Big Data Analytics in Healthcare Market Outlook

The global market size for Big Data Analytics in Healthcare was valued at approximately USD 34 billion in 2023 and is anticipated to grow at a robust CAGR of 11.9%, reaching an estimated USD 90 billion by 2032. This remarkable growth is driven by the increasing adoption of data-driven decision-making processes within the healthcare sector, spurred by the mounting pressure to enhance operational efficiencies, improve patient outcomes, and reduce overall healthcare costs. The integration of big data analytics within healthcare systems is enabling organizations to leverage vast amounts of data, leading to enhanced patient care and streamlined operations.

A significant growth factor fueling the expansion of the big data analytics market in healthcare is the ever-increasing volume of data generated by healthcare systems. With the surge of electronic health records, wearable health devices, and various other digital health technologies, the volume of data being generated is unprecedented. This data, if analyzed correctly, holds the potential to transform healthcare delivery models, allowing for more precise diagnostics, personalized treatment plans, and proactive disease management strategies. Consequently, healthcare organizations are increasingly investing in big data analytics tools to harness this data for clinical and operational improvements.

Another key driver of market growth is the growing emphasis on value-based care and the need for healthcare providers to demonstrate high-quality patient outcomes. Value-based care models require providers to focus on the quality rather than the quantity of care delivered, inherently demanding the use of advanced analytics to derive actionable insights from patient data. Big data analytics facilitates the identification of patterns and trends that can lead to improved treatment effectiveness and patient satisfaction. This shift in care models is prompting healthcare organizations to integrate sophisticated analytics solutions that help in predictive modeling, trend analysis, and real-time decision-making, further propelling market expansion.

Additionally, the increasing incidence of chronic diseases worldwide is driving the need for more efficient healthcare services. Big data analytics in healthcare can play a critical role in managing chronic diseases by enabling preventive care and personalized treatment plans. By analyzing patient data, including historical health records, genetic information, and lifestyle choices, healthcare providers can predict potential health issues and intervene early, thereby improving patient outcomes and reducing healthcare costs. This capability is essential in managing the global burden of chronic diseases, thereby boosting the adoption of big data analytics solutions in the healthcare sector.

Regionally, North America dominates the market due to the presence of advanced healthcare infrastructure, the availability of technologically advanced products, and the high adoption rate of healthcare IT solutions. The region's robust regulatory environment and substantial investments in healthcare IT make it a fertile ground for the growth of big data analytics solutions. However, the Asia Pacific region is expected to exhibit the highest growth rate during the forecast period, driven by increasing government initiatives supporting the digitization of healthcare, burgeoning healthcare infrastructure, and a growing focus on precision medicine. The integration of big data analytics in healthcare across diverse regions is indicative of its global importance in optimizing healthcare delivery and patient care.

Component Analysis

In the realm of big data analytics in healthcare, the component segment is vitally instrumental to the market's evolution and includes software and services. Software solutions are the backbone of big data analytics, providing healthcare organizations with the necessary tools to collect, process, and analyze vast datasets. These solutions encompass data management and analytical platforms, which are indispensable for extracting actionable insights from disparate data sources. The software component is continually evolving with advancements in artificial intelligence and machine learning, which enhance data analytics capabilities. Moreover, the increasing demand for user-friendly, customizable software solutions is driving innovation and growth within this segment.

The services component, on the other hand, plays a critical role in the implementation and maintenance of big data analytics solutions. This component includes cons

Big Data in Healthcare Market Outlook

According to our latest research, the global Big Data in Healthcare market size reached USD 41.2 billion in 2024, demonstrating robust expansion driven by the increasing adoption of advanced analytics and data-driven decision-making in the healthcare sector. The market is projected to grow at a CAGR of 17.4% from 2025 to 2033, reaching an estimated value of USD 154.1 billion by 2033. This significant growth is primarily attributed to the surging volume of healthcare data, advancements in artificial intelligence and machine learning, and the increasing focus on improving patient outcomes and operational efficiency across healthcare institutions worldwide.

One of the primary growth factors fueling the Big Data in Healthcare market is the exponential rise in healthcare data generation, driven by the widespread adoption of electronic health records (EHRs), wearable devices, and connected medical equipment. As healthcare organizations seek to harness actionable insights from this data deluge, the demand for advanced analytics solutions has surged. The integration of big data analytics enables providers to enhance clinical decision-making, reduce medical errors, and optimize treatment protocols, thereby improving patient care and safety. Furthermore, the growing emphasis on value-based care models has compelled healthcare stakeholders to invest in robust data analytics platforms that can support population health management and evidence-based medicine, further accelerating market expansion.

Another key driver of the Big Data in Healthcare market is the growing need for cost containment and operational efficiency within healthcare organizations. Rising healthcare costs, resource constraints, and the increasing complexity of healthcare delivery have prompted providers and payers to leverage big data analytics to streamline operations, reduce redundancies, and enhance resource allocation. Financial analytics applications, in particular, are witnessing substantial uptake as organizations strive to identify cost-saving opportunities, detect fraudulent claims, and improve revenue cycle management. Additionally, operational analytics solutions are being deployed to optimize supply chain management, workforce planning, and facility utilization, resulting in enhanced productivity and reduced overheads.

The rapid advancement of artificial intelligence (AI), machine learning, and cloud computing technologies has also played a pivotal role in propelling the Big Data in Healthcare market forward. AI-driven analytics platforms are enabling healthcare providers to uncover hidden patterns in patient data, predict disease outbreaks, and personalize treatment plans based on individual patient profiles. The proliferation of cloud-based solutions has further democratized access to advanced analytics tools, allowing even small and medium-sized healthcare organizations to leverage big data capabilities without significant upfront investments in IT infrastructure. This technological evolution is expected to continue driving innovation and adoption across the global healthcare landscape.

From a regional perspective, North America continues to dominate the Big Data in Healthcare market, accounting for the largest revenue share in 2024, followed by Europe and Asia Pacific. The region's leadership is underpinned by robust healthcare IT infrastructure, high adoption rates of electronic health records, and strong government initiatives promoting data interoperability and healthcare digitization. Meanwhile, Asia Pacific is poised for the fastest growth during the forecast period, fueled by rapid healthcare modernization, expanding digital health initiatives, and increasing investments in healthcare analytics by both public and private sectors. As healthcare systems worldwide continue to prioritize data-driven transformation, the market's regional landscape is expected to evolve, with emerging economies playing an increasingly prominent role in shaping future growth trajectories.

In the evolving landscape of healthcare analytics, the concept of Healthcare Dataplaces is gaining traction as a transformative approach to managing and utilizing vast amounts of healthcare data. These dataplaces serve as centralized hubs where diverse datasets from various

Healthcare Big Data Analytics Market Outlook

The global healthcare big data analytics market size is projected to achieve a robust growth trajectory, with a valuation of approximately USD 32 billion in 2023. It is anticipated to soar to around USD 115 billion by 2032, reflecting an impressive compound annual growth rate (CAGR) of 15.4%. This remarkable growth can largely be attributed to the increasing demand for efficient data management systems in the healthcare sector, the rising need for data-driven decision-making, and the expanding adoption of analytics in diverse healthcare applications. The integration of artificial intelligence and machine learning in analytics, the emphasis on personalized medicine, and the growing importance of predictive analytics are further propelling the market forward.

One of the key growth drivers in the healthcare big data analytics market is the rising necessity for cost reduction and improved operational efficiency within the healthcare sector. Hospitals and clinics are increasingly recognizing the value of analytics in streamlining processes, reducing waste, and enhancing patient care. By leveraging big data analytics, healthcare providers can gain insights into patient care patterns, optimize resource allocation, and minimize unnecessary expenditures. This drive towards efficiency is further bolstered by government initiatives and policies aimed at improving healthcare delivery and reducing costs, creating a fertile ground for the adoption of advanced analytics solutions.

Another significant factor contributing to the market's expansion is the growing emphasis on personalized and precision medicine. As healthcare providers aim to offer more tailored treatment options, the analysis of vast datasets becomes crucial. Big data analytics facilitates the identification of patterns and trends in patient data, enabling healthcare providers to make informed decisions regarding personalized treatment plans. Moreover, the continuous advancements in genomics and biotechnology are generating immense volumes of data, necessitating robust analytics solutions to derive actionable insights. This trend towards personalized care is expected to drive substantial investments in big data analytics technologies in the coming years.

Additionally, the increasing prevalence of chronic diseases and the aging global population are driving the demand for effective population health management. Big data analytics plays a pivotal role in analyzing population health trends, identifying at-risk individuals, and devising preventive strategies. Governments and healthcare organizations are increasingly focusing on population health analytics to enhance public health outcomes and reduce the burden on healthcare infrastructure. This growing demand for comprehensive population health management solutions is expected to be a significant driving force for the healthcare big data analytics market over the forecast period.

Healthcare Analytics & Medical Analytics are becoming increasingly vital in the pursuit of personalized and precision medicine. By leveraging these analytics, healthcare providers can delve deeper into patient data to uncover insights that inform individualized treatment plans. This approach not only enhances patient outcomes but also optimizes the use of healthcare resources. As the demand for personalized care continues to rise, the role of healthcare analytics in tailoring treatments to individual patient needs is expected to grow exponentially. The integration of advanced analytics tools into healthcare systems is facilitating a shift towards more patient-centric care models, thereby driving the adoption of these technologies across the sector.

The regional outlook for the healthcare big data analytics market shows a diverse growth pattern across different geographies. North America currently holds a significant share of the market, driven by the presence of advanced healthcare infrastructure, a high level of digitalization, and a strong focus on research and development. Europe is also witnessing considerable growth, with countries like Germany and the United Kingdom leading the charge in the adoption of analytics solutions. Meanwhile, the Asia Pacific region is poised to experience the fastest growth, fueled by rapid technological advancements, increasing healthcare investments, and the need to address healthcare challenges in densely populated regions. Latin America and the Middle East & Africa are expected to show steady growth, driven by improving healthcare infrastruct

The Outcomes-Based Healthcare market is experiencing significant transformation as healthcare systems increasingly shift focus from volume to value. This innovative approach emphasizes the importance of patient outcomes, holding healthcare providers accountable for their performance and enabling them to deliver high

Abstract The objective of this study is to present the state of the art about hospital care, from the period before the SUS until the formulation of the National Policy of Hospital Attention. This is a national and international systematic review with the adoption of Prism Protocol and survey of the scientific literature indexed in Lilacs, Scielo and Web of Science. The 157 articles included, organized in three periods, showed increase in scientific production of 2003. The findings, among other aspects, point to incipient capacity for systemic management before the creation of SUS. It is worth noting the little investment for the adjustment of the hospital care model between the 1988 Constitution and Hospital Attention Reform Plan 2003. During the period of this governmental plan and the National Policy of Hospital Attention of 2013, a set of problems led to strategies of systemic management and hospital services, such regionalization, instances of governance and adoption of indirect management models. The scientific production analyzed allowed identification of important dimensions of hospital management in SUS, from the perspective of Health Policy, Planning and Management, pointing out gaps and possibilities for the research agenda.

Cybersecurity in Healthcare Statistics - Importance in Healthcare

• Only 36% of healthcare organizations have a comprehensive cybersecurity incident response plan.
• 80% of healthcare organizations plan to increase their cybersecurity budgets in the coming years.

(Source: HIMSS Cybersecurity Survey, Black Book Market Research)

This dataset presents statistics on key health indicators within Qatar's private healthcare sector. It includes the total number and rate per 1,000 population of healthcare professionals such as physicians, dentists, nurses, pharmacists, and allied health workers, as well as hospital beds.The data is structured by profession and indicator type (number and rate), offering insights into the density and availability of private healthcare services. It is useful for health sector analysis, planning, and evaluating the role of the private sector in national health service delivery.

Abstract Objective: To evaluate the satisfaction of octogenarians with Primary Health Care services. Method: a descriptive study, with a quantitative approach, was carried out with 30 older users of the Family Health Strategy, selected by a non-probabilistic sample. Data were collected at home, using the following questionnaires: the mini-mental state exam, a questionnaire on sociodemographic factors, health conditions and access to services, and a questionnaire on satisfaction with Primary Health Care. Data were analyzed using descriptive statistics. Results: The satisfaction analysis showed that the elderly octogenarians are satisfied in terms of care ( X ´ = 6,0 ; ± 1,5) and the interest that community agents demonstrate in them ( X ´ = 5,9 ; ± 1,6) and the availability of nurses for their treatment ( X ´ = 5,9 ; ± 1,1). Aspects related to the waiting time for nurses ( X ´ = 4,6 ; ± 1,6) and doctors ( X ´ = 4,9 ; ± 1,6), facilities for the disabled ( X ´ = 4,6 ; ± 1,4) and the perception that the unit is close to a perfect health unit ( X ´ = 4,6 ; ± 1,8). Conclusion: The services were positively evaluated, reflecting the importance of considering the perspective of octogenarian users in the planning of healthcare actions, since the evaluation of the quality of these services can lead to changes and guide actions in a way that is coherent with the lives of users, increasing their effectiveness, especially regarding actions aimed at the octogenarian population.

Introduction

Healthcare Staffing Statistics: Healthcare staffing is a crucial facet of the healthcare industry. Involves the recruitment, hiring, and management of qualified professionals to meet the ever-changing demands of patients and medical institutions.

This intricate process plays a pivotal role in ensuring high-quality patient care by matching individuals' skills and qualifications to specific roles, considering factors like patient load and location.

Effective healthcare staffing requires anticipating staffing needs, managing schedules, addressing turnover, and adhering to regulatory standards.

Inadequate staffing can jeopardize patient safety and care quality. Effective staffing enhances patient outcomes and experiences, making it a cornerstone of healthcare delivery.

In essence, healthcare staffing is a complex, indispensable process that directly impacts patient well-being and the overall success of healthcare organizations. Demanding meticulous planning and unwavering commitment to excellent patient care.

Check out the PhilaStats Vital Statistics Dashboard for the City of Philadelphia, for interactive maps and charts of vital statistics and trends in natality (births), mortality (deaths), and population for Philadelphia residents. See also the technical notes for the creation and visualization of Philadelphia's Vital Statistics. View metadata for key information about this dataset.Vital statistics are annually published calculations on birth and death records that facilitate the tracking of important health and population trends in Philadelphia over time. Public officials, researchers, and citizens alike may use vital statistics to plan for population shifts and healthcare needs, to perform research, and to stay informed and up-to-date on the natality and mortality trends in our City. The vital statistics dataset consists of natality and mortality data on Philadelphia City residents for each year of finalized data available, back to 2011 for births and 2012 for deaths. Citywide metrics and metrics by Philadelphia Planning District are provided for both natality and mortality metrics. A population estimates table is also provided, which includes the population counts used to calculate some metrics.The Vital Statistics - Social Determinants of Health (SDOH) dataset is also available in this citywide table.For questions about this dataset, contact epi@phila.gov. For technical assistance, email maps@phila.gov.

The purpose of the collection of outpatient health statistics is to monitor, evaluate and plan curative and preventive health care at the primary and secondary level of health care system.

Data on outpatient statistics are an important source of information for population health monitoring indicators
and accessibility of outpatient health care activities in Slovenia. Health care providers collect data for each individual contact of the patients with the health service. It is reported by public and private healthcare providers.

Outpatient health statistics record contacts and services at general practicioners and specialist outpatient activities at the secondary level.

The Healthcare Physician Staffing market plays a pivotal role in ensuring that healthcare facilities can maintain adequate physician coverage to meet patient needs efficiently. With an increasing demand for healthcare services driven by aging populations, rising chronic diseases, and greater patient awareness, healt

Abstract

The Sudan Demographic and Health Survey (SDHS) was conducted in two phases between November 15, 1989 and May 21, 1990 by the Department of Statistics of the Ministry of Economic and National Planning. The survey collected information on fertility levels, marriage patterns, reproductive intentions, knowledge and use of contraception, maternal and child health, maternal mortality, and female circumcision. The survey findings provide the National Population Committee and the Ministry of Health with valuable information for use in evaluating population policy and planning public health programmes.

A total of 5860 ever-married women age 15-49 were interviewed in six regions in northern Sudan; three regions in southern Sudan could not be included in the survey because of civil unrest in that part of the country. The SDHS provides data on fertility and mortality comparable to the 1978-79 Sudan Fertility Survey (SFS) and complements the information collected in the 1983 census.

The primary objective of the SDHS was to provide data on fertility, nuptiality, family planning, fertility preferences, childhood mortality, indicators of maternal health care, and utilization of child health services. Additional information was coUected on educational level, literacy, source of household water, and other housing conditions.

The SDHS is intended to serve as a source of demographic data for comparison with the 1983 census and the Sudan Fertility Survey (SFS) 1978-79, and to provide population and health data for policymakers and researchers. The objectives of the survey are to: - assess the overall demographic situation in Sudan, - assist in the evaluation of population and health programmes, - assist the Department of Statistics in strengthening and improving its technical skills for conducting demographic and health surveys, - enable the National Population Committee (NPC) to develop a population policy for the country, and - measure changes in fertility and contraceptive prevalence, and study the factors which affect these changes, and - examine the basic indicators of maternal and child health in Sudan.

MAIN RESULTS

Fertility levels and trends

Fertility has declined sharply in Sudan, from an average of six children per women in the Sudan Fertility Survey (TFR 6.0) to five children in the Sudan DHS survey flTR 5.0). Women living in urban areas have lower fertility (TFR 4.1) than those in rural areas (5.6), and fertility is lower in the Khartoum and Northern regions than in other regions. The difference in fertility by education is particularly striking; at current rates, women who have attained secondary school education will have an average of 3.3 children compared with 5.9 children for women with no education, a difference of almost three children.

Although fertility in Sudan is low compared with most sub-Saharan countries, the desire for children is strong. One in three currently married women wants to have another child within two years and the same proportion want another child in two or more years; only one in four married women wants to stop childbearing. The proportion of women who want no more children increases with family size and age. The average ideal family size, 5.9 children, exceeds the total fertility rate (5.0) by approximately one child. Older women are more likely to want large families than younger women, and women just beginning their families say they want to have about five children.

Marriage

Almost all Sudanese women marry during their lifetime. At the time of the survey, 55 percent of women 15-49 were currently married and 5 percent were widowed or divorced. Nearly one in five currently married women lives in a polygynous union (i.e., is married to a man who has more than one wife). The prevalence of polygyny is about the same in the SDHS as it was in the Sudan Fertility Survey.

Marriage occurs at a fairly young age, although there is a trend toward later marriage among younger women (especially those with junior secondary or higher level of schooling). The proportion of women 15-49 who have never married is 12 percentage points higher in the SDHS than in the Sudan Fertiliy Survey.

There has been a substantial increase in the average age at first marriage in Sudan. Among SDHS. Since age at first marriage is closely associated with fertility, it is likely that fertility will decrease in the future. With marriages occurring later, women am having their first birth at a later age. While one in three women age 45-49 had her first birth before age 18, only one in six women age 20-24 began childbearing prior to age 18. The women most likely to postpone marriage and childbearing are those who live in urban areas ur in the Khartoum and Northern regions, and women with pest-primary education.

Breastfeeding and postpartum abstinence

Breastfeeding and postpartum abstinence provide substantial protection from pregnancy after the birth uf a child. In addition to the health benefits to the child, breastfeeding prolongs the length of postpartum amenorrhea. In Sudan, almost all women breastfeed their children; 93 percent of children are still being breastfed 10-11 months after birth, and 41 percent continue breastfeeding for 20-21 months. Postpartum abstinence is traditional in Sudan and in the first two months following the birth of a child 90 percent of women were abstaining; this decreases to 32 percent after two months, and to 5 percent at~er one year. The survey results indicate that the combined effects of breastfeeding and postpartum abstinence protect women from pregnancy for an average of 15 months after the birth of a child.

Knowledge and use of contraception

Most currently married women (71 percent) know at least one method of family planning, and 59 percent know a source for a method. The pill (70 percent) is the most widely known method, followed by injection, female sterilisation, and the IUD. Only 39 percent of women knew a traditional method of family planning.

Despite widespread knowledge of family planning, only about one-fourth of ever-married women have ever used a contraceptive method, and among currently married women, only 9 percent were using a method at the time of the survey (6 percent modem methods and 3 percent traditional methods). The level of contraceptive use while still low, has increased from less than 5 percent reported in the Sudan Fertility Survey.

Use of family planning varies by age, residence, and level of education. Current use is less than 4 percent among women 15-19, increases to 10 percent for women 30-44, then decreases to 6 percent for women 45-49. Seventeen percent of urban women practice family planning compared with only 4 percent of rural women; and women with senior secondary education are more likely to practice family planning (26 percent) than women with no education (3 percent).

There is widespread approval of family planning in Sudan. Almost two-thirds of currently married women who know a family planning method approve of the use of contraception. Husbands generally share their wives's views on family planning. Three-fourths of married women who were not using a contraceptive method at the time of the survey said they did not intend to use a method in the future.

Communication between husbands and wives is important for successful family planning. Less than half of currently married women who know a contraceptive method said they had talked about family planning with their husbands in the year before the survey; one in four women discussed it once or twice; and one in five discussed it more than twice. Younger women and older women were less likely to discuss family planning than those age 20 to 39.

Mortality among children

The neonatal mortality rate in Sudan remained virtually unchanged in the decade between the SDHS and the SFS (44 deaths per 1000 births), but under-five mortality decreased by 14 percent (from 143 deaths per 1000 births to 123 per thousand). Under-five mortality is 19 percent lower in urban areas (117 per 1000 births) than in rural areas (144 per 10(30 births).

The level of mother's education and the length of the preceding birth interval play important roles in child survival. Children of mothers with no education experience nearly twice the level of under-five mortality as children whose mother had attained senior secondary or nigher education. Mortality among children under five is 2.7 times higher among children born after an interval of less than 24 months than among children born after interval of 48 months or more.

Maternal mortality

The maternal mortality rate (maternal deaths per 1000 women years of exposure) has remained nearly constant over the twenty years preceding the survey, while the maternal mortality ratio (number of maternal deaths per 100,000 births), has increased (despite declining fertility). Using the direct method of estimation, the maternal mortality ratio is 352 maternal deaths per 100,000 births for the period 1976-82, and 552 per 100,000 births for the period 1983-89. The indirect estimate for the maternal mortality ratio is 537. The latter estimate is an average of women's experience over an extended period before the survey centred on 1977.

Maternal health care

The health care mothers receive during pregnancy and delivery is important to the survival and well-being of both children and mothers. The SDHS results indicate that most women in Sudan made at least one antenatal visit to a doctor or trained health worker/midwife. Eighty-seven percent of births benefitted from professional antenatal care in urban areas compared with 62 percent in rural areas. Although the proportion of pregnant mothers seen by trained health workers/midwives are similar in urban and rural areas, doctors provided antenatal care for 42 percent and 19 percent of births in urban and rural areas, respectively.

Neonatal tetanus, a major

ABSTRACT The purpose of this article is to analyze how the development of the Continuing Education actions takes place based on the planning and evaluation documents of the actions of the National Program for Improvement for Access and Quality Improvement of Primary Care (PMAQ-AB). As a methodology, a documentary analysis of the Self-Assessment for Improving Access and Quality of Primary Care (AMAQ-AB) was carried out between November 2017 and March 2018, completed by the management team and the teams of six Family Health Units of the Urban Zone, regarding the third cycle of the PMAQ-AB. In addition to the attendance sheet and/or minutes with Continuing Education actions, Continuing Education Plan carried out by the management in 2017 and Municipal Health Plan 2014-2017. The results showed that Continuing Education is positively self-assessed by both. In relation to the other documents, there were weaknesses in the planning and performance of these actions. It is concluded that AMAQ-AB is a powerful new device for the analysis of Continuing Education in primary care, and it is necessary to increase its importance in the qualification of Primary Health Care.

In a historical and developmental sense, the former one-year reporting on employees employed in healthcare grew during 1990/91. in the continuous collection and monitoring of data through the state Register of Health Professionals. The department maintains data on all healthcare workers and healthcare associates, and on administrative and technical staff for now only numerically, according to the number of permanent employees at the end of the year. In the future, it is intended to register employees who are not health-oriented and work in healthcare, and healthcare professionals who work outside the healthcare system can also be registered.

Data on health workers and health care associates are required to be submitted not only by state and county-owned health institutions, but also by all private institutions, health workers who independently perform private practice, as well as trading companies for the performance of health activities, regardless of whether they have a contract with the Croatian Institute for health insurance.

All employees are assigned a registration number (code) upon entry into the Registry's database on the day of employment. The connection with the Croatian Health Insurance Institute exists through the use of the registration number when registering, recognizing within the CEZIH system, as well as when registering prescriptions, referrals and other documents of the HZZO. that is, in monitoring and building the health information system.

As an integral part of the same, relational databases also include data on health organizational units, representing the Register of Health Institutions. Namely, in addition to data on employees, the Registry, based on the decision of the Ministry of Health on work authorization, also records basic data on health institutions, surgeries and all other types of independent health units, regardless of the contract with the Croatian Health Insurance Institute or the type of ownership. As for employees, received data on the opening, closing, change of name, address, type and activity of the health organizational unit is also updated daily.

Thus, the organizational structure of healthcare is monitored through the database, according to levels of healthcare, types of healthcare institutions, healthcare activities performed by institutions, divisions with regard to the type of ownership as well as territorial distribution.

In addition to the importance of data on human potential and space, that is, the units where health care is provided, medical equipment is also an important factor in management and planning. One part of the department's work is related to the collection of data on this material resource. In the near future, it is planned to form a Register of Medically Expensive Equipment, which would be technologically and functionally connected with the existing two registers into a whole register of resources in healthcare.

Also, the statistical research aims to include those entities that are not part of the health system, and in which health workers work, i.e. health activities are performed, such as long-term care homes, which means expanding the existing data of the Register of Health Institutions.

In the last decade, a new IT application of the Registry of Health Care Professionals was created and an even better connection with the Croatian Institute for Health Insurance, for example through the use of the so-called population register or the register of insured persons. The register continues to be the source of data and the authorized institution for the delivery of data to international bodies such as the WHO and the joint WHO/Eurostat/OECD database. Within the scope of the Department's activities are also activities in international initiatives and programs, and with regard to the problems of statistical monitoring, shortages and planning of health workers. Since 2012, we have been involved in the implementation of the "Global Code of Practice on International Recruitment of Health Personnel", a recommendation that is also an instrument in the regulation, improvement and establishment of standards in the migration process.

In the same year, the Department was involved in the work in the part of the program platform on the topic of Joint Action on European Health Workforce Planning and Forecasting.

Also, during the past years, there has been cooperation on the topic of health workers within the framework of the South-eastern Europe Health Network (SEEHN).

IntroductionThe use of health research evidence is essential for informed decision-making and effective health planning. Despite its importance, there is limited understanding of the determinants for the use of such evidence in planning processes, particularly in lower-middle-income countries (LMICs) like Tanzania. This study aims to investigate the proportion and determinants that affect the use of health research evidence in health planning in Tanzania.Materials and methodsThis quantitative study employed a cross-sectional design. Data on health research evidence and the factors influencing its use were collected using a structured questionnaire from 422 healthcare workers involved in planning within 9 regions of Tanzania from October to December 2023. The association between categorical variables was assessed using a chi-square test, while regression analysis was conducted to identify determinants, both at a 95% confidence level,ResultsThe study revealed that 270 (66.2%) of health planning team members strongly agreed that they use health research evidence during planning. Several key determinants were significantly associated with the level of research evidence utilization. These included limited dissemination of research findings (74.5%), inadequate human and non-human resources (70.0%), and insufficient knowledge and training in research (63.7%). A multivariate regression analysis confirmed significant associations between the determinants and the use of research evidence (p

The Healthcare Data Annotation Tools market is experiencing significant growth as the demand for precise and reliable data labeling continues to rise, driven largely by advancements in artificial intelligence and machine learning within the healthcare sector. These specialized tools play a critical role in annotatin

The Healthcare Supply Chain Software market plays a pivotal role in modernizing the healthcare sector, streamlining operations, and ensuring the efficient distribution of medical supplies and services. This software is designed to optimize the procurement, inventory management, order processing, and logistics of hea

The Advance Directives Software market is experiencing robust growth, driven by increasing demand for efficient and accessible end-of-life care planning. The aging global population and rising awareness of the importance of advance care planning are key factors fueling market expansion. Technological advancements, such as cloud-based solutions and improved user interfaces, are simplifying the process of creating and managing advance directives, making the software more user-friendly for both patients and healthcare providers. Furthermore, the integration of these systems with Electronic Health Records (EHRs) is streamlining data exchange and improving overall care coordination. We estimate the market size to be around $500 million in 2025, with a Compound Annual Growth Rate (CAGR) of approximately 15% over the forecast period (2025-2033). This growth is anticipated to be driven by the expansion of telehealth services and increasing government initiatives promoting proactive healthcare planning. However, market growth faces certain restraints. Data privacy concerns and regulatory complexities surrounding sensitive patient information represent significant challenges. Ensuring the security and compliance of these software solutions is crucial for widespread adoption. The integration of advance directives software with existing healthcare systems can also be complex and costly, potentially hindering market penetration in certain regions. Despite these challenges, the long-term outlook for the Advance Directives Software market remains positive, with continued technological innovation and growing demand expected to drive significant growth in the coming years. The competitive landscape is marked by a mix of established healthcare IT companies and specialized startups, each vying for market share through innovative solutions and strategic partnerships.

Abstract

Environmental statistics in the health care centers is very interested and this statistics is an important instrument to make decisions, planning, and draw the outlines for environment. And relating to infrequency of data about this subject in the Palestinian Territory, the Palestinian Central Bureau of Statistics (PCBS) building up and develop a database about environmental in the health care centers.

Geographic coverage

Palestinian Territory

Analysis unit

Health care centers

Universe

The target population of this survey is all health care centers in the Palestinian Territory, and they divide to: 1. Governmental health care centers (Ministry of Health, Health Care Military Service, Lijan Azakah). 2. Non-governmental health care centers (Health Union Committees, Union of Palestine Health Care Relief Committees, Refits Friends Benevolent Society, UNRWA, Red Crescent Society, and Red Cross) in the Palestinian Territory.

Kind of data

Complete enumeration [enu]

Sampling procedure

Governmental and Non-governmental Health care centers: The frame of the all centers which work in sector of health care which owned by Governmental and Non-governmental health care centers updated annually by thru the administration records in the PCBS.

Sampling deviation

Non applicable

Mode of data collection

Self Assessment Directed Questionnaire [SAQ]

Research instrument

The environmental questionnaire was designed in accordance with the similar country experiments and according to international standards and recommendations for the most important indicators, taking into account the special situation of Palestinian Territory.

To test the questionnaire we take the results of the last surveys that implemented by the PCBS in 2001, 2003 as a pretest; consequently some modifications were made on the questionnaire and on the instructions.

Cleaning operations

Data Processing The data processing stage consisted of the following operations:

Editing before data entry: All questionnaires were edited again in the office using the same instructions adopted for editing in the fields.

Data entry: In this stage data were entered into the computer, using Microsoft Access. The data entry program was prepared to satisfy a number of requirements such as: Duplication of the questionnaire on the computer screen. Logical and consistency check of data entered. Possibility for internal editing of questions answers. Maintaining a minimum of digital data entry and fieldwork errors. User-Friendly handling. Possibility of transferring data into another format to be used and analyzed using other statistical analytical systems such as SAS and SPSS.

Sampling error estimates

1. Statistical Errors This type of errors could be determined easily, and it is result from sampling errors, and this type of errors concern the data of private health care centers. And to reduce this errors the data mast pass tow stage:

2. Non-Statistical Errors This type of errors result from non-sampling errors, and could not be determined easily due to the diversity of sources (e.g. the interviewers, respondent, editor, data entry operator... etc).