Global Advanced Decision Support Platforms Market

The clinical decision support systems market was valued at approximately USD 1,686.3 million in 2021, and it is expected to reach USD 2,819.50 million by 2027, registering a CAGR of nearly 9.4% during the forecast period (2022-2027). The Market is driven by factors such as Growing incidence of medication error, Rise in geriatric population and Adoption of Cloud Computing in Healthcare Sector.

  • Definition / Scope
  • Market Overview
  • Market Risks
  • Top Market Opportunities
  • Market Drivers
  • Market Restraints
  • Industry Challenges
  • Technology Trends
  • Pricing Trends
  • Regulatory Trends
  • Post COVID-19 Recovery
  • Market Size and Forecast
  • Market Outlook
  • Technology Roadmap
  • Competitive Landscape
  • Competitive Factors
  • Key Market Players
  • Strategic Conclusion
  • References
  • Appendix

Definition / Scope

Advanced clinical decision support technology that gives actionable information to help health professionals make better decisions. It is a sort of system that provides doctors, employees, patients, and other individuals with health information technology that includes knowledge and person-specific information that is intelligently filtered or delivered at the proper time to improve health and health care. A clinical decision support system (CDSS) is a collection of tools meant to help doctors make better clinical judgments.

Clinical recommendations, condition-specific order sets, tailored patient data reports and summaries, documentation templates, diagnostic aid, and contextually appropriate reference information are just a few of the tools offered. According to Robert Hayward of the Centre for Health Evidence; clinical decision support systems link health observations with health knowledge to influence health choices by clinicians for improved health care.

Clinical decision support platforms market, by model

  • knowledge-based CDSS and
  • non-knowledge CDSS

Clinical decision support platforms market, by mode of delivery

  • cloud-based and
  • on-premise

Clinical decision support platforms market, by application

  • medical diagnosis,
  • alerts and reminders,
  • prescription decision support,
  • information retrieval, and
  • other applications

Clinical decision support platforms market, by Geography

  • North America,
  • Europe,
  • Asia-Pacific,
  • Middle-East and Africa,
  • and South America

Market Overview

The clinical decision support systems market was valued at approximately USD 1,686.3 million in 2021, and it is expected to reach USD 2,819.50 million by 2027, registering a CAGR of nearly 9.4% during the forecast period (2022-2027).

During the COVID-19 pandemic, countries’ health systems are heavily reliant on internet services. Patients are scheduling appointments with doctors via video chats, which aids in the treatment and monitoring of ailments, boosting the clinical decision support systems market. However, due to the COVID-19 outbreak across the world, hospitals and clinics are unable to provide services. Several countries are increasingly providing online services, which is boosting the market.

According to the World Aging 2019 Report, the world’s population of people aged 65 and more was predicted to be 703 million in 2019. This group of people is prone to a variety of chronic diseases and requires regular health screenings and treatments to stay healthy. Given the current global circumstances, a large number of people, such as the elderly and pregnant women, may require health examinations.

Furthermore, hospitals, diagnostic centres, and clinics are demonstrating an interest in clinical decision support systems to reduce pharmaceutical prescription errors, adverse drug event monitoring, and other medical errors.

The growing desire for lower healthcare costs, the need to improve service quality, and technical improvements in healthcare IT in hospitals are all expected to drive the clinical decision support systems (CDSS) market forward.

Furthermore, the Organization for Economic Co-operation and Development (OECD) Survey Report estimates that in 2020, Germany’s average per capita health spending would be USD 6,730.9, Norway’s will be USD 6,748.4, and Sweden’s will be USD 5,753.6. Due to high healthcare expenditure across the world, the rising demand to reduce healthcare expenditure has a positive impact on the market.

The hybrid optimization learning algorithm has the accuracy, sensitivity, and specificity metrics, according to a paper published in January 2020 titled “Development and implementation of a clinical decision support system for the diagnosis of social anxiety disorder.” The findings demonstrated that the proposed model was quite appropriate for SAD diagnosis and was consistent with other studies’ findings.

However, while CDSS are still in the early stages of development, a lack of faith in the systems, a scarcity of trained labor, and CDSS recommendations for superfluous diagnostic tests stymie market growth.

Market Risks

The Prime Risk for Market Players in the Global Advanced Clinical Decision Support Platforms Market is

Consolidated Market

The Global CDSS Market is highly consolidated with the top 5 players acquiring a market share of more than 60% and this along with the high investments required for R&D activities to find new software makes this industry a highly competitive segment and hence causing entry barriers and necessitating the acquisition or collaboration of small businesses with large corporations.

Top Market Opportunities

The Top Opportunities for Market Players in the Global Advanced Clinical Decision Support Platforms Market are

Emerging Asian countries

The CDSS market in Asia is predicted to increase due to a variety of factors, including the implementation of government policies boosting the adoption of HCIT solutions, rising government healthcare expenditure, and the availability of qualified IT experts in emerging Asian countries like China and India. Authorities in China are concentrating on revamping the country’s healthcare management sector, which is currently confronting issues such as a statewide scarcity of doctors, underfunded rural health centres, overburdened metropolis hospitals, and a confusing patient data system.

The Indian government launched the Digital India campaign in July 2015 to ensure that residents may access government services electronically by strengthening the country’s IT infrastructure and Internet connectivity. The e-health effort under the Digital India campaign will involve the integration of patient EHRs into a ‘digital locker’ that may be kept for a lifetime. The government released EMR/HER Standards in September 2013, which were amended in December 2016. Similarly, the CDSS market in Japan is predicted to increase rapidly as the senior population grows, the incidence of lifestyle diseases rises, and strong government initiatives such as the e-Japan policy, the new IT reform plan, and the i-Japan Strategy 2015 are implemented.

Advancements In the Healthcare IT Sector

The market for clinical decision support systems is being driven by the introduction of electronic health records and its successful integration with clinical decision support systems. Depending on the nature of the ailment being treated and the hospital’s expenditure capacity, the systems may incorporate a diverse set of equipment. Clinical decision support systems were utilized more like a clinical decision generator than a support system in the early years of their use, with the physician merely relying on the system’s output to treat the patient. In contrast to being employed as a stand-alone additional, the clinical decision support system must be integrated into the hospital’s overall working mechanism.

Market Drivers

The Major Factors driving the growth of the Global Advanced Decision Support Platform Market are

Growing incidence of medication error

A medication error is an unanticipated failure in the drug treatment process that can have a negative impact on patients’ health. Prescription errors, dispensing errors, storage errors, preparation errors, and administration errors are the most common preventable causes of unwanted adverse outcomes, and they pose a significant public health threat. Patients and healthcare providers will receive better care if they have access to complete and accurate EHRs that have a complete patient illness history. Such records can help doctors make better diagnoses, avoid mistakes, save time, and even shorten patient wait times. For hospitals and clinicians to provide quality treatment, CDSS and its accompanying technologies must be implemented and used successfully, which is hastening their acceptance around the world.

Rise in geriatric population

One of the major factors driving market revenue share is the growing elderly population. By 2050, it is anticipated that 16% of the global population would be over 65 years old. The World Health Organization (WHO), the United Nations (UN), and the European Commission all predict that ageing will be a big burden for society, requiring dedicated efforts to fulfil the needs of the elderly. Physicians delivering primary care are increasingly being asked to perform comprehensive and extensive health screenings of the senior population. CDSS helps healthcare providers find the most appropriate and relevant treatment for patients by providing the finest answers and diagnoses for medical problems.

Adoption of Cloud Computing in Healthcare Sector

Cloud computing adoption is driving market revenue share in the healthcare industry. Due to the growing use of healthcare Internet of Things (IoT) devices and the need to document and analyze vast amounts of data to deliver both personal and population health management services, the demand for cloud computing has increased at a rapid rate from both a business and technology standpoint. Cloud computing speeds up the delivery of sophisticated healthcare solutions by allowing the use of technologies like big data analytics, cognitive computing, mobile collaboration, and information interchange.

Market Restraints

The Major Factors restraining the growth of the Global Advanced Decision Support Platform Market are

Data security concerns related to cloud based CDSS

Data housed by the vendor is not as secure as data hosted on-premise, which is a big problem with cloud-based CDSS. Patient information is deemed sensitive, and a high level of privacy must be maintained so that only authorized people have access to it. Patient information has been scrutinized by legislative frameworks all throughout the world, such as the HIPAA data privacy standards (Health Insurance Portability and Accountability Act). In the same way, the European Union has enacted the EU Data Protection Regulation, which has consequences for the protection of sensitive health information. A patient’s protected health information (PHI) cannot be moved out of the country of origin in many nations. Because public cloud has the same security vulnerabilities as traditional IT systems, it is not recommended. Despite the fact that private clouds provide greater access procedures and systems, the healthcare business is skeptical of their efficacy.

As of June 2020, over 81 percent of healthcare businesses had experienced cloud data security breaches, according to a survey done by Ermetic, a cybersecurity investigation firm. In almost 31.25 percent of healthcare businesses, user access was denied as a result of a breach. Due to the necessity for access to patient data across many departments, major data security risks develop. As a result, security flaws emerge, which hackers might exploit to get access to critical information. As a result, a number of large hospitals continue to prefer on-premise solutions to cloud-based options.

Lack of interoperability

Clinical decision solutions may fail to interact successfully with other modules even after being integrated into the hospital IT environment due to the diversity of healthcare record standards. Fortunately, with the widespread use of Fast Healthcare Interoperability Resources (FHIR), the most recent HL7 format for exchanging and sharing healthcare data, the situation is constantly improving. Many HER providers and medical organizations are already using it. The standard should be embraced at all levels of a healthcare organization, as well as by any external systems you want to employ, to ensure easy data transmission.

Industry Challenges

The Key Challenge for Market Players in the Global Advanced Decision Support Platform Market is

High Cost of Implementation

CDSS implementation is not cost-effective for all hospitals and clinical centres, which could stifle market growth in the near term. The cost of servicing and software upgrades for these systems can sometimes exceed the cost of the original device, limiting the market’s growth.

Technology Trends

  • MIT researchers created a deep learning platform that combines bedside monitors, clinical notes, and other data sources to anticipate the health of ICU patients so that care plans for highly complex patients can be adjusted. As AI and machine learning gain traction in the healthcare industry, more CDS tools are being developed using these analytical methodologies.
  • University of Pennsylvania scientists have developed a CDS tool that cuts the time it takes to diagnose the life-threatening infection sepsis by 12 hours, potentially saving the lives of numerous people. For many people, it might mean the difference between life and death. It uses machine learning, and the system was trained on data from about 160,000 patients before being verified on a sample of 10,000 people.
  • The leaders in the development and deployment of anticoagulation clinical decision support software, Point of Care Decision Support, announced the release of a new edition of their AC programme in April 2018. This programme was created with the cooperation of clinical thrombosis experts to solve the complicated issues of treating warfarin and non-vitamin K antagonist oral anticoagulants, and it allows healthcare provider teams to provide evidence-based quality of care for anticoagulant patients.
  • In April 2018, Apple revealed that 39 health systems have signed up to give Apple’s Health Record HER patient data viewer access to their patients’ health data. These businesses can now access their health records on iOS devices such as iPhones and iPads. Patients may now access medical information from a variety of healthcare institutions through the revised Health Records feature of the Apple Health app. Patients are also notified when their health data is updated, and they can collaborate with clinicians to make more informed clinical decisions.
  • The Centers for Medicare and Medicaid Services has certified MedCurrent’s clinical decision support system, OrderWise. OrderWise is up to date and assists healthcare providers in ordering the appropriate imaging tests for their patients by utilizing data from Intermountain Healthcare, Sage Evidence-based Medicine & Practice Institute (SEMPI), National Comprehensive Cancer Network (NCCN), and the American College of Cardiology (ACC).

Pricing Trends

The Major factors determining the cost of an advanced clinical decision support platform are

  1. cost of development
  2. implementation cost and
  3. ongoing cost of operation

According to the studies, the annual cost per practice for a registry-based CDSS was around $9,500 for small practices, $20,600 for medium practices, and $76,000 for big practices, based on a survey of users and vendors. The annual costs per patient were estimated to be $69, $23, and $14, respectively. The annual per patient expenditures were estimated at $55 in a US study that projected the cost of scaling up a registry-based CDSS countrywide, which is quite close to the survey-based estimate for a small practice. On the other hand, based on data acquired during a controlled trial, another US study estimated the annual cost of a medium-sized CDSS at $106 per patient ($132,400 per practice).

Regulatory Trends

The US Government’s Health and Medicare Acts have endorsed CDSS, financially rewarding CDS integration into EHRs. In 2013, around 41% of US hospitals having an HER also had a CDSS, while 40.2 percent of US hospitals had advanced CDS capability in 2017. (HIMSS Stage 6). In other countries, EMR acceptance rates have been promising, with about 62 percent of practitioners in Canada using them in 2013. 12 Canada has received major government support, as well as support from Infoway, a non-profit organization. With up to 20 billion euros invested in healthcare IT in 2010, England has also been a world leader. Several countries, including Denmark, Estonia, Australia, and others, have successfully implemented national health records, at least for patient-facing data.

Post COVID-19 Recovery

The COVID-19 epidemic has created new hurdles in the health-care ecosystem. Huge influxes of critically ill patients, as well as personnel shortages and capacity constraints, face hospitals and health systems. Clinicians, on the other hand, are now better equipped with the information and abilities gained during the pandemic’s early stages.

The increased usage of clinical decision support software in COVID-19 has underlined the global need for reliable healthcare data while shortening decision-making timelines due to excessive stress. Many health-care organizations have changed their clinical decision support system vendors to make it easier to get the results they want. As a result, many of the world’s most major healthcare centres, which are among the first responders, have a greater understanding of the usefulness and challenges of clinical decision support systems. As a result, want clinical decision support in forms that make essential data easily accessible. Workflow integration is expected to be a key driver of market growth in the future years.

Market Size and Forecast

The clinical decision support systems market was valued at approximately USD 1,686.3 million in 2021, and it is expected to reach USD 2,819.50 million by 2027, registering a CAGR of nearly 9.4% during the forecast period (2022-2027).

The COVID-19 Pandemic has posed additional obstacles to the health-care sector. Hospitals and health systems are being challenged by an increase in the number of critically ill patients, as well as personnel shortages and capacity limits. It has directly resulted in an increase in the use of CDSS technologies for quick medical treatment and diagnosis. COVID-19’s growing use of clinical decision support software has highlighted the global need for standardized healthcare data while also decreasing decision-making times due to excessive stress.

Knowledge-based CDSS to lead the market in the forecast period

The market is divided into knowledge-based CDSS and non-knowledge-based CDSS based on the system model. The knowledge-based CDSS sector, which accounted for 59 percent of the market in 2021, was the most popular. During the projection period, this segment is expected to have the highest CAGR of 10.2 percent. The substantial share and rapid expansion of this market can be ascribed to the many useful features of knowledge-based CDSS, such as assisting physicians in making clinical decisions in the face of uncertainty using knowledge-based reasoning. In comparison to non-knowledge-based systems, these systems may be integrated into clinical workflows and are less prone to errors.

Active CDSS segment accounted for the largest share of 58.9% of the market in 2021

The CDSS market can be divided into active and passive CDSS based on the extent of interactivity. In 2020, the active CDSS segment held the greatest market share of 58.9%, and it is also expected to grow at the fastest CAGR over the forecast period.

Asia Pacific to witness significant growth from 2021 to 2027

The clinical decision support system market is divided into four geographic segments: North America, Europe, Asia Pacific (APAC), and the Rest of the World. Over the next five years, the APAC market is predicted to develop at the fastest rate. The CDSS market in Asia is predicted to increase due to factors such as a large geriatric population, improved government laws, a high burden of chronic diseases, and an increasing focus of various industry players on emerging Asian countries.

Market Outlook

The market for advanced clinical decision support systems was valued at $450.4 million in 2020, and is expected to grow to $1,049.8 million by 2030, with a CAGR of 8.70 percent between 2020 and 2030.

The increased usage of clinical decision support software in COVID-19 has underlined the global need for reliable healthcare data while shortening decision-making timelines due to excessive stress. Many health-care organizations have changed their clinical decision support system vendors to make it easier to get the results they want. As a result, many of the world’s most major healthcare centres, which are among the first responders, have a greater understanding of the usefulness and challenges of clinical decision support systems. As a result, want clinical decision support in forms that make essential data easily accessible. Workflow integration is expected to be a key driver of market growth in the future years.

Knowledge-based CDSS to lead the market in the forecast period and continue with its domination during the forecast period with a Market Share of 59%.

Active CDSS segment accounted for the largest share of 58.9% of the market in 2020 and is poised to expand its domination throughout the projection period (2020 – 2030).

The CDSS market in Asia is predicted to increase due to factors such as a large geriatric population, improved government laws, a high burden of chronic diseases, and an increasing focus of various industry players on emerging Asian countries.

Technology Roadmap

The Advanced Clinical Decision Support Platform finds application in the following areas and technology can improve the outcome from these applications with the potential of CDSS.

Drug selection

According to statistics, 7,000 to 9,000 individuals in the United States die each year as a result of drug errors. Aside from that, many more patients suffer from difficulties due by ineffective drugs, incorrect dosage, or drug incompatibility, resulting in annual treatment expenses of more than $40 billion.

The good news is that nearly half of all drug errors occur during the ordering or prescribing process. As a result, errors can be identified and avoided before they cause harm. And that’s where a decision support tool can help, by reducing the likelihood of medication errors caused by human factors like distraction, which accounts for about 75% of all prescription errors.

Using critical patient data such as weight, age, allergy status, and current prescriptions, CDSSs may automatically deal with the following tasks.

  1. Drug allergy checking
  2. Basic guidance on dosage
  3. Checking for duplicate therapy
  4. Drug interactions checking

Diagnostic support

Diagnostic decision support systems (DDSSs) or medical diagnosis systems are terms used to describe CDSSs for disease detection (MDSs). They use a knowledge base to compare facts about a patient’s condition and provide a list of possible diagnoses.

A solution that uses deep learning for diagnostic imaging is an example of a DDSS. It used to concentrate on a single issue, such as lung abnormalities or a specific form of cancer. AI-powered systems, like other CDS tools, act as a second pair of eyes, making suggestions and alerts rather than reaching a definitive judgement.

Cost containment

Decision support systems, when integrated into a CPOE system, can help reduce treatment costs by recommending cheaper drug alternatives or recognizing test duplications. According to studies, CDSSs save hospitals hundreds of thousands of dollars each year by alerting them to cases of unnecessary medical testing.

Clinical management

To improve adherence to clinical guidelines, several clinics use decision assistance software. Hospital regulations, like information about drugs and diseases, can be encoded as IF-THEN-ELSE pieces of information in a knowledge-based CDSS. Such software can accomplish everything from reminding nurses to collect precise measurements according to a procedure to alerting doctors about patients who aren’t sticking to their treatment plans.

Competitive Landscape

There are a number of multinational, regional, and local participants in the clinical decision support systems industry. However, due to their brand image and market reach, a few large international businesses dominate the market. The market is competitive and concentrated. Acquisitions, mergers, supply of bespoke solutions, and expansions into new commercial areas are all priorities for industry participants. Furthermore, as part of their commercialization strategy, corporations are investing significant resources in developing new products and platforms with upgraded and better capabilities.

Key Market Developments

  • In Dec 2020: Zynx Health revealed that it has meaningfully increased and modernized the publicly accessible COVID-19 clinical decision support obtainable on its website, The newest updates combined into the Zynx Health content consist of recommendations from organizations such as the Infectious Diseases Society of America, which is likely to make giant strides in the global Centers for Disease Control and Prevention the World Health Organization.
  • In October 2020, WeHealth Digital Medicine, Servier Group’s e-health business unit, and CureMatch, a leader in digital health precision medicine, announced that they had received CE Mark approval for Bionov. Bionov is a clinical decision support software platform that presents healthcare professionals with personalized single drug and combination drug treatment options based primarily on the molecular profile of their cancer patients.
  • In March 2020, IBM Watson Health and EBSCO Information Services announced a strategic collaboration aimed toward enhancing clinical decision support (CDS) and operations for healthcare providers and health systems. The companies are combining their respective solution suites into a single, high-value global solution called DynaMed and Micromedex with Watson. The combined solution suite is designed to bring together drug and disease content into a single source for evidence-based insights.

Competitive Factors

The Market Players are engaged in both Organic and Inorganic strategies of Market Growth. The Market Players are adopting organic strategies such as improving quality of the software by investing heavily on Research & Development (R&D) and inorganic strategies such as Mergers & Acquisitions (M&A), Strategic Partnerships and Alliances. For instance, In Nov 2020: NantHealth, Inc., a supplier of enterprise solutions that help businesses convert complex data into actionable insights, declared the issuing of a study that discovered RNA sequencing is not only feasible but may also deliver important clinical worth in examining a cancer patient’s exact disease biology to permit an enhanced treatment decision with an advanced likelihood of success. The study was conducted in collaboration with NantOmics, LLC and ImmunityBio, Inc.; the report was intended to explore the possible use of formalin-fixed paraffin-embedded (FFPE)-derived RNA transcriptome reporting for clinical decision-making.

Key Market Players

Though there are multiple providers offering decision support modules for different tasks, the market is dominated by five major players — Siemens, Philips, IBM, Cerner Corporation, and Change Healthcare.

Siemens Healthineers: strong focus on test results

Siemens Healthineers, a major provider of diagnostic imaging systems, also offers a variety of software solutions for healthcare facilities. Protis Data Management System is the company’s main decision-making tool, with Protis Assessment Software as an optional element. The former combines test results from many platforms into a single graphical report for a patient. The latter aids in the interpretation of clinical data by clinicians.

Besides Protis, the company offers the following CDS solutions:

  • AI RAD Companion, an AI-powered cloud app to help with analyzing CT, X-ray and MRI scans of the brain, prostate, chest and other organs;
  • Prisca system for prenatal risk calculation based on biochemical markers, ultrasound measurements, and demographics; and
  • Medicalis, a cloud-based clinical decision support mechanism to ensure compliance with the AUC program.

Philips Healthcare: continuous monitoring and sending alerts

The Philips Healthcare division put a lot of money on CDSS solutions to round out the company’s patient monitoring systems. There are now five tools available for use with Philips IntelliVue monitors.

  • Horizon Trends Monitors vital signs in real time (body temperature, pulse, breathing rate, and blood pressure) and sends out notifications if anything is out of the ordinary.
  • ST Map focuses on the ST-segment of the electrocardiogram. Patients with an acute coronary syndrome who are at risk of myocardial ischemia should have continuous ST-segment monitoring. Medical personnel can use ST Map to see critical changes and make timely judgments.
  • Event Surveillance tracks up to four clinical parameters, and when two, three, or four of them reveal serious variances, a physician is notified. You can use the solution to define individual thresholds and generate “smart alerts” based on the demands of a certain patient. For example, if your heart rate changes by more than 50% in 60 seconds, you’ll be notified.
  • ProtocolWatch Sepsis Checks a patient’s vital signs against sepsis criteria and alerts carers if they are met.
  • Histogram Trends module displays the measurements of a patient over a long length of time. It enables a doctor to determine whether a therapy or drug is having the desired impact.

IBM Watson Health: end-to-end management of drugs, diseases, and toxins

Micromedex Clinical Knowledge is an evidence-based clinical decision support system utilised in over 4,500 institutions around the world, according to IBM Watson Health. It works with all of the most popular EMR and CPOE systems. The modular framework allows hospitals to gradually add features as needed. Micromedex currently consists of three major components.

A Medication Management module examines all forms of drug interactions, such as drug-drug, drug-disease, drug-food, drug-laboratory, drug-ethanol, drug-pregnancy, and drug-lactation, to identify potentially dangerous or undesired combinations.

It also features a drug dosage calculator and makes suggestions on herbal and other alternative therapies that can be used alongside conventional medicine.

  • A Disease and Condition Management module allows for quick access to treatment information, reducing errors, lowering treatment costs, and avoiding unnecessary exams and procedures.
  • All American accredited Poison Control Centers and emergency departments use a Toxicology Management module to identify probable poison sources, offer toxicology analysis, and make timely informed judgments in the event of chemical accidents and exposures.
  • IBM announced a cooperation with DynaMed, a clinical reference resource that provides quick answers to medical concerns in a variety of specialties, in March 2020. For clinicians at the point of care, the two businesses offer a combined DynaMed and Micromedex with Watson platform. They continue to market their own solutions separately at the same time.

Cerner: addressing critical conditions

Cerner is a global health information technology company. The company also provides connection hardware components and medical devices, in addition to end-to-end EHR systems and a variety of clinical software solutions. Its CDS tools are developed for the most essential situations, where every hour counts.

  • Sepsis CDSS attempts to detect life-threatening infections in the bloodstream early. After Cerner co-founder Neal Patterson’s sister-in-law died of sepsis caused by pneumonia, the system was created. Doctors failed to notice early indicators of the condition; therefore, she did not receive proper treatment. Cerner’s sepsis surveillance system is now in use in hundreds of hospitals across the United States. It monitors a patient’s vital signs in real time and warns a clinical team if it detects sepsis-like behaviors.
  • Acute kidney infection (AKI) is a hazardous disorder that needs to be detected and treated as soon as possible. The module scans the urine for variations in serum creatinine levels. When its concentration begins to climb dangerously, the system alerts professionals and offers advice on what to do.
  • A Rapid Response component integrates with sepsis and AKI modules to enable immediate intervention when vital signs start changing rapidly and unexpectedly.

Change Healthcare: strict adherence to criteria at all levels of care

One of the major IT companies in the medical area, Change Healthcare, provides solutions that connect hospitals, patients, and payers. One-third of all clinical records in the United States are managed by the company’s networks. InterQual, a clinical decision support solution, has a 40-year track record of accumulating knowledge. The system divides evidence-based criteria — or nationally accepted standards of adequate care — into several big groups and makes them available to users.

The flagman system can be completed with a couple of useful cloud-based tools.

InterQual AutoReview is the first healthcare solution automating the medical review process. It uses Natural Language Processing (NLP) models to pull data from the EHR and identify diagnostic information in unstructured clinical content.

CareSelect Imaging brings advanced imaging guidelines into existing EHR workflows to meet PAMA requirements.

Strategic Conclusion

As clinical decision support platform (CDSS) technology is still in its early stages, doctors, patients, and other stakeholders will be required to provide ongoing input in order to effectively integrate CDSS technology in order to enhance relevant applications, reduce costs, and improve treatment outcomes, resulting in significant market growth.

The key drivers for market expansion are an increase in the aged population, an increase in the number of hospitals, an increase in the need for data-driven technologies, and an increase in the number of emergency department (ED) visits. The healthcare system is expected to confront a physician shortage in the next years, necessitating the employment of decision-making technologies to better manage physician time and avoid errors.



  • SMEs – Small & Medium Enterprises
  • CDSS – clinical decision support systems
  • OECD – Organization for Economic Co-operation and Development
  • R&D – Research & Development
  • WHO – World Health Organization
  • IoT – Internet of Things
  • HIPAA – Health Insurance Portability and Accountability Act
  • PHI – Protected Health Information
  • FHIR – Fast Healthcare Interoperability Resources

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