How Thinkitive AI Scribe Eliminates 70% of Clinical Documentation Time

Do you know what the biggest problem that healthcare providers have to face on a daily basis is?

Believe it or not, but it’s writing for the time we live in – typing.

Seeing a doctor write or type just feels so weird, right? We always imagine them working with patients or studying something physical and taking notes, anything but typing.

And that is the biggest problem right now. You see, according to a study by the American College of Physicians, for every hour a physician spends on patient care, they have to spend two additional hours on EHR and administrative work. This is the reason it feels weird to see doctors, especially physicians, typing.

Moreover, this is the tip of the iceberg; the more you dig into such problems, the more it paints a scary picture. You see, back in 2016, when EHR was just trying to reach every hospital in the United States, the AMA reported that only 27% of physicians’ time went into seeing their patients.

Interestingly, one of our latest ventures with a new EHR system we developed with an AI scribe feature has proved transformative for a healthcare system. Post implementation, it eliminated almost 70% of the clinical documentation time. Which is quite more than the 31% rise said by many providers, according to various media sources.

However, while the genesis started with custom EHR software development, the magic was brought to life with EHR data migration. This is the secret that allowed healthcare physicians to reduce their documentation by a whopping 70%.

On that note, in this blog, let’s briefly discuss the importance of custom EHR solutions and how EHR data migration, powering AI features, can transform practices.

So, without further ado, let’s get started!

Building the Right Foundation for Your New EHR Platform

Let’s start with the base – your new EHR platform. Building the right foundation for this platform is crucial because when you are developing it, you will also plan for migration and train your AI modules.

On that note, let’s have a look at the intricacies in this:

• Building Multi-Specialty EHR Architecture for Future Growth: Remember, your practice is multi-specialty or in the future it will naturally turn towards it. That is why your new EHR system should support their unique needs, workflows, and clinical processes. Scalability consideration here is important for the holistic and simultaneous growth of your practice and platform.

• Creating an Interoperable Healthcare Ecosystem: During development, EHR data migration pipelines will also work, and for your system to be able to share information with different systems, it needs to follow the interoperability standards like HL7 and FHIR. Furthermore, for ingrained interoperability, building a FHIR-native healthcare platform can go a long way as it enables easy connectivity and real-time data sharing between disparate healthcare systems.

• Protecting Patient Data Throughout the Migration Journey: Having security measures in place, adhering to your system with the compliance and other governing rules and regulations, is extremely necessary. As they safeguard patient information during and after EHR system migration. Also, in case of any mishaps, it helps you navigate through the legalities and other intricacies very smoothly.

Why EHR Data Migration Has Become a Strategic Priority

Now, coming to the crust on which your entire system’s scope depends – Electronic Health Records migration and why it is so important in the modern healthcare landscape. Along with that, let’s also cover why it has become a strategic priority for many healthcare practices.

Well, the reason why healthcare data migration is in talks is due to the inefficiencies of legacy healthcare systems. And several studies suggest that almost 60% to 76% of healthcare systems still use legacy systems.

Now, the problem with legacy systems is that achieving interoperability or giving your system the ability to exchange data with other systems is quite complicated, limited, and difficult.

In short, it is a time-consuming process. This is where electronic health record migration comes into the picture. Legacy EHR migration accelerates data sharing capabilities between systems effectively and efficiently. It enables your systems to exchange data in real-time with enhanced security and accuracy.

However, interoperability, compliance, and scalability challenges can complicate this process, but with the right partner, it can be easily overcome. This can risk delaying the modernization initiatives, but it needs to be done to ensure every stone is covered.

Now, starting your EHR data migration initiatives during development helps you align your system with your business and clinical needs. This way, your administrative processes get streamlined and efficient, while the accuracy and other aspects of your clinical aspects get improved.

Planning a Successful EHR System Migration

The key to a successful EHR system migration is hidden in its planning. Let’s have a look at the steps that are involved in this planning phase and how it sets your EHR migration strategy.

• Assess Existing System & Data: The first thing you need to do is assess your current system. Only when you know where the problem is can you address and fix it. The access system knows what you need, and along with the system, you also need to check your data readiness. This defines the scope of your healthcare data migration and what steps you need to take for clinical data conversion.

• Building an Effective EHR Migration Strategy: Once you know what you have to do, you can build an effective strategy that will help you achieve your goals. For this, you can choose any of the three approaches given in the table below. Depending on your needs, your choice can change.

Criteria	Big Bang Migration	Phased Migration	Parallel Migration
Approach	The entire EHR system and data are migrated in a single cutover event.	Migration is completed in stages, department by department or module by module.	Both legacy and new EHR systems run simultaneously until the new system is fully validated.
Implementation Speed	Fastest deployment approach with immediate transition.	Moderate pace as migration is spread over weeks or months.	Slowest approach due to maintaining two systems concurrently.
Risk Level	High risk because any issue affects the entire organization at once.	Moderate risk since issues are isolated to specific departments or modules.	Lowest risk because the legacy system remains available as a fallback.
Operational Impact	Significant short-term disruption but quicker overall adaptation.	Minimal disruption with gradual user adoption and training.	Very low disruption, though staff may need to work in both systems temporarily.
Best For	Smaller healthcare organizations, clinics, or well-tested EHR replacements with limited complexity.	Mid-sized healthcare systems seeking controlled adoption and risk mitigation.	Large hospitals, health systems, and mission-critical environments where downtime or data loss is unacceptable.

While going forward with this EHR migration strategy, discuss this with all the stakeholders involved in this process. This will help you align your business needs and make the changes actually beneficial for its end users.

Managing Data Conversion, Mapping & Validation

Remember, we talked about data conversion and converting data?

Well, this is one of the most important parts of your EHR migration strategy. In simple terms, you need to convert your data in a way that other healthcare systems can understand and make sense of.

For that, you need to know some of the data mapping fundamentals:

• Data Inventory: Identify all patient, clinical, financial, and operational data that needs to be migrated.

• Field Mapping: Match data fields from the legacy EHR to their corresponding fields of the new system.

• Data Standardization: Converting data into standardized formats, terminologies, and coding systems for consistency.

• Data Validation: Verification of the migrated data for accuracy, completeness, and correct placement in the new system.

• Testing & Reconciliation: Perform migration testing and compare source and destination records to ensure data integrity.

However, following these fundamentals is not a walk in the park. The first challenge comes in clinical data conversion. You see, when migrating patient records, medications, allergies, diagnoses, lab results, and clinical notes, they are often complex. On top of that, with different data structures, formats, and coding standards between the EHR systems, achieving interoperability can be extremely difficult.

You alone need to manage ETL processes for healthcare data migration. This involves extracting data from legacy systems, then transforming it into the required format and loading it into the EHR with accuracy and compliance.

Both these tasks mentioned above require experience and accuracy that of a machine. With a seasoned partner, it can easily be achieved.

Having said that, before migration, you must also remove duplicate records, correct the inaccurate data, use standardized formats, and archive outdated information to improve data quality and system performance.

Once all this is done, you will enter the testing for the EHR data migration. Here you will conduct a trial migration, validate data accuracy, and verify workflows. If required, you might even have to provide training to the users for a smooth transition to the new system.

Here is an EHR data migration checklist that might come in handy for your EHR data migration project:

EHR Data Migration Checklist	✓
Assess and inventory existing data	✓
Map data fields between systems	✓
Cleanse and remove duplicate records	✓
Standardize formats and coding systems	✓
Test migration with sample datasets	✓
Validate data accuracy and completeness	✓
Train users and prepare for go-live	✓
Monitor and audit post-migration performance	✓

Modernizing Clinical & Administrative Workflows After Migration

After a successful EHR data migration, the modernization of clinical and administrative workflows starts. Remember the training your AI modules on during the EHR data migration we talked about?

Well, this is where things actually start to take shape, because that is only half of the process. On that note, let’s see some of the aspects that are typically involved in modernizing clinical and administrative workflows.

• Transforming Clinical Documentation with AI: Since you have been preparing AI during the EHR data migration process, it knows certain intricacies about the way you want your data. So, when you implement these models in the workplace, this reduces the documentation burden for providers by a huge margin. On top of that, this also improves the productivity and efficiency of the users.

• Enabling Intelligent Clinical Workflows: One of the most talked-about AI modules is ambient clinical intelligence. By automatically capturing conversations and interactions in real-time, it can be used to improve documentation accuracy and automate most of the workflows. In simple words, you don’t have to copy and paste things from one system to another.

• Using AI to Simplify Prior Authorization: AI-powered prior authorization is another use case of AI that can solve many problems for healthcare practices. You see, since prior authorization takes a lot of time manually, it can reduce the administrative bottlenecks related to this. If implemented correctly, it can improve the approval rate with better documentation.

Turning Migrated Data Into Better Healthcare Outcomes

Just migrating data is not enough; it needs to be put to use so that better care can be delivered. One of the integral parts of this is supporting value-based care initiatives. For instance, with accurate data, you can measure every progress around the care you deliver.

However, something that you need to know about this is aligning your technology aspects with value-based reimbursement models. This is crucial as it leads you to holistic care delivery.

The major benefit still cannot be seen directly, as many practices are reducing physician burnout. This is done by minimizing administrative workloads and addressing the inefficiencies that streamlines these administrative processes.

This also helps in improving provider satisfaction and retaining patients by giving every user a delightful experience.

Why Custom EHR Software Development Delivers Long-Term Value

For a simple thing like EHR data migration and including AI-powered features into your EHR system, why should you choose a custom EHR Software, right?

Well, a custom EHR gives you greater flexibility in customization efforts and gives you complete ownership over the data and system. On top of that, with FHIR standards being ingrained from the start, it helps in long-term scalability and easy integration across systems.

On top of that, for future-proofing these investments, you can already shift the system to cloud-native, so that accessibility is ensured at all times.

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