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Healthcare Analytics Market Growth
Rise in adoption of big data in healthcare organizations for tackling various risks related to various different chronic diseases drives the market growth.
PORTLAND , PORTLAND, OR, UNITED STATE, July 28, 2022 /EINPresswire.com / -- Increase in adoption of big data in healthcare organizations, rise in government initiatives to escalate the adoption of electronic health records (EHRs) among healthcare organizations, and growing pressure in the healthcare sector to curb unnecessary expenditure fuel the growth of the global healthcare analytics market .
On the other hand, lack of skilled labors and high implementation costs restrain the growth to some extent. However, use of cloud-based analytics across various healthcare providers is anticipated to pave the way for lucrative opportunities for the key players in the industry.
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Impact of COVID-19 on Healthcare Analytics Market-
•The outbreak of the pandemic led to increase in demand for upgraded analytics solutions among healthcare organizations to support the establishments during critical situation in the pandemic. This, in turn, has driven the global healthcare analytics market.
•This trend is most likely to continue till the pandemic is completely not over.
Based on application, the financial analysis segment contributed to the largest share in 2020, holding more than two-fifths of the global healthcare analytics market. Rise in need to acclimatize in the ever-changing and unpredictable healthcare landscape drives the growth of the segment.
The clinical analysis segment, on the other hand, would grow at the fastest CAGR of 18.5% throughout the forecast period. Growing demand from patients to track their health data and share it with their respective healthcare professionals for additional remedies and advices fuels the segment growth.
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Based on component, the service segment accounted for nearly half of the global healthcare analytics market in 2020, and is projected to lead the trail by the end of 2030. Rise in demand for cloud-based healthcare analytics services during the global health crisis across the globe is expected to provide potential growth opportunities for the segment.
However, the software segment would manifest the fastest CAGR of 16.6% during the forecast period. This is because majority of health care providers choose data warehouse to maintain proper operations of their organizations.
Based on region, North America held the major share in 2020, garnering more than half of the global healthcare analytics market, due to increasing adoption of analytics solutions in the healthcare industry and presence of major players in the region.
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The market across Asia-Pacific would cite the fastest CAGR of 19.4% from 2021 to 2030. Growing government healthcare regulations to reduce the rising healthcare costs and increasing regulatory requirements propel the need for healthcare analytics in the region. This factor drives the market growth in this province.
The key players profiled in the healthcare analytics market analysis are Allscript Healthcare Solution, Cerner Corporation, Health Catalyst, HMS (Vitreoshealth)IBM Corporation, McKesson Corporation, MedeAnalytics, Inc., Oracle Corporation, Optum, Inc., and SAS, Institute. These players have adopted various strategies to increase their market penetration and strengthen their position in the healthcare analytics industry.
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Lastly, this report provides market intelligence most comprehensively. The report structure has been kept such that it offers maximum business value. It provides critical insights into the market dynamics and will enable strategic decision-making for the existing market players as well as those willing to enter the market.
1. Healthcare API Market
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2.23. The NHS was founded to provide universal access to healthcare, though healthcare is only one of many factors that influence our health. The social and economic environment in which we are born, grow up, live, work and age, as well as the decisions we make for ourselves and our families collectively have a bigger impact on our health than health care alone. While life expectancy continues to Improve for the most affluent 10% of our population, it has either stalled or fallen for the most deprived 10%. Premature mortality in Blackpool, the most deprived part of the country, is twice as high as in the most affluent areas . Women in the most deprived parts of England spend 34% of their lives in poor health, compared to 17% in the wealthiest areas . Multimorbidity is more common in deprived areas , and some parts of our population including BAME communities are at substantially higher risk of poor health and early death. On average, adults with a learning disability die 16 years earlier than the general population – 13 years for men, 20 years for women . People with severe mental health illnesses tend to die 15-20 years earlier than those without .
2.24. For reasons both of fairness and of overall outcomes improvement, the NHS Long Term Plan therefore takes a more concerted and systematic approach to reducing health inequalities and addressing unwarranted variation in care. In order to do so and reflecting our Public Sector Equality Duties and other public duties:
2.25. NHS England will continue to target a higher share of funding towards geographies with high health inequalities than would have been allocated using solely the core needs formulae. This funding is estimated to be worth over £1 billion by 2023/24. For the five-year CCG allocations that underpin this Long Term Plan, NHS England will introduce from April 2019 more accurate assessment of need for community health and mental health services, as well as ensuring the allocations formulae are more responsive to the greatest health inequalities and unmet need in areas such as Blackpool. Furthermore, no area will be more than 5% below its new target funding share effective from April 2019, with additional funding growth going to areas between 5% and 2.5% below their target share. NHS England will also commission the Advisory Committee on Resource Allocation to conduct and publish a review of the inequalities adjustment to the funding formulae.
2.26. To support local planning and ensure national programmes are focused on health inequality reduction, the NHS will set out specific, measurable goals for narrowing inequalities, including those relating to poverty, through the service improvements set out in this Long Term Plan. All local health systems will be expected to set out during 2019 how they will specifically reduce health inequalities by 2023/24 and 2028/29. These plans will also, for the first time, clearly set out how those CCGs benefiting from the health inequalities adjustment are targeting that funding to Improve the equity of access and outcomes. NHS England, working with PHE and our partners in the voluntary and community sector and local government, will develop and publish a ‘menu’ of evidence-based interventions that if adopted locally would contribute to this goal. We will expect CCGs to ensure that all screening and vaccination programmes are designed to support a narrowing of health inequalities.
2.27. While we cannot treat our way out of inequalities, the NHS can ensure that action to drive down health inequalities is central to everything we do. For example:
2.28. In maternity services, we will implement an enhanced and targeted continuity of carer model to help improve outcomes for the most vulnerable mothers and babies. By 2024, 75% of women from BAME communities and a similar percentage of women from the most deprived groups will receive continuity of care from their midwife throughout pregnancy, labour and the postnatal period. This will help reduce pre-term births, hospital admissions, the need for intervention during labour, and women’s experience of care.
2.29. Women from the most deprived communities are 12 times more likely to smoke during pregnancy than women from more affluent areas. In addition to the enhanced midwife model, we will offer all women who smoke during their pregnancy, specialist smoking cessation support to help them quit.
2.30. People with severe mental illnesses are at higher risk of poor physical health. Compared with the general patient population, patients with severe mental illnesses are at substantially higher risk of obesity, asthma, diabetes, chronic obstructive pulmonary disease (COPD) and cardiovascular disease  and make more use of urgent and emergency care . People with a long-standing mental health problem are twice as likely to smoke, with the highest rates among people with psychosis or bipolar disorder. By 2020/21, the NHS will ensure that at least 280,000 people living with severe mental health problems have their physical health needs met. By 2023/24, we will further increase the number of people receiving physical health checks to an additional 110,000 people per year, bringing the total to 390,000 checks delivered each year including the ambition in the Five Year Forward View for Mental Health.
2.31. Over 1.2 million people in England have a learning disability and face significant health inequalities compared with the rest of the population ,. Autism is a lifelong condition and a part of daily life for around 600,000 people in England. It is estimated that 20-30% of people with a learning disability also have autism . Despite suffering greater ill-health, people with a learning disability, autism or both often experience poorer access to healthcare . In 2017, the Learning Disabilities Mortality Review Programme (LeDeR) found that 31% of deaths in people with a learning disability were due to respiratory conditions and 18% were due to diseases of the circulatory system. Across the NHS, we will do more to ensure that all people with a learning disability, autism, or both can live happier, healthier, longer lives. This means that we will provide timely support to children and young people and their families. We will do more to keep people well with proactive care in the community. We will ensure that reasonable adjustments are made so that wider NHS services can support, listen to, and help Improve the health and wellbeing of people with learning disabilities and autism, and their families. Over the next five years, we will invest to ensure that children with learning disabilities have their needs met by eyesight, hearing and dental services, are included in reviews as part of general screening services and are supported by easily accessible, ongoing care. For people with the most complex needs, we will continue to Improve access to care in the community, so that more people can live in or near to their own homes and families. Finally, we will accelerate the LeDeR initiative to identify common themes and learning points and provide targeted support to local areas. Further action on top of this is also set out in Chapter Three.
2.32 The number of people sleeping rough has been increasing in latest years. People affected by homelessness die, on average, around 30 years earlier than the general population . Outside London, where people are more likely to sleep rough for longer, support needs may be 31% of people affected by homelessness have complex needs, and additional financial, interpersonal and emotional needs that make engagement with mainstream services difficult. 50% of people sleeping rough have mental health needs, but many parts of the country with large numbers of rough sleepers do not have specialist mental health support and access to mainstream services is challenging. We will invest up to £30 million extra on meeting the needs of rough sleepers, to ensure that the parts of England most affected by rough sleeping will have better access to specialist homelessness NHS mental health support, integrated with existing outreach services.
UCLH Pathway Programme
University College London Hospitals has developed the Pathway Programme for homeless patients admitted to hospital. It involves in-hospital GPs and dedicated Pathway nurses working with others to address the housing, financial and social issues of patients. Following its introduction, A&E attendances by supported individuals fell by 38% with a 78% reduction in bed days . Pathway, now a charity, helps the NHS to create hospital teams to support homeless patients and ten hospitals in London, Leeds, Bradford, Manchester and Brighton have since adopted the model .
2.33. We will continue to identify and support carers, particularly those from vulnerable communities. Carers are twice as likely to suffer from poor health compared to the general population, primarily due to a lack of information and support, finance concerns, stress and social isolation. Quality marks for carer-friendly GP practices, developed with the Care Quality Commission (CQC), will help carers identify GP services that can accommodate their needs. We will encourage the national adoption of carer’s passports, which identify someone as a carer and enable staff to involve them in a patient’s care, and set out guidelines for their use based on trials in Manchester and Bristol. These will be complemented by developments to electronic health records that allow people to share their caring status with healthcare professionals wherever they present.
2.34. Carers should not have to deal with emergencies on their own. We will ensure that more carers understand the out-of-hours options that are available to them and have appropriate back-up support in place for when they need it. Up to 100,000 carers will benefit from ‘contingency planning’ conversations and have their plans included in Summary Care Records, so that professionals know when and how to call those plans into action when they are needed.
2.35. Young carers feel say they feel invisible and often in distress, with up to 40% reporting mental health problems arising from their experience of caring. Young Carers should not feel they are struggling to cope on their own. The NHS will roll out ‘top tips’ for general practice which have been developed by Young Carers, which include access to preventive health and social prescribing, and timely referral to local support services. Up to 20,000 Young Carers will benefit from this more proactive approach by 23/24.
2.36. We will invest in expanding NHS specialist clinics to help more people with serious gambling problems. Over 400,000 people in England are problem gamblers and two million people are at risk, but current treatment only reaches a small number through one national clinic. We will therefore expand geographical coverage of NHS services for people with serious gambling problems, and work with partners to tackle the problem at source.
2.37. The NHS will continue to commission, partner with and champion local charities, social enterprises and community interest companies providing services and support to vulnerable and at-risk groups. These organisations are often leading innovators in their field. Many provide a range of essential health, care and wellbeing services to groups that mainstream services struggle to reach. Of 100,000 social enterprises in the UK, 31% work in the 20% most deprived communities , creating jobs and filling gaps in support as well as addressing wider determinants of health and wellbeing such as debt and housing. For example, Bevan Healthcare, a social enterprise in Bradford, provides NHS GP services alongside wider support to meet the needs of people who are homeless . Community Catalysts, a community interest company, works with people with long term health and care needs to help them develop and run their own micro community enterprises with over 1,800 enterprises being launched across the country . This kind of innovation will need to be encouraged and supported by ICSs to address health inequalities in their populations.
2.38. A major factor in maintaining good mental health is stable employment. This Plan sets out how the NHS is improving access to mental health support for people in work and our commitment to supporting people with severe mental illnesses to seek and retain employment. As the largest employer in England, we are also taking action to Improve the mental health and wellbeing of our workforce and setting an example to other employers.
2.39. As well as moderating growth in demand for healthcare, NHS action on health and health inequalities relieves pressure on other essential public services. Detail of some of these actions supported by this Long Term Plan are set out in the Appendix.
49. Public Health England (2018) Severe mental illness (SMI) and physical health inequalities: briefing. Available from: https://www.gov.uk/government/publications/severe-mental-illness-smi-physical-health-inequalities/severe-mental-illness-and-physical-health-inequalities-briefing
50. Dorning, H., Davies, A. & Blunt, I. (2015) Focus on: People with mental ill health and hospital use. The Nuffield Trust. Available from: https://www.nuffieldtrust.org.uk/research/focus-on-people-with-mental-ill-health-and-hospital-use
51. Mencap (2018) How common is learning disability?. Available from: https://www.mencap.org.uk/learning-disability-explained/research-and-statistics/how-common-learning-disability
52. Hosking, F., Carey, I., Shah, S., Harris, T., DeWilde, S., Beighton, C. & Cook, D. (2016) Mortality Among Adults With Intellectual Disability in England: Comparisons With the General Population. American Journal of Public Health. 106 (8), 1483-1490. Available from: https://doi.org/10.2105/AJPH.2016.303240
53. Emerson, E. & Baines, S. (2010) The Estimated Prevalence of Autism among Adults with Learning Disabilities in England. Improving Health and Lives: Learning Disabilities Observatory. Available from: http://www.wecommunities.org/MyNurChat/archive/LDdownloads/vid_8731_IHAL2010-05Autism.pdf
54. Lenehan, C. (2017) These are our children. Council for disabled children. Available from: https://www.ncb.org.uk/sites/default/files/field/attachment/These%20are%20Our%20CHildren_Lenehan_Review_Report.pdf
55. Thomas, B. (2012) Homelessness kills: An analysis of the mortality of homeless people in the early twentyfirst century in England. Crisis. Available from: https://www.crisis.org.uk/media/236798/crisis_homelessness_kills2012.pdf
56. Wyatt, L. (2017) Positive outcomes for homeless patients in UCLH Pathway programme. British Journal of Healthcare Management. 23 (8), 367-371. Available from: https://doi.org/10.12968/bjhc.2017.23.8.367
57. Pathway (2018) About us. Available from: https://www.pathway.org.uk/about-us/
58. Social Enterprise UK (2016) What is it all about? Available from: https://www.socialenterprise.org.uk/what-is-it-all-about
59. Bvan Healthcare (2018) About Bevan Healthcare. Available from: https://bevanhealthcare.co.uk/about-us/
60. Community Catalysts (2018) Community enterprise. Available from: https://www.communitycatalysts.co.uk/whatweoffer/communitymicro-enterprise/
This data includes the full details from every question on Modern Healthcare's 15th annual Management Consultant Firms Survey from all responding firms, as well as a PDF of the print ranking/analysis page. Some of the sharpest minds in healthcare share their wisdom on the best approaches to take on the challenges facing providers today. Firms are ranked by 2019 revenue from total healthcare consulting fees. Published Aug. 24, 2020, p. 42.
This list includes the following data points:
Also including answers to:
Note: Information is self-reported from companies responding to Modern Healthcare's survey; only those that participated were considered for this ranking.
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Many of us wonder what exactly literacy is and the role it plays in improving the lives of people on a daily basis. Literacy is a human right and can be considered a tool of personal empowerment: a means for social and human development. Educational opportunities depend on literacy. Thus, literacy is essential for eradicating poverty, improving the socio-economic status of communities, reducing child and maternal mortality rates, curbing population growth, achieving gender equality and promoting sustainable development at the local, regional and national levels.1
According to a report released by the United Nations Educational, Scientific and Cultural Institution (UNESCO) in 2007, the countries of South and South-West Asia have the highest number of illiterate adults in the world: an estimated 388 million. While literacy rates in Central Asia are not as high, the gender gap is of concern, as 72.5 per cent of the illiterate population are women.2 The lack of education and literacy among women and children is manifold causing a direct and indirect impact on their sense of empowerment, low socio-economic status, health care and ultimately poor health.
To Improve literacy rates, 2003-2012 has been designated as the United Nations Literacy Decade. In this context, unesco has been partnering with UN agencies and other organizations to promote literacy and teach basic health literacy, through formal and informal educational programmes in many countries.
Health literacy and the pivotal role it plays has been defined by the World Health Organization as follows:
Health literacy implies the achievement of a level of knowledge, personal skills and confidence to take action to Improve personal and community health by changing personal lifestyles and living conditions. Thus, health literacy means more than being able to read pamphlets and make appointments. By improving people's access to health information, and their capacity to use it effectively, health literacy is critical to empowerment. Health literacy is itself dependent upon more general levels of literacy. Poor literacy can affect people's health directly by limiting their personal, social and cultural development, as well as hindering the development of health literacy.3
Health care providers often face challenges when catering to the needs of the communities they serve. One of the important barriers which needs to be addressed is the lack of compliance due to the low levels of health care literacy worldwide. As a health care provider, public health practitioner and health educator working with global communities, I have found that certain groups of populations, such as women, those living in rural areas and immigrants are vulnerable to serious health disparities. Unfortunately, they experience significantly worse health outcomes such as higher rates of morbidity and mortality due to a lack of health literacy levels. Some of the health risks faced by these groups include a higher incidence of cancer, diabetes, high blood pressure and hiv/aids. These health risks demand effective communication between the providers and the target population -- to help them recognize, minimize and respond effectively and in a timely fashion to potential health problems. It is ironic that while there is such a compelling need for effective communication, the process is extremely complicated and often poorly developed. Language, socio-political, economic and cultural barriers and time constraints pose challenges to health care providers.
Incorporating health literacy into educational programmes for youth and adult learners is vital. An example of a groundbreaking health literacy project is the collaboration between UNESCO, the Joint United Nations Programme on hiv/aids (UNAIDS) and other stakeholders resulting in the launching of EDUCAIDS in 2004 -- the Global Initiative on Education and HIV&AIDS. The two primary goals of this initiative are:
1. To prevent the spread of HIV through education; and
2. To protect the core functions of the education system from the worst effects of the epidemic.4
This ground breaking initiative has been launched at various levels (partnering with local, national and international stakeholders) in many countries throughout the world.
The following are a few projects and initiatives illustrating the efforts made by UN agencies, local and national governments, non-governmental organizations and foundations partnering at the grass-roots level to increase health literacy rates and Improve the health status of communities:
Angola: Since 2007, UNESCO has been partnering with the Ministry of Education in Angola to offer mainstream education on HIV and AIDS throughout the school curriculum as part of the ongoing process of education reform. As a result, HIV and AIDS prevention is being integrated into education materials for primary and secondary schools across the country. UNESCO has been working with The Virginio Bruni Tedeschi Foundation to educate children about HIV/AIDS by enhancing the capacity of the Ministry of Education to deliver in-service training to teachers. The programme is designed to Improve the quality of primary and secondary school teacher-training in the area of HIV and AIDS, evaluate its outcomes and impact through consultations with stakeholders to ensure ownership, and produce harmonized guidelines and approaches to in-house teacher-training on HIV and AIDS prevention, care and support. The programme also aims to support the Ministry of Education in developing a strategy and an implementation plan for rolling-out in-service teacher training across the country.5
An ongoing project evaluation and assessment was conducted in mid-2008. One of the important lessons learned was that coordination of efforts among the stakeholders and support for the Government's education sector in response to HIV and AIDS is critical to achieving maximum impact of interventions in the post-conflict and transition phase in Angola.
Viet Nam: EDUCAIDS was launched in 2006 in Viet Nam; UNESCO has partnered with the United Nations Population Fund, the United Nations Children's Fund (UNICEF) and the School Health HIV and Education Working Group, which supports the Ministry of Education and Training (MoET). The project goals in Viet Nam were to institutionalize a policy framework to mandate reproductive health and HIV/AIDS education in schools, thereby mainstreaming prevention education in the school curriculum and promoting capacity-building for educational personnel through pre-service and in-service teacher training.6 The establishment of an interdepartmental coordination mechanism in MoET to manage and implement comprehensive responses to HIV and AIDS. This partnering also led to the development of guidelines for implementation of latest legislation on HIV/AIDS in Viet Nam's education sector. The programme seeks to address the various forms of discrimination faced by people living with HIV/AIDS and to protect their rights to health care access and equal employment opportunities.
Moldova: UNESCO launched the EDUCAIDS project in Moldova in 2006 after consultations with MoET, UNAIDS, the United Nations Development Programme, UNICEF, the World Bank, and community-based organizations. The EDUCAIDS project team identified the need for advocacy to mobilize support from decision makers as well as gaps in educator training and support. To address these specific needs, UNESCO in liaison with UNICEF and the Education for All-Fast Track Initiative, has organized life skills-based education seminars for educators from child and family community centres. In Moldova's sensitive environment, and by adhering to the country's prevailing cultural and religious beliefs, EDUCAIDS has been useful in promoting a coordinated approach among UN agencies and other partners in addressing the challenges posed by HIV/AIDS.7
Mexico: In June 2007, EDUCAIDS was launched in Mexico as a collaborative partnership between the Ministry of Education, UN agencies, civil society and youth. The main objective of EDUCAIDS in Mexico is to develop a national strategy to promote HIV and sex education in schools.8 Launching the project was instrumental in providing UNESCO with the opportunity to profile its initiatives and share lessons learned, advocate and network with relevant stakeholders, and learn about the latest developments and experience related to the AIDS epidemic at the XVII International AIDS Conference in Mexico City in August 2008.
In addition to these activities, UNESCO's Regional Office for Culture in Latin America and the Caribbean, in collaboration with several United Nations agencies and institutions under the umbrella of the Cuban Ministries of Culture and Public Health, launched a series of cultural events with an underlying focus on promoting health literacy, especially HIV/AIDS education and prevention. One such activity was a workshop created as a multidisciplinary space for the exchange of experiences and the assessment of arts-based approaches to HIV and AIDS, with a particular emphasis on theatre and audiovisual productions. A multimedia approach was used to consider the impact of arts, creativity and literacy on changing attitudes, as well as behaviour modification -- both on the individual and collective level -- regarding the pandemic.9
Non-governmental organizations have recently been partnering with national and international agencies to incorporate informal health literacy programmes in developing countries, so as to Improve health care access and safe motherhood initiatives. The White Ribbon Alliance for Safe Motherhood (WRA) in India, for example, has been working closely with the Partnership for Maternal and Child Health and the Government of India to educate and empower women to make the right choices and Improve their health status. In the state of Orissa, women have an unfortunately low socio-economic status, low literacy levels, high incidences of early marriage, and a maternal mortality rate of 358, (considerably higher than the national average of 301). One contributing factor to this dismal picture is the high incidence of anaemia among pregnant Indian women. Studies also indicate that more than 53 per cent of women living in the state of Orissa are not involved in making decisions about their own health. In order to address these challenges, the above-mentioned stakeholders are working at the grass-root level to reach out to women, community leaders and policy makers to Improve the levels of health literacy in the state. Efforts so far have resulted in the implementation of WRA-Orissa launching in 12 districts, a campaign entitled "Deliver Now for Women and Children: Advocacy for Maternal, Newborn and Child Health in India". The campaign centres around the creation of community demand for quality maternal and child health, bringing about political will and making policy changes for better delivery of maternal and child health care, with an underlying theme of health literacy.10
Recommendations to promote and Improve health literacy among populations
* Health professionals need to be aware of the levels of education and health literacy among the populations they serve.
* Disseminated health information needs to be user-friendly and efforts should be made to keep verbal and written information simple. The increased use of charts and pictures may be more beneficial in improving communication: this also includes the development and testing of alternative and text-free educational methods.
* A neutral and friendly atmosphere between the providers and the clients will help to increase the level of communication and understanding, as well as to Improve patient compliance.
* Training and educating health care professionals, teachers, social workers and community volunteers about the importance of health literacy and effective health communication is of vital importance. This can be achieved by a periodic review of the materials and processes in use by the various stakeholders, and by training in both verbal and written communication skills.
* Local cultural beliefs and customs need to be considered when developing interventions or programs to Improve health literacy rates in the target population.
* If needed current programmes can be redesigned or adapted, based on the recommendations made as a result of monitoring and evaluating project outcomes.
* Working with and supporting the adult education sector at various levels will also help Improve the health literary levels among communities.
* If necessary, existing policies at the national, state and local levels can be modified or redesigned to Improve health literacy outcomes.11
In conclusion, health literacy is a valuable tool in empowering women and communities to Improve their health status and achieve sustainable development by reaching the indicators of the Millennium Development Goals 1-6.
1. Literacy Portal (http://portal.unesco.org/education/en/ev.php-URL_ID=54369&URL_DO=DO_TOPIC&URL_SECTION=201.html)
2. Fourth UNESCO Regional Literacy Conference to open in New Delhi (http://portal.unesco.org/education/en/ev.php-URL_ID=54831&URL_DO=DO_TOPIC&URL_SECTION=201.html)
3. Health Promotion Glossary (http://whqlibdoc.who.int/hq/1998/WHO_HPR_HEP_98.1.pdf)
4. EDUCAIDS -- the Global Initiative on Education and HIV & AIDS (http://portal.unesco.org/en/ev.php-URL_ID%3D36400&URL_DO%3DDO_TOPIC&URL_SECTION%3D201.html)
5. EDUCAIDS -- Angola (http://unesdoc.unesco.org/images/0016/ 001610/161028E.pdf)
6. EDUCAIDS -- Viet Nam (http://unesdoc.unesco.org/images/0016/ 001626/162629E.pdf)
7. EDUCAIDS -- Moldova (http://unesdoc.unesco.org/images/0015/001538/153884E.pdf)
8. EDUCAIDS -- Mexico (http://unesdoc.unesco.org/images/0015/ 001569/156997E.pdf)
9. Theatre and Visual Arts: A New Approach to HIV and AIDS in Latin America and the Caribbean (http://portal.unesco.org/en/ev.phpURL_ID=38930&URL_DO=DO_TOPIC&URL_SECTION=201.html)
10. Brief Report on Safe Motherhood Rally-cum-Public Hearing 25th November 2008, Boudh District, Orissa (http://www.who.int/pmnch/events/20081125_dnpubhearing_orissa.pdf)
11. Health Literacy Studies (http://www.hsph.harvard.edu/healthliteracy/overview.html)
The UN Chronicle is not an official record. It is privileged to host senior United Nations officials as well as distinguished contributors from outside the United Nations system whose views are not necessarily those of the United Nations. Similarly, the boundaries and names shown, and the designations used, in maps or articles do not necessarily imply endorsement or acceptance by the United Nations.
NEW YORK, Aug. 9, 2022 /PRNewswire/ -- The Insight Partners published latest research study on "Predictive Analytics Market Forecast to 2028 - COVID-19 Impact and Global Analysis By Component [Solution (Risk Analytics, Marketing Analytics, Sales Analytics, Customer Analytics, and Others) and Service], Deployment Mode (On-Premise and Cloud-Based), Organization Size [Small and Medium Enterprises (SMEs) and Large Enterprises], and Industry Vertical (IT & Telecom, BFSI, Energy & Utilities, Government and Defence, Retail and e-Commerce, Manufacturing, and Others)", the global predictive analytics market size is projected to grow from $12.49 billion in 2022 to $38.03 billion by 2028; it is expected to grow at a CAGR of 20.4% from 2022 to 2028.
Download PDF Brochure of Predictive Analytics Market Size - COVID-19 Impact and Global Analysis with Strategic Developments at: https://www.theinsightpartners.com/sample/TIPTE100000160/
Predictive Analytics Market Report Scope & Strategic Insights:
Market Size Value in
US$ 12.49 Billion in 2022
Market Size Value by
US$ 38.03 Billion by 2028
CAGR of 20.4% from 2022 to 2028
No. of Pages
No. of Charts & Figures
Historical data available
Component, Deployment Mode, Organization Size, and Industry Vertical
North America; Europe; Asia Pacific; Latin America; MEA
US, UK, Canada, Germany, France, Italy, Australia, Russia, China, Japan, South Korea, Saudi Arabia, Brazil, Argentina
Revenue forecast, company ranking, competitive landscape, growth factors, and trends
Predictive Analytics Market: Competitive Landscape and Key Developments
IBM Corporation; Microsoft Corporation; Oracle Corporation; SAP SE; Google LLC; SAS Institute Inc.; Salesforce.com, inc.; Amazon Web Services; Hewlett Packard Enterprise Development LP (HPE); and NTT DATA Corporation are among the leading players profiled in this report of the predictive analytics market. Several other essential predictive analytics market players were analyzed for a holistic view of the predictive analytics market and its ecosystem. The report provides detailed predictive analytics market insights, which help the key players strategize their growth.
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In 2022, Microsoft partnered with Teradata, a provider of a multi-cloud platform for enterprise analytics, for the integration of Teradata's Vantage data platform into Microsoft Azure.
In 2021, IBM and Black & Veatch collaborated to assist customers in keeping their assets and equipment working at peak performance and reliability by integrating AI with real-time data analytics.
In 2020, Microsoft partnered with SAS for the extension of their business solutions. As a part of this move, the companies will migrate SAS analytical products and solutions to Microsoft Azure as a preferred cloud provider for SAS cloud.
Increase in Uptake of Predictive Analytics Tools Propels Predictive Analytics Market Growth:
Predictive analytics tools use data to state the probabilities of the possible outcomes in the future. Knowing these probabilities can help users plan many aspects of their business. Predictive analytics is part of a larger set of data analytics; other aspects of data analytics include descriptive analytics, which helps users understand what their data represent; diagnostic analytics, which helps identify the causes of past events; and prescriptive analytics, which provides users with practical advice to make better decisions.
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Prescriptive analytics is similar to predictive analytics. Predictive modeling is the most technical aspect of predictive analytics. Data analysts perform modeling with statistics and other historical data. The model then estimates the likelihood of different outcomes. In e-commerce, predictive modeling tools help analyze customer data. It can predict how many people are likely to buy a certain product. It can also predict the return on investment (ROI) of targeted marketing campaigns. Some software-as-a-service (SaaS) may collect data directly from online stores, such as Amazon Marketplace.
Predictive analytics tools may benefit social media marketing by guiding users to plan the type of content to post; these tools also recommend the best time and day to post. Manufacturing industries need predictive analytics to manage inventory, supply chains, and staff hiring processes. Transport planning and execution are performed more efficiently with predictive analytics tools. For instance, SAP is a leading multinational software company. Its Predictive Analytics was one of the leading data analytics platforms across the world. Now, the software is gradually being integrated into SAP's larger Cloud Analytics platform, which does more business intelligence (BI) than SAP Predictive Analytics. SAP Analytics Cloud, which works on all devices, utilizes artificial intelligence (AI) to Improve business planning and forecasting. This analytics platform can be easily extended to businesses of all sizes.
North America is one of the most vital regions for the uptake and growth of new technologies due to favorable government policies that boost innovation, the presence of a substantial industrial base, and high purchasing power, especially in developed countries such as the US and Canada. The industrial sector in the US is a prominent market for security analytics. The country consists of a large number of predictive analytics platform developers. The COVID-19 pandemic enforced companies to adopt the work-from-home culture, increasing the demand for big data and data analytics.
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The pandemic created an enormous challenge for businesses in North America to continue operating despite massive shutdowns of offices and other facilities. Furthermore, the surge in digital traffic presented an opportunity for numerous online frauds, phishing attacks, denial of inventory, and ransomware attacks. Due to the increased risk of cybercrimes, enterprises began adopting advanced predictive analytics-based solutions to detect and manage any abnormal behavior in their networks. Thus, with the growing number of remote working facilities, the need for predictive analytics solutions also increased in North America during the COVID-19 pandemic.
Predictive Analytics Market: Industry Overview
The predictive analytics market is segmented on the basis of component, deployment mode, organization size, industry vertical, and geography. The predictive analytics market analysis, by component, is segmented into solutions and services. The predictive analytics market based on solution is segmented into risk analytics, marketing analytics, sales analytics, customer analytics, and others. The predictive analytics market analysis, by deployment mode, is bifurcated into cloud and on-premises. The predictive analytics market, by organization size, is segmented into large enterprises, and small and medium-sized enterprises (SMEs). The predictive analytics market, by vertical, is segmented into BFSI, manufacturing, retail and e-Commerce, IT and telecom, energy and utilities, government and defense, and others.
In terms of geography, the predictive analytics market is categorized into five regions—North America, Europe, Asia Pacific (APAC), the Middle East & Africa (MEA), and South America (SAM). The predictive analytics market in North America is sub segmented into the US, Canada, and Mexico. Predictive analytics software is increasingly being adopted in multiple organizations, and cloud-based predictive analytics software solutions are gaining significance in SMEs in North America. The highly competitive retail sector in this region is harnessing the potential of this technique to efficiently transform store layouts and enhance the customer experience in various businesses. In a few North American countries, retailers use smart carts with locator beacons, pin-sized cameras installed near shelves, or the store's Wi-Fi network to determine the footfall in the store, provide directions to a specific product section, and check key areas visited by customers. This process can also provide basic demographic data for parameters such as gender and age.
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Wal-Mart, Costco, Kroger, The Home Depot, and Target have their origin in North America. The amount of data generated by stores surges with the rise in sales. Without implementing analytics solutions, it becomes difficult to manage such vast data that include records, behaviors, etc., of all customers. Players such as Euclid Analytics offer spatial analytics platforms for retailers operating offline to help them track customer traffic, loyalty, and other indicators associated with customer visits. Euclid's solutions include preconfigured sensors connected to switches that are linked through a network. These sensors can detect customer calls from devices that have Wi-Fi turned on. Additionally, IBM's Sterling Store Engagement solution provides a real-time view of store inventory, and order data through an intuitive user interface that can be accessed by store owners from counters and mobile devices.
Heavy investments in healthcare sectors, advancements in technologies to help manage a large number of medical records, and the use of Big Data analytics to efficiently predict at-risk patients and create effective treatment plans are further contributing to the growth of the predictive analytics market in North America. Predictive analytics helps assess patterns in a patients' medical records, thereby allowing healthcare professionals to develop effective treatment plans to Improve outcomes. During the COVID-19 pandemic, healthcare predictive analytics solutions helped provide hospitals with insightful predictions of the number of hospitalizations for various treatments, which significantly helped them deal with the influx of a large number of patients. However, the high costs of installation and a shortage of skilled workers may limit the use of predictive analytics solutions in, both, the retail and healthcare sectors.
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Objectives: To quantify geographic variation in home health expenditures per Medicare home health beneficiary and investigate factors associated with this variation.
Study Design: Retrospective study design analyzing US counties in which at least 1 home health agency served 11 or more beneficiaries in 2016. Several sources of 2016 national public data were used.
Methods: The key variable is county-level Medicare home health expenditures per home health beneficiary. Counties were grouped into quintiles based on per-beneficiary expenditures. Analyses included calculation of coefficients of variation, computation of the ratio of 90th percentile to 10th percentile in expenditures, and linear regression predicting expenditure. The control variables included characteristics of patients, agencies, and communities.
Results: Significant variation in home health expenditures was identified across county quintiles, with a 90th-to-10th-percentile expenditure ratio of 2.5. The percentage of for-profit agencies in the lowest quintile was 15.7 compared with 81.7 in the highest quintile of spending. Unadjusted spending differed by $3864 (95% CI, $3793-$3936), compared with $3611 (95% CI, $3514-$3708) in the adjusted model, between counties in spending quintiles 1 and 5. Although state fixed effects explained nearly 20% of the variation in home health expenditures, 42% of the variation remained unexplained.
Conclusions: Home health care exhibits considerable unwarranted variation in per-patient expenditures across counties, signifying inefficiency and waste. Given the expected growth in home health demand, strategies to reduce unwarranted geographic variation are needed.
Am J Manag Care. 2022;28(7):322-328. https://doi.org/10.37765/ajmc.2022.89179
Existing research on home health expenditures uses home health data more than 2 decades old. US home health expenditures rose by 113% between 2000 and 2016, from $8.5 billion to $18.1 billion. The Medicare program has implemented several policies in the past decade to combat the growth in expenditures. This study finds the following:
Unwarranted variation in the utilization of health services, or variation not related to differences in patient needs or conditions, is pervasive across health care settings in the United States.1,2 Unwarranted variation in services typically leads to increased health care spending without a concomitant improvement in health care outcomes.3 Reducing unwarranted variation in health care services is necessary to Improve efficiency in both public and private health care delivery systems.4 Concerns over program inefficiency and variation in health care spending led to a 2013 Institute of Medicine (IOM) report that documented the extent of variation in service utilization and expenditures in Medicare. The IOM report found that at least 36% percent of variation in regional spending was unwarranted—not explained by differences in disease burden or severity among patients.1 The IOM report also raised serious concerns with services provided in postacute and long-term care settings, finding that variation in postacute care spending alone accounted for 73% of the total observed variation in Medicare spending.1
Home health care is a critical component of postacute and long-term care services in the United States, which, despite extensive variation, remains understudied.5,6 As of 2017, more than 12,000 Medicare-certified home health agencies participated in the program, delivering care to more than 3 million beneficiaries.7 The number of beneficiaries is expected to increase due to the aging US population and policy changes by CMS.8
Medicare home health expenditures increased 113% from $8.5 billion in 2000 to $18.1 billion in 2016 in part due to the implementation of Home Health Resource Groups (HHRG), a prospective payment system that replaced the Medicare fee-for-service (FFS) mechanism previously used to reimburse home health agencies.7 With the increasing number of participating home health agencies, beneficiaries served, and expenditures under HHRG, information describing the extent of variation in home health care is needed to help policy makers and other stakeholders identify potential reforms.
This study describes regional variation in US home health spending to better understand unwarranted variation. Additionally, the study seeks to identify the sources of variation in home health care spending to inform policy makers on strategies to reduce unwarranted variation.
The conceptual framework is based on the literature describing home health utilization, which is a function of patient, home health agency, and community characteristics. In addition to age and gender, evidence has shown that dual-eligible Medicare and Medicaid beneficiaries use more home health resources.9 The CMS Hierarchical Conditional Category (HCC) risk score, a score assigned to patients based on health status and health conditions, is associated with health care consumption and used to adjust payment for private insurance plans that cover Medicare beneficiaries under Medicare Part C.10 Agency characteristics include ownership type (for profit, not for profit, government) and whether market entry took place during the era of the HHRG prospective payment system implemented in 2000.11,12 The number of primary care physicians in the community affects coordination between physicians and home health professionals and the timeliness of care received.13 Competition among home health agencies, skilled nursing facilities, and hospitals also affects patient choice about the use of home health vs other long-term care services.14
Study Design and Study Sample
This is a retrospective study design that aggregated home health agency data at the county level to examine variation. Analysis of service variation commonly relies on specific geographic areas, such as hospital referral regions, health service areas, or counties.4 The county was used as the geographic unit for analysis because the majority of Medicare home health beneficiaries receive care from agencies in their home county.15 The study demo consists of all Medicare-certified home health agencies serving 11 or more beneficiaries in 2016 across all 50 states and the District of Columbia.
Data sources included the 2016 Medicare Provider Utilization and Payment Data files: the Public Use File Home Health Agencies (PUF HHA) file, the Provider of Services (POS) file, the Home Health Compare (HHC) file, and the Area Health Resources File (AHRF). The PUF HHA file contains agency-level information, including provider identification number, the total Medicare standard payment amount for beneficiaries who receive at least 5 home health visits during their episode of care (non–Low Utilization Payment Adjustment [non-LUPA] beneficiaries), and summarized characteristics of the beneficiaries per home health agency. These include the mean age of beneficiaries, the percentage of dual-eligible beneficiaries, and the mean HCC risk score for patients served. The HHC file provides the agency’s initial date of the contract with CMS and ownership type. The AHRF provides state and county Federal Information Processing Standards (FIPS) codes for each county and details for county-level community characteristics, such as the number of primary care physicians, nursing home beds, and long-term hospital beds. Medicare wage adjustment per county based on Social Security Administration (SSA) state and county codes are available in the Medicare Wage Adjustment files.
The dependent variable is county-level Medicare standard home health expenditure per home health beneficiary because it eliminates geographic factors incorporated by Medicare to adjust provider payment. Per-beneficiary payments were calculated by aggregating agency-level Medicare standard payment amounts at the county level as the numerator and agency-level unique Medicare non-LUPA home health beneficiaries as the denominator.
Quintiles of county-level spending per Medicare home health beneficiary and how quintile assignment relates to the characteristics of patients, providers, and the community are the key measures of interest. Home health agencies behave differently based on when they entered the market in relation to the implementation of HHRG in 2000, as profitable practices in the prospective payment system differed from those in the previous FFS payment system.9 Thus, a measure of tenure as the percentage of home health agencies entering the market before 2000 in each county is included. The percentages of agencies that were government owned and for profit per county, as well as an indicator of agencies operated as part of home care chains, were drawn from the POS file. A link between the wage adjustment file and the PUF HHA data set was created by utilizing a crosswalk between SSA and FIPS codes. For community characteristics, a county-level Herfindahl-Hirschman Index (HHI) of competition was calculated as the sum of the squared market share based on the number of home health beneficiaries served by each agency. Finally, the number of primary care physicians per 1000 population, the number of nursing home beds and long-term hospital beds per 1000 population, and county-level median household income were included at the county level.
Counties were divided into quintiles based on Medicare home health expenditures per home health beneficiary. Counties in quintile 1 had the lowest expenditures; those in quintile 5 had the highest. Additionally, the coefficient of variation (COV) and the ratio of the 90th to 10th percentile for all variables were used to analyze variation in expenditures within and across each quintile.
Ordinary least square regression models were used to assess factors associated with geographic variation in home health expenditure per home health beneficiary. The first model included only 4 dummy variables for counties in quintiles 2 to 5, with those in quintile 1 serving as the reference group. Each iteration of the model successively added patient, agency, and community characteristics. The changes in R2 in each subsequent model show how much variation in home health expenditure per beneficiary is explained by adding patient, agency, and community characteristics.
Counties in each quintile include state effects that influence expenditures. To estimate geographic variation resulting from state-level fixed effects, we excluded the dummy variable for quintiles and added patient, agency, and community characteristics successively and analyzed models with and without state-level fixed effects. Statistical analysis was conducted with Stata 14.2 (StataCorp).
The PUF HHA file contains information on 10,046 home health agencies that served 11 or more patients in the United States in 2016. A total of 1925 of 3141 counties in the United States had at least 1 agency in the PUF HHA file and were included in our analysis. Counties not included in the study were more likely to be rural, with lower population levels and lower median incomes.
Table 1 presents the mean of county-level Medicare home health expenditures per home health beneficiary and county-level patient, agency, and community characteristics of the study demo across quintiles of Medicare home health expenditure. On average, overall Medicare expenditures were $5050 per home health beneficiary, ranging from $3440 in quintile 1 to $7305 in quintile 5. The within-quintile 90th-to-10th-percentile ratio of expenditures was 2.5, and the same ratio for the HCC scores was 1.13. Approximately 30.4% of patients were dual-eligible Medicare and Medicaid beneficiaries, representing 25.8% of beneficiaries in quintile 1 vs 37.6% in quintile 5. Overall, non-White beneficiaries comprised 14.6% of the sample, but this ranged from 8.7% in quintile 1 to 22.5% in quintile 5. Agencies included in the study had an mean HCC score of 2.1. Across quintiles, agency HCC score ranged from a low of 2.0 in quintile 1 to a high of 2.2 in quintile 4. The majority (50.3%) of agencies in the study were for profit; 17.1% were government agencies. Major differences were observed across quintiles in agency ownership. Counties in quintile 1 had the lowest percentage of for-profit agencies (15.6%) but had the highest percentage of government-owned agencies (35.1%). Counties in quintile 5 had the highest percentage of for-profit agencies (81.6%) but the lowest percentage of government-owned agencies (6.7%). Overall, tenured agencies that entered the market before HHRG implementation made up approximately 40% of the study sample; they were 43.3% of agencies in quintile 1 and 34.0% of agencies in quintile 5. Overall, 22.5% of agencies in the demo operated as branches of home health chains, with the highest proportion of chain agencies in quintile 5 (30.5%) and the lowest in quintile 1 (11.2%). Medicare wage adjustments were higher in lower quintiles, with quintile 1 at a wage adjustment of 0.90 and quintile 5 at 0.81. Counties in the study had an mean of 0.2 long-term hospital beds, 0.6 physicians, and 0.4 nursing beds per 1000 population. Median household income was $50,792, and the mean HHI score was 7146.
Figure 1 provides a visualization of the extent of variation in county-level home health expenditure per beneficiary by quintiles. Intraquintile variation was low, with quintiles 1 (COV = 0.1) and 5 (COV = 0.14) exhibiting the highest variation. However, the overall COV for mean expenditures per beneficiary in all study counties was 0.3, indicating substantial overall variation across quintiles. The overall 90th-to-10th-percentile ratio of 2.5 indicates that the 90th percentile mean expenditure is 2.5 times that of the 10th percentile. Figure 2 adds context to the results, identifying counties by quintile of per-patient expenditure by color on a map. The South, particularly Texas, Oklahoma, and Louisiana, has a higher concentration of high-expenditure counties. The New England and West Coast regions have higher concentrations of low-expenditure counties. Counties colored in gray were not included in the study due to a lack of eligible agencies for analysis.
Table 2 provides results from models adjusted for selected variables based on our conceptual framework. Coefficients are first presented in dollar spending for each quintile of per-patient expenditure in an unadjusted model and are then adjusted as we add patient, agency, and community characteristics (the results are available in eAppendix A [eAppendices available at ajmc.com]). In the unadjusted model, unexplained spending differences ranged from $758.28 (95% CI, $686.83-$829.73) between quintiles 1 and 2 up to $3864.70 (95% CI, $3793.25-$3936.16) between quintiles 1 and 5, with an R2 of 0.87; R2 remained unchanged after adding beneficiary, agency, and community characteristics to the model.
State policies and other characteristics likely influence expenditures for home health at the county level. To estimate state effects on variation, we excluded dummy variables for county quintiles and applied the models with and without state fixed effects (Table 3). The R2 between models with (0.50) and without (0.16) state fixed effects changed to 0.58 and 0.39 once agency and community characteristics were added, representing a percent difference reduction from 212.5% to 48.7%. However, the full model with state fixed effects explained only 58% of the variation (the results are available in eAppendix B).
The IOM report on spending variation identified postacute care as the primary driver of spending inefficiency in Medicare, with postacute care accounting for approximately 70% of the variation in patient-level Medicare spending. The home health industry is an integral component of postacute care for Medicare beneficiaries and provides services to 3.5 million beneficiaries annually through more than 12,000 contracted home health agencies. This study provides new information on the extent of spending variation that exists among home health beneficiaries. A prior study suggested that the source of variation in home health services utilization stems from differences in organizational behavior, local resources, or Medicaid factors,16 but in the present study, these measures had a marginal impact on explaining variation. Excluding the 3 states with the highest rates of variation (Texas, Oklahoma, and Louisiana) resulted in a drop in the 90th-to-10th-percentile ratio from 2.5 to 2.0, indicating persistent unexplained variation. And although these 3 high-utilization states opted not to expand Medicaid, a sensitivity analysis exploring the possible impact of Medicaid expansion on home health utilization showed that Medicaid expansion status was not statistically significant in state-level fixed effects or random effects models. After adjusting for patient, agency, and community factors, a difference of more than $2500 remained between per-beneficiary home health expenditures in quintiles 1 and 5, and more than 40% of the variation remained unexplained by the models in the study, an indication of waste and inefficiency in the home health care delivery system.
Several characteristics of beneficiaries, physicians, and agencies likely contribute to this observed variation. To receive services, the Medicare Home Health Benefit requires beneficiaries to meet 3 criteria: being homebound, requiring intermitted skilled care, and receiving a physician referral through a face-to-face encounter assessment.17 Beneficiaries bear no cost sharing and can receive unlimited 60-day episodes of home health care with physician recertification.17 Without beneficiaries sharing financial responsibility for episodes of home health care, cost does not influence beneficiary decision-making about whether another episode of care is needed, what actions they can take themselves to Improve their conditions, and what home health providers can do for them.
Although physicians are required to conduct a face-to-face assessment in order to refer their patients for home health care,18 latest evidence shows that the majority of physicians spend less than 1 to 2 minutes completing the referral form, do not change the referral form once home health professionals submit the renewal certification, and fail to ask home health professionals to clarify any information in the form.13 This physician certification mechanism leaves room for home health agencies to induce unnecessary demand.
At the agency level, home health agencies require only small capital assets to enter and operate in the market and can easily adjust operating systems to maximize profit margins.19 Cabin and colleagues found that for-profit agencies were more costly but provided lower quality of care compared with not-for-profit agencies.11 Under the HHRG, Kim and Norton also found that for-profit agencies that entered the market after 2000 were more financially incentivized to provide therapy visits that yielded high margins than agencies established before the HHRG implementation.12 The success of these new market entrants influenced for-profit peers to adopt similar practice patterns and pursue profitable therapy visits. In addition to for-profit agencies and peer effects, medical fraud is an issue in the home health industry. According to a report by the US Government Accountability Office, home health agencies exhibited the highest rate of medical fraud among all types of health care providers, accounting for more than 40% of medical fraud in the nation in 2010. Although fraud may contribute to unwarranted variation,20 it is not a major source of variation in health care delivery identified by the IOM.1
There are limitations to the study. First, the study analyses rely on data from just 1925 of 3141 US counties due to limitations in the PUF HHA file, which suppresses agencies providing services to 10 or fewer patients in the calendar year. Should the behavior of agencies in counties excluded be different from that of those in our study, our results would not generalize to them. Second, our data include only patient risk factors for gender, race, age, dual eligibility, and CMS HCC score. Other health and social risk factors, such as measures of activities of daily living and the capability and availability of informal caregivers, may affect how often home health professionals visit their patients,21,22 for which our models could not control. Finally, the county, based on the location of the home health agencies, is our geographic unit of measurement. Although the majority of beneficiaries seek care from home health agencies located in their residential county,15 our data do not allow us to distinguish expenditures at the patient level, and some beneficiary spending will be captured in the county of the home health agency rather than their county of residence.
Despite these limitations, our findings have policy implications. First, the Medicare program is a primary payer of home health for older patients and has the purchasing power to set payment rates. However, states regulate the home health market, which influences agency practice patterns. For example, states with certificate-of-need regulations consume less home health care and have lower growth in home health expenditures than those without.23,24 Findings from this study indicate a large effect of state regulatory policies and characteristics on overall spending, with approximately 20% of the observed variation attributable to state fixed effects. These findings indicate that the Medicare program should work with states to address geographic variation through market regulation.
Second, although face-to-face physician assessment encounters are required by policy, evidence in the literature indicates that the physician referral system should be strengthened, either through incentivizing physicians to perform more meaningful assessments or through assignment of legal responsibility to physicians to certify the referral process. Finally, for individual beneficiaries, increasing cost-consciousness through co-pays when accessing the Medicare Home Health Benefit—as recommended by the Medicare Payment Advisory Commission to CMS25—could reduce unnecessary preference-sensitive home health care utilization.
The demand for home health care is expected to continue to grow, given both the preference to stay home and the changing demographics of the country.26 Reducing unwarranted variation is key to strengthening the Medicare home health care benefit. In 2020, CMS implemented a new payment system, the Patient Driven Groupings Model, which eliminates the number of therapy visits from the payment equation.7 We recommend strengthening the physician referral system, adding co-pays for each episode of home health care, and improving collaboration between states and the Medicare program to ensure that the home health care delivery system provides sustainable, efficient, high-quality care to beneficiaries in need.
Author Affiliations: Department of Health Policy and Management, College of Public Health, University of Arkansas for Medical Sciences (RFS, ALML, HFC, JMT), Little Rock, AR.
Source of Funding: None.
Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (RFS, HFC, JMT); acquisition of data (RFS); analysis and interpretation of data (RFS, HFC, JMT); drafting of the manuscript (RFS, ALML, HFC, JMT); critical revision of the manuscript for important intellectual content (RFS, ALML, HFC, JMT); statistical analysis (RFS, HFC); administrative, technical, or logistic support (ALML, JMT); and supervision (HFC, JMT).
Address Correspondence to: Robert F. Schuldt, PhD, University of Arkansas for Medical Sciences, 4301 W Markham St, Little Rock, AR 72205. Email: Rfschuldt@uams.edu.
1. Institute of Medicine. Variation in Health Care Spending: Target Decision Making, Not Geography. The National Academies Press; 2013. doi:10.17226/18393
2. Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder EL. The implications of regional variations in Medicare spending. part 1: the content, quality, and accessibility of care. Ann Intern Med. 2003;138(4):273-287. doi:10.7326/0003-4819-138-4-200302180-00006
3. Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder EL. The implications of regional variations in Medicare spending. part 2: health outcomes and satisfaction with care. Ann Intern Med. 2003;138(4):288-298. doi:10.7326/0003-4819-138-4-200302180-00007
4. Wennberg JE. Tracking Medicine: A Researcher’s Quest to Understand Health Care. Oxford University Press; 2010.
5. Talaga SR. Medicare home health benefit primer: benefit basics and issues. Federation of American Scientists. March 14, 2013. Accessed January 10, 2020. https://fas.org/sgp/crs/misc/R42998.pdf
6. Newquist DD, DeLiema M, Wilber KH. Beware of data gaps in home care research: the streetlight effect and its implications for policy making on long-term services and supports. Med Care Res Rev. 2015;72(5):622-640. doi:10.1177/1077558715588437
7. Medicare Payment Advisory Commission. Home health care services. In: Report to the Congress: Medicare Payment Policy. Medicare Payment Advisory Commission; 2019:225-248. Accessed December 4, 2019.
8. Knickman JR, Snell EK. The 2030 problem: caring for aging baby boomers. Health Serv Res. 2002;37(4):849-884. doi:10.1034/j.1600-0560.2002.56.x
9. Joynt Maddox KE, Chen LM, Zuckerman R, Epstein AM. Association between race, neighborhood, and Medicaid enrollment and outcomes in Medicare home health care. J Am Geriatr Soc. 2018;66(2):239-246. doi:10.1111/jgs.15082
10. Pope GC, Ellis RP, Ash AS, et al. Diagnostic cost group hierarchical condition category models for Medicare risk adjustment. CMS. December 21, 2000. Accessed March 13, 2020. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Reports/downloads/pope_2000_2.pdf
11. Cabin W, Himmelstein DU, Siman ML, Woolhandler S. For-profit Medicare home health agencies’ costs appear higher and quality appears lower compared to nonprofit agencies. Health Aff (Millwood). 2014;33(8):1460-1465. doi:10.1377/hlthaff.2014.0307
12. Kim H, Norton EC. Practice patterns among entrants and incumbents in the home health market after the prospective payment system was implemented. Health Econ. 2015;24(suppl 1):118-131. doi:10.1002/hec.3147
13. Boyd CM, Leff B, Bellantoni J, et al. Interactions between physicians and skilled home health care agencies in the certification of Medicare beneficiaries’ plans of care: results of a nationally representative survey. Ann Intern Med. 2018;168(10):695-701. doi:10.7326/M17-2219
14. Li Q, Rahman M, Gozalo P, Keohane LM, Gold MR, Trivedi AN. Regional variations: the use of hospitals, home health, and skilled nursing in traditional Medicare and Medicare Advantage. Health Aff (Millwood). 2018;37(8):1274-1281. doi:10.1377/hlthaff.2018.0147
15. Franco SJ. Medicare home health care in rural America. Policy Anal Brief W Ser. 2004;(1):1-4.
16. Welch HG, Wennberg DE, Welch WP. The use of Medicare home health care services. N Engl J Med. 1996;335(5):324-329. doi:10.1056/NEJM199608013350506
17. Medicare & home health care. CMS. Updated September 2020. Accessed November 9, 2021. https://www.medicare.gov/Pubs/pdf/10969-Medicare-and-Home-Health-Care.pdf
18. Patient Protection and Affordable Care Act, Pub L No. 111-148 (2010) Sec. 6407. Accessed March 13, 2020. https://www.congress.gov/111/plaws/publ148/PLAW-111publ148.pdf
19. Medicare Payment Advisory Commission. Home health services. In: Report to the Congress: Medicare Payment Policy. Medicare Payment Advisory Commission; 2011:173-199. Accessed January 10, 2020. https://www.medpac.gov/wp-content/uploads/import_data/scrape_files/docs/default-source/reports/Mar11_Ch08.pdf
20. Health care fraud: types of providers involved in Medicare, Medicaid, and the Children’s Health Insurance Program cases. US Government Accountability Office. September 2012. Accessed March 13, 2020. https://www.gao.gov/assets/650/647849.pdf
21. Osakwe ZT, Larson E, Andrews H, Shang J. Activities of daily living of home healthcare patients. Home Healthc Now. 2019;37(3):165-173. doi:10.1097/NHH.0000000000000736
22. Cho E, Kim EY, Lee NJ. Effects of informal caregivers on function of older adults in home health care. West J Nurs Res. 2013;35(1):57-75. doi:10.1177/0193945911402847
23. Polsky D, David G, Yang J, Kinosian B, Werner R. The effect of entry regulation in the health care sector: the case of home health. J Public Econ. 2014;110:1-14. doi:10.1016/j.jpubeco.2013.11.003
24. Rahman M, Galarraga O, Zinn JS, Grabowski DC, Mor V. The impact of certificate-of-need laws on nursing home and home health care expenditures. Med Care Res Rev. 2016;73(1):85-105. doi:10.1177/1077558715597161
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26. Fixing to stay: a national survey on housing and home modification issues. AARP. May 2000. Accessed March 22, 2019. https://assets.aarp.org/rgcenter/il/home_mod.pdf
CHICAGO, July 29, 2022 /PRNewswire/ -- Home Healthcare Market size is projected to reach USD 298.2 billion by 2026 from USD 198.9 billion in 2021, at a CAGR of 8.4% during the forecast period, according to a new report by MarketsandMarkets™. The rapid growth in the elderly population, the rising incidence of chronic diseases, the growing need for cost-effective healthcare delivery due to the increasing healthcare costs, and technological advancements of home care devices are the major factors driving the growth of this market.
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Rapid growth in the elderly population and the rising incidence of chronic diseases;
According to the UN Department of Economic and Social Affairs, there were 703 million people aged 65 years and over globally in 2019; this number is projected to reach 1.5 billion by 2050. Additionally, the number of people aged 80 and over is projected to triple from 143 million in 2019 to 426 million by 2050.
The growth of this population segment will boost the demand for healthcare and greatly increase the burden on governments and health systems as the aging population is more prone to chronic diseases. This will prove favorable to the market for home healthcare. Home healthcare reduces unnecessary hospital admissions & readmissions and the time and costs involved in traveling to meet healthcare professionals.
Chronic illness is a long-lasting condition that can be controlled but not cured. Treating and managing chronic illnesses has become a major concern. Approximately 50% of all home healthcare patients have at least one chronic illness, and this number is expected to keep increasing in the future. Chronic diseases, which affect older adults disproportionately, contribute to disabilities, diminish the quality of life, and increase long-term care costs, thus opening an array of opportunities for various home healthcare companies.
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Based on products, the home healthcare market is segmented into testing, screening, and monitoring products; therapeutic products; and mobility care products. In 2020, the therapeutic segment accounted for the largest share of the home healthcare products market. The heightened prevalence of chronic ailments, such as kidney failure, respiratory diseases, diabetes, and cancer, has increased the demand for home healthcare therapeutic equipment.
Based on service, the home healthcare market is categorized into skilled nursing services, rehabilitation therapy services, hospice & palliative care services, unskilled care services, respiratory therapy services, infusion therapy services, and pregnancy care services. Skilled nursing services accounted for the largest share of the market in 2020. Skilled medical care in home settings can provide a comforting solution over residing in a hospital, nursing home, or an assisted living community. The favorable insurance coverage for skilled nursing services is expected to support the growth of this market during the forecast period.
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North America was the largest regional market for the home healthcare market in 2020
The global home healthcare market is segmented into North America (the US and Canada), Europe (Germany, the UK, France, Italy, Spain, and the Rest of Europe), Asia Pacific (Japan, China, India, and the Rest of Asia Pacific), and the Rest of the World. In 2020, North America dominated the global market, followed by Europe. The large share of North America in the global market is attributed to the rising prevalence of chronic conditions, high healthcare expenditure, high disposable income, the increasing overall geriatric population, high disposable income, and superior healthcare infrastructure. However, the Asia Pacific market is estimated to grow at the highest CAGR during the forecast period. Growth in the Asia Pacific home healthcare market is driven primarily by the rising aging population, high incidence of chronic diseases, rising disposable income, technological advancements, government initiatives to promote home healthcare, and increasing healthcare costs.
The global home healthcare market is highly fragmented. The prominent players in the overall market include Fresenius SE & Co. KGaA (Germany), GE Healthcare (US), Linde plc (Ireland), F. Hoffmann-La Roche Ltd (Switzerland), A&D Company (Japan), BAYADA Home Health Care (US), Invacare Corporation (US), Abbott (US), Amedisys (US), ResMed (US), LHC Group, Inc. (US), OMRON Corporation (Japan), Koninklijke Philips N.V. (Netherlands), Drive DeVilbiss Healthcare (US), Hamilton Medical (Switzerland), Sunrise Medical (Germany), Roma Medical (UK), Caremax Rehabilitation Equipment Co., Ltd(China), Vitalograph (UK), Advita Pflegedienst GmbH (Germany), RENAFAN GmbH (Germany), ADMR (France), Apex Medical Corporation (Taiwan), CONTEC MEDICAL SYSTEMS CO., LTD (China), and Löwenstein Medical Technology GmbH + Co. KG. (Germany).
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Canada’s urgent healthcare worker shortage may be due in part to the lack of accurate data about internationally educated healthcare professionals who have moved here.
World Education Services, a nonprofit organization that provides credential evaluations for international students and immigrants planning to study or work in Canada and the U.S., says there are gaping holes in the data collected and shared about newcomers who were healthcare practitioners in their home countries.
Though current data shows nearly half (47 per cent) of internationally trained healthcare professionals are either underemployed or underutilized, a latest WES policy brief suggests the scope of the problem might be far larger.
“We simply don’t know how many IEHPs are in the country…how many successfully re-enter their careers, or how long it takes them to become licensed,” the brief, released this past March, states. Read the full brief here: https://knowledge.wes.org/rs/317-CTM-316/images/canada-report-addressing-the-underutilization-of-iehps-in-canada.pdf?mkt_tok=MzE3LUNUTS0zMTYAAAGFB3PRvdtyykbb7B4FIQXaKpJJ4gs1L9Gup0Bq4JL4hPeKocygdUvLfg8B_7Fj_hB0VrdQ6vishVMnN6eYDNhGP39axBHVi76sWD0C7VCbWm-aWQ
Caroline Ewen, co-author of the report, says Canada lacks a pan-Canadian, comprehensive data collection and sharing system about internationally educated health professionals.
“The different sources of data need to be linked effectively, and they need to be connected and speak to each other to inform an accurate picture,” she told New Canadian Media. “Right now … all sorts of different agencies and organizations are collecting small pieces, but they aren’t linked in a comprehensive way.”
This has led to alarming discrepancies between data collected at the federal and provincial governmental and non-governmental levels about the potential talent pool that actually exists. That’s an even bigger problem now, given the shortage of healthcare workers plaguing the country.
Having accurate data “underscores pretty much anything you would do if you want to make evidence-based decisions,” says Ewen, who is also WES’ manager of policy and advocacy.
“You need to be working from an accurate base of evidence, and right now we don’t have that to gauge the effectiveness of policies or programmatic interventions.”
Accurate data also affects budgeting and funding decisions, adds Joan Atlin, WES’ director of strategy, policy and research and a second co-author.
“In order to do a proper cost-benefit analysis and design and invest in the right solutions, we need accurate data,” Atlin says. “Without it, we can’t budget for and invest in solutions at the appropriate scale.”
Immigration, Refugees and Citizenship Canada (IRCC) is one of the main federal agencies that collects data on newcomers’ intended occupations. Between 2015 and 2020, more than 24,500 healthcare professionals entered Canada and became permanent residents, IRCC says.
But that number only includes people who declared their intended occupation at the time of arrival. Since IRCC doesn’t collect that data systematically for all immigration streams, “other data sources tell a very different story about the size of the potential talent pool,” WES’ briefing note says.
For instance, in 2019, IRCC reported only 205 new permanent residents in Ontario declared nursing as their intended occupation.
However, the College of Nurses of Ontario (CNO) – an independent regulator created through provincial legislation – reported 4,500 new internationally educated nurses were pursuing professional registration that year alone – out of a total of more than 14,000 who are trying to get accredited for work.
The discrepancy, the brief explains, could be due to the fact that many of those nurses arrived as temporary workers (including through the caregiver immigration pathway). However, this is difficult to ascertain, says Ewen, as IRCC does not collect the educational qualifications of temporary workers or residents in a systematic way.
Additionally, Atlin says, data collected about the intended occupation of permanent residents is self-declared. Some people may opt not to declare if they believe it will negatively impact their immigration applications, thereby potentially blurring the actual figure.
In an emailed statement, IRCC spokesperson Rémi Larivière said “the number of permanent residents in any given year who declare an intended occupation is not directly comparable to the number of foreign nationals pursuing accreditation in the same occupation in Canada.”
The main difference, as per the email, is that the former is derived solely from the declaration on the permanent resident application, while the latter comes from “the full range of programs and pathways, including as students, temporary workers, sponsored family members, refugees, protected persons, etc.”
Gaps also exist in the College of Nurses of Ontario data, Ewen says. For instance, though the CNO reports to the Fairness Commissioner on fair registration practices, it doesn’t “clarify when those 14,000 began the registration process.”
Kristi Green, a CNO spokesperson, said in an emailed statement that the College registers nurses “who have the skills and competencies…to practice safely, whether they are educated in Canada or abroad.”
Additionally, she says, the College shares reports on their website and with “other organizations,” including “partners in the healthcare system,” though it does not have a data-sharing agreement with IRCC.
She says part of the College’s efforts to make its data available and transparent “includes looking at new-to-us organizations that might benefit from specific CNO expertise in this area.”
“What we have direct line of sight on is the number of applications open with CNO to seek registration in Ontario,” she wrote, adding that “you do not need to be living (in) Ontario or Canada when you apply.”
She also said the College is modernizing its registration practices, which included launching the Supervised Practice Experience Partnership (SPEP) earlier this year with Ontario Health.
The program provides current applicants registering to become nurses an opportunity to participate in a work experience to help complete evidence of practice and language proficiency requirements.
The WES brief recommends collecting educational background and intended occupation for all classes of immigrants, including those who transition from temporary work/study permit to permanent residence or citizenship status. It also recommends standardizing reporting processes for occupational regulatory bodies.
Ewen says a government or at-arms-length government agency should be the “main player…coordinating and implementing a data strategy.”
The idea is “having government oversight towards a centralized body that can actually design and implement an actual strategy for how all these different pieces could be interconnected, and bring together the different players who are already doing this in very disparate ways,” she says.
This echoes recommendations from a separate study earlier this year looking at Canada’s ethical obligations of recruiting IEHPs. The study found “Canada has neglected health workforce planning issues and lacks basic information” about the supply, demand and diversity of its workforce, and suggested improving the “quality and co-ordination of data collection and utilization through enhanced Federal government oversight.” Read the fully study here: https://journals.sagepub.com/doi/full/10.1177/08404704221095129
Atlin says until the system can offer IEHPs “a pathway back to their profession,” it will only continue “creating problems rather than solving” them.
In April, the Canadian Medical Association and Canadian Nursing Association sent a briefing to the House of Commons Standing Committee on Health identifying the creation of a Data and a National Workforce Agency as one of eight policy pillars to alleviate the health human resources crisis. This included committing $50 million over four years to first enhance health workforce data standardization and collection processes across provinces and territories.
The Canadian Health Workforce Network has also made a call to action “for better planning, better care and better work through better data.” Seventy experts have signed on behalf of a professional medical organization, and an additional 326 medical experts have signed on as individuals.
“I think the desperation of a shortage right now, and the understanding that a program here and a program there and a little investment here and a regulatory tweak there is not going to solve this problem,” Ewen stresses. “It needs to be a holistic, systematic, systemic solution.”
Fernando Arce, Local Journalism Initiative Reporter, New Canadian Media
Again this year, a report on maternal mortality details how complex societal issues of rampant obesity, health inequity and the opioid epidemic play roles in keeping Missouri's pregnancy-associated mortality rates high.
The annual Missouri Pregnancy-Associated Mortality Review Board's report, using data from 2017-19, found 75 percent of pregnancy-related deaths were preventable. And, all pregnancy-related deaths due to mental health conditions were determined to be preventable.
By law, the Missouri Department of Health and Senior Services (DHSS) is required to submit a report to the board, which is tasked with looking at the causes and contributing factors associated with maternal mortality and with determining interventions that could prevent the deaths. The report may be viewed at https://health.mo.gov/data/pamr/pdf/2019-annual-report.pdf.
The board looks at demographic factors, including age, race and educational attainment. The board evaluates places of residence, health care insurance coverage, and body mass index. It keeps in mind that correlation does not equal causation, but comparing ratios helps "determine the degree of disparity in health outcomes between each group," the report states.
The report looked at circumstances surrounding 185 women during the time period, who died while pregnant, or within one year of pregnancy. The average was 61 Missouri women who died each of the years. The highest number recorded was 68 in 2018.
The report cautions that the numbers used represent a small portion of the population, thus there is an increased likelihood of results being "Skewed." and some effects may be exaggerated, while others remain hidden. The report also offers a three-year ratio may prevent "skewness."
"While it is vital to analyze these deaths on a yearly basis," the report executive summary states, "the goal of this multi-year report is to provide a more comprehensive representation of maternal mortality in the state."
Among the board's key findings were:
• The greatest proportion of pregnancy-related deaths occurred between 43 days and one year after pregnancy, mental health conditions were the leading cause of pregnancy-related deaths (followed by cardiovascular disease).
• The most common means of fatal injury for pregnancy-related deaths was overdose/poisoning.
• Substance use disorder contributed to 32.7 percent of pregnancy-related deaths.
Seventy percent of deaths were pregnancy-associated, not related (meaning they occurred from any cause during or within one year of pregnancy). The most common cause was poisoning/overdose (33.9 percent), followed by motor vehicle collisions (30.4 percent). The report states substance use disorder contributed to 44.4 percent of pregnancy-associated, not related deaths.
The review board's report recommended four steps the Missouri Legislature could take to lower the amount of maternal mortality.
It recommended the lawmaking body provide funding for a perinatal quality collaborative by 2023. Multiple states have these networks of teams who work together to Improve the quality of care for mothers and babies. Several states participate in multi-state networks. For example, California uses a "mentor model" in which 20 pairs of nurse-and-physician mentors, experienced in quality improvement, supported and mentored six-eight hospitals.
The Legislature should establish and fund a statewide prenatal psychiatry access program to aid health care providers in providing evidence-based mental health care including substance use disorder treatment to Missouri women.
It should extend Medicaid coverage to one year postpartum for all conditions (including medical, mental health and substance use disorder), even if the woman did not start treatment prior to delivery. This would help women whose condition is exacerbated by the postpartum period, according to the report.
The report recommends health care providers receive ongoing education regarding screening, referral and treatment of mental health conditions, substance use disorder and cardiovascular disorders during and after pregnancy.
Providers should also perform a full assessment for depression and anxiety, using standardized and validated tools at least once during the perinatal period (as a baseline), once during the comprehensive postpartum visit (and add additional screenings as indicated). Providers should do likewise for substance use disorder. They should make referrals to behavioral health professionals, social workers, community health workers and treatment programs as appropriate, according to the report.
All health care workers should complete trauma-informed care training and implicit bias training at least annually.
The fax is dead. Long live the online fax?
A new study suggests many healthcare professionals believe that flaws in today’s web security landscape are prompting a return to what’s been deemed an “extremely” secure medium: fax.
Published earlier this month, eFax research surveyed 1,000 IT and business decision-makers in the UK and Europe.
According to the report (PDF), 62% of respondents in the healthcare sector said that security was the major reason for a “migration” to cloud-based fax systems, and 21% of those surveyed believe that digital fax systems are “extremely” secure.
Cloud faxing removes the need for on-premise equipment on both sides of a transmission. The gist is that users can send a fax quickly, via an online service, to be viewed and/or printed by the recipient.
Among fax users in healthcare, 37% of respondents said they use “cloud-based fax” systems, while 21% use both cloud and traditional faxing.
The research is the work of eFax, a company that uses the slogan: “The fast & easy way to send and receive faxes by email”.
It’s interesting, then, that the company’s own research says: “One of the main problems with email is its increasing vulnerability to interception, hacking, and fraud.”
“eFax is an internet fax service that eliminates the need for a fax machine, extra fax line, and all the associated expenses,” the company says. “Get a real local or toll-free fax number to send and receive faxes as email attachments. Online faxing is more reliable, secure, and convenient than analog fax machines.”
When you send a test eFax ‘fax’, you receive an ‘incoming’ fax email with a PDF attached. Faxes can be sent to a phone number or online assignment number and can be accessed via email, the eFax portal, mobile app, or a standard fax machine.
Overall, a third of respondents (37%) said fax usage was likely to increase in the future – but 35% also said there might be a decrease.
However, while eFax appears to be trying to separate email and fax security, the line between what can be considered a fax message, or just an email, has been blurred.
Traditional fax machines were considered secure in the past as they were ‘dumb’, internet connections were dial-up or nothing, and contained limited, analog functionality.
But the moment you connect a fax ‘number’ to a digital channel – whether this is an online portal accessed through a browser, email account, or app – there is always a risk of compromise.
When the study was published, Scott Wilson, vice president of sales and service at eFax, commented:
It’s clear that email is the established and widely accepted format for most communications, but it’s flawed and vulnerable to interception and hacking. Cloud faxing is more secure than email not least because fax infrastructure has limited exposure to the internet and internet-connected devices.
Using a fax number to send a message rather than an email address might not be traceable to a specific company department or user, and so could mitigate the risk of targeted attacks.
Sending a document directly to a physical fax machine, too, might have some perceived advantages – but it does not take away the risks of its underlying, digital infrastructure.
When asked by The Daily Swig how eFax differs from standard email, and what security or encryption measures are in place, the eFax did not respond. (The firm’s help center, however, does mention TLS and some form of encryption.)
Simon Mullis, CTO of Venari Security, commented: “Cloud-based fax systems are a resourceful way to ensure the secure communication of confidential information, but for most encryption will be king.
“With 25% of healthcare organizations saying they rely on email encrypted software, it’s important to recognize the role of end-to-end encryption in ensuring higher levels of security and privacy, while also remaining compliant of regulations like GDPR.”
Cloud fax services can be quicker, cheaper, and more convenient for businesses that don’t want to rely on analog lines. However, the jury’s out on whether digital ‘faxes’ are any more, or less, secure than email – especially when both would depend on the implementation of basic security measures such as end-to-end encryption.
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