From Analog to Digital Neurology: 3 Steps to Better Inform Patient Care

Dr. Nandor Pinter, Director of Neuroimaging Research, DENT Institute
Dr. Murray Gillies, General Manager of Digital Cognitive Dx Venture, Philips
The field of neurology is at an inflection point. With a growing aging population, neurologists are facing an increasing number of patients needing care, and the pent-up demand for services due to COVID-19 only exacerbates this issue. The pressure on neurologists is enormous, with surveys indicating excessive stress caused by inefficient workflow and mounting paperwork 1,2. It is becoming increasingly clear that the traditional analog neurological exam and referral system is overwhelmed, and that long waiting times are becoming the norm, impeding prompt care delivery3,4.  

For these patients, every moment counts when it comes to diagnosing and developing a treatment plan to address the often-irreversible effects of neurological disease. Neurologists need to be equipped with modern tools that provide the right data at the right time, and that helps them make confident diagnoses and effective treatment plans. This won’t happen overnight, though. By adopting clinically-driven solutions that allow for true data integration and by moving toward a holistic, personalized approach to care, neurology can overcome its historical burdens and advance the future of patient care. 

The Digital Revolution and Neurology 

The neurologist is the care orchestrator and the data integrator who refers patients out to other physicians and receives back clinical reports. In recent decades, the receiving physicians of the neurologist’s network have undergone a digital revolution. Take radiology for example, where radiologists increasingly rely on intelligent computer algorithms to extract meaningful information from scans, streamlining their workflows and boosting efficiency.

Similar advances are also starting to happen at the neuropsychologist’s office where antiquated paper-based cognitive tests and hand-written reports of results are slowly being replaced by more digital solutions with deeper insights. As the data sources flowing back to neurology become fully digital, the neurologist’s position will inevitably also change. Due to the data integrator role of the neurologist, digitization will enable advanced clinical decision support.

There is huge untapped potential in combining data streams with end-to-end analytics to enhance clinical decision-making and avoid both delayed treatment plans and siloed results. By following these three steps, neurologists will be better equipped to both keep pace with a growing volume of patients with complex needs as well as feel more empowered to make informed, data-driven decisions.

1. Embrace Clinically Driven Solutions 

As neurology becomes digital, applying AI algorithms to the data flowing to the neurologist would support efficient neurodiagnostics and enable neurologists to spend more time in other areas of care delivery. Because medicine requires precise measures, AI-powered tools for all parts of the neurological exam need to be thoroughly validated to ensure the results they provide are the same as those interpreted by a clinician. 

That being said, while AI and predictive analytics are well-intentioned and can improve workflows, they are only one component of achieving overarching clinically-focused goals. These tools are useful but are a means to the end goal of improving clinical outcomes, such as reducing waiting lists, providing a more precise diagnosis, or monitoring therapy. Whether the specific technology that will take us there is AI or rule-based is secondary.

2. Adopt Cloud-Based Systems for Enhanced Data Sharing

Interoperability will be a key step in advancing neurology. Both structured and unstructured data must be mapped and populated into one place to present neurologists with a complete view of the patient. Today’s workload burden in neurology arises largely from the fact that data points are stored in separate locations and inconsistent formats, and it is time-consuming and laborious to find and integrate them for decision-making.

An intelligent cloud-based solution could map data sources and identify all the relevant diagnostic and therapeutic data, from radiology reports to clinical notes to blood test results or cognitive deficits, to present the full patient picture to the neurologist. Organizing this data and highlighting the most relevant aspects for a neurologist can prompt specific, personalized care pathways.

For example, the multiple sclerosis pathway could present a timeline of lesion load changes and clinical attacks, and correlate it with drug therapy and cognitive changes. This provides the neurologist with a clear treatment plan, while also expediting the patient’s time to care. 

Moreover, a robust, secure cloud that allows for easily accessible and shareable data will both facilitate the transmission of data over more sites, such as academic institutions and research centers, helping to further advance our understanding of neurological conditions. By working with hundreds of millions of data points that are acquired, stored, and analyzed in standardized formats, the solution can directly inform future developments of clinical practice based on real-life data. Biomarker research, pharmacological trials, or developing new diagnostic applications can all benefit from such a comprehensive and integrated system.

3. Move Toward Personalized Medicine by Leveraging Clinical Pathways

Shifting our mindset to a personalized medicine approach and moving away from the typical one-size-fits-all will help optimize clinical care quality. The clinical care pathway is a process created by a series of consecutive decisions, which are made by understanding the chain of events in a patient’s own journey, as well as the other patients like them. Capturing data on a continuous basis can paint typical pathways for a given disease, allowing the neurologist to spot deviations from the “norm” that can be tracked per patient.

We can also consider a patient’s lifestyle and use data from cognitive assessments to extend care into the home, leveraging digital therapies and monitoring solutions to assess which activities of daily living are viable. Neurological data can also be used to predict milestones, such as when a patient may need to move into a senior living facility or other supported-care environments.

The more structured data that is accumulated and the more clinical guidelines that are available, the more tailored the care pathway recommendations will become for individual patients, paving the way for personalized neurology.

Looking Ahead to a Promising Future for Neurology

The workload and inefficient processes facing neurologists today are unsustainable. Focusing on the clinically-driven solutions and operating in cloud-based, interoperable systems will help neurology streamline operations and achieve confident clinical decisions. Such solutions would have a positive impact not only on daily clinical practice but on the future of neurology too. While helping the practice of today it can create the practice of tomorrow. 



2. Busis NA, Shanafelt TD, Keran CM, et al. Burnout, career satisfaction, and well-being among US neurologists in 2016. Neurology 2017;88:797-808.

3 MarkeTech Group, Davis, CA. Study of 75 neurologists with clinical practices, commissioned by Philips 2018.


*Dr Nandor Pinter is a paid consultant for Philips via NeuroNet Pro LLC.

Show CommentsClose Comments

Leave a comment

%d bloggers like this: