Getting Into the Data Seeker Mindset

Connecting to national healthcare networks turns your healthcare organization into a “data seeker”, opening up a world of possibilities for better outcomes.

Organizations that use Particle do something more than deliver care. With one connection to our API, they transform into...healthcare data seekers!

Being a data seeker means thinking about the ideal information your organization needs to improve care outcomes. The vast amount of data we make available may inspire you to imagine different, more proactive ways to treat medical conditions. With Particle, you can be selective about the resources that you want to receive, and how you’d like to receive them.

Particle works by querying the tens of thousands of sources on our network. On average, we return over 95 records per patient. Some of these records, like Continuity of Care Documents, can be quite long. So, as a data seeker, you won’t necessarily look for all of a patient’s data. Instead, you’ll start to seek out the most relevant data. 

Your first step will be to consider how the clinical records you can find will support your providers, and meet your organization’s objectives. For example, managing aftercare might require searching for both discharge summaries and transfer of care resources. On the other hand, organizations that want to reduce inpatient admissions could limit their focus to monitoring recent outpatient encounters. 

It’s an exciting change for most care organizations to query specific items of interest instead of settling for self-reported information. However, it does require exploring what data to look for instead of spending resources (whether engineering or clinical) to filter out the noise.

Particle can help bridge the gap between treatment issues and network queries. Our industry-leading platform, including our FHIR transformation process, turns rigid and verbose C-CDA documents into easy-to-parse data elements that can be ingested into your EHR or backend systems while leaving irrelevant information behind. This gives you flexibility in how you choose to display, analyze, or interpret the valuable clinical data that Particle provides.

Here are a few different ways to start applying the data seeker mindset to your organization:

1. Query Specific Biomarkers or Indicators

Specialist provider organizations tend to see an immediate benefit by looking for a relatively narrow selection of clinical data. 

If your organization focuses on treating a certain condition, then you can seek out a history of highly relevant biomarkers - like cholesterol levels, blood pressure, A1C values or previous diagnoses. By continuing to query for newly reported data, your providers can track the aspects of patient care that they're responsible for, without distractions.

It’s similarly possible to monitor general indicators of health in your patient population, like the total frequency of healthcare visits. Using a healthcare API like Particle Health can help you determine the cadence of a patient’s treatment. You can look for their most recent encounter with any provider, or search for the last time your patients had a specific type of appointment.

Data seekers can also pick up on intermittently-reported issues that patients or clinicians tend to leave out, like keywords that indicate social determinants of health. A March 2022 study determined that patients were 50% more likely to report certain sensitive health conditions on digital platforms instead of in-person. Continually screening for these across multiple encounters when they do appear helps your organization respond.

Healthcare APIs allow you to narrowly track specific conditions or milestones. If a certain intervention would have an outsized impact on your practice, Particle can help make it visible.

2. Catch Errors with Medication Reconciliation

Prescriptions come with their own set of issues for data seekers to consider. Medication data for patients tends to be more standardized than provider notes. It can be spread between different EHR fields, and organizations may need to track multiple data points to get a complete understanding of what their patients have been prescribed.

With a FHIR-compatible API, you’re able to search documents and extract specific details on what drugs your patients have been prescribed. Most healthcare systems will want to get medication lists for their patients, but you don’t have to stop there. Organizations can better account for drug interactions by searching for allergies and relevant labs too.

Data seekers who use an API won’t be surprised by medication mistakes any longer. They can sort out all the data they need for up-to-date, granular prescription monitoring via Particle’s API.

3. Get a Complete Picture to Provide Primary Care

A classic interoperability use case is knowing as much about your patients as possible. It can seem like your organization already has a relatively complete understanding of your patients, but data seekers are frequently surprised to learn that healthcare APIs deliver a FHIR-hose of information! 

If your organization already captures the bulk of data about your patients, then an API will close the gap between what happened in your practice and elsewhere. Data seekers who are accounting for value-based care objectives or serving as the first line of defense in patient care may want all the data they can handle, or may filter out only a few document types.

When your healthcare organization connects to Particle, you’ll be able to reliably pull additional medical records for your patients. Connecting to a healthcare API puts you in an empowering new role - that of a “data seeker”.

Much has been said about how patients are helped by full access to their medical records, and those records can play a role in your organization as well. Particle’s API improves on older approaches to healthcare data by giving data seekers the chance to select for useful information. 

Data seekers ask which challenges that patient data can solve. What questions will you answer once your organization has access to patient data at scale?