US Healthcare Issues. How Could IT Help?

The state of US healthcare is a topic that keeps everyone from patients to doctors to government officials up at night. Every new US president feels like they should say something about healthcare, promise to improve it, and criticize what’s been done before them. And more often than not, digitization is mentioned as a major part of a solution.

Indeed, information technology has played a vital role in the development of the healthcare ecosystem over the past decades. If there is one thing that has changed it would be just that ― a marriage of IT and healthcare. Tons of computers. Millions of devices. Electronic Health Records’ giants: Epic and Cerner.

The COVID-19 pandemic only accelerated digitization: wearables, remote monitoring, telemedicine solutions, and AI solutions became urgently needed. Healthcare IT companies reacted to this demand. According to MarketsandMarkets the global healthcare information technologies market size is projected to reach USD 270.3 billion by 2021. This is compared to USD 227.5 billion in 2020. In 2020, North America accounted for the largest revenue share in the global healthcare IT market, and it is expected to continue to dominate in terms of revenue share contribution over the forecast period.

So what is it that information technology improves in the healthcare industry? Generally, it’s one of the following:

  • documentation: clinical reports, tests results, prescriptions, recommendations;
  • communication between the patient and every service they receive within healthcare;
  • decision making: how decisions are made about diagnosis and treatment plans.

In this article, we describe the most commonly outlined problems of US healthcare and discuss how digitization can solve ― or at least help to solve ― these problems.

Preventable medical errors

A 2016 study by John Hopkins showed that in the US, preventable medical errors account for 10% of all deaths, which makes it the third leading cause of death in the country. Medical errors include drug errors in administration, as well as errors in treatment, actions, diagnoses, and administrative tasks. Studies showed that out of this list information technologies can reduce medical, administrative, and diagnostic errors. EHR (Electronic Health Records), CPOE (Computerized Provider Order Entry), and CDSS (clinical decision support system) are the IT solutions that have been most successful and most promising at reducing these types of medical errors.

Reducing preventable medical errors: EHR

EHR started its journey back in 2009, and it has received some praise and much more criticism ever since. The transition from paper to electronic records hasn’t been smooth, quick, or satisfying. However, electronic records are an obvious improvement over paper charts. And, what is even more important, twelve years later, the journey of EHR is still beginning. EHR paves the way for artificial intelligence that works to identify patterns in data, draw conclusions, and make predictions based on them. Some of this technology is already in use: Epic Systems is already offering features based on machine learning and artificial intelligence. The system can, for example, predict which patients might get sepsis based on data about their blood pressure, pulse, and temperature collected in advance. Epic sends a notification to the physician if a patient is at risk. The physician then monitors the patient more closely and is able to catch the disease in time. The North Oaks Health System in Hammond, La., implemented this model in 2017, and since then, the mortality caused by sepsis has decreased by 18 percent. In a similar way, AI is used to alert a physician of a patient’s drug allergy, possible side effects with drug A versus drug B, or any possible conflict between a patient’s health record and drug prescription.

The existence of EHR also reduces medical errors by ensuring an error-free medication management process. After EHR has brought barcodes and scanners into healthcare, it became possible to be absolutely sure that the right patient gets the right drug of the right dose via the right route at the right time. This happens because all new medication orders are entered electronically into the system and are then scanned and confirmed by every health professional involved in the process. This has shown to reduce medication prescribing errors by 75.47%, distribution errors of medications by 70.34%, medication administration time errors by 87.41%, and incorrect doses prescribed by 61.97%.

Reducing preventable medical errors: CPOE

CPOE (Computerized provider order enter) technology mechanizes the drug prescription process and provides reliable and accurate instructions for drug prescription. Technology assists health professionals by showing them relevant laboratory results and clinical studies, notifying physicians about allergies, informing them about drug inconsistencies and experimental interventions. It provides specific life-saving reminders, such as to include aspirin in coronary artery diseases, to get a flu vaccine, and inject subcutaneous heparin. CPOE also provides information to doctors at each step, suggesting a medication dosage and the right sequence of medications. Studies report that CPOE has reduced medication errors by 83%.

Reducing preventable medical errors: CDDS

CDDS (Clinical Decision Support System) is another example of information technology that helps prevent medical errors by providing information about the drugs and the patients in the most appropriate and timely manner. It gathers procedures and protocols, drug references, and allergies in one place. CDSS has been shown to reduce serious medication errors and total medication errors by 55% and 83%, respectively. The use of the system has also led to a reduction in the adverse effects of antibiotics by having improved reporting and tracking of medications’ side effects.

Poor Amenable Mortality Rates

Amenable mortality is defined as deaths resulting from diseases that don’t have to be deadly if they are taken care of in a timely and appropriate manner. Such diseases are, for example, diabetes, asthma, and appendicitis. While they are obviously dangerous, people in the twenty-first century shouldn’t be dying from them. Healthcare that is timely and effective has all the knowledge and capacity to allow people with such diseases to live a long and happy life. Amenable mortality rate, therefore, is used to assess the quality of healthcare. US healthcare has poor amenable mortality rates compared to the United Kingdom, Germany, and France.

There are plenty of changes US healthcare has to make to solve this problem. Information technology can do its part and facilitate preventive care. For example, big data analysis could identify people in need of recommended preventive care and create preventive plans for them. Wearable devices, such as diabetes wearables, collect relevant data, such as heart rate, blood sugar levels, and the amount of oxygen carried in the blood (many got familiar with oximeters which do the latter during the COVID-19 pandemic). Diabetes wearables can potentially notify physicians when care is required and notify the patient about preventive measures they should be taking. This would be a serious upgrade compared to the type of healthcare where each person with the chronic disease goes for a check-up once a year at best.

Lack of transparency

Lack of transparency in healthcare takes many forms. Firstly, frauds, cover-ups, and data breaches have been a problem for the US healthcare system for quite a while now. Secondly, the costs of medical services are unclear to patients, which makes healthcare a unique industry in North America in that consumers have no way of knowing how much the services they are paying for actual cost.

As with most of the US healthcare problems, existing US regulations are responsible. Technology that could make healthcare more transparent, while preventing data breaches and keeping track of financial transactions between patients, healthcare providers, and insurance companies is blockchain technology. Blockchain registers every transaction and flags any conflicting information, which prevents frauds, data breaches, and any other muddy activity. Despite the existing US regulations, some startups, such as Medicalchain are already trying to introduce blockchain into healthcare by creating blockchain-based EHR. And we know that this is the unavoidable future because the market is pretty clear: blockchain in the healthcare market is expected to reach $890.5 million by 2023, with Australia and the UK already experimenting with blockchain technology in their healthcare ecosystems.


The United States spends more money on healthcare than any other comparable country. Healthcare takes up almost 18% of the economy, which is over $10,000 per person per year. Yet, US healthcare is far from the best. Inefficiency and wasted resources have been flagged multiple times by doctors, scientists, and government officials. A 2017 healthcare international comparison report calculated that US healthcare takes the last place among 10 comparable countries in “administrative efficiency”. A 2019 study found that 20 to 25 percent of US health care spending is wasteful. This ends up costing the taxpayers about $760 billion per year.

So what takes up so many resources? Administrative costs have been found to be the largest source of waste. Luckily, this is exactly the field where technology could help.

From chatbots to voice assistants, technology is there to simplify almost any administrative task if you let it. Chatbots ― a healthcare market that is projected to reach $314.3 million by 2023 ― could take the place of customer service representatives of various kinds. AI-based IT solutions can do all the repetitive manual tasks that health professionals have to deal with every day. Scheduling, supply chain management, billing, data management, and so much more can be automated. Healthcare AI tools such as Notable, Protenus, and Olive already do that. There are also plenty of tools that deal with administrative tasks separately: for example, Elinext’s medical practice and billing software (see the case study here).

The shortage of staff

The US lacks medical staff, and the ones who do work are exhausted and burned out. While this has been an issue for a very long time, the COVID-19 pandemic exacerbated it. One in three healthcare workers has been burned out by the pandemic. And the situation is about to get worse: the demand for medical staff is growing and the supply is nowhere near to cover that, as recently reported by Mercer. The population is getting older, living longer, and not nearly enough young people are attracted to pursue medicine by hilarious TV shows based in hospital settings. It’s also worth pointing out that some geographical areas have it much worse than others, such as rural regions.

Technology can help understaffed hospitals by optimizing human resources: predictive analysis could help decide which people should be allocated to which facilities. It can help reach extremely understaffed areas by introducing telehealth, which is a great way of helping patients remotely. Telehealth can also decrease hospital admissions, freeing more time for medical staff.


It is often assumed that health professionals, just like all other people for that matter, resist change and would prefer the good old face-to-face admissions and a notebook to any new technology that will keep being updated until the world ends. Yet, the situation is so serious that even despite all the negative experiences, most clinicians support digitization. The American Medical Association conducted a study in 2019 that showed that clinicians would welcome digital tools. But of course, introducing digital tools into healthcare is easier said than done. While the evolution of technology is unstoppable, there are also plenty of factors holding it back. Information technology thrives on repetitive patterns and extrapolation. Yet, every patient is unique, and while computerizing the records of one person does help to know more about the other, every new piece of information complicates the model. The risks involved in IT healthcare are also enormous, which slows down and complicates development. So there is a long road ahead.