Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models.

BACKGROUND: Seasonal influenza places a substantial burden annually on healthcare services. Policies during the COVID-19 pandemic limited the transmission of seasonal influenza, making the timing and magnitude of a potential resurgence difficult to ascertain and its impact important to forecast. METHODS: We have developed a hierarchical generalised additive model (GAM) for the short-term forecasting of hospital admissions with a positive test for the influenza virus sub-regionally across England. The model incorporates a multi-level structure of spatio-temporal splines, weekly cycles in admissions, and spatial correlation. Using multiple performance metrics including interval score, coverage, bias, and median absolute error, the predictive performance is evaluated for the 2022-2023 seasonal wave. Performance is measured against autoregressive integrated moving average (ARIMA) and Prophet time series models. RESULTS: Across the epidemic phases the hierarchical GAM shows improved performance, at all geographic scales relative to the ARIMA and Prophet models. Temporally, the hierarchical GAM has overall an improved performance at 7 and 14 day time horizons. The performance of the GAM is most sensitive to the flexibility of the smoothing function that measures the national epidemic trend. CONCLUSIONS: This study introduces an approach to short-term forecasting of hospital admissions for the influenza virus using hierarchical, spatial, and temporal components. The methodology was designed for the real time forecasting of epidemics. This modelling framework was used across the 2022-2023 winter for healthcare operational planning by the UK Health Security Agency and the National Health Service in England.

Seasonal influenza causes a burden for hospitals and therefore it is useful to be able to accurately predict how many patients might be admitted with the disease. We attempted to predict influenza admissions up to 14 days in the future by creating a computational model that incorporates how the disease is reported and how it spreads. We evaluated our optimised model on data acquired during the winter of 2022-2023 data in England and compared it with previously developed models. Our model was better at modelling how influenza spreads and predicting future hospital admissions than the models we compared it to. Improving how influenza admissions are forecast can enable hospitals to prepare better for increased admissions, enabling improved treatment and reduced death for all patients in hospital over winter.

Indirect effect of the COVID-19 pandemic on hospital mortality in patients with hip fracture: a competing risk survival analysis using linked administrative data.

BACKGROUND: Hip fracture is a leading cause of disability and mortality among older people. During the COVID-19 pandemic, orthopaedic care pathways in the National Health Service in England were restructured to manage pressures on hospital capacity. We examined the indirect consequences of the pandemic for hospital mortality among older patients with hip fracture, admitted from care homes or the community. METHODS: Retrospective analysis of linked care home and hospital inpatient data for patients with hip fracture aged 65 years and over admitted to hospitals in England during the first year of the pandemic (1 March 2020 to 28 February 2021) or during the previous year. We performed survival analysis, adjusting for case mix and COVID-19 infection, and considered live discharge as a competing risk. We present cause-specific hazard ratios (HRCS) for the effect of admission year on hospital mortality risk. RESULTS: During the first year of the pandemic, there were 55 648 hip fracture admissions: a 5.2% decrease on the previous year. 9.5% of patients had confirmed or suspected COVID-19. Hospital stays were substantially shorter (p<0.05), and there was a higher daily chance of discharge (HRCS 1.40, 95% CI 1.38 to 1.41). Overall hip fracture inpatient mortality increased (7.2% in 2020/2021 vs 6.4% in 2019/2020), but patients without concomitant COVID-19 infection had lower mortality rates compared with the year before (5.3%). Admission during the pandemic was associated with a 11% increase in the daily risk of hospital death for patients with hip fracture (HRCS 1.11, 95% CI 1.05 to 1.16). CONCLUSIONS: Although COVID-19 infections led to increases in hospital mortality, overall hospital mortality risk for older patients with hip fracture remained largely stable during the first year of the pandemic.

Associations between multiple long-term conditions and mortality in diverse ethnic groups.

BACKGROUND: Multiple conditions are more prevalent in some minoritised ethnic groups and are associated with higher mortality rate but studies examining differential mortality once conditions are established is US-based. Our study tested whether the association between multiple conditions and mortality varies across ethnic groups in England. METHODS AND FINDINGS: A random sample of primary care patients from Clinical Practice Research Datalink (CPRD) was followed from 1st January 2015 until 31st December 2019. Ethnicity, usually self-ascribed, was obtained from primary care records if present or from hospital records. Long-term conditions were counted from a list of 32 that have previously been associated with greater primary care, hospital admissions, or mortality risk. Cox regression models were used to estimate mortality by count of conditions, ethnicity and their interaction, with adjustment for age and sex for 532,059 patients with complete data. During five years of follow-up, 5.9% of patients died. Each additional condition at baseline was associated with increased mortality. The direction of the interaction of number of conditions with ethnicity showed a statistically higher mortality rate associated with long-term conditions in Pakistani, Black African, Black Caribbean and Other Black ethnic groups. In ethnicity-stratified models, the mortality rate per additional condition at age 50 was 1.33 (95% CI 1.31,1.35) for White ethnicity, 1.43 (95% CI 1.26,1.61) for Black Caribbean ethnicity and 1.78 (95% CI 1.41,2.24) for Other Black ethnicity. CONCLUSIONS: The higher mortality rate associated with having multiple conditions is greater in minoritised compared with White ethnic groups. Research is now needed to identify factors that contribute to these inequalities. Within the health care setting, there may be opportunities to target clinical and self-management support for people with multiple conditions from minoritised ethnic groups.

Impact of non-pharmaceutical interventions on SARS-CoV-2 outbreaks in English care homes: a modelling study.

BACKGROUND: COVID-19 outbreaks still occur in English care homes despite the interventions in place. METHODS: We developed a stochastic compartmental model to simulate the spread of SARS-CoV-2 within an English care home. We quantified the outbreak risk with baseline non-pharmaceutical interventions (NPIs) already in place, the role of community prevalence in driving outbreaks, and the relative contribution of all importation routes into a fully susceptible care home. We also considered the potential impact of additional control measures in care homes with and without immunity, namely: increasing staff and resident testing frequency, using lateral flow antigen testing (LFD) tests instead of polymerase chain reaction (PCR), enhancing infection prevention and control (IPC), increasing the proportion of residents isolated, shortening the delay to isolation, improving the effectiveness of isolation, restricting visitors and limiting staff to working in one care home. We additionally present a Shiny application for users to apply this model to their facility of interest, specifying care home, outbreak and intervention characteristics. RESULTS: The model suggests that importation of SARS-CoV-2 by staff, from the community, is the main driver of outbreaks, that importation by visitors or from hospitals is rare, and that the past testing strategy (monthly testing of residents and daily testing of staff by PCR) likely provides negligible benefit in preventing outbreaks. Daily staff testing by LFD was 39% (95% 18-55%) effective in preventing outbreaks at 30 days compared to no testing. CONCLUSIONS: Increasing the frequency of testing in staff and enhancing IPC are important to preventing importations to the care home. Further work is needed to understand the impact of vaccination in this population, which is likely to be very effective in preventing outbreaks.

Categorising high-cost high-need children and young people.

OBJECTIVES: To describe the characteristics of high-cost high-need children and young people (CYP) (0-24 years) in England. METHODS: Retrospective observational study using data from the Clinical Practice Research Database linked to Hospital Episode Statistics in 2014/2015 and 2015/2016. Healthcare utilisation of primary and secondary care services were calculated, and costs were estimated using Healthcare Resource Group for secondary care and Personal Social Services Research Unit for primary care. High-cost high-need CYP were defined as the top 5% of users by cost. RESULTS: 3891 of 73 392 CYP made up the top 5% that were classified as high-cost high-need, and this group accounted for 54% of total annual costs. In this population, 7.3% were males <5 years and 11.0% were females 20-24 years. Inpatient care (acute) accounted for 63% of known spending in high-cost high-need patients. Total mean monthly cost per patient was 22.7 times greater in the high-cost high-need group compared with all other patients (£4417 vs £195). 29% of CYP in the high-cost high-need group in 2014/2015 were also classified as high-cost high-need in the following year. CONCLUSIONS: These findings indicate the importance of further understanding and anticipating trends in CYP health spending to optimise care, reduce costs and inform new models of care. This includes integrated services, a further look into societal factors in reducing health inequalities and a particular focus of mental health services, the demand of which increases with age.

A methodology for identifying high-need, high-cost patient personas for international comparisons.

OBJECTIVE: To establish a methodological approach to compare two high-need, high-cost (HNHC) patient personas internationally. DATA SOURCES: Linked individual-level administrative data from the inpatient and outpatient sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States. STUDY DESIGN: We outline a methodological approach to identify HNHC patient types for international comparisons that reflect complex, priority populations defined by the National Academy of Medicine. We define two patient profiles using accessible patient-level datasets linked across different domains of care-hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, long-term care, home-health care, and outpatient drugs. The personas include a frail older adult with a hip fracture with subsequent hip replacement and an older person with complex multimorbidity, including heart failure and diabetes. We demonstrate their comparability by examining the characteristics and clinical diagnoses captured across countries. DATA COLLECTION/EXTRACTION METHODS: Data collected by ICCONIC partners. PRINCIPAL FINDINGS: Across 11 countries, the identification of HNHC patient personas was feasible to examine variations in healthcare utilization, spending, and patient outcomes. The ability of countries to examine linked, individual-level data varied, with the Netherlands, Canada, and Germany able to comprehensively examine care across all seven domains, whereas other countries such as England, Switzerland, and New Zealand were more limited. All countries were able to identify a hip fracture persona and a heart failure persona. Patient characteristics were reassuringly similar across countries. CONCLUSION: Although there are cross-country differences in the availability and structure of data sources, countries had the ability to effectively identify comparable HNHC personas for international study. This work serves as the methodological paper for six accompanying papers examining differences in spending, utilization, and outcomes for these personas across countries.

International comparison of health spending and utilization among people with complex multimorbidity.

OBJECTIVE: The objective of this study was to explore cross-country differences in spending and utilization across different domains of care for a multimorbid persona with heart failure and diabetes. DATA SOURCES: We used individual-level administrative claims or registry data from inpatient and outpatient health care sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States (US). DATA COLLECTION/EXTRACTION METHODS: Data collected by ICCONIC partners. STUDY DESIGN: We retrospectively analyzed age-sex standardized utilization and spending of an older person (65-90 years) hospitalized with a heart failure exacerbation and a secondary diagnosis of diabetes across five domains of care: hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, and outpatient drugs. PRINCIPAL FINDINGS: Sample sizes ranged from n = 1270 in Spain to n = 21,803 in the United States. Mean age (standard deviation [SD]) ranged from 76.2 (5.6) in the Netherlands to 80.3 (6.8) in Sweden. We observed substantial variation in spending and utilization across care settings. On average, England spent $10,956 per person in hospital care while the United States spent $30,877. The United States had a shorter length of stay over the year (18.9 days) compared to France (32.9) and Germany (33.4). The United States spent more days in facility-based rehabilitative care than other countries. Australia spent $421 per person in primary care, while Spain (Aragon) spent $1557. The United States and Canada had proportionately more visits to specialist providers than primary care providers. Across almost all sectors, the United States spent more than other countries, suggesting higher prices per unit. CONCLUSION: Across 11 countries, there is substantial variation in health care spending and utilization for a complex multimorbid persona with heart failure and diabetes. Drivers of spending vary across countries, with the United States being the most expensive country due to high prices and higher use of facility-based rehabilitative care.

Differences in health outcomes for high-need high-cost patients across high-income countries.

OBJECTIVE: This study explores variations in outcomes of care for two types of patient personas-an older frail person recovering from a hip fracture and a multimorbid older patient with congestive heart failure (CHF) and diabetes. DATA SOURCES: We used individual-level patient data from 11 health systems. STUDY DESIGN: We compared inpatient mortality, mortality, and readmission rates at 30, 90, and 365 days. For the hip fracture persona, we also calculated time to surgery. Outcomes were standardized by age and sex. DATA COLLECTION/EXTRACTION METHODS: Data was compiled by the International Collaborative on Costs, Outcomes and Needs in Care across 11 countries for the years 2016-2017 (or nearest): Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States. PRINCIPAL FINDINGS: The hip sample across ranged from 1859 patients in Aragon, Spain, to 42,849 in France. Mean age ranged from 81.2 in Switzerland to 84.7 in Australia, and the majority of hip patients across countries were female. The congestive heart failure (CHF) sample ranged from 742 patients in England to 21,803 in the United States. Mean age ranged from 77.2 in the United States to 80.3 in Sweden, and the majority of CHF patients were males. Average in-hospital mortality across countries was 4.1%. for the hip persona and 6.3% for the CHF persona. At the year mark, the mean mortality across all countries was 25.3% for the hip persona and 32.7% for CHF persona. Across both patient types, England reported the highest mortality at 1 year followed by the United States. Readmission rates for all periods were higher for the CHF persona than the hip persona. At 30 days, the average readmission rate for the hip persona was 13.8% and 27.6% for the CHF persona. CONCLUSION: Across 11 countries, there are meaningful differences in health system outcomes for two types of patients.

Differences in health care spending and utilization among older frail adults in high-income countries: ICCONIC hip fracture persona.

OBJECTIVE: This study explores differences in spending and utilization of health care services for an older person with frailty before and after a hip fracture. DATA SOURCES: We used individual-level patient data from five care settings. STUDY DESIGN: We compared utilization and spending of an older person aged older than 65 years for 365 days before and after a hip fracture across 11 countries and five domains of care as follows: acute hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, and outpatient drugs. Utilization and spending were age and sex standardized.. DATA COLLECTION/EXTRACTION METHODS: The data were compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries as follows: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States. PRINCIPAL FINDINGS: The sample ranged from 1859 patients in Spain to 42,849 in France. Mean age ranged from 81.2 in Switzerland to 84.7 in Australia. The majority of patients across countries were female. Relative to other countries, the United States had the lowest inpatient length of stay (11.3), but the highest number of days were spent in post-acute care rehab (100.7) and, on average, had more visits to specialist providers (6.8 per year) than primary care providers (4.0 per year). Across almost all sectors, the United States spent more per person than other countries per unit ($13,622 per hospitalization, $233 per primary care visit, $386 per MD specialist visit). Patients also had high expenditures in the year prior to the hip fracture, mostly concentrated in the inpatient setting. CONCLUSION: Across 11 high-income countries, there is substantial variation in health care spending and utilization for an older person with frailty, both before and after a hip fracture. The United States is the most expensive country due to high prices and above average utilization of post-acute rehab care.

Primary care consultation length by deprivation and multimorbidity in England: an observational study using electronic patient records.

BACKGROUND: Longer GP consultations are recommended as one way of improving care for people with multimorbidity. In Scotland, patients who are multimorbid and living in deprived areas do not have longer consultations, although their counterparts in the least deprived areas do. This example of the inverse care law has not been examined in England. AIM: To assess GP consultation length by socioeconomic deprivation and multimorbidity. DESIGN AND SETTING: Random sample of 1.2 million consultations from 1 April 2014 to 31 March 2016 for 190 036 adults in England drawn from the Clinical Practice Research Datalink. METHOD: Consultation duration was derived from time of opening and closing the patient's electronic record. Mean duration was estimated by multimorbidity level and type, adjusted for number of consultations and other patient and staff characteristics and patient and practice random effects. RESULTS: Consultations lasted 10.9 minutes on average and mean duration increased with number of conditions. Patients with ≥6 conditions had 0.9 (95% confidence interval [CI] = 0.8 to 1.0) minutes longer than those with none. Patients who are multimorbid and with a mental health condition had 0.5 (CI = 0.4 to 0.5) minutes longer than patients who were not multimorbid. However, consultations were 0.5 (CI = 0.4 to 0.5) minutes shorter in the most compared with the least deprived fifth of areas at all levels of multimorbidity. CONCLUSION: GPs in England spend longer with patients who have more conditions, but, at all multimorbidity levels, those in deprived areas have less time per GP consultation. Further research is needed to assess the impact of consultation length on patient and system outcomes for those with multimorbidity.

Healthcare utilization among migrants to the UK: cross-sectional analysis of two national surveys.

OBJECTIVE: To contribute objective evidence on health care utilization among migrants to the UK to inform policy and service planning. METHODS: We analysed data from Understanding Society, a household survey with fieldwork from 2015 to 2017, and the European Health Interview Survey with data collected between 2013 and 2014. We explored health service utilization among migrants to the UK across primary care, inpatient admissions and maternity care, outpatient care, mental health, dental care and physiotherapy. We adjusted for age, sex, long-term health conditions and time since moving to the UK. RESULTS: Health care utilization among migrants to the UK was lower than utilization among the UK-born population for all health care dimensions except inpatient admissions for childbirth; odds ratio (95%CI) range 0.58 (0.50-0.68) for dental care to 0.88 (0.78-0.98) for primary care). After adjusting for differences in age and self-reported health, these differences were no longer observed, except for dental care (odds ratio 0.57, 95%CI 0.49-0.66, P < 0.001). Across primary care, outpatient and inpatient care, utilization was lower among those who had recently migrated, increasing to the levels of the nonmigrant population after 10 years or more since migrating to the UK. CONCLUSIONS: This study finds that newly arrived migrants tend to utilize less health care than the UK population and that this pattern was at least partly explained by better health, and younger age. Our findings contribute nationally representative evidence to inform public debate and decision-making on migration and health.

Multiple long-term conditions within households and use of health and social care: a retrospective cohort study.

BACKGROUND: The daily management of long-term conditions falls primarily on individuals and informal carers, but the impact of household context on health and social care activity among people with multiple long-term conditions (MLTCs) is understudied. AIM: To test whether co-residence with a person with MLTCs (compared with a co-resident without MLTCs) is associated with utilisation and cost of primary, community, secondary health care, and formal social care. DESIGN & SETTING: Linked data from health providers and local government in Barking and Dagenham for a retrospective cohort of people aged ≥50 years in two-person households in 2016-2018. METHOD: Two-part regression models were applied to estimate annualised use and cost of hospital, primary, community, mental health, and social care by MLTC status of individuals and co-residents, adjusted for age, sex, and deprivation. Applicability at the national level was tested using the Clinical Practice Research Datalink (CPRD). RESULTS: Forty-eight per cent of people with MLTCs in two-person households were co-resident with another person with MLTCs. They were 1.14 (95% confidence interval [CI] = 1.00 to 1.30) times as likely to have community care activity and 1.24 (95% CI = 0.99 to 1.54) times as likely to have mental health care activity compared with those co-resident with a healthy person. They had more primary care visits (8.5 [95% CI = 8.2 to 8.8] versus 7.9 [95% CI = 7.7 to 8.2]) and higher primary care costs. Outpatient care and elective admissions did not differ. Findings in national data were similar. CONCLUSION: Care utilisation for people with MLTCs varies by household context. There may be potential for connecting health and community service input across household members.

Optimal national prioritization policies for hospital care during the SARS-CoV-2 pandemic.

In response to unprecedented surges in the demand for hospital care during the SARS-CoV-2 pandemic, health systems have prioritized patients with COVID-19 to life-saving hospital care to the detriment of other patients. In contrast to these ad hoc policies, we develop a linear programming framework to optimally schedule elective procedures and allocate hospital beds among all planned and emergency patients to minimize years of life lost. Leveraging a large dataset of administrative patient medical records, we apply our framework to the National Health Service in England and show that an extra 50,750-5,891,608 years of life can be gained compared with prioritization policies that reflect those implemented during the pandemic. Notable health gains are observed for neoplasms, diseases of the digestive system, and injuries and poisoning. Our open-source framework provides a computationally efficient approximation of a large-scale discrete optimization problem that can be applied globally to support national-level care prioritization policies.

Hospital admissions from care homes in England during the COVID-19 pandemic: a retrospective, cross-sectional analysis using linked administrative data.

BACKGROUND: Care home residents have complex healthcare needs but may have faced barriers to accessing hospital treatment during the first wave of the COVID-19 pandemic. OBJECTIVES: To examine trends in the number of hospital admissions for care home residents during the first months of the COVID-19 outbreak. METHODS: Retrospective analysis of a national linked dataset on hospital admissions for residential and nursing home residents in England (257,843 residents, 45% in nursing homes) between 20 January 2020 and 28 June 2020, compared to admissions during the corresponding period in 2019 (252,432 residents, 45% in nursing homes). Elective and emergency admission rates, normalised to the time spent in care homes across all residents, were derived across the first three months of the pandemic between 1 March and 31 May 2020 and primary admission reasons for this period were compared across years. RESULTS: Hospital admission rates rapidly declined during early March 2020 and remained substantially lower than in 2019 until the end of June. Between March and May, 2,960 admissions from residential homes (16.2%) and 3,295 admissions from nursing homes (23.7%) were for suspected or confirmed COVID-19. Rates of other emergency admissions decreased by 36% for residential and by 38% for nursing home residents (13,191 fewer admissions in total). Emergency admissions for acute coronary syndromes fell by 43% and 29% (105 fewer admission) and emergency admissions for stroke fell by 17% and 25% (128 fewer admissions) for residential and nursing home residents, respectively. Elective admission rates declined by 64% for residential and by 61% for nursing home residents (3,762 fewer admissions). CONCLUSIONS: This is the first study showing that care home residents' hospital use declined during the first wave of COVID-19, potentially resulting in substantial unmet health need that will need to be addressed alongside ongoing pressures from COVID-19.

The health and cost burden of antibiotic resistant and susceptible Escherichia coli bacteraemia in the English hospital setting: A national retrospective cohort study.

INTRODUCTION: Antibiotic resistance poses a threat to public health and healthcare systems. Escherichia coli causes more bacteraemia episodes in England than any other bacterial species. This study aimed to estimate the burden of E. coli bacteraemia and associated antibiotic resistance in the secondary care setting. MATERIALS AND METHODS: This was a retrospective cohort study, with E. coli bacteraemia as the main exposure of interest. Adult hospital in-patients, admitted to acute NHS hospitals between July 2011 and June 2012 were included. English national surveillance and administrative datasets were utilised. Cox proportional hazard, subdistribution hazard and multistate models were constructed to estimate rate of discharge, rate of in-hospital death and excess length of stay, with a unit bed day cost applied to the latter to estimate cost burden from the healthcare system perspective. RESULTS: 14,042 E. coli bacteraemia and 8,919,284 non-infected inpatient observations were included. E. coli bacteraemia was associated with an increased rate of in-hospital death across all models, with an adjusted subdistribution hazard ratio of 5.88 (95% CI: 5.62-6.15). Resistance was not found to be associated with in-hospital mortality once adjusting for patient and hospital covariates. However, resistance was found to be associated with an increased excess length of stay. This was especially true for third generation cephalosporin (1.58 days excess length of stay, 95% CI: 0.84-2.31) and piperacillin/tazobactam resistance (1.23 days (95% CI: 0.50-1.95)). The annual cost of E. coli bacteraemia was estimated to be £14,346,400 (2012 £), with third-generation cephalosporin resistance associated with excess costs per infection of £420 (95% CI: 220-630). CONCLUSIONS: E. coli bacteraemia places a statistically significant burden on patient health and the hospital sector in England. Resistance to front-line antibiotics increases length of stay; increasing the cost burden of such infections in the secondary care setting.

The implications of high bed occupancy rates on readmission rates in England: A longitudinal study.

Hospital bed occupancy rates in the English National Health Service have risen to levels considered clinically unsafe. This study assesses the association of increased bed occupancy with changes in the percentage of overnight patients discharged from hospital on a given day, and their subsequent 30-day readmission rate. Longitudinal panel data methods are used to analyse secondary care records (n = 4,193,590) for 136 non-specialist Trusts between April 2014 and February 2016. The average bed occupancy rate across the study period was 90.4%. A 1% increase in bed occupancy was associated with a 0.49% rise in the discharge rate, and a 0.011% increase in the 30-day readmission rate for discharged patients. These associations became more pronounced once bed occupancy exceeded 95%. When bed occupancy rates were high, hospitals discharged a greater proportion of their patients. Those were mostly younger and less clinically complex, suggesting that hospitals are successfully prioritising early discharge amongst least vulnerable patients. However, while increased bed occupancy was not associated with a substantial increase in overall 30-day readmission rates, the relationship was more pronounced in older and sicker patients, indicating possible links with short-fallings in discharge processes.

A challenge to all. A primer on inter-country differences of high-need, high-cost patients.

BACKGROUND: Across countries, a small group of patients accounts for the majority of health care spending. These patients are more likely than other patients to experience problems with quality and safety in their care, suggesting that efforts targeting efficiency and quality among this population might have significant payoffs for health systems. Better understanding of similarities and differences in patient characteristics and health care use in different countries may ultimately inform further efforts to improve care for HNHC patients in these health systems. METHODS: We conducted a cross-sectional descriptive study using one year of patient-level data on high-cost patients in seven high-income OECD member countries. Countries were selected based on availability of detailed information (large enough samples of claims, administrative, and survey data of high-cost patients). We studied concentration of spending among high-cost patients, characteristics of high-cost patients, and per capita spending on high-cost patients. FINDINGS: Cost-concentration of the top 5% of patients varied across countries, from 41% in Japan to 60% in Canada, driven primarily by variation in the top 1% of spenders. In general, high-cost patients were more likely to be female (57.7% on average), had a significant number of multi-morbidities (up to on average 10 major diagnostic categories (ICD chapters), and had a lower socioeconomic status. Characteristics of high-cost patients varied as well: median age ranged from 62 in the Netherlands to 75 in Germany and the difference in socioeconomic status is particularly stark in the US. Lastly, utilization, particularly for inpatient care, varied with an average number of inpatient days ranging from 6.6 nights (US) to 97.7 nights in Japan. INTERPRETATION: In this descriptive study, there is substantial variation in the cost concentration, characteristics, and per capita spending on high-cost patient populations across high-income countries. Differences in the way that health systems are structured likely explains some of this variation, which suggests the potential of cross-system learning opportunities. Our findings highlight the need for further studies including comparable performance metrics and institutional analysis.