However, many healthcare organizations struggle to fully leverage their EHR investments. Gaps in EHR adoption and usage lead to workflow inefficiencies, poor data quality, and suboptimal care.
In this article, we’ll explore 5 of the most common EHR gaps and provide actionable strategies to address them. Filling these gaps can help your organization extract more value from your EHR system and support better patient outcomes.
Gap 1: Disconnected Systems and Data Silos
A major goal of EHR adoption is consolidating patient information into a unified medical record. However, many healthcare organizations end up with scattered patient data locked in separate departments and systems. This leads to an incomplete view of the patient and makes care coordination difficult.
Some common causes of data silos include:
- Maintaining legacy departmental systems instead of fully transitioning to the EHR
- Allowing clinicians to use personal preferences for documentation systems
- Adding software applications without integrating them with the EHR
- Inadequate identity management and patient matching capabilities
To break down data silos, healthcare IT leaders need to take deliberate steps to integrate systems and consolidate data repositories.
Some key strategies include:
- Performing an Application Inventory/Rationalization
Catalog all clinical and administrative systems used across the organization and identify redundant and obsolete applications that can be retired. Determine which applications need deeper integration with the core EHR system. - Implementing Enterprise Master Patient Indexing
Obtain software that can link records from disparate systems via a Master Patient Index based on identifiable data elements. This allows linking of records belonging to the same patient. - Requiring System Interfaces for All New Software
For any new system under consideration, require details on how it will interface with the EHR. Build integration requirements into software contracts. - Utilizing Data Warehouses and Analytics Tools
Extract data from departmental systems and the EHR into a central data warehouse. Apply analytics to gain enterprise views of organizational data. - Defining Data Transition Workflows
Develop standard workflows for migrating legacy data (e.g. scans, departmental records) into the consolidated EHR system.
Filling this gap requires a strategic, coordinated effort across IT, clinical, and administrative leaders. The good news is that platforms like FHIR and cloud computing have made interfacing systems and sharing data much more achievable for modern healthcare IT environments.
Gap 2: Clinical Documentation and Coding Gaps
Accurate and complete clinical documentation is essential for care coordination, revenue cycle management, and demonstrating quality of care. However, many healthcare organizations struggle with poor clinical documentation habits that lead to downstream issues.
Some common documentation and coding gaps include:
- Missing or vague progress notes that lack sufficient detail
- Inconsistent use of structured data fields vs. free text notes
- Clinicians not entering codes completely or accurately
- Documentation that doesn’t adequately support billing codes
- Variability in documentation style across clinicians
Improving clinical documentation requires addressing clinician work habits through training interventions.
Some best practices include:
- Ongoing Documentation Training
Provide regular training on documentation requirements and best practices, particularly for new clinicians. Include periodic refresher training. - Documentation Guidelines and Tip Sheets
Create and distribute clear guidelines and tip sheets on documentation expectations and how to avoid common mistakes. - Structuring Notes via Templates and Data Fields
Configure the EHR to guide complete documentation via templates, forms, and discrete data fields tailored to different visit types. - Clinical Documentation Specialists
Employ specialized clinicians to educate staff on documentation, review notes, and provide feedback to improve documentation quality. - Documentation Performance Feedback
Audit documentation periodically and share clinician performance reports and benchmarking data to encourage improvement.
With persistence and multifaceted interventions, healthcare organizations can improve documentation practices over time. This enhances documentation quality for clinical care and billing purposes.
Gap 3: Clinical Decision Support Underutilization
Many EHRs now include sophisticated clinical decision support tools to assist clinicians with tasks like medication ordering, care gap identification, and diagnostics. However, lack of clinician adoption results in wasted investments and missed opportunities to improve care.
Some common barriers to clinical decision support adoption include:
- Alert fatigue leading clinicians to ignore warnings and recommendations
- Workflows not accounting for responding to alerts and reminders
- Lack of customization and relevance to the clinical context
- Decision support not integrated into user workflows
- Clinicians not adequately trained on available tools
Boosting use of clinical decision support requires carefully designing and implementing tools with clinician adoption in mind.
Some best practices include:
- Limiting Alerts to the Highest Priority Warnings
Configure systems to avoid overload by focusing alerts on the most critical, high-severity items needing clinician attention. - Surfacing Guidance at Relevant Points in Workflow
Deliver guidance such as lab reference information, medication options, and care gap closure instructions directly within the clinician’s workflow at the appropriate time. - Providing Decision Aids for Complex Cases
For difficult cases with multiple treatment options, provide relevant clinical calculators, algorithms, and protocols to help guide clinician decisions. - Soliciting Clinician Feedback and Preferences
Actively engage end users in the design, implementation, and optimization of clinical decision support tools to promote adoption. - Evaluating Usage Patterns and Iterating
Analyze usage data to identify adopted vs. ignored tools. Refine and enhance the most utilized decision aids while phasing out those consistently ignored.
With focus on clinician-centered design and ongoing enhancement based on feedback, healthcare IT can deliver clinical decision support that becomes an indispensable part of the care delivery workflow.
Gap 4: Patient Portal Underutilization
Patient portals represent a significant opportunity to foster patient engagement. However, many organizations report lackluster adoption and usage of their patient portal tools. Without active participation, portals fail to achieve their potential for connecting patients to their health data, care teams, and related services. Providers should ask themselves, ‘why aren’t patients using patient portals?‘
Some common barriers contributing to poor patient portal adoption include:
- Complex, non-intuitive portal interfaces that frustrate patients
- Lack of promotion and enrollment of patients into the portal
- Patients not seeing meaningful utility and value from the portal
- Fragmented patient data from unintegrated systems
- Privacy concerns about security of online health data
- Access barriers for disadvantaged populations
There are a few key strategies healthcare organizations can use to drive better adoption of patient portals:
- Performing User Interface Enhancements
Apply health literacy principles and user experience (UX) design to create intuitive navigation and simplify portal use for patients. - Promoting Portal Awareness and Enrollment
Educate patients on portal capabilities and benefits. Automate patient sign-ups at first contact and discharge. Offer enrollment assistance navigators. - Connecting the Portal to Useful Tools and Services
Integrate elements like prescription refill requests, appointment self-scheduling, patient education, and secure messaging to make the portal more functional. - Addressing Digital Literacy Needs
For vulnerable populations, provide training on portal use and access to devices/internet to reduce barriers to adoption. - Communicating Clear Privacy Safeguards
Be transparent about portal security measures to foster trust. Allow patients to restrict visibility of sensitive health information.
Achieving high portal enrollment and regular usage requires understanding and addressing root causes of patient disinterest and friction. But the effort pays dividends in terms of better access, communication, and engagement with the patients you serve.
Gap 5: Analytics and Reporting Limitations
EHRs contain a wealth of data, but difficulty accessing, analyzing, and distributing insights from the data prevents optimal use. Data transparency and governance shortcomings also inhibit self-service analytics. These limitations result in missed opportunities to understand practice patterns and patient populations to continuously improve care.
Some common barriers around EHR analytics and reporting include:
- Metrics and reports being predefined but inflexible to user needs
- Siloed data in different systems preventing enterprise analysis
- Lack of intuitive data visualization tools for clinicians
- IT bottleneck for developing custom analytics content
- Undefined data stewardship roles and policies
To maximize the analytical value of EHR data, healthcare organizations should focus on the following areas:
- Providing Self-Service Analytics Tools
Equip clinical and administrative users to access/analyze data independently through intuitive analytics platforms and dashboards designed for their needs. - Developing Data Science Expertise
Hire or train specialized resources to apply techniques like machine learning and natural language processing to EHR data analysis. - Establishing Data Transparency Policies
Catalog available data sources and attributes. Define consistent policies for data requests, access, and quality assurance. - Leveraging a Data Warehouse Platform
Aggregate enterprise data into a central warehouse optimized for analysis and visualization. This enables multi-source analysis. - Building Partnerships Between IT and Users
Have IT partner directly with operational areas to understand their use cases and collaborate on designing analytics that are tailored to business needs. Ensure IT has resources dedicated to analytics support and customization. This helps shift perspective from IT controlling reports to enabling users to directly answer questions from their own data. It also fosters shared data stewardship rather than siloed data ownership. Strong partnerships between IT and business stakeholders are key to migrating from predefined static reporting to flexible analytics.
With better alignment between technical experts and day-to-day data needs, healthcare organizations can realize the full promise of analytics-driven insights from their EHR systems.
Summary
EHR adoption represents a significant investment for healthcare organizations. However, simply purchasing and installing an EHR does not guarantee realization of expected benefits – true success requires closing common gaps that prevent these systems from being leveraged to their full potential.
By being aware of pitfalls like data silos, documentation problems, lack of decision support adoption, poor patient portal uptake, and analytics limitations, healthcare leaders can take proactive steps to avoid them. Applying the strategies discussed in this article can help organizations fill EHR gaps and realize greater improvements in patient care and business operations.
While some challenges require evolving technologies to fully solve, a great deal can be accomplished through the diligent efforts of healthcare organization stakeholders working together across IT, administration, and clinical domains. This teamwork and attention to maximizing EHR capabilities for all users is critical for transforming these systems from passive repositories of patient data to dynamic tools that drive improvements in clinical quality, efficiency, and decision making.
Healthcare will continue to be shaped by emerging information technologies. Organizations that build strong competencies in areas like system integration, process improvement, analytics, and user-centered design will be best positioned to adapt and succeed as EHRs and other complex platforms become further ingrained into the fabric of healthcare delivery. Focusing efforts on filling known EHR gaps today lays the groundwork for keeping pace with the innovative solutions on the horizon.
