Doctors, whether generalists or specialists, can no longer control the entire medical knowledge to recognize disease or determine the best therapeutic management. Thus, they often use external sources of information, traditionally colleagues, books, and Clinical Practice Guidelines, to find the information they lack. Nevertheless, despite the on-line diffusion of large volumes of easily accessible documentary resources, finding a solution to the problem posed by a given patient remains a difficult task. Early on, clinical decision support systems have been developed as potential solutions to this difficulty (Berner, 2007). The development of such systems appears even more crucial that many studies are published each year and who report frequent mistakes in the management of patients. Since the publication of "To Err is Human" (Kohn et al., 2000), CDSS are gaining an increased pop-ularity in various domains of health care. …show more content…
According to Shortliffe (1987) a clinical DSS is “any computer program designed to help health professionals make clinical decisions". And as stated by Conejar and Kim (2014), CDSSs are expected to improve the quality of care by providing more accurate, effective, and reliable diagnoses and treatments, and by avoiding errors due to physicians' insufficient knowledge. Moreover, they allow the doctors especially the novice ones to learn more from existing experiences, evaluate their capabilities, and enhance their performance of diagnoses. In addition, CDSS can decrease healthcare costs by providing a more specific and faster diagnosis and by processing drug prescriptions more efficiently (Garg et al, 2005, Kawamoto et al, 2005, Roshanov et al,
Analyze the requirements of the system and how this DSS is reducing medical errors and improving clinical practice.
Gawande’s (2015) article “Overkill,” suggests that physicians overprescribe drugs and tests which are ultimately unnecessary for patients. To eradicate such behavior, I would implement an electronic health record (EHR) with the following functions: Computerized provider order entry (CPOE) with a clinical decision support system (CDSS) to assist physicians/clinicians (stakeholders) in their medical practice or at hospitals. These functions will help to alleviate redundant tests and make suggestions about treatment. According to HealthIT.gov (2014), CDSS caters chiefly to drugs, laboratory testing, radiology procedures, and helpful clinical literature (HealthIT.gov, 2014).
Clinical Information Systems (CIS) is a type of electronic computer system database that has the capability of storing clinical information for healthcare delivery (Biohealthmatics.com, 2016). CIS has been implemented in many clinical settings to help guide clinicians with decision making abilities to provide appropriate treatments based on the patient’s history of illness, age, and other information of care provided by the facility that has been entered in the electronic health record (EHR) (Biohealthmatics.com, 2016). In regards to the case study, CIS automatically prompted an MRI of the brain alert as an appropriate intervention based on Mrs. John’s history of present illness, diagnosis, age, and the assessment competed by the nurse entered into the (EHR).
The data associated with the utilization of the Diagnotes Platform have been provided. We intend to critically analyze the data, and establish relationships between different parameters in Diagnotes Platform. The analysis will be directed towards measuring/improving the quality and outcome of patient care which will increase patient’s acceptability toward Diagnotes and indirectly will improve the financial and operational performance of health organizations.Diagnotes, is a software platform that provide common communication platform that connects healthcare providers, physicians and patients in a secured way. Some of the features include HIPAA compliant communication, care coordination, referrals and consult, transitions of care, call center
I agree with you that the rush to meet compliance created haphazard and fragmented clinical decision support (CDS) tools throughout the health care industry. I also agree that workflows in health care can be complex; so what is the solution for usable and effective CDS tools? First and foremost an organization needs to have a clear picture of what the need is that will be supported by the implementation of CDS tools. Not all tools are relevant to all areas of health care.
A clinical information system (CIS) collects patient information from technological applications. The information is distributed to certain locations in the facility/healthcare setting. Locations vary based on unit, such as OBGYN, cardiology, ICU, or psychiatric. The CIS represents the patient’s history of illnesses and interactions with health care providers by encoding knowledge capable of helping clinicians decide about the patient’s condition, treatment options, and wellness activities (Sittig et al., 2002).
The value of Clinical Decision Support Systems is having additional avenues monitoring patient’s data input. The Clinical Decision Support Systems are offering notifications of patient’s record data to specified department or medical personal.
Clinical decision-support systems (CDSS) apply best-known medical knowledge to patient data for the purpose of generating case-specific decision-support advice. CDSS forms the cornerstone of health informatics research and practice. It is an embedded concept in almost all major clinical information systems and plays an instrumental role in helping health care achieve its ultimate goal: providing high quality patient care while, at the same time, assuring patient safety and reducing costs. This computer based systems designed to impact clinician decision making about individual patients at the point in time that these decisions are made. If used properly, CDSS have the potential to change the way medicine has been taught and
Clinical decision support system (CDSS) is gaining increased recognition in healthcare organizations. This is due to an increasing recognition that a stronger CDSS is crucial to achieve a high quality of patients care and safety1,2. CDSS is a class of computerized information system that supports decision-making activities2. It uses patient data to provide tailored patient assessments and evidence-based treatment recommendations for healthcare providers to consider2,3”. Patient data can be input by digital entry, queried from other clinical information systems or transmitted from medical devices. Patient data are compared against a knowledge-base and made sense of by an inference mechanism. The knowledge base can be procured commercially or developed in-house. The inference mechanism can be highly variable in sophistication ranging from a simple ‘yes ‘no and ‘if ‘then statement to Bayesian prediction techniques and/or fuzzy logic. The output can also take a number of forms and can be delivered to a number of destinations at any time before, during or post-interaction with the patient4.
Electronic Health Systems are equipped with many features that are designed to reduce medical errors and help navigate patients through the healthcare system. One system that is worth looking at is the MedicsDocAssistant™ (MDA™). MDA™ supports many features such as alerts (“MedicsDocAssistant,”). Alerts will pop up on a provider’s screen letting them know that there is something wrong with the patient’s care. Alerts can range from prescription alerts, warning physicians of potential adverse drug effects or allergy complications, to alerts pertaining to clinical decisions regarding patient examinations, procedures and screenings that may be crucial. For example, the system will alert to the physician to remind female patients of a certain age to schedule a mammogram screening. The objectives of these alerts are to aid in properly diagnosing patients, identifying gaps in care, running appropriate tests as well as improving patient outcomes (“How EHR Alerts,” 2012).
At the end of this semester, our group will articulate the results related to issues faced in different domains of CDSS. Then, we will also propose our own recommendation based on the literature sources that we will review about Clinical Decision Support System.
The major components of Clinical Decision-Support System (CDSS) was generated to manage daily work flow in a more effective manner in regards to clinicians cognitive thing. This would also help aid in “clinical data banks and algorithms, analytic or pathophysiologic models, clinical decision theoretical models, statistical pat-terns recognition methods, symbolic reasoning, and clinical expert knowledge bases....” (Tan, 1998 pp.220) The goal of CDSS was to improve patient care and assist in the patients’ quality of life with the help of the Clinical Reminder System (CRS).
Clinical information systems are used to store, collect, and retrieve information for use in the healthcare delivery process. This is where information such as patient demographics, history, and provider care are stored (Biohealthmatics.com, 2006). Some examples of clinical information systems are patient registration systems, laboratory information systems, emergency medical systems, and clinical decision support systems. Patient registration systems involve the admission, discharge, and transfer of patient demographics and insurance information. These systems must be linked to all departments to increase the quality of patient care. Laboratory information systems are used for reporting test results as well as a wide variety of other tasks
Technology can assist healthcare workers on every clinical and administrative level to use information more effectively in clinical decision-making for patients, and in implementing strategic goals within an organization.
Both a Clinical Data Repository (CDR) and Clinical Data Warehouse (CDW) have many benefits and limitations as they save data in databases, which consolidates data from a range of clinical sources. The databases are optimized to allow physicians to retrieve data on a specific patient instead of trying to identify a common ethnic group, population, or characteristics of patients. Clinical Data Repository is used in hospital settings to track patients’ records and suggesting trends as well as observing diseases or illnesses. CDR's are specifically used in the pharmaceutical industry when prescribing medications. CDR has some positive characteristics, such as clinical laboratory test results, patient demographics, pharmacy information, radiology reports and images, discharge and transfer datas, ICD-9 codes, and discharge summaries. These benefits will help provide more knowledge about patients their medical conditions and their outcomes. Clinical Data Repository is well designed to deliver the EHR content to users to access patient information and to help save time by limiting paper records, advances results through traditional displays, and also individual patients are able to access their data quicker and easier. Outcomes of patient’s care will be monitored and analyzed patient’s health information, etc.