ArborMetrix

Collaboratives

Move the needle forward in healthcare.

Measure and improve value in healthcare by advancing outcomes and reducing costs across a specific geography, region, or specialty—surgery, urology, emergency medicine—and then iterate. How? Utilize a framework that effectively blends data to address the limitations of individual sources and applies rigorous clinical and data science.

Now you can maximize the value of diverse data sets and present the reality in clean and easily digested visualizations. You can sit down at the table with your stakeholders and productively explore the opportunity. Create consensus. Take action.

Experience the power behind the framework.

Understand what is driving outcomes, variation, and costs.

Proven methods and models backed by our clinical and data experts provide the framework to transform your data into the backbone that drives your initiatives. Now you can gain clarity on what happened, why, and what is likely to happen next.

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Your Technological Framework

Data that means something.

1
Ingest

disparate sources, in massive amounts, that include abstraction, claims, EHRs, and PRO.

2
Enrich

in proven ways that ensure your initiatives have the best possible knowledge base.

3
Transform

with trusted application of analytics to quantify measurements that have a direct impact on your success.

4
Reveal

meaningful, easily understood views that will inspire your stakeholders to decisive action and move the needle forward.

To confidently take action.

Your Technological Framework

Systematic. Perpetual.

Click on AMx solution names to explore.

Your Technological Framework

Perspective to deliver impact.

The delivery of quality healthcare benefits everyone. Patients have better outcomes, clinicians make evidence-based decisions, hospitals and payers achieve financial efficiencies, and life science organizations develop safer products.

Help drive improved outcomes in a value-based care system. Leverage registry data—hub of quality improvement practices. Now you can bring multiple clinicians, sites, and patients together with a common goal. How? Through a robust data infrastructure and technical expertise—a framework.

Our framework has everything you need to securely collect, validate, transform, and interact with data to measure and improve processes and outcomes. Leverage powerful administrator tools as well as clinical, analytic, and business experts to provide strategic support. With ease, you can guide the path to quality care with flexible, consistent, control to meet your goals.

Ensure providers are compensated fairly and equitably for high-quality care.

1
Define your data goals.
With the end in mind, pull together data from many sources—including patient surveys—into one place.

2
Engage your stakeholders.
With solutions that are persona-driven, flexible, and configurable you can start iteratively and scale to ensure long-term sustainability and success.

3
Leverage your data to inspire data-driven action.
With meaningful presentation of data, identify the best path forward, assured that informed decisions are rooted in validated, accurate data and enriched with the application of trusted data science.

The possibilities are endless and measurable:

  • Track adherence and impact on outcomes through standard and specialized reports
  • Filter progress on initiatives by demographic, clinical variables or at the patient-level
  • Drill down to examine the numerators and denominators of measures
  • Use clinical-validated outcome measures—adjusted for fair comparisons (risk and reliability)—to benchmark with confidence
  • Predict the likelihood of readmission, program eligibility, and other condition-specific factors
  • Determine which patients receive certain interventions—such as tele-SNF encounters
  • Support informed patient-level decisions with predictive analytics at the point of care
  • Forecast optimum care path for specific patients and populations with predictive analytics to support real-time interventions at the point of care

30%

reduction in post-operative opioid consumption

PREDICTED

the likelihood of readmission, program eligibility and other condition-specific factors

17.5%

predicted at-risk population reduction

It is not always a straightforward path for researchers.

Questions are complicated.

Priorities shift.

Real-world data is messy.

 

Simplify these complexities with modern analytics and science that create an efficient, reliable way to glean real-world evidence (RWE) from rich sources of disparate data that helps you accelerate discovery, advance patient care, and develop novel treatments.

Many different study designs are leveraged to support clinical research. Make sure the data you include is not limited. Registry data allows you to:

  • Capture massive amounts of data from disparate sources and easily aggregate and enrich to provide a holistic lens
  • Deploy advanced, scientifically grounded analytics to produce trusted research-grade evidence
  • Interact at a deep clinical level with your data to create patient cohorts, analyze granular clinical details, and draw correlations within and across health conditions
  • Track patient safety and inform clinical trial/study design
  • Understand subpopulations including those affected by health disparities and heterogeneity of treatment effects
  • Ensure alignment with Value/Outcomes Based Contracts that is dependent on accessing trusted RWD
  • Employ registry technology to support post-market surveillance:
    • Access data from an existing registry
    • Partner with an existing registry
    • Create a new registry and consider combining one of the options above

A unique ‘treasure’ and resource in the worldwide scientific and medical environment.

Once you have your traditional research initiatives fueled, empower patients and extend your research breadth. Collect data from patients, their parents, siblings, partners, and caregivers to transform the full continuum of care. Allow patients to:

  • View their own information
  • Compare their information to de-identified, aggregate data from others with the same diagnosis
  • Access specialized resources and education

Monitor, evaluate, and manage the complete cost and quality of episodes of care. Reduce variation and understand drivers of post-acute care costs.

Real-world data (RWD) drives this. Your operational goals need to leverage a data design that will inform and provide the critical measurement to ensure success. The types and sources of RWD that you will want to be collected—in the context of the routine delivery of care—are as follows:

  • Clinical data from electronic health records (EHRs) and case report forms (eCRFs) provide patient demographics, family history, comorbidities, procedure and treatment history, and outcomes
  • Patient-generated data from patient-reported outcome (PRO) surveys—these data provide insights directly from the patient and inform what happens outside of clinic visits, procedures, and hospital stays
  • Cost and utilization data from claims and public datasets provide information regarding healthcare services utilization, population coverage, and prescribing patterns
  • Public health data from various government data sources add critical information to enable stakeholders to best serve the needs of the populations they serve

Combine RWD with real-world evidence (RWE) and now you see what really happens in everyday practice in healthcare vs. what is expected to happen. This holistic view of patients requires a combination of high-powered analytics, a validated approach, and a robust knowledge of available RWD sources. We break it down into 7 steps:

  1. Defining a study protocol answering relevant clinical questions
  2. Defining which data elements can be collected from which RWD sources
  3. Establishing data capture arrangements and protocols with existing RWD sources
  4. Blending disparate data sources through probabilistic record-matching algorithms
  5. Validating and supplementing blended data through editable eCRFs
  6. Defining and calculating clinically relevant outcomes and measures
  7. Appropriately assessing and controlling for variability in data quality, availability, and confounding patient factors affecting measured outcomes

Use this knowledge to fundamentally change the future of healthcare delivery and deliver on the promise of reducing waste in healthcare costs.

30%

reduction in post-operative opioid consumption

17.5%

predicted at-risk population reduction

$2.2B

saved statewide through payer-sponsored value partnerships

Ready to engage? Contact Us