Managed Care, Technology Adoption, and Health Care: The Adoption of Neonatal Intensive Care

Managed care activity may alter the incentives associated with the acquisition and use of new medical technologies, with potentially important implications for health care costs, patient care, and outcomes. This paper discusses mechanisms by which managed care could influence the adoption of new technologies and empirically examines the relationship between HMO market share and the diffusion of neonatal intensive care, a collection of technologies for the care of high risk newborns. We find that managed care slowed the adoption of NICUs, primarily by slowing the adoption of mid-level NICUs rather than the most advanced high-level units. Slowing the adoption of mid-level units would likely have generated savings. Moreover, opposite the frequent supposition that slowing technology growth is uniformly harmful to patients, in this case reduced adoption of mid-level units could have benefitted patients, since health outcomes for seriously ill newborns are better in higher-level NICUs and reductions in the availability of mid-level units appear to increase the chance of receiving care in a high-level center.

Is There Monopsony in the Labor Market? Evidence from a Natural Experiment

Recent theoretical and empirical advances have renewed interest in monopsonistic models of the labor market. However, there is little direct empirical support for these models. We use an exogenous change in wages at Department of Veterans Affairs (VA) hospitals as a natural experiment to investigate the extent of monopsony in the nurse labor market. We estimate that labor supply to individual hospitals is quite inelastic, with short-run elasticity around 0.1. We also find that non-VA hospitals responded to the VA wage change by changing their own wages

Human Capital and Organizational Performance: Evidence from the Healthcare Sector

This paper contributes to the literature on the relationship between human capital and organizational performance. We use detailed longitudinal monthly data on nursing units in the Veterans Administration hospital system to identify how the human capital (general, hospital-specific and unit or team-specific) of the nursing team on the unit affects patients' outcomes. Since we use monthly, not annual, data, we are able to avoid the omitted variable bias and endogeneity bias that could result when annual data are used. Nurse staffing levels, general human capital, and unit-specific human capital have positive and significant effects on patient outcomes while the use of contract nurses, who have less specific capital than regular staff nurses, negatively impacts patient outcomes. Policies that would increase the specific human capital of the nursing staff are found to be cost-effective.

Trends in resources for neonatal intensive care at delivery hospitals for infants born younger than 30 weeks' gestation, 2009-2020

Importance: In an ideal regionalized system, all infants born very preterm would be delivered at a large tertiary hospital capable of providing all necessary care. Objective: To examine whether the distribution of extremely preterm births changed between 2009 and 2020 based on neonatal intensive care resources at the delivery hospital. Design, setting, and participants: This retrospective cohort study was conducted at 822 Vermont Oxford Network (VON) centers in the US between 2009 and 2020. Participants included infants born at 22 to 29 weeks' gestation, delivered at or transferred to centers participating in the VON. Data were analyzed from February to December 2022. Exposures: Hospital of birth at 22 to 29 weeks' gestation. Main outcomes and measures: Birthplace neonatal intensive care unit (NICU) level was classified as A, restriction on assisted ventilation or no surgery; B, major surgery; or C, cardiac surgery requiring bypass. Level B centers were further divided into low-volume (<50 inborn infants at 22 to 29 weeks' gestation per year) and high-volume (≥50 inborn infants at 22 to 29 weeks' gestation per year) centers. High-volume level B and level C centers were combined, resulting in 3 distinct NICU categories: level A, low-volume B, and high-volume B and C NICUs. The main outcome was the change in the percentage of births at hospitals with level A, low-volume B, and high-volume B or C NICUs overall and by US Census region. Results: A total of 357 181 infants (mean [SD] gestational age, 26.4 [2.1] weeks; 188 761 [52.9%] male) were included in the analysis. Across regions, the Pacific (20 239 births [38.3%]) had the lowest while the South Atlantic (48 348 births [62.7%]) had the highest percentage of births at a hospital with a high-volume B- or C-level NICU. Births at hospitals with A-level NICUs increased by 5.6% (95% CI, 4.3% to 7.0%), and births at low-volume B-level NICUs increased by 3.6% (95% CI, 2.1% to 5.0%), while births at hospitals with high-volume B- or C-level NICUs decreased by 9.2% (95% CI, -10.3% to -8.1%). By 2020, less than half of the births for infants at 22 to 29 weeks' gestation occurred at hospitals with high-volume B- or C-level NICUs. Most US Census regions followed the nationwide trends; for example, births at hospitals with high-volume B- or C-level NICUs decreased by 10.9% [95% CI, -14.0% to -7.8%) in the East North Central region and by 21.1% (95% CI, -24.0% to -18.2%) in the West South Central region. Conclusions and relevance: This retrospective cohort study identified concerning deregionalization trends in birthplace hospital level of care for infants born at 22 to 29 weeks' gestation. These findings should serve to encourage policy makers to identify and enforce strategies to ensure that infants at the highest risk of adverse outcomes are born at the hospitals where they have the best chances to attain optimal outcomes

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

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.Veterans Hospitalization Distance