Medical Documentation : Advancements And It’s Impact On Patient Experiences And Outcomes
Digital health records have transformed the way contemporary medicine is practiced. Electronic health records (EHRs) are now being created, used, edited, and viewed by multiple entities like primary care physicians, hospitals, insurance companies, and patients. EHR systems continue to evolve as a system of record, a digital translation of paper-based records, with a focus on information collection, storage, and retrieval for compliance and risk mitigation. While EHRs demand substantial investments from providers, they are also associated with clinician frustration on account of:
- Increased documentation burden
- Reduced face-to-face interaction with patients
- Hampered earning potential
- Clinically incomplete or inaccurate data
- Risk of HIPAA compliance violations
- Keeping patient health information safe
- Ensuring standardization and patient record portability
- Extended workdays, backlogs, and information latency
In response to the shortcomings of EHR systems and the pursuit of maximization of impact on patient experiences and outcomes, clinical documentation solutions have evolved along two primary vectors:
(i) clinician burden alleviation approach and
(ii) technology-led innovation adoption.
The graphic above shows the trajectory of the evolution of clinical documentation across these two vectors.
What Were Favoured Until Now: Human-Led Solutions
Human-led systems task clinicians with creating documentation but provide tools to make the task simpler and more effective, for example with dictation support, semantic checking, and templates. The foundation for structured codified digital health records was laid with Direct Data Entry into EHR Systems by physicians. However, their point-and-click interface and long system response times meant that more than 1/3 of patient face-to-face time was spent on the EHR System UI and extensive typing rendering this ‘self-service’ approach cost ineffective, prone to data entry errors, and poor physician acceptance.
Computer-assisted transcription using Desktop Dictation Software provides documentation without the need for typing by leveraging speech recognition and facilitating movement between patient encounter fields in the EHR system more efficiently using simple voice commands. However, they come with a steep learning curve, and the challenge of iterative error correction resulting from inaccuracies due to deficiencies in the lexicon – as a result this technology-enabled ‘self-service’ solution too was doing precious little other than saving typing effort for physicians. Also, limitations on account of linguistic variations and preferred use of medical terminology were found to impact the quality of transcription adversely.
As the need for EHR documentation spiraled, and ‘self-service’ options failed to deliver on the promise of reducing physician burden, hired services (outsourcing) options were considered. The use of a Live/Remote Scribe (physician assistant) who listens to the patient-physician encounters, and documents the encounter in digital documents (PDF) or directly in EHR systems on behalf of the physician, began to find favor. Physicians found themselves to be more productive and more focused on patient outcomes than being worried about pulling templates or typing/dictating the reports into the computer. The challenges of time-intensive training and onboarding of scribes, managing high turnover rates (attrition), and avoiding the potential risk of backlogs on account of batch processing meant that these solution approaches were ‘high-touch’, came with incremental costs, and lacked scalability. Recent incidents of patient data breaches at medical transcription service providers’ end also highlight the concerns around patient data safety.
Some service providers who are on their journey to build fully digital solutions are providing part human-led and part system-led hybrid solutions in the interim where clinicians are tasked with generating analog summaries of a clinical encounter, a service provider is hired to convert the analog conversation summaries into digital data, to facilitate workflows for review and approval, and to upload the approved digital data into EHR systems. This is to compensate for the inadequacies of their nascent system-led components with human talent. The performance of these solutions is not significantly different than the outsourcing options discussed above.
What Must Be Considered Now: Digital Solutions
Digital solutions are computer-led systems that have full control of the clinical documentation processes and only request human interaction for resolving specific ambiguities in the clinical encounter, request missing details, or resolve contra-indications. With technological advancement in spec recognition, natural language processing, machine learning, and artificial intelligence, the trajectory of the evolution of the clinical documentation landscape has shifted back to ‘assisted self-service in real-time.
Voice dictation robots understand free-flowing dictation and using contextual methods they enter the data into the EHR fields automatically without integration. Unlike other dictation systems which are ‘bolted on’ to EHR systems and primarily designed with keyboard and mouse in mind, voice dictation robots capture patient stories appointment-wise as physicians go through the encounter and get the EHR entries and SOAP (subjective, objective, assessment, and plan) notes created, reviewed and uploaded in real-time.
Medical transcription robots transcription records a physician’s findings and summary of an encounter to appropriate templates and translates it into a formal record and enters it into the EHR automatically without the physician having to touch the computer. They transcribe the natural voice of the physician regardless of accent, have automatic punctuations, can handle linguistic variation and unique medical jargon use, and provide proven documentation accuracy of 99% and above with no necessity for voice profile training. The EHR entries and SOAP notes are created, reviewed, and uploaded in real-time.
Digital scribes employ advances in ambient listening (AL), automated speech recognition (ASR), and natural language processing (NLP), machine learning (ML), artificial intelligence (AI), to provide physicians with tools to automatically document elements of the spoken/equipment-sensed clinical encounter – even when it involves conversations in multiple languages. It consists of high-fidelity ASR and NLP with speaker identification which allows automatic transcription of doctor-patient interaction anywhere within an environment. Digital scribes are in effect knowledge engineered expert scribes that completely mimic a physician in terms of transcribing the encounters and automatically entering data into the EHR in real-time. They can also assist physicians with EHR-triggered and AI-based diagnostic and treatment decisions. Cloud-based digital scribe technology requires minimal training, costs significantly lesser, improves compliance, and frees up precious physician time thereby unlocking incremental earnings potential.
What The Future Holds: Intelligent Clinical Environments
Intelligent clinical environments permit augmented clinical encounters to occur in a fully digitized space with zero human touches. They augment EHR systems with complementing systems of engagement that bring clinical processes to the foreground while addressing clinical documentation in the background.
Intelligent documentation support software leverages emerging technologies like Machine Learning (ML) for clinical decision support (CDS), the Internet of Things (IoT) for primary data collection using devices such as biosensors, diagnostic and life-support equipment, scales, activity trackers, etc., and Artificial Intelligence (AI) for precise treatment recommendations and plan of care. They also provide the necessary foundation to anonymize and process data to help physicians become aware of the best practice experiences of other doctors and the lessons learned from all such doctor-patient interactions captured in electronic health records. AI can also democratize the expertise and performance of specialists to supplement providers who might otherwise not have access to such expertise. Real-time decision support capabilities of these systems can surface multiple treatment options to develop a personalized and contextualized plan of care. More modern solutions are even leveraging population health machine learning models to predict populations at risk. The nature of the electronic health record will soon shift from a human or human-led system-produced one to a machine-generated and codified one, potentially backed by full audio, video, and sensory record of the clinical encounter.
The arrival of digital solutions and the developments happening in the field of intelligent clinical environments are set to radically transform clinical practice. Clinicians will be leaders in re-imagining how they work with patients in an environment increasingly assisted by technology. The choice of solutions for the digitisation of health records and patient encounter documentation is the first step in the transformation, and it pays to take a comprehensive view of how the SIX Sources of ROI* impact your business. Don't trade short-term convenience for long-term consequences!
Recommended Reading: SIX Sources of ROI from Digitization of Health Records and Patient Encounter Documentation
Topics : Scribe EMR