Healthcare has always relied on evidence-based decision-making. One key difference between historical methods and today's practices lies in the volume of available evidence. Clinical trials, guidelines, and studies are published daily and are more accessible than ever.
In addition to new research, clinics manage patient records that contain imaging, diagnostic, and treatment information. This means that for clinicians on the floor, keeping up with all the data is challenging. Especially when they’re under a time constraint.
That’s where evidence-based, AI clinical decision support comes in. By synthesizing the research and patient data and by surfacing relevant insights, this new tooling can help transform bogged-down clinician workflows into action at the point of care. Here’s what that looks like, and what to consider before getting started.
What Is AI Clinical Decision Support?
Imagine having an artificial intelligence tool that surfaces evidence-based research in seconds, based on the prompts and questions you provide. That’s an AI clinical decision support tool. These platforms are user-friendly, typically available on desktop and mobile devices, and serve as a useful guide for making diagnostic and treatment decisions.
By using natural language processing, predictive analytics, and machine learning, these AI systems can synthesize vast amounts of data within seconds. They draw on closed systems such as peer-reviewed literature and evidence-based materials, rather than on user input.
These tools won’t replace a doctor, nurse practitioner, or PAs’ judgment; they provide AI clinical decision guidance. Without compromising real expertise, they will enable clinicians to streamline their workflows and spend more time on dedicated patient care.
How AI Supports Evidence-Based Decisions In Hospitals
Whether large or small, hospitals generate enormous amounts of clinical data, making them the ideal environments for AI-powered clinical tooling. Potential settings it could be most helpful might include:
- Emergency departments: These tools could assist with diagnostic prioritization. Algorithms could analyze presenting symptoms, vitals, and medical history to surface high-risk conditions such as a pulmonary embolism or stroke.
- Inpatient settings: Clinicians can enter patient symptoms to surface early signs of deterioration. When appropriately prompted, clinical decision support tools can alert care teams to risks such as infection or sepsis earlier than traditional methods.
- Oncology: AI clinical decision support tools offer custom templates for specialties like oncology. It also synthesizes clinical trial data, the latest treatment guidelines, and presents personalized therapy options.
- Intensive care: These tools help draft clinical notes to smooth out handoffs between care providers working around the clock on sensitive cases.
Across all scenarios, the value remains consistent. AI accelerates evidence retrieval and presents it in an easily digestible format on the fly. It streamlines workflows and returns time to clinicians where it counts.
How AI Supports Evidence-Based Decisions In Clinics
While hospitals often focus on acute care, outpatient clinics face a different set of challenges. Here, clinicians must manage large patient panels, preventative care needs, chronic disease management, and more within short visit windows.
AI clinical decision support tools are increasingly tailored to these environments. In primary care, tools can flag care gaps, such as overdue screenings and vaccinations. In chronic disease management, AI can recommend care plans and identify complication risks. Hypertension, diabetes, and heart disease management are just a few examples of ailments that could benefit from predictive insights.
In clinical settings, AI can also surface drug interactions, contraindications, and dosing risks within a few sections. In these ways, AI helps outpatient clinicians apply evidence efficiently within their tight workflows.
Challenges And Implementation
Although promising, implementing AI as a clinical decision support tool requires planning. Data quality, for one, remains a foundational issue. Tools that use algorithms trained on incomplete or nonrepresentative datasets may produce biased outputs. Those that retrain on inputs, use unreliable sources, or fail to comply with regulations such as HIPAA must also be avoided, as they are not secure.
Workflow integration also presents a challenge. If the AI tooling has limited or siloed features, it could cause more administrative burden, not less. Additionally, if the tool is complex to learn and use, the time savings could take months.
Finally, consider cost. If the tools cost hundreds of dollars per seat, it’s effectively inaccessible or not scalable for practices of all kinds. For these reasons, clinician oversight is essential.
Accessibility And Care: About Doximity
Clinicians rely on Doximity to stay informed about emerging research and to guide clinical workflows. It’s user-friendly, HIPAA-compliant, and uses AI to operate within closed systems that source information from reputable, often peer-reviewed, literature.
DoxGPT works similarly to public GPT products. Clinicians can simply ask a question and quickly receive guidance from trusted sources. Users can also prompt DoxGPT to draft documents and surface drug-dosing information. Doctors across all specialties can customize templates and reuse prompts to tailor their DoxGPT workflow to their niche.
Doximity Scribe live records patient appointments and generates a summary of the visit to save clinicians' time on manual note-taking. Scribe captures and transcribes key points while excluding small talk from the final summary. Clinicians maintain control by reviewing the summary and editing as needed.
Both tools are AI-powered, secure, and can serve as guides to reduce administrative burden and improve workflow efficiency. For those seeking simple, trusted, effective tooling, Doximity is a fit.
Try It For Free Today
As hospitals and clinics continue adopting new technologies, Doximity remains an accessible, free resource for practices that need it. AI will play an increasingly central role in translating medical knowledge into stronger workflows, and Doximity makes it happen.
Whether using the AI-powered DoxGPT or Doximity Scribe, or the telehealth tool Doximity Dialer, getting started is as simple as signing up with valid healthcare credentials. Sign up and get started today.