Mistake 1: Not Creating a Vision for Health Cloud
A clear vision is a concise statement that serves as the source-of-truth your team will look back to during development. It keeps your teams focused on the long-term goal, regardless of short-term distractions or road bumps.
Some people confuse vision with mission…while both are important, they serve different roles. A mission statement declares what a company does, while a vision statement prescribes what a company aspires to achieve in the future.
Vision is crucial because every part of the project runs downstream from it – including setting goals, defining requirements, setting priorities, and determining project management style.
When creating vision, you will probably ask yourself some of these key questions:
- What problems are we trying to solve?
- What are our core values?
- Who’s pain are we hoping to relieve?
- Who will this affect internally?
- Who will this affect externally?
- What does success look like?
Vision starts with understanding your existing issues, and quantifying the impact it has on your business, patients, or partners. Establishing a shared vision requires a holistic readout of your organization. You’ll need to interview key stakeholders across sales, marketing, operations, and clinical departments to understand how a new platform will impact them. This process can uncover massive amounts of information…however, the key to strong vision is being able to condense findings into a brief summary that summarizes the project’s goals and success criteria.
Be the primary source for all mobility, independence and life-enhancing solutions
Enabling verifiable science and making lab life easier for researchers
Creating exceptional healthcare experiences
Mayo Clinic will provide an unparalleled experience as the most trusted partner for health care
Be the unmatched leader in improving quality and reducing the cost of health care for patients in the communities we serve
To be the leader and partner of choice in managing care in a value based system
Mistake 2: Not auditing bad data
Health Cloud is only as good as your data – the old adage “garbage in, garbage out” definitely applies here. Most issues are caused by duplicate, inaccurate, or bloated data. It’s vital to address data problems prior to migration, because it’s 10x as hard to correct data issues post-implementation.
According to Gartner, bad data costs the average company $15 million dollars in losses – starting with good data is vital to the fulfillment of your vision.
In order to set up your data model for success, follow these guidelines:
Check for duplicate data
Duplicate data is often created when migrating data between systems. It causes your data to be less reliable, makes personalization more of a challenge, reduces user trust, and makes reporting less accurate.
It can also cause data protection, privacy, and compliance issues for healthcare companies. On the financial side, duplicate data also creates a significant reduction in ROI due to unnecessary storage costs.
Duplicate data is often created on an on-going basis. Salesforce has tools for reducing the creation of duplicate data, including rules that prevent users from creating duplicate records in the first place, and managing duplicate data globally. Follow these three steps to get on the right track:
- Set up duplicate matching rules
- Create duplicate reports
- Document a process for merging records
Check for inaccurate data
Inaccurate data sows distrust in your users. Inaccurate data gets into Health Cloud through poor migrations, data entry errors, formatting issues, or simply the passage of time. Even the best Health Cloud implementation can’t run effectively with inaccurate data.
- Standardize input with verification rules
- Enrich data with 3rd-party partners (ZoomInfo, Definitive Healthcare)
- Hire a Salesforce Admin or Managed Services Consultant
Only include the data you need to achieve your vision
Migrating unnecessary data is one of the biggest mistakes new Health Cloud users make. It often starts with good intentions. Hypothetically, it could make your system more scalable, flexible, and powerful. However, in reality this is not the case. Not only does it create avoidable storage costs, but it introduces your organization to several security liabilities – and doesn’t take your patient’s privacy seriously…unnecessary PHI can make data breaches or unintended access far more problematic.
It’s important to practice moderation. Limit data migration to what you need to achieve your initial vision…anything more than that, and you’re setting yourself up to fail.
The fight against bad data doesn’t end at a Health Cloud implementation. Be vigilant. Routinely audit data, leverage 3rd-party tools, and reduce manual data entry on an on-going basis.
Mistake 3: Not integrating to an EHR, EMR, or ERP
Salesforce Health Cloud doesn’t replace your EHR.
As patients and healthcare partners increasingly expect personalized, transparent care models, EHRs aren’t enough to deliver consumer-grade experiences. The question is not EHR vs. CRM, but EHR + CRM.
Customer (Patient) Relationship Management
Electronic Health Record
Health Cloud exists to make the data in your EHR, EMR, or ERP actionable. If you don’t integrate, you’re missing out on the core Health Cloud value proposition – and it will be much less valuable across your organization, whether in sales, marketing, operations, or clinical departments.
Some EHRs natively integrate into Health Cloud, such as Cerner via HealtheCRM. Others require the use of third-party integration tools like Mulesoft, and the assistance of a Health Cloud implementation partner.
Regardless of the effort involved, ensuring tight integration between Health Cloud and your EHR, EMR, or ERP is crucial to reaching your vision.
Mistake 4: Not having a backup solution
Health Cloud is a constantly changing, real-time engagement platform. Whether through human error, server malfunction, or malicious insiders, data loss is particularly dangerous in the healthcare industry. Data loss not only causes costly downtime but could result in negative healthcare outcomes.
Many regulatory bodies require a backup solution as well. For instance, HIPAA compliance advocates for the number of backups you need, how long data must be retained, how storage must be distributed, and more.
Many healthcare companies assume their data is protected by the SaaS vendor – this is often not the case, and data loss will result in significant downtime and revenue loss. We typically recommend third-party Salesforce backup solutions like OwnBackup to protect uptime, retain data, and comply with strict industry regulations.
Mistake 5: Not analyzing and eliminating tech debt
Technical debt in Health Cloud is any rule, flow, dashboard, data, code, or app that doesn’t have a current purpose. Examples include hard coded references, unused validation rules, old reports, and legacy apps. Technical debt slows operations, jeopardizes stability, diminishes scalability, increases license costs, and poses security risks.
We recommend a process called “App Rationalization” as as framework for addressing tech debt in Salesforce. It’s a process that audits existing Health Cloud components to discover whether they should be kept.
Mistake 6: Not paying attention to built-in controls for compliance and security
Health Cloud-oriented organizations are able to become compliant with regulatory requirements in very approachable ways. Salesforce has been a known entity in regulated industries like fintech, government, and healthcare for almost 20 years. They have app and infrastructure security at every level and offer a variety of components that make HIPAA compliance easier.
HIPAA describes the outcomes of compliance but doesn’t lay out in detail how to achieve them. How you obtain compliant outcomes is up to you and your team – but Salesforce and Penrod are here to help.
We use the acronym “AAIT” to identify the primary controls available in Health Cloud to work towards HIPAA compliance. They include access controls, audit controls, integrity controls, and transmission security.
Health Cloud implementations should utilize:
- Salesforce Shield for platform encryption
- System Security for setting user profiles, password complexity settings, and logout rules
- Database Security for sharing policies, object permissions, and permission sets
- Interface Security to secure page layouts, set access for community pages, and lightning and Visualforce components
- Auditing & Integrity for tracking fields, events, reports, audit trails, and backups
Mistake 7: Not documenting field maps
Field mapping tells data where it needs to go. Without documenting field mappings, your integration could likely fall victim to data corruption, duplicated data, inaccurate data, and unnecessary data.
Creating documentation starts with understanding the anatomy of a field in Health Cloud.
Fields are made up of:
Friendly name of the field
Unique name used by the Health Cloud API
- Source Systems
Name of the data source
- Target Object
The parent entity for the external ID
- External ID Fields
ID of the field in the external platform
Makes the field available to users
The role the field
Here’s a simple example of how to document field mappings between Cerner and Salesforce Health Cloud.
Salesforce Health Cloud
By avoiding the common mistakes we discussed, you can create a foundation of of success for your Health Cloud implementation. It’s important to remember that viligance is not only important during implementation, but on an on-going basis as well.