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Laurie Lafleur

April 28, 2022 By Laurie Lafleur Leave a Comment

Paragon subject matter experts have served healthcare industry for over 30 years and bring more than 200 years of collective experience. Working with various healthcare providers and implementation methodologies, the Paragon team has identified that smooth software adoption with a focus on continuous improvement is one of the most significant gaps in the industry. In response, Strings professional services were designed to break the status quo by delivering a new, more collaborative approach to software implementation, adoption, and optimization.

Overcoming Analysis Paralysis

In an Enterprise Imaging project there may be hundreds of Key Performance Indicators (KPIs) identified; however, only a handful are deemed relevant and actionable for daily monitoring and alerting. There are known risks with analytics solution adoption when an overwhelming amount of data and reporting is flooded to the User Interface (UI), especially in the early stages. Analytics solutions are only as effective as the user’s ability to comprehend the data and apply it in daily alerting/reporting.

This is why seasoned Paragon experts collaborate closely with key stakeholders to identify the most relevant initial KPIs and work together to expand that list as the overall solution and team matures. By ensuring each Enterprise Imaging solution is architected correctly and the most appropriate KPIs are closely monitored, healthcare IT teams can more effectively assess application performance, data accessibility and quality, and critical operations metrics.

Avoiding Alert Fatigue

Strings by Paragon implementation experts strongly value the process of collectively defining KPIs. This approach creates an organizational prioritization of what is critical in the monitoring/alerting phase and what might be more appropriate for a dashboard or regular reporting. For instance, Application Performance Monitoring (APM) could generate a broad range of alerts, but only a tiny percentage could be considered critical based on the organization’s dataflow design. Strings experts work together with the customer to establish a weighted approach so that alerting is beneficial – not overwhelming to an administrator. One of the most significant risks with any analytics software is the flooding of data and reporting – where administrators find it more of a daily task versus a tool. Designing and implementing short-term and long-term KPIs could make or break the solution in the early user adoption phase.

Continuous Improvement Has No Finish Line!

Implementation and adoption of Strings by Paragon is a starting point, not the finish line! Healthcare organizations are overwhelmed with various industry challenges, and analytics reporting solutions that create additional work with minimal returns are rarely succesful. The primary objective of Strings services is to ensure that monitoring and alerting are constantly evaluated and measured to ensure the best possible outcomes for your Enterprise Imaging program. Using a regular, agreed upon cadence (e.g. daily, weekly, monthly) Strings experts take a collaborative approach to assessing each active KPI and fine-tune it with administrators to yield maximum results. In the early stages of adopting a new analytics tool, it is critical that end-users are not intimated by the solution but find it helpful and regularly examine its functionality. One of the service offerings is having Strings experts generate a weekly Monitoring Summary Report capturing all triggered alerts. The report is reviewed with the customer for root cause analysis and issue resolution plan. The customer is engaged throughout the analysis cycle and is left more educated about the solution and the issue resolution path. The goal is to empower the end-user further to understand their environment and Strings as an effective tool.

Building a Strong, Long-Term Relationship

Strings by Paragon takes pride in establishing a long-term relationship with its customers. Whether the customer has limited technical resources, or is a highly sophisticated user, the ultimate goal is to continue to innovate together. The Healthcare industry is constantly changing, and data mining/analysis is becoming an absolute need for organizations to stay competitive. Strings experts are committed to optimizing Enterprise Imaging software and working together to innovate new, novel workflow solutions. Establishing a long-term partnership is the key to accomplishing both objectives. The more we know about each other, the more gaps can be identified with opportunities to improve.

Interested in learning more about how Strings by Paragon delivers analytics as a managed service? Subscribe to our blog to learn more.



Filed Under: Uncategorized Tagged With: analytics, analytics-as-a-managed-service, application monitoring, Enterprise Imaging, enterprise imaging analytics, healthcare analytics, key performance indicators, performance monitoring

April 5, 2022 By Laurie Lafleur Leave a Comment

The progressive growth of utilizing data analytics solutions in healthcare settings has facilitated clinical and operational use cases. With that said, large healthcare systems still face significant challenges when trying to understand their complex multi-vendor technology networks. Although there is an abundance of application performance monitoring solutions being used in healthcare settings, there are gaps when trying to make connections between performance monitoring and monitoring system health.

Paragon Consulting Partners’ one-of-a-kind data analytics, Strings by Paragon, is a data analytics platform that helps healthcare IT administrators to better understand the data related to their clinical workflows, the applications being used, and the equipment that supports them. By dynamically collecting and analyzing data from disparate sources, Strings can simplify the management of intricate multi-vendor technology ecosystems. From there, it can analyze and establish relationships and correlations across sources. Enrichment algorithms can be implemented to further analyze data, thereby providing increasingly valuable insights. This enriched data can also be used to make predictions on future trends which can be monitored for any inconsistencies, ultimately helping clients take a more actionable approach to optimizing system, application and clinical workflows. So, how exactly are all these unique features achieved?

What Makes Strings Unique and Special?

Data Collection and Banding

Strings by Paragon is purpose-built to monitor system health and operations. To accomplish this, Strings can pull data across disparate systems and applications, making it easier for users to obtain a more complete picture of their applications, clinical workflows, and operations. To effectively collect data across a multi-vendor healthcare system, Strings  has leveraged an advanced graphing database, which  applies graph theory, a mathematical structure that is used to model complex relationships between objects that belong to dynamic systems that have many moving parts.

In comparison to traditional relational database management systems, graphing databases do not require a pre-defined schema. Data elements within them  can be defined with any number of attributes. This makes it much easier to update attributes and create new relationships between data elements. This means that not only can Strings collect data from multiple systems and applications, but it can also dynamically band these data elements together to form meaningful relationships. As data elements are being banded across systems and applications, we can begin to gain a better understanding of the end-user experiences as they interact with various application systems. Additionally, data banding helps to evaluate the impact any infrastructure bottlenecks have on the end-user’s ability to deliver patient care.

Data Enrichment and Discovery

Strings by Paragon goes beyond simply modeling data. It has applied enrichment algorithms to help answer questions and gain insights about the complexity of multi-vendor technology ecosystems. Through these algorithms, Strings can analyze and enrich the data to understand more about the data elements themselves and how they interact with each other. For example, it can create procedure attributes to enhance the monitoring of archived medical imaging studies. Various event log entries being tracked across applications and web servers can be categorized by event type and then monitored. With these new data attributes, new connections and relationships can be made. By being knowledgeable about the relationships and data structures that comprise the complex infrastructure, decision-making is greatly improved.

String takes it a step further by applying predictive graph algorithms to discover even more. For example, algorithms can be applied to identify communities where data entities have substantial interactions that can further reveal tight node clusters or isolated node groups. More specifically, relevant interactions and behaviours made by application end-users can be grouped together to predict future behaviours and preferences. By exploring these interactions and relationships, predictions can be made about future trends. These predictive trends and data enrichments can be continuously monitored which provides our clients the ability to track system performance and take proactive measures towards preventing adverse system events before clinical workflows are negatively impacted.

Tying it All Together

With these unique features, Strings by Paragon brings together data on clinical and system performance to monitor and measure the possible positive or negative impacts on each other. Not only does Strings leverage advanced software capabilities, but Paragon subject matter experts can also help evaluate the unique challenges healthcare organizations face to add more customization for Strings.

Interested in how Strings by Paragon actually does it? Subscribe to our blog to learn more about what’s under the hood in our next instalment: The How: The Magic Behind Strings by Paragon.



Filed Under: Uncategorized

March 2, 2022 By Laurie Lafleur Leave a Comment

“Do more with less.” “Leverage our investments.” “Execute the strategy.” These are the comments we hear from our clients every day.

Following a decade of extensive investment into data consolidation efforts across PACS, VNAs, EHRs, and other IT systems, healthcare providers are hyper-focused to make the most of these investments and bring their vision to reality. With a consolidated set of vendor solutions, health systems seek to drive user adoption, demonstrate their clinical value, and improve the delivery of patient care – all in alignment with a broader strategy.  

The result of these efforts is emerging. Healthcare providers are consolidating clinical workflows across fewer applications, thereby reducing the number of data repositories and IT systems to maintain. However, while consolidation efforts have simplified application/system management, achieving interoperability among/across IT environments remains complex, prompting internal discussion among imaging teams around necessary skillsets and improved resource scalability. This evolution has led to an increased demand for expertise in workflow optimization across clinical, operational, and system workflows and the ability to implement the right changes as part of the broader strategy: do more with less and leverage our investments. To deliver on the needs of our clients – achieving greater outcomes with fewer IT systems – Paragon Consulting Partners recognized that the ability to measure and monitor the impact of this transformation is critical to the success of our clients and their ability to deliver the best possible care.  

Strings by Paragon is a first-of-its-kind data analytics platform. Designed to aggregate, measure and monitor user and application workflows, it was created to support our clients’ needs by filling a critical gap in performance monitoring and operation analytics. Most healthcare providers have no shortage of application performance monitoring (APM) solutions, but identifying infrastructure spikes and the ability to monitor system performance counters isn’t enough. Users don’t just need to know that there was a CPU spike at a given date and time, they need to understand why it occurred in the first place and trace it back to its origin so they can act on it. Strings by Paragon offers a more holistic and comprehensive approach to monitoring system health and operations. It was designed to understand both the utilization and tendencies of clinical users, the solutions they use, and the equipment that supports them, and to then correlate those data elements to system infrastructure. To accomplish this, data needs to be pulled from across disparate systems and applications. Data analytics from a single information system, PACS, or VNA, is not enough to form a complete end-to-end picture of application and clinical workflows. When data is dynamically banded across application data elements we can begin to understand the true end-user experience and the impact an infrastructure bottleneck has on the user’s ability to deliver the best possible care.

Today our clients can measure and monitor application and user workflows to clear a daily load of studies, to identify the most optimal click pattern, and to reduce burnout and improve efficiency. Our clients better understand modality utilization, the various stages of turnaround time, and can justify where investment may improve clinical access and care. Today, we are enabling our clients to do more with less, make the most of their consolidation efforts, and execute the strategies they have worked tirelessly to design. With a unique ability to extract meaningful information from a sea of data, Strings by Paragon is simplifying the management of complex multi-vendor technology ecosystems and enabling an actionable approach to performance.

Interested in how Strings by Paragon actually does it? Subscribe to our blog to learn more about what’s under the hood in our next instalment: The How: The Magic Behind Strings by Paragon.



Filed Under: Uncategorized

November 13, 2019 By Laurie Lafleur 1 Comment

AI so fast it has time to read your images and clean your floors.

This tongue-in-cheek statement isn’t unlike the many other bold claims that are out there. The recent hype surrounding AI in healthcare is boundless, with promises that it can exponentially increase productivity, improve accuracy, and slash operational costs at a scale that was previously unfathomable. As a result, many healthcare organizations are actively developing strategies to incorporate AI into their technology roadmaps and clinical workflows, hoping to immediately reap the promised benefits.

Unfortunately, in many cases, implementation of AI in clinical practice has fallen short of expectations, proving to be more complicated, expensive, and cumbersome than originally advertised. This is largely due to an overarching perception in the industry that off-the-shelf AI applications can be procured and integrated ‘out-of-the-box’ into a variety of existing technologies, such as EHRs, PACS, and other data sources. The reality, however, is that successful adoption and deployment of AI requires careful evaluation of the following key considerations: 

1. Finding the right AI fit for your organization

There is a plethora of different AI algorithms out there – each with their own distinct use cases and value propositions including but not limited to: 

  • Predictive analytics to profile your organization’s capacity and performance potential in line with demand and growth patterns; 
  • Image analysis to automatically detect, escalate, and monitor abnormalities or disease; 
  • And proactive recommendations to treat or mitigate disease based on family, clinical, and social and environmental factors. 

Determining which AI applications will provide the most ‘bang for your buck’ requires thoughtful evaluation and identification of your organization’s own unique challenges and objectives. As well, it’s important to consider how AI will integrate into your existing technologies and day-to-day operations. Applications that fragment workflow or introduce cumbersome steps rarely achieve successful adoption – especially among busy clinicians. Be sure that your AI roadmap prioritizes applications that will bring meaningful and measurable benefits to address your burning platforms, and ensure your AI vendor has designed integrations, interfaces, and feedback loops that deliver a seamless and efficient user experience.

2. AI is only as good as its underlying data

AI models typically have specific requirements regarding the structure, content, and format of the data they are analyzing. Unfortunately, most healthcare organizations have a unique data fingerprint, with diverse technology ecosystems, image acquisition techniques, clinical documentation practices, and population characteristics that can introduce variability and negatively impact the accuracy of AI algorithms in clinical practice.

Careful analysis of each algorithm’s data requirements alongside your own data warehouse is required to determine whether there are any content or formatting gaps that will need to be addressed, and/or whether changes will be required to HL7/FHIR, DICOM, XDS, or other interfaces.

As well, it’s essential that your AI vendor has a strategy in-place to validate and, if necessary, re-train their algorithms against your own unique datasets before going live to ensure quality and accuracy of results.

Finally, it’s common – even expected – for changes in data structure and semantics to shift over time due to a number of factors such as process changes, introduction of new or updated imaging modalities, or changes in patient population characteristics, etc. It’s therefore critical that AI vendors have processes in place to proactively identify and accommodate these changes on an ongoing basis to ensure continued accuracy and efficacy within the live clinical environment.

3. Striking a cost-value balance

One of the biggest barriers to adoption for AI today continues to be the financial reimbursement model – or lack thereof. AI introduces additional operational, and sometimes capital costs, which in most cases do not realize a full return through billable outcomes.

While there are a few examples where computer-generated findings qualify for reimbursements (i.e. CAD for mammography), CMS has yet to provide direct reimbursement models for providers to bill for AI-rendered diagnostic interpretations or reviews. This doesn’t mean AI is a money pit – rather ROI is measured based on improved workflow and provider efficiency and accuracy, which in turn increases capacity (revenue) and decreases resource utilization, risk, and other ‘waste’ (costs).

As well, AI can automate risk stratification, data correlation, and reporting to help providers qualify for additional reimbursements, incentives, or even grants related to specific disease profiles and patient populations – a process that would be all but impossible if done manually due to the sheer volume and variability of the underlying data. The cost-value balance is unique for each healthcare organization and depends upon the opportunities, challenges, and priorities identified above. In any case, be sure to challenge your AI vendor to provide quantifiable evidence that they will be able to deliver the ROI you’re expecting – whatever that may be. 

Love the logo? Contact us for details on how to order your limited edition tee.

Are you ready to integrate AI into your organization? We can help you separate truth from fiction and select a strategy, technology, and vendor that will best fit your organizational capabilities and needs. Contact us to setup a meeting at RSNA 2019.


Filed Under: Artificial Intelligence, Healthcare IT, Imaging, Workflow

November 7, 2019 By Laurie Lafleur 1 Comment

Why be limited by industry standards or 5G infrastructure? Share your images with anyone, anytime using sound-wave technology that transmits data at a frequency only dogs can hear.

Imagine what we could do if we could share massive volumes of data between hospital networks in a matter of milliseconds – regardless of their legal affiliation. Not only could we liberate patients’ complete medical and imaging records, making them truly portable from one healthcare facility to another, but we could also make newer services and technologies more feasible and reliable – from telemedicine visits to robot-performed telesurgery. 

Two big obstacles separated this coveted fiction from becoming a reality – trust (i.e. security, privacy, and identity management) and infrastructure (i.e. server processing power and high-speed networks). There was a lot of hype surrounding blockchain for addressing the former not all that long ago, which largely fell flat because of the latter. However, the emergence of 5G networks is bringing renewed promise for enabling economies of scale in the healthcare industry that were previously unimaginable.

So what is 5G anyway, and what does it mean for healthcare?

The next-generation in mobile communication technology, 5G uses ultra-high-frequency ‘air interfaces’ that have a much higher capacity than traditional wireless networks to transmit data and bring the promise of unprecedented transmission speed and bandwidth capacity with near-zero latency.

Quite simply, this means that 5G will allow healthcare organizations to connect more devices (think IoT), send more data – both in size and volume (think growing ageing populations and hi-res CTs), and facilitate true real-time communication between care providers and patients (think robot-performed telesurgery). 

This dam-breaking technology has the potential to truly support the flood of healthcare data that is being generated and continues to grow at an exponential rate. 5G is already rolling out in some major cities, and it is estimated to become mainstream by 2022 – the only problem is, healthcare won’t be able to realize the full benefit of this technology until we address the other elephant in the room – trust. 

Enter the Blockchain…  

Fundamentally, Blockchain provides a secure method of indexing and sharing information across a network of unaffiliated systems. As part of a distributed and collaborative ledger each system plays an integral role in recording and validating health transactions from across the network (the existence and location of patient images, for example). All systems in a Blockchain keep a comprehensive ledger of all transactions that have occurred across the network – such as updates to an electronic health record, or the addition of a new imaging exam. When information is requested from the network consensus across participating systems is required to confirm the accuracy of data being shared. This decentralized data stewardship model ensures that information is always synchronized across the chain and prevents any one person or system from being able to corrupt or take down the network. The benefits of this model are many, but to name a few:  

  1. Reuniting the patient record: One of the biggest interoperability challenges today is patient identity management. Because healthcare providers exist in their own technology silos patients are assigned unique identities for each facility or provider they visit – resulting in a fragmented patient record and care experience where technologies from the 90’s like CDs and fax machines are the primary method for information sharing. With Blockchain multiple patient identifiers from disparate organizations can be tracked and connected across the network, resulting in a truly unified and transparent medical record. 
  2. Achieving real economies of scale: Most healthcare organizations would argue that their technical infrastructure is expensive, often failing to deliver the promised ROI. Because Blockchain shares resources across the network it can realize real economies of scale – leveraging compute power across the network to facilitate faster and more efficient information exchange and leveraging network-wide volume to drive down individual transaction costs. 
  3. Facilitating faster, cheaper, and more reliable cross-entity transactions: Because a Blockchain can be shared across a variety of authorized providers in a secure and standardized way it has the potential to greatly reduce the cost and complexity of common transactions such as brokering referrals, accessing relevant medical history, communicating test results or incidental/critical findings, and managing billing and payment for network participants including but not limited to hospitals, specialists, primary care physicians, social service providers, and insurance payers, etc. And once again, because of that ledger and the inherent cryptographic protocols underlying Blockchain technology clinical and financial transactions are guaranteed to be accurate and secure.

Love the logo? Contact us for details on how to order your limited edition tee.

Are you ready for the next wave of digital transformation? We can help you separate truth from fiction and build a future-proof technology strategy that will best fit your organizational capabilities and needs. Contact us to setup a meeting at RSNA 2019.


Filed Under: 5G, Blockchain, Data Management, Healthcare IT

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