Trends in hospital capacity and utilization in Puerto Rico by health regions, 2010-2020.

Like many under resourced, island communities, most of the municipalities in Puerto Rico are medically underserved. However, there is limited information about changes in hospital capacity and any regional disparities in availability of hospital services in Puerto Rico, especially given the multiple public health emergencies the island has faced in recent years (e.g. hurricanes, earthquakes, and COVID-19). This study described the trends in hospital capacity and utilization for the Island of Puerto Rico and by health regions from 2010 to 2020. We analyzed the 2021-22 Area Health Resource File (AHRF) and aggregated the data by seven health regions, which are groupings of municipalities defined by the Puerto Rico Department of Health. Ten-year estimates for hospital utilization were adjusted for population size by health region. During the more recent five-year period, there were decreases in hospitals, hospital beds, and surgeries, which represent a shift from the earlier five-year period. Over the 10 years of the study period, there was an overall decrease in population-adjusted measures of hospital utilization on the island of Puerto Rico-despite multiple disasters that would, theoretically, increase need for health care services. We also found variation in hospital capacity and utilization by health regions indicating the rate of change was not uniform across Puerto Rico. The capacity of Puerto Rico's hospital system has shrunk over the past decade which may pose a challenge when responding to recurrent major public health emergencies, especially within specific health regions.

Emergency Department Visits And Hospital Capacity In The US: Trends In The Medicare Population During The COVID-19 Pandemic.

Although emergency department (ED) and hospital overcrowding were reported during the later parts of the COVID-19 pandemic, the true extent and potential causes of this overcrowding remain unclear. Using data on the traditional fee-for-service Medicare population, we examined patterns in ED and hospital use during the period 2019-22. We evaluated trends in ED visits, rates of admission from the ED, and thirty-day mortality, as well as measures suggestive of hospital capacity, including hospital Medicare census, length-of-stay, and discharge destination. We found that ED visits remained below baseline throughout the study period, with the standardized number of visits at the end of the study period being approximately 25 percent lower than baseline. Longer length-of-stay persisted through 2022, whereas hospital census was considerably above baseline until stabilizing just above baseline in 2022. Rates of discharge to postacute facilities initially declined and then leveled off at 2 percent below baseline in 2022. These results suggest that widespread reports of overcrowding were not driven by a resurgence in ED visits. Nonetheless, length-of-stay remains higher, presumably related to increased acuity and reduced available bed capacity in the postacute care system.

The impact of deprivation on colorectal cancer-stage distribution in a setting with high hospital bed density: A Japanese multilevel study.

BACKGROUND: A methodology for determining the appropriate balance between medical access and combating poverty remains undetermined. To address the boundary conditions for exceedingly good medical access, this study examined whether the impact of deprivation on cancer stage distribution could be eliminated in Japan, which has the highest hospital bed density in the world. METHODS: A nationwide medical claims-based database was used to evaluate the influence of municipality-level hospital bed density and the postal code-level areal deprivation index on cancer stage at diagnosis. Given the limited number of similar studies in Japan, we focused on colorectal cancer (CRC), for which disparities have been reported in a prefecture-level study. Multilevel multivariate logistic regression models were used, with odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for baseline and socioeconomic factors. RESULTS: Regardless of the early/advanced-stage definitions, CRC consistently tended to be detected at more advanced stages in more deprived areas. In the analysis of stages 0-I/II-IV, the OR (95% CI) was 1.09 (1.05, 1.14) (p < 0.001). In the analyses of stages 0-I/II-IV and 0-II/III-IV, gradients were observed, and later detections were observed for more deprived segments. Hospital bed density was not significantly associated with the stage distribution. CONCLUSION: The results indicate that inequalities in CRC detection due to deprivation persist even in the country with the highest hospital bed density worldwide, suggesting that poverty measures remain indispensable regardless of hospital bed access. Further investigation of various regions and cancers is required to develop a practical framework.

Closer to Home: A Quality Improvement Initiative to Optimize Satellite Site Bed Capacity.

BACKGROUND: The coronavirus disease 2019 pandemic resulted in the underutilization of inpatient beds at our satellite location. A lack of clarity and standardized admission criteria for the satellite led to frequent transfers to the main campus, resulting in patients traveling larger distances to receive inpatient care. We sought to optimize inpatient resource use at the satellite campus and keep patients "closer to home" by admitting eligible patients to that inpatient unit (LA4). Our aim was to increase bed capacity use at the satellite from 45% to 70% within 10 months. Our process measure was to increase the proportion of patients needing hospitalization who presented to the satellite emergency department (ED) and were then admitted to LA4 from 76% to 85%. METHODS: A multidisciplinary team used quality improvement methods to optimize bed capacity use. Interventions included (1) the revision and dissemination of satellite admission guidelines, (2) steps to create shared understanding of appropriate satellite admissions between ED and inpatient providers, (3) directed provider feedback on preventable main campus admissions, and (4) consistent patient and family messaging about the potential for transfer. Data were collected via chart review. Annotated run charts were used to assess the impact of interventions over time. RESULTS: Average LA4 bed capacity use increased from 45% to 69%, which was sustained for 1 year. The average percentage of patients admitted from the satellite ED to LA4 increased from 76% to 84%. CONCLUSIONS: We improved bed capacity use at our satellite campus through transparent admission criteria and shared mental models of patient care needs between ED and inpatient providers.

Exploring COVID-19 census burdens by US hospital characteristics: Implications of quality reporting at rural and critical access hospitals.

PURPOSE: By assessing longitudinal associations between COVID-19 census burdens and hospital characteristics, such as bed size and critical access status, we can explore whether pandemic-era hospital quality benchmarking requires risk-adjustment or stratification for hospital-level characteristics. METHODS: We used hospital-level data from the US Department of Health and Human Services including weekly total hospital and COVID-19 censuses from August 2020 to August 2023 and the 2021 American Hospital Association survey. We calculated weekly percentages of total adult hospital beds containing COVID-19 patients. We then calculated the number of weeks each hospital spent at Extreme (≥20% of beds occupied by COVID-19 patients), High (10%-19%), Moderate (5%-9%), and Low (<5%) COVID-19 stress. We assessed longitudinal hospital-level COVID-19 stress, stratified by 15 hospital characteristics including joint commission accreditation, bed size, teaching status, critical access hospital status, and core-based statistical area (CBSA) rurality. FINDINGS: Among n = 2582 US hospitals, the median(IQR) weekly percentage of hospital capacity occupied by COVID-19 patients was 6.7%(3.6%-13.0%). 80,268/213,383 (38%) hospital-weeks experienced Low COVID-19 census stress, 28% Moderate stress, 22% High stress, and 12% Extreme stress. COVID-19 census burdens were similar across most hospital characteristics, but were significantly greater for critical access hospitals. CONCLUSIONS: US hospitals experienced similar COVID-19 census burdens across multiple institutional characteristics. Evidence-based inclusion of pandemic-era outcomes in hospital quality reporting may not require significant hospital-level risk-adjustment or stratification, with the exception of rural or critical access hospitals, which experienced differentially greater COVID-19 census burdens and may merit hospital-level risk-adjustment considerations.

Association between the quantity of stroke care units and the complement of neurosurgical and neurology specialists in Japan: A retrospective study.

BACKGROUND: Stroke care units provide advanced intensive care for unstable patients with acute stroke. We conducted a survey to clarify the differences in stroke care units between urban and regional cities and the relationship between the number of stroke care unit beds and neurologists. METHODS: This retrospective observational study was conducted in 2,857 and 4,184 hospitals in urban and regional cities in 47 provinces of Japan, respectively, between January 2020 and August 2023. Tokyo and ordinance-designated cities in provinces were defined as urban cities, and those without such cities were defined as regional cities. The primary endpoint was the presence or absence of a stroke care unit. RESULTS: Multiple linear regression analysis revealed that the presence of stroke care units was significantly associated with the number of neurosurgical specialists. Receiver operating characteristic curve analysis was performed to predict the number of personnel required for stroke care unit installation based on the number of neurosurgical specialists. The area under the receiver operating characteristic curve, Youden index, sensitivity, and specificity were 0.721, 0.483, 0.783, and 0.700, respectively. CONCLUSIONS: Our study underscores the indispensability of SCUs in stroke treatment, advocating for a strategic allocation of medical resources, heightened accessibility to neurosurgical specialists, and a concerted effort to address geographic and resource imbalances. The identified cutoff value of 8.99 neurosurgical specialists per 100,000 population serves as a practical benchmark for optimizing SCU establishment, thereby potentially mitigating stroke-related mortality.

Association of medical care capacity and the patient mortality of septic shock: a cross-sectional study.

BACKGROUND: Hospitals with higher septic shock case volume demonstrated lower hospital mortality. We conducted this study to investigate whether this phenomenon was only caused by the increase in the number of admissions or the need to improve the medical care capacity in septic shock at the same time. METHODS: Seven-hundred and eighty-seven hospitals from China collected in a survey from January 1, 2021 to December 31, 2021. Medical care capacity for septic shock was explored by patients with septic shock in intensive care units (ICU) divided into beds, intensivists, and nurses respectively. MAIN RESULTS: The proportion of ICU patients with septic shock was negatively associated with the patient mortality of septic shock (Estimate [95%CI], -0.2532 [-0.5038, -0.0026]) (p-value 0.048). The ratios of patients with septic shock to beds, intensivists, and nurses were negatively associated with mortality of septic shock (Estimate [95%CI], -0.370 [-0.591, -0.150], -0.136 [-0.241, -0.031], and -0.774 [-1.158, -0.389]) (p-value 0.001, 0.011 and < 0.001). Severe pneumonia, the most common infection that caused a septic shock, correlated positively with its mortality (Estimate [95%CI], 0.1002 [0.0617, 0.1387]) (p-value < 0.001). CONCLUSIONS: Hospitals with higher medical care capacity for septic shock were associated with lower hospital mortality.

The role of stroke care infrastructure on the effectiveness of a hub-and-spoke telestroke model in South Carolina.

OBJECTIVE: To examine the relationship between stroke care infrastructure and stroke quality-of-care outcomes at 29 spoke hospitals participating in the Medical University of South Carolina (MUSC) hub-and-spoke telestroke network. MATERIALS AND METHODS: Encounter-level data from MUSC's telestroke patient registry were filtered to include encounters during 2015-2022 for patients aged 18 and above with a clinical diagnosis of acute ischemic stroke, and who received intravenous tissue plasminogen activator. Unadjusted and adjusted generalized estimating equations assessed associations between time-related stroke quality-of-care metrics captured during the encounter and the existence of the two components of stroke care infrastructure-stroke coordinators and stroke center certifications-across all hospitals and within hospital subgroups defined by size and rurality. RESULTS: Telestroke encounters at spoke hospitals with stroke coordinators and stroke center certifications were associated with shorter door-to-needle (DTN) times (60.9 min for hospitals with both components and 57.3 min for hospitals with one, vs. 81.2 min for hospitals with neither component, p <.001). Similar patterns were observed for the percentage of encounters with DTN time of ≤60 min (63.8% and 68.9% vs. 32.0%, p <.001) and ≤45 min (34.0% and 38.4% vs. 8.42%, p <.001). Associations were similar for other metrics (e.g., door-to-registration time), and were stronger for smaller (vs. larger) hospitals and rural (vs. urban) hospitals. CONCLUSIONS: Stroke coordinators or stroke center certifications may be important for stroke quality of care, especially at spoke hospitals with limited resources or in rural areas.

Addressing the Knowledge Deficit in Hospital Bed Planning and Defining an Optimum Region for the Number of Different Types of Hospital Beds in an Effective Health Care System.

Based upon 30-years of research by the author, a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 people is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem, a new approach to bed modeling has been developed that plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with a higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence of overutilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, and surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.

A stochastic programming approach to perform hospital capacity assessments.

This article introduces a bespoke risk averse stochastic programming approach for performing a strategic level assessment of hospital capacity (QAHC). We include stochastic treatment durations and length of stay in the analysis for the first time. To the best of our knowledge this is a new capability, not yet provided in the literature. Our stochastic programming approach identifies the maximum caseload that can be treated over a specified duration of time subject to a specified risk threshold in relation to temporary exceedances of capacity. Sample averaging techniques are applied to handle probabilistic constraints, but due to the size and complexity of the resultant mixed integer programming model, a novel two-stage hierarchical solution approach is needed. Our two-stage hierarchical solution approach is novel as it combines the application of a meta-heuristic with a binary search. It is also computationally fast. A case study of a large public hospital has been considered and extensive numerical tests have been undertaken to highlight the nuances and intricacies of the analysis. We conclude that the proposed approach is effective and can provide extra clarity and insights around hospital outputs. It provides a way to better calibrate hospitals and other health care infrastructure to future demands and challenges, like those created by the COVID pandemic.

Odontologia hospitalar: uma análise crítica sobre a inserção do cirurgião dentista na atenção terciária no estado do Rio Grande do Sul, Brasil / Hospital dentistry: a critical analysis of the role of the dental surgeon in tertiary care in the state of Rio Grande do Sul, Brazil

Objetivo: analisar a inserção do cirurgião dentista na atenção terciária no estado do Rio Grande do Sul, Brasil. Método: estudo descritivo ecológico, com uso de dados secundários registrados pelo Cadastro Nacional de Estabelecimentos de Saúde no ano de 2023. A coleta de dados foi realizada em duas etapas. Na primeira etapa também foram coletados os dados do CNES referentes à presença do cirurgião dentista, tipo de vínculo contratual e especialidades ofertadas pelos serviços. Já na segunda etapa os dados coletados foram referentes aos indicadores sociodemográficos dos profissionais com habilitação em odontologia hospitalar utilizando as informações disponibilizadas pelo Sistema WSCFO do Conselho Federal de Odontologia. A análise dos dados foi realizada com o suporte do software TabWin, versão 3.6, e do software estatístico R v. 4.2.3. Os dados foram analisados por meio de análise descritiva. Resultados: apenas 6,11% das instituições são certificadas e consideradas Hospitais de Ensino. A maioria dos estabelecimentos (87,14%) oferece atendimento pelo SUS. Quanto à presença de cirurgiões dentistas nos estabelecimentos, 64,63% dos estabelecimentos relataram tê-los, enquanto 35,37% não possuem esse profissional em sua equipe. Neste estudo, constatamos que uma correlação positiva do cirurgião dentista com o número de leitos de UTI adulto e ao maior porte do hospital. Conclusão: observa-se que ainda há necessidade de estruturação da atenção terciária no Estado do Rio Grande do Sul, no que se refere à odontologia hospitalar. Há poucos os cirurgiões dentistas com uma carga horária dedicada exclusivamente ao atendimento hospitalar clínico a beira leito.(AU)

Objective: To analyze the inclusion of dental surgeons in tertiary care in the state of Rio Grande do Sul, Brazil. Method: a descriptive ecological study using secondary data recorded by the National Register of Health Establishments in 2023. Data was collected in two stages. In the first stage, data was also collected from the CNES regarding the presence of a dental surgeon, the type of contractual relationship and the specialties offered by the services. In the second stage, data was collected on the sociodemographic indicators of professionals qualified in hospital dentistry using the information provided by the WSCFO System of the Federal Council of Dentistry. The data was analyzed using TabWin software, version 3.6, and R v. 4.2.3 statistical software. The data was analyzed using descriptive analysis. Results: only 6.11% of institutions are certified and considered Teaching Hospitals. The majority of establishments (87.14%) provide care through the SUS. As for the presence of dental surgeons in the establishments, 64.63% of the establishments reported having them, while 35.37% did not have this professional on their team. In this study, we found a positive correlation between the number of adult ICU beds and the size of the hospital. Conclusion: There is still a need to structure tertiary care in the state of Rio Grande do Sul, in terms of hospital dentistry. There are few dental surgeons with a workload dedicated exclusively to bedside clinical hospital care.(AU)

The Function of Bed Management in Pandemic Times-A Case Study of Reaction Time and Bed Reconversion.

The last decade was characterized by the reduction in hospital beds throughout Europe. When facing the COVID pandemic, this has been an issue of major importance as hospitals were seriously overloaded with an unexpected growth in demand. The dichotomy formed by the scarcity of beds and the need for acute care was handled by the Bed Management (BM) function. This case study explores how BM was able to help the solidness of the healthcare system, managing hospital beds at best and recruiting others in different settings as intermediate care in a large Local Health Authority (LHA) in central Italy. Administrative data show how the provision of appropriate care was achieved by recruiting approximately 500 beds belonging to private healthcare facilities affiliated with the regional healthcare system and exercising the best BM function. The ability of the system to absorb the extra demand caused by COVID was made possible by using intermediate care beds, which were allowed to stretch the logistic boundaries of the hospitals, and by the promptness of Bed Management in converting beds into COVID beds and reconverting them, and by the timely management of internal patient logistics, thus creating space according to the healthcare demands.

Gestión de camas hospitalarias durantela pandemia en Navarra con el apoyo demétodos matemáticos de predicción / Management of hospital beds during the pandemic in Navarra with the support of mathematical prediction methods

Durante la pandemia por coronavirus, en Navarra se utilizaron modelos matemáticos depredicción para estimar las camas necesarias, convencionales y de críticos, para atender alos pacientes COVID-19. Las seis ondas pandémicas presentaron distinta incidencia en la población, ocasionandovariabilidad en los ingresos hospitalarios y en la ocupación hospitalaria. La respuesta a laenfermedad de los pacientes no fue constante en cada onda, por lo que, para la predicción decada una, se utilizaron los datos correspondientes de esa onda.El método de predicción constó de dos partes: una describió la entrada de pacientes alhospital y la otra su estancia dentro del mismo. El modelo requirió de la alimentación a tiempo real de los datos actualizados. Los resultados delos modelos de predicción fueron posteriormente volcados al sistema de información corporativotipo Business Intelligence. Esta información fue utilizada para planificar el recurso cama y lasnecesidades de profesionales asociadas a la atención de estos pacientes en el ámbito hospitalario.En la cuarta onda se realizó un análisis para cuantificar el grado de acierto de los modelospredictivos. Los modelos predijeron adecuadamente el pico, la meseta y el cambio detendencia, pero sobreestimaron los recursos necesarios para la atención de los pacientes enla parte descendente de la curva. El principal punto fuerte de la sistemática utilizada para la construcción de modelospredictivos fue proporcionar modelos en tiempo real con datos recogidos con precisión porlos sistemas de información que consiguieron un grado de acierto aceptable permitiendo unautilización inmediata.(AU)

Hospital COVID-19 preparedness: Are (were) we ready?

BACKGROUND: Terrorist attacks and natural disasters such as Hurricanes Katrina and Harvey have increased focus on disaster preparedness planning. Despite the attention on planning, many studies have found that hospitals in the United States are underprepared to manage extended disasters appropriately and the surge in patient volume it might bring. AIM: This study aims to profile and examine the availability of hospital capacity specifically related to COVID-19 patients, such as emergency department (ED) beds, intensive care unit (ICU) beds, temporary space setup, and ventilators. METHOD: A cross-sectional retrospective study design was used to examine secondary data from the 2020 American Hospital Association (AHA) Annual Survey. A series of multivariate logistic analyses were conducted to investigate the strength of association between changes in ED beds, ICU beds, staffed beds, and temporary spaces setup, and the 3,655 hospitals' characteristics. RESULTS: Our results highlight that the odds of a change in ED beds are 44 percent lower for government hospitals and 54 percent for for-profit hospitals than not-for-profit hospitals. The odds of ED bed change for nonteaching hospitals were 34 percent lower compared to teaching hospitals. Small and medium hospitals have significantly lower odds (75 and 51 percent, respectively) than large hospitals. For ICU bed change, staffed bed change, and temporary spaces setup, the conclusions were consistently significant regarding the impact of hospital ownership, teaching status, and hospital size. However, temporary spaces setup differs by hospital location. The odds of change is significantly lower (OR = 0.71) in urban hospitals compared with rural hospitals, while for ED beds, the odds of change is considerably higher (OR = 1.57) in urban hospitals compared to rural hospitals. CONCLUSION: There is a need for policymakers to consider not only resource limitations that were created from supply line disruptions during the COVID-19 pandemic but also a more global assessment of the adequacy of funding and support for insurance coverage, hospital finance, and how hospitals meet the needs of the populations they serve.

One System, Multiple Hospitals: A Unified Paediatric Healthcare System Response to the COVID-19 Pandemic.

To address severe adult in-patient capacity pressures during the COVID-19 pandemic, 15 community hospitals were mandated to close their in-patient paediatric units (167 beds) and transfer paediatric in-patients to a single paediatric tertiary hospital. The tertiary hospital increased bed capacity through a surge plan activation, while community hospitals redeployed resources to fill the gaps in adult care. Also, 530 patients were transferred solely to increase adult bed capacity during the closure. Several factors enabled the system to function collaboratively. Closures increased the potential adult in-patient capacity by 6,740 bed days and demonstrated an unprecedented system-wide approach to the provision of integrated paediatric care across the region.

Research on outpatient capacity planning combining lean thinking and integer linear programming.

BACKGROUND: The size and cost of outpatient capacity directly affect the operational efficiency of a whole hospital. Many scholars have faced the study of outpatient capacity planning from an operations management perspective. OBJECTIVE: The outpatient service is refined, and the quantity allocation problem of each type of outpatient service is modeled as an integer linear programming problem. Thus, doctors' work efficiency can be improved, patients' waiting time can be effectively reduced, and patients can be provided with more satisfactory medical services. METHODS: Outpatient service is divided into examination and diagnosis service according to lean thinking. CPLEX is used to solve the integer linear programming problem of outpatient service allocation, and the maximum working time is minimized by constraint solution. RESULTS: A variety of values are taken for the relevant parameters of the outpatient service, using CPLEX to obtain the minimum and maximum working time corresponding to each situation. Compared with no refinement stratification, the work efficiency of senior doctors has increased by an average of 25%. In comparison, the patient flow of associate senior doctors has increased by an average of 50%. CONCLUSION: In this paper, the method of outpatient capacity planning improves the work efficiency of senior doctors and provides outpatient services for more patients in need; At the same time, it indirectly reduces the waiting time of patients receiving outpatient services from senior doctors. And the patient flow of the associate senior doctors is improved, which helps to improve doctors' technical level and solve the problem of shortage of medical resources.