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Healthcare Fraud Detection Market Size 2025-2029

The healthcare fraud detection market size is forecast to increase by USD 1.09 billion at a CAGR of 11.8% between 2024 and 2029.

The market is experiencing significant growth due to the increasing number of patients seeking health insurance and the emergence of social media's influence on the healthcare industry. The rise in healthcare fraud cases, driven by the influx of insurance claims, necessitates robust fraud detection solutions. Social media's impact on healthcare extends to fraudulent activities, with fake claims and identity theft posing challenges. However, the deployment of healthcare fraud detection systems remains a time-consuming process, and the need for frequent upgrades to keep up with evolving fraud schemes adds complexity.
Additionally, collaborating with regulatory bodies and industry associations can help stay informed of the latest fraud trends and best practices. Overall, the market presents opportunities for innovation and growth, as the demand for effective solutions to combat fraudulent activities continues to rise. Companies must navigate these challenges by investing in advanced technologies, such as machine learning and artificial intelligence, to streamline deployment and enhance fraud detection capabilities.

What will be the Size of the Healthcare Fraud Detection 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 market encompasses various solutions and services designed to mitigate fraudulent activities in Medicaid services and health insurance. Data analytics plays a pivotal role in this domain, with statistical methods and data science techniques used to identify fraudulent healthcare activities. Prescriptive analytics and machine learning algorithms enable the prediction of potential fraudulent claims and billing schemes. Medical services, including pharmacy billing fraud and prescription fraud, are prime targets for offenders. Identity theft and social media are also significant contributors to healthcare fraud costs. Payment integrity is crucial for insurers to minimize financial losses, making fraud detection a priority.

On-premise and cloud-based solutions offer analytics capabilities to combat fraud. Descriptive analytics provides insights into historical data, while predictive analytics and prescriptive analytics offer proactive fraud detection. Despite the advancements in fraud detection, data limitations pose challenges. The use of artificial intelligence and machine learning in fraud detection is increasing, providing more accurate and efficient solutions. Insurance claims review is a critical component of fraud detection, with fraudulent claims costing billions annually. Fraudsters continue to evolve their tactics, necessitating the need for advanced fraud detection solutions.

How is this Healthcare Fraud Detection Industry segmented?

The healthcare fraud detection 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.

Type

  Descriptive analytics
  Predictive analytics
  Prescriptive analytics


End-user

  Private insurance payers
  Third-party administrators (TPAs)
  Government agencies
  Hospitals and healthcare providers


Delivery Mode

  Cloud-based
  On-premises


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The Descriptive analytics segment is estimated to witness significant growth during the forecast period. In the dynamic landscape of healthcare, Anomalies Detection and Healthcare Fraud Analytics play a pivotal role in safeguarding Financial Resources from Fraudulent Healthcare Activities. Descriptive analytics, a foundational type of analytics, forms the backbone of this industry. With its ability to aggregate and examine vast healthcare data, descriptive analytics identifies trends and operational performance insights. It is widely used in various departments, from Healthcare IT adoption to Urgent care, and supports Insurance Claims Review processes. Cloud-Based Solutions and On-Premises Solutions are two delivery models that cater to diverse organizational needs. Machine Learning and Statistical Methods are integral to advanced analytics, including Prescriptive analytics and Predictive analytics, which uncover intricate patterns and prevent Fraudulent Claims.

Social Media and Data Analytics offer valuable insights into potential Fraudulent Activities, while Real-Time Analytics ensure Payment Integrity in Healthca

BackgroundThe 5-year survival rate of cancer patients is the most commonly used statistic to reflect improvements in the war against cancer. This idea, however, was refuted based on an analysis showing that changes in 5-year survival over time bear no relationship with changes in cancer mortality.MethodsHere we show that progress in the fight against cancer can be evaluated by analyzing the association between 5-year survival rates and mortality rates normalized by the incidence (mortality over incidence, MOI). Changes in mortality rates are caused by improved clinical management as well as changing incidence rates, and since the latter can mask the effects of the former, it can also mask the correlation between survival and mortality rates. However, MOI is a more robust quantity and reflects improvements in cancer outcomes by overcoming the masking effect of changing incidence rates. Using population-based statistics for the US and the European Nordic countries, we determined the association of changes in 5-year survival rates and MOI.ResultsWe observed a strong correlation between changes in 5-year survival rates of cancer patients and changes in the MOI for all the countries tested. This finding demonstrates that there is no reason to assume that the improvements in 5-year survival rates are artificial. We obtained consistent results when examining the subset of cancer types whose incidence did not increase, suggesting that over-diagnosis does not obscure the results.ConclusionsWe have demonstrated, via the negative correlation between changes in 5-year survival rates and changes in MOI, that increases in 5-year survival rates reflect real improvements over time made in the clinical management of cancer. Furthermore, we found that increases in 5-year survival rates are not predominantly artificial byproducts of lead-time bias, as implied in the literature. The survival measure alone can therefore be used for a rough approximation of the amount of progress in the clinical management of cancer, but should ideally be used with other measures.

Medical Coding Market size was valued at USD 31,170.85 Million in 2023 and is projected to reach USD 53,654.53 Million by 2031, at a CAGR of 8.07% from 2024 to 2031.

Global Medical Coding Market Overview

Global healthcare expenditure has been on a steady rise in recent years, driven by factors such as an aging population, the prevalence of chronic diseases, and the adoption of advanced medical technologies. The global expansion of healthcare services, including hospitals, clinics, and specialized medical facilities, increases the demand for accurate medical coding to manage billing, patient records, and healthcare analytics efficiently. According to American Hospital Association, there were around 33.67 million patient’s admissions in the 6120 hospitals in the United States. According to the OECD Health Statistics 2023, the USA leads with a health expenditure to GDP ratio of 16.6% in 2022, followed by Germany at 12.7% and France at 12.1%. In the USA, healthcare spending surged to USD 4.5 trillion in 2022, reflecting a 4.1% growth, outpacing the 3.2% increase in 2021, as reported by the U.S. Centers for Medicare & Medicaid Services. The rise in the number of insured individuals means more people are accessing healthcare services. As healthcare utilization increases, the demand for accurate medical coding to process insurance claims also grows. Hospitals and other healthcare providers are constantly seeking ways to improve their billing efficiency and reduce administrative costs.

Medical coding plays a vital role in this process by ensuring that claims are submitted accurately and reimbursed promptly. Efficient coding systems can help healthcare providers to reduce claim denials and delays in payments. The lack of skilled professionals is a significant restraint on the growth of the Global Medical Coding Market. The medical coding industry requires specialized knowledge and expertise to navigate the complex systems and continuously evolving coding guidelines. Healthcare organizations, which are the primary end-users of medical coding solutions, often struggle to maintain a sufficient pool of skilled medical coding professionals within their internal workforce. The adoption of advanced technologies such as artificial intelligence (AI), machine learning, and natural language processing (NLP) is revolutionizing the global Medical Coding Market, creating significant opportunities for growth and efficiency. As healthcare organizations continue to grapple with the challenges posed by the shortage of skilled medical coding professionals, the integration of innovative technological solutions has emerged as a promising avenue to enhance the efficiency and accuracy of the coding process.

*Predictors were identified using center-specific stepwise Cox regression in the derivation sample. Those factors being significantly (two-sided P-value

Overview

The Associated Press is sharing data from the COVID Impact Survey, which provides statistics about physical health, mental health, economic security and social dynamics related to the coronavirus pandemic in the United States.

Conducted by NORC at the University of Chicago for the Data Foundation, the probability-based survey provides estimates for the United States as a whole, as well as in 10 states (California, Colorado, Florida, Louisiana, Minnesota, Missouri, Montana, New York, Oregon and Texas) and eight metropolitan areas (Atlanta, Baltimore, Birmingham, Chicago, Cleveland, Columbus, Phoenix and Pittsburgh).

The survey is designed to allow for an ongoing gauge of public perception, health and economic status to see what is shifting during the pandemic. When multiple sets of data are available, it will allow for the tracking of how issues ranging from COVID-19 symptoms to economic status change over time.

The survey is focused on three core areas of research:

• Physical Health: Symptoms related to COVID-19, relevant existing conditions and health insurance coverage.
• Economic and Financial Health: Employment, food security, and government cash assistance.
• Social and Mental Health: Communication with friends and family, anxiety and volunteerism. (Questions based on those used on the U.S. Census Bureau’s Current Population Survey.) ## Using this Data - IMPORTANT This is survey data and must be properly weighted during analysis: DO NOT REPORT THIS DATA AS RAW OR AGGREGATE NUMBERS!!

Instead, use our queries linked below or statistical software such as R or SPSS to weight the data.

Queries

If you'd like to create a table to see how people nationally or in your state or city feel about a topic in the survey, use the survey questionnaire and codebook to match a question (the variable label) to a variable name. For instance, "How often have you felt lonely in the past 7 days?" is variable "soc5c".

Nationally: Go to this query and enter soc5c as the variable. Hit the blue Run Query button in the upper right hand corner.

Local or State: To find figures for that response in a specific state, go to this query and type in a state name and soc5c as the variable, and then hit the blue Run Query button in the upper right hand corner.

The resulting sentence you could write out of these queries is: "People in some states are less likely to report loneliness than others. For example, 66% of Louisianans report feeling lonely on none of the last seven days, compared with 52% of Californians. Nationally, 60% of people said they hadn't felt lonely."

Margin of Error

The margin of error for the national and regional surveys is found in the attached methods statement. You will need the margin of error to determine if the comparisons are statistically significant. If the difference is:

• At least twice the margin of error, you can report there is a clear difference.
• At least as large as the margin of error, you can report there is a slight or apparent difference.
• Less than or equal to the margin of error, you can report that the respondents are divided or there is no difference. ## A Note on Timing Survey results will generally be posted under embargo on Tuesday evenings. The data is available for release at 1 p.m. ET Thursdays.

About the Data

The survey data will be provided under embargo in both comma-delimited and statistical formats.

Each set of survey data will be numbered and have the date the embargo lifts in front of it in the format of: 01_April_30_covid_impact_survey. The survey has been organized by the Data Foundation, a non-profit non-partisan think tank, and is sponsored by the Federal Reserve Bank of Minneapolis and the Packard Foundation. It is conducted by NORC at the University of Chicago, a non-partisan research organization. (NORC is not an abbreviation, it part of the organization's formal name.)

Data for the national estimates are collected using the AmeriSpeak Panel, NORC’s probability-based panel designed to be representative of the U.S. household population. Interviews are conducted with adults age 18 and over representing the 50 states and the District of Columbia. Panel members are randomly drawn from AmeriSpeak with a target of achieving 2,000 interviews in each survey. Invited panel members may complete the survey online or by telephone with an NORC telephone interviewer.

Once all the study data have been made final, an iterative raking process is used to adjust for any survey nonresponse as well as any noncoverage or under and oversampling resulting from the study specific sample design. Raking variables include age, gender, census division, race/ethnicity, education, and county groupings based on county level counts of the number of COVID-19 deaths. Demographic weighting variables were obtained from the 2020 Current Population Survey. The count of COVID-19 deaths by county was obtained from USA Facts. The weighted data reflect the U.S. population of adults age 18 and over.

Data for the regional estimates are collected using a multi-mode address-based (ABS) approach that allows residents of each area to complete the interview via web or with an NORC telephone interviewer. All sampled households are mailed a postcard inviting them to complete the survey either online using a unique PIN or via telephone by calling a toll-free number. Interviews are conducted with adults age 18 and over with a target of achieving 400 interviews in each region in each survey.Additional details on the survey methodology and the survey questionnaire are attached below or can be found at https://www.covid-impact.org.

Attribution

Results should be credited to the COVID Impact Survey, conducted by NORC at the University of Chicago for the Data Foundation.

AP Data Distributions

​To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

Introduction

Electronic Health Records Statistics: In today's fast-paced and data-driven healthcare landscape, Electronic Health Records (EHRs) play a pivotal role in transforming how medical information is stored, accessed, and shared.

EHRs have revolutionized the way healthcare providers deliver patient care by replacing traditional paper-based systems with digital records.

These digital systems enable healthcare professionals to access patient data securely, make informed decisions, and collaborate effectively across the care continuum.

The adoption and utilization of EHR systems have seen significant growth in recent years due to various factors such as government initiatives, advancements in technology, and the increasing need for streamlined healthcare processes.

As EHRs become more prevalent, they offer immense benefits in terms of improved patient outcomes, increased efficiency, and enhanced research opportunities.

Abstract

Objectives: To obtain reliable, valid and comparable health, health-related and well-being data over a range of key domains for adult and older adult populations in nationally representative samples To examine patterns and dynamics of age-related changes in health and well-being using longitudinal follow-up of a cohort as they age, and to investigate socio-economic consequences of these health changes To supplement and cross-validate self-reported measures of health and the anchoring vignette approach to improving comparability of self-reported measures, through measured performance tests for selected health domains To collect health examination and biomarker data that improves reliability of morbidity and risk factor data and to objectively monitor the effect of interventions

Additional Objectives: To generate large cohorts of older adult populations and comparison cohorts of younger populations for following-up intermediate outcomes, monitoring trends, examining transitions and life events, and addressing relationships between determinants and health, well-being and health-related outcomes To develop a mechanism to link survey data to demographic surveillance site data To build linkages with other national and multi-country ageing studies To improve the methodologies to enhance the reliability and validity of health outcomes and determinants data To provide a public-access information base to engage all stakeholders, including national policy makers and health systems planners, in planning and decision-making processes about the health and well-being of older adults

Methods: SAGE's first full round of data collection included both follow-up and new respondents in most participating countries. The goal of the sampling design was to obtain a nationally representative cohort of persons aged 50 years and older, with a smaller cohort of persons aged 18 to 49 for comparison purposes. In the older households, all persons aged 50+ years (for example, spouses and siblings) were invited to participate. Proxy respondents were identified for respondents who were unable to respond for themselves. Standardized SAGE survey instruments were used in all countries consisting of five main parts: 1) household questionnaire; 2) individual questionnaire; 3) proxy questionnaire; 4) verbal autopsy questionnaire; and, 5) appendices including showcards. A VAQ was completed for deaths in the household over the last 24 months. The procedures for including country-specific adaptations to the standardized questionnaire and translations into local languages from English follow those developed by and used for the World Health Survey.

Content Household questionnaire 0000 Coversheet 0100 Sampling Information 0200 Geocoding and GPS Information 0300 Recontact Information 0350 Contact Record 0400 Household Roster 0450 Kish Tables and Household Consent 0500 Housing 0600 Household and Family Support Networks and Transfers 0700 Assets and Household Income 0800 Household Expenditures 0900 Interviewer Observations

Individual questionnaire 1000 Socio-Demographic Characteristics 1500 Work History and Benefits 2000 Health State Descriptions and Vignettes 2500 Anthropometrics, Performance Tests and Biomarkers 3000 Risk Factors and Preventive Health Behaviours 4000 Chronic Conditions and Health Services Coverage 5000 Health Care Utilization 6000 Social Cohesion 7000 Subjective Well-Being and Quality of Life (WHOQoL-8 and Day Reconstruction Method) 9000 Interviewer Assessment

Geographic coverage

National coverage

Analysis unit

households and individuals

Universe

The household section of the survey covered all households in the People's Republic of China. Two special administrative regions Hong Kong and Macau are excluded. Institutionalised populations are also excluded. The individual section covered all persons aged 18 years and older residing within individual households. As the focus of SAGE is older adults, a much larger sample of respondents aged 50 years and older were selected with a smaller comparative sample of respondents aged 18-49 years

Kind of data

Sample survey data [ssd]

Sampling procedure

The People's Republic of China(PRC) administers 22 provinces. These were grouped into Eastern, Central and Western provinces based on geographical location and economic status.PRC used a stratified multistage cluster sample design. Eight provinces were sampled. Strata were defined by the eight province(Guangdong,Hubei,Jilin,Shaanxi,Shandong,Shanghai,Yunnan,Zhejiang) and locality (urban or rural), there were 16 strata in total. One district(urban) and one county(rural) was randomly selected from each province. From each district/county 4 communities/townships were selected probability proportional to size; the measure of size being the number of households in the community/township. From each community/township 2 residential blocks/villages were selected probability proportional to size; the measure of size being the number of households in the residential blocks/villages. In each selected residential block/village 84 households were randomly selected:70 50 plus households and 14 18-49 households. All 50 plus members of the 50 plus households were eligible for the individual interview. One person aged 18-49 was eligible for the individual interview, and the individual to be included was selected using a Kish Grid.

Stages of selection Strata: Province, Locality=16 PSU: Township/Community=64 surveyed SSU: Village/Neighbourhood Community=127 surveyed TSU: Households=10278 surveyed QSU: Individuals=15050 surveyed

Mode of data collection

Face-to-face [f2f] PAPI and CAPI

Research instrument

The questionnaires were based on the WHS Model Questionnaire with some modification and many new additions. A household questionnaire was administered to all households eligible for the study. An Individual questionniare was administered to eligible respondents identified from the household roster. A Proxy questionnaire was administered to individual respondents who had cognitive limitations. The questionnaires were developed in English and were piloted as part of the SAGE pretest in 2005. All documents were translated into Chinese. All SAGE generic questionnaires are available as external resources.

Cleaning operations

Data editing took place at a number of stages including: (1) office editing and coding (2) during data entry (3) structural checking of the CSPro files (4) range and consistency secondary edits in Stata

Response rate

Household Response rate=95% Cooperation rate=99%

Individual: Response rate=93% Cooperation rate=98%

Statistical Analysis Software Market size was valued at USD 7,963.44 Million in 2023 and is projected to reach USD 13,023.63 Million by 2030, growing at a CAGR of 7.28% during the forecast period 2024-2030.

Global Statistical Analysis Software Market Drivers

The market drivers for the Statistical Analysis Software Market can be influenced by various factors. These may include:

Growing Data Complexity and Volume: The demand for sophisticated statistical analysis tools has been fueled by the exponential rise in data volume and complexity across a range of industries. Robust software solutions are necessary for organizations to evaluate and extract significant insights from huge datasets. Growing Adoption of Data-Driven Decision-Making: Businesses are adopting a data-driven approach to decision-making at a faster rate. Utilizing statistical analysis tools, companies can extract meaningful insights from data to improve operational effectiveness and strategic planning. Developments in Analytics and Machine Learning: As these fields continue to progress, statistical analysis software is now capable of more. These tools' increasing popularity can be attributed to features like sophisticated modeling and predictive analytics. A greater emphasis is being placed on business intelligence: Analytics and business intelligence are now essential components of corporate strategy. In order to provide business intelligence tools for studying trends, patterns, and performance measures, statistical analysis software is essential. Increasing Need in Life Sciences and Healthcare: Large volumes of data are produced by the life sciences and healthcare sectors, necessitating complex statistical analysis. The need for data-driven insights in clinical trials, medical research, and healthcare administration is driving the market for statistical analysis software. Growth of Retail and E-Commerce: The retail and e-commerce industries use statistical analytic tools for inventory optimization, demand forecasting, and customer behavior analysis. The need for analytics tools is fueled in part by the expansion of online retail and data-driven marketing techniques. Government Regulations and Initiatives: Statistical analysis is frequently required for regulatory reporting and compliance with government initiatives, particularly in the healthcare and finance sectors. In these regulated industries, statistical analysis software uptake is driven by this. Big Data Analytics's Emergence: As big data analytics has grown in popularity, there has been a demand for advanced tools that can handle and analyze enormous datasets effectively. Software for statistical analysis is essential for deriving valuable conclusions from large amounts of data. Demand for Real-Time Analytics: In order to make deft judgments fast, there is a growing need for real-time analytics. Many different businesses have a significant demand for statistical analysis software that provides real-time data processing and analysis capabilities. Growing Awareness and Education: As more people become aware of the advantages of using statistical analysis in decision-making, its use has expanded across a range of academic and research institutions. The market for statistical analysis software is influenced by the academic sector. Trends in Remote Work: As more people around the world work from home, they are depending more on digital tools and analytics to collaborate and make decisions. Software for statistical analysis makes it possible for distant teams to efficiently examine data and exchange findings.

Objectives Value-based Health Care (VBHC) is a health system reform gradually being implemented in health systems worldwide. A previous national-level survey has shown that Latin American countries were in the early stages of alignment with VBHC. Data at the healthcare providers level are lacking. This study aim was to investigate how healthcare providers in five Latin American countries are implementing the Value Agenda. Design Mixed-methods research was conducted using online questionnaire, semi-structured interviews (from December of 2018 to June of 2020), and analyses of aggregated data and documents. Statistical analysis was performed using Fisher's exact test. Univariate analysis was used to compare organizations in relation to the implementation of VBHC initiatives. P value ≤0.05 was considered significant. Participants Top and middle-level executives from 70 healthcare provider organizations from Argentina, Brazil, Chile, Colombia and Mexico. Results From a total of 172 initiatives referred by 55 participants, 58 referred by 33 participants were aligned with the value agenda and focused on care delivery organization (56.9%), outcomes measurement (22.4%), cost measurement (10.3%) and bundled payments (10.3%). Although fee-for-service predominated, one third of providers were experimenting with alternative payment models. Univariate analysis showed that specialty hospitals (p=0.05), a high level of alignment with care delivery organization (p<0,01) and outcomes measurement (p=0.01), implementation of ICHOM standard sets (p<0.01), and participation in alternative payment models were associated with VBHC implementation (p=0.01). Conclusions A wide variation in the level of implementation of the value agenda existed across participating providers. A list of initiatives was produced that may provide insights for different stakeholders. Scalability of such initiatives will demand investments on education of stakeholders and on systematic measurement and use of outcomes and cost data. Further research is needed to identify successful implementation cases that may serve as regional benchmark for other Latin American providers advancing with VBHC. Mixed-methods research combining both qualitative and quantitative techniques were used. Quantitative methods included an online questionnaire to assess the level of implementation of the value agenda components and to map VBHC initiatives, and analyses of aggregated data on the initiatives referred in the interview. Qualitative methods included semi-structured interviews and analysis of relevant documents, including meeting notes and published documents. Online surveys and interviews were applied between December of 2018 and June of 2020. From a total of 182 organizations considered to participate in the study, 71 signed the written consent. Two organizations requested to participate as a single organization, as they work as a single management and care provider, which resulted in a final sample of 70 participants. Quantitative and qualitative data were analyzed using descriptive statistics. Fisher's exact test was performed to compare organizations that had implemented VBHC initiatives with those that had not implemented. Univariate analysis was used to identify differences between the two groups in relation to VBHC implementation. To compare organizations regarding their level of alignment with the value agenda, answers to the online survey were transformed into binary variables, where ‘yes’ (high level of alignment) was considered if options ‘a or b’ had been selected, and ‘no’ (low level of alignment) for all other options. To keep data anonymized all information regarding country, size, and organization profiles were also turned into binary variables. A dictionary of terms to describe variables is available as part of the spreadsheet.

Abstract

Purpose: The multi-country Study on Global Ageing and Adult Health (SAGE) is run by the World Health Organization's Multi-Country Studies unit in the Innovation, Information, Evidence and Research Cluster. SAGE is part of the unit's Longitudinal Study Programme which is compiling longitudinal data on the health and well-being of adult populations, and the ageing process, through primary data collection and secondary data analysis. INDEPTH SAGE Wave 1 (2006/7) provides data on the health and well-being of adults in: Ghana, India and South Africa.

Objectives: To obtain reliable, valid and comparable health, health-related and well-being data over a range of key domains for adult and older adult populations in nationally representative samples To examine patterns and dynamics of age-related changes in health and well-being using longitudinal follow-up of a cohort as they age, and to investigate socio-economic consequences of these health changes To supplement and cross-validate self-reported measures of health and the anchoring vignette approach to improving comparability of self-reported measures, through measured performance tests for selected health domains To collect health examination and biomarker data that improves reliability of morbidity and risk factor data and to objectively monitor the effect of interventions

Additional Objectives: To generate large cohorts of older adult populations and comparison cohorts of younger populations for following-up intermediate outcomes, monitoring trends, examining transitions and life events, and addressing relationships between determinants and health, well-being and health-related outcomes To develop a mechanism to link survey data to demographic surveillance site data To build linkages with other national and multi-country ageing studies To improve the methodologies to enhance the reliability and validity of health outcomes and determinants data To provide a public-access information base to engage all stakeholders, including national policy makers and health systems planners, in planning and decision-making processes about the health and well-being of older adults

Methods: INDEPTH SAGE's first full round of data collection included persons aged 50 years and older in the health and demographic surveillance sites. All persons aged 50+ years (for example, spouses and siblings) were invited to participate. Standardized SAGE survey instruments were used in all countries consisting of two main parts: 1) household questionnaire; 2) individual questionnaire. The procedures for including country-specific adaptations to the standardized questionnaire and translations into local languages from English follow those developed by and used for the World Health Survey.

Content - Household questionnaire 0000 Coversheet 0100 Sampling Information 0200 Geocoding and GPS Information 0300 Recontact Information 0350 Contact Record 0400 Household Roster 0450 Kish Tables and Household Consent 0500 Housing 0600 Household and Family Support Networks and Transfers 0700 Assets and Household Income 0800 Household Expenditures 0900 Interviewer Observations

• Individual questionnaire 1000 Socio-Demographic Characteristics 1500 Work History and Benefits 2000 Health State Descriptions and Vignettes 2500 Anthropometrics, Performance Tests and Biomarkers 3000 Risk Factors and Preventive Health Behaviours 4000 Chronic Conditions and Health Services Coverage 5000 Health Care Utilization 6000 Social Cohesion 7000 Subjective Well-Being and Quality of Life (WHOQoL-8 and Day Reconstruction Method) 8000 Impact of Caregiving 9000 Interviewer Assessment

Geographic coverage

Rural subdistrict Mpumalanga Province

Analysis unit

household and individuals

Universe

Agincourt Health and Demographic Surveillance Site fifty plus population

Kind of data

Sample survey data [ssd]

Sampling procedure

Simple random sample of 575 persons 50 years and older with an oversample of women from the 2005 HDSS census.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were based on the WHS Model Questionnaire with some modification and many new additions. A household questionnaire was administered to all households eligible for the study. An Individual questionnaire was administered to eligible respondents identified from the household roster. The questionnaires were developed in English and were piloted as part of the SAGE pretest. All documents were translated into Shangaan.

Cleaning operations

Data editing took place at a number of stages including: (1) office editing and coding (2) during data entry (3) structural checking of the CSPro files (4) range and consistency secondary edits in Stata

Response rate

86% of participants accepted to participate, 10% were not found and 4% refused to participate.

Various financial and non-financial conflicts of interests have been shown to influence the reporting of research findings, particularly in clinical medicine. In this study, we examine whether this extends to prognostic instruments designed to assess violence risk. Such instruments have increasingly become a routine part of clinical practice in mental health and criminal justice settings. The present meta-analysis investigated whether an authorship effect exists in the violence risk assessment literature by comparing predictive accuracy outcomes in studies where the individuals who designed these instruments were study authors with independent investigations. A systematic search from 1966 to 2011 was conducted using PsycINFO, EMBASE, MEDLINE, and US National Criminal Justice Reference Service Abstracts to identify predictive validity studies for the nine most commonly used risk assessment tools. Tabular data from 83 studies comprising 104 samples was collected, information on two-thirds of which was received directly from study authors for the review. Random effects subgroup analysis and metaregression were used to explore evidence of an authorship effect. We found a substantial and statistically significant authorship effect. Overall, studies authored by tool designers reported predictive validity findings around two times higher those of investigations reported by independent authors (DOR = 6.22 [95% CI = 4.68–8.26] in designers' studies vs. DOR = 3.08 [95% CI = 2.45–3.88] in independent studies). As there was evidence of an authorship effect, we also examined disclosure rates. None of the 25 studies where tool designers or translators were also study authors published a conflict of interest statement to that effect, despite a number of journals requiring that potential conflicts be disclosed. The field of risk assessment would benefit from routine disclosure and registration of research studies. The extent to which similar conflict of interests exists in those developing risk assessment guidelines and providing expert testimony needs clarification.

Evidence-based medicine: assessment of

knowledge of basic epidemiological and research methods among medical doctors

Submitted to Venera ma'am by Roshan Shinde Group 32

EVIDENCE BASED MEDICINE is the main source of new knowledge for doctors in this era. The main objectives of EBM are as follows,

To evaluate the knowledge of basic research methods and data analysis among medical doctors. To assess factors such as the country of the medical school graduation profession.

Importance of Research Competence:

1. The study emphasizes that a solid understanding of epidemiology and biostatistics is essential for doctors to critically appraise medical literature and make informed clinical decisions.

2. Previous Findings: Prior studies indicated that many doctors lack proficiency in research methods, with significant gaps in understanding key concepts of evidence-based medicine (EBM).

Materials and Methods

Data collection and study population

The study involved 40 departments and employed around 500 doctors.

A random selection of 15 departments was made for participant recruitment.

Data collection

A supervised, self-administered questionnaire was distributed during morning staff meetings.

The questionnaire consisted of 10 multiple-choice questions focused on basic epidemiology and statistics, along with demographic data.

Participants were divided into two groups based on their country of medical school graduation: those from the former Soviet Union (Eastern education) and those from other countries (Western education).

The questionnaire was completed anonymously, and all participants were efficient in Hebrew.

Questionnaire

1. Sections of the Questionnaire:

Personal Details: This section collected demographic information about the doctors, including:

• Country of graduation

• Year of graduation from medical school

• Professional status (whether they are specialists or residents)

• Reading and writing habits related to medical literature.

Knowledge Assessment: This section consisted of 10 multiple-choice questions focused on basic research methods and statistics, divided as follows:

Statistics: 5 questions

Epidemiology: 5 questions

2. Basis for Statistical Questions:

The questions on statistics were derived from a list of commonly used statistical methods identified by Emerson and Colditz in 1983. This list was previously utilized for quality evaluations of articles published in the New England Journal of Medicine and referenced in a similar study by Horton and Switzee. This approach ensures that the questions are relevant and grounded in established research practices.

3. Scoring Methodology:

• Any missing answers to questions on epidemiological and statistical methods were considered incorrect. This scoring method emphasizes the importance of attempting to answer all questions and reflects a strict approach to assessing knowledge.

• The decision to mark unanswered questions as incorrect may encourage participants to engage more thoughtfully with the questionnaire, although it could also discourage some from attempting to answer if they are unsure

To ensure validity of the questionnaire, the 10 questions assessing knowledge were given to 15 members of the Epidemiology Department, Ben‐Gurion University. All of them correctly answered all the questions.

Results:

Response Rate: Out of 260 eligible doctors, 219 completed the questionnaire (84.2% response rate).

Statistical methods

1. Comparison of Categorical Variables:

Chi-Squared Test (x²): This test was used to examine differences between categorical variables. It assesses whether the observed frequencies in each category differ from what would be expected under the null hypothesis.

Fisher's Exact Test: This test was employed when sample sizes were small or when the assumptions of the chi-squared test were not met. It is particularly useful for 2×2 contingency tables.

2. Comparison of Ordinal Variables:

Mann-Whitney U Test: This non-parametric test was used to compare ordinal variables with multiple values, such as the scores obtained from the questionnaire. It assesses whether the distributions of two independent samples differ.

3. Paired Comparisons:

Wilcoxon's Signed Rank Test: This non-parametric test was used for paired comparisons of scores. It evaluates whether the median of the differences between paired observations is significantly different from zero.

4. Correlation Analysis:

Spearman's Rank Correlation Coefficient: This test was used to estimate the correlation between continuous variables. It assesses how well the relationship between two variables can be described using a monotonic function.

5. Multivariable Analysis:

Linear Regression: This method was used to explain the final score based on multiple variables. The analysis adjusted for all variables that were found to be related in the univariable analysis with a p-value of less than 0.1. This approach helps to identify the independent effects of each variable on the outcome.

6. Significance Level:

A p-value of 0.05 was considered statistically significant, indicating that there is less than a 5% probability that the observed results occurred by chance.

7. Data Presentation:

Normally distributed variables were expressed as mean (standard deviation, SD), while non-normally distributed variables were presented as median and interquartile range (IQR). This distinction is important for accurately representing the data's distribution.

Table 2 depicts doctors' professional characteristics according to the country of medical school graduation. Of 219 participants, 84 (38.4%) graduated from the former Soviet republics. The remaining 135 doctors were distributed by the country of graduation as follows: Israel, 100 (45.7%); West and Central Europe, 22 (10.0%); Italy, 8; Germany, 3; Czech Republic, 3; Hungary, 3; Netherlands, 1; Romania, 4; South America, 10 (4.6%); Argentina, 5; Cuba, 3; Uruguay, 1; Brazil, 1; and North America, 3 (1.4%).

Time Elapsed Since Graduation:

• Doctors from Israel and other countries had a shorter time since graduation compared to those from the former Soviet Union:

• Foreign Graduates: 8 years

(Interquartile Range (IQR) 4-19)

Former Soviet Union Graduates: 10 years (IQR 6-19)

• The difference was statistically significant (p = 0.02), indicating that foreign graduates tended to have graduated more recently.

Professional Status:

There were fewer specialists among foreign graduates compared to those who graduated from Israel

Foreign Graduates: 32.8% were specialists

Israeli Graduates: 48.0% were specialists

This difference was also statistically significant (p = 0.02).

Choice of Residency:

There were notable differences in the choice of residency between the two groups:

Domestic Graduates: 29.3% chose pediatrics or obstetrics and gynecology

Conclusion

The analysis of doctors' professional characteristics based on their country of medical school graduation reveals important insights into the diversity of medical training backgrounds and their implications for specialization and residency choices. These findings underscore the need for ongoing evaluation of medical education and training systems to ensure that all graduates, regardless of their background, are adequately prepared to meet the healthcare needs of the population

Table 3 describes the reading and publishing habits of the participants. A total of 96% of the participants reported reading at least one article per week, whereas 35.2% usually read at least three articles. Specialists read significantly more articles per week—52.3% of them read at least three articles, compared with only 23.8% of the residents; p<0.001. Most of the doctors, 63.6%, participated in the writing of ⩽5 articles. Similar to the reading pattern, only 21.1% of the residents wrote ⩾6 articles compared with 44.0% of the specialists; p<0.001. The Spearman correlation value between reading and writing variables was 0.35; p<0.001

Conclusion

The analysis of reading and publishing habits among the study participants reveals important insights into the professional engagement of doctors with medical literature. The differences between specialists and residents, along with the positive correlation between reading and writing, underscore the need for targeted educational initiatives to enhance research literacy and foster a culture of inquiry within the medical community. Encouraging both reading and writing can contribute to the overall quality of medical practice and the advancement of evidence-based medicine.

Figure 1

The figure describes the average of correct answers to 10 questions in understanding different aspects of basic research methods. Two populations of doctors are compared: those who graduated in the former Soviet Union (Eastern type of education) and those who graduated in Israel, USA, Western and Central Europe,

In 2023, Mexico’s healthcare expenditure represented an estimated 5.7 percent of its gross domestic product (GDP), a decrease of 0.4 percentage points in comparison to 2020. This figure had remained relatively stable in previous years. In that year, Mexico's GDP amounted to approximately 1.8 trillion U.S. dollars. Mexico in a global contextHealthcare expenditure is comprised of insurance, research, facility provision, and all other expenses associated with public health. Mexico's spending on healthcare in relation to its GDP is staggeringly low compared to most OECD countries. The United States, for instance, allocated approximately 17 percent of its GDP to healthcare in 2023. Furthermore, Mexico had one of the lowest levels of per capita health expenditures worldwide that year, at 1,500 U.S dollars. This figure was equivalent to less than half of that reported by Chile, which spent 3,350 U.S. dollars per citizen on health. Health coverage in the North American countryIn 2021, around 56 percent of the Mexican population was covered under one of the country’s public health care programs. Another 46 percent was affiliated to public healthcare insurance. However, despite Mexico’s efforts and investment in healthcare, a significant share of their population is still considered vulnerable due to inadequate access to health services. According to a survey carried out in Mexico in 2020, around 43 percent of respondents in whose households there was at least one member that presented symptoms of an illness did not attend a medical consultation because there were no available appointments.

Urgent care centers face dynamic market conditions driven by fluctuating insurance reimbursement rate levels, the health of the economy and changing attitudes to technology-driven healthcare. Urgent care providers offer a convenient and cost-effective alternative to primary care doctor services, notably in short supply and emergency department services, which are more costly and impose burdensome, long wait times. Urgent care centers leverage flexible, extended hours and online scheduling to further consumer appeal. In response to these centers' convenience, cost and quality, industry revenue has grown at a CAGR of 3.1% over the past five years and is expected to total $46.7 billion in 2024 when revenue will jump by an estimated 0.5%. The emergence of technology and private equity plays a significant role in industry growth and performance. Innovative diagnostics and telemedicine have expanded competition even from do-it-yourself trends, bolstered by out-of-market businesses like retail clinics and pharmacies with diagnostic kits that offer new ways for individuals to connect with healthcare providers. Private equity partnerships increasingly drive industry growth as investors bring resources for expansion and innovation. While these partnerships can fuel consolidation, new technologies also enhance the quality of care, reduce costs and broaden the reach of smaller establishments. The industry faces opportunities associated with broader economic conditions, disposable income levels and healthcare access. Urgent care centers are especially relevant in geographic "healthcare deserts" where alternatives like primary healthcare providers are absent. However, market entry can also be complex because of challenges in securing capital and maintaining innovation. With federal funding for Medicare and Medicaid and the number of individuals with private health insurance expected to grow, profit will remain stable despite a slight wage increase. Despite evolving healthcare preferences that accept technology-driven services as a substitute for urgent care visits, industry revenue is forecast to grow at a CAGR of 2.9% through 2029 to $53.8 billion.

The number of medical cannabis patients in the U.S. according to estimates mostly from year-end 2024 was highest in the State of Florida. Florida had around *** thousand medical cannabis patients at that time. In that same year, Oklahoma had the highest percentage of medical cannabis patients. Medical marijuana There may be many positive effects of medical cannabis, including to patient health and to the economy. However, medical cannabis market forecasts in the U.S. for the coming years have been revised down. From a medical point of view, the most commonly cited benefits of the drug were pain reduction and sleep. There are currently numerous research projects underway in the U.S. to determine the medical benefits and therapeutic uses of marijuana products, as well as the potential impact of marijuana legalization on the U.S. economy. Public opinionPublic opinion on the effects of marijuana and its ability to be used in patient care vary. However, it is clear that many U.S. adults support the legalization of marijuana in some form. A recent study indicated that the support for marijuana legalization has been increasing in recent history. Another study has shown that an overwhelming majority of participants felt that cannabis has valid medical uses. Despite current efforts at legalization and research underway, marijuana with over *** percent of THC – for any use – is considered illegal under federal U.S. law.

Abstract

Purpose: The multi-country Study on Global Ageing and Adult Health (SAGE) is run by the World Health Organization's Multi-Country Studies unit in the Innovation, Information, Evidence and Research Cluster. SAGE is part of the unit's Longitudinal Study Programme which is compiling longitudinal data on the health and well-being of adult populations, and the ageing process, through primary data collection and secondary data analysis. INDEPTH SAGE Wave 1 (2006/7) provides data on the health and well-being of adults in: Ghana, India and South Africa. Objectives: To obtain reliable, valid and comparable health, health-related and well-being data over a range of key domains for adult and older adult populations in nationally representative samples To examine patterns and dynamics of age-related changes in health and well-being using longitudinal follow-up of a cohort as they age, and to investigate socio-economic consequences of these health changes To supplement and cross-validate self-reported measures of health and the anchoring vignette approach to improving comparability of self-reported measures, through measured performance tests for selected health domains To collect health examination and biomarker data that improves reliability of morbidity and risk factor data and to objectively monitor the effect of interventions

Additional Objectives: To generate large cohorts of older adult populations and comparison cohorts of younger populations for following-up intermediate outcomes, monitoring trends, examining transitions and life events, and addressing relationships between determinants and health, well-being and health-related outcomes To develop a mechanism to link survey data to demographic surveillance site data To build linkages with other national and multi-country ageing studies To improve the methodologies to enhance the reliability and validity of health outcomes and determinants data To provide a public-access information base to engage all stakeholders, including national policy makers and health systems planners, in planning and decision-making processes about the health and well-being of older adults

Methods: INDEPTH SAGE's first full round of data collection included persons aged 50 years and older in the health and demographic surveillance sites. All persons aged 50+ years (for example, spouses and siblings) were invited to participate. Standardized SAGE survey instruments were used in all countries consisting of two main parts: 1) household questionnaire; 2) individual questionnaire. The procedures for including country-specific adaptations to the standardized questionnaire and translations into local languages from English follow those developed by and used for the World Health Survey.

Content

Household questionnaire 0000 Coversheet 0100 Sampling Information 0200 Geocoding and GPS Information 0300 Recontact Information 0350 Contact Record 0400 Household Roster 0450 Kish Tables and Household Consent 0500 Housing 0600 Household and Family Support Networks and Transfers 0700 Assets and Household Income 0800 Household Expenditures 0900 Interviewer Observations

Individual questionnaire 1000 Socio-Demographic Characteristics 1500 Work History and Benefits 2000 Health State Descriptions and Vignettes 2500 Anthropometrics, Performance Tests and Biomarkers 3000 Risk Factors and Preventive Health Behaviours 4000 Chronic Conditions and Health Services Coverage 5000 Health Care Utilization 6000 Social Cohesion 7000 Subjective Well-Being and Quality of Life (WHOQoL-8 and Day Reconstruction Method) 8000 Impact of Caregiving 9000 Interviewer Assessment

Geographic coverage

Kassena-Nankana District of the Upper East region of Ghana.

Analysis unit

households and individuals

Universe

Navrongo Health and Demographic Surveillance Site fifty plus population

Kind of data

Sample survey data [ssd]

Sampling procedure

Single random sample of individuals 50+ years. Sampling frame obtained from demographic surveillance database. No replacement of individuals not met, not found or for refusals.

Mode of data collection

Face-to-face [f2f], PAPI

Research instrument

The questionnaires were based on the WHS Model Questionnaire with some modification and many new additions. A household questionnaire was administered to all households eligible for the study. An Individual questionnaire was administered to eligible respondents identified from the household roster. The questionnaires were developed in English and were piloted as part of the SAGE pretest. All documents were translated into XX. All INDEPTH SAGE generic questionnaires are available as external resources.

Cleaning operations

Data editing took place at a number of stages including: (1) office editing and coding (2) during data entry (3) structural checking of the CSPro files (4) range and consistency secondary edits in Stata

Response rate

A total of 900 were sampled. 593 successful respondents in data set. Response rate (593/900) is 65.9%

ObjectiveTo examine the validity of the Recent Physical Activity Questionnaire (RPAQ) which assesses physical activity (PA) in 4 domains (leisure, work, commuting, home) during past month.Methods580 men and 1343 women from 10 European countries attended 2 visits at which PA energy expenditure (PAEE), time at moderate-to-vigorous PA (MVPA) and sedentary time were measured using individually-calibrated combined heart-rate and movement sensing. At the second visit, RPAQ was administered electronically. Validity was assessed using agreement analysis.ResultsRPAQ significantly underestimated PAEE in women [median(IQR) 34.1 (22.1, 52.2) vs. 40.6 (32.4, 50.9) kJ/kg/day, 95%LoA: −44.4, 63.4 kJ/kg/day) and in men (43.7 (29.0, 69.0) vs. 45.5 (34.1, 57.6) kJ/kg/day, 95%LoA: −47.2, 101.3 kJ/kg/day]. Using individualised definition of 1MET, RPAQ significantly underestimated MVPA in women [median(IQR): 62.1 (29.4, 124.3) vs. 73.6 (47.8, 107.2) min/day, 95%LoA: −130.5, 305.3 min/day] and men [82.7 (38.8, 185.6) vs. 83.3 (55.1, 125.0) min/day, 95%LoA: −136.4, 400.1 min/day]. Correlations (95%CI) between subjective and objective estimates were statistically significant [PAEE: women, rho = 0.20 (0.15–0.26); men, rho = 0.37 (0.30–0.44); MVPA: women, rho = 0.18 (0.13–0.23); men, rho = 0.31 (0.24–0.39)]. When using non-individualised definition of 1MET (3.5 mlO2/kg/min), MVPA was substantially overestimated (∼30 min/day). Revisiting occupational intensity assumptions in questionnaire estimation algorithms with occupational group-level empirical distributions reduced median PAEE-bias in manual (25.1 kJ/kg/day vs. −9.0 kJ/kg/day, p

IntroductionArts and health practice and research has expanded rapidly since the turn of the millennium. A World Health Organization scoping review of a large body of evidence claims positive health benefits from arts participation and makes recommendations for policy and implementation of arts for health initiatives. A more recent scoping review (CultureForHealth) also claims that current evidence is sufficient to form recommendations for policy and practice. However, scoping reviews of arts and health research—without critical appraisal of included studies—do not provide a sound basis for recommendations on the wider implantation of healthcare interventions.MethodsWe performed a detailed assessment of 18 Randomised Controlled Trials (RCTs) on arts-based interventions included in Section 1 of the CultureForHealth report using the Joanna Briggs Institute Critical Appraisal Tool for RCTs (2023).ResultsThe 18 RCTs included demonstrated considerable risks of bias regarding internal and statistical conclusion validity. Moreover, the trials are substantially heterogeneous with respect to settings, health-issues, interventions, and outcomes, which limits their external validity, reliability, and generalisability.ConclusionsThe absence of a critical appraisal of studies included in the CultureForHealth report leads to an overinterpretation and overstatement of the health outcomes of arts-based interventions. As such, the CultureForHealth review is not a suitable foundation for policy recommendations, nor for formulating guidance on implementation of arts-based interventions for health.

BCG, Bacillus Calmette-Guérin; DPT, diphtheria-pertussis-tetanus; HBV, hepatitis B virus.

Scenarios of true effect distribution used in the calculation of likelihood of degradation.