What is an example of a clinical decision support system?
Examples of CDS tools include order sets created for particular conditions or types of patients, recommendations, and databases that can provide information relevant to particular patients, reminders for preventive care, and alerts about potentially dangerous situations.
What are the top three clinical decision support systems?
Top 10 Leading Companies offering Clinical Decision Support Systems (CDSS) To Enable Better and Enhanced Medical Decision-MakingIBM Watson Health.Hearst.Cerner Corporation.Wolters Kluwer Health.Philips Healthcare.Elsevier B.V.NextGen Healthcare.MEDITECH.More items...•
What are the stages of CDSS?
A typical CDSS contains three core elements: a base or data management layer, inference engine or processing layer, and user interface.
How does CDS promote patient safety?
CDS tools enable prescribers to access real-time patient data, ideally resulting in enhanced patient safety and medication accuracy. CDS tools can also alert prescribers about potential patient warnings to prevent errors and additional adverse drug events from happening.
What are the benefits of clinical decision support?
CDS has a number of important benefits, including: Increased quality of care and enhanced health outcomes. Avoidance of errors and adverse events. Improved efficiency, cost-benefit, and provider and patient satisfaction.
What are some disadvantages of CDSS?
Several negative impacts were also reported by the studies, namely: inefficient documentation, interruption in the patient-physician communication, and an increase in unnecessary referrals.
What are the key functions of CDSS?
The purpose of a clinical decision support system is to assist healthcare providers, enabling an analysis of patient data and using that information to aid in formulating a diagnosis. A CDSS offers information to clinicians and primary care providers to improve the quality of the care their patients receive.
What is a decision support system and how is it used?
A decision support system (DSS) is a computer program application used to improve a company's decision-making capabilities. It analyzes large amounts of data and presents an organization with the best possible options available.
What are the requirements for developing a clinical decision support system?
The three main pillars being: (1) High Adoption and Effective Use. (2) Best Knowledge Available When Needed. (3) Continuous Improvement of Knowledge and CDSS Methods [32]. In the following paragraphs these three pillars will be highlighted to give an overview of tasks and challenges that lay ahead.
What are the 5 rights of CDS?
The 5 rights of CDS are as follows: The right information, to the right person, in the right format, through the right channel, at the right time in the workflow.
What are CDS tools?
Clinical decision support (CDS) tools are designed to help sift through enormous amounts of digital data to suggest next steps for treatments, alert providers to available information they may not have seen, or catch potential problems, such as dangerous medication interactions.
What is a clinical decision support alert?
CDS is not simply an alert, notification, or explicit care suggestion. CDS encompasses a variety of tools. including, but not limited to: computerized alerts and reminders for providers and patients; clinical. guidelines; condition-specific order sets; focused patient data reports and summaries; documentation.
What are the types of decision support system?
Types of decision support systemsData-driven DSS. A data-driven DSS is a computer program that makes decisions based on data from internal databases or external databases. ... Model-driven DSS. ... Communication-driven and group DSS. ... Knowledge-driven DSS. ... Document-driven DSS.
How many types are there in CDSS?
two mainThe two main types of CDSS are knowledge-based and non-knowledge-based: An example of how a clinical decision support system might be used by a clinician is a diagnosis decision support system (DDSS).
What are CDS tools?
Clinical decision support (CDS) tools are designed to help sift through enormous amounts of digital data to suggest next steps for treatments, alert providers to available information they may not have seen, or catch potential problems, such as dangerous medication interactions.
Which of the following are the major applications of CDSS?
Functions and advantages of CDSSPatient safety. Strategies to reduce medication errors commonly make use of CDSS (Table 1). ... Clinical management. Studies have shown CDSS can increase adherence to clinical guidelines. ... Cost containment. ... Administrative functions. ... Diagnostics support. ... Patient-facing decision support.
What is a CDSS?
Clinical decision support systems (CDSS) are computer-based programs that analyze data within EHRs to provide prompts and reminders to assist health care providers in implementing evidence-based clinical guidelines at the point of care. Applied to cardiovascular disease (CVD) prevention, this Domain 3 strategy can be used to facilitate care in various ways—for example, by reminding providers to screen for CVD risk factors, flagging cases of hypertension or hyperlipidemia, providing information on treatment protocols, prompting questions on medication adherence, and providing tailored recommendations for health behavior changes.
What are the legal considerations for CDSS?
Legal considerations for CDSS begin with the vendors who interpret and translate guidelines into algorithms used by these systems. Vendors must fully disclose the sources used to build the knowledge base for their software and any limitations or weaknesses of the software. Providers must ensure that CDSS programming is updated regularly to account for changes in evidence and guidelines, and that EHRs associated with CDSS include complete and up-to-date information about patients’ medical histories and allergies. 1,8,13 Provider fatigue or avoidance of CDSS guidance has been raised as a barrier to successful outcomes, leading to suggestions that initial and repeat trainings be a mandatory part of CDSS implementation.
Is CDSS effective?
Research studies that examined CDSS had strong internal and external validity, the Community Preventive Services Task Force concluded that CDSS is effective, and CDSS trials have been replicated with positive results. Implementation guidance on CDSS is available from several sources.
Does CDSS lower blood pressure?
Evidence shows that CDSS can be tied to lower blood pressure and cholesterol levels, but the findings on this association are inconsistent.
What are the functions of CDSS?
The scope of functions provided by CDSS is vast, including diagnostics, alarm systems, disease management, prescription (Rx), drug control, and much more.15They can manifest as computerized alerts and reminders, computerized guidelines, order sets, patient data reports, documentation templates, and clinical workflow tools.16Each CDSS function will be discussed in detail throughout this review, with the potential and realized benefits of these functions, as well as unintended negative consequences, and strategies to avoid harm from CDSS. Methodology used to inform the review is shown in Box 1.
What is CDSS in healthcare?
Computerized clinical decision support systems , or CDSS, represent a paradigm shift in healthcare today. CDSS are used to augment clinicians in their complex decision-making processes. Since their first use in the 1980s, CDSS have seen a rapid evolution. They are now commonly administered through electronic medical records and other computerized clinical workflows, which has been facilitated by increasing global adoption of electronic medical records with advanced capabilities. Despite these advances, there remain unknowns regarding the effect CDSS have on the providers who use them, patient outcomes, and costs. There have been numerous published examples in the past decade(s) of CDSS success stories, but notable setbacks have also shown us that CDSS are not without risks. In this paper, we provide a state-of-the-art overview on the use of clinical decision support systems in medicine, including the different types, current use cases with proven efficacy, common pitfalls, and potential harms. We conclude with evidence-based recommendations for minimizing risk in CDSS design, implementation, evaluation, and maintenance.
What are the different types of CDSS?
CDSSs have been classified and subdivided into various categories and types, including intervention timing, and whether they have active or passive delivery .7,8CDSS are frequently classified as knowledge-based or non-knowledge based. In knowledge-based systems, rules (IF-THEN statements) are created, with the system retrieving data to evaluate the rule, and producing an action or output7; Rules can be made using literature-based, practice-based, or patient-directed evidence.2CDSS that are non-knowledge based still require a data source, but the decision leverages artificial intelligence (AI), machine learning (ML), or statistical pattern recognition, rather than being programmed to follow expert medical knowledge.7Non-knowledge based CDSS, although a rapidly growing use case for AI in medicine, are rife with challenges including problems understanding the logic that AI uses to produce recommendations (black boxes), and problems with data availability.9They have yet to reach widespread implementation. Both types of CDSS have common components with subtle differences, illustrated in Fig. Fig.11.
What is a CDSS?
A clinical decision support system (CDSS) is intended to improve healthcare delivery by enhancing medical decisions with targeted clinical knowledge, patient information, and other health information.1A traditional CDSS is comprised of software designed to be a direct aid to clinical-decision making, in which the characteristics of an individual patient are matched to a computerized clinical knowledge base and patient-specific assessments or recommendations are then presented to the clinician for a decision.2CDSSs today are primarily used at the point-of-care, for the clinician to combine their knowledge with information or suggestions provided by the CDSS. Increasingly however, there are CDSS being developed with the capability to leverage data and observations otherwise unobtainable or uninterpretable by humans.
Why do we need to do an analysis?
An analysis should be done to determine if the costs are justified and if there is a good return on investment.110Cost analysis is notoriously missing in the literature, but examples can be found.107,111,112Payers may be more willing to support CDSS if cost-savings can be shown elsewhere in the system / process. This means looking at more than just direct costs a using metrics such as patient outcomes or quality-adjusted life years (QALY).
Why is it important to conduct analysis of a system?
It is important to conduct analysis to see how the system is being used in the long term, after implementation. If accuracy is an issue, design changes might need to be taken to prompt extra checks or confirmation of orders.85
Is setup cost effective?
Setup can be expensive (capital or human resource), and long-term cost-effectiveness is not guaranteed.
How are healthcare decisions made?
Moreover, decisions by healthcare professionals are often made during direct patient contact, ward rounds or multidisciplinary meetings. This means that many decisions are made in a matter of seconds or minutes, and depend on the healthcare provider having all patient parameters and medical knowledge readily available at that time of the decision. Consequently, current decisions are still strongly determined by experience and knowledge of the professional. Also, subtle changes in a patient’s condition taking place before hospital- or ward admission are often overlooked because clinicians regularly perceive a patient in his current state without taking into account changes within normal range. A computer however, takes into account all data available making it also possible to notice changes outside the scope of the professional and notices changes specific for a certain patient, within normal limits.
What is CDSS in EHR?
A CDSS can take into account all data available in the EHR making it possible to notice changes outside the scope of the professional and notice changes specific for a certain patient, within normal limits. However, to use of CDSS in practice, it is important to understand the basic requirements of these systems.
How long has CDSS been around?
They date back as long as the 1960s [ 22 ]. They supported pharmacists with drug allergy checking, dose guidance, drug-drug interaction checking and duplicate therapy checking. Medication related CDSS took further shape when directly linked to computerized physician order entry (CPOE) [ 23 ]. CPOE being the system that enabled physicians to prescribe medication using electronic entry. The combination of CPOE and CDSS helped physicians choose the right drug in the right dose and alert the physician during prescribing if for example the patient is allergic. Combining CPOE with basic medication related CDSS meant a giant leap in safer medication prescribing [ 24, 25 ]. However, all of the checks mentioned above follow simple ‘if then else’ logic and do not combine multiple patient characteristics when producing alerts. This addition came with the introduction of advanced medication related CDSS.
Why do we use CPOE and CDSS?
The combination of CPOE and CDSS helped physicians choose the right drug in the right dose and alert the physician during prescribing if for example the patient is allergic. Combining CPOE with basic medication related CDSS meant a giant leap in safer medication prescribing [24, 25].
When did CDSS start?
As mentioned earlier thepromise of CDSS has been around since the 1960s. In 2008, Simon et al. still found that the vast majority of EHRs across the U.S.A. implemented little or any decision support [ 30 ]. A recent survey send out to all Dutch hospital pharmacies showed similar disappointing results, only 48% of them using some kind of advanced CDSS [ 31 ].
What are the characteristics of CDSS?
Categorization of CDSS is often based on the following characteristics: system function, model for giving advice, style of communication, underlying decision making process and human computer interaction which are briefly explained below [ 11 ].
What are the three pillars of the American Medical Informatics Association?
The three main pillars being: (1) High Adoption and Effective Use. (2) Best Knowledge Available When Needed. (3) Continuous Improvement of Knowledge and CDSS Methods [ 32 ]. In the following paragraphs these three pillars will be highlighted to give an overview of tasks and challenges that lay ahead.
What is clinical decision support?
Clinical decision support systems use specific parameters (such as diagnoses, laboratory results, medication choices, or complex combinations of clinical data) to provide information or recommendations directly relevant to a specific patient encounter at the point of care.
How effective are decision support systems?
Decision support systems are effective at improving medication safety in both inpatient and outpatient settings. Multiple reviews have found that computerized provider order entry (CPOE) systems with integrated CDSS reliably prevent prescribing errors (although current systems are not effective at preventing errors at other stages of the medication use process and therefore may not reduce overall adverse drug event rates). CDSS are also being used to augment clinicians' skills in other areas—such as diagnostic accuracy—but less evidence currently supports these applications.
What is a CDSS decision support system?
Decision support systems were initially designed to be used by clinicians at the point of care , but they are now being implemented for a broader range of users. Clinical decision support systems are increasingly being used to provide support for interdisciplinary teams—for example, in the hospital setting, CDSS can calculate an individual patient's risk of readmission based on clinical and demographic factors and suggest appropriate postdischarge resources to care coordination staff. Efforts are also underway to include patients in the development, implementation, and evaluation of CDSS. Patient-centered clinical decision support (PCCDS) refers to decision support systems that support individual patients, caregivers, and health care teams in health-related decisions and actions by leveraging patient-specific information (e.g., patient-generated health data) and patient-centered outcomes research findings. This work is being led by the AHRQ-funded Patient-Centered CDS Learning Network. Although preliminary, this work holds considerable promise for increasing patient engagement in care.
What are the benefits of health information technology?
The promised benefits of health information technology rest in large part on the ability of these systems to use patient-specific data to provide personalized recommendations for care. Clinical decision support systems (CDSS—defined as any system designed to improve clinical decision-making related to diagnostic or therapeutic processes of care—were initially developed more than 40 years ago, and they have become increasingly sophisticated over time. Clinical decision support systems use specific parameters (such as diagnoses, laboratory results, medication choices, or complex combinations of clinical data) to provide information or recommendations directly relevant to a specific patient encounter at the point of care. The federal HITECH Act of 2009 incentivized health care organizations to implement health information technology, and it included decision support systems as one of its criteria for certifying electronic health record systems. As a result, by 2017 more than 90% of hospitals and 80% of clinics had implemented electronic health records (EHRs) with some form of clinical decision support.
Who funded the 75Q80119C00004?
This project was funded under contract number 75Q80119C00004 from the Agency for Healthcare Research and Quality ( AHRQ), U.S. Department of Health and Human Services. The authors are solely responsible for this report’s contents, findings, and conclusions, which do not necessarily represent the views of AHRQ. Readers should not interpret any statement in this report as an official position of AHRQ or of the U.S. Department of Health and Human Services. None of the authors has any affiliation or financial involvement that conflicts with the material presented in this report. View AHRQ Disclaimers
Why Is Clinical Decision Support Important?
The main purpose of CDS is to provide timely information to clinicians, patients, and others to inform decisions about health care. Examples of CDS tools include order sets created for particular conditions or types of patients, recommendations, and databases that can provide information relevant to particular patients, reminders for preventive care, and alerts about potentially dangerous situations. CDS can potentially lower costs, improve efficiency, and reduce patient inconvenience. In fact, CDS can sometimes address all three of these areas at the same time—for example, by alerting clinicians about possible duplicate tests a patient may be about to receive.
How does CDS help patients?
CDS can potentially lower costs, improve efficiency, and reduce patient inconvenience. In fact, CDS can sometimes address all three of these areas at the same time—for example, by alerting clinicians about possible duplicate tests a patient may be about to receive.
What is a CDS in healthcare?
Clinical decision support (CDS) provides timely information, usually at the point of care, to help inform decisions about a patient's care. CDS tools and systems help clinical teams by taking over some routine tasks, warning of potential problems, or providing suggestions for the clinical team and patient to consider.
What is CDS in AHRQ?
AHRQ's CDS Initiative includes a variety of research projects and outreach efforts to develop agreement in the health care field around the use of CDS to promote safe and effective health care. Each part of the initiative attempts to engage clinicians, provider organizations, guideline and quality measurement developers, and IT professionals in the ongoing work to improve making health care decisions using CDS systems.
What is clinical decision support?
Clinical decision support is any tool that provides clinicians, administrative staff, patients, caregivers, or other members of the care team with information that is filtered or targeted to a specific person or situation.
How can healthcare organizations implement CDS effectively?
No matter what the technical foundation, clinical decision support tools can easily turn from a blessing into a curse for clinicians.
What is the importance of reducing clinical variation and duplicative testing?
Reducing clinical variation and duplicative testing, ensuring patient safety, and avoiding complications that may result in expensive hospital readmissions are top priorities for providers in the modern regulatory and reimbursement environment – and harnessing the hidden insights of big data is essential for achieving these goals.
What is a CDS tool?
Clinical decision support (CDS) tools are designed to help sift through enormous amounts of digital data to suggest next steps for treatments, alert providers to available information they may not have seen, or catch potential problems, such as dangerous medication interactions.
Why is tapping clinical champions important?
Tapping clinical champions, including members of the nursing staff, could help to create a more receptive environment while developing a feedback pipeline to inform future efforts.
How can health IT advances help?
Reminding providers that some health IT advances have already produced positive impacts could help to soften their resistance to the idea of adding new items to their toolkit.
Why do health IT projects fail?
Many health IT projects fail because organizations are working off of different data, different visions for the outcome, or different ideas of how a tool will affect their daily operations.
Why do clinics use decision support software?
Some clinics employ decision support software to enhance adherence to clinical guidance. Similar to information about drugs and diseases, hospital rules can be encoded into a knowledge-based CDSS in the form of IF-THEN-ELSE pieces of information. Such solutions perform various tasks, from prompting nurses to take specific measurements according to a protocol to informing doctors about patients who don’t follow their treatment plans.
What is CDSS in healthcare?
Broadly speaking, a clinical decision support system (CDSS) is a program module that helps medical professionals make decisions at the point of care . The concept is not new to the healthcare sector: The first CDSS called MYCIN was built in the early 1970s at Stanford University.
Why are CDSSs built?
No matter the primary declared reason for implementation, all CDSSs are built with a matter-of-course intention to cut healthcare costs while improving patient safety. The next part will describe the advances of existing systems in achieving this ambitious goal.
Why was Mycin never put in practice?
Though MYCIN outperformed medical staff in evaluation accuracy, it was never put in practice — partially, because of slow performance, but mainly due to the ethical and legal issues. The very idea of the computer acting as a medical expert was too ahead of its time to be accepted.
What are the components of a CDSS?
CDSS architecture. A typical CDSS contains three core elements: a base or data management layer, inference engine or processing layer, and user interface. Core modules of a typical clinical decision support system. a clinical database storing information on diseases, diagnoses, and lab findings;
What is a clinical database?
a clinical database storing information on diseases, diagnoses, and lab findings; patient data; and. a knowledge base in the form of if-then rules or machine learning models. An inference engine or processing layer applies rules or algorithms and datasets from the knowledge base to available patient data.
How do health care workers pinpoint the best solution for a particular patient or case?
To pinpoint the best solution for a particular patient or case, health workers have to sift through numerous details and factors — and do it fast, under a great deal of pressure. Luckily, the most routine part of this job can be done by computers — or, to be more specific, by clinical decision support systems.
