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

Reasons for hospitalisation and cumulative mortality in people, 75 years or older, at high risk of hospital admission: a prospective study

BACKGROUND

A small proportion of the older population accounts for a high proportion of healthcare use. For effective use of limited healthcare resources, it is important to identify the group with greatest needs. The aim of this study was to explore frequency and reason for hospitalisation and cumulative mortality, in an older population at predicted high risk of hospital admission, and to assess if a prediction model can be used to identify individuals with the greatest healthcare needs. Furthermore, discharge diagnoses were explored to investigate if they can be used as basis for specific interventions in the high-risk group.

METHODS

All residents, 75 years or older, living in Östergötland, Sweden, on January 1st, 2017, were included. Healthcare data from 2016 was gathered and used by a validated prediction model to create risk scores for hospital admission. The population was then divided into groups by percentiles of risk. Using healthcare data from 2017-2018, two-year cumulative incidence of hospitalisation was analysed using Gray´s test. Cumulative mortality was analysed with the Kaplan-Meier method and primary discharge diagnoses were analysed with standardised residuals.

RESULTS

Forty thousand six hundred eighteen individuals were identified (mean age 82 years, 57.8% women). The cumulative incidence of hospitalisation increased with increasing risk of hospital admission (24% for percentiles < 60 to 66% for percentiles 95-100). The cumulative mortality also increased with increasing risk (7% for percentiles < 60 to 43% for percentiles 95-100). The most frequent primary discharge diagnoses for the population were heart diseases, respiratory infections, and hip injuries. The incidence was significantly higher for heart diseases and respiratory infections and significantly lower for hip injuries, for the population with the highest risk of hospital admission (percentiles 85-100).

CONCLUSIONS

Individuals 75 years or older, with high risk of hospital admission, were demonstrated to have considerable higher cumulative mortality as well as incidence of hospitalisation. The results support the use of the prediction model to direct resources towards individuals with highest risk scores, and thus, likely the greatest care needs. There were only small differences in discharge diagnoses between the risk groups, indicating that interventions to reduce hospitalisations should be personalised.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT03180606, first posted 08/06/2017.

Burden of delayed discharge on acute hospital medical wards: A retrospective ecological study in Rome, Italy

INTRODUCTION

Delayed discharge represents the difficulty in proceeding with discharge of patients who do not have any further benefit from prolonged stay. A quota of this problem is related to organizational issues. In the Lazio region in Italy, a macro service re-organization in on the way, with a network of hospital and territorial centers engaged in structuring in- and out- of hospital patient pathways, with a special focus on intermediate care structures. Purpose of this study is to quantify the burden of delayed discharge on a single hospital structure, in order to estimate costs and occurrence of potential resource misplacement.

MATERIAL AND METHODS

Observational Retrospective study conducted at the Santo Spirito Hospital in Rome, Italy. Observation period ranged from 1/09/2022, when the local database was instituted, to 1/03/2023 (6 months). Data from admissions records was anonymously collected. Data linkage with administrative local hospital database was performed in order to identify the date a discharge request was fired for each admission. Surgical discharges and Intensive Care Unit (ICU) discharges were excluded from this study. A Poisson hierarchical regression model was employed to investigate for the role of ward, Severity of Disease (SoD) and Risk of Mortality (RoM) on elongation of discharge time.

RESULTS

1222 medical ward admissions were recorded in the timeframe. 16% of them were considered as subject to potentially elongated stay, and a mean Delay in discharge of 6.3 days (SD 7.9) was observed.

DISCUSSION AND CONCLUSIONS

Delayed discharge may cause a "bottleneck" in admissions and result in overcrowded Emergency Department, overall poor performance, and increase in overall costs. A consisted proportion of available beds can get inappropriately occupied, and this inflates both direct and indirect costs. Clinical conditions on admission are not a good predictor of delay in discharge, and the root causes of this phenomenon likely lie in organizational issues (on structure\system level) and social issues (on patient's level).

Patient emergency health-care use before hospital admission for COVID-19 and long-term outcomes in Scotland: a national cohort study

BACKGROUND

It is unclear what effect the pattern of health-care use before admission to hospital with COVID-19 (index admission) has on the long-term outcomes for patients. We sought to describe mortality and emergency readmission to hospital after discharge following the index admission (index discharge), and to assess associations between these outcomes and patterns of health-care use before such admissions.

METHODS

We did a national, retrospective, complete cohort study by extracting data from several national databases and linking the databases for all adult patients admitted to hospital in Scotland with COVID-19. We used latent class trajectory modelling to identify distinct clusters of patients on the basis of their emergency admissions to hospital in the 2 years before the index admission. The primary outcomes were mortality and emergency readmission up to 1 year after index admission. We used multivariable regression models to explore associations between these outcomes and patient demographics, vaccination status, level of care received in hospital, and previous emergency hospital use.

FINDINGS

Between March 1, 2020, and Oct 25, 2021, 33 580 patients were admitted to hospital with COVID-19 in Scotland. Overall, the Kaplan-Meier estimate of mortality within 1 year of index admission was 29·6% (95% CI 29·1-30·2). The cumulative incidence of emergency hospital readmission within 30 days of index discharge was 14·4% (95% CI 14·0-14·8), with the number increasing to 35·6% (34·9-36·3) patients at 1 year. Among the 33 580 patients, we identified four distinct patterns of previous emergency hospital use: no admissions (n=18 772 [55·9%]); minimal admissions (n=12 057 [35·9%]); recently high admissions (n=1931 [5·8%]), and persistently high admissions (n=820 [2·4%]). Patients with recently or persistently high admissions were older, more multimorbid, and more likely to have hospital-acquired COVID-19 than patients with no or minimal admissions. People in the minimal, recently high, and persistently high admissions groups had an increased risk of mortality and hospital readmission compared with those in the no admissions group. Compared with the no admissions group, mortality was highest in the recently high admissions group (post-hospital mortality HR 2·70 [95% CI 2·35-2·81]; p<0·0001) and the risk of readmission was highest in the persistently high admissions group (3·23 [2·89-3·61]; p<0·0001).

INTERPRETATION

Long-term mortality and readmission rates for patients hospitalised with COVID-19 were high; within 1 year, one in three patients had died and a third had been readmitted as an emergency. Patterns of hospital use before index admission were strongly predictive of mortality and readmission risk, independent of age, pre-existing comorbidities, and COVID-19 vaccination status. This increasingly precise identification of individuals at high risk of poor outcomes from COVID-19 will enable targeted support.

FUNDING

Chief Scientist Office Scotland, UK National Institute for Health Research, and UK Research and Innovation.

Why the US spends more treating high-need high-cost patients: a comparative study of pricing and utilization of care in six high-income countries

One of the most pressing challenges facing most health care systems is rising costs. As the population ages and the demand for health care services grows, there is a growing need to understand the drivers of these costs across systems. This paper attempts to address this gap by examining utilization and spending of the course of a year for two specific high-need high-cost patient types: a frail older person with a hip fracture and an older person with congestive heart failure and diabetes. Data on utilization and expenditure is collected across five health care settings (hospital, post-acute rehabilitation, primary care, outpatient specialty and drugs), in six countries (Canada (Ontario), France, Germany, Spain (Aragon), Sweden and the United States (fee for service Medicare) and used to construct treatment episode Purchasing Power Parities (PPPs) that compare prices using baskets of goods from the different care settings. The treatment episode PPPs suggest other countries have more similar volumes of care to the US as compared to other standardization approaches, suggesting that US prices account for more of the differential in US health care expenditures. The US also differs with regards to the share of expenditures across care settings, with post-acute rehab and outpatient speciality expenditures accounting for a larger share of the total relative to comparators.

Identifying Characteristics Associated with the Concentration and Persistence of Medical Expenses among Middle-Aged and Elderly Adults: Findings from the China Health and Retirement Longitudinal Survey

Medical expenses, especially among middle-aged and elderly people, have increased in China over recent decades. However, few studies have analyzed the concentration or persistence of medical expenses among Chinese residents or vulnerable groups with longitudinal survey data. Based on the data of CHARLS (China Health and Retirement Longitudinal Study), this study sought to identify characteristics associated with the concentration and persistence of medical expenses among Chinese middle-aged and elderly adults and to help alleviate medical spending and the operational risk of social medical insurance. Concentration was measured using the cumulative percentages of ranked annual medical expenses and descriptive statistics were used to define the characteristics of individuals with high medical expenses. The persistence of medical expenses and associated factors were estimated using transfer rate calculations and Heckman selection modeling. The results show that total medical expenses were concentrated among a few adults and the concentration increased over time. People in the high medical expense group were more likely to be older, live in urban areas, be less wealthy, have chronic diseases, and attend higher-ranking medical institutions. Lagged medical expenses had a persistent positive effect on current medical expenses and the effect of a one-period lag was strongest. Individuals with chronic diseases during the lagged period had a higher likelihood of experiencing persistent medical expenses. Policy efforts should focus on preventive management, more efficient care systems, improvement of serious illness insurance level, and strengthening the persistent protection effect of social medical insurance to reduce the high medical financial risk and long-term financial healthcare burden in China.

Prediction Models for Future High-Need High-Cost Healthcare Use: a Systematic Review

BACKGROUND

In an effort to improve both quality of care and cost-effectiveness, various care-management programmes have been developed for high-need high-cost (HNHC) patients. Early identification of patients at risk of becoming HNHC (i.e. case finding) is crucial to a programme's success. We aim to systematically identify prediction models predicting future HNHC healthcare use in adults, to describe their predictive performance and to assess their applicability.

METHODS

Ovid MEDLINE® All, EMBASE, CINAHL, Web of Science and Google Scholar were systematically searched from inception through January 31, 2021. Risk of bias and methodological quality assessment was performed through the Prediction model Risk Of Bias Assessment Tool (PROBAST).

RESULTS

Of 5890 studies, 60 studies met inclusion criteria. Within these studies, 313 unique models were presented using a median development cohort size of 20,248 patients (IQR 5601-174,242). Predictors were derived from a combination of data sources, most often claims data (n = 37; 62%) and patient survey data (n = 29; 48%). Most studies (n = 36; 60%) estimated patients' risk to become part of some top percentage of the cost distribution (top-1-20%) within a mean time horizon of 16 months (range 12-60). Five studies (8%) predicted HNHC persistence over multiple years. Model validation was performed in 45 studies (76%). Model performance in terms of both calibration and discrimination was reported in 14 studies (23%). Overall risk of bias was rated as 'high' in 40 studies (67%), mostly due to a 'high' risk of bias in the subdomain 'Analysis' (n = 37; 62%).

DISCUSSION

This is the first systematic review (PROSPERO CRD42020164734) of non-proprietary prognostic models predicting HNHC healthcare use. Meta-analysis was not possible due to heterogeneity. Most identified models estimated a patient's risk to incur high healthcare expenditure during the subsequent year. However, case-finding strategies for HNHC care-management programmes are best informed by a model predicting HNHC persistence. Therefore, future studies should not only focus on validating and extending existing models, but also concentrate on clinical usefulness.

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.

Comparing the dangers of a stay in English and German hospitals for high-need patients

OBJECTIVE

To estimate the risk of an avoidable adverse event for high-need patients in England and Germany and the causal impact that has on outcomes.

DATA SOURCES

We use administrative, secondary data for all hospital inpatients in 2018. Patient records for the English National Health Service are provided by the Hospital Episode Statistics database and for the German health care system accessed through the Research Data Center of the Federal Statistical Office.

STUDY DESIGN

We calculated rates of three hospital-acquired adverse events and their causal impact on mortality and length of stay through propensity score matching and estimation of average treatment effects.

DATA COLLECTION/EXTRACTION METHODS

Patients were identified based on diagnoses codes and translated Patient Safety Indicators developed by the Agency for Healthcare Research and Quality.

PRINCIPAL FINDINGS

For the average hospital stay, the risk of an adverse event was 5.37% in the English National Health Service and 3.26% in the German health care system. High-need patients are more likely to experience an adverse event, driven by hospital-acquired infections (2.06%-4.45%), adverse drug reactions (2.37%-2.49%), and pressure ulcers (2.25%-0.45%). Adverse event risk is particularly high for patients with advancing illnesses (10.50%-27.11%) and the frail elderly (17.75%-28.19%). Compared to the counterfactual, high-need patients with an adverse event are more likely to die during their hospital stay and experience a longer length of stay.

CONCLUSIONS

High-need patients are particularly vulnerable with an adverse event risking further deterioration of health status and adding resource use. Our results indicate the need to assess the costs and benefits of a hospital stay, particularly when care could be provided in settings considered less hazardous.

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.

Trends in the Concentration and Distribution of Health Care Expenditures in the US, 2001-2018

IMPORTANCE

The concentration of health care expenditures has important implications for managing risk pools, drug benefit design, and care management.

OBJECTIVE

To examine trends in the concentration of health care spending in different population groups and expenditure categories in the US between 2001 and 2018.

DESIGN, SETTING, AND PARTICIPANTS

This study is a cross-sectional analysis of Medical Expenditure Panel Surveys (MEPS) collected between 2001 and 2018. The MEPS is a household survey of medical expenditures weighted to represent national estimates in the US. Respondents were a nationally representative sample of the US civilian noninstitutionalized population. Data analysis was performed from December 2020 to February 2021.

MAIN OUTCOMES AND MEASURES

The main outcome is the concentration of health care expenditures as measured by the cumulative percentage of health expenditure vs percentage of ranked population. This study reports trends in the distribution of populations across 4 concentration curve parameters: top 50% expenditure (high spenders), next 49% expenditure (medium spenders), next 1% expenditure (low spenders), and nonspenders.

RESULTS

The mean sample size of the MEPS surveys used in the analysis was 34 539 individuals, and the sample size varied between 30 461 and 39 165 individuals over the years studied. On the basis of data from 30 461 MEPS respondents (15 867 women [52.1%]; mean [SD] age, 38.9 [24.0] years) in 2018, the top 4.6% (95% CI, 4.3%-4.9%) of the US population by spending accounted for 50% of health care expenditures. Although this fraction varied across population groups or expenditure categories, it remained remarkably stable over time with one exception: the concentration of spending on prescription drugs. In 2001, one-half of all expenditures on prescription drugs were concentrated in 6.0% (95% CI, 5.6%-6.4%) of the US population, but by 2018, this proportion had decreased to 2.3% (95% CI, 2.1%-2.5%). This change does not appear to be associated with a change in the overall share of prescription drug expenses, which increased by only a small amount, from 20.4% in 2001 to 24.8% in 2018.

CONCLUSIONS AND RELEVANCE

The overall concentration of health care expenditures remained stable between 2001 and 2018, but these findings suggest that there has been a sharp increase in the concentration of spending on prescription drugs in the US. This coincides with the genericization of many primary care drugs, along with a shift in focus of the biopharmaceutical industry toward high-cost specialty drugs targeted at smaller populations. If this trend continues, it will have implications for the minimum scale of risk-bearing and drug management needed to operate efficiently, as well as the optimal cost-sharing features of insurance products.

Heterogeneity in Longitudinal Healthcare Utilisation by Older Adults: A Latent Transition Analysis of the Irish Longitudinal Study on Ageing

Background

Older adults likely exhibit considerable differences in healthcare need and usage. Identifying differences in healthcare utilisation both between and within individuals over time may support future service development.

Objectives

To characterise temporal changes in healthcare utilisation among a nationally representative sample of community-dwelling older adults.

Methods

A latent transition analysis of the first three waves of The Irish Longitudinal Study on Ageing (TILDA) (N = 6128) was conducted.

Results

Three latent classes of healthcare utilisation were identified, ‘primary care only’; ‘primary care and outpatient visits’ and ‘multiple utilisation’. The classes were invariant across all three waves. Transition probabilities indicated dynamic changes over time, particularly for the ‘primary care and outpatient visits’ and ‘multiple utilisation’ statuses.

Discussion

Older adults exhibit temporal changes in healthcare utilisation which may reflect changes in healthcare need and disease progression. Further research is required to identify the factors which influence movement between healthcare utilisation patterns.

Retrospective secondary data analysis to identify high-cost users in inpatient department of hospitals in Thailand, a middle-income country with universal healthcare coverage

OBJECTIVES

The study aims to identify high-cost users (HCUs) in the inpatient departments of hospitals in Thailand including their common characteristics, patterns of healthcare utilisation and expenditure compared with low-cost users, and to explore potential factors associated with HCUs so the healthcare system can be prepared to support the HCUs including those who have increased chances of becoming HCUs.

DESIGN AND SETTING

A retrospective secondary data analysis using hospitalisation data from Thailand's Universal Coverage Scheme (UCS) obtained from the National Health Security Office over a 5-year period from October 2014 to September 2019 (fiscal year 2014-2018).

PARTICIPANTS

Study participants included Thai citizens who had at least one inpatient admission to hospitals under the UCS over the study period.

RESULTS

Over the 5-year period, the top 5% of the hospitalised population (or HCUs) consumed almost 50% of the health expenditure each year. HCUs were more likely to have longer hospital stays, a higher annual number of visits and be admitted to multiple hospitals each year when compared with the low-cost users (the bottom 50% of the hospitalised population). The study further reported that the chance of becoming an HCU is associated with several factors such as increasing age, being male, having a comorbidity and being admitted to hospitals in Bangkok.

CONCLUSIONS

This study confirmed that the HCU phenomenon existed in Thailand, where a majority of inpatient care spending is concentrated in the top 5% of the hospitalised population. The study findings call attention to potential initiatives that can help monitor the magnitude and trend of HCUs and develop policies to prevent HCUs.

Machine-learning-based prediction models for high-need high-cost patients using nationwide clinical and claims data

High-need, high-cost (HNHC) patients—usually defined as those who account for the top 5% of annual healthcare costs—use as much as half of the total healthcare costs. Accurately predicting future HNHC patients and designing targeted interventions for them has the potential to effectively control rapidly growing healthcare expenditures. To achieve this goal, we used a nationally representative random sample of the working-age population who underwent a screening program in Japan in 2013–2016, and developed five machine-learning-based prediction models for HNHC patients in the subsequent year. Predictors include demographics, blood pressure, laboratory tests (e.g., HbA1c, LDL-C, and AST), survey responses (e.g., smoking status, medications, and past medical history), and annual healthcare cost in the prior year. Our prediction models for HNHC patients combining clinical data from the national screening program with claims data showed a c-statistics of 0.84 (95%CI, 0.83–0.86), and overperformed traditional prediction models relying only on claims data.

[High-cost patients in Germany: General description of utilization and costs]

BACKGROUND

Studies from different countries have shown that a small number of insured persons (high-cost patients) are responsible for a large portion of health care spending. At the same time, it is assumed that some of these costs could be saved by a better management of this group of people. The aim of this article is to analyze the performance and cost profiles of high-cost patients, to put them in an international comparison, and to derive a better management approach.

METHODS

Retrospective observation study based on statutory health insurance data from two statutory health insurances for the year 2013.

STUDY POPULATION

top 5 %, as well as top 1 % of the most expensive insured persons. Identification of characteristics of high-cost patients and international comparison with the Netherlands, the USA, Canada, Spain, England and Japan.

RESULTS

5 % of insured persons account for almost half of the total costs and the most expensive 1 % of 22 %. These high-cost patients in Germany are, on average, 20 years older than the general population. Almost every person of the high-cost population was prescribed at least one medication during the study period (99.2 %), and 85.8 % had at least one hospital stay. Hospital care accounts for the biggest part of total costs: 75 % together with drugs. The average per capita costs caused by one of the 5 % most expensive insured persons in the year under review are 20 times higher than that of the other 95 % of insured persons. High-cost patients are generally more multimorbid and have higher mortality rates. The most common diagnoses of these patients are hypertension, lipoprotein metabolism disorder and back pain.

CONCLUSION

Similar to other developed countries, Germany faces the challenge to develop and implement adequate intervention approaches addressing the special requirements of high-cost insured persons. This paper provides a first basis. The analogies of high-cost patients in Germany and other countries illustrate the need for transnational research and intervention approaches on this specific issue. More in-depth work is needed to investigate the potentials of Predictive Modelling and integrated care approaches to the management of this group of insured persons.