Electronic health Records and Clinical Decision Support System

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In implementing an electronic health record (EHR), it is important to keep in mind the importance of acquiring a reliable clinical decision support system (CDSS).

According to ISO (the International Organization for Standardization) Electronic Health Record (EHR) is defined as "repository of information regarding the health status of a subject of care, in computer processable form" ("Health informatics - Electronic health record"). The widespread use of EHRs was represented by the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009. EHR will transform the paper based health care system to computerized health care system which will improve the quality of health care to patients. The EHRs includes the health information of patients like immunizations, medical history, medical problems and their treatment, progress of medication, vital signs, radiology and laboratory data and all about demographics of patient. The EHR is not merely a storing of medical information it also includes analyzing and comparison of results and data, reminders, alarms etc. It improves communication within the medical team and even with patients so that efficiency of health care system will be increased with speedy solutions. EHRs have many potential capabilities but, clinical decision support (CDS) tools, computerized physician order entry (CPOE) systems, and health information exchange (HIE) are the three important functionalities which improves quality of care with reduced cost (Nir Menachemi, 2011).

How does a clinical decision support work with an EHR? What does it consist of?
Describe their capabilities and how they are used to enhance health care.

Integrated CDSS/EHR:
A CDS is health information technology system which helps the health care provider to analyze the data and to make decisions related to patient care. EHR will make the patient data and other information available for Clinical Data Support System (CDSS), so that clinical decisions can be made (Douglas L. McGee). There are numerous benefits when we integrate CDSS with EHR. Their integration will provide best practice with high quality health care. By integrating both CDSS and EHR prescription errors, medical errors and adverse drug reactions can be easily addressed so that a quality patient care can be provided. While using a fully integrated CDSS/EHR, some points need to be concerned. They include ("Clinical decision support system")
1. Privacy
2. Confidentiality
3. User-friendliness
4. Document accuracy and completeness
5. Integration
6. Uniformity
7. Acceptance
8. Alert desensitization

The major components of EHR system are

1. User interface

2. Record services

3. Terminology services

4. Clinical Decision Support System (CDSS)

1. User interface: It is the fundamental component of the EHR. It is used to enter and display the patient health records. Thus, it has two main functions. Firstly, to provide inputs to CDSS and secondly, to display alerts, guidelines and advices.

2. Record services: They contain set of services for managing patient health records. Its functions include entering, searching, retrieving, querying, extracting, communicating and exchange the data in health records.

3. Terminology services: They are used to manage the terminology resources.

4. Clinical Decision Support System (CDSS): It executes the decision. It includes number of subcomponents and sub processes.

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Previously CDSS were used to make decisions for the clinicians literally, but now a day, it is modified in such a way that the clinicians are able to enter their inputs into system and can wait for system to advice them the correct action with its output. There are so many functions for a CDSS, but the four important functions include (Essays, UK, 2018)

1. Administrative function - system must be administrable i.e., should support clinical coding, documentation, procedures of medical center.

2. Managing clinical details and complexity - should be able to track patient orders, follow up the status and preventive care of the patient.

3. Cost control - avoid duplication of process and lab tests by documenting them

4. Decision support - provides decision regarding clinical diagnosis and treatment.

There are four basic components in a CDSS, they are
1. Knowledge base
2. Inference engine
3. Communications

1. Knowledge base: It is the brain of CDSS. Clinical knowledge of clinical experts in respective domains is loaded into knowledge base as knowledge articrafts and is stored in machine processable format. This knowledge base is then connected to inference engine to execute decision. With new clinical knowledge these knowledge articrafts should be updated. Knowledge artifact management interface are available to perform tasks such as rule creation, customization, and updating.

Knowledge Base

2. Inference engine: It is used to process the knowledge articrafts, rules and guidelines. This uses the information from terminology service, record service and user input. It establishes whether the CDS conditions are met and based on it determines the outcome appropriately.

Inference engine

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3. Communications: It handles the CDS communications into and out of the system. The final outputs are then delivered to user interface.

Communications

Examples for inputs and outputs of CDSS are:
Inputs: clinical data entry, drug selection, treatment regime etc.
Outputs: alerts, guidelines, treatment refinement etc.

Integrated CDSS/EHR

The above figure clearly explains about the integration of CDSS and EHR. When they both work together in an integrated way, then there will be more quality patient health care ("Decision Support with SNOMED CT").

Based on the framework of organization, decision time during treatment and to whom it is designed for, the CDSS are of various types. The most important and general classification of CDSS is (Sahar S. Alqahtani, 2016)

1. Knowledge based CDSS

2. Non-Knowledge based CDSS

1. Knowledge based CDSS: This is emerged from earlier research. In this the computer program is designed in such a way that it will simulate human thinking during data processing. It contains all the three components of the CDSS i.e., knowledge base, inference engine and communications. It is the most acceptable type of CDSS which improves the quality of health care.

2. Non-Knowledge based CDSS: This is a kind of artificial intelligence. It uses machine learning techniques that learn from the experience by recognizing the pattern. Examples include genetic algorithm, artificial neural network.

There are various challenges which are to be considered during implementation of CDSS. These challenges are low computer skills among physicians, designing alerts, loss of physicians autonomy, installation and maintenance cost etc.,

The success factors in implementing CDSS include Right message with accurate content, easy, actionable and reliable message at Right time which saves time, integrate workflow, increases system speed in Right place with Right system (Anne-Marie J.W, 2011).

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