This dataset shows the the world's best hospital in 2023 issued by the Newsweek and Statista.

According to a ranking of the best hospitals in the U.S., the best hospital for adult cancer is the University of *******************************, which had a score of *** out of 100, as of 2025. This statistic shows the top 10 hospitals for adult cancer in the United States based on the score given by U.S. News and World Report's annual hospital ranking.

According to a ranking by Statista and Newsweek, the best hospital in the United States is the *********** in Rochester, Minnesota. Moreover, the *********** was also ranked as the best hospital in the world, among over 50,000 hospitals in 30 countries. **************** in Ohio and the ************* Hospital in Maryland were ranked as second and third best respectively in the U.S., while they were second and forth best respectively in the World.

As of 2025, New York-Presbyterian hospital is the largest hospital in the United States with its eight campuses based in New York City. This was followed by AdventHealth Orlando in Florida stands as the second largest hospital in the United States, boasting an impressive 2,787 beds. Evolving landscape of U.S. hospitals Despite the decline in the total number of hospitals since 1980, the healthcare sector continues to grow in other ways. U.S. hospitals now employ about 7.5 million workers and generate a gross output of around 1,263 billion U.S. dollars. The Hospital Corporation of America, based in Nashville, Tennessee, leads the pack as the largest health system in the country, operating 222 hospitals as of February 2025. This reflects a trend towards consolidation and the rise of for-profit hospital chains, which gained prominence in the 1990s. Specialization and emergency care While bed count is one measure of hospital size, institutions also distinguish themselves through specialization and emergency care capabilities. For instance, the University of California at Los Angeles Medical Center performed 22,287 organ transplants between January 1988 and March 2025, making it the leading transplant center in the nation. In terms of emergency care, Parkland Health and Hospital System in Dallas recorded the highest number of emergency department visits in 2024, with 235,893 patients seeking urgent care.

According to a hospital ranking carried out by Fudan University in 2022, the best hospital in China was Peking Union Medical College Hospital, with a quality index score of *****. The second position went to West China Hospital affliated to Sichuan University, with a score of *****.

*Standardized units.Characteristics of the top 50 Cancer Hospitals, as ranked by the US News and World Report.

According to a ranking by Statista and Newsweek, the world's best hospital is the *********** in Rochester, Minnesota. A total of **** U.S. hospitals made it to the top ten list, while one hospital in each of the following countries was also ranked among the top ten best hospitals in the world: Canada, Sweden, Germany, Israel, Singapore, and Switzerland.

HCAHPS Hospital Ratings Survey

Patient Experience Ratings 2018-2020

By Health [source]

About this dataset

This dataset contains ratings of hospitals, based on the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). This survey collects data from hospital patients on their experiences during an inpatient stay. The list includes several indicators to help gauge a hospital's quality, such as star ratings based on patient opinions and percentage of positive answers to HCAHPS questions. Additionally, there are measures such as the number of completed surveys, survey response rate percent and linear mean value which assist in evaluating patient experience at each medical institution. With this comprehensive dataset you can easily draw comparisons between hospitals and make informed decisions about healthcare services provided in your area

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How to use the dataset

This dataset provides useful information on the quality of care that hospitals provide. This dataset provides ratings and reviews of several hospitals, making it easy to compare hospitals in order to find out which hospital may best meet your needs.

The following guide will walk you through how to use this dataset effectively:

• Navigate the different columns available in this dataset by scrolling through the table. These include Hospital Name, Address, City, State, ZIP Code, County Name, Phone Number and HCAHPS Question among others.
• Examine important information such as the patient survey star rating and HCAHPS linear mean value for each hospital included in the dataset in order to evaluate it's performance against other hospitals based on standards set out by HCAHPS .
• Read any footnotes associated with each column carefully in order to fully understand what exactly is being measured. These may directly affect your evaluation of a particular hospital’s performance compared to others included in this dataset or even more so when compared against external sources of data outside this dataset such as other surveys or studies related to health care quality measurement metrics within that state or region where applicable & relevant (i..e Measure Start Date and Measure End Date).

• Pay careful attention also when evaluating factors related to survey response rates (e..g Survey Response Rate Percent Footnote) & what percentages are being reported here within each category; these figures may selectively bias results so ensure full transparency is achieved by reviewing all potential influencing factors/variables prior commencing investigations/data analysis/interpretation based upon this data-set alone(or any subset thereof).

  By following these steps you should be able set up your own criteria for measuring various aspects of health care quality across different states & cities - ensuring optimal access & safety measures for both patients & healthcare providers alike over time - thus ultimately aiding decision making processes towards improved patient outcomes worldwide!

Research Ideas

• Tracking patient experience trends over time: This dataset can be used to analyze trends in patient experience over time by identifying changes in survey responses, star ratings, and response rates across hospitals.
• Establishing a benchmark for high-quality hospital care: By studying the scores of the top-performing hospitals within each category, healthcare administrators can set standards and benchmarks for quality of care in their own hospitals.
• Comparing hospital ratings to inform decision making: Patients and family members looking to book an appointment at a hospital or doctors office can use this dataset to compare different facilities’ HCAHPS scores and make an informed decision about where they would like to go for their medical treatment

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - **Keep int...

The dataset contains counts for the Top Five inpatient diagnosis groups based on Major Diagnostic Categories (MDCs) from the Patient Discharge Data (PDD) for each California hospital. Each MDC corresponds to a major organ system (e.g., Respiratory System, Circulatory System, Digestive System) rather than a specific disease (e.g., cancer, sepsis). The MDCs are also generally associated with a particular medical specialty. Therefore, the MDCs can be used to help identify what types of health care specialists are needed at each facility. For instance, a facility with “Circulatory System, Disease and Disorders” as one of their Top Five MDC diagnosis groups is more likely to have a greater need for cardiac specialists. The data will be updated on an annual basis.

The acute-care pathway (from the emergency department (ED) through acute medical units or ambulatory care and on to wards) is the most visible aspect of the hospital health-care system to most patients. Acute hospital admissions are increasing yearly and overcrowded emergency departments and high bed occupancy rates are associated with a range of adverse patient outcomes. Predicted growth in demand for acute care driven by an ageing population and increasing multimorbidity is likely to exacerbate these problems in the absence of innovation to improve the processes of care.

Key targets for Emergency Medicine services are changing, moving away from previous 4-hour targets. This will likely impact the assessment of patients admitted to hospital through Emergency Departments.

This data set provides highly granular patient level information, showing the day-to-day variation in case mix and acuity. The data includes detailed demography, co-morbidity, symptoms, longitudinal acuity scores, physiology and laboratory results, all investigations, prescriptions, diagnoses and outcomes. It could be used to develop new pathways or understand the prevalence or severity of specific disease presentations.

PIONEER geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix.

Electronic Health Record: University Hospital Birmingham is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & an expanded 250 ITU bed capacity during COVID. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Scope: All patients with a medical emergency admitted to hospital, flowing through the acute medical unit. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes patient demographics, co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to process of care (timings, admissions, wards and readmissions), physiology readings (NEWS2 score and clinical frailty scale), Charlson comorbidity index and time dimensions.

Available supplementary data: Matched controls; ambulance data, OMOP data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Children's Hospitals Pricing Data

Hospital pricing information for Children's Hospitals and Clinics of Minnesota

By Amber Thomas [source]

About this dataset

This dataset provides machine-readable hospital pricing information from Children's Hospitals and Clinics of Minnesota. It includes three files: 2022-top-25-hospital-based-clinics-list.csv, which contains the top 25 primary care procedure prices for hospital-based clinics at Children's Hospitals; 2022-standard-list-of-charges-hospital-op.csv, which comprises the standard charges for outpatient procedures in 2022, including procedure codes, fees, and insurance coverage; and 2022-msdrg.csv, containing machine-readable hospital pricing information specifically related to the 2022 Medicare Severity Diagnosis Related Groups (MS-DRG) codes. These datasets were obtained directly from Children's Hospitals' website as part of their compliance with the Centers for Medicare and Medicaid Services IPPS Final Rule. The data was collected programmatically using a custom script written in Node.js and Microsoft Playwright, then mirrored on the data.world platform. If you come across any errors or discrepancies in this data, please report them in the Discussion tab or contact supportdata.world

How to use the dataset

• Understanding the Files:

  • The dataset consists of three files: 2022-top-25-hospital-based-clinics-list.csv, 2022-standard-list-of-charges-hospital-op.csv, and 2022-msdrg.csv.
  • 2022-top-25-hospital-based-clinics-list.csv contains the top 25 primary care procedure prices for hospital-based clinics at Children's Hospitals and Clinics of Minnesota.
  • 2022-standard-list-of-charges-hospital-op.csv includes the standard list of charges for outpatient procedures at Children's Hospitals and Clinics of Minnesota, including procedure codes, fees, and insurance coverage.
  • The file 2022-msdrg.csv provides machine-readable hospital pricing information specifically related to the Medicare Severity Diagnosis Related Groups (MS-DRG) codes.

• Accessing the Data:

  • The data can be accessed from their source on the Children's Hospitals and Clinics of Minnesota website.

• Data Collection Method:

  • All data in this dataset was collected programmatically using a custom script written in Node.js and utilizing Microsoft Playwright, an open-source library for browser automation.

• How to Handle Errors or Suggestions:

  • If you have found any errors or have suggestions regarding this dataset, you can leave a note on the Discussion tab of this dataset on Kaggle or reach out via email to supportdata.world.

• Dataset Use Cases:

  a) Research & Analysis: Analyze primary care procedure prices at Children's Hospitals and Clinics of Minnesota based on different procedure codes present in the top-25 list from 2022 hospital-based clinics file (2022-top-25-hospital-based-clinics-list.csv).

  b) Cost Comparison: Compare fees and charges for outpatient procedures at Children's Hospitals and Clinics of Minnesota with other healthcare providers using the 2022 standard list of charges file (2022-standard-list-of-charges-hospital-op.csv).

  c) Insurance Coverage Analysis: Investigate insurance coverage details for outpatient procedures at Children's Hospitals and Clinics of Minnesota by referring to the insurance coverage column in the 2022 standard list of charges file (2022-standard-list-of-charges-hospital-op.csv).

  d) Medicare Severity Diagnosis Related Groups (MS-DRG): Explore machine-readable hospital pricing information specifically

Research Ideas

• Price comparison: This dataset can be used to compare the prices of different primary care procedures and outpatient procedures at Children's Hospitals and Clinics of Minnesota. This information can help patients make informed decisions about their healthcare options based on affordability.
• Insurance coverage analysis: The dataset includes information about insurance coverage for each procedure, which can be analyzed to understand which procedures are covered by different insurance providers. This analysis can help patients determine if their insurance will cover a specific procedure or if they will need to pay out-of-pocket.
• Trend analysis: By comparing the pricing information from previous years' datasets, this dataset can be used to analyze trends in healthcare costs over time at Children's Hospitals and Clinics of Minnesota. This analysis can provide insights into how healthcare costs are changing and help identify areas where cost improvements may be needed

...

According to a hospital ranking carried out in 2022 and based on seven different dimensions, Hospital Israelita Albert Einstein was considered the hospital with the highest care quality in Latin America. Located in São Paulo - Brazil, this health institution reached a quality index score of *****. Hospital Sírio-Libanês also located in Brazil, ranked second, with a score of *****. Latin American hospitals and their capacity to host patients When it comes to hosting patients, hospitals Irmandade da Santa Casa de Misericórdia de Porto Alegre located in Brazil, and Sanatorio Guemes based in Argentina, ranked among the leading hospitals in Latin America as of 2022. It was estimated that Brazil and Argentina were the two Latin American countries with the highest number of hospital beds in the region in 2020, with more than ******* and ******* hospital beds, respectively. Public opinion on healthcare quality It was also Argentina that had the highest share of satisfied patients among a selection of countries in Latin America according to a 2023 survey, with ** percent of interviewees stating they had accessed a good or very good healthcare service. Colombian patients followed, with **** out of ten people satisfied with the healthcare received. Accordingly, a recent study estimated that nearly half of the population in Argentina and Colombia distrusted the healthcare system, with approximately ** percent and ** percent of respondents claiming they trust the health systems in their respective countries.

The Google Map Hospital Data for Dhaka City is a dataset available on Kaggle that provides comprehensive information on various hospitals located in Dhaka city. The dataset includes important attributes such as hospital name, ratings, number of ratings, category, address, contact information, links, and comments. With this dataset, researchers can analyze and compare the quality of healthcare services provided by different hospitals in the city. This dataset can also be used for various healthcare applications, such as finding the nearest hospital with specific facilities, identifying the most popular hospitals in the city, and more.

Hospital Door Hangers for Newborns Market Outlook

According to our latest research, the global hospital door hangers for newborns market size reached USD 185 million in 2024, with a robust year-on-year growth momentum. The market is forecasted to grow at a CAGR of 6.4% between 2025 and 2033, reaching an estimated value of USD 322 million by 2033. This growth is primarily driven by the increasing emphasis on personalized patient care, enhanced hospital branding, and the rising birth rates in emerging economies. As per our comprehensive industry analysis, the market is experiencing substantial traction due to the growing adoption of innovative, customizable products and the expanding focus on newborn safety and family engagement within healthcare facilities.

One of the most significant growth factors propelling the hospital door hangers for newborns market is the heightened awareness regarding newborn safety and the need for clear identification in hospital environments. Hospitals and maternity clinics are increasingly prioritizing measures that ensure both infant security and parental peace of mind. Door hangers serve as a simple yet effective tool for visually communicating essential details such as the newborn’s name, gender, and other critical information, reducing the risk of misidentification. Additionally, the integration of QR codes and RFID tags in advanced door hangers is further enhancing their utility by enabling real-time information access and tracking, which is highly valued in modern healthcare settings.

Another key driver is the growing demand for personalized and themed hospital door hangers, which aligns with the broader trend of customization in healthcare services. Parents today seek a more memorable and engaging experience during childbirth, and hospitals are responding by offering customizable door hangers that reflect the newborn’s identity and family preferences. This trend is particularly pronounced in private hospitals and high-end maternity clinics, where patient satisfaction is a top priority. Themed door hangers, featuring popular characters or motifs, are also gaining traction as they add a celebratory touch to the birthing experience, making it more special for families and visitors alike.

The rapid expansion of healthcare infrastructure in emerging markets is another crucial growth catalyst for the hospital door hangers for newborns market. Countries in Asia Pacific and Latin America are witnessing significant investments in new hospitals, birthing centers, and maternity clinics, driven by rising birth rates and improved access to healthcare services. This infrastructural growth is directly contributing to higher demand for hospital door hangers, as these facilities strive to implement international best practices in patient care and security. Moreover, government initiatives promoting maternal and child health are further amplifying the adoption of such products across public and private healthcare institutions.

Regionally, North America continues to dominate the market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The presence of advanced healthcare systems, high standards of patient safety, and a strong culture of personalization are key factors supporting market growth in these regions. Meanwhile, Asia Pacific is expected to exhibit the highest CAGR during the forecast period, driven by increasing healthcare investments and a burgeoning population. Latin America and the Middle East & Africa are also showing promising growth, though at a relatively moderate pace, as healthcare modernization efforts gain momentum in these regions.

Product Type Analysis

The hospital door hangers for newborns market is segmented by product type into Personalized Door Hangers, Standard Door Hangers, Themed Door Hangers, and Others. Personalized door hangers have emerged as the most popular segment, accounting for a significant share of the market in 2024. These products are highly favored by both healthcare providers and parents as they allow for the inclusion of specific details such as the newborn’s name, date of birth, and sometimes even a photograph. Hospitals leveraging personalized door hangers often report higher levels of parental satisfaction, as these products contribute to a more intimate and memorable birth experience. The demand for personalized options is particularly strong in private hospitals and urban healthcare centers, where diffe

2010 New York State Hospital Inpatient Discharge Data

Detailed Characteristics, Diagnoses, Treatments and Payments

By Health Data New York [source]

About this dataset

The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified dataset is a wealth of information, containing discharge level detail on various aspects of hospital inpatient discharges in New York State during the year 2010. From patient characteristics such as age group, gender, race and ethnicity to diagnoses, treatments, services and charges - all data elements excluding those consideredidentifiable have been made available within this dataset. This data does not contain any protected health information (PHI) under the Health Insurance Portability and Accountability Act (HIPAA). Understanding the plethora of details in this data can give individuals insights into many varying aspects related to hospital care. Before using or referencing any data from this dataset it is important to read and understand the Terms of Service which can be found at [link]. Dive into understanding more about what goes on behind closed doors at hospitals with the SPARCS Inpatient De-identified Dataset!

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How to use the dataset

This guide is here to provide you with information on how to use this dataset efficiently and effectively. Here are some useful tips:

• Familiarize Yourself With The Data: Before diving into the data itself it is important to understand what it is you will be working with. Take time to read through the columns that are included in the dataset as well as any other relevant documentation associated with this data so that you know exactly what it is you are looking at.
• Clean and Process The Data: When working with raw datasets such as this one it is important to ensure that all of the data provided has been properly cleaned and structured before being used for further analysis or machine learning models. Taking contamination for example; if not correctly diagnosed then these can affect your results later down the line when drawing conclusions from your analysis results. Additionally take care when handling missing values - weighing usage / exclusion of certain values and where applicable looking for patterns which may suggest underlying reasons leading up to them being absent from certain records etc...
• Explore Your Hypothesis/Goals Further: After understanding more about what this data has got behind offer explore any potential hypothesis/goals further by analysing different correlations between various factors across different dimensions (by taking various columns into consideration). Visualisation tools such s Tableau can be used here - however take great care when doing so; visualisations too easily dictate terms leaving a bias sometimes without particularly realising or consciously intending so when carrying out an analysis on a large dataset (which isn’t necessarily bad but something which needs close attention).

4 Lastly Utilise Actionable Insights Gathered From Your Findings: Once your initial exploration phase has been completed utilize any insights gathered within a productive manner - share your findings & collaborate closely with key stakeholders where applicable presenting any actionable insights gained from your analysis making use potential optimization strategies & aiming towards greater understanding of issues / opportunities affecting business practices

Research Ideas

• Identifying health disparities in hospital inpatient discharges across New York State – This dataset can be used to understand the regional variations between communities across NY and diagnose which areas need more healthcare coverage for certain diagnosis codes or procedure codes.
• Knowing patient needs ahead of time based on demographics, diagnosis, and procedures – With this dataset, health professionals will be able to get an idea of what kind of treatments most patients look for when they come down with a particular illness or injury. This will allow them to better prepare the necessary equipment, medicine and resources needed beforehand so that they don't have to search while the patient is already at their facility waiting for treatment.
• Improving cost efficiency by looking at correlations between different payment sources – With this dataset, hospitals could identify any patterns or correlations between different payment sources (such as Medicaid and private insurance) that could be used toward improving cost efficiency during inpatient visits by optimizing resource allocation according to source ...

Annual Excel pivot tables display the top 25 MS-DRGs (Medicare Severity-Diagnosis Related Groups) per hospital. The ranking can be sorted by the number of discharges, average charge per stay, or average length of stay.

In 2024, Bumrungrad International Hospital ranked first among the leading hospitals in Thailand with a score of ** percent. In the same year, it was the only hospital from Thailand that placed 130th among the *** world's best hospitals on the Global Hospital Rating by Newsweek and Statista. Thailand is one of the most popular medical tourism hubs in Southeast Asia.

IntroductionIn confronting the sudden COVID-19 epidemic, China and other countries have been under great pressure to block virus transmission and reduce fatalities. Converting large-scale public venues into makeshift hospitals is a popular response. This addresses the outbreak and can maintain smooth operation of a country or region's healthcare system during a pandemic. However, large makeshift hospitals, such as the Shanghai New International Expo Center (SNIEC) makeshift hospital, which was one of the largest makeshift hospitals in the world, face two major problems: Effective and precise transfer of patients and heterogeneity of the medical care teams.MethodsTo solve these problems, this study presents the medical practices of the SNIEC makeshift hospital in Shanghai, China. The experiences include constructing two groups, developing a medical management protocol, implementing a multi-dimensional management mode to screen patients, transferring them effectively, and achieving homogeneous quality of medical care. To evaluate the medical practice performance of the SNIEC makeshift hospital, 41,941 infected patients were retrospectively reviewed from March 31 to May 23, 2022. Multivariate logistic regression method and a tree-augmented naive (TAN) Bayesian network mode were used.ResultsWe identified that the three most important variables were chronic disease, age, and type of cabin, with importance values of 0.63, 0.15, and 0.11, respectively. The constructed TAN Bayesian network model had good predictive values; the overall correct rates of the model-training dataset partition and test dataset partition were 99.19 and 99.05%, respectively, and the respective values for the area under the receiver operating characteristic curve were 0.939 and 0.957.ConclusionThe medical practice in the SNIEC makeshift hospital was implemented well, had good medical care performance, and could be copied worldwide as a practical intervention to fight the epidemic in China and other developing countries.

List of Top Authors of University College Hospital sorted by article citations.

IntroductionThe use of Complementary and Integrative Medicine (CIM) is very popular among the general population in Germany. However, international studies show that nurses, physicians, and other health care professionals (HCPs) at hospitals often do not feel sufficiently informed about different CIM approaches. Moreover, they do not feel trained enough to counsel their patients appropriately. In the German-speaking context, particularly within university hospitals, research on this subject is scarce. Therefore, the aim of this explorative study was to evaluate attitudes, subjective knowledge, and needs regarding CIM among HCPs with direct patient interaction across all four university hospitals in the federal state of Baden-Württemberg, Germany (Tübingen, Ulm, Freiburg, Heidelberg).MethodsThe multicenter, cross-sectional, anonymous full survey was conducted online using a self-developed, semi-structured, web-based questionnaire. Recruitment took place via all-inclusive e-mail distribution lists of all four university hospitals.ResultsA total of n = 2,026 participants (response rate varied by location from about 5 to 14%) fully answered the questionnaire. Nurses constituted the largest professional group (n = 1,196; 59%), followed by physicians (n = 567; 28%), physiotherapists (n = 54), psychologists (n = 48), midwives (n = 37), and other professions (n = 124). More than two-thirds (71%, n = 1,437) of the participants were female and 14% (n = 286) reported additional training in CIM. The overall attitude toward CIM (10-point Likert scale, 10 = “very favorable”) was clearly positive (M ± SD: 7.43 ± 2.33), with notable differences between professional groups: midwives (9.05 ± 1.18), physiotherapists (8.44 ± 1.74), and nurses (8.08 ± 1.95) expressed the highest support, whereas physicians (5.80 ± 2.39) the lowest. 42% of the participants incorporated CIM in patient care (from 33% of physicians to 86% of midwives). Overall, relaxation therapy (n = 1,951; 96%), external applications (n = 1,911; 94%), massage (n = 1,836; 91%), and meditation/mindfulness (n = 1,812; 89%) were rated as useful or rather useful for patients. The average self-assessed knowledge level about CIM was moderate (M ± SD: 5.83 ± 2.03). Most of the participants found CIM training at university hospitals important and saw research about CIM as one of the tasks of university hospitals. The participants expressed the highest interest in education for acupuncture/acupressure, relaxation therapies, and manual medicine.DiscussionThis comprehensive survey of health care professionals (HCPs) at university hospitals in Germany reveals a clearly positive disposition toward CIM, aligning with findings from other hospital-based surveys and highlighting differences among professional groups. While most therapies deemed beneficial for patient care are supported by positive evidence, further research is required for others. Given the average self-reported knowledge of CIM, targeted education is essential to meet the needs of both HCPs and patients and to ensure the provision of evidence-based information on the risks and benefits of CIM.