Why senior care requires more intelligent data synthesis

Elderly patients' medical records have gaps that hamper good clinical care

It’s 8:30 a.m. and the first patient of the day, a 77-year-old woman, is sitting in the exam room. She's seen three other physicians and a physical therapist over the past month. When the doctor enters, the patient produces a bag of prescriptions, along with discharge papers from a recent emergency room visit.

When the clinician looks at the patient’s electronic health record, only one set of detailed notes from a previous physician is in the chart, and only a third of the prescriptions presented are noted. The provider asks questions to fill in the gaps, turning a 15-minute visit into a 25-minute visit, and throwing off the entire day’s schedule.

Even after this extra time, the provider still may not have the full picture of their patient's health.

This scenario is fictional, but not far-fetched — considering the nearly 1 in 3 adults around age 60 are taking five or more medications¹, and about one in three Medicare beneficiaries sees² more than five doctors each year. Even the most diligent providers are left having to diagnose patients and perform medication reconciliation using incomplete health records and information.

In senior care, this isn’t just inefficient. It’s risky.

Older patients see care providers across a variety of settings, including their primary care doctors, specialists, hospitals, clinics, physical therapy and rehab facilities, and home health providers. Each encounter generates a unique dataset. Polypharmacy management adds more. But the problem is this data is rarely unified, timely, or contextualized, which makes it difficult to translate and make sense of across a full care journey.

Senior care has extensive amounts of data, and it demands increased coordination

The risks and challenges leading to poor care coordination in senior care

Care transitions, especially post-acute care coordination, are one of the most vulnerable milestones in a patient’s care. They're also one of the most fragmented from a data perspective. Missing context due to a lack of encounter data can prove devastating to senior care data interoperability, especially during care transitions.

A recent BMC Geriatrics study³ found that 68% of patients 65 and older who were on chronic medications had medication errors during care transitions related to stays in emergency department ICUs. Another study⁴ in the Annals of Family Medicine found that “physicians often do not communicate with each other at the time of referral or after consultation.”

What ties many of these coordination issues together is not simply missing data, but broken continuity of context:

• Medication lists are incomplete or outdated
• Discharge instructions arrive too late to influence care
• Post-acute providers rely on fax or phone instead of real-time data

In senior care, these gaps compound. The more clinicians, medications, and transitions involved, the more dangerous incomplete data becomes. It’s critical for the holistic healthcare ecosystem to acknowledge these challenges and meet them as our aging population grows.

The number of Americans ages 65 and older is projected to increase from 58 million in 2022 to 82 million by 2050 (a 40% increase), and the 65-and-older age group’s share of the total population is projected to rise from 17% to 23%, according to the U.S. Census Bureau.⁵

But scaling ecosystem coordination and communication and giving everyone useful access to patient records can be daunting.

Another study published in the Patient Education and Counseling journal examined an increasing use of formal care coordinators, such as nurses. The study found that broad implementation and operationalization of coordinator roles had limitations based on challenges related to payer reimbursements, as well as organizational barriers to successful interpersonal communication between clinical staff.⁶

Without a way to better coordinate, capture, and synthesize patient data from every healthcare touchpoint, patients may suffer.

Standard interoperability and data sharing alone are not enough

Healthcare organizations have invested big in finding interoperability solutions. These include the Trusted Exchange Framework and Common Agreement (TEFCA) framework and the Fast Healthcare Interoperability Resources (FHIR) application programming interface. These efforts are critical, especially as TEFCA expands nationwide data exchange across networks.

However, data access isn’t the same as usability. Even when EHRs are available, patient data rarely arrives as a complete picture of the patient. The challenges and dangers can be even more pronounced in primary care for seniors, given the number of post-acute care locations and provider organizations that aren’t online and still faxing records.

Interoperability enables data to move. But intelligent interoperability is a standard by which the data has completeness and timeliness during transitory or actionable moments of care.

From connectivity to coordination: The role of intelligent data synthesis

Moving beyond basic interoperability and data exchange to intelligent interoperability requires effort to help improve coordination.

That includes:

• Aggregating data from multiple sources
• Reconciling inconsistencies
• Preserving longitudinal context
• Surfacing what matters at the moment of care

AI-powered data synthesis can prove essential in addressing these elements while helping minimize the amount of burden on clinical staff. Rather than forcing clinicians to manually assemble a patient’s history across fragmented systems, intelligent platforms leveraging foundational AI can unify and interpret that data in real time, deploying updates across the network.

For example, medication reconciliation becomes safer when systems can:

• Aggregate prescriptions from pharmacies, EHRs, and discharge records
• Identify duplicate therapies and consolidate them within the patient record
• Flag contraindications before harm occurs

This shifts the burden from the clinician to the system and helps reduce one of the most persistent risks in senior care.

How AI-native solutions support senior care coordination

athenahealth's AI-native approach combines a TEFCA-aligned, network-enabled infrastructure with a foundational Advanced Intelligence Layer that helps native AI transform longitudinal patient data across care settings into actionable insights.

The athenaOne® platform can aggregate medication data from multiple sources, including EHRs, pharmacies, and discharge papers, allowing data to flow across the full care continuum. This is what it looks like:

• Medication histories are aggregated across sources
• The ChartSync functionality in athenaOne helps deduplicate information and flag interventions
• Discharge summaries and care transitions are visible earlier in the workflow
• Patient context — including comorbidities and prior utilization — is preserved across encounters

Instead of chasing records, providers can act on a more complete understanding of the patient.

AI-powered data synthesis also helps significantly with post-acute care coordination by enabling clinicians to know ahead of time that they have received a high-risk patient based on their profile and other data. This is important because a broken hip for a relatively healthy patient doesn’t mean the same thing as it does for one who has diabetes or other comorbidities.

Creating positive outcomes — and fewer readmissions

Improvement in care coordination and striving for more intelligent interoperability can help drive measurable impact in senior care.

Hospital readmissions, medication errors, and provider time are all directly affected by how well data is shared and understood across settings. With a more complete and timely view of the patient, providers are better positioned to:

• Intervene earlier in high-risk cases
• Reduce medication-related complications
• Spend less time reconstructing patient history and more time delivering care

The result is a more seamless care experience that benefits both practice and patient. Health organizations can see improved operational efficiency while helping provide senior patients with safer, more consistent care.

Providing coordinated senior care at scale

Senior care has always depended on care coordination. What has changed is the ability to help support that coordination at scale.

The need for connected, context-rich data becomes more urgent as care is distributed across settings for senior patients. The question becomes whether this data can be trusted, understood, and acted on in real time. That is the true shift from interoperability to intelligent interoperability and better care coordination.

Explore how athenahealth’s network and AI-powered data synthesis help bring that coordination to life.