Category: Healthcare Technology

healthcare technology

The Evolution of Healthcare: Adapting to New Technologies

In today’s fast-paced, ever-evolving world, the healthcare industry is no exception to the transformative power of technology. From electronic health records (EHRs) to telemedicine and artificial intelligence, hospitals and healthcare providers are rapidly embracing new technologies to enhance patient care, streamline operations, and improve overall efficiency. In this blog, we’ll explore how the hospitals and healthcare industry are adapting to these innovations.

  1. Electronic Health Records (EHRs):
    One of the most significant technological advancements in healthcare is the widespread adoption of EHRs. These digital systems have replaced traditional paper records, making patient information easily accessible to healthcare professionals. EHRs improve the accuracy and efficiency of patient care by reducing paperwork and allowing for seamless sharing of medical histories and test results among providers.
  2. Telemedicine:
    Telemedicine has gained prominence in recent years, especially during the COVID-19 pandemic. This technology allows patients to receive medical consultations remotely, eliminating the need for physical office visits. Telemedicine not only enhances access to care, particularly for patients in remote areas, but also reduces the risk of disease transmission during in-person appointments.
  3. Artificial Intelligence (AI):
    AI is revolutionizing healthcare in numerous ways. Machine learning algorithms are used to analyze vast amounts of medical data, providing insights into patient outcomes and treatment efficacy. AI-powered chatbots and virtual assistants also help streamline administrative tasks and provide patients with quick responses to their queries.
  4. Robotics:
    The use of robots in healthcare is expanding, from assisting in surgeries to automating routine tasks in hospitals. Surgical robots, for instance, enable more precise procedures with fewer complications, while service robots can deliver medications and transport supplies throughout a hospital, reducing staff workload.
  5. Wearable Devices:
    Wearable technology, such as fitness trackers and smartwatches, is increasingly used for monitoring patients’ health. These devices can track vital signs, detect irregularities, and provide real-time data to healthcare providers, enabling early intervention and personalized care.
  6. Big Data Analytics:
    Hospitals and healthcare organizations are harnessing the power of big data to improve patient care and outcomes. By analyzing vast amounts of healthcare data, professionals can identify trends, track disease outbreaks, and develop predictive models for patient risk assessment.
  7. Blockchain:
    Blockchain technology is being explored to enhance data security and privacy in healthcare. By providing a secure and tamper-proof record of patient information, it helps protect sensitive data and streamline processes like insurance claims.
  8. 3D Printing:
    3D printing is increasingly used to create custom medical devices, prosthetics, and even tissues and organs. This technology offers more personalized and cost-effective solutions, especially for patients in need of complex or unique medical interventions.
  9. Virtual Reality (VR) and Augmented Reality (AR):
    VR and AR are being used for medical training, patient education, and even pain management during procedures. They provide immersive and interactive experiences that enhance learning and engagement.

As the healthcare industry adapts to new technologies, it is essential to ensure that patient privacy and data security are maintained. Additionally, healthcare professionals must receive proper training to use these technologies effectively and safely.

In conclusion, the healthcare industry’s embrace of new technologies is revolutionizing the way medical services are delivered, improving patient care, and increasing the efficiency of healthcare systems. As technology continues to advance, hospitals and healthcare providers will continue to find innovative ways to adapt, ensuring that patients receive the best care possible in an ever-changing world.

star rating system

The Significance of Star Rating Systems and Quality Improvement Measures in Healthcare

The healthcare industry is inherently dynamic, marked by constant advancements in medical science and technology. Amid this ever-evolving landscape, ensuring that patients receive the highest quality of care remains paramount. Two critical components that play a pivotal role in achieving this goal are the star rating system and quality improvement measures.

Star Rating System: A Transparent Evaluation

Star rating systems, widely employed in healthcare, provide a transparent and easily understandable way to assess the quality of healthcare providers and facilities. These ratings, typically ranging from one to five stars, are often publicly available and serve as a valuable resource for patients, caregivers, and healthcare professionals alike.

Why Star Ratings Matter:

Informed Decision-Making: Patients can make more informed decisions about their healthcare when armed with information about the quality of care provided by hospitals, nursing homes, and physicians. Star ratings serve as a quick reference point to gauge a facility or provider’s performance.

Accountability: The star rating system fosters accountability within the healthcare industry. Facilities and professionals strive to improve their ratings, driving them to consistently deliver high-quality care and patient satisfaction.

Quality Benchmarking: Star ratings facilitate benchmarking against industry standards. Facilities can identify areas in need of improvement and adopt best practices from high-performing institutions.

Patient-Centered Care: These ratings prioritize patient-centered care by focusing on aspects that matter most to patients, such as communication, responsiveness, and overall patient experience.

Data-Driven Decision-Making: Health systems can use star ratings as a basis for data-driven decision-making. This allows for targeted interventions and allocation of resources where they are needed most.

Quality Improvement Measures: Enhancing Healthcare Excellence

Quality improvement measures encompass a wide range of strategies and initiatives aimed at enhancing the quality of care delivered across the healthcare continuum. These measures are an integral part of achieving better patient outcomes and optimizing the overall healthcare experience.

Key Aspects of Quality Improvement Measures:

Evidence-Based Practice: Implementing evidence-based guidelines and best practices ensures that patients receive care based on the latest research and clinical knowledge.

Continuous Monitoring: Regular assessment and monitoring of clinical outcomes, patient satisfaction, and safety indicators allow healthcare organizations to identify areas of improvement.

Patient Engagement: Involving patients in their care decisions and engaging them in their health journey fosters a patient-centered approach and leads to better adherence to treatment plans.

Interdisciplinary Collaboration: Encouraging collaboration among healthcare professionals, including physicians, nurses, and allied health providers, promotes a multidisciplinary approach to patient care.

Performance Metrics: Establishing performance metrics and setting targets helps healthcare organizations measure progress and adapt strategies as needed.

Feedback Loops: Creating feedback loops for healthcare providers allows them to learn from patient experiences and make necessary improvements.

The Synergy of Star Ratings and Quality Improvement Measures:

The interplay between star ratings and quality improvement measures is a powerful force for enhancing healthcare quality. Star ratings provide the impetus for healthcare organizations to embark on quality improvement journeys, while the continuous pursuit of excellence through quality improvement measures positively impacts star ratings.

In conclusion, the healthcare industry’s commitment to delivering high-quality care is exemplified through the utilization of star rating systems and quality improvement measures. These tools work in tandem to ensure that patients receive the best care possible, driving healthcare facilities and providers to continually raise the bar for excellence in patient care.

Saince announces the launch of tele-medicine feature within its clinical documentation solution

Doc-U-Scribe clinical documentation solution now comes integrated with tele-medicine workflow. Physicians and administrators can create tele-consultation sessions with patients seamlessly from within the application. This process eliminates the need for providers to use separate solutions – one for clinical documentation and another for video session.

The COVID-19 public health crisis has accelerated the use of tele-medicine solutions among healthcare provides across the nation. However, many small hospitals and physician offices do not have access to a single solution that takes care of all their needs. Physicians are forced to use multiple solutions to complete their tele-medicine workflow. They are often finding this process frustrating and cumbersome.

Doc-U-Scribe clinical documentation solution which is used by hundreds of hospitals and physician offices across the country provides an integrated and seamless workflow for clinical documentation as well as tele-medicine.   This new HIPAA compliant tele-medicine solution can cut costs, increase efficiency, and improve physician satisfaction significantly.

Saince announced that this new feature will be available to all their existing customers immediately. Saince also announced that with their plug and play model, any new hospital or physician office can be up and running with their tele-medicine program within 48 hours.

CMS Announces Release of 2018 National Impact Assessment of Quality Measures Report

Center for Medicare and Medicaid Services (CMS) conducts and publishes an assessment of the quality and efficiency impact of the use of endorsed measures in CMS programs every three years as required by statute.  The first report was published March 1, 2012 and the 2018 Impact Assessment Report is the third such report.   The data-driven results of this Report support the use of measures implemented in CMS reporting programs to drive improvement in the quality of care provided to patients in facilities and across settings nationwide.  This report is used by the measure developer community, patients and families, clinicians, providers, federal partners, and researchers.

The 2018 Impact Assessment Report demonstrates that performance on CMS measures contributed to better care and reduced expenditures, and identified critical areas of improvement across settings with respect to six CMS quality priorities:  patient safety, person and family engagement, care coordination, effective treatment, healthy living, and affordable care.

Highlights include these main findings:

  • Patient impacts estimated from improved national measure rates indicated approximately:
    • 670,000 additional patients with controlled blood pressure (2006–2015).
    • 510,000 fewer patients with poor diabetes control (2006–2015).
    • 12,000 fewer deaths following hospitalization for a heart attack (2008–2015).
    • 70,000 fewer unplanned readmissions (2011–2015).
    • 840,000 fewer pressure ulcers among nursing home residents (2011–2015).
    • 9 million more patients reporting a highly favorable experience with their hospital (2008–2015).
  • Costs avoided were estimated for a subset of Key Indicators, data permitting. The highest were associated with increased medication adherence ($4.2 billion–$26.9 billion), reduced pressure ulcers ($2.8 billion–$20.0 billion), and fewer patients with poor control of diabetes ($6.5 billion–$10.4 billion).
  • National performance trends are improving for 60% of the measures analyzed, including a majority of outcome measures, and are stable for about 31%.
  • Overwhelmingly, hospitals (92%) and nursing homes (91%) surveyed reported they consider CMS measures clinically important. Likewise, 90% of hospitals and 83% of nursing homes agreed that performance on CMS quality measures reflects improvements in care. Respondents also described barriers to reporting, including burden; barriers to improving performance; and unintended consequences of CMS measures.

CMS introduces new payment model for both inpatient and outpatient care

The Centers for Medicare & Medicaid Services (CMS) announced the launch of a new voluntary bundled payment model called Bundled Payments for Care Improvement Advanced (BPCI Advanced). Under traditional fee-for-service payment, Medicare pays providers for each individual service they perform. Under this bundled payment model, participants can earn additional payment if all expenditures for a beneficiary’s episode of care are under a spending target that factors in quality.

Bundled payments create incentives for providers and practitioners to work together to coordinate care and engage in continuous improvement to keep spending under a target amount. BPCI Advanced participants may receive payments for performance on 32 different clinical episodes which are listed below.

Of note, BPCI Advanced will qualify as an Advanced Alternative Payment Model (Advanced APM) under the Quality Payment Program (QPP). Under Advanced APMs, providers take on financial risk to earn the Advanced APM incentive payment.

BPCI Advanced will operate under a total-cost-of-care concept, in which the total Medicare fee for services (FFS) spending on all items and services furnished to a BPCI Advanced Beneficiary during the  Clinical Episode, including outlier payments, will be part of the Clinical Episode expenditures for purposes of the Target Price and reconciliation calculations, unless specifically excluded.

Clinical Episodes

BPCI Advanced will initially include 29 inpatient Clinical Episodes and 3 outpatient Clinical Episodes. Participants selected to participate in BPCI Advanced beginning on October 1, 2018, must commit to be held accountable for one or more Clinical Episodes and may not add or drop such Clinical Episodes until January 1, 2020.

Inpatient Clinical Episodes – 29

  • Disorders of the liver excluding malignancy, cirrhosis, alcoholic hepatitis *
    *(New episode added to BPCI Advanced)
  • Acute myocardial infarction
  • Back & neck except spinal fusion
  • Cardiac arrhythmia
  • Cardiac defibrillator
  • Cardiac valve
  • Cellulitis
  • Cervical spinal fusion
  • COPD, bronchitis, asthma
  • Combined anterior posterior spinal fusion
  • Congestive heart failure
  • Coronary artery bypass graft
  • Double joint replacement of the lower extremity
  • Fractures of the femur and hip or pelvis
  • Gastrointestinal hemorrhage
  • Gastrointestinal obstruction
  • Hip & femur procedures except major joint
  • Lower extremity/humerus procedure except hip, foot, femur
  • Major bowel procedure
  • Major joint replacement of the lower extremity
  • Major joint replacement of the upper extremity
  • Pacemaker
  • Percutaneous coronary intervention
  • Renal failure
  • Sepsis
  • Simple pneumonia and respiratory infections
  • Spinal fusion (non-cervical)
  • Stroke
  • Urinary tract infection

Outpatient Clinical Episodes – 3

  • Percutaneous Coronary Intervention (PCI)
  • Cardiac Defibrillator
  • Back & Neck except Spinal Fusion

EMRs Taking Away Close to One-Third of Physicians’ Work Time – AMA

The EMR Time Crunch

A common complaint among physicians across practices and specialties has been the amount of time that was previously spent attending to patients is now being occupied by clinical documentation.  These time disparities can have adverse effects on physician-patient relationships, and also limit the number of patients able to receive care from a physician or practice. Value-based purchasing models are frequently the basis for physician reimbursements, and because these models require extensive documentation to accurately report the quality and cost of care, the EMR software physicians are required to use is becoming increasingly complex and time consuming.

AMA Findings

A recent study conducted by the American Medical Association focusing specifically on the use of electronic health records in academic centers concluded that an average of 27% of the participating Ophthalmologists’ time spent on patient examinations was occupied by EMR use. On average a total of 5.8 minutes per patient and 3.7 hours was spent working in EMR on any given full day of clinic.  The study also found a negative association between the amount of time spent on EMR per patient encounter and overall clinic patient volume.

The AMA study concluded what many physicians have been expressing for years: doctors have limited time to spend with patients while they are spending more time within EMRs. Aside from the strain EMR places on physicians’ time and patient relationships, it is also creating cumbersome clerical burdens when completed incorrectly or hastily. Large swaths of copied and pasted text create bloated and messy records, and a lack of training and technical knowledge can result in incorrect coding, medical errors, and frequent interruptions in the documentation process.

Physician Dissatisfaction

The amount of physician dissatisfaction has also grown with the increased implementation of EMRs. Nearly half of all physicians report feeling unsatisfied with their work-life balance, and 57% of physicians display signs of burnout. The additional time requirements of clinical documentation are a significant factor in both of these statistics. Physicians are spending an increasing amount of time outside of regular work hours completing EMRs, and an increasingly less amount of time on actual patient care and interaction. This has led to heightened levels of stress and job dissatisfaction.

Looking Forward

While the path hasn’t always been an easy one, electronic medical records are here to stay, and they do present a plethora of benefits to clinical documentation, patient care, and bottom lines. The challenge that needs to be addressed is how to make EMRs efficient and thorough, while minimizing the amount of time physicians are required to spend on them.  Perhaps the solution for better EMR efficiency lies within a hybrid workflow — a workflow that combines the traditional model of medical transcription, where physicians dictate patient encounters and trained transcriptionists and coders review the reports for accuracy and sufficiency, combined with the advantages of using a modern day EMR is the most efficient way to ensure document quality and lessen the time burden EMRs place on physicians. When the responsibility of clinical documentation is not placed solely on the physician, doctors will be able to attend to more patients, improve patient relationships, and increase their job satisfaction.

The Prevalence and Consequences of Medical Errors in American Medicine

Part I

There are numerous records that we maintain, or are maintained on us, over the course of our lives.  Our school records track our grades and accolades. Our public records track our civic life and criminality. Our resumes document our accomplishments and abilities.  And our medical records compile the history of our overall health and wellness throughout the course of our lives. Inevitably, we are all dependent on the precision of these records to portray ourselves truthfully. Any inaccuracy could have a monumental impact on some aspect of our lives. Missing credits could keep us from graduating. A mistake in our criminal background could result in the loss of liberties. And an error in our medical records could cost us our health, perhaps even our lives.


Patient Perception on Healthcare Safety

We trust doctors, as we should. They’re dedicated, intelligent, and went to school a lot longer than most of us did, so we put our health and well-being in their hands and trust that they will know how to fix us and keep us healthy.  A recent study out of the University of Chicago and the Institute for Healthcare Improvement found that 90% of Americans interacted with some kind of healthcare provider in the last year, and that most people’s experiences were positive. The care was comprehensive, the physicians were attentive, and they understood how to care for themselves after their visits. (1) Over all, Americans do not feel that they run the risk of experiencing a medical error. However, this could largely be contributed to a general misunderstanding of what, exactly, constitutes one.


Defining “Medical Error” and Patient Experience

For most of us, the thought of “medical error” conjures images of a scalpel left inside of us after a surgery or something else gruesome, newsworthy, and incredibly unlikely to ever occur. In reality, a medical error can mean a simple miswording in diagnoses, perhaps stating an injury to a right foot instead of left, or a few switched numbers in a medical code show you diagnosed and treated with something else entirely. The same study found that, after having the term “medical error” defined to them, 21% of participants expressed that they had personally experienced a medical error, while 31% said that they had cared for someone who had experienced one.  All total, 41% of adults in the United States have either personally experienced a medical error in their own care, or were directly involved in caring for someone who had. (1)

The Consequences of Medical Errors

When it comes to medical errors, 41% is a disparaging, and frankly, frightening number, especially considering that 73% of people who reported experiencing a medical error or caring for someone who had said that the mistake had some kind of long term or permanent health detriment or financial impact. There is also a clear correlation between medial errors and harm with 36% of patients who reported personally experiencing a medical error also reporting that they had been harmed while receiving medical care. (1)

Another alarming statistic coming out of this study is that only about 1/3 of the participants who reported experiencing a medical error were made aware of the error by someone at the facility where they were treated. Around half of the participants brought their medical error to the attention of medical personnel on their own. (1) The important assumption to then take from this data, is that not only are medical errors occurring frequently, most of them are not being caught by medical personnel or facility staff. This leads then to the even larger issue of medical disparity, as medical record errors tend to impact vulnerable populations more so than populations with greater health literacy, a factor closely tied to education and income.(1)

Of the participants who reported dealing with medical errors, 59% reported that the error was centered around diagnosis, where the patient was either diagnosed incorrectly, had a delayed diagnosis, or was not diagnosed at all when they were, in fact, ill or injured. (1) The reasons for misdiagnosis are broad and varying, and misdiagnosis is the leading cause of medical malpractice suits in the United States. Diagnostic errors can have dire, long lasting, and even fatal consequences for patients, and yet they are so common that nearly everyone will experience at least one incorrect or delayed diagnosis in their lifetime. (2)

The question then becomes, what is causing such a high prevalence of medical errors and what can be done to rectify that?

Changes in Medical Documentation and Resulting Challenges

In 2004, thanks to new government incentives, medical records began to change with a push from paper charts to electronic archives. While the benefits of EMRs are undeniable—they can lower costs, enhance efficiency, and make patient records immediately available across care settings– the transition, unfortunately, has been less than smooth. Many medical facilities are still scrambling to fully and comprehensively changeover. (3)

One of the biggest hinderances to care and sources of medical errors is the extra documentation burden that now falls on doctors. Prior to EMR, physicians would fill out charts or record their observations, and those documents would then go to a trained medical transcriptionist, a coding expert, and then a billing specialist. In this new system of clinical documentation, doctors are responsible for filling out patient charts and coding, often using clunky systems that they are ill-trained to use. (3) Not only does this result in a substantial amount of physicians’ time shifting from patient interaction to documentation as they navigate unfamiliar and complicated computer programs, but it also drastically reduces the potential for any mistakes that physicians might have made to be caught and queried by professionals trained in transcription and coding. 

In addition to the obvious consequences placed on patients when medical errors arise from EMR complications, medical documentation is also a significant factor in the increasing rise of physician burnout. Physicians report higher levels of job dissatisfaction when the amount of time they spend on documentation encroaches on, and even surpasses in many cases, the amount of time they spend on patient care. (4) Essentially, new clinical documentation standards are forcing doctors to perform tasks and use technology with which they’ve had practically no training, resulting in transitional delays with the learning curve, professional frustrations, and a high prevalence of mistakes.


New Solutions in Traditional Practices

Medical errors are costly and dangerous and combatting them is a top priority in patient safety and hospital efficiency. With EMR hiccups contributing to a substantial amount of errors in medical documentation, the most obvious solution to begin combating medical error is to elevate the quality, capabilities, and usability of clinical documentation workflows. New software solutions and technology, specifically backend speech recognition and natural language processing, are capable of significantly improving the quality and accuracy of medical transcriptions.

The traditional transcription model where physicians dictate patient encounters and trained transcriptionists and coders review the reports to ensure quality and integrity is by far the most comprehensive way to prevent medical errors. Thanks to advancements in transcription technologies, the cost of transcription has come down significantly, and can more than offset the costs accumulated as a result of the medical errors it can eliminate. With new solutions and technologies, the outlook for not only reducing medical error, but enhancing the entire system of medical transcription and diagnosis, is exciting and promising.           

The Cost of Care: How AI is Revolutionizing Healthcare and Driving Down Prices

The cost of healthcare is once again at the center of a national debate.  With premiums rising, the baby boomers aging, and diabetes, the most expensive disease in the world, affecting 10% of the US population, the rising cost of healthcare in America is an issue that affects all of us.  In the past, the implementation of new and emerging technologies in healthcare has contributed to the climbing costs. In contrast, the application of AI into healthcare is promising to drive those costs down.

Healthcare is an enormously expensive industry and the costs are steadily climbing.  According to World Book, in 2014 healthcare made up 17.1% of the GDP of the United States– up 4% from 1995, and continuing to grow.  The application of artificial intelligence into healthcare is promising to greatly reduce these expanding expenses while improving healthcare quality and access.  By 2026, it’s estimated $150 billion could be saved annually in the US healthcare economy by AI applications. It’s no wonder that healthcare is currently the number one investor in AI.

One of the areas in healthcare that will be most significantly impacted by the application of artificial intelligence is clinical documentation. AI applications in medical workflow management are estimated to accumulate $18 billion in annual savings for the healthcare industry by 2026, the third largest estimated savings from AI technology in healthcare after robotic surgery and virtual assistants.  Modern healthcare AI is capable of learning and comprehending and can perform clinical healthcare functions in much the same way as a human, minus human error.

Physician error in clinical documentation is an understandable yet costly complication in healthcare, and AI is able to streamline the tedious clinical documentation process and automatically generate accurate and complete reports.  Many AI healthcare programs are capable of fully augmenting human behavior and can perform tasks from risk analysis to patient diagnosis. Physician engagement in clinical documentation is a critical component to the quality and costs of healthcare, and AI applications are proving to increase physician engagement and improve clinical documentation quality.

With so much potential to improve not only healthcare costs, but also access and quality, the AI health market is currently experiencing a boom, and is expected to grow into a $6.6 billion dollar industry by 2021. This growth makes sense when you consider that the nation and the world are currently facing a shortage of doctors and healthcare personnel, and AI offers hospitals and physician practices a way to combat their rising operational and labor costs, while enabling them to better perform critical administrative functions quickly, accurately, and cost effectively.

Artificial Intelligence seems like the wave of the future, but the reality is, the future is here. In today’s medical environment of value-based care, appropriate reimbursements are incumbent upon accurate, high quality clinical documentation. As AI continues to grow and evolve, AI enabled clinical documentation improvement technology will continue to transform the healthcare industry, improving patient outcomes and optimizing revenue.

Rise of the Machines: Artificial Intelligence in Healthcare

Artificial intelligence in Clinical Documentation

When we think of artificial intelligence, the images that come to mind for many of us are probably somewhere along the lines of Rosie from The Jetsons or Arnold in Terminator.  While we’re still most likely several years from sentient household or murder robots, AI is playing an increasingly large role in our everyday lives.

One area that is beginning to see a significant increase in the applications of artificial intelligence systems is healthcare.  Massive amounts of clinical health data are becoming increasingly available through clinical documentation, electronic health records, and online medical interactions, as well as new and evolving academic health data which is constantly being generated and updated. This increase in available data coupled with the emergence of new, sophisticated algorithms and software has begun a revolutionizing trend in the healthcare industry that is changing the way we’re diagnosed and treated, how we interact with physicians, and how physicians operate within a clinical setting.

Artificial intelligence is a computing system engineered to allow digital devices to perform tasks without being directly instructed by a human. By utilizing multiple algorithms to sort and analyze data, these systems are able to recognize patterns, make decisions, and even change the way they “learn” when presented with new information. Ultimately, AI is designed to emulate the human cognitive process at an exponentially accelerated rate. In healthcare, essentially this means teaching a computer system to learn and think like a doctor.

Diagnosis and Treatment

One of the most practical yet profound applications of AI in healthcare is in patient diagnosis. Using algorithms that are capable of scouring enormous databases of both structured data from clinical trials and unstructured data from medical journals, AI systems can search for a patient’s symptoms while also considering the patient’s own medical history to come up with the most likely diagnoses. It can then generate a list of probable diagnoses and assist in structuring highly personalized treatment plans based on the patient’s medical history, and considering the latest advancement in medical treatments and their success rates across broad population spectrums.

In a clinical trial of 1000 cancer patients, Watson, a technology being developed by IBM which uses an AI system to diagnose and treat cancer, concluded the same diagnoses and treatment recommendations as oncologists 99% of the time.  The far reaching implications of this are particularly important for rural and remote communities where finding a doctor who specializes in a particular kind of disease may be impossible. For example, if there are only two doctors in the country who specialize in a rare, genetic kidney disorder and they are both located in Manhattan while the patient with the kidney disorder lives in Honolulu, using AI diagnoses and treatment plans, a local doctor who is not an expert in the kidney disorder can treat that patient with all of the expertise of the specialist available to them.        

Personal Assistants and Remote Access

Personal health assistant apps operate by asking the patient a series of pointed questions about their symptoms and medical history to reach a diagnosis. The apps can then recommend treatments or suggest that the patient see a doctor in person. As this technology becomes more widely available, it could help to see a significant decrease in doctor’s office traffic since patients with minor illnesses or injuries who only require rest, over the counter medication, or home remedies won’t need to make the trip, freeing up doctor’s time to focus on more critical patients.

These “pocket doctors” can also essentially function as a live-in doctor and health coach for chronically sick patients who require round the clock care. By periodically entering their health data like blood pressure, heart rate, blood glucose, weight, activity, temperature etc, and answering questions regarding physical and mental functions like appetite, energy levels, and sleep patterns, medical personal assistants can track a patient’s health and treatment plan, recommend changes to things like diet and exercise to improve outcomes, and monitor for warning signs that something more serious that requires a visit to an IRL physician is occurring.  

Clinical Documentation Improvement

Clinical documentation in and of itself is an important aspect in the development and accuracy of medical AI technology because it is the data from clinical documentation that is fed into EMR and EHR systems that produce the robust structured databases AI uses to “learn”. In our next post, we’ll be taking a closer look at the pragmatic applications of artificial intelligence in clinical documentation and how they are maximizing appropriate reimbursements and alleviating physician burnout.

Only for about the last two years has the technology and the data that are driving the AI revolution in healthcare been available, and already the results are awe inspiring and the potential seemingly limitless.  While AI still has some obstacles to overcome in the healthcare field the artificial intelligence movement is likely to continue to grow in healthcare, and help improve upon the human endeavor of providing the most comprehensive and effective healthcare possible.