The document provides an overview of clinical analytics (CA), which involves analyzing clinical data to improve healthcare quality, safety, and efficiency. It defines CA and describes common uses like tracking quality measures. Challenges to CA include the heterogeneity of medical data and lack of data integration. The document also outlines the types of practitioners involved in CA, common tools used like data warehouses, and examples of how hospitals have leveraged CA to reduce infections, improve coding to increase revenues, and plan for public health issues. The future of CA is presented as moving from academic centers to broader healthcare and enabling personalized medicine through integrated genomic and other data.
Clinical research and clinical data management - Ikya Globalikya global
Data management functions in clinical trials—extensive data cleaning, full query management, protocol deviation management, batch processing, as examples—have traditionally been served by stand-alone clinical data management systems (CDMS), whose input is from paper forms or from separate electronic data capture systems. Distinct electronic data capture and data management systems require data integration, with resulting timing and reconciliation issues.
Electronic Data Capture & Remote Data CaptureCRB Tech
CRB Tech is one of the best leading Software Development Company in Pune. We are offering Software Development Services as well as IT Training including Java, Dot Net, SEO and Clinical Research training in pune.
Appalla Venkataprabhakar and I presented this at the Oracle\'s Annual Clinical Development and Safety Conference 2010 at Hyderabad, India on 6th October 2010.
Have full fleged clinical trial data management systems which bring them a good amount of business and revenue.
CDM is a fundamental process which controls data accuracy of each trial besides helping the timelessness to be achieved.
It helps in linking clinical research co-ordinator = who monitor all the sites & collects the data.
it Links with biostatisticians = who analyze, interpret and report data in clinically meaningful way.
Clinical research and clinical data management - Ikya Globalikya global
Data management functions in clinical trials—extensive data cleaning, full query management, protocol deviation management, batch processing, as examples—have traditionally been served by stand-alone clinical data management systems (CDMS), whose input is from paper forms or from separate electronic data capture systems. Distinct electronic data capture and data management systems require data integration, with resulting timing and reconciliation issues.
Electronic Data Capture & Remote Data CaptureCRB Tech
CRB Tech is one of the best leading Software Development Company in Pune. We are offering Software Development Services as well as IT Training including Java, Dot Net, SEO and Clinical Research training in pune.
Appalla Venkataprabhakar and I presented this at the Oracle\'s Annual Clinical Development and Safety Conference 2010 at Hyderabad, India on 6th October 2010.
Have full fleged clinical trial data management systems which bring them a good amount of business and revenue.
CDM is a fundamental process which controls data accuracy of each trial besides helping the timelessness to be achieved.
It helps in linking clinical research co-ordinator = who monitor all the sites & collects the data.
it Links with biostatisticians = who analyze, interpret and report data in clinically meaningful way.
A Trial Master File (TMF) is a comprehensive collection of essential documents and records that are generated or collected during the conduct of a clinical trial. The TMF serves as the centralized repository of all study-related documentation and provides a complete and accurate account of the trial's planning, execution, and outcomes. It is an important component of Good Clinical Practice (GCP) and regulatory compliance.
Adverse Events and Serious Adverse Events - Katalyst HLSKatalyst HLS
Introduction to Adverse Events & Serious Adverse Events in Pharmacovigilance and Drug Safety in Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Contact:
"Katalyst Healthcares & Life Sciences"
South Plainfield, NJ, USA
info@KatalystHLS.com
What is Health Informatics?
HI Goals
HI stakeholders
HI subfields / subspecialties
Healthcare trends & HI
HI professional environments
HI education / training opportunities & degrees
HI organizations / journals / meetings / events
HI professional certificates
HI books
TMF Fundamentals - An Introduction to Better Trial Master File Management - M...Montrium
In this presentation, we explore the TMF fundamentals and an introduction to better managing your TMF. We'll start by diving into the world of TMF management, how to properly leverage the regulations, which documents constitute as TMF-worthy and what basic metrics you can track to increase the efficiency of your trial.
Finally, we will also discuss some of the features Montrium has developed to facilitate the management of the Trial Master File in a fundamental way.
This presentation covers the following topics:
-Fundamentals of TMF management process
-How to use the regulations to ensure success
-What cross functional groups hold TMF worthy documents
-TMF management challenges and how you can alleviate them
-Base metrics to track and what they mean to your organization
-How an eTMF helps TMF Management
You can follow along with this presentation via our webinar:
https://info.montrium.com/tmf-fundamentals-an-introduction-to-better-trial-master-file-management
Presentation from the 2016 MAGI West conference on how to prepare your organization for inspection readiness by focusing on processes, governance, and tools.
A Trial Master File (TMF) is set up at the beginning of the trial. It is a collection of all essential documents pertaining to the trial, which in turn will allow for effective monitoring and supervision (audit). In order to demonstrate compliance with the applicable regulations, Good Clinical Practice (GCP) guidelines and the protocol – a well organised TMF is essential.
According to the GCP guidelines, it is the responsibility of the sponsor to ensure that the TMF includes all relevant essential documents, and is stored in a secure location, with restricted access. Generally, the TMF is maintained at the sponsor’s office, co-ordinating site or by the Contract Research Organisation (CRO), if contracted. In addition to the TMF, copies of all relevant documents must be kept at each participating site, in an Investigator Site File (ISF). The ISF will also include all site-specific essential documents. For example, site preparedness log or site visit logs, etc.
A member of the research or trial team should be delegated with the task of updating, maintaining and reviewing the TMF and ISF, periodically throughout the course of the clinical trial as per the defined SOPs. Ideally, the documents included in the TMF are:
Trial documents (protocol, investigator’s brochure, participant information documents, SOPs, instructions, manuals, guidelines, etc.)
Documents related to the Investigational Product (certificates of analysis, shipment records, storage records, etc.)
Training documentation for the trial team
Details of the laboratories, if applicable.
Contracts, agreements, budgets, etc.
Monitoring visit reports (for each site visit onsite or central)
Documents related to the safety reporting
Ethics Committees documents (composition of the EC, approvals, notifications, reports, etc.)
Site-specific documents (list of site staff and their curriculum vitae, investigator’s undertaking, site preparedness documents, training of site staff, etc.)
Audit related documents, if available (if an audit was conducted).
Significant communications
Others
The GCP guidelines provide comprehensive guidance regarding the documents to be included in a Trial Master File categorised according to the lifecycle of the trial. This information can also be accessed here.
It shall be the responsibility of the sponsor to make arrangements for the safe and secure custody of all study-related documents and material for a period of three years after the completion of the study or submission of the data to the regulatory authority(ies) whichever is later.
Georgina Gal, Regulatory Affairs Manager, AbbVie, Hungary
Presentation at EIPG – BIPA Symposium “Clinical Trials Research” at the Faculty of Pharmacy, Medical University of Sofia, Sofia 2014.
Medical Device Clinical Studies and Protocol DesignMichael Swit
August 17, 2006 presentation to the IVT Medical Device Conference, focusing on the following relative to medical devices:
* Standards of Approval – What the Protocol Targets
* Key Considerations in Designing Clinical Studies
* Practical Lessons in Clinical Trial Design & Execution
In this presentation, Shaheen Gauher talks about two things: (1) How data science and machine learning can be used to manage and control escalating healthcare costs, and (2) How to create a Population Health Management Solution using state of the art Azure Data Lake Analytics and Population Health Report with real time visualization capability using Power BI. The solution presented can be deployed on Azure through a one-click deployment option in https://gallery.cortanaintelligence.com/
A Trial Master File (TMF) is a comprehensive collection of essential documents and records that are generated or collected during the conduct of a clinical trial. The TMF serves as the centralized repository of all study-related documentation and provides a complete and accurate account of the trial's planning, execution, and outcomes. It is an important component of Good Clinical Practice (GCP) and regulatory compliance.
Adverse Events and Serious Adverse Events - Katalyst HLSKatalyst HLS
Introduction to Adverse Events & Serious Adverse Events in Pharmacovigilance and Drug Safety in Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Contact:
"Katalyst Healthcares & Life Sciences"
South Plainfield, NJ, USA
info@KatalystHLS.com
What is Health Informatics?
HI Goals
HI stakeholders
HI subfields / subspecialties
Healthcare trends & HI
HI professional environments
HI education / training opportunities & degrees
HI organizations / journals / meetings / events
HI professional certificates
HI books
TMF Fundamentals - An Introduction to Better Trial Master File Management - M...Montrium
In this presentation, we explore the TMF fundamentals and an introduction to better managing your TMF. We'll start by diving into the world of TMF management, how to properly leverage the regulations, which documents constitute as TMF-worthy and what basic metrics you can track to increase the efficiency of your trial.
Finally, we will also discuss some of the features Montrium has developed to facilitate the management of the Trial Master File in a fundamental way.
This presentation covers the following topics:
-Fundamentals of TMF management process
-How to use the regulations to ensure success
-What cross functional groups hold TMF worthy documents
-TMF management challenges and how you can alleviate them
-Base metrics to track and what they mean to your organization
-How an eTMF helps TMF Management
You can follow along with this presentation via our webinar:
https://info.montrium.com/tmf-fundamentals-an-introduction-to-better-trial-master-file-management
Presentation from the 2016 MAGI West conference on how to prepare your organization for inspection readiness by focusing on processes, governance, and tools.
A Trial Master File (TMF) is set up at the beginning of the trial. It is a collection of all essential documents pertaining to the trial, which in turn will allow for effective monitoring and supervision (audit). In order to demonstrate compliance with the applicable regulations, Good Clinical Practice (GCP) guidelines and the protocol – a well organised TMF is essential.
According to the GCP guidelines, it is the responsibility of the sponsor to ensure that the TMF includes all relevant essential documents, and is stored in a secure location, with restricted access. Generally, the TMF is maintained at the sponsor’s office, co-ordinating site or by the Contract Research Organisation (CRO), if contracted. In addition to the TMF, copies of all relevant documents must be kept at each participating site, in an Investigator Site File (ISF). The ISF will also include all site-specific essential documents. For example, site preparedness log or site visit logs, etc.
A member of the research or trial team should be delegated with the task of updating, maintaining and reviewing the TMF and ISF, periodically throughout the course of the clinical trial as per the defined SOPs. Ideally, the documents included in the TMF are:
Trial documents (protocol, investigator’s brochure, participant information documents, SOPs, instructions, manuals, guidelines, etc.)
Documents related to the Investigational Product (certificates of analysis, shipment records, storage records, etc.)
Training documentation for the trial team
Details of the laboratories, if applicable.
Contracts, agreements, budgets, etc.
Monitoring visit reports (for each site visit onsite or central)
Documents related to the safety reporting
Ethics Committees documents (composition of the EC, approvals, notifications, reports, etc.)
Site-specific documents (list of site staff and their curriculum vitae, investigator’s undertaking, site preparedness documents, training of site staff, etc.)
Audit related documents, if available (if an audit was conducted).
Significant communications
Others
The GCP guidelines provide comprehensive guidance regarding the documents to be included in a Trial Master File categorised according to the lifecycle of the trial. This information can also be accessed here.
It shall be the responsibility of the sponsor to make arrangements for the safe and secure custody of all study-related documents and material for a period of three years after the completion of the study or submission of the data to the regulatory authority(ies) whichever is later.
Georgina Gal, Regulatory Affairs Manager, AbbVie, Hungary
Presentation at EIPG – BIPA Symposium “Clinical Trials Research” at the Faculty of Pharmacy, Medical University of Sofia, Sofia 2014.
Medical Device Clinical Studies and Protocol DesignMichael Swit
August 17, 2006 presentation to the IVT Medical Device Conference, focusing on the following relative to medical devices:
* Standards of Approval – What the Protocol Targets
* Key Considerations in Designing Clinical Studies
* Practical Lessons in Clinical Trial Design & Execution
In this presentation, Shaheen Gauher talks about two things: (1) How data science and machine learning can be used to manage and control escalating healthcare costs, and (2) How to create a Population Health Management Solution using state of the art Azure Data Lake Analytics and Population Health Report with real time visualization capability using Power BI. The solution presented can be deployed on Azure through a one-click deployment option in https://gallery.cortanaintelligence.com/
Health IT Summit Houston 2014 - Case Study "EHR Optimization for Organizational Value in a Changing Healthcare Environment"
Luis Saldana, MD, MBA, FACEP
CMIO
Texas Health Resources
iHT2 case studies and presentations illustrate challenges, successes and various factors in the outcomes of numerous types of health IT implementations. They are interactive and dynamic sessions providing opportunity for dialogue, debate and exchanging ideas and best practices. This session will be presented by a thought leader in the provider, payer or government space.
Best Practices for Enabling HIE and Incorporating Capabilities into EHR Workf...Justin Campbell
Health Information Exchange (HIE) allows health care providers to access and share a patient’s medical information securely and electronically, providing a unified view of patient data across health care organizations. HIE enhances clinicians’ workflow and their ability to connect, coordinate, and collaborate on patient care quickly and easily. However, health care organizations frequently struggle with last-mile connectivity from their clinical system of record to the receiving system and incorporating HIE capabilities into EHR workflows. This session will provide a framework for successful HIE onboarding including data access, conformance testing & validation, as well as share strategies for implementing HIE capabilities at the point of care. This session will also introduce the concept of Patient Centered Data Home and illustrate how the exchange of information utilizing the PCDH model is a cost-effective, scalable solution to assuring real-time clinical data is available whenever and wherever care occurs to improve the quality of care.
Case Study “Investment in a Health IT Infrastructure, the Future Quality Imperative”
Steven Anderman
Chief Operating Officer & SVP, Operations
Bronx-Lebanon Hospital Center
A hybrid approach to data management is emerging in healthcare as organizations recognize the value of an enterprise data warehouse in combination with a data lake.
In this SlideShare, we discuss data lakes in healthcare and we:
Provide an overview of a Hadoop-based data lake architecture and integration platform, and its application in machine learning, predictive modeling, and data discovery
Discuss several key use cases driving the adoption of data lakes for both providers and health plans
Discuss available data storage forms and the required tools for a data lake environment
Detail best practices for conducting data lake assessments and review key implementation considerations for healthcare
An overview of clinical healthcare data analytics from the perspective of an interventional cardiology registry. This was initially presented as part of a workshop at the University of Illinois College of Computer Science on April 20, 2017.
All patients are different, and data collected during product development or Randomised Clinical Trials (RCT) does not always paint the full picture of everyday patients. RWE insights complement the manufacturing process and RCT findings, adding more value and providing real-world impact. While together data from the manufacturing process and RWD paint a fuller picture.
Due to the limitations of the study design, data from the manufacturing process and RCTs are inadequate for demonstrating an intervention’s long-term safety and effectiveness. Moreover, it is possible to compare multiple product or interventions in RWE.
> HTA and Real World Evidence (RWE)
> Why RWE? - Limitations with RCT
> RCT v/s RWE
> Definition of RWE
> Sources of RWE
> Advantages of RWE
> Application of Real World Data (RWD) in RWE
> Benefits of RWD in RWE
> Why Data Sharing is Important?
> Important Stakeholders
> How to Encourage Data Sharing?
> Benefits of Data Sharing
> Case Studies
> Data Privacy Scenario
> Data Security in India
> Regulatory Perspectives Around RWD/RWE
> Way Forward
> Definition of RWD
> RWD - Big Data Characteristics
> Sources of RWD
> Important Stakeholders
> Benefits of RWD
> Why Data Sharing is Important?
> Benefits of Data Sharing
> Who Benefits?
> Ultimate Goals
> Case Studies
> Challenges
> Data Privacy Scenario
> Data Security in India
> Regulatory Perspectives Around RWD
> How to Encourage Data Sharing?
Network physicians, hospitals, and other care continuum providers work collaboratively in active clinical process improvement programs across service lines and specialties to define, establish, implement, monitor, evaluate and periodically update the processes of:
- Evidence-based medicine
- Beneficiary engagement
- Care coordination
- Conservation of healthcare resources
- Clinical data reporting
We understand the unique challenges pickleball players face and are committed to helping you stay healthy and active. In this presentation, we’ll explore the three most common pickleball injuries and provide strategies for prevention and treatment.
Leading the Way in Nephrology: Dr. David Greene's Work with Stem Cells for Ki...Dr. David Greene Arizona
As we watch Dr. Greene's continued efforts and research in Arizona, it's clear that stem cell therapy holds a promising key to unlocking new doors in the treatment of kidney disease. With each study and trial, we step closer to a world where kidney disease is no longer a life sentence but a treatable condition, thanks to pioneers like Dr. David Greene.
Welcome to Secret Tantric, London’s finest VIP Massage agency. Since we first opened our doors, we have provided the ultimate erotic massage experience to innumerable clients, each one searching for the very best sensual massage in London. We come by this reputation honestly with a dynamic team of the city’s most beautiful masseuses.
CHAPTER 1 SEMESTER V PREVENTIVE-PEDIATRICS.pdfSachin Sharma
This content provides an overview of preventive pediatrics. It defines preventive pediatrics as preventing disease and promoting children's physical, mental, and social well-being to achieve positive health. It discusses antenatal, postnatal, and social preventive pediatrics. It also covers various child health programs like immunization, breastfeeding, ICDS, and the roles of organizations like WHO, UNICEF, and nurses in preventive pediatrics.
Navigating Challenges: Mental Health, Legislation, and the Prison System in B...Guillermo Rivera
This conference will delve into the intricate intersections between mental health, legal frameworks, and the prison system in Bolivia. It aims to provide a comprehensive overview of the current challenges faced by mental health professionals working within the legislative and correctional landscapes. Topics of discussion will include the prevalence and impact of mental health issues among the incarcerated population, the effectiveness of existing mental health policies and legislation, and potential reforms to enhance the mental health support system within prisons.
Global launch of the Healthy Ageing and Prevention Index 2nd wave – alongside...ILC- UK
The Healthy Ageing and Prevention Index is an online tool created by ILC that ranks countries on six metrics including, life span, health span, work span, income, environmental performance, and happiness. The Index helps us understand how well countries have adapted to longevity and inform decision makers on what must be done to maximise the economic benefits that comes with living well for longer.
Alongside the 77th World Health Assembly in Geneva on 28 May 2024, we launched the second version of our Index, allowing us to track progress and give new insights into what needs to be done to keep populations healthier for longer.
The speakers included:
Professor Orazio Schillaci, Minister of Health, Italy
Dr Hans Groth, Chairman of the Board, World Demographic & Ageing Forum
Professor Ilona Kickbusch, Founder and Chair, Global Health Centre, Geneva Graduate Institute and co-chair, World Health Summit Council
Dr Natasha Azzopardi Muscat, Director, Country Health Policies and Systems Division, World Health Organisation EURO
Dr Marta Lomazzi, Executive Manager, World Federation of Public Health Associations
Dr Shyam Bishen, Head, Centre for Health and Healthcare and Member of the Executive Committee, World Economic Forum
Dr Karin Tegmark Wisell, Director General, Public Health Agency of Sweden
How many patients does case series should have In comparison to case reports.pdfpubrica101
Pubrica’s team of researchers and writers create scientific and medical research articles, which may be important resources for authors and practitioners. Pubrica medical writers assist you in creating and revising the introduction by alerting the reader to gaps in the chosen study subject. Our professionals understand the order in which the hypothesis topic is followed by the broad subject, the issue, and the backdrop.
https://pubrica.com/academy/case-study-or-series/how-many-patients-does-case-series-should-have-in-comparison-to-case-reports/
Medical Technology Tackles New Health Care Demand - Research Report - March 2...pchutichetpong
M Capital Group (“MCG”) predicts that with, against, despite, and even without the global pandemic, the medical technology (MedTech) industry shows signs of continuous healthy growth, driven by smaller, faster, and cheaper devices, growing demand for home-based applications, technological innovation, strategic acquisitions, investments, and SPAC listings. MCG predicts that this should reflects itself in annual growth of over 6%, well beyond 2028.
According to Chris Mouchabhani, Managing Partner at M Capital Group, “Despite all economic scenarios that one may consider, beyond overall economic shocks, medical technology should remain one of the most promising and robust sectors over the short to medium term and well beyond 2028.”
There is a movement towards home-based care for the elderly, next generation scanning and MRI devices, wearable technology, artificial intelligence incorporation, and online connectivity. Experts also see a focus on predictive, preventive, personalized, participatory, and precision medicine, with rising levels of integration of home care and technological innovation.
The average cost of treatment has been rising across the board, creating additional financial burdens to governments, healthcare providers and insurance companies. According to MCG, cost-per-inpatient-stay in the United States alone rose on average annually by over 13% between 2014 to 2021, leading MedTech to focus research efforts on optimized medical equipment at lower price points, whilst emphasizing portability and ease of use. Namely, 46% of the 1,008 medical technology companies in the 2021 MedTech Innovator (“MTI”) database are focusing on prevention, wellness, detection, or diagnosis, signaling a clear push for preventive care to also tackle costs.
In addition, there has also been a lasting impact on consumer and medical demand for home care, supported by the pandemic. Lockdowns, closure of care facilities, and healthcare systems subjected to capacity pressure, accelerated demand away from traditional inpatient care. Now, outpatient care solutions are driving industry production, with nearly 70% of recent diagnostics start-up companies producing products in areas such as ambulatory clinics, at-home care, and self-administered diagnostics.
CRISPR-Cas9, a revolutionary gene-editing tool, holds immense potential to reshape medicine, agriculture, and our understanding of life. But like any powerful tool, it comes with ethical considerations.
Unveiling CRISPR: This naturally occurring bacterial defense system (crRNA & Cas9 protein) fights viruses. Scientists repurposed it for precise gene editing (correction, deletion, insertion) by targeting specific DNA sequences.
The Promise: CRISPR offers exciting possibilities:
Gene Therapy: Correcting genetic diseases like cystic fibrosis.
Agriculture: Engineering crops resistant to pests and harsh environments.
Research: Studying gene function to unlock new knowledge.
The Peril: Ethical concerns demand attention:
Off-target Effects: Unintended DNA edits can have unforeseen consequences.
Eugenics: Misusing CRISPR for designer babies raises social and ethical questions.
Equity: High costs could limit access to this potentially life-saving technology.
The Path Forward: Responsible development is crucial:
International Collaboration: Clear guidelines are needed for research and human trials.
Public Education: Open discussions ensure informed decisions about CRISPR.
Prioritize Safety and Ethics: Safety and ethical principles must be paramount.
CRISPR offers a powerful tool for a better future, but responsible development and addressing ethical concerns are essential. By prioritizing safety, fostering open dialogue, and ensuring equitable access, we can harness CRISPR's power for the benefit of all. (2998 characters)
The dimensions of healthcare quality refer to various attributes or aspects that define the standard of healthcare services. These dimensions are used to evaluate, measure, and improve the quality of care provided to patients. A comprehensive understanding of these dimensions ensures that healthcare systems can address various aspects of patient care effectively and holistically. Dimensions of Healthcare Quality and Performance of care include the following; Appropriateness, Availability, Competence, Continuity, Effectiveness, Efficiency, Efficacy, Prevention, Respect and Care, Safety as well as Timeliness.
1. An Overview of Clinical Analytics
Michael O. Bice
Health Informatics Consultant
2. Agenda
• Clinical informatics as context for clinical
analytics
• Uniqueness of medical data mining
• Define and describe the practice of clinical
analytics
• Challenges facing use of clinical analytics
• Tools used to analyze clinical data
• Use of clinical analytics in different healthcare
settings
• The future of clinical analytics
4. Uniqueness of Medical Data Mining
• Heterogeneity of medical data
▫ Raw medical data are voluminous and heterogeneous
▫ Medical data may be collected from various images, interviews
with the patient, laboratory data, and the physician’s
observations and interpretations
▫ All these components may bear upon the diagnosis, prognosis,
and treatment of the patient, and cannot be ignored
• Ethical, legal, and social issues
▫ Privacy and security considerations
▫ Fear of lawsuits
▫ Need to balance the expected benefits of research against
any inconvenience or possible injury to the patient
5. Uniqueness of Medical Data Mining
• Statistical philosophy: Methods of medical data
mining must address
▫ The heterogeneity of data sources
▫ Data structures
▫ The pervasiveness of missing values
• Special status of medicine
▫ Outcomes of medical care are life-or-death
▫ They apply to everybody
▫ Medicine is a necessity, not merely an optional
luxury, pleasure, or convenience
6. Definition of Clinical Analytics (CA)
• Clinical analytics encompasses
the capture and use of discrete
clinical data to identify and
measure quality, patient safety, or
service line efficiencies and
improvements
7. Promise of Clinical Analytics
• Through careful implementation of health
analytics, hospitals can transform unwieldy
amalgamations of data into information that
can:
▫ Improve patient outcomes
▫ Increase safety
▫ Enhance operational efficiency
▫ Support public health efforts
8. Promise of Clinical Analytics
• CA applications are designed to place:
▫ timely
▫ relevant
▫ actionable information
• Into the hands of all users with a
legitimate interest in it
9. Current Use of CA
• Collecting and leveraging clinical and claims data to
enhance patient care cost, safety and efficiency
• Data is looked at on a variety of levels
▫ A specific patient
▫ Population-based, such as data specific to a particular
physician or to a certain condition, such as diabetes or
hypertension
• Using rule sets from a wide variety of organizations
▫ Voluntary programs (the Leapfrog Group)
▫ Government sources (the Hospital Compare Database)
▫ Trade organizations (the Council of Teaching Hospitals or
the Society for Thoracic Surgeons)
10. Current Use of CA
• Much of the information that healthcare
organizations ultimately choose to report is
driven in one of three ways:
▫ Data that they are required to track by the
government or other external organizations
▫ Data that healthcare organizations choose to look
at that is driven by QA or cost containment
opportunities
▫ Information that is required for recertification of
professional staff
11. Types of CA Practitioners
• Pharmacists with formal informatics training
(e.g., Masters or Doctorate in Medical
Informatics or Informatics fellowship) or
extensive clinical informatics experience to
develop and maintain pharmacy content
• Physicians with informatics experience to
translate clinical guidelines and study protocols
into CDS interventions
• Doctoral-level medical informaticians
12. Types of CA Practitioners
• Registered nurses (RNs) with informatics
training and experience
• Dedicated software developers and project
managers without a clinical background
• Master’s in Health Informatics
• Master’s in Health Administration with
Concentration in Health Informatics
13. CA Continuum
• Data extraction tools (Bottom of Hierarchy)
▫ Collect data from existing databases
• Data warehouses and data marts
• Formatting tools and techniques
▫ Used to "cleanse" the data and convert it to
formats that can easily be understood
14. CA Continuum
• Enterprise reporting and analytical tools
▫ Online analytic process (OLAP) engines and
analytical application development tools are for
professionals who analyze data and perform
business forecasting, modeling and trend analysis
• Human intelligence tools (Top of Hierarchy)
▫ Human expertise, opinions and observations
15. CA Challenges
• Modern medicine generates, almost daily, huge
amounts of heterogeneous data. Those who deal
with such data understand that there is a widening
gap between data collection and data
comprehension.
• In industry, data are typically viewed as a critical
enterprise asset; medicine, in contrast, tends to view
data as a byproduct of operations
• Clinical analytics continues to be used primarily for
retrospective analyses, rather than real-time clinical
decision support.
16. CA Challenges
• Organizational, not data or financial concerns,
are holding back adoption. Primary obstacles to
widespread analytics adoption include:
▫ Knowing how to use analytics to improve the
business
▫ Management bandwidth due to competing
priorities
▫ Lack of skills internally
▫ Ability to get the data
▫ Existing culture discourages info sharing
17. CA Challenges
• Lack of use of tools to support the work of
clinical analytics
• Lack of money to hire additional appropriately
trained clinical informaticians
• Rapidly expanding regulatory reporting and
compliance requirements along with increasing
emphasis on quality measures
• Healthcare provider organizations are struggling
to understand how the government’s role in
clinical analytics is going to evolve in the future
18. Inventory of Tools and Best Practices
• A multidisciplinary team responsible for
creating and maintaining the clinical content
• An external repository of clinical content with
web-based viewer that allows anyone to review it
• An online, interactive, Internet-based tool to
facilitate content development and collaboration
19. Inventory of Tools and Best Practices
• An enterprise-wide tool to maintain the
controlled clinical terminology concepts
▫ The availability of a robust, controlled clinical
terminology(e.g., SNOMED for problems, LOINC
for lab results and ICD-10 for billing diagnoses,
etc.)
▫ Many controlled terminologies include some sort
of semantic network that maintains various types
of relationships among the clinical terms
20. Inventory of Tools and Best Practices
• Niche vendors that specialize in the development
of data warehouses or data mining to assist in
this type of analysis (See www. Explorys.com)
• Use of data warehouses for clinical purposes is
evolving
▫ According to data from the HIMSS Analytics™
Database, approximately 30% of U.S. hospitals
presently use a clinical data warehouse
▫ Usage is more widespread among hospital systems
and academic health centers
21. Case Studies (Duke UHS)
• Leveraging enterprise data through computerized
patient safety initiatives
▫ Integrated data warehouse
▫ Web-based safety dashboard
▫ Proactive detection and subsequent amelioration of
Clostridium difficile colitis rates
Prevented 158 potential cases of nosocomially acquired C
difficile colitis per year
Financial burden of C difficile colitis to range from $3669
to $7234 in additional hospital costs per infected patient,
which by conservative analysis translates into a total
savings of $578,968
22. Case Studies (Duke UHS)
• Improving the business cycle: the Duke intensive
care nursery
▫ Current and projected losses in the ICNursery
▫ Traditional cost-cutting not feasible
▫ Analysis suggested 4 areas for targeted
improvement: MD documentation, medical record
coding, revenue modeling, and 3rd party payments
▫ Current and retroactive profits recorded
23. Case Studies (Duke UHS)
• Leveraging health analytics for emerging health
issues
▫ Used its data warehouse to provide a highly
refined estimate of patients likely to need H1N1
vaccine (Swine Flu)
Inpatient status
Diagnosis of chronic disease
High–risk mothers and children
▫ Timely and accurate information to the state and
to better define DUHS strategy for vaccine
administration
24. Case Studies (Beth Israel Deaconess
Medical Center)
• Challenge
▫ Need for a CDS tool capable of identifying the
most appropriate imaging test for a specific
patient
BIDPO physicians had the capability to select from
2,000 orderable radiological studies, many of which
were state of the art technologies
The abundance of such options also resulted in
potentially inappropriate testing, false positives, and
potential risk to patients (e.g., contrast injections,
interventional procedures, and radiation exposure)
25. Case Studies (Beth Israel Deaconess
Medical Center)
• Solution
▫ An advanced CDS system with computerized
provider order entry (CPOE) and real-time insurer
authorization
▫ Create a natural language ordering vocabulary
▫ A web-based, physician-designed user interface
for Anvita Health’s imaging implementation was
then seamlessly integrated into BIDMC’s existing
EMR
26. Case Studies (Beth Israel Deaconess
Medical Center)
• Results
▫ CDS positively influenced up to 35% of all
ordering decisions, and up to 10% of high-tech
radiology decisions were changed
▫ CDS decreased inappropriate imaging, which
reduced overall cost trends for the hospital,
patients, and the health plan while increasing
quality
▫ CDS identified testing contraindications (e.g.,
contrast dye use) in patients at high risk for
adverse reactions
27. Future Considerations
• Early stages of an information revolution in
healthcare, as genomics, pharmacogenomics, and
point-of-care decision support converge in a new era
of personalized medicine
• Active investment in health analytics, data
integration, and data sharing are critical to creating
efficiencies (Improve Signal to Noise ratio)
• New approaches to data visualization and analysis
are neededhttp://visual.ly/learn/data-visualization-tools
28. Future Considerations
CA is the next wave of HIT–converting paper to
electronic impulses is a massive undertaking, but
clearly not sufficient
A widening gap between data collection and
data comprehension – An industry that is
drowning in data and starving for information and
knowledge
Conventional cost cutting may have run its course-need
for finely grained systems analysis (Duke UHS
example)
29. Future Considerations
Moving CA from few large academic medical
centers to general healthcare field (Few players
dominate the CA discussions)
Distinction between having information and
knowledge – and acting on it, either individually or
collectively
Evolving discipline with significant upside
potential
30. Pause and Reflect
• Why study CA and why now?
• What roles should the CEO, CFO and CIO play
in bringing CA expertise into the organization?
• How would you go about establishing CA
capability in your hospital?
• What skills and experience will you need to be
CA “job ready” upon graduation?
Editor's Notes
As you examine the literature, you find a mixture of terms used to describe “Clinical Analytics.” There are references to Business Intelligence (BI), Health Intelligence, Clinical Knowledge Management (CKM), Healthcare or Medical Data Mining, and Health Analytics. Suspect it is a function of a discipline that is young and evolving. We’ll stay with the use of Clinical Analytics (CA) throughout the presentation.
April 6, 2011
Revision: August 12, 2014
Source: AMIA Board White Paper Core Content for the Subspecialty of Clinical Informatics, JAMIA (2009)
Clinical informatics encompasses three spheres of activity:
1. Clinical care (i.e., the provision of clinical services to an individual patient),
2. The health system (i.e., the structures, processes, and incentives that shape the clinical care environment; this includes major health domains such as public health, population health, personal health, health professional education, and clinical research, in addition to clinical care),
3. Information and communications technology (i.e., the tools that enable the efficient capture, delivery, transmission, and use of data, information, and knowledge and the knowledge of how to apply those tools effectively).
K.J. Cios and G. W. Moore, Uniqueness of medical data mining, Artificial Intelligence in Medicine 26 (2002) 1–24
The major points of uniqueness of medical data may be organized under four general headings:
Heterogeneity: Raw medical data are voluminous and heterogeneous. Medical data may be collected from various images, interviews with the patient, laboratory data, and the physician’s observations and interpretations. All these components may bear upon the diagnosis, prognosis, and treatment of the patient, and cannot be ignored.
Ethical: The ethical, legal, and social limitations on medical data mining relate to privacy and security considerations, fear of lawsuits, and the need to balance the expected benefits of research against any inconvenience or possible injury to the patient.
K.J. Cios and G. W. Moore, Uniqueness of medical data mining, Artificial Intelligence in Medicine 26 (2002) 1–24
Statistical: Methods of medical data mining must address the heterogeneity of data sources, data structures, and the pervasiveness of missing values. In any large database, we encounter a problem of missing values. A missing value may have been accidentally not entered, or purposely not obtained for technical, economic, or ethical reasons.
Example: AMIA 10x10 Course Lesson 3.1 Slide 11 Missing clinical information during primary care visits (Smith, 2005) Finding-Information reported missing in 13.6% of clinical visits.
Status: Finally, medicine has a special status in science, philosophy, and daily life. The outcomes of medical care are life-or-death, and they apply to everybody. Medicine is a necessity, not merely an optional luxury, pleasure, or convenience.
Source: Jeffrey M Ferranti, et al, Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness J Am Med Inform Assoc 2010;17:136-143.
These applications, commonly known as business intelligence (BI), place timely, relevant, and actionable information into the hands of all users with a legitimate interest in it.
Source: Jeffrey M Ferranti, et al, Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness J Am Med Inform Assoc 2010;17:136-143.
These applications, commonly known as business intelligence (BI), place timely, relevant, and actionable information into the hands of all users with a legitimate interest in it.
Source: Clinical Analytics: Can Organizations Maximize Clinical Data? HIMSS Analytics (2010)
One example provided in this area is the Ongoing Professional Practice Evaluation (OPPE), which examines performance data for all practitioners with privileges on an on-going basis relative to their two-year reappointment process.
Dean F. Sittig, et al The state of the art in clinical knowledge management: An inventory of tools and techniques IJMI 79 (2010) 44–57
What types of people do you have to help manage your clinical knowledge? All of the organizations studied had one or more of the following types of people involved in the CKM process:
Source: Defining the Landscape: Data Warehouse and Mining Intelligence Continuum Copyright 2007 by the Healthcare Information and Management Systems Society.
At the bottom of the BI hierarchy are extraction and formatting tools which are also known as data-extraction tools. These tools collect data from existing databases for inclusion in data warehouses and data marts.
Thus the next level of the BI hierarchy is known as warehouses and marts.
Because the data come from so many different, often incompatible systems in various file formats, the next step in the BI hierarchy is formatting tools. These tools and techniques are used to "cleanse" the data and convert it to formats that can easily be understood in the data warehouse or data mart.
Next, tools are needed to support the reporting and analytical techniques. These are known as enterprise reporting and analytical tools. Online analytic process (OLAP) engines and analytical application development tools are for professionals who analyze data and perform business forecasting, modeling and trend analysis.
Human intelligence tools form the next level in the hierarchy and involve human expertise, opinions and observations to be recorded to create a knowledge repository. These tools are at the very top of the BI hierarchy and serve to amalgamate analytical and BI capabilities along with human expertise.
1. Modern medicine generates, almost daily, huge amounts of heterogeneous data. For example, medical data may contain CT scan, signals like ECG, clinical information like temperature, cholesterol levels, etc., as well as the physician's interpretation. Those who deal with such data understand that there is a widening gap between data collection and data comprehension. Computerized techniques are needed to help humans address this problem.
Source: Cios, Krzysztof J. (Ed.) Medical Data Mining and Knowledge Discovery (2001) http://www.springer.com/public+health/book/978-3-7908-1340-1
2. This latter view is not without promise, but in general this ‘byproduct’ is not being fully leveraged.
Source: Jeffrey M Ferranti, et al, Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness J Am Med Inform Assoc 2010;17:136-143.
Clinical Analytics in the World of Meaningful Use (February 2011) HIMSS Analytics™ White Paper P. 6
Dean F. Sittig, et al The state of the art in clinical knowledge management: An inventory of tools and techniques IJMI 79 (2010) 44–57
Further, the rapidly expanding regulatory reporting and compliance requirements along with increasing emphasis on quality measures (e.g., The Joint Commissions’ CORE Measures [27] and National Patient Safety
Goals [28] or Medicare’s Physician Quality Reporting Initiative (PQRI) [29], to name just a few…
Point #4 Source: Clinical Analytics: Can Organizations Maximize Clinical Data? HIMSS Analytics (2010)
Dean F. Sittig, et al The state of the art in clinical knowledge management: An inventory of tools and techniques IJMI 79 (2010) 44–57
We identified a variety of tools and current practices for CKM. After reviewing all of the responses to our survey and discussing the summarization of the data, we have identified the following tools and practices as the most widely used in organizations with successful CPOE and CDS implementations
Finding: All organizations had such a team and all agreed that these individuals were the most essential component of their CDS success. In addition, they stated that a transparent governance structure for all content-related decision making was also important.
Dean F. Sittig, et al The state of the art in clinical knowledge management: An inventory of tools and techniques IJMI 79 (2010) 44–57
SNOMED CT Systematized Nomenclature of Medicine -- Clinical Terms
Logical Observation Identifiers Names and Codes The purpose of LOINC® is to facilitate the exchange and pooling of clinical results for clinical care, outcomes management, and research by providing a set of universal codes and names to identify laboratory and other clinical observations.
ICD = International Classification of Diseases ICD 9 to ICD 10 The deadline for ICD 10 compliance is October 1, 2014 (See CMS post)
Source: Clinical Analytics: Can Organizations Maximize Clinical Data? HIMSS Analytics (2010)
More specifically, approximately 40 percent of hospitals with more than 500 beds use this technology, compared to 18 percent of hospitals with 100 beds or fewer.
HIMSSanalytics™ Database (www.himssanalytics.org) January 2011
Clinical Analytics in the World of Meaningful Use (February 2011) HIMSSanalytics™ White Paper P. 5
Source: Jeffrey M Ferranti, et al, Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness J Am Med Inform Assoc 2010;17:136-143.
We also present three case studies that illustrate the use of health analytics to leverage preexisting data resources to support improvements in patient safety and quality of care, to increase the accuracy of billing and collection, and support emerging health issues.
More importantly, our dynamic BI interface allows clinicians and leaders to analyze data at the level of the health system as a whole or in a service-specific manner. Using our Web-based safety dashboard, clinicians can identify cohorts of interest, display census-corrected aggregate safety statistics, and click on bars within graphs to ‘drill down’ into encounter-specific or event-specific details .
Of greater significance, however, are the rising estimates of serious complications of C difficile infection (ie, surgery, prolonged hospitalization, intensive care services) and the case fatality rate of about 2.2%,40 meaning that the ability to forestall such infections has serious implications for patient wellbeing.
Source: Jeffrey M Ferranti, et al, Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness J Am Med Inform Assoc 2010;17:136-143.
As is the case at many institutions, the DUHS data warehouse was originally designed as a financial system and has only recently been used to support safety, research, and QI.
Traditional cost-cutting strategies were not feasible, because nearly 75% of costs were due to personnel, leaving only 25% of costs amenable to reduction through reduced resource utilization.
Source: Jeffrey M Ferranti, et al, Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness J Am Med Inform Assoc 2010;17:136-143.
In the wake of a declaration of a pandemic of H1N1 influenza (‘swine flu’) by the WHO in the spring of 2009,45 the DUHS faced the problem of estimating the amount of vaccine it would need to request in order to meet the needs of the communities it serves. In doing so, the DUHS sought to avoid two undesirable outcomes: (1) ordering too little vaccine, resulting in local shortages and diminished protection among unvaccinated patients and customers served by Duke, or (2) ordering too much vaccine, resulting in waste and potentially contributing to shortages in other locations, as well as incrementally adding to stress on the national vaccine distribution network.
Source: http://www.anvitahealth.com/pdf/Case%20Study_Anvita%20Health%20Partners%20with%20Beth%20Israel%20Deaconess%20Medical%20Center.pdf
Richard Parker, M.D., Medical Director of BIDPO “Anvita Health is providing a breakthrough CDS solution to help confront a major challenge facing physicians today – the abundance of a bewildering number of high tech imaging choices, some of which are extremely powerful, and others which are expensive and risky, yet may not yield a rapid diagnosis.”
Source: Jeffrey M Ferranti, et al, Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness J Am Med Inform Assoc 2010;17:136-143.
We are in the early stages of a revolution in healthcare, as genomics, proteomics, pharmacogenomics, and point-of-care decision support converge in a new era of personalized medicine.
Without timely and appropriate investment in data infrastructure, however, the potential benefits of this revolution may be impeded
BI tools allow us to continuously monitor health system performance, separate signals from noise, and scientifically evaluate the return on investment provided by QI initiatives. As patient populations grow and operating budgets are increasingly constrained, such efficiencies will be vital to the success of healthcare institutions.
Dave Fiser’s recent comment-Need CA competent people (Per Becca Meehan)