Showing posts with label health IT. Show all posts
Showing posts with label health IT. Show all posts

Wednesday, June 8, 2022

How to choose medical software for your practice

Diverse medical software has already become essential for the efficient operation of any healthcare provider, be it a cross-state healthcare network or a small private practice. Though providers can probably make use of any type of medical software, the financial resources they can invest in medical solutions differ significantly based on the type of practice.

There are numerous healthcare providers’ classifications. In this article, we use the one that divides providers into groups depending on the life cycle stage the clinic is at the given moment. According to this classification, medical providers fall into three groups:Beginners
Growing clinics


Well-established providers


Healthcare providers are business entities, so their life cycle, like that of any business, consists of the early stage or launch, growth, and maturity. At each stage, providers have different priorities and goals, and the choice of medical software solutions should be made accordingly.


Medical software for beginners


The launch phase can be tough. At this stage, the profits are usually low and providers may even incur losses. Hence, they need tools that would enable efficient work at this point, such as an EHR solution, a patient scheduling tool, and billing software. Those tools can make a solid foundation for any clinical operation.

An EHR tool stores patient health data, including medical histories, lab data, and more. This information is paramount for accurate diagnostics. Scheduling solutions allow providers to coordinate patients’ appointments with clinicians’ schedules and the available rooms, thus preventing confusion and ensuring time- and cost-efficiency. Billing software automates billing and filing insurance claims and helps manage them. Such software can also inform users about upcoming deadlines on document submission or payments. With those solutions in place, a clinic can function properly and provide due treatment and care.


Medical software for growing clinics


At the stage when the profits are stable, providers are aimed at increasing their customer base. This is when mobile technologies may be of help. As of 2021, 85% of the US population own a smartphone. This means that medical providers can consider integrating some engaging mobile apps in their practice. The experts recommend setting off with a mobile-friendly patient portal, as it allows providers to build strong relationships with their patients.

Using the portal, a patient can view, download, and send their health information to selected practitioners. They can also view and suggest edits to their treatment and medication plans, which improves their treatment adherence. While patients manage their health independently, doctors can always be around to supervise.

Experts recommend setting up a telemedicine solution after launching a portal. Telemedicine tools worked like life vests for medical providers during the pandemic outbreak, offering an opportunity to deliver care without virus exposure. Though the crisis is subsiding, telemedicine tools remain relevant. They can prove to be valid solutions for non-urgent care provision for busy professionals, chronic-condition patients, and people from remote and rural locations.


Medical software for well-established providers


At this stage, all clinical processes are up and running. However, their course is not always smooth and trouble-free, so there is a need for process optimization. Direct messaging solutions and speech recognition software can speed up clinical processes and even reduce clinicians’ burnout rate. According to a recent poll by Medical Economics, about 80% of respondents struggle with it. Curiously, it’s not the pandemic that is to blame here. Instead, the burdens are caused by the complexity of administrative tasks. So how can technology help reduce the burnout rate? Direct messaging solutions and speech recognition tools are relevant for this matter.

Direct messaging solutions ensure secure health data transmission across a private network run by a Health Information Service Provider (HISP). Healthcare providers use direct secure messaging to send referrals, transfer patient care plans, and communicate with patients. Such tools are HIPAA-compliant and support confidentiality of patient-doctor communication. Those tools save clinicians a lot of time and effort on secure data sharing.

As for speech recognition software, the tools transform speech into text, thus allowing clinicians to save time on tasks like taking patient notes.

Well-informed decision-making is often the key success factor in healthcare, and analytics solutions can bring this process to a new level. While such tools are optional for beginners, they are a game-changer for well-established providers. Analytical tools help improve health outcomes for diverse patient populations, speed up some operational aspects, and enhance the quality of medical research.


Summing up


Today, medical software types are numerous, and each helps speed up or refine daily healthcare tasks. Unfortunately, deploying all necessary tools at once is hardly possible due to budget constraints providers typically face. Therefore, they need to select solutions meeting their goals at a given life cycle stage. Deploying the necessary tools at the right time helps make healthcare provision smooth and efficient without incurring unbearably high costs.


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Wednesday, March 2, 2022

How AI-based tools can help manage COVID-19’s aftermath

Payers and providers have traditionally experienced competing interests, but today they share the same reality of an uncertain business environment caused by COVID-19 – and in many cases they are using the same technology to overcome operating challenges created by the pandemic.

As the pandemic began to unfold, many providers paused elective surgeries and others experienced significant declines in office visits, screenings, and routine care. The pause on elective surgeries alone created an estimated $200 billion in financial losses for hospitals and health systems between March and June 2020 alone, according to a McKinsey report.

Then the pandemic eased for a little while and volumes and procedures began to return to usual rates until the omicron variant led many providers to again postpone nonemergent procedures in late 2021 and early 2022.

Now, payers and providers both must deal with a backlog of elective procedures and it’s anyone’s guess how long it will take to clear. One executive with an endoscopy center said the backlog of colonoscopies could take “years to recover from.” In reports cited by McKinsey, the Journal of Bone and Joint Surgery estimated a cumulative backlog of more than 1 million joint and spine surgeries by 2022 and the Journal of Cataract & Refractive Surgery estimated a backlog of between 1.1 and 1.6 million cataract surgeries by the end of this year.

At the same time, patients have faced significant financial challenges from the pandemic. For example, a Kaiser Family Foundation analysis found that over a three-month period last year, the cost of treating unvaccinated COVID-19 patients in hospitals was a staggering $5.7 billion. Additionally, a study published in JAMA Network Open estimates that Americans who get seriously ill from COVID-19 might be responsible for thousands of dollars in medical bills from hospitals, doctors, and ambulance companies.



For providers, postponements have equated to delayed care and declining revenues. For payers, delays in care, testing and procedures often translate to more expensive care needs for patients whose conditions were complicated and worsened when timely treatment was not available.

A better alternative for chart reviews

To address patients’ care needs, payers and providers must identify gaps in care and prioritize the highest risk individuals. To do this effectively and efficiently, many payers and providers will turn to artificial-intelligence-based technologies such as natural language processing (NLP). By enabling computers to “read” and understand text by simulating humans’ ability to interpret language, NLP helps payers and providers extract key insights from colossal amounts of medical records data – without the bias or fatigue that is inherent to humans. NLP automates – with more accuracy - expensive, manual chart reviews, without requiring clinicians to wade through thousands of pages of documentation to pick out tiny pieces of data.

In giving computers the ability to read, understand and interpret language, NLP does far more than merely identify the presence of words or elements within text. By leveraging NLP, clinicians and researchers can organize data from an individual’s health journey, an entire patient population, or an enterprise's data warehouse. Additionally, NLP gives organizations the ability to retrospectively analyze longitudinal health data to find one particular piece of information about one particular patient or identify populations that require further exploration.

Following are three ways that NLP can help payers and providers manage in the aftermath of the COVID-19 pandemic:
  1. Prioritizing patients for care: In the wake of the pandemic, it has become critical for both providers and payers to triage care to determine which patients are in the most urgent need and, alternatively, which can effectively be placed at the back of the line. NLP can help payers and providers sort through mountains of patient records to pinpoint the information that reveals which patients are most in need of urgent interventions.
  2. Closing care gaps: As healthcare workers across the nation endured disruptions to usual operations and pandemic-related stress, it’s inevitable that some vulnerable patients fell through the cracks – and in some cases likely saw chronic conditions deteriorate. By analyzing longitudinal patient records to identify care gaps, payers and providers can generate outreach lists of patients to target for much-needed follow-up care.
  3. Ensuring payment integrity: With shifting regulations and policies in flux as a result of the pandemic, it has been challenging for payers and providers to ensure proper payment for COVID-19-related tests and procedures. NLP can automate audits of medical records to identify potential fraud or improper payments, billing inaccuracies, or clerical errors, and to assess the accuracy and completeness of clinical documentation. Records are reviewed with more efficiency and accuracy, which also facilitates faster claims processing.

Although it’s unclear when the pandemic will transition to an endemic, payers and providers need to be ready to manage a backlog of delayed care whenever it happens. Once it does, AI-based tools such as NLP will represent a critical means of prioritizing care, closing care gaps and ensuring payment integrity.


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Saturday, January 8, 2022

The future of capacity management lies in predictive analytics, digitization

There’s no doubt that the U.S. healthcare system is one of the best in the world from a clinical perspective. It’s far from perfect, however,as for years the industry has struggled to overcome the fundamental issue of matching supply with demand. The truth is most health systems operate at the edge of their capacity – just like freeways during rush hour. Meaning a shock to the system on either the demand or supply side will push the health system into a state of chaos and gridlock.

The pandemic was a shock to both the demand and the supply side. On the demand side, tens of thousands of people in a small geographic area suddenly needed intensive medical care. On the supply side, there were shortages – first in PPE, followed by ventilators, ICU beds, regular inpatient beds, and now ultimately for nursing staff. The crisis has also put enormous financial pressure on many health systems. This makes it difficult to maintain the old approach of building more hospitals, more operating rooms, more inpatient bed units, and more ambulatory care facilities. The balance must shift from building more assets to getting more out of the existing assets.

Recently the team at LeanTaaS hosted its second Transform Hospital Operations Virtual Summit. Over 20 speakers from some of the most prestigious health institutes in the country hosted presentations and had detailed conversations to illuminate capacity management for hospitals and health systems alike. As discussed during the summit, though the pandemic forced the healthcare industry to embrace digital tools like telehealth seemingly overnight, there is much more work to be done to digitize healthcare. Traditional scheduling methods and manual workflows are still being used to manage capacity and will no longer cut it in today’s world.

Data-driven solutions that utilize predictive analytics, AI, and ML are leading the path forward. Below are the top reasons why the future of healthcare capacity management lies in digitization.

Creating operating room efficiency


It’s no secret that operating rooms are the financial backbone of any hospital. They are also one of the most challenging areas to effectively manage. In a given hospital, one or more operating rooms will be idle for several hours during the day, yet many surgeries will be forced to take place late into the evening and night. Also, up to a third of the surgeries completed each day are performed by a surgeon who wasn’t the original assigned owner of the block in which it was performed. Finally, many of the surgeries performed each day are classified as urgent add-ons only because they were squeezed in at the last minute to take advantage of supply suddenly coming available.

To avoid these issues, hospitals must stop relying on simple-minded average utilization calculations. The future lies instead in using sophisticated data science to analyze the patterns of actual time used by surgeons to identify large, contiguous blocks of time left unused, blocks that were abandoned at short notice, and blocks that are consistently being released.

During Transform, Novant Health shared how they deployed tools to combat these issues. In May 2020, within a period of six weeks in the midst of the COVID-19 pandemic, they implemented a solution across 138 operating rooms at 16 medical centers, involving over 1,000 physicians and hospital staff members. During this time they accommodated their entire backlog of surgeries postponed from the pandemic in less than 3 months. They also increased their volume by 8% and even more impressively, increased splitter surgeon volume by almost 13%.


Reducing long infusion wait times


Infusion centers face the same unique challenges every single day. In the morning and late afternoons, the centers are quite empty. But from about 11 a.m. to 2 p.m. it can be busier than an airport during Thanksgiving break. Infusion nurse schedulers and managers rely on traditional methods to reserve chairs, such as looking at calendars as if they were reserving a conference room for a meeting. Because many more factors are involved in an infusion appointment than in that meeting, such methods aren’t efficient in creating a supply and demand balance in a scenario with this many moving parts.

Infusion centers need to better predict the incoming demand pattern for every single day going six to eight weeks into the future. Additionally, a detailed understanding of the individual components of the supply – nurses, chairs, pumps, pharmacy and the rules that govern their usage – is essential to figuring out the equation. Lastly, centers need a scalable way of guiding the scheduler to place each patient into the best possible slot for the day on which the infusion treatment is being scheduled. Prescriptive and predictive analytics can perform these advanced calculations and analyze real-time data to help staff safely accommodate patients. At Transform, Michigan Medicine shared how it used an analytics solution to unlock 8% higher volume with 20% fewer chairs during the pandemic.

Unlocking inpatient bed capacity


As a result of COVID-19, the number of available inpatient beds has become the utmost concern for hospitals and health systems around the country. Beds are organized into small units of 12-24, based on the specific needs of patients. Units are constrained to take only certain kinds of patients, and can only operate at a level of capacity dictated by their ability to staff the unit with the right number of nurses. On the demand side, there are three major sources of patients – from the ORs, from the ER, and from transfers from other hospitals.

The surgery roster is clear several days in advance and can help estimate the demand for beds–but this accounts for only 15-20% of total demand. Predicting demand volume from the ER and inbound transfers is much more difficult. Typically, nurses try to manage ongoing bed capacity through nurse huddles. In short, they try to solve an incredibly complex math problem manually through spreadsheets, discussion, and sheer intuition. While these methods often work, they are also high stress and time consuming. Nurses need a better prediction of the incoming volume for each unit, an accurate prediction of discharges, and a scalable way to surface units that are likely to experience pressures hour-by-hour.

Another Transform speaker, UCHealth, deployed predictive analytics tools at the start of the pandemic in 2020. As a result, they have since seen a 37% reduction in the time to complete an ICU transfer, an 8% reduction in the number of excess bed nights, which is worth millions of dollars each year to most hospitals, and a 4% reduction in the time to place a patient in a bed even though the volume of admissions went up by 18%.

It can be incredibly difficult to optimize asset utilization in health systems with simple calendars and process improvement pushes. Dashboards with alerts just do not do enough. But we do have the digital tools available to effectively manage capacity within healthcare.

The path forward is to leverage sophisticated math and algorithms that are intelligent and can continuously learn. It will enable the front line at hospitals to automatically and rapidly make smarter decisions that consistently match the supply and demand for each hospital’s assets throughout the day, and on every single day – not only unlocking capacity, but leading to improved patient access and reduced administrative burdens on hospital staff.


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