Invented by David McEwing, Mirr LLC

The Market for Diagnostic and Treatment Tools for Electronic Recording and Indexing of Patient Encounters to Allow Instant Search

In today’s fast-paced world, the healthcare industry is constantly evolving to keep up with the demands of patients and healthcare providers. One area that has seen significant advancements is the development of diagnostic and treatment tools for electronic recording and indexing of patient encounters. These tools allow for instant search capabilities, revolutionizing the way medical professionals access and analyze patient information.

Traditionally, patient encounters were documented using pen and paper, making it time-consuming and cumbersome to retrieve specific information. However, with the advent of electronic health records (EHRs), healthcare providers can now record patient encounters digitally, streamlining the process and improving efficiency. The market for diagnostic and treatment tools in this domain has witnessed tremendous growth, as healthcare organizations recognize the benefits of instant search functionality.

One of the key advantages of these tools is the ability to quickly retrieve patient information. With instant search capabilities, healthcare providers can easily access a patient’s medical history, lab results, and previous treatments, enabling them to make more informed decisions. This not only saves time but also enhances patient care by ensuring accurate and up-to-date information is readily available.

Furthermore, the electronic recording and indexing of patient encounters allow for improved collaboration among healthcare professionals. With instant search, different specialists involved in a patient’s care can quickly access relevant information, facilitating seamless communication and coordination. This leads to better continuity of care and reduces the risk of errors or miscommunication.

The market for these tools is not limited to hospitals and clinics alone. Private practices, urgent care centers, and even telemedicine providers are increasingly adopting electronic recording and indexing systems. This widespread adoption is driven by the need for efficient and accurate patient data management, as well as the growing demand for telehealth services.

Moreover, the integration of artificial intelligence (AI) and machine learning (ML) technologies into these tools further enhances their capabilities. AI-powered algorithms can analyze vast amounts of patient data, identify patterns, and provide valuable insights to healthcare providers. This assists in early detection of diseases, personalized treatment plans, and improved patient outcomes.

However, as with any technological advancement, there are challenges that need to be addressed. One major concern is ensuring the security and privacy of patient data. Healthcare organizations must implement robust cybersecurity measures to protect sensitive information from unauthorized access or breaches. Additionally, healthcare providers need to be trained on the proper use of these tools to maximize their benefits and minimize potential errors.

In conclusion, the market for diagnostic and treatment tools for electronic recording and indexing of patient encounters to allow instant search is rapidly expanding. These tools offer healthcare providers quick access to patient information, improved collaboration, and enhanced patient care. With the integration of AI and ML technologies, the potential for better diagnosis and treatment outcomes is immense. However, it is crucial for healthcare organizations to prioritize data security and provide adequate training to ensure the effective utilization of these tools. As the healthcare industry continues to evolve, these advancements will play a pivotal role in shaping the future of patient care.

The Mirr LLC invention works as follows

Devices and methods for improved diagnosis and treatment of patients.” The notes made by the clinicians regarding diagnosis, testing or treatment are recorded electronically and become an entry into a patient-specific EHR. The clinician can adapt the codes to fit the diagnosis, etc. and integrate them into the EHR. Search the EHR using codes adapted as an index for diagnosis, testing and treatment. The tool and method include a program to facilitate the entry of clinician notes, including autocomplete and autocorrection. It also suggests appropriate code entries that correlate with the content of those notes. The program can include authentication protocols to protect privacy and accesses of patient EHR. The code and descriptors are likely to be a product of protocols like CBD-10 or CPT. The tool and method can allow an immediate search in the patient’s EHR to find prior relevant conditions or treatments thereby facilitating rapid treatment of underlying causes of malady.

Background for Diagnostic and treatmentmetnt tool for electronic recording of and indexing of patient encounters to allow instant search on patient history

Coding Function

Code Searching

The “Autocorrect and Suggestion” Functions

AutoComplete user interface

Entering Partial Data and Finding a Unique match:

Entering Partial Data Over a Suggestion Completion

Entering Partial Data and Finding Multiple Matches

How to convert a partial data entry into a case-sensitive format

AutoComplete: A State Machine

Case Conversion

EHR search Request

EHR Security

Clinician Specification & Selection


Initialization Interface

Code Protocol Amendment

Patient Identity Authentication

Data Entry Validation

Encryption Device and EHR Data


Machine Learning

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