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AI medical scribe adoption is the process of scaling the implementation of artificial intelligence-powered scribing tools to help automate parts of clinical documentation for medical practitioners. When adopting an AI medical scribe in your healthcare practice, it’s crucial to carefully plan the implementation process to ensure a smooth and productive transition to AI-supported clinical documentation.
Each service will have different considerations. However, successful AI medical scribe adoption usually involves steps such as clarifying goals, deciding on KPIs, selecting a product, preparing for rollout, and performing ongoing monitoring and evaluation.
In this article, we provide a detailed step-by-step guide covering everything you need to know about AI medical scribe adoption. Our goal is to help you develop an effective implementation plan for your service so that you can get the most out of an AI medical scribe like Heidi.
The rate of adoption of AI medical scribes is steadily increasing, with a recent survey by the American Medical Association (AMA) revealing that 2 in 3 physicians are now using AI in their practice.
Despite their widespread acceptance and appeal, it remains imperative that organizations carefully plan their implementation strategy when adopting an AI medical scribe. Otherwise, a small oversight in something like product choice or the onboarding process can severely limit uptake among clinicians and reduce the benefits obtained by this groundbreaking new technology.
Below are seven key high-level considerations to think about before embarking on AI medical scribe adoption. Knowing the answers to these questions will help you gather the basic information you need to start evaluating vendors and planning for successful implementation.
For most organizations, goals and priorities behind AI medical scribe adoption centre around achieving one or more of the following positive outcomes:
Clearly defining your primary objectives at the outset helps focus all subsequent decisions around AI medical scribe adoption on supporting these key aims.
Understanding your expected usage volume is critical for budgeting, vendor negotiations, and implementation planning. Utilization of a tool also directly correlates with its transformational potential within your organization. Tools that are used more will have a larger impact across organisations.
To accurately estimate usage volume, consider:
Modern AI medical scribes offer varying levels of functionality beyond basic transcription.
We recommend creating a list of “must-have” vs. “nice-to-have” features, which may comprise the following:
The two biggest factors influencing AI medical scribe costs are the number of required seats (active users) and choice of vendor.
Medical records software integrations and team capabilities have some influence on price. However, it’s fair to say that the features of an AI medical scribe don’t necessarily correlate to its price. For example, Heidi has a Free tier with features comparable to some products that cost $150+ per seat, per month.
The best approach regarding budget is to decide on an ideal per-seat fee, which can then guide vendor selection when you get to that stage.
Buy-in from clinical staff is crucial to successful AI medical scribe adoption.
While most clinicians are supportive, it’s worth surveying staff regarding their thoughts, hopes, fears, and opinions about the implementation of an AI medical scribe.
Opening this dialogue early in the process paves the way for clinicians to be heard and included in the process. It also allows potential barriers to adoption to be identified and addressed prior to commencing rollout.
Familiarizing yourself with any regional regulations or local guidance before adopting an AI medical scribe is vital.
This knowledge ensures that any product you choose is compliant with local healthcare privacy and data security regulations. It also provides important context for expectations of how an AI medical scribe should be implemented in your region, along with any restrictions for use.
The NHS England Guidance on the use of AI-enabled ambient scribing products in health and care settings is a good example of regional AI medical scribe adoption guidance. If similar implementation guidelines are not available in your area, consider consulting your professional body or healthcare authority for advice.
Heidi CEO and Co-Founder, Dr. Thomas Kelly, shares what drives successful adoption | Learn more about Enterprise
Demonstrating the power of pairing a high-quality AI medical scribe with a thoughtful implementation plan, Modality Partnership (the largest NHS GP super-partnership) just released results from their trial of Heidi Health.
Modality reported the following results after 47 primary care doctors used Heidi across more than 2,800 patient consultations:
Following the successful pilot, Modality has now scaled Heidi to over 200 clinicians across its network of 53 GP surgeries. Heidi is used by 1 in 2 GPs across the UK, in 15 NHS trusts, and supports over 1.5 million NHS appointments every month.
Despite their proven benefits, there are some challenges and potential risks associated with AI medical scribe adoption. While these can generally be managed effectively through proper planning, training, and oversight, managers and leaders must be aware of these considerations during implementation.
In general, risks associated with AI medical scribe use can be avoided by following the good clinical protocols and practices already in place around technology-supported clinical documentation. Therefore, the four main points below serve mainly to increase awareness on each topic, not to provide a detailed risk management strategy.
Like human scribes, AI tools occasionally make mistakes. While not insignificant, this risk is entirely overcome by adhering to standard practices regarding appropriate review of clinical documentation before it’s placed on the medical record.
When a student, junior doctor, human scribe, or administrative assistant supports the documentation process, the treating clinician retains full responsibility for ensuring the accuracy of all AI-generated documentation that’s added to the patient’s medical record.
Fortunately, well-designed AI medical scribes like Heidi make reviewing and editing AI-generated documentation a breeze. The average 50% reduction in daily documentation time reported by Heidi customers includes the thoughtful review of every note and document produced by the scribe.
AI medical scribes must comply with all healthcare data security and privacy regulations for their region of operation (e.g., HIPAA, GDPR, APP).
Ensuring compliance with this aspect of AI medical scribe adoption doesn’t have to be complicated. Simply familiarize yourself with the requirements for your location (they are essentially the same as for an EHR, PMS, or EMR). Then, confirm compliance with relevant regulations via a vendor’s website or customer support staff.
For an example of what to expect from an AI medical scribe whose leadership takes privacy and data security seriously, check out Heidi’s safety information and audited compliance with relevant security regulations.
Data security is perhaps the main medicolegal consideration with AI medical scribe adoption. However, two other issues warrant attention.
Patient consent. Most regions require clinicians to seek permission from the patient before using an AI medical scribe in a session. At Heidi, we ensure this crucial step is never overlooked through the use of a consent pop-up before each session.
Risk of bias. Because they are trained on human data, AI tools and algorithms may perpetuate existing biases present in society. Heidi’s quality assurance and risk mitigation team monitors for and addresses instances of model bias. However, clinicians should also be vigilant about identifying, correcting, and reporting any terminology or behavior that might indicate subtle or overt cultural bias in AI-generated documentation.
When implemented poorly, even the most intuitive tool can interrupt existing workflows and make clinicians’ lives harder, rather than easier.
Most clinicians find that a well-designed AI medical scribe fits rather seamlessly into their current practices. However, there’s still a learning curve, and when planning for AI medical scribe adoption, organizations should account for additional training needs throughout the process.
Urologist, Dr. David Canes, demonstrates his workflow with Heidi
At Heidi, we have a custom onboarding process that provides tailored support to organizations and individual clinicians undertaking AI medical scribe adoption. However, even if you choose another vendor, following the steps in the guide below will provide the best chance of success.
How Heidi’s clinician-led approach supports AI medical scribe adoption
Heidi is trusted to support over 2 million clinical sessions each week, worldwide. Our experienced implementation team has assisted clinicians around the world with safe and effective AI medical scribe adoption in practice areas as diverse as primary care, behavioral health, pediatrics, allied health, urology, and even veterinary medicine.
With a strong track record of delivering positive ROI across all areas of the healthcare system, Heidi has earned a reputation as a reliable partner that helps clinicians and organizations realize the full benefits of AI medical scribe adoption. Here are just a few of the ways Heidi stands out as a leading product and company:
Built for security from the ground up, Heidi meets the highest standards for healthcare data security and regulatory compliance. We’re fully compliant with HIPAA, GDPR, PIPEDA, NHS guidance requirements, and (APP), while also maintaining active security certifications like ISO 27001, SOC2, and Cyber Essentials Plus.
Activation rate (the percentage of clinicians utilizing the scribe) is the key requirement for AI medical scribe adoption in healthcare. Put simply, no matter how good a product is, if clinicians don’t use it, no one can benefit. Most AI scribe implementations see activation rates of 20–40%, whereas Heidi averages 60–80% activation.