DashPoint Analytics

5 Things PALTC Providers Should Consider Before Investing in Analytics

Post-Acute Analytics

Post-acute analytics and business intelligence are all the rage these days. And rightly so!

Skilled nursing facilities (SNFs) now face a host of increasingly complex challenges such as:

  • Staffing shortages.
  • Fluctuating payer mix and reduced reimbursement.
  • Changing resident and client demands.
  • Escalating operational expenses.
  • Changing regulation and compliance requirements.

As a result, electronic medical record (EMR) providers (NetSmart, MatrixCare, PointClickCare) and other vendors now trumpet a variety of products that will allow you to check “analytics” off your to-do list.

But how do you choose the best solution for your organization?

Your C-suite wants dashboards of key-performance-indicators (KPIs) across metrics like census, reimbursement, hospital readmissions, and staff turnover.

Meanwhile, your clinical leadership has access to a firehose of clinical data but needs help to leverage it to improve care and quality measures.

Lastly, your operations, facilities, and human resources teams each have systems and data they want to analyze.

Figuring out which analytics solution best meets all of these demands is a daunting task.

Here are five important things to consider before you invest.

1. Think Beyond Your EMR

While your EMR system is likely one of your SNF’s most heavily used applications, it’s certainly not the only one.

You have applications for accounting, human resources, payroll, timekeeping, CRM, supplies management and more. Often, these systems have only a single-purpose interface linking them. Or, more typically, they remain completely siloed from each other.

This dramatically narrows the scope of insight that an analytics platform can draw from your data.

While your EMR is likely one of your organization’s most utilized info systems, it’s certainly not the only significant data source.

Most post-acute analytics applications are restricted to data that resides within your EMR. But a source-agnostic analytics platform layers your various applications into a unified view.

As a result, you get real-time access to a bevy of metrics that are crucial to running your organization.

Here are a few examples:

  • Hours per Patient Day by Acuity (accesses EMR census, timekeeping, and clinical acuity)
  • Costs by Diagnosis (accesses payer/claims data, payroll, supplies, accounting)
  • Cost of Services by Level of Care (accesses EMR, inventory, facilities, payroll)

As you can see, it’s important to invest in a solution with the flexibility to handle new data challenges as they arise. A source-agnostic analytics platform fits the bill.

2. How “Stale” Is Your Data?

In today’s Post-Acute and Long-Term Care (PALTC) organizations, a single resident or patient can have hundreds of data elements entered into various systems during a single shift.  Data is gathered on activities of daily living (ADLs). Vitals are taken. Interdisciplinary notes are made.  

This data informs assessments such as the Minimum Data Set (MDS) in skilled nursing facilities and the Outcome and Assessment Information Set (OASIS) for home care.  And it’s what most post-acute analytics platforms focus on.

The problem is that this data can be “stale,” often as old as 90 days (plus a look-back period). 

Resident or patient conditions can change rapidly and your analytics needs to have access to real-time data to provide critical alerts, allowing you to make decisions based on the most recent information.

3. Account for Your Varied Data Types

Applications and systems in your organization are based on numerous different data types. Your analytics solution needs to be able to accommodate all of them with ease. 

For example, nurse’s notes or CRM activities are often text-heavy and unstructured. Vital signs, on the other hand, are structured, continuous, and consistent in their structure. 

Review all of these data elements and ensure your analytical platform can access, extract, transform, and load them.

4. Artificial Intelligence and Machine-Learning are Must-Haves

Don’t consider any healthcare analytics solution that doesn’t come with machine learning (ML) and artificial intelligence (AI) built-in, period. 

AI-powered tools can transform your data into actionable intelligence.  They’re critical to predictive decision-making and risk mitigation, allowing you to act with confidence.  

Moreover, as your data footprint grows, they deliver increasingly accurate insights that might not be readily apparent without their assistance. 

5. Balance Customization, Cost, and Competency

You have a lot of choices when it comes to your investment in data analytics.  Some solutions offer an analytics-as-a-service model that comes with low up-front costs, but they typically don’t allow for much customization. 

Other solutions offer customization options but require in-house competence and expertise to deliver actionable results. 

You’ll need to consider your organization’s unique requirements and constraints in order to determine which solution will deliver the best return on investment.

Take some time to think about each of the five points above and you’ll be well on your way to deploying a successful post-acute analytics solution.

Interested in learning more about how data analytics can improve outcomes at your PALTC organization? Drop us a line here.

Keith Hoover
Keith is Dashpoint Analytics’ Founder and CEO. He designs and implements business intelligence solutions for PALTC organizations.