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The PADS Framework for Compliance and Security - Part 1

Gabriel Lowy

The PADS (Performance Analytics Decision Support) Framework recommends a more strategic approach to user experience and application performance. Providing superior user experience consistently is a clear competitive differentiator on the path to achieving the three components of higher return on investment (ROI). These components are:

1. Reducing costs

2. Enhancing productivity

3. Generating incremental revenue streams

But deeper intelligence into the application delivery chain can also help companies meet compliance and security requirements more effectively in order to achieve their risk management objectives. Industries such as healthcare and financial services are under increasing regulatory pressure to demonstrate systems efficacy and security for protecting sensitive personal information and resilience against market disruptions.

Below we highlight new regulations in these two industries that underscore the risks companies face when they don’t have a good handle on user experience or application performance across the application delivery chain.

Healthcare: Pressure to Improve Patient Outcomes at Lower Costs

Major reforms are driving the healthcare community to leverage technology in a manner that provides for a timely and secure exchange of information related to patient care.  The Affordable Care Act has resulted in upgrades to existing data exchange services, deployment of new ones, and the incorporation of mobile access and communication between providers and patients.

Among the drivers are new measures that estimate the effectiveness of health plans. The National Committee for Quality Assurance's Healthcare Effectiveness Data and Information Set (HEDIS) sets performance metrics on provider quality of care. The data required to calculate HEDIS scores come from many different sources, such as clinical applications and pharmacy and medical data claims systems.

Many health providers and plans have been focused on the International Classification of Diseases, Tenth Edition (ICD-10). ICD 10 is a clinical cataloging system that went into effect for the U.S. healthcare industry on Oct. 1, 2015. Providers, coders, IT professionals, insurance carriers, government agencies and others use ICD codes to properly note diseases on health records, track epidemiological trends, and assist in medical reimbursement decisions. These codes must be consistent across systems to ensure proper classification in diagnoses.

Providers are also occupied with Meaningful Use stage 2 (MU2), which is the second phase of the Meaningful Use incentive program. MU2 is designed for eligible providers to demonstrate their progress toward meaningful patient engagement using state-of-the-art healthcare IT and methods best suited to their practice.

The Centers for Medicare and Medicaid Services (CMS) established criteria that eligible professionals, hospitals and critical access hospitals must meet in order to continue to participate in Medicare and Medicaid Electronic Health Record (EHR) Incentive Programs.

Common themes of healthcare reform are patient engagement and the information exchange with external stakeholders. These include secure communication with patients, collaboration with other providers and an exchange of information with registries. Each organization is required to track, monitor and report on their efforts to meaningfully use technology to meet quality of service measures.

The Health Insurance Portability and Accountability Act (HIPAA) defines electronic personal health information and what covered entities and business associates must do to secure and protect it via the Security Rule. This includes conducting annual assessments of security and compliance with 42 specific safeguards, covering Administration, such as policies and procedures, Physical, such as access to the workplace where personal health information (PHI) is commonly used, and Technical, such as encrypting PHI data at rest and on the move.

Stellar user experience and application performance among and between constituent systems are critical to ensure systems efficacy and accurate scoring, as well as consistent diagnoses to reduce errors and improve patient outcomes. It also facilitates regulatory compliance for all stakeholders throughout the healthcare ecosystem.

Read The PADS Framework for Compliance and Security - Part 2, covering the global securities market.

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The PADS Framework for Compliance and Security - Part 1

Gabriel Lowy

The PADS (Performance Analytics Decision Support) Framework recommends a more strategic approach to user experience and application performance. Providing superior user experience consistently is a clear competitive differentiator on the path to achieving the three components of higher return on investment (ROI). These components are:

1. Reducing costs

2. Enhancing productivity

3. Generating incremental revenue streams

But deeper intelligence into the application delivery chain can also help companies meet compliance and security requirements more effectively in order to achieve their risk management objectives. Industries such as healthcare and financial services are under increasing regulatory pressure to demonstrate systems efficacy and security for protecting sensitive personal information and resilience against market disruptions.

Below we highlight new regulations in these two industries that underscore the risks companies face when they don’t have a good handle on user experience or application performance across the application delivery chain.

Healthcare: Pressure to Improve Patient Outcomes at Lower Costs

Major reforms are driving the healthcare community to leverage technology in a manner that provides for a timely and secure exchange of information related to patient care.  The Affordable Care Act has resulted in upgrades to existing data exchange services, deployment of new ones, and the incorporation of mobile access and communication between providers and patients.

Among the drivers are new measures that estimate the effectiveness of health plans. The National Committee for Quality Assurance's Healthcare Effectiveness Data and Information Set (HEDIS) sets performance metrics on provider quality of care. The data required to calculate HEDIS scores come from many different sources, such as clinical applications and pharmacy and medical data claims systems.

Many health providers and plans have been focused on the International Classification of Diseases, Tenth Edition (ICD-10). ICD 10 is a clinical cataloging system that went into effect for the U.S. healthcare industry on Oct. 1, 2015. Providers, coders, IT professionals, insurance carriers, government agencies and others use ICD codes to properly note diseases on health records, track epidemiological trends, and assist in medical reimbursement decisions. These codes must be consistent across systems to ensure proper classification in diagnoses.

Providers are also occupied with Meaningful Use stage 2 (MU2), which is the second phase of the Meaningful Use incentive program. MU2 is designed for eligible providers to demonstrate their progress toward meaningful patient engagement using state-of-the-art healthcare IT and methods best suited to their practice.

The Centers for Medicare and Medicaid Services (CMS) established criteria that eligible professionals, hospitals and critical access hospitals must meet in order to continue to participate in Medicare and Medicaid Electronic Health Record (EHR) Incentive Programs.

Common themes of healthcare reform are patient engagement and the information exchange with external stakeholders. These include secure communication with patients, collaboration with other providers and an exchange of information with registries. Each organization is required to track, monitor and report on their efforts to meaningfully use technology to meet quality of service measures.

The Health Insurance Portability and Accountability Act (HIPAA) defines electronic personal health information and what covered entities and business associates must do to secure and protect it via the Security Rule. This includes conducting annual assessments of security and compliance with 42 specific safeguards, covering Administration, such as policies and procedures, Physical, such as access to the workplace where personal health information (PHI) is commonly used, and Technical, such as encrypting PHI data at rest and on the move.

Stellar user experience and application performance among and between constituent systems are critical to ensure systems efficacy and accurate scoring, as well as consistent diagnoses to reduce errors and improve patient outcomes. It also facilitates regulatory compliance for all stakeholders throughout the healthcare ecosystem.

Read The PADS Framework for Compliance and Security - Part 2, covering the global securities market.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...