Capacity and Utilization in Health Care: The Effect of Empty Beds on Neonatal Intensive Care Admission.
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ABSTRACT:
SUBMITTER: Freedman S
PROVIDER: S-EPMC5142636 | biostudies-literature | 2016 May
REPOSITORIES: biostudies-literature
Publications
Capacity and Utilization in Health Care: The Effect of Empty Beds on Neonatal Intensive Care Admission.
American economic journal. Economic policy 20160501 2
Because geographic variation in medical care utilization is jointly determined by both supply and demand, it is difficult to empirically estimate whether capacity itself has a causal impact on utilization in health care. In this paper, I exploit short-term variation in Neonatal Intensive Care Unit (NICU) capacity that is unlikely to be correlated with unobserved demand determinants. I find that available NICU beds have little to no effect on NICU utilization for the sickest infants, but do incre ...[more]
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Project description:ImportanceThere are few population-based studies addressing trends in neonatal intensive care unit (NICU) admission and NICU patient-days, especially in the subpopulation that, by gestational age (GA) and birth weight (BW), might otherwise be able to stay in the room with their mothers.ObjectiveTo describe population-based trends in NICU admissions, NICU patient-days, readmissions, and mortality in the birth population of a large integrated health care system.Design, setting, and participantsThis cohort study was conducted using data extracted from electronic medical records at Kaiser Permanente Southern California (KPSC) health care system. Participants included all women who gave birth at KPSC hospitals and their newborns from January 1, 2010, through December 31, 2018. Data extraction was limited to data entry fields whose contents were either numbers or fixed categorical choices. Rates of NICU admission, NICU patient-days, readmission rates, and mortality rates were measured in the total population, in newborns with GA 35 weeks or greater and BW 2000 g or more (high GA and BW group), and in the remaining newborns (low GA and BW group). Admissions to the NICU and NICU patient-days were risk adjusted with a machine learning model based on demographic and clinical characteristics before NICU admission. Changes in the trends were assessed with 2-sided correlated seasonal Mann-Kendall test. Data analysis was performed in August 2019.ExposuresAdmission to the NICU and NICU patient-days among the birth cohort.Main outcomes and measuresThe primary outcomes were NICU admission and NICU patient-days in the total neonatal population and GA and BW subgroups. The secondary outcomes were readmission and mortality rates.ResultsOver the study period there were 320 340 births (mean [SD] age of mothers, 30.1 [5.7] years; mean [SD] gestational age, 38.6 [1.97] weeks; mean [SD] birth weight, 3302 [573] g). The risk-adjusted NICU admission rate decreased from a mean of 14.5% (95% CI, 14.2%-14.7%) to 10.9% (95% CI, 10.7%-11.7%) (P for trend = .002); 92% of the change was associated with changes in the care of newborns in the high GA and BW group. The number of risk-adjusted NICU patient-days per birth decreased from a mean of 1.50 patient-days (95% CI, 1.43-1.54 patient-days) to 1.40 patient-days (95% CI, 1.36-1.48 patient-days) (P for trend = .03); 70% of the change was associated with newborns in the high GA and BW group. The unadjusted 30-day readmission rates and mortality rates did not change.Conclusions and relevanceAdmission rates to the NICU and numbers of NICU patient-days decreased over the study period without an increase in readmissions or mortality. The observed decrease was associated with the high GA and BW newborn population. How much of this decrease is attributable to intercurrent health care systemwide quality improvement initiatives would require further investigation. The remaining unexplained variation suggests that further changes are also possible.
| S-EPMC7303809 | biostudies-literature
Project description: Not available
| S-EPMC7194590 | biostudies-literature
Project description: Not available
| S-EPMC10954973 | biostudies-literature
Project description:High-risk infants transitioning from the neonatal intensive care unit (NICU) to home represent a vulnerable population, given their complex care requirements. Little is known about errors during this period.Identify and describe homecare and healthcare utilization errors in high-risk infants following NICU discharge.This was a prospective observational cohort study of homecare (feeding, medication, and equipment) and healthcare utilization (appointment) errors in infants discharged from a regional NICU between 2011 and 2015. Chi-square test and Wilcoxon rank-sum test were used to compare infant and maternal demographics between infants with and without errors.A total of 363 errors were identified in 241 infants during 635 home visits. The median number of visits was 2. No significance was found between infant and maternal demographics in those with or without errors.High-risk infants have complex care needs and can benefit from regular follow-up services. Home visits provide an opportunity to identify, intervene, and resolve homecare and healthcare utilization errors.Further research is needed to evaluate the prevalence and cause of homecare errors in high-risk infants and how healthcare resources and infant health outcomes are affected by those errors. Preventive measures and mitigating interventions that best address homecare errors require further development and subsequent description.
| S-EPMC5533584 | biostudies-other
Project description:IntroductionIt is well established that a premature birth increases the likelihood of developing anxiety during the postpartum period, and that the environment of the neonatal intensive care unit (NICU) might be a contributing factor. Mothers of earlier premature infants may experience these anxieties to a higher degree compared to mothers of later premature infants. The aim of this study was to explore the association between prematurity and postpartum-specific anxiety, and the relationship between postpartum-specific anxiety and stress in the NICU.Materials and methodsMothers (N = 237) of infants aged between birth and 12 months completed an online survey containing the Postpartum Specific Anxiety Scale - Research Short Form (PSAS-RSF) and the Parental Stressor Scale: Neonatal Intensive Care Unit (PSS:NICU). Structural equation modeling was used to analyze the relationship between gestational age and postpartum-specific anxiety, with one-way ANOVAs used to analyze this relationship with respect to categories of gestational age. Hierarchical regression models analyzed the relationship between postpartum-specific anxiety and stress in the NICU.ResultsFor the PSAS-RSF, Practical Infant Care Anxieties (p = 0.001), Maternal Competence and Attachment Anxieties (p = 0.033), and Infant Safety and Welfare Anxieties (p = 0.020) were significantly associated with week of gestation. Practical Infant Care and Infant Safety and Welfare Anxieties were significantly higher for mothers of late premature infants, compared to mothers of term infants (p < 0.001; p = 0.019). There were no significant between-group differences with respect to Maternal Competence and Attachment Anxieties. After controlling for potential confounders, Infant Safety and Welfare Anxieties were significantly associated with increased stress in the NICU (p < 0.001) as measured by the PSS:NICU.ConclusionsOur findings highlight the need for interventions for mothers with premature infants, which specifically target anxieties reflected in the PSAS-RSF, such as routine care and increasing maternal self-efficacy.
| S-EPMC10921229 | biostudies-literature
Project description:ObjectiveTo compare methods of characterizing intensive care unit (ICU) bed use and estimate the number of beds needed.Study settingThree geographic regions in the Canadian province of Manitoba.Study designRetrospective analysis of population-based data from April 1, 2000, to March 31, 2007.MethodsWe compared three methods to estimate ICU bed requirements. Method 1 analyzed yearly patient-days. Methods 2 and 3 analyzed day-to-day fluctuations in patient census; these differed by whether each hospital needed to independently fulfill its own demand or this resource was shared across hospitals.Principal findingsThree main findings were as follows: (1) estimates based on yearly average usage generally underestimated the number of beds needed compared to analysis of fluctuations in census, especially in the smaller regions where underestimation ranged 25-58 percent; (2) 4-29 percent fewer beds were needed if it was acceptable for demand to exceed supply 18 days/year, versus 4 days/year; and (3) 13-36 percent fewer beds were needed if hospitals within a region could effectively share ICU beds.ConclusionsCompared to using yearly averages, analyzing day-to-day fluctuations in patient census gives a more accurate picture of ICU bed use. Failing to provide adequate "surge capacity" can lead to demand that frequently and severely exceeds supply.
| S-EPMC4319880 | biostudies-literature
Project description:Rationale: Prior approaches to measuring healthcare capacity strain have been constrained by using individual care units, limited metrics of strain, or general, rather than disease-specific, populations.Objectives: We sought to develop a novel composite strain index and measure its association with intensive care unit (ICU) admission decisions and hospital outcomes.Methods: Using more than 9.2 million acute care encounters from 27 Kaiser Permanente Northern California and Penn Medicine hospitals from 2013 to 2018, we deployed multivariable ridge logistic regression to develop a composite strain index based on hourly measurements of 22 capacity-strain metrics across emergency departments, wards, step-down units, and ICUs. We measured the association of this strain index with ICU admission and clinical outcomes using multivariable logistic and quantile regression.Results: Among high-acuity patients with sepsis (n = 90,150) and acute respiratory failure (ARF; n = 45,339) not requiring mechanical ventilation or vasopressors, strain at the time of emergency department disposition decision was inversely associated with the probability of ICU admission (sepsis: adjusted probability ranging from 29.0% [95% confidence interval, 28.0-30.0%] at the lowest strain index decile to 9.3% [8.7-9.9%] at the highest strain index decile; ARF: adjusted probability ranging from 47.2% [45.6-48.9%] at the lowest strain index decile to 12.1% [11.0-13.2%] at the highest strain index decile; P < 0.001 at all deciles). Among subgroups of patients who almost always or never went to the ICU, strain was not associated with hospital length of stay, mortality, or discharge disposition (all P ≥ 0.13). Strain was also not meaningfully associated with patient characteristics.Conclusions: Hospital strain, measured by a novel composite strain index, is strongly associated with ICU admission among patients with sepsis and/or ARF. This strain index fulfills the assumptions of a strong within-hospital instrumental variable for quantifying the net benefit of admission to the ICU for patients with sepsis and/or ARF.
| S-EPMC7640725 | biostudies-literature
Project description:PURPOSE:Little is known about the molecular epidemiology of Staphylococcus aureus in Chinese neonatal intensive care units (NICUs). We describe the molecular epidemiology of S. aureus isolated from neonates on admission to Beijing Children's Hospital. METHODS:From May 2015-March 2016, nasal swabs were obtained on admission from 536 neonates. Cultures were also obtained from body sites with suspected infections. S. aureus isolates were characterized by staphylococcal chromosomal cassette (SCCmec) type, staphylococcal protein A (spa) type, multilocus sequence type (MLST), sasX gene, antimicrobial susceptibility and cytotoxicity. Logistic regression assessed risk factors for colonization. RESULTS:Overall, 92 (17%) infants were colonized with S. aureus and 20 (3.7%) were diagnosed with culture-positive S. aureus infection. Of the colonized infants, 70% (64/92) harbored methicillin-susceptible S. aureus (MSSA), 30% (28/92) harbored methicillin-resistant S. aureus (MRSA) while 70% (14/20) of infected infants were culture-positive for MRSA, 30% (6/20) were culture-positive for MSSA. Risk factors for colonization included female sex, age 7-28 days, higher birthweight (3270 IQR [2020-3655] grams) and vaginal delivery (p<0.05). The most common MRSA and MSSA clones were community-associated ST59-SCCmecIVa-t437 (60%) and ST188-t189 (15%), respectively. The sasX gene was not detected. Some MSSA isolates (16%) were penicillin-susceptible and some MRSA isolates (18%) were oxacillin-susceptible. MRSA and MSSA had similar cytotoxicity, but colonizing strains were less cytotoxic than strains associated with infections. CONCLUSIONS:S. aureus colonization was common in infants admitted to our NICU and two community-associated clones predominated. Several non-modifiable risk factors for S. aureus colonization were identified. These results suggest that screening infants for S. aureus upon admission and targeting decolonization of high-risk infants and/or those colonized with high-risk clones could be useful to prevent transmission.
| S-EPMC7018019 | biostudies-literature
Project description:BackgroundNeonatal intensive care unit (NICU) admission among term neonates is a rare event. The aim of this study was to study the association of the NICU admission of term neonates on the risk of long-term childhood mortality.MethodsA single-center case-control retrospective study between 2005 and 2019, including all in-hospital ≥ 37 weeks' gestation singleton live-born neonates. The center perinatal database was linked with the birth and death certificate registries of the Israeli Ministry of Internal Affairs. The primary aim of the study was to study the association between NICU admission and childhood mortality throughout a 15-year follow-up period.ResultsDuring the study period, 206,509 births were registered; 192,527 (93.22%) term neonates were included in the study; 5292 (2.75%) were admitted to NICU. Throughout the follow-up period, the mortality risk for term neonates admitted to the NICU remained elevated; hazard ratio (HR), 19.72 [14.66, 26.53], (p < 0.001). For all term neonates, the mortality rate was 0.16% (n = 311); 47.9% (n = 149) of those had records of a NICU admission. The mortality rate by time points (ratio1:10,0000 births) related to the age at death during the follow-up period was as follows: 29, up to 7 days; 20, 7-28 days; 37, 28 days to 6 months; 21, 6 months to 1 year; 19, 1-2 years; 9, 2-3 years; 10, 3-4 years; and 27, 4 years and more. Following the exclusion of congenital malformations and chromosomal abnormalities, NICU admission remained the most significant risk factor associated with mortality of the study population, HRs, 364.4 [145.3; 913.3] for mortality in the first 7 days of life; 19.6 [12.1; 32.0] for mortality from 28 days through 6 months of life and remained markedly elevated after age 4 years; HR, 7.1 [3.0; 17.0]. The mortality risk related to the NICU admission event, adjusted for admission diagnoses remained significant; HR = 8.21 [5.43; 12.4].ConclusionsNICU admission for term neonates is a pondering event for the risk of long-term childhood mortality. This group of term neonates may benefit from focused health care.
| S-EPMC9903506 | biostudies-literature
Project description:BackgroundThis paper describes a model for estimating COVID-19 related excess deaths that are a direct consequence of insufficient hospital ward bed and intensive care unit (ICU) capacity.MethodsCompartmental models were used to estimate deaths under different combinations of ICU and ward care required and received in England up to late April 2021. Model parameters were sourced from publicly available government information and organisations collating COVID-19 data. A sub-model was used to estimate the mortality scalars that represent increased mortality due to insufficient ICU or general ward bed capacity. Three illustrative scenarios for admissions numbers, 'Optimistic', 'Middling' and 'Pessimistic', were modelled and compared with the subsequent observations to the 3rd February.ResultsThe key output was the demand and capacity model described. There were no excess deaths from a lack of capacity in the 'Optimistic' scenario. Several of the 'Middling' scenario applications resulted in excess deaths-up to 597 deaths (0.6% increase) with a 20% reduction compared to best estimate ICU capacity. All the 'Pessimistic' scenario applications resulted in excess deaths, ranging from 49,178 (17.0% increase) for a 20% increase in ward bed availability, to 103,735 (35.8% increase) for a 20% shortfall in ward bed availability. These scenarios took no account of the emergence of the new, more transmissible, variant of concern (b.1.1.7).ConclusionsMortality is increased when hospital demand exceeds available capacity. No excess deaths from breaching capacity would be expected under the 'Optimistic' scenario. The 'Middling' scenario could result in some excess deaths-up to a 0.7% increase relative to the total number of deaths. The 'Pessimistic' scenario would have resulted in significant excess deaths. Our sensitivity analysis indicated a range between 49,178 (17% increase) and 103,735 (35.8% increase). Given the new variant, the pessimistic scenario appeared increasingly likely and could have resulted in a substantial increase in the number of COVID-19 deaths. In the event, it would appear that capacity was not breached at any stage at a national level with no excess deaths. it will remain unclear if minor local capacity breaches resulted in any small number of excess deaths.
| S-EPMC8076441 | biostudies-literature