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

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.

As of February 2025, the Hospital Corporation of America, based in Nashville, Tennessee, was the largest health system in the United States, with a total of 222 hospitals. HCA Healthcare is also the largest U.S. health system when ranked by the number of beds and, as expected, by net patient revenue.Hospitals in the United StatesCurrently, there are approximately 6,120 hospitals in the United States. Looking over the past decades, this figure was constantly decreasing. For example, there were nearly 7,000 hospitals in 1980. There are some 5.3 million persons employed in U.S. hospitals in full-time. Contrary to the decrease in the number of hospitals, employment has been increasing steadily. According to the Bureau of Economic Analysis, U.S. hospitals generate a total gross output of around 1,075 billion U.S. dollars. The largest portion of U.S. hospitals are non-profit facilities. A smaller share includes private-owned for-profit hospitals. In most cases, these hospitals are part of hospital chains. For-profit hospitals developed especially in the 1990s, with the aim to gain profit for their shareholders. The Hospital Corporation of America, based in Nashville, Tennessee, is the U.S. for-profit hospital operator with the highest number of hospitals.

The average for 2020 based on 36 countries was 4.44 hospital beds. The highest value was in South Korea: 12.65 hospital beds and the lowest value was in Mexico: 0.99 hospital beds. The indicator is available from 1960 to 2021. Below is a chart for all countries where data are available.

According to a ranking by Statista and Newsweek, the best hospital in Norway is Oslo Universitetssykehus in Oslo. Moreover, Oslo Universitetssykehus was also ranked as the **** best hospital in the world, among over ****** hospitals in ** countries. St. Olavs Hospital in Trondheim and Haukeland Universitetssykehus in Bergen were ranked as second and third best respectively in the Norway, while they were ***** and ***** best respectively in the World.

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Hospital Beds Market Size 2025-2029

The hospital beds market size is forecast to increase by USD 2.69 billion, at a CAGR of 9.9% between 2024 and 2029.

The market is experiencing significant growth due to the rising number of medical emergencies and the increase in infectious diseases. The global health crisis has highlighted the importance of having an adequate supply of hospital beds to manage the influx of patients. However, the high cost of automated hospital beds poses a challenge for healthcare providers, as they seek to balance the need for advanced technology with budget constraints. Moreover, the growing prevalence of chronic diseases, such as diabetes and cardiovascular diseases, necessitates long-term hospitalization, further increasing the demand for hospital beds. Additionally, the aging population and their subsequent healthcare needs are also contributing to market growth.
To capitalize on these opportunities, companies can focus on developing cost-effective solutions that offer advanced features, ensuring they cater to the evolving needs of healthcare providers while remaining competitive in the market. Navigating the challenges of cost and affordability will be crucial for market success, as providers seek to optimize their budgets while maintaining the highest level of patient care.

What will be the Size of the Hospital Beds Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The hospital bed market continues to evolve, with dynamic shifts in market trends and applications across various healthcare sectors. Hospital bed frames, a fundamental component of patient care, undergo constant innovation to enhance ergonomics and support systems. Mattresses with advanced pressure distribution technology cater to the unique needs of bariatric patients, while ICU beds integrate intravenous pole systems and height adjustment mechanisms for intensive care. Bedside safety features, such as fall prevention systems and bedside rails, are increasingly integrated into hospital bed designs. Bedside monitors, lighting, and call systems further enhance patient safety and comfort. Hospital bed sustainability is a growing concern, with a focus on recycling and disposal methods, as well as the use of eco-friendly materials in bed covers and linens.

Anti-embolism stockings and durability are essential considerations in hospital bed design, ensuring patient safety and longevity. Hospital bed certification standards continue to evolve, driving innovation in bedside safety and maintenance. The market for hospital bed accessories, such as overbed tables and height adjustment mechanisms, is expanding to cater to diverse patient needs. Ergonomics and aesthetics are increasingly important in hospital bed design, with a focus on patient comfort and satisfaction. The integration of electric actuators and sterilization systems further enhances the functionality and efficiency of hospital beds. The ongoing development of pressure relief systems and anti-decubitus mattresses underscores the continuous pursuit of innovation in this dynamic market.

How is this Hospital Beds Industry segmented?

The hospital beds industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Manual beds
  Semi-automated beds
  Automated beds


Application

  Intensive care
  Acute care
  Home care


End-user

  Hospitals
  Home healthcare
  Elderly care facilities
  Ambulatory surgical centers


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

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By Product Insights

The manual beds segment is estimated to witness significant growth during the forecast period.

The market encompasses a range of products designed for healthcare settings, including manual and electric beds, bariatric beds, ICU beds, and recovery room beds. These beds prioritize ergonomics, offering mattress support systems, adjustable frames, and pressure distribution systems to ensure patient comfort and support. Hospital bed sustainability is a growing concern, leading to the development of eco-friendly materials and recycling programs for bed components. Bedside tables, rails, and lighting provide added functionality, while certifications ensure safety and compliance. Hospital bed linens and covers, along with anti-embolism stockings, contribute to patient care and hygiene. Fall prevention systems and repair services ensure patient safety and bed longevity.

Operating room tables and electric actuators facilitate efficien

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.

This dataset provides values for HOSPITAL BEDS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

South Korea Number of Hospital was up 3.5% in 2019, compared to the previous year.

According to a ranking by Statista and Newsweek, the best hospital in Denmark is the Rigshospitalet - København in Copenhagen. Moreover, the Rigshospitalet - København was also ranked as the **** best hospital in the world, among over ****** hospitals in ** countries. Aarhus Universitetshospital in Aarhus and Odense Universitetshospital in Odense were ranked as second and third best respectively in the Denmark, while they were **** and **** best respectively in the World.

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 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.

Hospitals play a critical role in healthcare, offering specialized treatments and emergency services essential for public health, regardless of economic fluctuations or individuals' financial situations. Rising incomes and broader access to insurance have fueled demand for care in recent years, supporting hospitals' post-pandemic recovery initiated by federal policies and funding. The recovery for many hospitals was also promoted by mergers that lessened financial strains, especially in rural hospitals. This trend toward consolidation has resulted in fewer enterprises relative to establishments, enhancing hospitals' bargaining power regarding input costs and insurance reimbursements. With this improved position, hospitals are expected to see revenue climb at a CAGR of 2.0%, reaching $1.5 trillion by 2025, with a 3.2% increase in 2025 alone. Competition, economic conditions and regulatory changes will impact hospitals based on size and location. Smaller hospitals, particularly rural ones, may encounter more significant obstacles as the industry transitions from fee-based to value-based care. Independent hospitals face wage inflation, staffing shortages and drug supply costs. Although state and federal policies aim to support small rural hospitals in addressing hospital deserts, uncertainties linger over federal Medicare funding and Medicaid reimbursements, which account for nearly half of hospital care spending. Even so, increasing per capita disposable income and increasing the number of individuals with private insurance will boost revenues from private insurers and out-of-pocket payments for all hospitals, big and small. Hospitals will continue incorporating technological advancements in AI, telemedicine and wearables to enhance their services and reduce cost. These technologies aid hospital systems in strategically expanding outpatient services, mitigating the increasing competitive pressures from Ambulatory Surgery Centers (ASCs) and capitalizing on the increased needs of an aging adult population and shifts in healthcare delivery preferences. As the consolidation trend advances and technology adoption further leverages economies of scale, industry revenue is expected to strengthen at a CAGR of 2.4%, reaching $1.7 trillion by 2030, with steady profit over the period.

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

ContextPrior research has faulted the US News and World Report hospital specialty rankings for excessive reliance on reputation, a subjective measure of a hospital's performance.ObjectiveTo determine whether and to what extent reputation correlates with objective measures of research productivity among cancer hospitals.DesignA retrospective observational study.SettingAutomated search of NIH Reporter, BioEntrez, BioMedline and Clinicaltrials.gov databases.ParticipantsThe 50 highest ranked cancer hospitals in 2013's US News and World Report Rankings.ExposureWe ascertained the number of NCI funded grants, and the cumulative funds received by each cancer center. Additionally, we identified the number of phase I, phase II, and phase III studies published and indexed in MEDLINE, and registered at clinicaltrials.gov. All counts were over the preceding 5 years. For published articles, we summed the impact factor of the journals in which they appeared. Trials were attributed to centers on the basis of the affiliation of the lead author or study principal investigator.Main OutcomeCorrelation coefficients from simple and multiple linear regressions for measures of research productivity and a center's reputation.ResultsAll measures of research productivity demonstrated robust correlation with reputation (mean r-squared  = 0.65, median r-squared = 0.68, minimum r-squared = .41, maximum r-squared = 0.80). A multivariable model showed that 93% of the variation in reputation is explained by objective measures.ConclusionContrary to prior criticism, the majority of reputation, used in US News and World Rankings, can be explained by objective measures of research productivity among cancer hospitals.

Thailand TH: Hospital Beds: per 1000 People data was reported at 2.100 Number in 2010. This records a decrease from the previous number of 2.200 Number for 2002. Thailand TH: Hospital Beds: per 1000 People data is updated yearly, averaging 1.684 Number from Dec 1960 (Median) to 2010, with 12 observations. The data reached an all-time high of 2.200 Number in 1999 and a record low of 0.740 Number in 1960. Thailand TH: Hospital Beds: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.World Bank: Health Statistics. Hospital beds include inpatient beds available in public, private, general, and specialized hospitals and rehabilitation centers. In most cases beds for both acute and chronic care are included.; ; Data are from the World Health Organization, supplemented by country data.; Weighted average;

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.

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.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Smart Hospital Market size was valued at USD 67.77 Billion in 2024 and is projected to reach 310.17 USD Billion by 2031 growing at a CAGR of 23.10% from 2024 to 2031.

Global Smart Hospital Market Drivers

The market drivers for the Smart Hospital Market can be influenced by various factors. These may include:

Technological breakthroughs: The adoption of smart solutions in hospitals is being driven by the rapid breakthroughs in technology, such as wearables, robotics, artificial intelligence (AI), and the Internet of Things (IoT). Need for Streamlined Operations: To improve efficiency, cut expenses, and streamline operations, hospitals are progressively implementing smart technology. Smart hospital solutions facilitate the automation and optimisation of multiple operations, including resource allocation, inventory management, and patient management. Increasing Healthcare Costs: There is pressure on healthcare providers to cut costs without sacrificing quality of care. By minimising inefficiencies, preventing medical errors, and optimising resource utilisation, smart hospital solutions can lower total healthcare costs. Growing Ageing Population: The need for healthcare services is rising as a result of the global ageing population. More individualised and effective care delivery is made possible by smart hospital technology like telemedicine and remote monitoring, especially for older patients with chronic illnesses. Emphasis on Patient-Centric Care: Improving patient experiences and offering patient-centric care are becoming more and more important in healthcare facilities. Electronic health records (EHRs), patient portals, and remote monitoring devices are examples of smart hospital solutions that enable people to take an active role in their healthcare management and improve communication between patients and healthcare professionals. Government Regulations and Initiatives: The adoption of smart hospital solutions is being driven by government regulations and initiatives that aim to improve healthcare infrastructure and promote healthcare digitization. Additionally, hospitals are being encouraged to invest in smart technologies for compliance by regulatory demands such as those pertaining to electronic medical records and patient data protection. Impact of the COVID-19 Pandemic: In order to facilitate contactless healthcare delivery, telemedicine consultations, and remote patient monitoring, smart hospital solutions have become increasingly popular. This has helped the market for smart hospitals develop even more.