Slides to accompany talk given by Dr Richard Sills on Wednesday 23rd September 2015 at the 63rd International Congress of Aviation and Space Medicine, held at Oxford University (UK).
http://icasm2015.org/
For more information on Instant Medical History and adding Computer Patient Interviewing to Pilot Medical Assessments please visit MedicalHistory.com and contact Richard Sills at rosills1@gmail.com
'인공지능은 의료를 어떻게 혁신하는가' 주제의 2017년 11월 버전입니다.
'How Artificial Intelligence would Innovate the medicine of the future'
최윤섭 소장 (최윤섭 디지털 헬스케어 연구소)
Yoon Sup Choi, PhD (Director/Founder, Digital Healthcare Institute)
yoonsup.choi@gmail.com
TreatmentMAP™
TreatmentMAP supports physicians in optimizing their treatment decisions, even for cancer patients in advanced stages of cancer, or when all of the standard treatment options for a patient have been exhausted.
Big Data, CEP and IoT : Redefining Holistic Healthcare Information Systems an...Tauseef Naquishbandi
Healthcare industry has been a significant area for innovative application of various technologies over decades. Being an area of social relevance governmental spending on healthcare have always been on the rise over the years. Event Processing (CEP) has been in use for many years for situational awareness and response generation. Computing technologies have played an important role in improvising several aspects of healthcare. Recently emergent technology paradigms of Big Data, Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with pain areas of healthcare domain but also to redefine healthcare offerings. This paper aims to lay the groundwork for a healthcare system which builds upon integration of Big Data, CEP and IoT.
'인공지능은 의료를 어떻게 혁신하는가' 주제의 2017년 11월 버전입니다.
'How Artificial Intelligence would Innovate the medicine of the future'
최윤섭 소장 (최윤섭 디지털 헬스케어 연구소)
Yoon Sup Choi, PhD (Director/Founder, Digital Healthcare Institute)
yoonsup.choi@gmail.com
TreatmentMAP™
TreatmentMAP supports physicians in optimizing their treatment decisions, even for cancer patients in advanced stages of cancer, or when all of the standard treatment options for a patient have been exhausted.
Big Data, CEP and IoT : Redefining Holistic Healthcare Information Systems an...Tauseef Naquishbandi
Healthcare industry has been a significant area for innovative application of various technologies over decades. Being an area of social relevance governmental spending on healthcare have always been on the rise over the years. Event Processing (CEP) has been in use for many years for situational awareness and response generation. Computing technologies have played an important role in improvising several aspects of healthcare. Recently emergent technology paradigms of Big Data, Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with pain areas of healthcare domain but also to redefine healthcare offerings. This paper aims to lay the groundwork for a healthcare system which builds upon integration of Big Data, CEP and IoT.
Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games – tasks which would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in healthcare. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades – and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome. Tarun Jaiswal | Sushma Jaiswal ""Deep Learning in Medicine"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23641.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/23641/deep-learning-in-medicine/tarun-jaiswal
HEC 2016 Panel: Putting User-Generated Data in Action: Improving Interpretabi...Pei-Yun Sabrina Hsueh
Chair/Moderator: Pei-Yun Sabrina HSUEH, PhD (IBM T.J. Watson Research Center)
Panelists: XinXin ZHU, Bian YANG, Ying-Kuen CHEUNG , Thomas WETTER, and Sanjoy DEY
a IBM T.J. Watson Research Center, USA
b Norwegian University of Science and Technology, Norway
c Mailman School of Public health, Columbia University, USA
d, Department of Biomedical Informatics, University of Washington, USA
e Department of Medical Informatics, University of Heidelberg, Germany
The rise of consumer health awareness and the recent advent of personal health management tools (including mobile and health wearable devices) have contributed to another shift transforming the healthcare landscape. Despite the rise of health consumers, the impact of user-generated health data remains to be validated. In fact, many applications are hinged on the interpretability issues of this sort of data. The aim of this panel is two-fold. First, this panel aims to review the key dimensions in the interpretability, spanning from quality and reliability to information security and trust management. Secondly, since similar issues and methodologies have been proposed in different application areas ranging from clinical decision support to behavioral interventions and clinical trials, the panelists will also discuss both the success stories and the areas that fall short. The opportunities and barriers identified can then serve as guidelines or action items individuals can bring to their organizations to further improve the interpretability of user-generated data.
The reality of moving towards precision medicineElia Stupka
How do we move towards precision medicine? How can we deliver on the big data in health promise? Who will be the enablers and players? Pharma, Big Tech, or newcomers?
Presentation at Social & Healthcare ICT Conference organized by The Association of Finnish Local and Regional Authorities, about Artificial Intelligence in pharmacology, clinical diagnosis, intensive care, hospital ward, assisted living and home care.
Presented at the 9th Thailand Pharmacy Congress: Smart Aging Life & Digital Pharmacy 4.0, The Pharmaceutical Association of Thailand under Royal Patronage on November 18, 2017.
Introduction to Health Informatics and Health Information Technology (Part 1)...Nawanan Theera-Ampornpunt
Presented at the Health Informatics and Health Information Technology Course, Doctor of Philosophy and Master of Science Programs in Data Science for Health Care (International Program), Faculty of Medicine Ramathibodi Hospital, Mahidol University on October 3, 2017
Big Data Analytics using in Healthcare Management Systemijtsrd
Big data is the new technology for healthcare management system. Present day's big data analytics are using in everywhere because of its good data management and its large storage capacity. In hospital managements the patients and doctors record keeping safe is the important role in healthcare system. In worldwide the big data method is extended use in the area of medicine and healthcare system. In this sector so many problems are there in implementing big data in healthcare system especially in relation to securities, privacy matters, standard records, good governance, managing of data, data storing and maintenance, etc. It is critical that these challenges to overcome before big data can be implemented successfully in healthcare. The amount of data being digitally collected and stored safely in big data Hadoop clusters. This paper introduces healthcare data, big data in healthcare systems, applications, advantages, issues of Big Data analytics in healthcare sector. Gagana H. S | Bhavani B. T | Gouthami H. S "Big Data Analytics using in Healthcare Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31014.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/31014/big-data-analytics-using-in-healthcare-management-system/gagana-h-s
The Present and Future of Personal Health Record and Artificial Intelligence ...Hyung Jin Choi
1. Why Personal Health Record and Artificial Intelligence ?
2. Obesity Example
3. Personal Health Record
1) Genetic Data
2) Electrical Health Records
3) National Healthcare Data
4) Medical Images
5) Sensor/Mobile Data
6) Data Integration
4. PHR+AI Applications
Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular variant of poker, learned the laws of physics from experimental data, and become experts in video games – tasks which would have been deemed impossible not too long ago. In parallel, the number of companies centered on applying complex data analysis to varying industries has exploded, and it is thus unsurprising that some analytic companies are turning attention to problems in healthcare. The purpose of this review is to explore what problems in medicine might benefit from such learning approaches and use examples from the literature to introduce basic concepts in machine learning. It is important to note that seemingly large enough medical data sets and adequate learning algorithms have been available for many decades – and yet, although there are thousands of papers applying machine learning algorithms to medical data, very few have contributed meaningfully to clinical care. This lack of impact stands in stark contrast to the enormous relevance of machine learning to many other industries. Thus part of my effort will be to identify what obstacles there may be to changing the practice of medicine through statistical learning approaches, and discuss how these might be overcome. Tarun Jaiswal | Sushma Jaiswal ""Deep Learning in Medicine"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23641.pdf
Paper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/23641/deep-learning-in-medicine/tarun-jaiswal
HEC 2016 Panel: Putting User-Generated Data in Action: Improving Interpretabi...Pei-Yun Sabrina Hsueh
Chair/Moderator: Pei-Yun Sabrina HSUEH, PhD (IBM T.J. Watson Research Center)
Panelists: XinXin ZHU, Bian YANG, Ying-Kuen CHEUNG , Thomas WETTER, and Sanjoy DEY
a IBM T.J. Watson Research Center, USA
b Norwegian University of Science and Technology, Norway
c Mailman School of Public health, Columbia University, USA
d, Department of Biomedical Informatics, University of Washington, USA
e Department of Medical Informatics, University of Heidelberg, Germany
The rise of consumer health awareness and the recent advent of personal health management tools (including mobile and health wearable devices) have contributed to another shift transforming the healthcare landscape. Despite the rise of health consumers, the impact of user-generated health data remains to be validated. In fact, many applications are hinged on the interpretability issues of this sort of data. The aim of this panel is two-fold. First, this panel aims to review the key dimensions in the interpretability, spanning from quality and reliability to information security and trust management. Secondly, since similar issues and methodologies have been proposed in different application areas ranging from clinical decision support to behavioral interventions and clinical trials, the panelists will also discuss both the success stories and the areas that fall short. The opportunities and barriers identified can then serve as guidelines or action items individuals can bring to their organizations to further improve the interpretability of user-generated data.
The reality of moving towards precision medicineElia Stupka
How do we move towards precision medicine? How can we deliver on the big data in health promise? Who will be the enablers and players? Pharma, Big Tech, or newcomers?
Presentation at Social & Healthcare ICT Conference organized by The Association of Finnish Local and Regional Authorities, about Artificial Intelligence in pharmacology, clinical diagnosis, intensive care, hospital ward, assisted living and home care.
Presented at the 9th Thailand Pharmacy Congress: Smart Aging Life & Digital Pharmacy 4.0, The Pharmaceutical Association of Thailand under Royal Patronage on November 18, 2017.
Introduction to Health Informatics and Health Information Technology (Part 1)...Nawanan Theera-Ampornpunt
Presented at the Health Informatics and Health Information Technology Course, Doctor of Philosophy and Master of Science Programs in Data Science for Health Care (International Program), Faculty of Medicine Ramathibodi Hospital, Mahidol University on October 3, 2017
Big Data Analytics using in Healthcare Management Systemijtsrd
Big data is the new technology for healthcare management system. Present day's big data analytics are using in everywhere because of its good data management and its large storage capacity. In hospital managements the patients and doctors record keeping safe is the important role in healthcare system. In worldwide the big data method is extended use in the area of medicine and healthcare system. In this sector so many problems are there in implementing big data in healthcare system especially in relation to securities, privacy matters, standard records, good governance, managing of data, data storing and maintenance, etc. It is critical that these challenges to overcome before big data can be implemented successfully in healthcare. The amount of data being digitally collected and stored safely in big data Hadoop clusters. This paper introduces healthcare data, big data in healthcare systems, applications, advantages, issues of Big Data analytics in healthcare sector. Gagana H. S | Bhavani B. T | Gouthami H. S "Big Data Analytics using in Healthcare Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31014.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/31014/big-data-analytics-using-in-healthcare-management-system/gagana-h-s
The Present and Future of Personal Health Record and Artificial Intelligence ...Hyung Jin Choi
1. Why Personal Health Record and Artificial Intelligence ?
2. Obesity Example
3. Personal Health Record
1) Genetic Data
2) Electrical Health Records
3) National Healthcare Data
4) Medical Images
5) Sensor/Mobile Data
6) Data Integration
4. PHR+AI Applications
Presentation "The Impact of All Data on Healthcare"
Keith Perry
Associate VP & Deputy CIO
UT MD Anderson Cancer Center
With continuing advancement in both technology and medicine, the drive is on to make all data meaningful to drive medical discovery and create actionable outcomes. With tools and capabilities to capture more data than ever before, the challenge becomes linking existing structured and unstructured clinical data with genomic data to increase the industry’s analytical footprint.
Learning Objectives:
∙ Discuss the need to make all data meaningful in order to speed discovery of new knowledge
∙ Provide examples of an analytical direction that supports evolution in medicine
∙ Expose the challenges facing the industry with respect to ~omits
Presented at the 7th Healthcare CIO Program, Hospital Administration School, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Thailand on July 8, 2016
CORD Rare Drug Conference, June 8 - 9, 2022
Opportunities and Challenges for Data Management Real-World Data and Real-World Evidence
• Patient support programs: Sandra Anderson, Innomar Strategies
• AI for Data Management and Enhancement: Aaron Leibtag, Pentavere
• Patient Support and RWE: Laurie Lambert, CADTH
Dr Sanjoy Sanyal wrote this article when he was doing his Masters in Royal College of Surgeons of Edinburgh, University of Bath, United Kingdom.
It traces the origin of the term and discipline called 'Medical Informatics'; describes its evolution and mentions its current healthcare applicability and academic status.
It is fundamental towards understanding today's Information Explosion and its digital implications in all work atmospheres.
Today Dr Sanjoy Sanyal is Professor and Course Director of Neuroscience and FCM-III in Caribbean.
Introduction to Health Informatics and Health Information Technology (Part 2)...Nawanan Theera-Ampornpunt
Presented at the Health Informatics and Health Information Technology Course, Doctor of Philosophy and Master of Science Programs in Data Science for Health Care (International Program), Faculty of Medicine Ramathibodi Hospital, Mahidol University on October 3, 2017
IBM Watson Health: How cognitive technologies have begun transforming clinica...Maged N. Kamel Boulos
Cite as: Kamel Boulos MN. IBM Watson Health: how cognitive technologies have begun transforming clinical medicine and healthcare (Oral session IV – Patient safety tools, Thursday 19 May 2016, 15:45-16:45, Hotel Puijonsarvi, Kuopio). In: Proceedings of the 4th Nordic Conference on Research in Patient Safety and Quality in Healthcare (NSQH2016), Kuopio, Finland, 18-20 May 2016 (organised by University of Eastern Finland), p.29. URL: http://www.uef.fi/NSQH2016 (In: Nykanen I (ed.). The 4th Nordic Conference on Research in Patient Safety and Quality in Healthcare. Kuopio, Finland, May 18-20, 2016. Program and Abstracts. Publications of the University of Eastern Finland. Report and Studies in Health Sciences 21. 2016, p.29 (of 119 p.). ISBN: 978-952-61-2130-7 (nid.), ISSNL: 1798-5722, ISSN: 1798-5730.)
IBM Watson health: how cognitive technologies have begun transforming clinical medicine and healthcare
Maged N Kamel Boulos
ABSTRACT
Background: IBM Watson Health (http://www.ibm.com/smarterplanet/us/en/ibmwatson/health/) belongs to a new generation of smart cognitive computing technologies (a type of artificial intelligence) that are poised to transform the way healthcare is delivered, and to vastly improve clinical outcomes, quality of care and patient safety.
Objectives: Our goal was to collect and document the huge potential of a range of emerging and exemplary uses of IBM Watson in healthcare in both developed and developing country settings.
Methods: A survey of current peer reviewed and grey literature has been conducted, looking for reports and case studies involving the use of IBM Watson in different health and healthcare applications.
Results, conclusions and clinical implications: With its ability to make sense of unstructured medical information by analysing the meaning and context of natural language, and uncovering important knowledge buried within large volumes of data and information, including medical images, IBM Watson is exceptionally well suited for clinical and healthcare decision support, where there are often elements of ambiguity and uncertainty. It has been (or is currently being) successfully deployed in many developed countries in the West, as well as in developing countries, such as India and South Africa. IBM Watson unlocks a complex case by acquiring information from multiple sources, e.g., accessing the electronic patient record, then parsing all related medical evidence at up to 60 million pages per second. After processing all of this information, Watson offers relevant and prioritised suggestions to the decision-maker, e.g., helping clinicians identify the best diagnosis and treatment options in complex oncology cases, and providing hospital managers with new operational insights. The ultimate goals are to reduce cost, medical errors, mortality rates, and help improve patients' quality of life.
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
263778731218 Abortion Clinic /Pills In Harare ,sisternakatoto
263778731218 Abortion Clinic /Pills In Harare ,ABORTION WOMEN’S CLINIC +27730423979 IN women clinic we believe that every woman should be able to make choices in her pregnancy. Our job is to provide compassionate care, safety,affordable and confidential services. That’s why we have won the trust from all generations of women all over the world. we use non surgical method(Abortion pills) to terminate…Dr.LISA +27730423979women Clinic is committed to providing the highest quality of obstetrical and gynecological care to women of all ages. Our dedicated staff aim to treat each patient and her health concerns with compassion and respect.Our dedicated group ABORTION WOMEN’S CLINIC +27730423979 IN women clinic we believe that every woman should be able to make choices in her pregnancy. Our job is to provide compassionate care, safety,affordable and confidential services. That’s why we have won the trust from all generations of women all over the world. we use non surgical method(Abortion pills) to terminate…Dr.LISA +27730423979women Clinic is committed to providing the highest quality of obstetrical and gynecological care to women of all ages. Our dedicated staff aim to treat each patient and her health concerns with compassion and respect.Our dedicated group of receptionists, nurses, and physicians have worked together as a teamof receptionists, nurses, and physicians have worked together as a team wwww.lisywomensclinic.co.za/
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
2. Acklowledgements & Declarations
#ICASM2015
The AAME (UK) Has kindly contributed towards my
attendance at the conference
I have a commercial relationship with Primetime Medical
Software Inc (developers of the “Instant Medical History” CPI
system)
Prof Ray Jones, Health Informatics, University of Plymouth
John Bachman MD, Professor of Primary Care, Mayo Clinic
3. Why particularly relevant
#ICASM2015
Recent tragic events
Need to improve Psychological Assessment
Need to be seen to be improving Psychological Assessment
Need to improve efficiency of Aeromedical Assessment and
Documentation
4. From this conference
#ICASM2015
Significant under reporting of psychological symtpoms and
sub-optimal documentation
Difficulty of persuading pilots to part with information
Need to ask specific questions
5. Anyone recognise this man?
#ICASM2015
A Canadian Physician, one of the four
founding Professors of John Hopkins
Hospital, he is described as the
"Father of Modern Medicine".
6. Sir William Osler (1849-1919)
#ICASM2015
“Talk to the Patient long enough
& he will tell you what is wrong
with him”
7. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz
8. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz
When was this published?
2007?
9. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz
When was this published?
2004?
10. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz
When was this published?
1996?
11. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz
When was this published?
1989?
12. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz
When was this published?
1988?
13. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz
When was this published?
1979?
14. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz
When was this published?
Before 1969?
15. “Toward Automating
the Medical History”
#ICASM2015
“...to relieve the physician from routine, although
important, time‑consuming activities, thereby
extending his capabilities to provide medical care. If
the time physicians spend in collecting, organizing,
recording, and retrieving data could be reduced, at
least in part, by information technology, more time
would be available for actual delivery of medical care
and at the same time the physician’s capabilities for
collecting information from patients would be
extended...”
by Mayne, Weksel, and Sholz (1968)
16. Important reviews
#ICASM2015
Jones RB, Knill-Jones RP. Electronic Patient Record
Project: Direct Patient Input to the Record. Report for the
Strategy Division of the Information Management Group
of the NHS Management Executive: University of
Glasgow, 1994. (Updated 1997).
Bachman JW. The patient-computer interview: A
neglected tool that can aid the clinician. Mayo Clinic
Proceedings 2003;78(1):67-78.
Slack WV. Cybermedicine for the patient. American
Journal of Preventive Medicine 2007;32(5):S135-S136.
17. Highlights
#ICASM2015
Warner Slack paper 1960’s
Ray Jones paper 1990’s
Pringle, BMJ 1988
Prof Bachman literature review 2003
Slack WV. Cybermedicine for the patient.
Prof Bachman “evisits” 2010
18. Common conclusions
#ICASM2015
“A well designed computer system can be used
to interview patients about their medical history,
signs and symptoms”
“Such systems are acceptable to the majority
of patients”
“Systems give patients more time to think
about questions”
19. From 1968
#ICASM2015
“A branching series of questions is developed to
assist the medical history taking of the clinician.
Standard, carefully worded questions are used to
collect a history, with systems having hundreds
if not thousands of questions, but patients only
answering those relevant”
20. Professor Ray Jones
#ICASM2015
From the number of published research studies in
which computers have been successfully used to interview
patients, I think there is no need to spend
time discussing the following:
> A well designed computer system can be used to
interview patients about their medical history,
signs and symptoms.
> Such systems are acceptable to the majority of
patients
@rjonesplymouth
21. Dr M Pringle
#ICASM2015
“Computers may be used acceptably to gather
accurate information and to improve medical
decisions without diminishing the role of the
doctor”
Using computers to take patient histories,
M Pringle, Nottingham University Medical School,
BMJ volume 297, Sept 1988
22. Professor John Bachman MD
#ICASM2015
“Computer Patient Interviewing is valid”
“Instant Medical History is the World leader”
Bachman JW. The patient-computer interview: A
neglected tool that can aid the clinician. Mayo Clinic
Proceedings 2003;78(1): 67-78.
23. Can a computer take a Psychiatric History?
#ICASM2015
“A program on an inexpensive microcomputer was designed to elicit
personal histories from patients in a general psychiatric ward. Their
answers were compared with the information recorded by the responsible
psychiatric team. Where answers disagreed with the clinicians' records, the
patient was interviewed to investigate the discrepancy”
“Most patients' computer histories revealed several items unknown to the
clinicians and of importance in the management of the patient. Most
patients (88%) found that the computer interrogation was as easy as a
clinical interview”
“Computer assessment is proposed as a useful technique for the routine
assessment of patients to augment the clinician's findings and to allow her
to concentrate on the most relevant areas”
Carr AC. Ghosh A. Ancill RJ. Can a computer take a
psychiatric history? Psychological Medicine. 13(1):151-8,
1983 Feb.
24. Comparison of computer-based & personal interviews
#ICASM2015
“A computer-based questionnaire can generate responses that are
equivalent to the responses to a traditional personal interview. In
some cases, a computer may be more successful in eliciting risk
factors”
Hasley S A comparison of computer-based and personal
interviews for the gynecologic history update. Obstetrics &
Gynecology. 85(4):494-8, 1995 Apr.
25. Mayo Clinic eVisits 2010
#ICASM2015
“The e-visits made surgery visits unnecessary in 1012
cases (40%)”
“In the basic e-visit process, patients entered their
reported problem in free text (eg, “back pain”) and
then answered questions one at a time. The questions
branched such that the history was organised into a
readable clinical format”
Pilot Study of Providing Online Care in a Primary
Care Setting Steven C. Adamson, MD, and John W.
Bachman, MD. Mayo Clinic Proceedings August
2010 vol. 85 no. 8704-710
26. History taking: How do we perform?
#ICASM2015
Physicians miss 54% of patients problems and
45% of their concerns
In 50% of visits patients and doctors do not
agree on the presenting problem
50% of psychological problems are missed
Only 23 seconds before patient is interrupted
(12 secs for medical residents)
Biggest complaint in patient “satisfaction” is poor
physician communication skills.
(See Bachman Literature review for references)
28. Strengths of Computerised interview
#ICASM2015
Structured, all questions are asked
Does not Interrupt
Good at obtaining sensitive information
Patients better prepared for a subsequent face to
face consultation
Legible summaries and direct input to Electronic Record
Scales calculated well
Effective at improving care quality
29. Strengths of Computerised interview
#ICASM2015
All questions usually answered
Can be done anywhere, at Patient’s pace
& with family help
Different languages
Better data- better research
Checklist
Does not require Clinician’s time
Acceptable to Patients in multiple studies
30. Patient can complete as little or
as much as they feel able and the
depth of questioning can be tailored
to suit the clinical setting
31. Computers show no embarrassment
in asking important questions where
responses deem that question is
worth answering
32. Otolarngology
History of Ear surgery for infection
Accidents and Injuries
History of Concussion. Bone fracture. Post head injury confusion and fatigue. Memory loss a few seconds
before injury. Injury from ligaments. Head injury. Loss of consciousness Immediately at time of injury, a few
seconds after injury, and for an undetermined time period. Torn ligament of the right foot. Rib sprains. Cervical
sprain. Sprained middle back. Doesn't know Number of leg sprains. One leg torn ligament. Head laceration.
Family History
History of Heart disease (immediate family), Asthma (distant family).
Sister
History of Asthma
Social History
History of Thinking someone in family has a substance abuse problem
Activities for Daily Living
History of Sports participation restricted for health reasons
Substance Use
Tobacco Use
History of Friend or family use tobacco
Alcohol
History of Alcohol intake
Drug Usage
History of Friends bring alcohol to School
Medication History
Ongoing Medications
History of Prescription medication for more than 3 months. Medication stopped in the last month and
dosage change. Prescribed medication very effective. Medications prescribed by another physician. Most
of the time compliant with Prescription. Inhaler use.
Over-the-counter Medications
History of Non-prescription medication
Complementary Medicines
History of Nutritional supplements in last month and for weight gain
Adverse Drug Reactions
33. Otolarngology
History of Ear surgery for infection
Accidents and Injuries
History of Concussion. Bone fracture. Post head injury confusion and fatigue. Memory loss a few seconds
before injury. Injury from ligaments. Head injury. Loss of consciousness Immediately at time of injury, a few
seconds after injury, and for an undetermined time period. Torn ligament of the right foot. Rib sprains. Cervical
sprain. Sprained middle back. Doesn't know Number of leg sprains. One leg torn ligament. Head laceration.
Family History
History of Heart disease (immediate family), Asthma (distant family).
Sister
History of Asthma
Social History
History of Thinking someone in family has a substance abuse problem
Activities for Daily Living
History of Sports participation restricted for health reasons
Substance Use
Tobacco Use
History of Friend or family use tobacco
Alcohol
History of Alcohol intake
Drug Usage
History of Friends bring alcohol to School
Medication History
Ongoing Medications
History of Prescription medication for more than 3 months. Medication stopped in the last month and
dosage change. Prescribed medication very effective. Medications prescribed by another physician. Most
of the time compliant with Prescription. Inhaler use.
Over-the-counter Medications
History of Non-prescription medication
Complementary Medicines
History of Nutritional supplements in last month and for weight gain
Adverse Drug Reactions
34. Psychiatric
Anxiety Disorders
He reported: Stress now.
Risk Factors, Prevention and Patient issues
Prevention
Counselling
He reported: Not wearing protective eye. Carried weapon 6 or more days last month.
Nutrition
He reported Diet in last month
Patient Issues
He reported: Consulting another physician
Self-assessment Scales
Title: Asthma Control Test
Description: 5-item scale to determine problems with asthma in the last month.
Patient Score 20 – Asthma may be under control
Scoring Key and Interpretation:
0-19 : Asthma not well controlled
20-25 : Asthma may be under control
Reference: Nathan RA, Sorkness CA, Kosinski M, et al. Development of the Asthma Control Test a survey for assessing asthma control J Allergy
Clin Immunol 2004,113 59-65
Title: Mental Health Inventory Screening Test (MHI-5)
Description: Short 5-item version of the 18 item Mental Health Inventory for detecting affective disorders. No level of severity is
revealed because of the brevity of the scale.
Patient Score 9 – Passed mental health screen
Scoring Key and Interpretation:
0-17 : Passed mental health screen
18-30 : Failed mental health screen
Reference: Berwick, DM, Murphy, JM Goldman, PA, “Performance of a Five item Mentla Health Screening Test”, Med Care 1991, 29,2 169-176.
Title: Children of Alcoholics Screening Test (CAST)
Description: 30-item inventory identifies children and adolescents who are living with at least one alcoholic parent. It measures
children's feelings, attitudes, perceptions and experiences related to their parents' drinking behaviour. It reliably identified 100% of
the children or both clinically diagnosed and self-reported alcoholics.
Patient Score 11 – Severe family dysfunction due to alcoholism
Scoring Key and Interpretation:
0-3 : Non-alcoholic family
4-9 : Family problem with alcholism likely
10-30: Severe family dysfunction due to alcoholism
Reference: Jones JW Chilren of Alcoholics Screening Test, (CAST) Chicago, III Camelot Unlimited 1983
35. Psychiatric
Anxiety Disorders
He reported: Stress now.
Risk Factors, Prevention and Patient issues
Prevention
Counselling
He reported: Not wearing protective eye. Carried weapon 6 or more days last month.
Nutrition
He reported Diet in last month
Patient Issues
He reported: Consulting another physician
Self-assessment Scales
Title: Asthma Control Test
Description: 5-item scale to determine problems with asthma in the last month.
Patient Score 20 – Asthma may be under control
Scoring Key and Interpretation:
0-19 : Asthma not well controlled
20-25 : Asthma may be under control
Reference: Nathan RA, Sorkness CA, Kosinski M, et al. Development of the Asthma Control Test a survey for assessing asthma control J Allergy
Clin Immunol 2004,113 59-65
Title: Mental Health Inventory Screening Test (MHI-5)
Description: Short 5-item version of the 18 item Mental Health Inventory for detecting affective disorders. No level of severity is
revealed because of the brevity of the scale.
Patient Score 9 – Passed mental health screen
Scoring Key and Interpretation:
0-17 : Passed mental health screen
18-30 : Failed mental health screen
Reference: Berwick, DM, Murphy, JM Goldman, PA, “Performance of a Five item Mentla Health Screening Test”, Med Care 1991, 29,2 169-176.
Title: Children of Alcoholics Screening Test (CAST)
Description: 30-item inventory identifies children and adolescents who are living with at least one alcoholic parent. It measures
children's feelings, attitudes, perceptions and experiences related to their parents' drinking behaviour. It reliably identified 100% of
the children or both clinically diagnosed and self-reported alcoholics.
Patient Score 11 – Severe family dysfunction due to alcoholism
Scoring Key and Interpretation:
0-3 : Non-alcoholic family
4-9 : Family problem with alcholism likely
10-30: Severe family dysfunction due to alcoholism
Reference: Jones JW Chilren of Alcoholics Screening Test, (CAST) Chicago, III Camelot Unlimited 1983
36. Chief Complaint
E M is a 11 year old male. His reason for visit is “12 year old check-up”
Past, Family, and Social History
Social History
History of: Within the last six months changing schools. Within the last two years marriage of a family
member, gaining of a family member, and change in the health of a family member. Lives with parents.
Sexual History
History of Slight concerns with HIV infection.
Review of Systems
Musculoskeletal
He reported: Back pain sometimes
Neurologic
He reported: Headaches once a week. Dyssomnia.
Risk Factors, Prevention, and Patient Issues
Prevention
Counseling
He reported: Does not use bike safety helmet.
Nutrition
He reported 1-2 servings of fruit daily. 1-2 servings of vegtables daily. Desiring to be thinner. cial History
Self-assessment Scales
Title: SCOFF
Description: Brief 5-question screening tool for eating disorders.
Patient Score 0 – Normal eating, no indication of anorexia nervosa or bulimia
Scoring Key and Interpretation:
0-1 : Normal eating, no indication of anorexia nervosa or bulimia
2-5 : Abnormal eating, likely indication of anorexia nervosa or bulimia
Reference: Morgan JF, Reid F, Lacey JH. The SCOFF questionniare assessment of a new screening tool for eating disorders.. British
Medical Journal 1999, 319-1467
37. Chief Complaint
E M is a 11 year old male. His reason for visit is “12 year old check-up”
Past, Family, and Social History
Social History
History of: Within the last six months changing schools. Within the last two years marriage of a family
member, gaining of a family member, and change in the health of a family member. Lives with parents.
Sexual History
History of Slight concerns with HIV infection.
Review of Systems
Musculoskeletal
He reported: Back pain sometimes
Neurologic
He reported: Headaches once a week. Dyssomnia.
Risk Factors, Prevention, and Patient Issues
Prevention
Counseling
He reported: Does not use bike safety helmet.
Nutrition
He reported 1-2 servings of fruit daily. 1-2 servings of vegtables daily. Desiring to be thinner. cial History
Self-assessment Scales
Title: SCOFF
Description: Brief 5-question screening tool for eating disorders.
Patient Score 0 – Normal eating, no indication of anorexia nervosa or bulimia
Scoring Key and Interpretation:
0-1 : Normal eating, no indication of anorexia nervosa or bulimia
2-5 : Abnormal eating, likely indication of anorexia nervosa or bulimia
Reference: Morgan JF, Reid F, Lacey JH. The SCOFF questionniare assessment of a new screening tool for eating disorders.. British
Medical Journal 1999, 319-1467
38. Chief Complaint
A M is a 13 year old male. His reason for visit is “Pre-Participation Sports Exam”
Past, Family, and Social History
Accidents and injuries
History of: Concussion. Injury torn ligaments. Head injury. Doesn't know number of leg torn ligaments.
Doesn't know which bones were broken in lower leg. Head laceration.
Family History
Mother
History of: Asthma
Social History
History of: Physical assualt less than 2 monhts ago and by unknown person
Allergy History
History of: No allergies to medicines, pollen, foods or stinging insects
Prior Available Tests
History of: Previous evaluation included an X-Ray of the shoulder. Treatment for musculoskeletal injury.
Doesn't know number of leg X-Rays. Doesn't know number of arm X-Rays.
Review of Systems
Eye
He reported: Vision change
Neurologic
He reported: Paresthesia post traumatic. Paralysis post traumatic. Headaches sometimes precipitated or
aggravated by exertion.
Risk Factors, Prevention, and Patient Issues
Prevention
Counseling
He reported: Not weating protective eyewear
Time/Date
10:16am August 6 2010
39. Chief Complaint
A M is a 13 year old male. His reason for visit is “Pre-Participation Sports Exam”
Past, Family, and Social History
Accidents and injuries
History of: Concussion. Injury torn ligaments. Head injury. Doesn't know number of leg torn ligaments.
Doesn't know which bones were broken in lower leg. Head laceration.
Family History
Mother
History of: Asthma
Social History
History of: Physical assualt less than 2 monhts ago and by unknown person
Allergy History
History of: No allergies to medicines, pollen, foods or stinging insects
Prior Available Tests
History of: Previous evaluation included an X-Ray of the shoulder. Treatment for musculoskeletal injury.
Doesn't know number of leg X-Rays. Doesn't know number of arm X-Rays.
Review of Systems
Eye
He reported: Vision change
Neurologic
He reported: Paresthesia post traumatic. Paralysis post traumatic. Headaches sometimes precipitated or
aggravated by exertion.
Risk Factors, Prevention, and Patient Issues
Prevention
Counseling
He reported: Not weating protective eyewear
Time/Date
10:16am August 6 2010
40. She denied pressure or pain in chest, heart murmur, intermittent chest pain, heavy squeezing tight chest
pressure, edema, varicose veins, claudication.
Gastrointestinal
She denied gastrointestinal symptoms, nausea, diarrhea, constipation, change in bowel habits, yellow rash.
Genitourinary
She denied genitourinary symptoms, dysuria, vaginal discharge.
Endocrine
She denied gland trouble, diabetesm goutm or thyroid condition, change in thirst or appetite.
Hematological Muskuloskeletal
She denied excessive bleeding, swollen glands She denied rheumatic symptoms, swelling of
extremities.
Neurologial
She reported frequent headaches, headaches more than twice a month, headache similar to previous
headaches, onset of headaches under age of 24.
She denied motor disturbances, dyssomnia, headaches usually periorbital at onset, periauricular headaches
associated with opening jaw, headaches cause awakening from sleep, headaches more frequent certain days of
the week, headaches occur in groups or clusters, aura preceeding headache, visual flashes or partial visual loss
before the headache, alcohol or drugs precipitate a headache, chocolate consumption precipitates a headache,
recently stopped taking any substance like a medication, drug, alcohol, caffeine or nicotine.Headaches are
accompanied by nuasea, vomitting, paresthesia or weakness associated with headache, eyes water or become
red with headaches, headaches are accompanied by frequent urination, nasal congestion or discharge
accompanying headaches.
Psychiatric
She reported history of suicidal idea or attempt, change in financial state within the last six months, change in
responsibilities at work within the last six months, mild stressed feeling, enjoys interaction with opposite sex
some of the time, normal thinking most of the time, normal activities most of the time, life full most of the time,
irritable some of the time, iquickly becomes too tired to carry out activities, decisive most of the time, hopeful
good part of the time, useful good part of the time, enjoy activities good part of the time. She denied personality
changes in last six months, emotional complaints, recent stress, tobacco pipe, tobacco smokeless, tobacco use
more than 10 years, personality change before headache.
Risk Factors
Physical Conditioning
She reported less than 30 mins exercise per day
Nutrition
41. She denied pressure or pain in chest, heart murmur, intermittent chest pain, heavy squeezing tight chest
pressure, edema, varicose veins, claudication.
Gastrointestinal
She denied gastrointestinal symptoms, nausea, diarrhea, constipation, change in bowel habits, yellow rash.
Genitourinary
She denied genitourinary symptoms, dysuria, vaginal discharge.
Endocrine
She denied gland trouble, diabetesm goutm or thyroid condition, change in thirst or appetite.
Hematological Muskuloskeletal
She denied excessive bleeding, swollen glands She denied rheumatic symptoms, swelling of
extremities.
Neurologial
She reported frequent headaches, headaches more than twice a month, headache similar to previous
headaches, onset of headaches under age of 24.
She denied motor disturbances, dyssomnia, headaches usually periorbital at onset, periauricular headaches
associated with opening jaw, headaches cause awakening from sleep, headaches more frequent certain days of
the week, headaches occur in groups or clusters, aura preceeding headache, visual flashes or partial visual loss
before the headache, alcohol or drugs precipitate a headache, chocolate consumption precipitates a headache,
recently stopped taking any substance like a medication, drug, alcohol, caffeine or nicotine.Headaches are
accompanied by nuasea, vomitting, paresthesia or weakness associated with headache, eyes water or become
red with headaches, headaches are accompanied by frequent urination, nasal congestion or discharge
accompanying headaches.
Psychiatric
She reported history of suicidal idea or attempt, change in financial state within the last six months, change in
responsibilities at work within the last six months, mild stressed feeling, enjoys interaction with opposite sex
some of the time, normal thinking most of the time, normal activities most of the time, life full most of the time,
irritable some of the time, iquickly becomes too tired to carry out activities, decisive most of the time, hopeful
good part of the time, useful good part of the time, enjoy activities good part of the time. She denied personality
changes in last six months, emotional complaints, recent stress, tobacco pipe, tobacco smokeless, tobacco use
more than 10 years, personality change before headache.
Risk Factors
Physical Conditioning
She reported less than 30 mins exercise per day
Nutrition
42. Patients collect info that Clinicians miss
#ICASM2015
40% of the time the questionnaire provided
useful information that would not be typically
elicited
Essential Questions aren't missed
Pilot’s Checklist
43. Relevance to Pilot Assessment
#ICASM2015
Psychological issues
Illicit Drugs
Alcohol
Documentation
Evidence strongly suggests that people will be
more honest with the CPI than face to face.
44. Completeness
#ICASM2015
CPI ensures that lines of investigation are not forgotten, leading to more
complete data and fewer errors in diagnosis and better agreement between
Patient and Doctor.
For example, a recent German hospital study found that computer histories
reported an additional average of 3.5 problems per patient which were not
recorded in corresponding physician histories. The authors recommended a
combination of computer and physician histories as the best method.
Zakim D, Braun N, Fritz P, Alscher MD. Underutilization of information and knowledge
in everyday medical practice: Evaluation of a computer-based solution. BMC Medical
Informatics and Decision Making 2008;8:12.
46. Let Pilots do the work
#ICASM2015
The use of Computer Patient Interviewing allows pilots
to give a very full history whilst saving the AME time.
This will capture sensitive information at least as well as
a face to face questions and probably more reliable.
Many more direct questions can be asked.
Standard Instruments can be administered and scored
as a routine (PHQ-9, GAD-7 etc)
47. Outcomes of using CPI
#ICASM2015
More complete questioning.
Better documentation which in turn will enhance the
ability to compare responses over time.
Much better coded data.
Standard Instruments scored.
Improved assessment and particularly Psychological.
We will be seen to be improving our processes.
48. Change Management in Healthcare
#ICASM2015
“That the stethoscope will ever come into general use,
notwithstanding its value, is extremely doubtful because its
beneficial application requires much time and gives a good
bit of trouble, both to the patient and the practitioner
because it's hue and character are foreign and opposed to
all our habits and associations”
The Times 1834
49. Thank you for your interest
#ICASM2015
Dr Richard Sills
rosills1@gmail.com
+44 (0) 7940836337
slideshare.net/ICASM2015
(If you would like to add your slides to the
collection please email them to me)
51. “Yes, yes, Mrs Jones... ...we'll talk about your chest pain in one
minute. Right now I'm just trying to remember my password”
52. A machine cannot come between
me and my Patient!
#ICASM2015
All of this is true
It need not happen
53. A case (thanks to Prof Bachman)
#ICASM2015
A patient who has hypertension comes to see you
because in the last ten days she has noted that her
blood pressure is elevated from its baseline.
Meds Lisinopril 20 mg daily
BP 152/93
54. Chief Complaint Time/Date
Sonk is a 65 year old female. Her reason for visit is “Hypertension” 13:34pm. April 17, 2003
History of Present Illness
SOnk reported: palpitations. Irregular, missed, or skipped heart beats.
SOnk denied: angina pectoris. Pressure or pain in chest. Pale or white episodes sometimes.
Past, Family and Social History
Past Medical History
History of: last blood pressure high. Hypertension within five to ten years. Hypercholesterolemia.
Hypertriglyceridemia.
Family History
History of family members with high blood pressure.
Social History
Alcohol
History of: alcohol use weekly
Medication History
Ongoing Medications
History of: female hormoe medication. Conjugated estrogens. Non-prescription non-steroidal anti-
inflammatory medication for pain.
Past Medications
History of: estrogen replacement hormones. Estorgen and progesterone combination replacement
hormones. Estrogen progresterone combination therapy 11 to 15 years. Estrogen replacement
therapy 11 to 15 years. Oral contraceptives.
Review of Systems
Constitutional Respiratory
SOnk denied: Overweight SOnk denied: dyspnea.
Genitourinary Skin
SOnk denied: dyspnea. SOnk denied: acne
Musculoskeletal Psychiatric
SOnk denied: legs painful. SOnk denied: recent stress
Neurological Skin
SOnk denied: headaches. Tremulousness. SOnk reported: Paresis
Risk Factors
Physical Conditioning Nutrition
SOnk reported: <30 min per day exercise SOnk reported: Eating imported licorice
55. A case (thanks to Prof Bachman)
#ICASM2015
WHAT A DOC!!!!!
1) Her B/P is coming down: 138/80 and now 128/78
2) Her “numb feet” have responded well to the iron
supplements. She is glad.
3) She has stopped her licorice and excess salt intake
4) She thanks you for sending her to the Patient
Education class on Hypertension and YES you were right
– she did learn something! This IS the truth and nothing
but the truth....
56. What can we learn from this?
#ICASM2015
We can not judge quality of care by reviewing
a chart!
Inputs are important
Computerised history provided more information
that was critical to this case, and was valuable
to the clinician
57. Embarrassing Topics
#ICASM2015
CPI allows patients to more easily disclose information
about embarrassing topics eg. computer interviewing for
pelvic floor symptoms in both primary care and hospital
found ‘Despite the taboo nature of many of the items, the
questionnaire was well received by women in both settings’
Radley SC, Jones GL, Tanguy EA, Stevens VG, Nelson C, Mathers
NJ. Computer interviewing in urogynaecology: concept,
development and psychometric testing of an electronic pelvic
floor assessment questionnaire in primary and secondary care.
BJOG 2006;113(2):231-238.