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

Abstract 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.


What is known on this topic
• International comparisons of health systems mostly rely on comparisons of the inpatient setting.
• Little comparative work examines patterns of spending and utilization of high-need, high-cost (HNHC) patients across different components of the healthcare system, despite constituting a priority group for policymakers.
• Vignette methodologies are a useful way to compare resource use for similar types of patients across countries.

What this study adds
• This study presents a framework and methodology for examining differences in spending, utilization and patient outcomes for specific types of priority high-need, high-cost patients across countries • This study serves as the methodological paper for an international comparison series of six other papers that examines differences across different care settings, including hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, long-term care, homehealth care, and outpatient drugs.
• 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.

| INTRODUCTION
International comparisons of patient trajectories across health systems can be a useful tool to help national policymakers understand whether countries are achieving comparable outcomes at similar costs for their populations. To date, most international efforts have largely focused on understanding variation across individual conditions or episodes of care in the inpatient setting for general populations. [1][2][3][4][5][6] Other work focused on evaluating end-of-life care in people with cancer and revealed considerable variation in the use of intensive and hospital-centric care across high-income countries.
However, the lack of available and similarly structured patientlevel information for specific types of high-need patients across the entire care trajectory limits the potential to identify improvements to be made across the health system. For these patients in particular, it is important for policymakers to understand how care is distributed across settings, such as primary care, outpatient specialty care, and even long-term care, and how use in one setting may influence utilization in another. Understanding which health systems are more effective at managing specific types of HNHC populations could offer key insights to address rising costs, waste, and inequities in the system, as well as improve patient outcomes.
In order to address this challenge, the International Collaborative on Costs, Outcomes and Needs in Care (ICCONIC) was formed in 2018. In this article, we put forward a methodological framework to enable the cross-country comparison of resource use and outcomes for specific types of HNHC patients across the entire patient pathway. Our methodology builds upon previous international comparisons work and utilizes a clinical vignette approach, 3,4,6,7 which allows for the systematic collection and comparison of data across countries with different structures of patient-level datasets.
Specifically, we had three key objectives. First, we outline an approach for selecting two types of HNHC patient "personas," drawing on a typology put forward by the National Academy of Medicine (NAM), to be used as tracers across different countries and health systems. 8 Second, we propose a detailed clinical vignette to be used across countries to identify two types of HNHC personas using available and accessible patient-level datasets that allow for the comparison of utilization, spending, and patient outcomes across countries. Finally, we demonstrate the comparability of these two specific personas-(1) an older adult with frailty who sustains a hip fracture and subsequent hip replacement or osteosynthesis, and (2) an older person with complex multimorbidity, specifically a person hospitalized with heart failure and a comorbidity of diabetesacross the 11 countries in the ICCONIC collaborative. Importantly, this work provides the methodological framework used in an accompanying six original research manuscripts copublished in the Health Services Research "Special Issue on International Comparisons of High Need, High-Cost Patients." [9][10][11][12][13][14] These six original research articles examine detailed variation in spending, utilization, and patient outcomes of the two specific high-need patient cohorts across different care settings.

| Formation of the ICCONIC collaborative
To carry out this work, we formed the ICCONIC research collaborative in 2018 where we brought together partners from each of the 11 countries, representing a wide range of institutions, including universities, healthcare providers, think tanks, research centers, and international organizations. 15 The research partners included collaborators with experience using routine data to compare healthcare performance at the international level and access to the datasets of interest for the study of HNHC patients. [16][17][18][19][20] The 11 participating countries-Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States-all represent high-income countries with high expenditures on health care, but also healthcare systems that are funded and organized differently. For a list of important health system differences, please see Table A1.
Our methodological approach to examine variations in resource use for HNHC personas combines two existing approaches that are relatively novel for international comparison of health systems. First, we propose to use linked, patient-level data to examine the entire care pathway, rather than focusing only on care in the hospital setting allowing us to trace the resources used by patients across the system. Second, our unit of analysis for comparison is the patient, who we follow throughout the system. This approach builds on the use of clinical vignette methodologies to identify similar cohorts of patients, as have been used by other projects to examine resource use in the inpatient setting, [3][4][5]7 and by international organizations to examine variations in clinical practice. 21,22 To advise the conceptual and methodological approach, and comment on the results, we formed an advisory board consisting of national and international experts within each of the 11 countries.
The members include health economists, health services researchers, clinicians, policymakers, and representatives from payers of healthcare services (see Table A2).

| Defining the HNHC patient personas
The first step of the project was to identify a group of HNHC patient subtypes to trace through the different health systems using a predefined clinical vignette, which in this article, we refer to as "HNHC patient personas." This step is necessary for two reasons. First, HNHC patients are not a homogenous group, and while they include patients with substantial clinical need, their care needs will differ. In order to identify more actionable insights for policymakers and practitioners, we wanted to focus on certain types of HNHC patients that were defined by the same types of need. The second reason we focus on distinct HNHC patients is to ensure comparability of the patient cohorts across countries. This is because the composition of HNHC patient types may vary across countries. Therefore, looking at care trajectories and outcomes of this broader group may produce misleading policy recommendations.
To identify these HNHC patient personas, we defined clinical vignettes that were based from the NAM typology of HNHC priority populations. 8 The NAM recently identified priority groups of patients that were among the most expensive to care for have substantial healthcare needs, and are particularly vulnerable to poor-quality care. [23][24][25] Based on the NAM framework, we selected two specific HNHC patient profiles that we believed would be most identifiable across countries, given existing data collection and coding systems, and identified specific types of patients that would belong to this category using a clinical vignette approach. The first included an older adult with frailty (defined by the following clinical vignette: person above age 65 who is hospitalized with hip fracture and received a subsequent hip replacement), and a person with major complex comorbidities (defined by the following clinical vignette: a person between the ages of 65 and 90 hospitalized with heart failure and a comorbidity of diabetes) ( Table 1). Both of these clinical vignettes were identifiable through an inpatient admission, which are more consistently coded through more comparable coding systems (mostly deriving from the WHO ICD-10 code system) than those in other settings (e.g., primary care, outpatient care). These decisions were made through a consensus decision-making process by all members in the collaborative, which included physicians, policymakers, data scientists, statisticians, and health economists.

| Identifying HNHC personas across countries' datasets
In order to identify and follow each of these personas across their pathway of care over a period of a year, we required at least 2 years of patient-level data. The first year was used as the base year to identify all index cases of relevant patients that met the specific prespecified clinical vignette definition. We then followed patients for 12 months from the index date of hospitalization to measure the service use, costs, and outcomes of the patients. To identify the index cases, we identified all patients in the base year that were hospitalized for the acute event, using a common set of diagnostic codes and relevant procedure codes (Table 1). Across most countries, we used 2 years between 2015 and 2017, except in Australia (2012Australia ( -2016 and England (2014-2017), which had smaller samples and, therefore, pooled more years of data (Table A3)

| Country selection and datasets
In order to validate our approach, data for the two personas-the older frail adult with hip fracture and the older adult with complex multimorbidity-were extracted from the 11 country databases and examined for comparability. We examined comparability in terms of patient characteristics, including age and sex, and also explored variations in the number of chronic conditions captured in administrative data using Elixhauser definitions. 26 The participating countries use a range of datasets including administrative claims data, survey data, and registry data. The priority was to have a dataset that captured patient-level and linked information across different components of the healthcare system. For further details on the representativeness of each dataset and years of data used across countries, see Table A3. The datasets differed with regards to their representativeness of the national population as well as their ability to provide linked data across all seven care settings (

42.7%
Note: The Netherlands was unable to identify Elixhauser conditions in the data provided by the insurer. Clinical experts were used to identify the relevant codes in the insurer data that matched the primary diagnoses of interest.

| Characteristics of the hip persona across countries
Across the 11 countries, sample sizes ranged from n = 1859 in Aragon (Spain) to n = 29,134 in the United States (  Figure A1). Within the different diagnostic codes, the breakdown of procedure type differed. Among patients with the S72.0 code, the most common procedure across countries was a partial hip replacement (see Figure A2). For the patients with S72.1 and S72.2, the most common procedure was osteosynthesis (e.g., internal fixation using screws, screw-rod, or screw-plate constructs). These  While all countries are able to report data on expenditures, there are differences in what information they are able to report on the different care settings (Table A1). In addition, the cost accounting methods used to estimate expenditure differ across countries, in part due to the differences in payment systems adopted, which also vary across care settings within countries. For example, some countries are able to report direct spending from incurred costs (those with full costing systems), whereas others provide information on reimbursement for specific episodes (e.g., diagnosis-related groups) or an unweighted average unit price. In addition, the reporting and imputation of capital investments or indirect costs also varies across system.

| DISCUSSION
In this study, we present a novel methodological framework for identify- In order to better understand how resource use may vary for those who die during the course of the study period, a separate paper examines spending and utilization at the end of life among people with hip fracture. 13 A fifth paper examines the within-country variation of healthcare utilization and spending among people with complex multimorbidity (heart failure and diabetes) to better understand if there are important inequalities in care utilization across countries. 14 Finally, for countries that have access to data on long-term care utilization and spending, an accompanying sixth paper examines the relative use of different types of long-term and post-acute care use among those who experience a hip fracture. 10 A key strength of the methodology presented in this article is that it segments the HNHC population into distinct patient types who require different types of care from the health system and therefore move across the care settings differently. We identified the two chosen personas from a hospitalization as the initial inciting event. All 11 countries in our study had reliable hospital data that allowed the identification of the hip fracture persona and the complex multimorbid persona with heart failure and diabetes.
Furthermore, the use of the HNHC patient persona approach offers some standardization across participating countries that is important for two reasons. First, most existing comparative studies of high-cost patients to date have focused on comparing a broad group of patients that make up the top 1%-10% of health care spending in different countries. The types of patients found in this group are quite heterogenous and therefore make it challenging for these comparisons to yield actionable insights for policymakers. 1,30 In contrast, our approach is designed to identify homogenous groups of HNHC personas that allow for more comparability across countries.
Second, the merit of applying a clinical vignette approach is that by applying specific diagnostic and age criteria to identify patients across countries, we are able to compare a more similar cohort of individuals. This is necessary given the many factors that can influence patient resource use and outcomes across countries, such as structural differences in how they capture and incentivize coding of pri- recorded the fewest number of comorbidities. Therefore, differences in comorbidities likely reflect structural differences rather than severity of illness, which may limit our ability to risk-adjust using comorbidities.
There are also important limitations in the ability to identify other types of HNHC personas. For example, the NAM identified other priority populations, including those with serious mental illness and older adults with dementia. However, the identification of personas that require the use of diagnostic codes in primary care or outpatient specialty care settings is not possible in many countries. Only five countries have the ability to capture chronic conditions in nonhospital settings. We also observe large differences in data availability, which may influence generalizability within countries. In some countries, regional samples were used (e.g., Canada, Spain, and New Zealand), which may not be representative for other populations in the country. In addition, many countries have gaps in their ability to follow patients across the entire care pathway. For example, data on long-term care was lacking across most countries. Linked post-acute care and home care was also not available for research use in many countries.