maximum likelihood estimates. The latter results are substantively and significantly different from those using traditional techniques. More importantly, the linear estimates are much more sensitive to the proportion of zeros. We thus conclude that maximum likelihood estimates are preferable when there are many zeros.

An evaluation of Medicaid selective contracting in California

This study used 1982-1986 data on 262 private community hospitals to evaluate the effects of selective contracting for inpatient services by California's Medicaid program. Selective contracting by Medicaid significantly reduced the rate of inflation in average costs per admission and per patient day, while slightly increasing average lengths of patient stays. Private sector contracting also reduced cost inflation rates significantly and caused small, non-significant, reductions in lengths of stays. Hospital savings in 1986 due to Medicaid selective contracting were $836 million, 7.6% of what hospital expenditures would have been in the absence of contracting.

Alternative to diagnosis-related groups for newborn intensive care

Clinical and billing data were collected on all admissions to six California newborn intensive care units during a 6-month period. Charges were adjusted to costs using Medicaid cost to charge ratios and for inflation, and patients were classified by the diagnosis-related group (DRG) system. Costs were from 97% to 708% more than the proposed DRG reimbursement levels. Regression analysis showed that DRGs explained 22% of the variation in costs. An alternative model using binary variables to control for birth weight, assisted ventilation, surgery, survival, multiple births, and mode of discharge explained 42% of the variation in costs. In contrast to other proposed DRG alternatives, this simple model does not require special training or subjective decision-making.

Newborn risk factors and costs of neonatal intensive care

To understand the sources of the high costs of neonatal intensive care, financial and medical information on 1,185 admissions to an intensive care nursery was gathered. Multiple regression analysis showed that a significant portion of the variation in individual costs was explained by three measures of risk: low birth weight, surgical intervention, and assisted ventilation. There was a highly skewed distribution of costs. Nearly half of all admissions had none of the above risk factors, had an average cost of about $2,000, and accounted for only 13% of the total costs for the whole sample. In contrast, less than one quarter of the admissions had two or more of the risk factors, had an average cost of $19,800, and accounted for nearly 60% of the total costs. Models that predict costs and length of stay on a basis of seven risk factors were developed to allow for differences in patient populations.