Centralized monitoring is becoming an attractive alternative to traditional on-site clinical trial monitoring. It allows monitoring of data in real time using electronic systems to identify risks and issues early. Some sponsors are slow to adopt it due to concerns over change management, staff resistance to new roles, and desire to fully validate the process through pilots before widespread use. Centralized monitoring can achieve many of the same goals as on-site monitoring but in a more efficient, cost-effective manner by reducing routine on-site visits and optimizing monitor time.
4 Strategies to Influence Digital Health Approaches in Clinical Research StudiesJohn Reites
Drug Information Association (DIA) 2016 Conference presentation by John Reites on June 26, 2016. Session entitled; "Digital Health Debate" including this presentation on the four strategies to influence digital health approaches in clinical research studies.
Lisa Annaly, Head of Provider Analytics at the Care Quality Commission, discusses lessons learned from the CQC as they have worked to monitor care quality over time.
Monitoring quality of care: making the most of dataNuffield Trust
Chris Sherlaw-Johnson, Senior Research Analyst at the Nuffield Trust, introduced the Monitoring quality of care conference and gives an overview of some of the approaches that we've been using at the Trust to identify where care quality has been improving, especially for frail and older people.
Evolution in the Role of Patient Participation in Clinical ResearchCraig Lipset
Presentation by Craig Lipset at Precision Medicine World Congress (Palo Alto CA, 24 January 2020).
This presentation shares a "top 10 list" of places where patient participation in research is facing radical change for the better.
4 Strategies to Influence Digital Health Approaches in Clinical Research StudiesJohn Reites
Drug Information Association (DIA) 2016 Conference presentation by John Reites on June 26, 2016. Session entitled; "Digital Health Debate" including this presentation on the four strategies to influence digital health approaches in clinical research studies.
Lisa Annaly, Head of Provider Analytics at the Care Quality Commission, discusses lessons learned from the CQC as they have worked to monitor care quality over time.
Monitoring quality of care: making the most of dataNuffield Trust
Chris Sherlaw-Johnson, Senior Research Analyst at the Nuffield Trust, introduced the Monitoring quality of care conference and gives an overview of some of the approaches that we've been using at the Trust to identify where care quality has been improving, especially for frail and older people.
Evolution in the Role of Patient Participation in Clinical ResearchCraig Lipset
Presentation by Craig Lipset at Precision Medicine World Congress (Palo Alto CA, 24 January 2020).
This presentation shares a "top 10 list" of places where patient participation in research is facing radical change for the better.
Accelerate and Integrate Digital Health InnovationJohn Reites
4 strategies to influence and execute digital health approaches. Presented on 23 Mar 2016 by John Reites at the Data 4 Decisions Conference in Raleigh, NC.
Mark Ramsey, Former CDAO at GlaxoSmithKline, discusses clinical trials data, health tech, and moving your company and employees forward by enhancing analytics know how.
Check out the full presentation here: https://www.tamr.com/7-steps-for-boosting-rd-outcomes/
Through the use of case studies, we demonstrate how our system solves important problems in clinical trials while ensuring compliance, data integrity and overall performance.
This Slideshare discusses the current state, technical and workflow challenges, and the future state of Patient Generated Health Data. Learn more: https://accntu.re/2KeGkZ6
Late Binding: The New Standard For Data WarehousingHealth Catalyst
Join Dale Sanders as he explains the concepts behind the Late-Binding (TM) Data Warehouse for healthcare. In this webinar, Dale covers 5 main concepts including 1) The history and concept of "binding" in software and data engineering, 2) Examples of data binding in healthcare, 3) the two tests for early binding (comprehensive and persistent agreement), 4) the six points of binding in data warehouse design (including a comparison of data modeling and late binding), and 5) the importance of binding in analytic progressions (including the eight levels of analytic adoption in healthcare).
mHealth Israel_Growth Opportunities in Clinical Trial Execution_Craig LipsetLevi Shapiro
Craig Lipsent, former Worldwide Head of Clinical Innovation at Pfizer, presents to the mHealth Israel Community, Feb, 2020. Theme: Clinical trials are vital for developing new medicines but they are broken. Clinical trial trends include the increasing attention and investment in participant & investigator experience
Digitization and innovative data capture. Forecast for clinical trials will be decentralized, distributed, democratized and disruptive.
Medical research:-rebuilt,-retooled -and -rebooted pptPuja Roy
Medical Research: Rebuilt, Retooled and Rebooted An early stage mobile medical device company developing a human-centered suite of consumer products using science and technology to empower everyday people to monitor and better understand their own health—anytime, anywhere.
Birmingham Heartlands Hospital in the U.K. has been using the Roche Digital Pathology portfolio to transform tissue diagnostics. They have streamlined collaboration, especially for their multi-disciplinary meetings and they have used digital technology in the education of new pathologists. Lab workflow has become more efficient and pathologists are now more seamlessly connected.
RTDPC-DP-0034b 6021A-3
Digital Pathology streamlines tissue diagnostics and helps protect patient sa...Roche Tissue Diagnostics
RZ Tienen Hospital became one of the first hospitals in Belgium, and one of the first in Europe, to implement and integrate digital pathology into daily operations. They have transformed their AP lab and are now able to manage caseloads remotely, facility MDT oncology meetings and enhance collaboration with colleagues. The benefits of digital pathology have been well recognized and RZ Tienen expects continued growth in this area.
Will I see you in Philadelphia next week? In case you don’t already know, I’ve been invited to speak at CBI’s Risk-Based Trial Management and Monitoring Conference.
I’m going to be sharing real world, pragmatic guidance that you can implement immediately to effectively influence your clinical trial performance.
My presentation, Practical Usage of KRIs and QTLs in Clinical Trials, will take place next Thursday, November 14th at 9:45am. I’m going to share with you:
• How to identify and close the gaps between risks and KRIs
• What the difference is between KRIs and QTLs, and how to use them effectively
• Useful examples of Centralized Monitoring findings from open data
• How to detect, combat and prevent fraud and sloppiness at an early stage
• How AI and ML advance risk-based approaches
So I can’t wait to see you at this informative and fun-filled industry expert forum,
– Artem Andrianov, CEO Cyntegrity
Delivering Quality Through eHealth and Information TechnologyNHSScotlandEvent
Using information to improve the quality of care is becoming increasingly important. This session will highlight how the new eHealth Strategy links to the quality agenda and the benefits and successes of three innovative eHealth tools.
Developing a Strategic Analytics Framework that Drives Healthcare TransformationTrevor Strome
About the presentation.
Based on Chapter 3 of my book "Healthcare Analytics for Quality and Performance Improvement", this presentation describes the key components of a strategic analytics framework that can enable your healthcare organization to leverage data from source-systems to achieve its quality, safety, and performance improvement goals.
What is an analytics strategy?
Analytics is currently a very “trendy” topic. The internet is scattered with many buzzwords, marketing angles, white papers, and opinions on the topic of healthcare analytics. With all this “noise”, it is easy to get distracted from what is actually required, from an analytics perspective, by your organization. An analytics strategy helps cut through the noise and keep focus on what is important for the organization. Regardless of what the latest “buzz” is, your analytics strategy will enable your organization to Invest now for what is required now, and invest later for what is required in the future.
An analytics strategy helps ensure that analytics development and capabilities are in alignment with enterprise quality and performance goals and helps avoids the “all dashboard, no improvement” syndrome. Furthermore, a well formed strategy document helps to achieve optimal use of analytics within a healthcare organization and can mean the difference between a “collection of reports” versus a high-value information resource.
An analytics strategy can rarely stand on its own. In general, the analytics strategy should use as input an organization’s Quality Improvement (QI) strategy and should be used to inform an organization’s Business Intelligence (BI) or Information Technology (IT) strategy. The analytics strategy is an important input to technical strategies because analytics, after all, can involve a sophisticated use of data and technology. Requirements for analytics may trigger a cascade of enhancements throughout other components of IT and BI (i.e., reporting, data storage, ETL, etc)
The document is intended to accompany Chapter 3, “Developing an Analytics Strategy to Drive Change”, so please refer to the chapter for further information about developing an analytics strategy.
Accelerate and Integrate Digital Health InnovationJohn Reites
4 strategies to influence and execute digital health approaches. Presented on 23 Mar 2016 by John Reites at the Data 4 Decisions Conference in Raleigh, NC.
Mark Ramsey, Former CDAO at GlaxoSmithKline, discusses clinical trials data, health tech, and moving your company and employees forward by enhancing analytics know how.
Check out the full presentation here: https://www.tamr.com/7-steps-for-boosting-rd-outcomes/
Through the use of case studies, we demonstrate how our system solves important problems in clinical trials while ensuring compliance, data integrity and overall performance.
This Slideshare discusses the current state, technical and workflow challenges, and the future state of Patient Generated Health Data. Learn more: https://accntu.re/2KeGkZ6
Late Binding: The New Standard For Data WarehousingHealth Catalyst
Join Dale Sanders as he explains the concepts behind the Late-Binding (TM) Data Warehouse for healthcare. In this webinar, Dale covers 5 main concepts including 1) The history and concept of "binding" in software and data engineering, 2) Examples of data binding in healthcare, 3) the two tests for early binding (comprehensive and persistent agreement), 4) the six points of binding in data warehouse design (including a comparison of data modeling and late binding), and 5) the importance of binding in analytic progressions (including the eight levels of analytic adoption in healthcare).
mHealth Israel_Growth Opportunities in Clinical Trial Execution_Craig LipsetLevi Shapiro
Craig Lipsent, former Worldwide Head of Clinical Innovation at Pfizer, presents to the mHealth Israel Community, Feb, 2020. Theme: Clinical trials are vital for developing new medicines but they are broken. Clinical trial trends include the increasing attention and investment in participant & investigator experience
Digitization and innovative data capture. Forecast for clinical trials will be decentralized, distributed, democratized and disruptive.
Medical research:-rebuilt,-retooled -and -rebooted pptPuja Roy
Medical Research: Rebuilt, Retooled and Rebooted An early stage mobile medical device company developing a human-centered suite of consumer products using science and technology to empower everyday people to monitor and better understand their own health—anytime, anywhere.
Birmingham Heartlands Hospital in the U.K. has been using the Roche Digital Pathology portfolio to transform tissue diagnostics. They have streamlined collaboration, especially for their multi-disciplinary meetings and they have used digital technology in the education of new pathologists. Lab workflow has become more efficient and pathologists are now more seamlessly connected.
RTDPC-DP-0034b 6021A-3
Digital Pathology streamlines tissue diagnostics and helps protect patient sa...Roche Tissue Diagnostics
RZ Tienen Hospital became one of the first hospitals in Belgium, and one of the first in Europe, to implement and integrate digital pathology into daily operations. They have transformed their AP lab and are now able to manage caseloads remotely, facility MDT oncology meetings and enhance collaboration with colleagues. The benefits of digital pathology have been well recognized and RZ Tienen expects continued growth in this area.
Will I see you in Philadelphia next week? In case you don’t already know, I’ve been invited to speak at CBI’s Risk-Based Trial Management and Monitoring Conference.
I’m going to be sharing real world, pragmatic guidance that you can implement immediately to effectively influence your clinical trial performance.
My presentation, Practical Usage of KRIs and QTLs in Clinical Trials, will take place next Thursday, November 14th at 9:45am. I’m going to share with you:
• How to identify and close the gaps between risks and KRIs
• What the difference is between KRIs and QTLs, and how to use them effectively
• Useful examples of Centralized Monitoring findings from open data
• How to detect, combat and prevent fraud and sloppiness at an early stage
• How AI and ML advance risk-based approaches
So I can’t wait to see you at this informative and fun-filled industry expert forum,
– Artem Andrianov, CEO Cyntegrity
Delivering Quality Through eHealth and Information TechnologyNHSScotlandEvent
Using information to improve the quality of care is becoming increasingly important. This session will highlight how the new eHealth Strategy links to the quality agenda and the benefits and successes of three innovative eHealth tools.
Developing a Strategic Analytics Framework that Drives Healthcare TransformationTrevor Strome
About the presentation.
Based on Chapter 3 of my book "Healthcare Analytics for Quality and Performance Improvement", this presentation describes the key components of a strategic analytics framework that can enable your healthcare organization to leverage data from source-systems to achieve its quality, safety, and performance improvement goals.
What is an analytics strategy?
Analytics is currently a very “trendy” topic. The internet is scattered with many buzzwords, marketing angles, white papers, and opinions on the topic of healthcare analytics. With all this “noise”, it is easy to get distracted from what is actually required, from an analytics perspective, by your organization. An analytics strategy helps cut through the noise and keep focus on what is important for the organization. Regardless of what the latest “buzz” is, your analytics strategy will enable your organization to Invest now for what is required now, and invest later for what is required in the future.
An analytics strategy helps ensure that analytics development and capabilities are in alignment with enterprise quality and performance goals and helps avoids the “all dashboard, no improvement” syndrome. Furthermore, a well formed strategy document helps to achieve optimal use of analytics within a healthcare organization and can mean the difference between a “collection of reports” versus a high-value information resource.
An analytics strategy can rarely stand on its own. In general, the analytics strategy should use as input an organization’s Quality Improvement (QI) strategy and should be used to inform an organization’s Business Intelligence (BI) or Information Technology (IT) strategy. The analytics strategy is an important input to technical strategies because analytics, after all, can involve a sophisticated use of data and technology. Requirements for analytics may trigger a cascade of enhancements throughout other components of IT and BI (i.e., reporting, data storage, ETL, etc)
The document is intended to accompany Chapter 3, “Developing an Analytics Strategy to Drive Change”, so please refer to the chapter for further information about developing an analytics strategy.
In the past decade, there has been a significant increase in the use of Data Monitoring
Committees (DMC) and Adaptive Designs (AD) in clinical trials. While the monitoring of safety
data by a formal committee is not required for all clinical trials, it has become the norm to have
a formal DMC conduct periodic safety reviews for any controlled trial that evaluates treatments
intended to prolong life or reduce risk of major adverse health outcomes, or for trials that
compare rates of mortality or major morbidity. Confirmatory, pivotal, and adaptive design trials
have more complex operational issues requiring an external and independent DMC. The DMC
may have access to unblinded interim data, be required to make expert recommendations
about how the trial should continue, and then ensure that planned adaptations are
implemented as outlined in the protocol without involving the sponsor or exposing it to
unblinded data or results.
This added complexity creates a challenge and a question: how can the DMC, statisticians, and
sponsor effectively communicate, share blinded and unblinded data, perform analyses, and
implement adaptations without introducing operational bias or compromising the integrity of
the trial? One solution is to utilize a sophisticated computer system that can provide the
security and necessary firewalls to ensure that interim data is only accessible to those it is
intended for, that the rules and processes outlined in the protocol and DMC charter are
enforced, and that communication between the DMC and sponsor is effectively facilitated while
protecting the integrity of the trial and preventing the introduction of operational bias.
The system must also provide an audit trail that tracks “who saw what and when” providing
evidence to regulatory authorities that the protocol was strictly followed with a minimal
possibility of bias. This white paper describes the computer system, ACES, which Cytel has built,
that makes all of this possible. ACES (Access Control Execution System) has been purpose-built
to address the operational complexities inherent in adaptive design and pivotal clinical trials.
Risk Based Monitoring in Clinical Trials.ClinosolIndia
Risk-based monitoring (RBM) is a monitoring strategy in clinical trials that aims to improve the quality and efficiency of data collection while reducing costs and burden on study participants. Rather than conducting monitoring activities at fixed intervals, RBM utilizes a risk assessment approach to identify areas of the study that are at higher risk of errors or deviations from the protocol and focuses monitoring efforts on those areas.
The RBM process begins with a risk assessment, which involves identifying potential risks to the study's data integrity, participant safety, and study conduct. This may include risks related to patient enrollment, data collection, adverse event reporting, or protocol compliance. Based on the risk assessment, the study team creates a risk management plan that outlines the monitoring strategy to be employed throughout the trial.
In RBM, monitoring activities are targeted to focus on the areas of the study that present the highest risk. For example, if a study has a high risk of data entry errors, the monitoring plan may include a more intensive review of data entry activities or require that data be entered in real-time, so errors can be identified and corrected more quickly.
RBM can be facilitated through several tools, such as centralized monitoring, key risk indicator (KRI) dashboards, or data analytics. Centralized monitoring allows for remote review of study data by a team of experts who can identify trends and issues more efficiently. KRIs are pre-defined metrics used to track performance and detect areas of concern, allowing for proactive management of risks. Data analytics can identify unusual patterns or outliers in the data, enabling the study team to focus on those areas of concern.
RBM is a dynamic process that involves ongoing evaluation of the study's risk profile and adjusting the monitoring strategy accordingly. By focusing monitoring efforts on the areas of the study that pose the highest risk, RBM can improve data quality and participant safety, while reducing monitoring costs and burden.
Defining a Central Monitoring Capability: Sharing the Experience of TransCele...www.datatrak.com
Central monitoring, on-site monitoring, and off-site monitoring provide an integrated approach to clinical trial quality management. TransCelerate distinguishes central monitoring from other types of central data review activities and puts it in the context of an overall monitoring strategy. Any organization seeking to implement central monitoring will need people with the right skills, technology options that support a holistic review of study-related information, and adaptable processes. There are different approaches actively being used to implement central monitoring. This article provides a description of how companies are deploying central monitoring, as well as samples of the workflows that illustrate how some have implemented it. The desired outcomes include earlier, more predictive detection of quality issues. This paper describes the initial implementation steps designed to learn what organizational capabilities are necessary.
Risk-based Monitoring Strategies for Improved Clinical Trial PerformanceCognizant
To address draft regulatory guidance for risk-based clinical trial monitoring, sponsors should consider strategies that utilize social, mobile, analytics and cloud technologies to create responsive methodologies that satisfy both the spirit and the letter of these new guidelines.
Overview of Risk Based Monitoring in Clinical Trial ProcessesEditorIJTSRD1
Risk based monitoring RBM has emerged as a transformative approach in clinical trial processes. This paper provides an overview of RBM and its impact on the field of clinical research. By moving away from traditional on site monitoring and adopting a targeted and efficient approach, RBM has demonstrated numerous benefits in terms of cost effectiveness, data quality, and patient safety. This abstract summarizes the key findings discussed in the conclusion. The proactive identification and management of risks throughout the trial lifecycle have led to improved decision making, increased study participant compliance, and enhanced overall trial success rates. With advancing technology, RBM approaches are expected to evolve further, allowing for greater optimization and streamlining of clinical trial processes. The abstract concludes by emphasizing the potential of risk based monitoring to shape the future of clinical research and contribute to the development of safe and effective therapies for patients worldwide. Kelam Himasri | Sankara Narayanan. K "Overview of Risk-Based Monitoring in Clinical Trial Processes" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd58586.pdf Paper URL: https://www.ijtsrd.com.com/pharmacy/pharmacy-practice/58586/overview-of-riskbased-monitoring-in-clinical-trial-processes/kelam-himasri
Risk Based Monitoring in Clinical trials_Aishwarya Janjale.pptxClinosolIndia
Risk-Based Monitoring (RBM) in clinical trials represents a departure from traditional, one-size-fits-all monitoring approaches. This innovative strategy tailors monitoring activities to the specific risks associated with a trial, optimizing resource utilization and enhancing data quality. This article explores the key principles, benefits, and challenges of RBM, illustrating its transformative impact on the landscape of clinical trial oversight.
Key Principles:
Risk Identification and Assessment:
RBM begins with a comprehensive assessment of potential risks to data integrity, patient safety, and study endpoints. These risks are identified based on factors such as study complexity, patient population, and investigational product characteristics.
MedTech clinical data collection problems have been found throughout our ten years of work with over 250 medical device studies from across the globe. We keep running across these seven hazards while working in the MedTech business and clinical operations.
TRI was founded as a subsidiary of Triumph Consultancy Services in 2013, following 12 years of consulting to the clinical trial industry. TRI has been evaluating the specific challenges facing the industry when implementing a risk-based monitoring strategy and the various approaches and products being utilized by organizations as they move into the RBM arena. This paper aims to summarize our findings and provide guidance as to how the main challenges can be overcome.
Safety & Regulatory Solutions for Small and Medium-sized Life Science Organiz...Covance
A key issue for small and medium-sized enterprises is the optimal utilization of their limited resources for moving their product pipeline through clinical development, and launching and marketing their approved product(s). This is further heightened as both clinical trials and post-marketing activities continue to grow in complexity and scope due to stringent regulatory pressures, patient involvement and globalization. Yet companies face overwhelming pressure to get their product to market as quickly as possible.
Integrate RWE into clinical developmentIMSHealthRWES
With greater application of RWE throughout the pharmaceutical
lifecycle, learnings are emerging that offer guidance for
approaches to derive the maximum value. This article captures
the author’s experience at a leading international biotech, with
insights for smoothing RWE assimilation into clinical
development and realizing the benefits it brings.
Patients Recruitment Forecast in Clinical TrialsCognizant
Inaccurate patient recruitment forecasts for clinical trials cost pharmaceuticals and medical device manufacturers a huge amount of resources each year. We offer descriptions and examples of applying stochastic and non-stochastic approaches to increase accuracy in this crucial stage of drug testing.
The Role of Technology in Streamlining Clinical Trial ProcessesClinosolIndia
Technology plays a significant role in streamlining clinical trial processes, enhancing efficiency, data quality, and participant engagement. Here are some key areas where technology contributes to the optimization of clinical trials