How many beds? Capacity implications of hospital care demand projections in the Irish hospital system, 2015-2030

"They say they listen. But do they really listen?": A qualitative study of hospital doctors' experiences of organisational deafness, disconnect and denial

The sharing of information and feedback directly from service-providing staff to healthcare organisational management is vital for organisational culture and service improvement. However, hospital doctors report feeling unable to communicate effectively with management to provide evidence and affect improvement, and this can impact job satisfaction, workplace relations, service delivery and ultimately patient safety. In this paper, we draw on data elicited from a Mobile Instant Messaging Ethnography (MIME) study involving 28 hospital doctors working in Irish hospitals, to explore the barriers preventing them from speaking up and effecting change, and the impact of this on staff morale and services. We identify three major barriers, consistent with previous literature, to effective feedback and communication: (1) organisational deafness, (2) disconnect between managers and frontline staff, and (3) denial of the narratives and issues raised. We draw these together to identify key implications from these findings for healthcare managers, and suggest policy and practice improvements.

Perceived barriers and facilitators to good end of life care: Focusing on people with intellectual disabilities

BACKGROUND

People with intellectual disabilities are often left out of research on important topics. This exploratory study investigated their views on barriers and facilitators to accessing care at end of life, both at home and in a hospice setting.

METHOD

This qualitative study used reflexive thematic analysis. Two focus groups were held via Zoom with a total of four participants.

RESULTS

Three themes were produced: Unsettling Transitions, Maintaining Familiarity, and Respecting People's Wishes. Keeping things as unchanged as possible at end of life was highlighted as an ideal. Respecting people's wishes and education were highlighted as facilitators to good end of life care.

CONCLUSIONS

The themes identified in this study highlight the fears and wishes of this population with regards to receiving quality end of life care. Training for staff and families, as well as advanced care planning, could focus on enhancing facilitators and decreasing barriers for this population.

COVID-19 community assessment hubs in Ireland: A study of staff and patient perceptions of their value

BACKGROUND

Critical care bed capacity per capita in Ireland is among the lowest in Europe. The COVID-19 pandemic has put additional strain on an over-stretched healthcare system. COVID-19 community assessment hubs (CAHs) were established to prevent unnecessary admission to acute hospitals and to reduce infection spread.

OBJECTIVE

The aim of this study was to assess the effectiveness and acceptability of CAHs and identify how the service might be improved or adapted for possible future use.

DESIGN

This was a mixed methods study, incorporating co-design with clinical stakeholders. Data collection was via an online survey and semistructured telephone interviews with staff and patients conducted between January and May 2021.

SETTING AND PARTICIPANTS

Thirty-one patients completed the survey and nine were interviewed. Twenty interviews were conducted with staff.

RESULTS

The findings suggest that the CAH model was successful in providing a dedicated pathway for assessing patients with COVID-19 symptoms, whilst mitigating the risk of infection. Patients were particularly positive about the timely, comprehensive and holistic care they received, as well as the accessibility of the clinics and the friendly attitudes of the staff. Staff welcomed the training and clinical protocols which contributed to their feelings of safety and competency in delivering care to this cohort of patients. They also highlighted the benefits of working in a multidisciplinary environment. Both staff and patients felt that the hubs could be repurposed for alternative use, including the treatment of chronic diseases.

DISCUSSION

This study describes staff and patients' experiences of these hubs. An unexpected outcome of this study is its demonstration of the true value of effective multidisciplinary working, not only for the staff who were deployed to this service but also for the patients in receipt of care in these hubs.

CONCLUSION

This multidisciplinary patient-centred service may provide a useful model for the delivery of other services currently delivered in hospital settings.

PATIENT OR PUBLIC CONTRIBUTION

An earlier phase of this study involved interviews with COVID-19-positive patients on a remote monitoring programme. The data informed this phase. Several of the authors had worked in the CAHs and provided valuable input into the design of the staff and patient interviews.

A Model to Compare International Hospital Bed Numbers, including a Case Study on the Role of Indigenous People on Acute 'Occupied' Bed Demand in Australian States

Comparing international or regional hospital bed numbers is not an easy matter, and a pragmatic method has been proposed that plots the number of beds per 1000 deaths versus the log of deaths per 1000 population. This method relies on the fact that 55% of a person's lifetime hospital bed utilization occurs in the last year of life-irrespective of the age at death. This is called the nearness to death effect. The slope and intercept of the logarithmic relationship between the two are highly correlated. This study demonstrates how lines of equivalent bed provision can be constructed based on the value of the intercept. Sweden looks to be the most bed-efficient country due to long-term investment in integrated care. The potential limitations of the method are illustrated using data from English Clinical Commissioning Groups. The main limitation is that maternity, paediatric, and mental health care do not conform to the nearness to death effect, and hence, the method mainly applies to adult acute care, especially medical and critical care bed numbers. It is also suggested that sensible comparison can only be made by comparing levels of occupied beds rather than available beds. Occupied beds measure the expressed bed demand (although often constrained by access to care issues), while available beds measure supply. The issue of bed supply is made complex by the role of hospital size on the average occupancy margin. Smaller hospitals are forced to operate at a lower average occupancy; hence, countries with many smaller hospitals such as Germany and the USA appear to have very high numbers of available beds. The so-called 85% occupancy rule is an "urban myth" and has no fundamental basis whatsoever. The very high number of "hospital" beds in Japan is simply an artefact arising from "nursing home" beds being counted as a "hospital" bed in this country. Finally, the new method is applied to the expressed demand for occupied acute beds in Australian states. Using data specific to acute care, i.e., excluding mental health and maternity, a long-standing deficit of beds was identified in Tasmania, while an unusually high level of occupied beds in the Northern Territory (NT) was revealed. The high level of demand for beds in the NT appears due to an exceptionally large population of indigenous people in this state, who are recognized to have elevated health care needs relative to non-indigenous Australians. In this respect, indigenous Australians use 3.5 times more occupied bed days per 1000 deaths (1509 versus 429 beds per 1000 deaths) and 6 times more occupied bed days per 1000 population (90 versus 15 beds per 1000 population) than their non-indigenous counterparts. The figure of 1509 beds per 1000 deaths (or 4.13 occupied beds per 1000 deaths) for indigenous Australians is indicative of a high level of "acute" nursing care in the last months of life, probably because nursing home care is not readily available due to remoteness. A lack of acute beds in the NT then results in an extremely high average bed occupancy rate with contingent efficiency and delayed access implications.

The impact of inpatient bed capacity on length of stay

OBJECTIVE

Large reductions in inpatient length of stay and inpatient bed supply have occurred across health systems in recent years. However, the direction of causation between length of stay and bed supply is often overlooked. This study examines the impact of changes to inpatient bed supply, as a result of recession-induced healthcare expenditure changes, on emergency inpatient length of stay in Ireland between 2010 and 2015.

STUDY DESIGN

We analyse all public hospital emergency inpatient discharges in Ireland from 2010 to 2015 using the administrative Hospital In-Patient Enquiry dataset. We use changes to inpatient bed supply across hospitals over time to examine the impact of bed supply on length of stay. Linear, negative binomial, and hospital-month-level fixed effects models are estimated.

RESULTS

U-shaped trends are observed for both average length of stay and inpatient bed supply between 2010 and 2015. A consistently large positive relationship is found between bed supply and length of stay across all regression analyses. Between 2010 and 2012 while length of stay fell by 6.4%, our analyses estimate that approximately 42% (2.7% points) of this reduction was associated with declines in bed supply.

CONCLUSION

Changes in emergency inpatient length of stay in Ireland between 2010 and 2015 were closely related to changes in bed supply during those years. The use of length of stay as an efficiency measure should be understood in the contextual basis of other health system changes. Lower length of stay may be indicative of the lack of resources or available bed supply as opposed to reduced demand for care or the shifting of care to other settings.

A retrospective cohort study of outcomes in hospitalised COVID-19 patients during the first pandemic wave in Ireland

Aim

Describe the epidemiology, resource use and adverse outcomes of COVID-19 patients hospitalised during wave 1 of the COVID-19 pandemic in Ireland. Use this data to identify specific cohorts at high risk of adverse outcomes and to inform acute hospital requirements for future COVID-19 waves in Ireland.

Methods

The Health Service Executive’s (HSE) Hospital Inpatient Enquiry (HIPE) system produced a daily database of COVID-19 discharge episodes from the onset of the COVID-19 pandemic in Ireland. This study analysed data on episodes of COVID-19 hospitalisation recorded between February 29 and July 31, 2020. A deterministic record linkage process transformed records from episode to patient level. Logistic regression modelling identified factors associated with long length of stay (LLOS), intensive care unit (ICU) admission and inhospital mortality.

Results

Median length of stay was 9 days; 12.8% of patients had ICU admission and 16.6% died in hospital. Male patients were more likely to have ICU admission and die in hospital. Likelihood of LLOS and inhospital mortality increased with age. Obesity, hypertension and diabetes were associated with ICU admission while chronic kidney disease and chronic obstructive pulmonary disease were associated with inhospital mortality. Nursing home residents were less likely to be admitted to ICU and more likely to die in hospital compared to patients admitted from home.

Conclusion

This study provides patient-level epidemiological characterisation of hospitalisations during the first COVID-19 pandemic wave in Ireland. The higher risk of adverse outcomes in older age groups supports the age-based prioritisation of COVID-19 vaccinations currently used in Ireland.

A mixed methods protocol to evaluate the effectiveness and acceptability of COVID-19 Community Assessment Hubs

Background: Ireland's health system has been under significant strain due to staff shortages and inadequate capacity. Critical care bed capacity per capita in Ireland is among the lowest in Europe, thus, the coronavirus disease 2019 (COVID-19) pandemic has put additional strain on an over-stretched system. COVID-19 Community Assessment Hubs (CAHs) were established to mitigate unnecessary admission to acute hospitals, and reduce infection spread by supporting COVID-19 positive or suspected positive patients to isolate at home, or in isolation facilities. There is some evidence that similar assessment centres may be a successful triage strategy to reduce burden on hospital and acute care. Aim : The aim of this study is to evaluate the impact of COVID-19 Community Assessment Hubs on service delivery in two regions in Ireland during the pandemic. Methods: A mixed-methods approach will be used, incorporating co-design to engage stakeholders and ensure informed data capture and analysis. Online surveys will assess CAH patients' experiences of access to and quality of care. Clinical patient data from CAHs will be collected and analysed using multinomial logistic regression to check for association with patient demographics and COVID-19 symptoms, and CAH early warning scores and outcomes (Transfer to Emergency Department, Transfer to isolation unit, Sent home with care plan). Semi-structured interviews will be conducted with: patients to elicit an in-depth understanding of experiences and acceptability of attending CAHs; and staff to understand challenges, benefits, and effectiveness of CAHs. Interview data will be analysed using thematic analysis. Discussion: This study will provide valuable insights from both patient and staff perspectives on the operation of CAHs. We will evaluate the effectiveness and acceptability of CAHs and propose areas for improvement of the service. This will contribute to international literature on the use of community assessment centres during infectious disease pandemics.

A mixed methods protocol to evaluate the effectiveness and acceptability of COVID-19 Community Assessment Hubs

Background: Ireland's health system has been under significant strain due to staff shortages and inadequate capacity. Critical care bed capacity per capita in Ireland is among the lowest in Europe, thus, the coronavirus disease 2019 (COVID-19) pandemic has put additional strain on an over-stretched system. COVID-19 Community Assessment Hubs (CAHs) were established to mitigate unnecessary admission to acute hospitals, and reduce infection spread by supporting COVID-19 positive or suspected positive patients to isolate at home, or in isolation facilities. There is some evidence that similar assessment centres may be a successful triage strategy to reduce burden on hospital and acute care. Aim : The aim of this study is to evaluate the impact of COVID-19 Community Assessment Hubs on service delivery in one region in Ireland. Methods: A mixed-methods approach will be used, incorporating co-design to engage stakeholders and ensure informed data capture and analysis. Online surveys will assess CAH patients' experiences of access to and quality of care. Clinical patient data from CAHs will be collected and analysed using multinomial logistic regression to check for association with patient demographics and COVID-19 symptoms, and CAH early warning scores and outcomes (Transfer to Emergency Department, Transfer to isolation unit, Sent home with care plan). Semi-structured interviews will be conducted with: patients to elicit an in-depth understanding of experiences and acceptability of attending CAHs; and staff to understand challenges, benefits, and effectiveness of CAHs. Interview data will be analysed using a thematic analysis approach. Discussion: This study will provide valuable insights from both patient and staff perspectives on the operation of CAHs. We will evaluate the effectiveness and acceptability of CAHs and propose areas for improvement of the service. This will contribute to international literature on the use of community assessment centres during infectious disease pandemics.

Does formal home care reduce inpatient length of stay?

Formal home care is an appropriate substitute for acute hospital care for many older people. However, limited empirical evidence exists on the extent of substitution between the supply of home care and hospital use. This study examines whether patients from areas with a better supply of home care have lower inpatient length of stay (LOS). We link administrative data on over 300,000 public hospital inpatient admissions in Ireland between 2012 and 2015 to region-year panel data on public home care supply. In addition to modeling average LOS, we estimate unconditional quantile regressions to examine whether home care supply has a disproportionately strong impact on long LOS. We find that inpatients from areas with higher per capita home care supply have lower average LOS; a 10% increase in home care is associated with a 1.2%-2.1% reduction in LOS. This result is driven by the subset of patients with the longest LOS, likely delayed discharges. Stronger results were found for stroke and hip fracture patients, who might be expected to have higher than average propensity to use home care services, and for patients from a region that experienced an unusually large increase in home care supply.

A Country Pandemic Risk Exposure Measurement Model

Purpose

The purpose of this study is to develop a Pandemic Risk Exposure Measurement (PREM) model to determine the factors that affect a country’s prospective vulnerability to a pandemic risk exposure also considering the current COVID-19 pandemic.

Methods

To develop the model, drew up an inventory of possible factor variables that might expose a country’s vulnerability to a pandemic such as COVID-19. This model was based on the analysis of existing literature and consultations with some experts and associations. To support the inventory of selected possible factor variables, we have conducted a survey with participants sampled from people working in a risk management environment carrying out a risk management function. The data were subjected to statistical analysis, specifically exploratory factor analysis and Cronbach Alpha to determine and group these factor variables and determine their reliability, respectively. This enabled the development of the PREM model. To eliminate possible bias, hierarchical regression analysis was carried out to examine the effect of the “Level of Experienced Hazard of the Participant (LEH)” considering also the “Level of Expertise and Knowledge about Risk and Risk Management (LEK)”.

Results

Exploratory factor analysis loaded best on four factors from 19 variables: Demographic Features, Country’s Activity Features, Economic Exposure and Societal Vulnerability (i.e. the PREM Model). This model explains 65.5% of the variance in the level of experienced hazard (LEH). Additionally, we determined that LEK explains only about 2% of the variance in LEH.

Conclusion

The developed PREM model shows that monitoring of Demographic Features, Country’s Activity Features, Economic Exposure and Societal Vulnerability can help a country to identify the possible impact of pandemic risk exposure and develop policies, strategies, regulations, etc., to help a country strengthen its capacity to meet the economic, social and in turn healthcare demands due to pandemic hazards such as COVID-19.

Would the United States Have Had Too Few Beds for Universal Emergency Care in the Event of a More Widespread Covid-19 Epidemic?

(1) Background: To evaluate the level of hospital bed numbers in U.S. states relative to other countries using a new method for evaluating bed numbers, and to determine if this is sufficient for universal health care during a major Covid-19 epidemic in all states (2) Methods: Hospital bed numbers in each state were compared using a new international comparison methodology. Covid-19 deaths per 100 hospital beds were used as a proxy for bed capacity pressures. (3) Results: Hospital bed numbers show large variation between U.S. states and half of the states have equivalent beds to those in developing countries. Relatively low population density in over half of US states appeared to have limited the spread of Covid-19 thus averting a potential major hospital capacity crisis. (4) Conclusions: Many U.S. states had too few beds to cope with a major Covid-19 epidemic, but this was averted by low population density in many states, which seemed to limit the spread of the virus.

The drivers and impact of emergency care reconfiguration in Ireland: Results from a large mixed-methods research programme

Ireland, like many countries, has reconfigured emergency care in recent years towards a more centralised model. Although centralisation is presented as 'evidence-based', the relevance of this evidence is challenged by groups which hold values beyond those implicit in the literature. The Study of the Impact of Reconfiguration on Emergency and Urgent Care Networks (SIREN) programme was funded to evaluate the development and performance of emergency and urgent care systems in Ireland. SIREN found that the drivers of reconfiguration in Ireland are based on safety and efficiency claims which are highly contestable. Reconfiguration was not associated with improvements in safety or efficiency and may have exacerbated the growing capacity challenges for acute hospitals. These findings are consistent with UK research. Our study adds to an emerging literature on the interaction between a narrow technocratic approach to health system planning and the perspectives of the public and patients.