The need for public involvement when operating a regionalized neonatal care system at maximum capacity
Bibliographic record
Abstract
Regionalization of neonatal and perinatal care is a widely used strategy to provide access to optimal care for a geographically dispersed population while using resources effectively (1). Despite being highly regionalized, the Canadian system is experiencing mounting pressure on neonatal intensive care unit (NICU) beds due to a combination of increasing overall birth rates (Figure 1), increasing rates of late preterm birth, and increasing survival rates of previously nonviable premature and term infants. The rise in birth rate is the result of two colliding events: the baby boomers' children are now giving birth to their own children, and rising fertility rates due to delayed child-bearing. We present an argument in support of the need for public involvement in decisions regarding health care resource allocation (2). Annual births in British Columbia, 1971 to 2007. Note: Plotted line shows actual annual births; solid line shows linear regression. Since 2001, there has been a rise in the birth rate as a result of the baby boom generation's children now having children. It is projected that the rise in birth rate will continue for at least 10 years. Source of data: Statistics Canada, Canadian Socioeconomic Information and Management Optimal functioning of a regionalized perinatal care system is dependent not only on the availability of tertiary NICU beds, but also beds in step-down units (level 2) to provide an appropriate level of care closer to home for convalescent babies (1), thereby freeing up beds elsewhere. However, unpredictable day-to-day fluctuations in demand for neonatal care must be accommodated. The proposed optimal and safe recommended bed occupancy rates for the NICU component are 75% to 80% (3). Operating a tertiary NICU beyond that level induces significant problems (4) such as nosocomial infections and reduced survival rate (5). In addition, fluctuations in bed availability at tertiary and secondary levels are not likely to be aligned on any given day. Conversely, high NICU bed occupancy can promote management of the maximum number of patients within a fixed budget. British Columbia (BC) has had the lowest number of level 2 and level 3 beds of any province in Canada per 1000 births (6). Decreased capacity might lead to multiple transfers of the same patient between institutions within our system (7). It is this last consequence that is a focus of the present commentary. BC has a well-developed regionalized neonatal/perinatal care system, with an efficient centralized perinatal/neonatal transport service (8). The NICU at the Children's and Women's Hospitals (C&W) in Vancouver, BC, is a tertiary/quaternary referral centre for the entire province. When no longer reliant on intensive care, babies need to be transferred promptly to a lower level of care to be closer to home and to free up acute beds for new admissions. The neonatal specialists at the NICU of the C&W also coordinate acute neonatal transfers and manage the neonatal bed state for the province. The BC Perinatal Health Program prospectively collects data on hospital admissions and discharges for newborn infants across the province. From the BC Perinatal Health Program, we obtained data on interhospital transfers for infants admitted to the C&W NICU between 2005 and 2008, following a surge in out-of-province transfers (9). We obtained approval from the Institutional Research Board of the University of British Columbia, Vancouver, to obtain anonymized information from the database on the number of transfers a given infant had between institutions until first discharge home or at five months of age. This included acute transfers into the NICU for neonatal intensive care, and reverse transfers out of the NICU to a lower level of care. Discharge home from any neonatal unit was not counted as a transfer. These data included all acute neonatal transfers, but did not include antenatal transfers. Extremely low-birthweight infants (weighing less than 1000 g) represent a minor proportion (11%) of babies admitted to a NICU. These infants experience the longest hospital stays (Figure 2), but account for only 33% of total hospital days. In our setting, very high-staffed bed occupancy (96% in 2007) in the NICU at the C&W was associated with a 40% drop in length of stay for the smallest babies (Figure 2), coinciding with a high rate of interhospital transfer and an average 91% bed occupancy in the level 2 and level 3 beds throughout the province. This occurred without an increase in overall mortality for admitted babies. This mounting pressure on beds in the NICU is also illustrated by the increase in the total number of admissions during this period (Table 1). The increasing number of interhospital transfers of this selected population admitted to the C&W NICU reflects challenges with bed capacity at the provincial level. Only 28% of infants were discharged directly home from the NICU, demonstrating the regionalized nature of our tertiary NICU patient population. However, this proportion was not influenced year to year by bed availability (Table 1). Our overall bed utilization numbers reflect the experience of the majority of patients we serve, indicating efficiency from a single-hospital perspective. Of the 2642 admissions to the NICU over the four-year observation period, 166 (6% of our NICU population) were transferred more than twice. Length of hospital stay (LOS, days) according to birth weight group from 2005 to 2008 Interhospital transfers per infant before discharge home for all levels 2 and 3 patients admitted to the Children's and Women's Hospitals (Vancouver, British Columbia) neonatal intensive care unit between 2005 and 2008 Data are presented as n unless otherwise indicated Interhospital transfers per infant before discharge home for all levels 2 and 3 patients admitted to the Children's and Women's Hospitals (Vancouver, British Columbia) neonatal intensive care unit between 2005 and 2008 Data are presented as n unless otherwise indicated Multiple transfers (greater than two) were not confined to extremely low-birthweight babies: 23% weighed less than 1000 g, and 22% weighed more than 2.5 kg. In addition, at the provincial level, critical pressure on bed availability impacted the need to transfer mothers and babies out of the province/country: 2005, n=84; 2006, n=42; 2007, n=123; and 2008, n=29. The 166 multiple-transferred babies and the 278 mothers or mother/baby pairs transferred out of the province/country during this four-year period illustrated the effects on patients and families of operating a neonatal/perinatal care system beyond usually accepted limits of bed capacity. Because fluctuations in the number of out-of province/country transfers were accompanied by a sustained rise in multiple reverse transfers, we suggest the latter is a more robust indicator of functioning over capacity. In the publicly funded Canadian health care system, we are fortunate that full neonatal care is accessible to all families who need it. By contrast, in other systems, the inability to pay can prove to be a critical impediment to access to the highest levels of acute neonatal/perinatal care. Optimal utilization of every bed in a tertiary neonatal intensive care system should be desirable to make fiscally responsible use of available staffed beds. The data provided in Table 1 suggest that there may be an upper ceiling for bed utilization, beyond which unintended collateral consequences occur for patients and their families. The situation changes from one of efficient use of resources, to crisis management as a result of lack of capacity (4). The increased number of interhospital transfers strains air and land ambulance capacity, threatening availability of highly specialized ambulance staff for acute transfers in. This increases costs, which must be offset by any potential fiscal advantage of maximal bed use. The findings described in the present commentary may be particularly evident in BC, where the population is dispersed over a large area, with geography being an important factor influencing the need for transfer. Therefore, these findings may not be generalizable to other geographical situations. We propose that health care managers need to consider innovative indicators not usually collected in utilization data, such as the occurrence of multiple transfers, to identify when the system is operating beyond capacity. Repeated and multiple transfers present infants, families and caregivers with additional challenges, complicating care. Families suffer multiple relocations to different units at different sites with different care policies and different caregivers. This experience risks disruption of continuity of care, which contravenes fundamental principles of modern neonatology including family centred care, and the provision of an environment that fosters optimal mother-infant dyadic partnership by consistent caregivers (10). In our follow-up clinic, these families have described the overwhelming additional difficulties that multiple transfers bring. We have yet to conduct formal focus groups to objectively establish the nature and extent of the ensuing consequences. In making choices about alternative uses of health care resources in a publicly funded system, “public involvement is key, as the public is not only the most important stakeholder in a publicly funded health care system, but can provide crucial perspectives about values and priorities” (2). Appropriate, informed public participation needs to extend to very difficult health care management decisions articulating preferences regarding how systems should respond when resources are critically stretched. In our system, we are faced with having to make compromises balancing fiscal constraints against individual quality of care including availability of care at the limits of viability at both ends of the life span. A publicly funded health care system does not belong to the health care administrators or the health care workers; it belongs to the members of the public who are not only taxpayers, but who may inadvertently become ‘outliers’ who pay the individual cost of the system functioning at or beyond maximum capacity. We refute the contention that there is no shortage in the system and that the solution is simply to move patients around. In view of the current rapid increase in birth rate in BC (Figure 1) and forecasted mounting demographic pressure (6), we need to more actively seek public engagement in these difficult policy decisions that involve balancing fiscal constraint with the highest quality care, and care closer to home. The authors thank Terri Pacheco for collating the data on multiple transfers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".