A Race to Superior Performance

Healthcare organizations have worked hard to improve patient safety over the past  several decades, however harm is still occurring at an unacceptable rate. Though the healthcare industry has made efforts (largely regulatory) to reduce patient harm, these measures are often not integrated with health system quality improvement efforts and may not result in fewer adverse events. This is largely because they fail to integrate regulatory data with improvement initiatives and, thus, to turn patient harm information into actionable insight.

Fully integrated clinical, cost, and operational data coupled with predictive analytics and machine learning are crucial to patient safety improvement. Tools that leverage this methodology will identify risk and suggest interventions across the continuum of care.

Avoiding patient harm is intrinsic to the work of healthcare professionals. Hippocrates, known as the Father of Modern Medicine, helped set this precedent when he said, “The physician must…have two special objects in view with regard to disease, namely, to do good or to do no harm.”

Contemporary medicine, however, still struggles to realize its primary mission. Today, researchers estimate that one in three hospitalized patients experiences preventable harm and over 400,000 individuals per year die from these injuries.

There is a gap in healthcare safety culture and the way health systems uses data (or think they use data) to understand patient harm and what to do about it. Much of the data collection is manual and not integrated with financial, operational, and other data, resulting in a fragmented approach to safety analytics that’s not actionable or predictive. Scores are recorded and boxes are checked, but the real work to make patients safer—closing the loop between information and action—is incomplete.

The status of patient safety moving forward, however, stands to improve. Despite the discouraging statistics above, in today’s era of data-driven healthcare, machine learning, and predictive analytics, the industry can turnaround decades of lost ground in patient safety and finally make much needed improvement in preventable errors. 

Patient Safety 

Patient harm is defined as, “an injury that was caused by medical management (rather than the underlying disease) and that prolonged the hospitalization, produced a disability at the time of discharge, or both.” Adverse events can affect quality of life, delay treatment, lead to readmission, cause permanently disability, and more; at their worst, patients die.

Examples of patient harm include:

  • Hospital-acquired infections (HAIs).
  • Falls at the healthcare facility.

Illusion of Completeness

In the industry “There’s an illusion that we’ve worked on safety,” Health systems have failed to develop real insight into risks for patient harm, and to develop appropriate intervention protocols.

“The concept of safety as a box-checking enterprise, where we start and finish, is lethal to patients of the now and future”

Quality and Patient Safety Also Impacts the Bottom Line

With the transition from fee-for-service (FFS) to value-based reimbursement, patient safety extends beyond patient welfare to increasingly impact a health system’s financial bottom line. Reimbursement will be tied to patient safety (and quality metrics). Health systems that aren’t currently engaged in driving down patient harm, or have high readmission rates, risk reduced reimbursement.

This is a significant shift in how hospitals are compensated for services; formerly, added services due to complications or readmissions made the organization money. As the industry moves toward safety-driven reimbursement, however, health systems risk not only loss of revenue if they don’t prioritize safety, but also the possibility that insurance companies will refuse to work with them.

Key Weaknesses in Patient Safety Today

Two significant studies concluded, respectively, that a) patient harm occurs frequent and is often caused by substandard care and b) adverse events are more likely the result of systemic flaw, rather than individual negligence.

Further, adverse events and preventable errors in healthcare are the third leading cause of death in the U.S.—proving that while the industry may have done work and performed research to improve patient safety, it’s made little to no progress. 

If anything, the industry has regressed in the realm of patient safety. The system is inefficient: The industry repeatedly looks at the same HAIs when it needs to look at all-cause harm. Without a data-driven, all-cause approach to patient safety, history will continue to repeat itself.

Several issues stand out as weaknesses in the industry’s approach to patient safety:

Lack of an all-cause harm strategy: Health systems follow organizational—mostly governmental—mandates and specific metrics. When organizations take a siloed approach to patient safety, selecting a few harm initiatives, they may be putting their patients’ safety at risk. As a result, the industry loses a culture of always providing safety for the sake of staying safe in certain metrics.

Insufficient tracking of harm: The healthcare industry hasn’t developed an efficient way to track all-cause harm. Health systems lack internal automated surveillance and reporting systems. While reporting to regulatory agencies is required, these reports are not aligned with quality improvement initiatives. As a result, organizations tend to spend a lot of time on patient safety reporting, but have little time left for actual improvement; they have the data,(albeit in many cases a manual, time-intensive process), but there’s no follow-through with improvement initiatives based on that data. In addition, the current voluntary approach (in which frontline staff and physicians report adverse events at their discretion) is passable at best, but largely ineffective. Employees fear repercussions if they bring an issue forward; or they believe, based on experience, that no one will follow up, so there’s no use in reporting.

Lack of real-time harm data: Harm data from medical coders isn’t reliably accurate. The rates don’t always reflect accurate trends, and they’re retrospective, so there’s no real-time data to show near misses or opportunities to prevent harm.

Machine learning supports patient safety improvement with capabilities that are reactive, proactive, and fully integrated.

Reactive capabilities: With internal triggers, the safety tool reacts to potential harm by identifying risk and notifying frontline caregivers. This adds a layer of critical thinking to the tool.

Proactive capabilities: Once the tool determines risk within a patient set, predictive analytics identifies interventions to reduce or prevent harm. This proactive capability makes the information from risk triggers actionable—by suggesting intervention—and accessible—by putting otherwise hard-to-find procedures and protocols at the user’s fingertips. For example, the application might show that a patient is at risk for pressure ulcers and remind the caregiver to rotate them regularly and follow safe skincare practices to reduce risk.

Full integration capability: Because the tool is integrated across workflow tools, it enables improvement across the continuum of care. This allows improvement efforts to not be isolated and fragmented within departments—potentially impacting only a few patients—but implemented across an organization to impact many. 

From Risk Transfer to Risk Prevention

How NIXN is reshaping Insurance

The insurance industry has a history of providing financial relief to companies and individuals through disaster, illness, injury, and loss. However with growing access to data and technology, insurance has the potential to become much more.

The industry is approaching an inflection point, on one hand, companies continue to offer broader service offerings consuming more risk that daily, become more complex. On the other hand, the availability of data processing and technology should give greater insights and opportunities to influence behaviors and risk. This ability via NIXN allows the insurance industry to offer actionable advice and develop risk prevention services that open new markets, we call this “Risk Streaming”. Our world as we know it continues to change, the end user expects a tailored experience, with on demand service, and 24/7 connection, NIXN allows the insurer to offer this.

The Case for NIXN

Insurers need to build sustainable business cases in order to offer value to customers. The reality is NIXN’s business case is complex. Unfortunately, it’s not one of those endeavors that you can launch and have a return that is immediate.

NIXN is an investment. To make a decision to commit to telematics is committing to a new way of doing the entire insurance ecosystem.

The value is exponential based on the levels of maturity the stakeholder wishes to achieve with their program. The business case almost has to be looked at as an evolving artifact, with measured steps and managed expectations along the way. Depending on the program strategy that is adopted, a carrier may have to base the business case on incremental KPIs as its program matures. The first phase, for example, could focus on customer enrollment, risk mitigation and behavioral trends. Later in the program, KPIs could be introduced around retention and loss frequency. Further still, KPIs around underwriting profitability and segmentation may become more apparent.

Early on, a stakeholder may see value from a loss control and safety angle. Insurers around the world are investing in two approaches:

1. Real-time risk mitigation, where the detection of a risky situation triggers a reaction to prevent an accident.

2. Behavioral change enhancing the activity of the loss control team but also rewarding employees’ safe behaviors.

Moreover, as the program matures, the NIXN begins to provide value for pricing sophistication, risk selection and underwriting. To complete the value chain, NIXN can then have positive impacts on claims in terms of services, efficiency of the process and effectiveness of the decisions (including minimization of fraud and inflated claims). All these elements of the value creation equation need to be managed in order to deliver an adequate value for all the relevant stakeholders.

Automate Risk Management

Process > Outcome

Safety and Risk professionals across every industry from construction to general industry to insurance are scrambling to identify the most important measurements they can use to generate a sustainable and predictable safety performance.  Outcome metrics (Incident Rate, TRIR, EMR, DART, Safe / Unsafe, etc.) is where the industry has landed. Outcomes do matter, however if we only track outcomes we do not know if this based on a process, a system, a style of decision making, or just luck.  It is human nature to see an outcome and tell ourselves we as humans can control it, however, we all know when relying on other humans, that becomes impossible. The goal of every safety professional is to improve safety, quality, and costs, the metrics need to be grounded in evidence-based process measurements, that allow those same people to drive better outcomes.

Process Measures are Important

Process measures are the evidence-based best practices that represent a company’s efforts to systematize its improvement efforts. To illustrate this, I’ll use an injury prevention example.  Let’s say your organization needs to reduce falls from height injuries.  That is your outcome measure, you know your baseline rate, and you want to reduce it, but how are you going to actually drive improvement?

The answer is straightforward: by implementing and tracking the right process metrics.  Process measures in this example are the steps that should be preformed every time an employee is working from heights 4.5 feet or more.  Using NIXN preform risk assessments assessing and predicting risk of incident across all locations where employees work at heights 4.5 feet or more.

All employees at locations identified at 88 or more on NIXN risk scale would then go through a series of best practice preventative steps from engineering controls, proper planning, retraining, etc.  As each step within the preventative process is completed you can reapply NIXN assessments identifying the highest yielding preventative steps.  This process becomes scalable creating a sustainable solution that can last with the company.

Determining Root Cause to Solve the Problem

One of the greatest benefits of having this process metric data on hand is the ability to identify what is really causing the problem with employees working at heights.  The problem does not stem from the people.  It stems from your process.  In most organizations, however, the system of incident reporting does not recognize this fact.  The stigma attached to filling out the incident report “Employee Failed because he fell”.  Often, many near misses then go unreported because of organizations focus on outcome metrics.

“Really, it is the process that failed, not the person.”

By tracking process measures, you can pinpoint the root cause of the system’s failure.  You might find the employees are unable to maintain 100% tie off throughout job activity, or instead of being up on the platform scaffold would vastly reduce the need to be working from heights without adequate protection.

What you’re trying to do is move from a craftsmanship mentality to a system of production. And process metrics are the way that you do that. NIXN is the tool to systematically guarantee that employees perform in the safest manner, every time.

Process measures improve quality, cost, and safety by enabling organizations to reduce the amount of variation in job activity.  When the correlation of employee and company performance are high, it is optimal to establish process metrics, to reduce variation, standardize output, and drive optimal outcomes.

NIXN Allows Companies to Trust the Process

So why don’t more organizations have these kinds of systems in place? The answer is that they don’t have the infrastructure to handle outcome and process metrics. If they only have the resources to track one of these, they’ll choose outcome metrics, because those are the measures that must be submitted to regulatory bodies and insurance providers.

The reason organizations struggle to track all types of measures is because their analytics methodologies rely too much on manual work. When you don’t have the RIGHT technology infrastructure in place to automate the extraction and distribution of data, you end up having to do it all manually via spreadsheets and paper documents. You might be able to successfully use manual methods to track improvement for one process or even two, but once you get to the third, fourth, or fifth process, the manual work becomes unsustainable. And without continuous measurement, you won’t be able to sustain the gains you made in one process once you move on to the next.

That’s where NIXN with a robust and flexible analytics architecture comes in. NIXN forms the foundation for risk analytics by bringing all an organization’s data into a single source of organizational truth. This makes it possible to eliminate many of the manual process of compiling data and instead, delivers the automation you need to track a wide variety of outcome and process measures simultaneously. With NIXN, safety and risk analysts can then focus their time on discovering patterns in the data that will lead to understanding, insight, and ultimately action. But without NIXN, it will be very difficult for analysts to provide reliable and repeatable reports and in-depth analyses of areas that will reveal the best opportunities for improving outcomes.

Streamline Safety and Optimize RISK Reduction with these NEW NIXN Features.

Over the past 6 months we have taken everything that you wanted and tried to not only add it, but enhance it. These new features we believe are not only what you want, but what the industry as a whole needs. Taking past data and making it matter to the end user in real time. The architecture of NIXN makes connecting the past to the present and future possible, but you, the user(s), make it a reality. A reality we believe will change the industry moving forward. So, without further ado, NIXN’s new Features:

INCIDENTS become Leading Indicators in NIXN

Incident Investigations are “strongly suggested” per OSHA. OSHA says “Addressing underlying or root causes is necessary to truly understand why an incident occurred, to develop truly effective corrective actions, and to minimize or eliminate serious consequences from similar future incidents.” When dissecting this sentence we can see the point of the Incident Investigation is to figure out correlations and cause, then learn from those to prevent future Incidents. But, How? How can we learn from incident Investigations that are stored in file cabinets after completed and maybe reviewed annually with your insurance broker? In the moment incident investigations are important, however we believe, Incident Investigations should be just as important, 6 months later, or even 6 years later. That being said we have created the ability to report, analyze, store, and connect Incident Investigations. This makes each company’s Incident Investigations living things within their own company’s network of users.

What this looks like:

  • User out in the field doing typical daily observations
  • NIXN in the background running a proprietary algorithm comparing current observation to stored past incidents within that company.
    • Company will have ability to choose if this is dependent on location
  • If NIXN finds that an Observation is 75% or more alike (Company can personalize this number) to an incident the User will immediately be alerted with a Modal in NIXN. We can also setup notifications for others within company and or Insurance Broker to be alerted in real time.
  • Each alert will have a live link to the Incident(s) that match, along with cost of loss if any, likelihood of Incident occurring again, corrections, and Root Cause.
Real Insight, Real Leading Indicators, In real time.

We get asked the question consistently by perspective partners, “How do I get my people to use NIXN?”. Our answer, give the end user real insight in real time. Our consistent question to ourselves as we continue to build NIXN is “Is this a tool for the field, or busy work for the field?” We believe that with this feature we have truly made NIXN a tool for the field, which increases the value of NIXN per company exponentially. This information is also how we and our insurance partners across the country plan moving away from selling a policy, to a state, where a risk streaming service is sold, allowing brokers to assist companies with tailored risk reduction services in a timely manner (within minutes) based off of the field data being collected.

RISK LAB

Training is at the core of any safety management system. Within the safety industry training has always been a hurdle with ever changing content, the trainer him or herself, the personnel being trained, the topic, the environment the training is taking place, all attribute to the unknowns of how EFFECTIVE the training will be. A company can have the Bill Belichick of safety training, but, the training can STILL be ineffective and usually tied back to one of the ever changing attributes listed above. (Ask the 2020 New England Patriots). We wanted to create an environment for companies and users to learn from all of the data collected in NIXN that was scalable within each company and also repeatable.

A side note on the volume of data collected in NIXN, close to 5 terabytes as of August 2021 and growing rapidly. To put this in context 1TB of data is the storage of 8 IPhone 12’s (128gb). To date NIXN has collected and the Risk Lab utilizes close 40 IPhone’s worth of data.

The Risk Lab is a place for users to go within NIXN and buildout real event scenarios of company specific field work. What actions happen in conjunction? What risks are consistently present within a given companies work environment that makes things consider “Routine Work”, what risk being present would change the scope and necessary Mitigating Factors, Making the work “Non Routine”. All of these things can be done within the Risk Lab. We believe the best part however is the output. Introducing our Proprietary “ARM TREE”

Visualizing Risk

The ARM Tree is how trainers can explain relationship and cause and effect of present or not present Risks and Mitigators. NIXN also provides the Risk Score (seen in RED), along with a data driven Incident Probability (seen in Yellow). In NIXN the ARM Tree is completely dynamic so you can continue to iterate your tree clicking and showing throughout the entire process, and each time you do make a change to one of you ARM’s (Actions, Risks, Mitigators) the Incident Probability number will update based on said changes showing true impacts.

Beyond training, we believe that you will be able utilize the Risk Lab in planning, policy writing, SOP Development, cost benefit analysis, Insurance negotiating, and internal Loss Analysis. We imagine this feature has tons of runway to grow, and we plan on relying on all of you to tell us how you will utilize it today and where we should take it.

Whats Next?

We’ve been working hard on continuing to take company legacy data and make it meaningful in NIXN and better integrate NIXNs’ already existing data into company’s safety culture. We hope these updates showcase those initiatives. Moving forward we will continue to iterate and build on the foundation driving toward to new metrics, new tools, and new ways of thinking about Risk. We hope you will join us.