Optimize Limited Resources, Drive Net New Patients

Identifying the Problems

In order to solve the service line optimization use case, it's important to understand why providers struggle to engage the right patients in the first place.

The struggle often comes down to the quality of data marketers can access.

Many hospitals have a large amount of data siloed across EHRs, CRMs, email platforms, and EPRs. However, marketers don't have access to all of this information

Targeted marketing campaigns require actionable, unified patient profiles made up of clinical and marketing data. Without granular data, campaigns are too broad to align specific service lines to each patient.

Here are the gaps created by disparate data:

• Gap 1: Siloed Data
  Data is spread across disparate EHRs, CRMs, and marketing platforms that don't talk to one another.
• Gap 2: Fragmented Architecture
  Because systems don't talk with each other, marketers aren't able to align patients with service lines.
• Gap 3: Inaccessible Datasets
  Because markers are unable to align patients, they can't promote specific service lines with targeted messaging.

Aligning the right patients with the right service lines requires unified patient profiles built with an integrated tech stack. This is where customer data platforms (CDPs) like Data Cloud come into play.

Solving the Use Case

We use Salesforce Data Cloud to unify patient data from EHRs, CRMs, and other marketing tools. This creates a 360-degree patient profile, giving marketing teams the data they need based on medical records, website activity, claims info, and more.

Patients with the highest propensity to engage with particular service lines can be fed into email, direct mail, mobile, and digital advertising campaigns. We typically recommend identifying profitable service lines based on gross revenue. Some of the most successful service line campaigns are:

• Cardiovascular Surgery
• Neurosurgery
• Total Joint Arthroplasty
• Orthopedic Surgery
• Interventional Cardiology
• Digital Mammography