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Objectives To compare in-hospital mortality between intracerebral hemorrhage (ICH) patients in rural hospitals to those in urban hospitals of the USA. Methods We used the National Inpatient Sample to retrospectively identify all cases of ICH in the USA over the period 2004–2014. We used multivariable-adjusted models to compare odds of mortality between rural and urban hospitals. Joinpoint regression was used to evaluate trends in age- and sex-adjusted mortality in rural and urban hospitals over time. Results From 2004 to 2014, 5.8% of ICH patients were admitted in rural hospitals. Rural patients were older (mean [SE] 76.0 [0.44] years vs. 68.8 [0.11] years in urban), more likely to be white and have Medicare insurance. Age- and sex-adjusted mortality was greater in rural hospitals (32.2%) compared to urban patients (26.5%) (p value

BackgroundIn Brazil, 211 thousand (16.14%) of all death certificates in 2016 identified cancer as the underlying cause of death, and it is expected that around 320 thousand will receive a cancer diagnosis in 2019. We aimed to describe trends of cancer mortality from 1996 to 2016, in 133 intermediate regions of Brazil, and to discuss macro-regional differences of trends by human development and healthcare provision.MethodsThis ecological study assessed georeferenced official data on population and mortality, health spending, and healthcare provision from Brazilian governmental agencies. The regional office of the United Nations Development Program provided data on the Human Development Index in Brazil. Deaths by misclassified or unspecified causes (garbage codes) were redistributed proportionally to known causes. Age-standardized mortality rates used the world population as reference. Prais-Winsten autoregression allowed calculating trends for each region, sex and cancer type.ResultsTrends were predominantly on the increase in the North and Northeast, whereas they were mainly decreasing or stationary in the South, Southeast, and Center-West. Also, the variation of trends within intermediate regions was more pronounced in the North and Northeast. Intermediate regions with higher human development, government health spending, and hospital beds had more favorable trends for all cancers and many specific cancer types.ConclusionsPatterns of cancer trends in the country reflect differences in human development and the provision of health resources across the regions. Increasing trends of cancer mortality in low-income Brazilian regions can overburden their already fragile health infrastructure. Improving the healthcare provision and reducing socioeconomic disparities can prevent increasing trends of mortality by all cancers and specific cancer types in Brazilian more impoverished regions.

Locating open beds in hospital and residential mental health and substance use disorder treatment settings has been an ongoing challenge in the United States. The inability to find open beds has contributed to long emergency department wait times and missed opportunities to engage patients in treatment. Increasingly, states are creating online bed tracking systems to improve access to timely information about bed availability. This study aimed to document how states are implementing bed tracking systems, their successes and challenges, and lessons learned.A review was conducted of the published and gray literature available between 2008 and 2018, and 13 interviews were conducted with 18 stakeholders in five states (Connecticut, Iowa, Kansas, Massachusetts, and Virginia).The authors identified 17 states with bed tracking systems, of which five make information available to consumers. Most interviewees reported that the bed tracking systems were improving the ability of providers and consumers to more readily locate openings. Challenges identified included that some hospitals will not participate in bed registries, data on bed availability is sometimes not timely enough, bed registries do not provide enough detail on whether the facility is capable of meeting a particular patient's needs, providers have not been coached to use the bed registry system and continue existing practices, and states that provide information to the public have not publicized the registry's existence.Bed tracking systems offer promise, but more needs to be done to understand how to realize their potential and to more widely implement lessons learned.

Background The rigid and old-fashioned structure of the Hungarian healthcare system has been discussed since the mid-1990s and is at the center of professional and policy debates. It is characterized by the too high number of acute care hospital beds in international comparison; access is regionally unequal; levels of progressive care are mixed; and there is a nonuniform emergency service system with unequal access to the emergency room, heterogeneous quality of care, and unexploited opportunities of modern health technology (eg, 1-day surgery, minimally invasive procedures, telemedicine). Objectives The aim of this study is to analyze the indicators of ongoing structural changes of the Hungarian healthcare system between 2000 and 2017. Methods Data are derived from the Organisation for Economic Co-operation and Development Heath Statistics, Hungarian National Statistical Office, National Health Insurance Fund Administration and the database of the European Structural Funds. The methods used for the analysis are descriptive statistics, trend analysis, and longitudinal data. Results The total number of hospitals beds showed a 32% reduction between 2005 and 2017. Parallel with this subsequent reduction of hospital bed capacities, we can see a moderate reduction (22.3%) in the number of discharged patients from hospitals: from 2005 to 2017, 2.55 million to 1.95 million. The average length of stay in acute hospital care has decreased from 6.3 to 5.1 days. About 25 to 27 small local hospitals lost their acute or short-term care profile (mainly intensive care units, internal medicine, surgery, and pediatric care wards) and became long-term care, chronic care, or rehabilitation profile hospitals. Conclusion Structural change is in progress in the Hungarian healthcare system, and some efficiency gains have been reached. Nevertheless, still there are significant potential efficiency gains in the better organization and management of health services in addition to the dissemination and better incorporation of modern healthcare technologies.

OBJECTIVES We assessed the growth, distribution, and characteristics of pediatric intensive care in 2016. DESIGN Hospitals with PICUs were identified from prior surveys, databases, online searching, and clinician networking. A structured web-based survey was distributed in 2016 and compared with responses in a 2001 survey. SETTING PICUs were defined as a separate unit, specifically for the treatment of children with life-threatening conditions. PICU hospitals contained greater than or equal to 1 PICU. SUBJECTS Physician medical directors and nurse managers. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS PICU beds per pediatric population (< 18 yr), PICU bed distribution by state and region, and PICU characteristics and their relationship with PICU beds were measured. Between 2001 and 2016, the U.S. pediatric population grew 1.9% to greater than 73.6 million children, and PICU hospitals decreased 0.9% from 347 to 344 (58 closed, 55 opened). In contrast, PICU bed numbers increased 43% (4,135 to 5,908 beds); the median PICU beds per PICU hospital rose from 9 to 12 (interquartile range 8, 20 beds). PICU hospitals with greater than or equal to 15 beds in 2001 had significant bed growth by 2016, whereas PICU hospitals with less than 15 beds experienced little average growth. In 2016, there were eight PICU beds per 100,000 U.S. children (5.7 in 2001), with U.S. census region differences in bed availability (6.8 to 8.8 beds/100,000 children). Sixty-three PICU hospitals (18%) accounted for 47% of PICU beds. Specialized PICUs were available in 59 hospitals (17.2%), 48 were cardiac (129% growth). Academic affiliation, extracorporeal membrane oxygenation availability, and 24-hour in-hospital intensivist staffing increased with PICU beds per hospital. CONCLUSIONS U.S. PICU bed growth exceeded pediatric population growth over 15 years with a relatively small percentage of PICU hospitals containing almost half of all PICU beds. PICU bed availability is variable across U.S. states and regions, potentially influencing access to care and emergency preparedness.

Purpose In Malaysia, private healthcare sector has become a major player in delivering healthcare services alongside the government healthcare sector. However, wide disparities in health outcomes have been recorded, and adverse events in these contexts have yet to be explored. The purpose of this study was to explore associations between nurse's ethnicity and experience, hospital size, accreditation, and teaching status with adverse events in Malaysian private hospitals. Methods A cross-sectional survey was conducted in 12 private hospitals in Malaysia. A total of 652 (response rate = 61.8%) nurses participated in the study. Data were collected using self-administered questionnaire on nurses' characteristic, adverse events and events reporting, and perceived patient safety. Results Patient and family complaints events were the most common adverse events in Malaysian private hospitals as result of increased cost of care (3.24 ± 0.95) and verbal miscommunication (3.52 ± 0.87). Conclusion Hospital size, accreditation status, teaching status, and nurse ethnicity had a mixed effect on patient safety, perceived adverse events, and events reporting. Policy makers can benefit that errors are related to several human and system related factors. Several system reforms and multidisciplinary efforts were recommended for optimizing health, healthcare and preventing patient harm.

Summary Aim Identified Palliative Care Beds (Lits Identifies Soins Palliatifs – LISPs) is a French specificity. Primarily created to integrate palliative care culture into conventional hospital units, the relevance of this measure became a controversial issue. Nowadays, hospital teams continue to frequently encounter complex situations regarding medical care for palliative patients. To the best of our knowledge, there is only one study, a quantitative one, bridging the gap about that subject. It showed failure in practicing palliative care work around LISP. Our study is based on a qualitative method that complements the quantitative study. It aimed to describe difficulties that limit palliative care practices in managing adult patients in LISP. Method This qualitative exploratory survey was conducted with a sample of health service professionals (n = 20), from senior physicians to caregivers. Each semi-structured interview included open questions regarding their experiences, feelings and difficulties with palliative care practices on LISP. It also included closed questions concerning interviewee's demographics and career course. The data for this research were submitted to a two-stage analysis: first, a global review of each interview was performed to identify trends. Then, a detailed breakdown, question by question, was implemented. Results From a quantitative perspective, the interviews revealed 305 difficulties, indicating the gaps and barriers limiting the implementation of a palliative approach in these services. From a qualitative perspective, five topics raised our attention by their recurrence in discourses: (1) partial knowledge about palliative care definition and legislation mostly due to a lack of training; (2) need for time; (3) need for human resources; (4) need for communication; (5) hard time in transitioning from curative to palliative care. Perspective This survey gives the opportunity to understand health service professionals’ difficulties in practicing palliative care in conventional medical services. It raises the central issue of the pricing reform on the health institutes activity. It also provides angles of inquiry to improve LISP effectiveness. This qualitative and descriptive study was designed to explore difficulties in practicing palliative care around LISP. Nevertheless, according to the size of the sample, results will need to be confirmed by a more extensive qualitative survey.

Background Korea is in a condition where the impact of patient and supplier factors on cesarean section rates can be clearly described. The cesarean section rates in Korea are among the highest in the world while the number of obstetricians is decreasing sharply. This study aimed to investigate the geographic variation in cesarean section rates in Korea and its factors. Methods The data were obtained from the National Health Insurance database in Korea in 2013. We calculated the age-standardized and crude cesarean section rates of 251 districts in Korea and variation statistics. A linear regression analysis was performed to determine factors for cesarean section rates. Results The overall cesarean section rate in Korea was 364.6 cases per 1000 live births. The deprivation index score was strongly associated with the increase in the cesarean section rate while the density of hospital obstetricians and hospital beds showed a negative association. Average maternal age and total fertility rate showed a negative relationship with the cesarean section rate. Conclusions Korea is suffering from a continuing decrease in obstetricians. Our study shows that this decline has more of an effect on mothers in the disadvantaged areas. Securing equal access to obstetric care among areas is necessary, and measures to encourage obstetricians and mothers not to opt for cesarean section are required. Electronic supplementary material The online version of this article (10.1186/s12884-019-2300-0) contains supplementary material, which is available to authorized users.

In this cross-sectional study, we assessed the relationship between hospital volume and clinical outcomes for inpatients with acute myocardial infarction (AMI) in tertiary A hospitals in Shanxi, China (N = 12 931). In-hospital mortality, length of stay (LOS), and total cost were measured. The crude in-hospital mortality rate was 1.69%. Adjusted in-hospital mortality was significantly lower for medium-volume hospitals (odds ratio (OR) = 0.605, 95% confidence interval (CI) = 0.411-0.900) compared with low-volume hospitals. LOS in medium- and high-volume hospitals were 0.915 (95% CI = 0.880-0.951) and 1.069 (95% CI = 1.041-1.098) days longer than in low-volume hospitals, respectively. The cost of inpatients attending low- and high-volume hospitals (OR = 1.180, 95% CI = 1.140-1.221) was higher than that of medium-volume hospitals (OR = 0.897, 95% CI = 0.868-0.926). These results inform health care policy in countries with strained medical resources.

Background Decisions to admit high-risk postoperative patients to critical care may be affected by resource availability. We aimed to quantify adult ICU/high-dependency unit (ICU/HDU) capacity in hospitals from the UK, Australia, and New Zealand (NZ), and to identify and describe additional ‘high-acuity' beds capable of managing high-risk patients outside the ICU/HDU environment. Methods We used a modified Delphi consensus method to design a survey that was disseminated via investigator networks in the UK, Australia, and NZ. Hospital- and ward-level data were collected, including bed numbers, tertiary services offered, presence of an emergency department, ward staffing levels, and the availability of critical care facilities. Results We received responses from 257 UK (response rate: 97.7%), 35 Australian (response rate: 32.7%), and 17 NZ (response rate: 94.4%) hospitals (total 309). Of these hospitals, 91.6% reported on-site ICU or HDU facilities. UK hospitals reported fewer critical care beds per 100 hospital beds (median=2.7) compared with Australia (median=3.7) and NZ (median=3.5). Additionally, 31.1% of hospitals reported having high-acuity beds to which high-risk patients were admitted for postoperative management, in addition to standard ICU/HDU facilities. The estimated numbers of critical care beds per 100 000 population were 9.3, 14.1, and 9.1 in the UK, Australia, and NZ, respectively. The estimated per capita high-acuity bed capacities per 100 000 population were 1.2, 3.8, and 6.4 in the UK, Australia, and NZ, respectively. Conclusions Postoperative critical care resources differ in the UK, Australia, and NZ. High-acuity beds may have developed to augment the capacity to deliver postoperative critical care.

Background: There is significant heterogeneity in the treatment of stage IIIA non–small cell lung cancer (NSCLC). This study evaluated the therapeutic and survival disparities in patients with stage IIIA NSCLC based on the facility volume using the National Cancer Database. Methods: Patients with stage IIIA NSCLC diagnosed from 2004 through 2015 were included. Facilities were classified by tertiles based on mean patients treated per year, with low-volume facilities treating ≤8 patients, intermediate-volume treating 9 to 14 patients, and high-volume treating ≥15 patients. Cox multivariate analysis was used to determine the volume–outcome relationship. Results: Analysis included 83,673 patients treated at 1,319 facilities. Compared with patients treated at low-volume facilities, those treated at high-volume centers were more likely to be treated with surgical (25% vs 18%) and trimodality (12% vs 9%) therapies. In multivariate analysis, facility volume was independently associated with all-cause mortality (PPConclusions: Patients treated for stage IIIA NSCLC at high-volume facilities were more likely to receive surgical and trimodality therapies and had a significant improvement in survival.

Introduction Patient Safety Indicator (PSI) 90 is a composite measure widely used in federal pay-for-performance and public reporting programs. A component metric of PSI 90, venous thromboembolism (VTE) rate, has been shown to be subject to surveillance bias and not a valid measure for hospital quality comparisons. A study was conducted to examine how hospital PSI 90 scores would change if the VTE measure were removed from calculation of this composite measure. Methods Using 2014 Medicare inpatient claims data, PSI 90 scores were calculated with and without the VTE measure for 3,203 hospitals. Hospital characteristics obtained from the American Hospital Association Annual Survey and Centers for Medicare & Medicaid Services Payment Update Impact File were merged with PSI 90 scores. Results Removing the VTE outcome measure from the calculation of PSI 90 version 5 improved PSI 90 scores for 17.1% of hospitals but lowered scores for 20.8% of hospitals, while 62.1% had no change in scores. Hospitals were more likely to improve on PSI 90 when the VTE measure was removed if they were larger (odds ratio [OR] = 1.60; 95% confidence interval [CI] = 1.00–2.58), were major teaching hospitals (OR = 1.76; 95% CI = 1.10–2.79), had greater technological resources (OR = 2.03; 95% CI = 1.40–2.94), or cared for sicker patients (OR = 1.12; 95% CI = 1.01–1.25). Conclusion Inclusion of the surveillance bias–prone VTE outcome measure in the PSI 90 composite disproportionately penalizes larger, academic hospitals and those that care for sicker patients. Removal of the VTE outcome measure from PSI 90 should be strongly considered.

The number of psychiatric beds, in most developed countries, has decreased progressively since the late 1950s. Many clinicians believe that this reduction has gone too far. But how can we determine the number of psychiatric beds a mental health system needs? While the population health approach has advantages over the normative approach, it makes assumptions about optimal and minimum duration of hospitalization required for various psychiatric disorders. In this paper, we describe a naturalistic approach that estimates the required number of psychiatric beds by comparing the bed levels at which negative outcomes develop in different jurisdictions. We hypothesize that there will be a threshold below which negative outcomes will be seen across jurisdictions. We predict that hospital key performance indices will be more sensitive to bed reductions than the clinical and social outcomes of patients. The observed outcome approach can complement other approaches to determining bed numbers at the national and local levels, and should be a priority for future health services research.

BACKGROUND Neurosciences intensive care units (NICUs) provide institutional centers for specialized care. Despite a demonstrable reduction in morbidity and mortality, NICUs may experience significant capacity strain with resulting supraoptimal utilization and diseconomies of scale. We present an implementation study in the recognition and management of capacity strain within a large NICU in the United States. Excessive resource demand in an NICU creates significant operational issues. OBJECTIVE To evaluate the efficacy of a Reserved Bed Pilot Program (RBPP), implemented to maximize economies of scale, to reduce transfer declines due to lack of capacity, and to increase transfer volume for the neurosciences service-line. METHODS Key performance indicators (KPIs) were created to evaluate RBPP efficacy with respect to primary (strategic) objectives. Operational KPIs were established to evaluate changes in operational throughput for the neurosciences and other service-lines. For each KPI, pilot-period data were compared to the previous fiscal year. RESULTS RBPP implementation resulted in a significant increase in accepted transfer volume to the neurosciences service-line (P = .02). Transfer declines due to capacity decreased significantly (P = .01). Unit utilization significantly improved across service-line units relative to theoretical optima (P

Background/Purpose: Overcrowding of hospital emergency departments (ED) is a worldwide health problem. The Taiwan Joint Commission on Hospital Accreditation has stressed the importance of finding solutions to overcrowding, including, reducing the number of patients with >48 h stay in the ED. Moreover, the Ministry of Health and Welfare aims at transferring non-critical patients to district or regional hospitals. We report the results of our Quality Improvement Project (QIP) on ED overcrowding, especially focusing on reducing length of stay (LOS) in ED. Methods: For QIP, the following 3 action plans were initiated: 1) Changing the choice architecture of patients' willingness to transfer from opt-in to opt-out; 2) increasing the turnover rate of beds and daily monitoring of the number of free beds for boarding ED patients; 3) reevaluation of patients with a LOS of >32 h after the morning shift. Results: Transfer rates increased minimally after implementation of this project, but the sample size was too small to achieve statistical significance. No significant increase was observed in the number of free medical beds, but discharge rates after 12 pm decreased significantly (p 32 h were reevaluated first. After QIP, the proportion of LOSs of >48 h dropped significantly. Changing the choice architecture may require further systemic effort and a longer observation duration. Higher-level administrators will need to formulate a more comprehensive bed management plan to speed up the turnover rate of free inpatient beds. Keywords: Emergency service, Length of stay, Quality improvement

ObjectivesDisease-modifying therapies in development for Huntington’s disease (HD) may require specialised administration and additional resource capacity. We sought to understand current and future capacity for HD management in Canada considering the possible introduction of an intrathecal (IT) disease-modifying treatment (DMT).Design, setting and participantsUsing a case study, mixed methods framework, online surveys followed by semistructured interviews were conducted in late 2020 and early 2021. Neurologists from Canadian HD (n=16) and community (n=11) centres and social workers (n=16) were invited to complete online surveys assessing current HD management and potential capacity to support administration of an IT DMT.Outcome measuresSurvey responses, anticipated demand and assumed resource requirements were modelled to reveal capacity to treat (ie, % of eligible patients) by centre. Resource bottlenecks and incremental support required (full-time equivalent, FTE) were also determined.ResultsNeurologists from 15/16 HD centres and 5/11 community centres, plus 16/16 social workers participated. HD centres manage 94% of patients with HD currently seeking care in Canada, however, only 20% of IT DMT-eligible patients are currently seen by neurologists. One-third of centres have no access to nursing support. The average national incremental nursing, room, neurologist and social worker support required to provide IT DMT to all eligible patients is 0.73, 0.36, 0.30 and 0.21 FTE per HD centre, respectively. At peak demand, current capacity would support the treatment of 6% of IT DMT-eligible patients. If frequency of administration is halved, capacity for IT-DMT administration only increases to 11%.ConclusionsIn Canada, there is little to no capacity to support the administration of an IT DMT for HD. Current inequitable and inadequate resourcing will require solutions that consider regional gaps and patient needs.

BackgroundThe coronavirus outbreak (COVID-19) in China has influenced every aspect of life worldwide. Given the unique characteristics of the dental setting, the risk of cross-infection between dental practitioners and patients is high in the absence of adequate protective measures, and dentists may develop severe anxiety in relation to the current pandemic. The limited provision of services and widespread closure of dental practices have raised concerns among dental professionals about the financial impact. The present study assessed the frequency of dental practice closure during the pandemic’s first wave in several countries and whether closures and their associated factors differ between the private and non-private sectors.MethodsAn electronic cross-sectional survey questionnaire was sent to dentists in several countries, from April to May 2020. The survey assessed professional, practice related and country-level structural factors elucidating the reason for practice closure. Multilevel logistic regression was used to assess the association between practice closure and these factors, and differences were evaluated by sector type.ResultsDentists from 29 countries (n = 3243) participated in this study. Most of the participants (75.9%) reported practice closure with significantly higher percentage in the private sector than the non-private sector. Greater pandemic-related fears were associated with a significantly higher likelihood of practice closure in the private (odds ratio [OR] = 1.54, 95% confidence interval [CI] 1.24, 1.92) and non-private (OR = 1.38, 95% CI 1.04, 1.82) sectors. Dentists in non-private rural areas (OR = 0.58, 95% CI 0.42, 0.81), and those in hospitals (overall OR = 0.60, 95% CI 0.36, 0.99) reported a low likelihood of closure. A high likelihood of closure was reported by dentists in the academia (OR = 2.13, 95% CI 1.23, 3.71). More hospital beds at the country-level were associated with a lower likelihood of closure in the non-private sector (OR = 0.65, 95% CI 0.46, 0.91). Private- sector dentists in high- income countries (HICs) reported fewer closures than those in non-HICs (OR = 0.55, 95% CI 0.15, 1.93).ConclusionsMost dentists reported practice closure because of COVID-19, and greater impacts were reported in the private sector than in the non-private sector. Closure was associated with professional, practice, and country-levels factors.

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Objectives. To estimate the critical care bed capacity that would be required to admit all critical COVID-19 cases in a setting of unchecked SARS-CoV-2 transmission, both with and without elderly-specific protection measures. Methods. Using electronic health records of all 2432 COVID-19 patients hospitalized in a large hospital in Madrid, Spain, between February 28 and April 23, 2020, we estimated the number of critical care beds needed to admit all critical care patients. To mimic a hypothetical intervention that halves SARS-CoV-2 infections among the elderly, we randomly excluded 50% of patients aged 65 years and older. Results. Critical care requirements peaked at 49 beds per 100 000 on April 1—2 weeks after the start of a national lockdown. After randomly excluding 50% of elderly patients, the estimated peak was 39 beds per 100 000. Conclusions. Under unchecked SARS-CoV-2 transmission, peak critical care requirements in Madrid were at least fivefold higher than prepandemic capacity. Under a hypothetical intervention that halves infections among the elderly, critical care peak requirements would have exceeded the prepandemic capacity of most high-income countries. Public Health Implications. Pandemic control strategies that rely exclusively on protecting the elderly are likely to overwhelm health care systems.

General hospitals provide most pediatric inpatient care in the United States.1 As hospitalization rates decrease nationwide, the regionalization of inpatient pediatric care and concentration at children’s hospitals could limit health care accessibility, especially for those in rural communities.2,3 In this month’s issue of Pediatrics, Cushing et al4 use data from the American Hospital Association survey to describe trends in pediatric inpatient capacity and access over 10 years. They demonstrate that, although there has been an overall decline in pediatric inpatient units and beds, there has also been consolidation of pediatric care with an increase in the number of inpatient beds at children’s hospitals. Lower-volume pediatric units, those without an associated PICU, and those in more rural areas were at highest risk for closure. As a result of … Address correspondence to Jeffrey Riese, MD, Department of Pediatrics, Rhode Island Hospital, 593 Eddy St, Providence, RI 02903. E-mail: jriese{at}lifespan.org

Resumo Este artigo analisa a agenda governamental estratégica para enfrentamento da COVID-19 no Brasil, com foco na atenção hospitalar. Foram analisados 28 Planos de Contingência na íntegra, sendo 01 nacional, 26 estaduais e 01 do Distrito Federal. Utilizou-se o referencial teórico do Ciclo da Política Pública, especificamente os momentos de pré-decisão e decisão governamental para o enfrentamento da pandemia. As evidências revelaram convergências entre os níveis nacional e estaduais quanto às propostas de reorientação do fluxo de atendimento, detecção dos casos e indicação de hospitais de referência. Todavia, as agendas estaduais demonstraram fragilidades correlacionadas à aquisição de aparelhos de ventilação mecânica, dimensionamento de recursos humanos, regionalização da atenção hospitalar, além de poucos estados terem estabelecido um método de cálculo de leitos de retaguarda, principalmente quanto a previsão de abertura de hospitais de referência ou contratação complementar de leitos de UTI. Conclui-se que a heterogeneidade de ações explicitadas nos planos revelaa complexidade do processo de enfrentamento da COVID-19 no Brasil com suas desigualdades regionais, fragilidades dos sistemas estaduais de saúde e reduzida coordenação do Ministério da Saúde. Abstract This paper analyzes the government’s strategic agenda for coping with COVID-19 in Brazil, focusing on hospital care. Twenty-eight Contingency Plans were analyzed in full, one national, 26 at state level, and one from the Federal District. The Public Policy Cycle’s theoretical framework was used, specifically governmental pre-decision and decision to face the pandemic. The evidence revealed convergences between the national and state levels concerning proposals for reorienting care flow, detecting cases, and indicating referral hospitals. However, the state agendas revealed weaknesses in acquiring mechanical ventilation devices, sizing human resources, and regionalizing hospital care. Moreover, few states have established a method for calculating back-end beds, mainly regarding the outlook of opening hospitals of reference or contracting additional ICU beds. We can conclude that the heterogeneous actions explained in the plans show the complex process of coping with COVID-19 in Brazil with its regional inequalities, weaknesses in the state health systems, and reduced coordination by the Ministry of Health.

Background The health system of Liberia, a low-income country in West Africa, was devastated by a civil war lasting from 1989 to 2003. Gains made in the post-war period were compromised by the 2014-2016 Ebola epidemic. The already fragile health system experienced worsening of health indicators, including an estimated 111% increase in the country's maternal mortality rate post-Ebola. Access to safe surgery is necessary for improvement of these metrics, yet data on surgical and anesthesia capacity in Liberia post-Ebola are sparse. The aim of this study was to describe anesthesia capacity in Liberia post-Ebola as part of the development of a National Surgical, Obstetric, and Anesthesia Plan (NSOAP). Methods Using the World Federation of Societies of Anaesthesiologists (WFSA) Anaesthesia Facility Assessment Tool (AFAT), we conducted a cross-sectional survey of 26 of 32 Ministry of Health recognized hospitals that provide surgical care in Liberia. The surveyed hospitals served approximately 90% of the Liberian population. This assessment surveyed infrastructure, workforce, service delivery, information management, medications, and equipment and was performed between July and September 2019. Researchers obtained data from interviews with anesthesia department heads, medical directors and through direct site visits where possible. Results Anesthesiologist and nurse anesthetist workforce densities were 0.02 and 1.56 per 100,000 population, respectively, compared to 0.63 surgeons per 100,000 population and 0.52 obstetricians/gynecologists per 100,000 population. On average, there were 2 functioning operating rooms (ORs; OR in working condition that can be used for patient care) per hospital (standard deviation [SD] = 0.79; range, 1-3). Half of the hospitals surveyed had a postanesthesia care unit (PACU) and intensive care unit (ICU); however, only 1 hospital had mechanical ventilation capacity in the ICU. Ketamine and lidocaine were widely available. Intravenous (IV) morphine was always available in only 6 hospitals. None of the hospitals surveyed completely met the minimum World Health Organization (WHO)-WFSA standards for health care facilities where surgery and anesthesia are provided. Conclusions Overall, we noted several critical gaps in anesthesia and surgical capacity in Liberia, in spite of the massive global response post-Ebola directed toward health system development. Further investment across all domains is necessary to attain minimum international standards and to facilitate the provision of safe surgery and anesthesia in Liberia. The study results will be considered in development of an NSOAP for Liberia.

Italy was one of the countries most affected by the number of people infected and dead during the first COVID-19 wave. The authors describe the rapid rollout of a population health clinical and organizational response in preparedness and capabilities to support the first wave of the COVID-19 pandemic in the Italian province of Modena. The authors review the processes, the challenges faced, and describe how excess demand for hospital services was successfully mitigated and thus overwhelming the healthcare services avoided the collapse of the local health care system. An analysis of bed occupancy in the region predicted during the first weeks of the epidemic. The SEIR model estimated the number of infected people under different containment measures. Community resources were mobilized to reduce provincial hospitals' burden of care. A population health approach, based on a radical reorganization of the workflow and emergency patient management, was implemented. The bed saturation of the Modena Healthcare Agency was measured by an ad hoc, newly implemented intensive care unit (ICU) bed occupancy and COVID-19 centralized governance dashboard. ICU bed occupancy increased by 114%, avoiding saturation of the Modena Healthcare Agency system. The Emilia-Romagna region achieved a higher rate of ICU bed availability at 2.15 ICU beds per 10,000 inhabitants as compared with community 1 ICU bed availability prior to the pandemic. Rapid and radical local reorganization of regional efforts helped inform the successful development and implementation of strategic choices within the hospital and the community to prevent the saturation of key facilities.

Key Points Question What hospital characteristics are associated with overuse of health care services in the US? Findings In this cross-sectional study of 1 325 256 services performed at 3351 hospitals, we found that hospitals in the South, for-profit hospitals, and nonteaching hospitals were associated with the highest rates of overuse. Meaning Variation within specific hospital types and regions may uncover opportunities for targeted interventions to address overuse., This cross-sectional study uses Medicare fee-for-service claims data to assess overuse of medical tests and treatments in US hospitals., Importance Overuse of health care services exposes patients to unnecessary risk of harm and costs. Distinguishing patterns of overuse among hospitals requires hospital-level measures across multiple services. Objective To describe characteristics of hospitals associated with overuse of health care services in the US. Design, Setting, and Participants This retrospective cross-sectional analysis used Medicare fee-for-service claims data for beneficiaries older than 65 years from January 1, 2015, to December 31, 2017, with a lookback of 1 year. Inpatient and outpatient services were included, and services offered at specialty and federal hospitals were excluded. Patients were from hospitals with the capacity (based on a claims filter developed for this study) to perform at least 7 of 12 investigated services. Statistical analyses were performed from July 1, 2020, to December 20, 2020. Main Outcomes and Measures Outcomes of interest were a composite overuse score ranging from 0 (no overuse of services) to 1 (relatively high overuse of services) and characteristics of hospitals clustered by overuse rates. Twelve published low-value service algorithms were applied to the data to find overuse rates for each hospital, normalized and aggregated to a composite score and then compared across 6 hospital characteristics using multivariable regression. A k-means cluster analysis was used on normalized overuse rates to identify hospital clusters. Results The primary analysis was performed on 2415 cohort A hospitals (ie, hospitals with capacity for 7 or more services), which included 1 263 592 patients (mean [SD] age, 72.4 [14] years; 678 549 women [53.7%]; 101 017 191 White patients [80.5%]). Head imaging for syncope was the highest-volume low-value service (377 745 patients [29.9%]), followed by coronary artery stenting for stable coronary disease (199 579 [15.8%]). The mean (SD) composite overuse score was 0.40 (0.10) points. Southern hospitals had a higher mean score than midwestern (difference in means: 0.06 [95% CI, 0.05-0.07] points; P

Background As the COVID-19 pandemic continues, there is a question of whether hospitals have adequate resources to manage patients. We aim to investigate global hospital bed (HB), acute care bed (ACB), and intensive care unit (ICU) bed capacity and determine any correlation between these hospital resources and COVID-19 mortality. Method Cross-sectional study utilizing data from the World Health Organization (WHO) and other official organizations regarding global HB, ACB, ICU bed capacity, and confirmed COVID-19 cases/mortality. Descriptive statistics and linear regression were performed. Results A total of 183 countries were included with a mean of 307.1 HBs, 413.9 ACBs, and 8.73 ICU beds/100,000 population. High-income regions had the highest mean number of ICU beds (12.79) and HBs (402.32) per 100,000 population whereas upper middle-income regions had the highest mean number of ACBs (424.75) per 100,000. A weakly positive significant association was discovered between the number of ICU beds/100,000 population and COVID-19 mortality. No significant associations exist between the number of HBs or ACBs per 100,000 population and COVID-19 mortality. Conclusions Global COVID-19 mortality rates are likely affected by multiple factors, including hospital resources, personnel, and bed capacity. Higher income regions of the world have greater ICU, acute care, and hospital bed capacities. Mandatory reporting of ICU, acute care, and hospital bed capacity/occupancy and information relating to coronavirus should be implemented. Adopting a tiered critical care approach and targeting the expansion of space, staff, and supplies may serve to maximize the quality of care during resurgences and future disasters.

Some hospitals have faced a surge of patients with COVID-19, while others have not. We assessed whether COVID-19 burden (number of patients with COVID-19 admitted during April 2020 divided by hospital certified bed count) was associated with mortality in a large sample of US hospitals. Our study population included 14,226 patients with COVID-19 (median age 66 years, 45.2% women) at 117 hospitals, of whom 20.9% had died at 5 weeks of follow-up. At the hospital level, the observed mortality ranged from 0% to 44.4%. After adjustment for age, sex, and comorbidities, the adjusted odds ratio for in-hospital death in the highest quintile of burden was 1.46 (95% CI, 1.07-2.00) compared to all other quintiles. Still, there was large variability in outcomes, even among hospitals with a similar level of COVID-19 burden and after adjusting for age, sex, and comorbidities.

Background. The role of the district hospital (DH) in surgical care has been undervalued. However, decentralised surgical services at DHs have been identified as a key component of universal health coverage. Surgical capacity at DHs in Western Cape (WC) Province, South Africa, has not been described. Objectives. To describe DH surgical capacity in WC and identify barriers to scaling up surgical capacity at these facilities. Methods. This was a cross-sectional survey of 33 DHs using the World Health Organization surgical situational analysis tool administered to hospital staff from June to December 2019. The survey addressed the following domains: general services and financing; service delivery and surgical volume; surgical workforce; hospital and operating theatre (OT) infrastructure, equipment and medication; and barriers to scaling up surgical care. Results. Seven of 33 DHs (21%) did not have a functional OT. Of the 28 World Bank DH procedures, small WC DHs performed up to 22 (79%) and medium/large DHs up to 26 (93%). Only medium/large DHs performed all three bellwether procedures. Five DHs (15%) had a full-time surgeon, anaesthetist or obstetrician (SAO). Of DHs without any SAO specialists, 14 (50%) had family physicians (FPs). These DHs performed more operative procedures than those without FPs ( p =0.005). Lack of finances dedicated for surgical care and lack of surgical providers were the most reported barriers to providing and expanding surgical services. Conclusions. WC DH surgical capacity varied by hospital size. However, FPs could play an essential role in surgery at DHs with appropriate training, oversight and support from SAO specialists. Strategies to scale up surgical capacity include dedicated financial and human resources.

Background: The COVID-19 pandemic has had global effects, cases have been counted in the tens of millions, and there have been over two million deaths throughout the world. Health systems have been stressed in trying to provide a response to the increasing demand for hospital beds during the different waves. This paper analyzes the dynamic response of the hospitals of the Community of Madrid (CoM) during the first wave of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in the period between 18 March and 31 May 2020. The aim was to model the response of the CoM’s health system in terms of the number of available beds. Methods: A research design based on a case study of the CoM was developed. To model this response, we use two concepts: “bed margin” (available beds minus occupied beds, expressed as a percentage) and “flexibility” (which describes the ability to adapt to the growing demand for beds). The Linear Hinges Model allowed a robust estimation of the key performance indicators for capturing the flexibility of the available beds in hospitals. Three new flexibility indicators were defined: the Average Ramp Rate Until the Peak (ARRUP), the Ramp Duration Until the Peak (RDUP), and the Ramp Growth Until the Peak (RGUP). Results: The public and private hospitals of the CoM were able to increase the number of available beds from 18,692 on 18 March 2020 to 23,623 on 2 April 2020. At the peak of the wave, the number of available beds increased by 160 in 48 h, with an occupancy of 90.3%. Within that fifteen-day period, the number of COVID-19 inpatients increased by 200% in non-intensive care unit (non-ICU) wards and by 155% in intensive care unit (ICU) wards. The estimated ARRUP for non-ICU beds in the CoM hospital network during the first pandemic wave was 305.56 beds/day, the RDUP was 15 days, and the RGUP was 4598 beds. For the ICU beds, the ARRUP was 36.73 beds/day, the RDUP was 20 days, and the RGUP was 735 beds. This paper includes a further analysis of the response estimated for each hospital. Conclusions:This research provides insights not only for academia, but also for hospital management and practitioners. The results show that not all of the hospitals dealt with the sudden increase in bed demand in the same way, nor did they provide the same flexibility in order to increase their bed capabilities. The bed margin and the proposed indicators of flexibility summarize the dynamic response and can be included as part of a hospital’s management dashboard for monitoring its behavior during pandemic waves or other health crises as a complement to other, more steady-state indicators.

Addressing oxygen requirements of rural India should aim at using a safe, low-cost, easily available, and replenishable source of oxygen of moderate purity. This may be possible with the provision of a self-sustaining oxygen concentrator (pressure swing adsorption with multiple molecular sieve technology) capable of delivering oxygen at high-flow rates, through a centralized distribution system to 100 or more bedded rural hospitals, with back up from an oxygen bank of 10 × 10 cylinders. This will provide a 24 × 7 supply of oxygen of acceptable purity (~93%) for the treatment of hypoxemic conditions and will enable hospitals to specifically provide for high-flow oxygen in at least 15% of the beds. It may also serve as a facility for a local refill of oxygen cylinders for emergency use within the hospital as well as to subsidiary primary health centers, subcenters, and ambulances, thereby nudging our health-care system toward self-sufficiency in oxygen generation and utilization.

Determining the level of social distancing, quantified here as the reduction in daily number of social contacts per person, i.e. the daily contact rate, needed to maintain control of the COVID-19 epidemic and not exceed acute bed capacity in case of future epidemic waves, is important for future planning of relaxing of strict social distancing measures. This work uses mathematical modelling to simulate the levels of COVID-19 in North East London (NEL) and inform the level of social distancing necessary to protect the public and the healthcare demand from future COVID-19 waves. We used a Susceptible-Exposed-Infected-Removed (SEIR) model describing the transmission of SARS-CoV-2 in NEL, calibrated to data on hospitalised patients with confirmed COVID-19, hospital discharges and in-hospital deaths in NEL during the first epidemic wave. To account for the uncertainty in both the infectiousness period and the proportion of symptomatic infection, we simulated nine scenarios for different combinations of infectiousness period (1, 3 and 5 days) and proportion of symptomatic infection (70%, 50% and 25% of all infections). Across all scenarios, the calibrated model was used to assess the risk of occurrence and predict the strength and timing of a second COVID-19 wave under varying levels of daily contact rate from July 04, 2020. Specifically, the daily contact rate required to suppress the epidemic and prevent a resurgence of COVID-19 cases, and the daily contact rate required to stay within the acute bed capacity of the NEL system without any additional intervention measures after July 2020, were determined across the nine different scenarios. Our results caution against a full relaxing of the lockdown later in 2020, predicting that a return to pre-COVID-19 levels of social contact from July 04, 2020, would induce a second wave up to eight times the original wave. With different levels of ongoing social distancing, future resurgence can be avoided, or the strength of the resurgence can be mitigated. Keeping the daily contact rate lower than 5 or 6, depending on scenarios, can prevent an increase in the number of COVID-19 cases, could keep the effective reproduction number Re below 1 and a secondary COVID-19 wave may be avoided in NEL. A daily contact rate between 6 and 7, across scenarios, is likely to increase Re above 1 and result in a secondary COVID-19 wave with significantly increased COVID-19 cases and associated deaths, but with demand for hospital-based care remaining within the bed capacity of the NEL health and care system. In contrast, an increase in daily contact rate above 8 to 9, depending on scenarios, will likely exceed the acute bed capacity in NEL and may potentially require additional lockdowns. This scenario is associated with significantly increased COVID-19 cases and deaths, and acute COVID-19 care demand is likely to require significant scaling down of the usual operation of the health and care system and should be avoided. Our findings suggest that to avoid future COVID-19 waves and to stay within the acute bed capacity of the NEL health and care system, maintaining social distancing in NEL is advised with a view to limiting the average number of social interactions in the population. Increasing the level of social interaction beyond the limits described in this work could result in future COVID-19 waves that will likely exceed the acute bed capacity in the system, and depending on the strength of the resurgence may require additional lockdown measures.

BackgroundThis paper describes the construction of a model used to estimate the number of excess deaths that could be expected as a direct consequence of a lack of hospital bed and intensive care unit (ICU) capacity.MethodsA series of compartmental models was used to estimate the number of deaths under different combinations of care required (ICU or ward), and care received (ICU, ward or no care) in England up to the end of April 2021. Model parameters were sourced from publicly available government information, organisations collating COVID-19 data and calculations using existing parameters. A compartmental sub-model was used to estimate the mortality scalars that represent the increase in mortality that would be expected from a lack of provision of an ICU or general ward bed when one is required. Three illustrative scenarios for admissions numbers, ‘Optimistic’, ‘Middling’ and ‘Pessimistic’, are described showing how the model can be used to estimate mortality rates under different scenarios of capacity.ResultsThe key output of our collaboration was the model itself rather than the results of any of the scenarios. The model allows a user to understand the excess mortality impact arising as a direct consequence of capacity being breached under various scenarios or forecasts of hospital admissions. The scenarios described in this paper are illustrative and are not forecasts.There were no excess deaths from a lack of capacity in any of the ‘Optimistic’ scenario applications in sensitivity analysis.Several of the ‘Middling’ scenario applications under sensitivity testing resulted in excess deaths directly attributable to a lack of capacity. Most excess deaths arose when we modelled a 20% reduction compared to best estimate ICU capacity. This led to 597 deaths (0.7% increase).All the ‘Pessimistic’ scenario applications under sensitivity analysis had excess deaths. These ranged from 49,219 (19.4% increase) when we modelled a 20% increase in ward bed availability over the best-estimate, to 103,845 (40.9% increase) when we modelled a 20% shortfall in ward bed availability below the best-estimate. The emergence of a new, more transmissible variant (VOC 202012/01) increases the likelihood of real world outcomes at, or beyond, those modelled in our ‘Pessimistic’ scenario.The results can be explained by considering how capacity evolves in each of the scenarios. In the Middling scenario, whilst ICU capacity may be approached and even possibly breached, there remains sufficient ward capacity to take lives who need either ward or ICU support, keeping excess deaths relatively low. However, the Pessimistic scenario sees ward capacity breached, and in many scenarios for a period of several weeks, resulting in much higher mortality in those lives who require care but do not receive it.ConclusionsNo excess deaths from breaching capacity would be expected under the unadjusted ‘Optimistic’ assumptions of demand. The ‘Middling’ scenario could result in some excess deaths from breaching capacity, though these would be small (0.7% increase) relative to the total number of deaths in that scenario. The ‘Pessimistic’ scenario would certainly result in significant excess deaths from breaching capacity. Our sensitivity analysis indicated a range between 49,219 (19.4% increase) and 103,845 (40.9% increase) excess deaths.Without the new variant, exceeding capacity for hospital and ICU beds did not appear to be the most likely outcome but given the new variant it now appears more plausible and, if so, would result in a substantial increase in the number of deaths from COVID-19.

Keller Army Community Hospital, a 12-bed community hospital located in the Hudson Valley of New York State, within the pandemic epicenter anticipated the surge of critically ill patients, which would overwhelm local resources during the coronavirus pandemic sweeping across the globe. In this facility, there were no Intensive Care Unit (ICU) beds and resources were mobilized in order to create a negative pressure Corona Virus Unit (CVU) consisting of seven ICU beds and two step-down beds. Although the creation of the CVU decreased the non-COVID inpatient capacity to five beds, the hospital also formulated a plan to expand overall bed capacity from 12 inpatient beds to 45 beds within 24 hours.To create a ICU embedded within a CVU and implement a three day curriculum to prepare four mixed teams of critical care and non-critical care staff nurses to manage critically ill patients with the novel coronavirus disease 2019 (COVID-19).Nursing leaders and hospital education staff developed a critical care curriculum utilizing Elsevier didactic, the DoD COVID-19 Practice Guide, and hands-on training for 34 nurses.1,2 Nurses had varied scope of practice levels from licensed practical nurses to advance practice nurses, with diverse critical care expertise to non-critical care nursing staff from the primary care medical home (PCMH), all of which participated in the cross-leveling to the CVU unit during the pandemic response. Educational elements included PPE donning and doffing, mechanical ventilation, central venous catheter maintenance, arterial catheter management, hemodynamics, and critical care pharmacotherapy. A medical model skills station with common critical care equipment such as ventilators allowed for instantaneous feedback and 13 hands-on skills training.A fully functional ICU and CVU was created with thirty-four nurses who completed training within seven days with a didactic completing rate of 94.65 % and 100% hands-on skills. The program endures with monthly tailored re-fresher training to improve efficiency and maintain critical competencies. The team maintained operational readiness through the surge and remain resolute for the next surge.On-going program execution and evaluation continues to develop new staff members due to permanent change of station, recent on-boarding, or because of evidence based clinical guideline changes. Training has continued, but shifted to include normal inpatient operations over the summer of 2020. Re-fresher classes covering the treatment and care of COVID patients continue with the anticipation of a second wave surge of COVID-19 cases emerges this fall based on epidemiology predictions.