Health Care Reimbursement Research Articles

Inequalities in health and resources between siblings of individuals with and without mental health disorder: an observational study using the French national health data system.

The aim of the present study was to describe the effect of an individual's mental health disorder on the resources of his or her adult siblings. A subject rarely analyzed on a large scale. The French National Health Data System (SNDS) collects data on individuals, including their characteristics and the types of healthcare used. A national observational sectional case-control study included individuals covered as of 1 January 2019 and receiving yearly at least one healthcare reimbursement in 2019 including their SNDS data collected from 2013 to 2018. The main variables of interest were a Complementary Universal Health Coverage (CUHC) granted to people who had limited resources. There is also a long-term disease (LTD) status qualifying also for 100% for a specific disease and an ecological index of social deprivation of the place of residence. Conditions were also collected using a specific tool including LTD and hospital diagnosis. Analyzed siblings included 280709 cases with at least one member suffering from a mental health disorder and 561418 randomly selected control individuals were addressed using a multilevel model. Siblings of people with mental health problems were more likely to benefit from CUHC or to live in the most deprived area. In addition, the study also highlighted the importance of parental background, which appears to be poorer than in the control population. Social inequalities are particularly marked among the siblings of a person suffering from mental health disorder. Further studies are needed to better understand and enlarge these observational results.

Healthcare resource utilization and costs in immunodeficient patients receiving subcutaneous Ig: Real-world evidence from France.

Subcutaneous immunoglobulin (SCIg) replacement therapy is indicated for patients with hypogammaglobulinemia caused by primary (PID) and secondary immunodeficiencies (SID). To compare healthcare resource utilization (HCRU) and related direct medical costs of patients in France treated with weekly conventional SCIg (cSCIg) vs monthly hyaluronidase-facilitated SCIg (fSCIg). This retrospective study of Ig-naïve patients with PID or SID newly receiving a SCIg between 2016 and 2018, extracted from the French National Healthcare reimbursement database (SNDS), analyzed the SCIg-related HCRU and reimbursed costs generated from in-hospital (hospitalizations and SCIg doses) or at-home (nurse visits [NV] and pump provider visits [PPV], drug doses) SCIg administration. Overall, 2,012 patients (PID:534; SID:1,478) were analyzed. The follow-up duration varied between 7.5 and 8.7 months according to sub-groups. Compared with fSCIg-treated patients, monthly mean rates of NV and PPV were respectively 2.5 and 3.1 times higher in PID, and 1.6 and 3.1 times higher in SID cSCIg-treated patients. Monthly mean rates for SCIg administration-related hospitalizations were lower overall, while their costs were 1.6 and 1.8 times higher for cSCIg than fSCIg subgroups, in PIDs and SIDs respectively; these results are due to more frequent hospitalizations with fSCIg being mainly shorter, without stayover. Total HCRU costs from the French NHI's perspective were estimated to be lower with fSCIg vs cSCIg, in PIDs and SIDs. This study provides real-world evidence of SCIg administration in a large French population. Patients with PID or SID treated with fSCIg had fewer at-home HCRU and lower overall costs for in-hospital or at-home SCIg administration compared with cSCIg-treated patients.

Understanding excess mortality during COVID in Belgium: the influence of pre-existing health status and social factors

BackgroundThis study aims to investigate how pre-existing health status and social background contribute to excess mortality during the COVID-19 crisis in Belgium.MethodsThe study population consists of almost 1.4 million adult members of Solidaris, the second largest health insurance fund in Belgium. Pre-existing health status was identified using health care reimbursement data, including medication use. Social characteristics included a proxy for low socio-economic status, nationality of origin, and living arrangement. Excess mortality during the COVID-19 crisis was measured by computing the relative difference between all-cause mortality in 2020 or 2021 and the average yearly mortality in 2015–2019. Directly Standardised Mortality Rates (DSMRs) were calculated to investigate absolute mortality inequalities. Mortality Rate Ratios (MRRs) were computed using Poisson regression analyses to investigate relative mortality inequalities.ResultsDSMRs show that persons with no previous disease experienced significant excess mortality in 2020, like men with one, two or three diseases and women with various numbers of pre-existing diseases. Results by specific disease show heterogenous results. After adjusting for age, sex and social characteristics, persons with cancer experienced a significant mortality deficit of 17% in 2020 and of 9% in 2021. For persons with cancer and asthma or COPD, significant mortality deficits of 10% and 3% were observed in 2020 and 2021, respectively.ConclusionThe study provides insights into the complex dynamics of mortality during the COVID-19 crisis, emphasising the need to consider individual-level information on pre-existing health and social background jointly.

Towards implementing new payment models for the reimbursement of high-cost, curative therapies in Europe: insights from semi-structured interviews.

New ways of reimbursement for high-cost, one-shot curative therapies such as advanced therapy medicinal products (ATMPs) are a growing area of interest to stakeholders in market access such as industry representatives, legislative and accounting experts, physicians, hospital managers, hospital pharmacists, patient representatives, policymakers, and sickness funds. Due to the complex nature of ATMPs, new payment models and reimbursement modalities are proposed yet not widely applied across Europe. This study aimed to elicit opinions on and insights into the governance aspect of implementing outcome-based spread payments (OBSP) in Belgium for the reimbursement of innovative therapies. Stakeholders' responsibilities and roles were analysed and proposed solutions or general beliefs were assessed to identify necessary or sufficient conditions to establish outcome-based spread payments. Semi-structured interviews (n = 33) were conducted with physicians (n = 2), hospital pharmacists (n = 4), hospital managers (n = 2), Belgian policymakers (n = 6), legislative experts (n = 2), accounting experts (n = 5), representatives of patients (n = 3), of industry (n = 5), and sickness funds (n = 4). The interviews took place between July 2020 and October 2020. The framework method analysis was performed using Nvivo software (version 20.4.1.851). Statements were allocated into six main topics: payment structure, spread payments, outcome-based agreements, governance, transparency, and regulation. Interviews revealed the necessary conditions that, fulfilled together, are seen to be sufficient for the successful implementation of OBSP, including consensus on pricing, payment logistics, robust data infrastructure and financing, clear agreement terms (duration, outcome parameters, payment triggers), long-term patient follow-up solutions, an external multi-stakeholder governance body, and transparency regarding agreement types. Despite the interest, the effective implementation of OBSP falls behind due to a lack of consensus on how this new reimbursement method can be a sustainable solution. By stating the necessary conditions that, when fulfilled together, are deemed sufficient for successful OBSP implementation, this study provides a framework towards overcoming implementation barriers and realizing the potential of OBSP in transforming healthcare reimbursement practices.

Socioeconomic Burden of Pulmonary Embolism in Europe: Shifting Priorities and Challenges for Novel Reperfusion Strategies.

In-hospital case fatality related to acute pulmonary embolism (PE) has been falling since the beginning of this century. However, annual incidence rates continue to climb, and an increasing number of PE survivors need long-term follow-up, chronic anticoagulation treatment, and readmission(s) to the hospital. In European countries, median reimbursed hospital costs for acute PE are still moderate compared with the United States but can increase several-fold in patients with comorbidities and those necessitating potentially life-saving reperfusion treatment. The use of catheter-directed treatment (CDT) has constantly increased in the United States since the past decade, and it has now entered a rapid growth phase in Europe as well, estimated to reach an annual penetration rate of up to 31% among patients with intermediate-high- or high-risk PE by 2030. Ongoing randomised controlled trials are currently investigating the clinical efficacy and safety of these devices. In addition, they will deliver data permitting calculation of their cost-effectiveness in different health care reimbursement systems, by revealing the extent to which they can reduce complications and consequently the need for intensive care and the overall length of hospital stay. After discharge, key cost drivers are related to chronic cardiopulmonary diseases (other than PE itself) leading to frequent readmissions, persistent symptoms, and functional limitations which result in poor quality of life, productivity loss, and substantial indirect costs. Implementation of structured outpatient programmes with a holistic approach to post-PE care, targeting overall cardiovascular health and the patient's well-being, bears the potential to cost-effectively reduce the overall socioeconomic burden of PE.

The 2024 APLAR Consensus on the Management of Lupus Nephritis.

The APLAR has published a set of recommendations on the management of systemic lupus erythematosus (SLE) in 2021. The current consensus paper supplements and updates specifically the treatment of lupus nephritis (LN) according to two rounds of Delphi exercise from members of the APLAR SLE special interest group, invited nephrologists, histopathologists, and lupus nephritis patients. For initial treatment of LN, we recommend a combination of glucocorticoids (GCs) with cyclophosphamide (CYC), mycophenolate mofetil (MMF), or the calcineurin inhibitors (CNIs) as first-line options. An upfront combination of immunosuppressive drugs and the biological agents may be considered in patients at significant risk of disease progression and renal function deterioration. Switching or "add-on" among different immunosuppressive agents, including biological agents, may be considered for refractory disease. Subsequent/maintenance therapy of LN should continue for at least 3 years to reduce the risk of renal flares. Lower dose MMF and azathioprine are options, but MMF maintenance should follow induction by the same drug. Prednisolone or equivalent should be maintained at a dose of 5 mg/day or less. The APLAR consensus for the management of LN includes recommendations for adjunctive therapies, monitoring and treatment of LN-related co-morbidities, and renal replacement therapies. It is hoped that this consensus paper can provide an evidence-based and pragmatic approach to the management of LN, taking into account the evidence level of therapies in Asian patients, cost-effectiveness, and differences in health care resources and reimbursement policies in the Asia-Pacific region.

Global Insights from Patients, Providers, and Staff on Challenges and Solutions in Managing Neovascular Age-Related Macular Degeneration.

Neovascular age-related macular degeneration is a global public-health concern, associated with a considerable burden to individuals, healthcare systems, and society. The objective of this study was to understand different perspectives on the challenges associated with the clinical management of neovascular age-related macular degeneration, which could elucidate measures to comprehensively improve clinical care and outcomes. A survey was carried out of patients with neovascular age-related macular degeneration, their providers, and clinic staff in 77 clinics across 24 countries on six continents, from a diverse range of healthcare systems, settings, and reimbursement models. Surveys comprised a series of single/multiple-response questions completed anonymously. Data gathered included patient personal characteristics, appointment attendance challenges, treatment experiences, and opportunities to improve support. Provider and clinic staff surveys asked similar questions about their perspectives; clinic characteristics were also captured. There were 6425 responses; 4558 patients with neovascular age-related macular degeneration, 659 providers, and 1208 clinic staff. Challenges identified included concern about patient burden to family/friends, high frequency of treatment, difficulties in traveling to appointments, long waiting times, and insufficient comprehension of neovascular age-related macular degeneration. Participants identified logistical (improved financial assistance with treatment and out-of-pocket costs, and appointment reminders), operational (addressing clinic set up to reduce waiting times and improving the amount of time providers spend with patients), and educational (improving quality and provision of patient information and expectation-setting) opportunities to improve care. The wealth of data generated by this global survey highlights the breadth of challenges associated with clinical management of patients with neovascular age-related macular degeneration. Addressing the opportunities raised could improve patient adherence to treatment and potentially outcomes, reduce appointment burden, and increase clinic capacity.

Financial Barriers to Rural Graduate Medical Education: Medicare Funding Methods for Sole Community and Medicare-Dependent Hospitals.

Policymakers are exploring options to address rural-urban physician maldistribution, including reducing rural residency training barriers. This study estimated Medicare graduate medical education (GME) reimbursement that sole community hospitals (SCHs) and Medicare-dependent hospitals (MDHs) are disqualified from receiving compared with hospitals under the Prospective Payment System (PPS) and calculated the GME reimbursement per resident for MDHs and SCHs under different scenarios. This simulation study used Healthcare Cost Report Information System data on hospitals that had been SCHs or MDHs between 2011 and 2021 and did not have any resident full-time equivalents (FTEs) in the most recent year. Reimbursements were calculated under the PPS and hospital-specific rate (HSR), assuming all other hospital financing elements remained unchanged, apart from adding resident FTEs. A total of 242 hospitals were identified as current or recent SCHs or MDHs with an average daily census of 25 or more and no residents in their most recent cost reports; 139 (57.4%) were paid under the HSR. The median (interquartile range) reimbursement per resident was $179,442 ($153,078-$208,412) under PPS and $107,294 ($85,134-$128,259) under HSR, a difference of nearly $70,000 per resident. The median opportunity cost per FTE was approximately $73,000 for SCHs and approximately $65,000 for MDHs. No significant per-resident differences were observed in the GME payments based on program size. Due to higher GME payments from PPS vs HSR, the number of hospitals defaulting to HSR decreased, and by the end of the third year of the program, more than 10% hospitals switched from HSR to PPS. Under the current health care and GME reimbursement method, SCHs and MDHs face considerable financial barriers to launching or participating in GME programs. Policy adjustments to address this barrier may incentivize more rural facilities to launch or participate in GME, potentially mitigating the geographic maldistribution of physicians.

PD04 A Systematic Review Of Decision Analytical Modeling Studies Of Medicines In The Middle East

IntroductionEconomic evaluation using decision analytical models (DAMs) plays a limited role in shaping healthcare resource optimization and reimbursement decisions in the Middle East. This review aimed to systematically examine economic evaluation studies focusing on DAMs of medicines in the Middle East, defining methodological characteristics and appraising the quality of the identified models.Methods Six databases were searched (MEDLINE, Embase, EconLit, Web of Science, the Global Health Cost-Effectiveness Analysis Registry, and the Global Index Medicus) from 1998 to September 2023 to identify published DAMs of medicines in the Middle East. Studies meeting the inclusion criteria—full economic evaluations of medicines using a model-based method in the Middle East—were included. Data were extracted and tabulated to include study characteristics and methodological specifications. The results were analyzed narratively. The Philips checklist was used to assess the quality of the studies.ResultsSixty-two DAM studies of medicines were identified from nine Middle Eastern countries, the majority of which (76%) were conducted in Iran, Turkey, and Saudi Arabia. The cost effectiveness of medications for non-communicable diseases was explored in 70 percent of the models. Cost-effectiveness thresholds based on gross domestic product were commonly used. International sources provided data on intervention effectiveness and health outcomes, while national sources were mainly used for the costs of resource use. Most models incorporated an assessment of parameter uncertainty, whereas other types of uncertainty were not explored. Studies from high-income countries were generally of higher quality than those from middle-income countries.ConclusionsThe number of published DAMs was low considering the available medicines and disease burden. Key aspects of high quality DAMs regarding model structure, input sources, and uncertainty assessment were not consistently fulfilled. Recommendations for future studies and policies included strengthening existing health economic capacities, establishing country-specific health technology assessment systems, and initiating collaborations to generate national cost and outcome data.

OP10 Affordability Decision Rules: Systematic Review And Categorization Of Budget Impact Thresholds For 174 Countries Based On International Practices

IntroductionEffective health intervention coverage decision-making hinges on understanding budget impact (BI). Despite progress in estimating cost-effectiveness thresholds, a standardized approach for defining BI, particularly high BI, remains elusive. Addressing this gap, our systematic review aims to identify existing BI thresholds and establish universally applicable BI categories, providing a much-needed framework for global health policy.MethodsIn our systematic review, we adhered to Cochrane methods and PRISMA reporting guidelines (PROSPERO protocol CRD42020221652). We included articles that detailed current BI or affordability thresholds used by national or regional healthcare systems, sourcing from PubMed, Embase, and International Network of Agencies for Health Technology Assessment (INAHTA) communications. To address variability across jurisdictions, we normalized BI/affordability thresholds to a fraction of each country’s total healthcare expenditure. This approach enabled us to categorize BI thresholds into four distinct levels (low, moderate, high, and very high) and apply these categories universally across countries.ResultsWe retrieved 1,592 records, identifying affordability thresholds and their underlying rationales in 12 countries: Argentina, Australia, England, Canada, Germany, France, Netherlands, USA, Taiwan, Ukraine, Scotland, and Singapore. Utilizing this data, we established four BI threshold levels relative to the total health budget: low (below 0.00005), moderate (0.00005 to <0.0001), high (0.0001 to <0.0002), and very high (>=0.0002). We then extrapolated these thresholds, along with their uncertainty ranges, to 174 countries, using 2022 World Bank data.ConclusionsOur study provides a comprehensive overview of current global affordability thresholds and their implications for healthcare coverage and reimbursement. We found that explicit BI thresholds are predominantly established in high-income countries. Our findings offer critical, evidence-based guidance on affordability decision rules, applicable to health systems in 174 countries, thereby contributing significantly to the standardization and informed policymaking in global healthcare.

Trends in Intermittent Scanning Continuous Glucose Monitoring Usage in The Netherlands-An Opportunity for Elderly Individuals with Diabetes.

Background: Intermittent scanning continuous glucose monitoring (is-CGM) technology has gained widespread adoption and is known to improve glycemic control and quality of life for persons with diabetes. The elderly may lag behind in their adoption of the technology, which could be a potential avenue for improving quality of care. In this study, we investigated the adoption of is-CGM technology in the Dutch population, including effects of age. Methods: A retrospective observational study was performed using data from the Drug Information Project, a public database hosted by the Dutch National Health Care Institute. The database contained information concerning healthcare reimbursements from 2017 until 2022 and covered approximately 95% of the total population. Data concerning is-CGM and fast-acting insulin reimbursements were extracted, identifying actual and potential is-CGM users, who were subdivided into the categories 0-24, 25-44, 45-64, 65-74 and ≥75 years old. Results: From 2017 until 2022, is-CGM usage rapidly increased: from 38 to 82.050 actual users. The age categories 0-24 and 25-55 showed the highest is-CGM usage (62% and 84% of the potential population in 2022, respectively), and 65-74 and ≥75 the least (38% and 33%, respectively). However, the elderly had higher growth rates (+75% in the category ≥75 from 2021 to 2022) compared to the youngest (+54% in the category 0-24 in the same period). Conclusions: Data from this study demonstrate that the elderly lag behind in is-CGM adoption. Given the potential advantages of is-CGM for elderly persons with diabetes, we argue that strategies should be developed to address this (paradoxical) underutilization of is-CGM.

Benchmarking Large Language Models for Extraction of International Classification of Diseases Codes from Clinical Documentation.

Healthcare reimbursement and coding is dependent on accurate extraction of International Classification of Diseases-tenth revision - clinical modification (ICD-10-CM) codes from clinical documentation. Attempts to automate this task have had limited success. This study aimed to evaluate the performance of large language models (LLMs) in extracting ICD-10-CM codes from unstructured inpatient notes and benchmark them against human coder. This study compared performance of GPT-3.5, GPT4, Claude 2.1, Claude 3, Gemini Advanced, and Llama 2-70b in extracting ICD-10-CM codes from unstructured inpatient notes against a human coder. We presented deidentified inpatient notes from American Health Information Management Association Vlab authentic patient cases to LLMs and human coder for extraction of ICD-10-CM codes. We used a standard prompt for extracting ICD-10-CM codes. The human coder analyzed the same notes using 3M Encoder, adhering to the 2022-ICD-10-CM Coding Guidelines. In this study, we analyzed 50 inpatient notes, comprising of 23 history and physicals and 27 progress notes. The human coder identified 165 unique codes with a median of 4 codes per note. The LLMs extracted varying numbers of median codes per note: GPT 3.5: 7, GPT4: 6, Claude 2.1: 6, Claude 3: 8, Gemini Advanced: 5, and Llama 2-70b:11. GPT 4 had the best performance though the agreement with human coder was poor at 15.2% for overall extraction of ICD-10-CM codes and 26.4% for extraction of category ICD-10-CM codes. Current LLMs have poor performance in extraction of ICD-10-CM codes from inpatient notes when compared against a human coder.

Predicting Fear of Breast Cancer Recurrence in women five years after diagnosis using Machine Learning and healthcare reimbursement data from the French nationwide VICAN survey

A major concern for cancer survivors after treatment is the Fear of Cancer Recurrence (FCR), which is the fear that cancer will reappear or progress. This fear can be exacerbated by medical uncertainty about the future, leading to harmful obsession and having a negative impact on quality of life. This study aims to develop a predictive Machine Learning (ML) model using healthcare reimbursement data to better predict FCR and understand the factors influencing FCR in women with breast cancer five years after their diagnosis. We used data from the VICAN (VIe après le CANcer) survey to propose an interpretable model to identify patients at risk of developing clinical FCR. The reimbursement data for each patient were analyzed beyond the first two years of treatment, excluding the initial phase influenced by the cancer curative therapeutic process. Data experiments were conducted, including the use of algorithms such as Random Forest, Support Vector Machines, Gradient Boosting, eXtreme Gradient Boosting, and Multilayer Perceptron. The AUC was used to choose the optimal model. The dataset is composed of 918 patients classified regarding FCR. The experimental design incorporated classification levels of medications, biological and medical procedures. Subsequently, data was generated for two experiments, facilitating examination at the ultimate healthcare classification level in Experiment 1, while Experiment 2 targeted the penultimate classification level. Overall, the best-performing model achieved an AUC of 66%. This demonstrates some effectiveness of the algorithms in detecting patients at risk of developing clinical FCR and encourages further investigations to enhance the model's performance and assess its generalizability. ML applied to reimbursement data has shown promise in predicting FCR, aiding in the identification of patients at risk of developing it. The results pave the way for personalized prevention and intervention strategies, representing a significant advancement in postcancer care focusing on the needs of survivors.

We Are on the Verge of Breakthrough Cures for Type 1 Diabetes, but Who Are the 2 Million Americans Who Have It?

Background: Two million Americans have type 1 diabetes (T1DM). Innovative treatments have standardized insulin delivery and improved outcomes for patients, but patients' access to such technologies depends on social determinants of health, including insurance coverage, proper diagnosis, and appropriate patient supports. Prior estimates of US prevalence, incidence, and patient characteristics have relied on data from select regions and younger ages and miss important determinants. Objectives: This study sought to use large, nationally representative healthcare claims data sets to holistically estimate the size of the current US population with T1DM and investigate geographic nuances in prevalence and incidence, patient demographics, insurance coverage, and device use. This work also aimed to project T1DM population growth over the next 10 years. Methods: We used administrative claims from 4 sources to identify prevalent and incident T1DM patients in the US, as well as various demographic and insurance characteristics of the patient population. We combined this data with information from national population growth projections and literature to construct an actuarial model to project growth of the T1DM population based on current trends and scenarios for 2024, 2029, and 2033. Results: We estimated 2.07 million T1DM patients nationally across all insurance coverages in our 2024 baseline model year: 1.79 million adults (≥20 years) and 0.28 million children. This represents a US T1DM prevalence rate of 617 per 100 000 and an incidence rate of 0.016%. By 2033, we project the US population with T1DM will grow by about 10%, reaching approximately 2.29 million patients. Discussion: Our results showed important differences in T1DM prevalence and incidence across regions, payers, and ethnic groups. This suggests studies based on more geographically concentrated data may miss important variation in prevalence and incidence across regions. It also indicates T1DM prevalence tends to vary by income, consistent with several international studies. Conclusions: Accurate projections of T1DM population growth are critical to ensure appropriate healthcare coverage and reimbursement for treatments. Our work supports future policy and research efforts with 2024, 2029, and 2033 projections of demographics and insurance coverage for people with T1DM.

We Are on the Verge of Breakthrough Cures for Type 1 Diabetes, but Who Are the 2 Million Americans Who Have It?

Background: Two million Americans have type 1 diabetes (T1DM). Innovative treatments have standardized insulin delivery and improved outcomes for patients, but patients’ access to such technologies depends on social determinants of health, including insurance coverage, proper diagnosis, and appropriate patient supports. Prior estimates of US prevalence, incidence, and patient characteristics have relied on data from select regions and younger ages and miss important determinants. Objectives: This study sought to use large, nationally representative healthcare claims data sets to holistically estimate the size of the current US population with T1DM and investigate geographic nuances in prevalence and incidence, patient demographics, insurance coverage, and device use. This work also aimed to project T1DM population growth over the next 10 years. Methods: We used administrative claims from 4 sources to identify prevalent and incident T1DM patients in the US, as well as various demographic and insurance characteristics of the patient population. We combined this data with information from national population growth projections and literature to construct an actuarial model to project growth of the T1DM population based on current trends and scenarios for 2024, 2029, and 2033. Results: We estimated 2.07 million T1DM patients nationally across all insurance coverages in our 2024 baseline model year: 1.79 million adults (≥20 years) and 0.28 million children. This represents a US T1DM prevalence rate of 617 per 100 000 and an incidence rate of 0.016%. By 2033, we project the US population with T1DM will grow by about 10%, reaching approximately 2.29 million patients. Discussion: Our results showed important differences in T1DM prevalence and incidence across regions, payers, and ethnic groups. This suggests studies based on more geographically concentrated data may miss important variation in prevalence and incidence across regions. It also indicates T1DM prevalence tends to vary by income, consistent with several international studies. Conclusions: Accurate projections of T1DM population growth are critical to ensure appropriate healthcare coverage and reimbursement for treatments. Our work supports future policy and research efforts with 2024, 2029, and 2033 projections of demographics and insurance coverage for people with T1DM.

Claim Pricing in Claim Adjudication Process

The claim adjudication process is a critical function within healthcare organizations, determining the legitimacy and value of claims submitted for payment. This paper explores the pricing logic applied during claim adjudication, focusing on the algorithms and methodologies used to evaluate claims effectively. By analyzing the impact of pricing logic on the overall efficiency and accuracy of claim processing, this study aims to provide insights that can enhance healthcare reimbursement practices and improve operational efficiency. Keywords – Claim Adjudication, Claim Pricing, Healthcare Organization, Reimbursement, Algorithms.

The value of a neurosurgeon: is neurosurgical compensation proportional to value added? A systematic review of the literature and an update on a changing healthcare economy.

Determining the value of a neurosurgeon is complex. Services provided by neurosurgeons have a range of interested parties-from a patient's singular health interest to a community catchment area rendering on-call emergency services. Such complexity makes it difficult to determine and define value. As healthcare reimbursement changes continue to transition further toward value-based/bundled payments, such determinations remain difficult and confusing. Given these factors, now more than ever before, neurosurgeons need to be active participants in the evolving discussions surrounding healthcare advocacy, value, and compensation in an ever-evolving and convoluted system. The objective of this study was to review and present current trends within the evolving landscape of healthcare economics and their impacts on the perceived value of neurosurgical services. A systematic review regarding payments and compensation within neurosurgery was performed using a key term search. Additionally, a neurosurgical value model for hospitals was created using Medicare reimbursement methods to attempt to determine the financial contribution of a single neurosurgeon to a hospital system. Furthermore, Internal Revenue Service (IRS) form 990 tax filings from 5380 organizations were examined for comparative trends in profits and revenue on a hospital-wide basis. Mean and median annualized excess hospitalization revenue from a neurosurgeon over the same number of equal medical admissions was $5,120,533 and $5,141,160, respectively. For private practice groups, the annualized mean and median yearly hospital revenue over a comparable medical admission was calculated to be $1,539,704 and $1,902,555, respectively. For hospital-employed neurosurgeons, the respective addition of Medicare part B payments increased the mean and median values to $2,249,552 and $2,612,403, respectively. Analysis of nonprofit hospital IRS form 990 filings revealed a substantial increase in executive compensation and hospital revenue since 2011. Neurosurgeon median earnings over a similar period, reported through surveys, exhibited varied increases, but significant reporting variation exists. Medical compensation continues to evolve toward more value-driven methods. Value created as a neurosurgeon is complex, but it should not be underestimated as a key driver of hospital revenue, with up to $2.6 million created annually from neurosurgical hospital admissions. Further discussion is needed to elucidate alternative innovative payment strategies to ensure physicians remain active in the evolving structure of our healthcare system.

Substitution of care through the eyes of Dutch health insurers: a qualitative study

Abstract Objectives The objective of health policy measures in the Netherlands is to promote the substitution of care from hospitals to general practitioners (GPs), with reimbursement facilitating this shift. Given that health insurers are tasked with healthcare reimbursement in the Netherlands, understanding their experiences regarding care substitution is crucial. Methods First, informal interviews were held with employees from the Dutch Ministry of Health, Welfare and Sports, the National Health Care Institute and the Netherlands Institute of Health Services Research to construct the topic list. Then, we conducted semi-structured interviews with 15 employees from 7 health insurers, including healthcare purchasers, strategists, client relations executives, and business analysts, between February and April 2024. Transcripts were analyzed in MAXQDA by two researchers, after member checking. Results Insurers navigating substitution face a complex interplay of competition and collaboration, lacking a comprehensive framework. Long-term agreements with hospitals and GPs are seen as potential solutions, contingent on building trust. Diverse views on insurers’ roles emerge, from passive reimbursement to active infrastructure support. Budgetary constraints vary, with some insurers feeling constrained by national budgets for GPs and hospitals while others perceive more flexibility. Risks equalization and deductibles are identified as hindrances to substitution efforts, necessitating changes in financial incentives. Conclusions Overall, addressing these complexities requires aligning incentives and balancing collaboration and competition to optimize resource allocation to effectively meet evolving healthcare needs. A comprehensive framework to balance collaboration and competition might be helpful. Key messages • Understanding insurers’ views on care substitution is vital for healthcare policy in the Netherlands. • A comprehensive framework is needed to balance collaboration and competition, aligning incentives effectively.

Monitoring the digital healthcare transition in the Netherlands: Challenges, achievements and future

Abstract Since 2013, the Netherlands Institute of Health Service Research, along with other Dutch research institutes, has monitored the digital healthcare transition in The Netherlands. Through annual surveys of both healthcare professionals (from primary and secondary care) and users (patients as well as the general population) from 2013 to 2023, trends in digital health utilization and experiences have been tracked. Overall, there has been a steady increase in digital care adoption since 2013, but in 2023, growth among professionals stabilized while slightly rising among users. Some tools saw significant increases, like automatic medicine dispensers and home monitoring, freeing up nurses’ time. Utilization patterns differ among patients according to their educational attainment and age, showing lower usage rates among older individuals and those with lower levels of education. Most professionals, especially nurses, view digital care positively, but they recognize its limitations in solving healthcare challenges entirely. Healthcare professionals believe it offers only a limited contribution to cost management, workload reduction, and job satisfaction and emphasize the need for seamless integration into routine care. User opinions are divided, with those with chronic conditions often expressing skepticism. Both professionals and patients agree that personal experience is crucial in determining its value. Additionally, ensuring user-friendliness and clarifying reimbursement for digital healthcare are essential. This workshop provides an overview of developments in the Netherlands and a discussion of challenges, achievements, and prospects. Particular attention will be paid to the monitoring of digitalization progress and effects, and the use of digital solutions in primary and secondary care.

Unraveling Social Health Inequalities during COVID-19 in Belgium: The Vital Role of Data Linkages

Abstract Background During the COVID-19 crisis, data linkages were set up to efficiently monitor the outbreak and identify vulnerable population groups. Yet, considerable technical, administrative and data security issues have hindered the effectiveness of data linkages as a critical instrument during public health emergencies. This workshop aims to provide a practical demonstration of the challenges encountered in a Belgian data linkage during the COVID-19 crisis, along with the strategies implemented to overcome these challenges. This case study offers insights into the development of a highly sensitive linkage between COVID-19 hospital data and information related to social and health use in Belgium. Methods The HELICON data linkage is developed at the individual level to investigate the risk of COVID-19 hospitalization and the influence of various social and biomedical factors during and after the crisis. Data are drawn from data collections on hospitalization from the COVID-19 health surveillance (Sciensano), on the socioeconomic and sociodemographic context (Statistics Belgium), and on healthcare use and reimbursement (InterMutualistic Agency). Results A representative case-cohort study is established comprising 1,149,264 million randomly selected Belgians and 44,508 hospitalized patients. Annual follow-up is scheduled over a four-year span, allowing the investigation of pre- and post-pandemic health data from July 2020 to January 2026. Conclusions The HELICON data linkage took 3.5 years to complete. Among the many challenges, we were faced with complicated approval procedures, ambiguous data security guidelines, unclear cost estimates, and technical issues related to the analysis environment. Building on these experiences, we explore the strengths and weaknesses of data linkages as a research instrument during the COVID-19 pandemic and discuss which lessons should be drawn to for the post-pandemic era.