clinical decision support

CHAPTER 3 Clinical Decision Support: 

CHAPTER 3 Clinical Decision Support

Chapter Outline: 

Chapter Outline Key Definition Introduction HIT Standards Types of CDSS Maximizing the Benefit of CDSS Value of CDSS CDSS Unintended Consequences A Call for CDSS Research CDSS Governance Committee The Arden Syntax Standard CDS Governance and Importing MLMs Medical Logic Modules Rules for Rules: Planning and Development of Medical Logic Modules Future Trends References

KEY DEFINITIONS : 

KEY DEFINITIONS

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Alert An urgent notice generated by a computerized clinical decision support system (CDSS). These are usually in the form of a just-in-time, patient-specific message directed to one or more clinicians. It may be a warning regarding a clinician's documented decision Alert Fatigue A state of irritability, exhaustion, or bewilderment triggered in clinicians who have been exposed to too many alerts, or alerts with a perceived history of irrelevance, which cause the user to ignore some or all of the alerts, thereby reducing the safety benefit of the decision support system.

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American National Standards Institute (ANSI) Co-ordinates the development and use of voluntary consensus standards including Health Level Seven’s (HL7) Arden Syntax Standard Arden Syntax Standard An HL7 standard designed to allow clinicians to program medical logic into a clinical rule or guideline. The American Society for Testing and Materials first approved the Arden Syntax as a standard in 1992 (E-1460-92) Ownership was transferred to HL7 and ANSI in 1999 with the approval of version 2.0 of the standard. The encode medical logic into clinical rules known as Medical Logic Modules (MLM)

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Bar Code Medication Administration (BCMA) An inpatient CDSS to assist nurses with the five-rights of medication administration (right patient, right drug, right dose, right route, and right time). Systems provide warning if any of the five-rights are violated and most BCMA systems require the nurses to enter an override reason if he or she chooses to proceed. Promotes right-documentation (some hospitals call this the sixth right of medication administration). Centers for Medicare and Medicaid Services (CMS) The federal healthcare programs for the elderly and ingredient

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Clinical Decision Support (CDS) Refers broadly to providing clinicians or patient with clinical knowledge and patient-related information, intelligently filtered or presented at appropriate times, to enhance patient care. Clinical knowledge of interest could range from simple facts and relationship to best practice for managing patients with specific disease states, new medical knowledge from clinical research, and other types of information.

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Clinical Decision Support System (CDSS) A system (computer or otherwise) intended to provide CDS to clinicians, caregivers, and healthcare consumers. Automated CDSS are usually just-in-time, point-of-care messages in the form of an alert, reminders, recommendation, or informational notification regarding a patient. Automated CDS systems typically include a knowledge base (which contains stored facts and some method of algorithmic logic), an event monitor (to detect date entry or the storage of data from laboratory of other system), and a communication system to the end user (unidirectional or bidirectional)

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Computerized Provider Order Entry (CPOE) Automated portion of a clinical information systems that enables a patient’s care provider to enter an order for medication, clinical laboratories, radiology test, or procedure directly into the computer. The systems then transmits the order to the appropriate department, or individuals, so that it can be carried out. E-iatrogenesis Patient harm caused at least in part by the application of health information technology. Heath Level Seven (HL7) An important standards development organization for health information technology (HIT).

Health Information Technology (HIT): 

Health Information Technology (HIT) Any computer systems designed to automate and/ or enhance a healthcare process or workflow. Can be small apparatus such as an IV infusion pump or a Glucometer , a departmental information system such as a pharmacy or laboratory information system. It can be an institutional information system such as an admissions, discharges, and transfer (ADT) system, which may interface or interoperate with other departmental system. Can be multi-institutional system, such as regional health information organization (RHIO), or even a national health information network (NHIN).

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Information System(IS) Computerized systems for workflow management such as a pharmacy computer system, or an information retrieval system such as a library. A department of HIT or computer professionals . Information Notice May be patient-specific automated rule, such as an MLM , to inform of a change in patient status. This type of information notice may be urgent(e.g., to report a change in renal function) or non-urgent (e.g., to report a hospital admission of a potential study patient) An informational notice may also be product-specific such as poop-up box during order entry to announce a look-alike, sound-alike(LASA) drug.

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Knowledge Base A collection of stored facts, rules, algorithm, heuristics, and models for problem solving. May be organized n a database or even a simple table in which explicit relationship exist. Logical Observation Identifiers Names and Codes (LOINC) A standard to facilitate the exchange of clinical laboratory results. Look-alike, Sound-alike (LASA) A medication safety designation to prevent confusion between drug with similar spelling or pronunciation.

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Medical Logic Module (MLM) A rule for an Arden Syntax based clinical rules engine HL7 defines a MLM as an encoded clinical rule that contains enough logic to make a single clinical decision. MLMs in use today have been developed for many purposes, such as Clinical alerts, recommendation, reminders, informational notices, interpretation, diagnosis, quality assurance functions, continuous quality improvement, bio-surveillance, administrative support, and for clinical research. National Council for Prescription Drug Program(NCPDP) Script Is a standard for ambulatory prescription messaging between pharmacies and third party payers.

Protected Health Information(PHI): 

Protected Health Information(PHI) This information about a person that must remain secure, as defined by Health Insurance Portability and Accountability Act (HIPAA) .

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Recommendation An automated rule, such as an MLM , that suggests a course of action. All recommendations are evidence-based and institutionally approved. Reminders An automated rule, such as an MLM , that suggest the clinician has overlooked or forgotten to perform an action such as documenting a decision, event, or finding.

Regional Health Information Organization(RHIO): 

Regional Health Information Organization(RHIO) Proposed definition by the Department of Health and Human Service, BearingPoint and the National Alliance for Health Information and technology. A governance entity comprising separate and independent healthcare-related organization that have come together to improve the quality, safety, and efficiency of healthcare communities in which it operates and for which it take responsibility to developed transparent, inclusive processes that enables the interoperable exchange of health information in a manner that protects the confidentially and security of an individual’s information.

Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT): 

Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) A comprehensive clinical terminology, originally created by the College of American Pathologists.

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CLINICAL DECISION SUPPORT SYSTEM it is an interactive decision support system software which is designed to assist physicians with decision making tasks, as determining diagnosis of patient data. it links observation with health knowledge to influence health choices by clinicians for improving health care.

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HIT Standard Most pharmacist are not well versed in healthcare information technology(HIT). Standard in general are important to help society function. One of the current federal efforts of the Department of Health and Human Services is to determine which standard should be required for HIT application. Types of Clinical Decision Support System The open clinical website ( http://www.open-clinical.org/dss.html ) defines clinical decision support system as “ active knowledge systems which use two or ore item of patient data to generate case-specific advice…are typically designed to integrate a medical knowledge base, patient data and an inference engine to generate case specific advice.” CDS system was divided into major categories:

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Patient-specific CDSS Commercial drug-interaction alerting system. These are most common in CPOE and pharmacy information systems and provide alert for drug-allergy, drug-drug, drug-pregnancy, and other interaction. These outcome are true positive, true negative, false positive, and false negative for each drug-interaction check. Modern CDSS allow pharmacy managers to deactivate selected drug-interactions deemed a “nuisance”. Allow deactivation by individual drug-interaction or an entire group based on. Managers filter out the lower severity alerts to reduce alert fatigue. Practice has the potential to increase risk of patient harm by increasing the number of false negative.

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One limitation of current drug-interaction CDSS design in that severity levels Pre-assigned by the vendor based on the anticipated adverse reaction and cannot be customized based on an individual patient’s prescribed dose, age, body size, race, gender or clinical situation. New CDSS architecture for drug-interactions requires the implementation of comprehensive Electronic Health Record (EHR ) with codified patient conditions and diagnoses using standard terminology such as the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). Two knowledge based that are possible today, but are still missing from these commercial system, involve checking for interaction with drug-laboratory test and drug-disease interaction. Drug-laboratory interactions alerting systems require the use of a standard laboratory coding system such as the Logical

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Observation Identifiers Names and Codes(LOINC). For drug-disease interaction checking, it necessary that the patient’s problem list and diagnoses use standard terminology such as SNOMED CT. 2. Commercial dose and dose-range checking alerts. Rudimentary using few patient data, usually only age. Therefore, these systems only loosely fit the patient-specific category. 3. Commercial clinical rules engine. these allow local development of customization of clinical content (a knowledge base) and programming logic. Medical Logic Modules (MLMs) developed using a rule builder application utilizing the Arden Syntax standard. MLM classes include alerts, reminders, recommendation, and informational notification about a patient. Non-Arden type rules engine. These generally are more difficult to work with and have limited logic relative to the sophistication of the Arden Syntax.

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Artificial Neural Network (ANN)> These are experimental systems that simulates human respoding from examples II. Non Patient-Specific CDSS Require a clinician to adapt general specific relationships and information Data mining Provides population specific relationships and informations. Information Notice Usually just-in-time, product-specific information. Orders An organized set of patient care orders that are usually population, produce-based such as clinical guideline.

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4. Knowledge retrieval Systems (KRS) Primary Literature Retrieval System- such as Google and PubMed return original articles and expert literature reviews. Secondary KRS- are online books or collections of online books Tertiary KRS- such as online drug and therapy information are knowledge bases available from several vendors such as ASHP, Lexi -Comp, Thomson Healthcare, and Wolters Kluwer Health.

Four Possible Results from an Alerting System: 

Four Possible Results from an Alerting System True Positive True positive produce an alert. Alert is relevant to the clinical situation and there is a risk of harm. Clinician needs to see this alert False Positive False Negative produce an alert There is no check for relevance to the clinical situation and no risk of harm. Clinician considers this alert an inconvenience Clinician does not need to see this alert True Negative True negative produces no alert. There is no problem for the clinician to deal with Clinician do not need to see an alert False Negative False negative is really true positive, but produces no alert The alert would be relevant to the clinical situation and there is a risk of harm Frequently caused by blocking low severity alerts so they do not display. Clinicians need to see these alerts, but never gets the chance.

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Maximizing the Benefit of CDSS The value of CDSS lies in its ability to bring together evidence-based best practice information with patient-specific data in order to support clinical decisions. Otherwise is to risk affecting patient outcomes, as clinical decisions are made with outdated information. Vital that the data be current evidence-based knowledge based. Commercial knowledge base is being utilized, the vendor should supply regular updates to the information, and these updates must be installed locally as soon as they become available.

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Value of CDSS the impact of CDS can most easily be described in terms of the various technologies into which it has been incorporated. This discussion will focus on the application of CDSS to medication prescribing, dispensing, administration, and monitoring. CPOE CPOE-based CDSS have the ability to screen for a variety of potential risks at the time of order entry. More passive method are available. B. Electronic Medication Administration Record( eMar ) CDSS may be incorporated into the eMAr to screen for recent changes in laboratory parameters, vital sings, or allergy status, which may interact with a scheduled medication and alert the nurse prior to administration. An eMar based CDSS can only be effective when associated with an up-to-date and comprehensive knowledge base to serve as a source of potential drug-lab value and allergen interaction.

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CDSS can provide a real-time confirmation of the “five rights” of medication administration Right Medication Right Route Right Dose Right Patient Right Time C. Medication Administration Record(MAR) A printed eMAR is simply a snapshot of the patient’s orders as of the moment it was printed. D. Smart Pumps These system can provide a real-time confirmation of the volume, rate and concentration of the solution, or provide alerts when concentration or rate fall outside of establishes safe ranges E. Automated Distribution Cabinets In addition to providing security and documentation of

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controlled substance access. Can also provide alerts when medication is withdrawn too early or too late based on scheduled administration time. Also it present a another opportunity to provide links to additional drug information references. Future systems should also include the ability to display an image of the medication being withdrawn for visual confirmation that the correct product has been dispensed. CDSS Unintended Consequences Alert-tendency for users to become overwhelmed and begin to ignore clinical decision support messages due to a high quantity of alerts or a perception that the alerts have little perceived value. Delay in Care- the risk that interruptions in the workflow caused by clinical decision support alerts or system limitation may lead to a delay in delivery of patient care. System Performance- the risk processor resources used by the

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CDSS will cause the hospital information system software to perform slowly. A Call for CDSS Research The goals of automated CDSS are to enhance quality of care and outcomes, reduce cost of care, increase reimbursement, optimize regulatory compliance, align practice with national quality initiatives, and reduce risk and liability (both individual and institutional). Osheroff et al. describes statistical methods to analyze some aspects of CDSS unintended consequences and CDSS effectiveness. Home grown or extensively customized CDSS are resource-intensive, both for initial implementation and ongoing maintenance. High quality CDS and CDSS research is required to find the best CDS methods to assist the institution.

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CDSS Governance Committee This may be a new committee for most institutions and should be comprised of CDS stakeholders and champions. It may be piggybacked onto an existing CPOE governance committee, or vice versa. Its purpose should be reasonably analogous across institution. That is, To ensure safe Efficient To manage expectations To handle clinical and satisfaction issues arising from CDSS use Otherwise cultivate communication with administration and end-user. Organization American medical informatics association Healthcare information management’s system society.

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Governance of CDSS: An opportunity for Pharmacy Pharmacotherapy CDSS resided within the pharmacy, and a pharmacy manager or management committees informally made decision regarding CDSS functionality of pharmacy computer system. Modern pharmacy information systems are providing increasing control and flexibility for CDS functions. Some pharmacy systems have facilities for building rules to alert of changes in patient condition. Alert fatigue is the major cause of pharmacist frustration and serious impediment to quality pharmaceutical care. Contributing factor to this ADE problem is the lack of a standardized coding systems for allergies and drug interaction that would allow this information to move between HIT systems. Standard recommended by the IOM, the following are of particular importance to pharmacotherapy and associated CDSS

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NCPDP script for prescription data HL7 for clinical date messaging, which includes the RxNorm data standard for clinical drug and their components LOINC for laboratory test results SNOMED CT for standard clinical terminology and system nomenclature. Adoption of the recommendation data standard would greatly enhance sharing of information between systems, private-sector investment in HIT. Possible rule for this committee is to recognize and distribute alerts those best suited to make the final decision on them. Structural and Leadership of the CDS Governance Committee Dependent on local resources, needs, politics, etc. It is important that pharmacy leadership ensure that it is well represented on this committee.

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There are two reason for this: Medication are a well-known source of medical errors CDSS for some other important error prone domains like diagnosis have proven to be much harder to successfully implement. Function of the CDS Governance Committee CDS governance for CDSS selection/development, implementation deployment, and maintenance has several strategic and associated tactical components that vary by application and by the vendors. Possible Activities of a CDS Governance Committee: Evaluate institutional CDSS needs. This might include: Research and analyzes healthcare-related errors. Create an annual CDSS report to hospital Administration Develop and monitor quality improvement plans for institutional CDSS

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d. Monitor and evaluate quality improvement plans for institutional CDSS e. Consider use of medical logic modules to cover gaps. 2. Evaluate Clinical and CDS issues specific to each HIT system. This might include: Decisions regarding drug-drug interaction severity level for CPOE and the pharmacy information system. CPOE order sets with imbedded CDS Bar code medication administration with CDS reminders point-of-care documentation systems. 3. Monitor markets availability and function of commercial, state of the art CDS. 4. Stay abreast of CDS national trends, evolving Hit standard and medico-legal issue.

How to Stay Informed on HIT Issues: 

How to Stay Informed on HIT Issues Access Point Professional organization Email list service Academic courses Active participation in standards organizations Opportunity ASHP’s Section on Pharmacy Informatics and Technology has a taskforce on standard and regulations that monitors evolving HIT standards and regulation. ASHP, AMIA, HIMSS, and other professional organization provide email list service to their member focusing on HIT issues. AMIA 10x10 Program introduces biomedical informatics in a 12-week online course. Always looking for healthcare professionals to bring new perspectives to their organization.

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5. Participate in recommending human and technical resource requirement for CDSS implementation Development of evidence-based content Testing Maintenance Monitoring various aspects of CDSS 6. Establish policies and standards for medical logic module that encompass risk/benefit analysis, including the risk/benefit of doing nothing Development and customization of MLMs Message development-clinical content, medico-legal, and template formats. Notification and escalation of notification: Notification policy and order of escalation for each MLM Mode of notification

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e. audits, audit files, and quality improvement processes f. Deployment schedules for new MLMs g. Maintenance schedules for existing MLMs h. Documentation standards for the MLM itself and for the evidence that supports it. Legal Concerns CDS governance committee should follow is the initiatives currently under way to harmonize state and federal laws and regulations. The CDS governance committee should vigorously reinforce the notion that the clinicians with their quality and safety effort and are not intended to replace clinical judgment.

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The Arden Syntax Is a programming language designed for clinicians to build clinical rules. It a streamlined computer programming language based on Pascal (a computer language designed to teach students good programming style). The arden syntax is still officially approved standard clinicians to encode medical knowledge into clinical rules. The important of this standard is that clinical rules developers can move from system to system with relative ease, and clinical rules themselves can be shared with other Arden Syntax-based system. Provide a method to construct clinical rules. Provides a flexible and clinically sophisticated way to develop MLMs.

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The following are some key features of the Arden Syntax that might be of interest to pharmacy managers: HL7 intends MLMs to be sharable between institutions. The Arden Syntax has many built-in convenience that simplify programming and lessen burden of development and maintenance clinical logic frequently involves temporal reasoning The clinicians developer can focus more time on the medical logic and algorithms The Arden Syntax standard promotes extensive documentation of MLMs The Arden Syntax structure provides the following features: Free text purpose Free text explanation Free text citations The comment features

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Example of Documenting an MLM with Comment Statement The syntax for a comment is “/*…*/ and for this example is highlighted in bolded text for clarity. Comments provides a way to explain in plain words a portion of the MLM. In this case, it mentions a reference that is listed in the “citation” section of the MLM /* Blood volume calculation equation based on the work of Feldschuh & Enson, 1997 */ Deviation:= ((weight-LBW)/LBW)* 100; /* deviation from LBW as % */ if deviation is presented and deviation is number then If deviation <-6 then cBV :=-0.7886* Deviation +67.684; Elseif Deviation < 19 then cBV := 69. 881 * exp(-o.oo72* deviation); Elseif deviation < 118 then cBV := 98.031 * Deviation ** (-0.1557; Elseif deviation >=118 then cBV := 98.362* deviation ** (-0.1596 Endif: cBv :=cBV* weight/ 1000; /* Blood volume in Liters */ Endif;

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CDS Governance and Importing MLM Editing Imported Rules Determine what modification are necessary for safe and effective use at your institution. Typical modification include: Maintenance and library sections. Should be a high priority of the CDS governance committee. These two sections contains a pt of important information. In the maintenance section The local persons or committees who will assumes responsibility for the MLM clinical content, customization, and maintenance are identified. For the library section Contains the medical evidence base supporting the clinical need for the MLM Reviewing the clinical content and establishing usage criteria Updating query statement that link MLM to institutions data. Editing the alert notification and messages to reflect local style and delivery methods.

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Medical Logic Modules MLMs may be either clinical or nonclinical. Nonclinical MLMs do not send message clinicians engaged in patient care. The CDS governance committee ensures proper selection, development, deployment and maintenance of clinical MLMs. In selecting which MLMs to deploy, the CDS governance committee will balance factors such s clinical need, financial consider-action, potential for e-iatrogenesis, security of PHI, validity of evidence-based content, compliance with internal design standards; and perceived ease of implementation and maintenance.

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Rules for Rules: Planning and Development of Medical Logic Modules for in house development, the CDS governance committee leadership should be aware of certain MLM development principles that will be useful to clinicians aspiring to become MLM developers. The following is a brief, high-level introduction to two of these principles, and other information that might help cultivate the body of knowledge needed for in-house MLM development. The initial steps to MLM development have nothing to do with the computers or programming, but rather gaining an understanding of the problem to be solved. MLM developers and expert clinicians must take the time to understand the clinical problems and to anticipate the untoward consequences that even a well-designed MLM might introduce, including the issues with clinical problem.

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2. The 80:20 heuristic of MLM development. Approximately 80% of the program logic will be dedicated to “error trapping”, and only about 20% of the code is to solve the clinical problem. There re two places for error trapping, these are validation of 1. patient data, and 2. validation of calculated results within the MLM. In this case of patient data such as a serum potassium result: first make sure it actually exist, is the appropriate data type, and is within the expected range. The second form of error trapping is for validating calculated results.

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Body of knowledge for MLM Developers The Arden Syntax website, http://cslxinfmtcs.csms.edu/hi7/arden/ , has a basic tutorial that is well worth studying. Provides valuable insight into features, and has a number of programming examples. The Arden Syntax is useful and informative. Those interested in MLM development should train under the guidance of an experienced MLM developer. The bottom line for managers who see the value of locally customized medical logic modules is to invest in at least one clinician from each of the following department: pharmacy, nursing, IS, and perhaps medicine to build a cadre knowledgeable MLM developers.

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Future Trends if we assume inpatient and ambulatory electronic health record(EHRs) then interoperability will be possible. ambulatory and inpatient EHRs, standardized medicinal terminology, and interoperability. Over the last decade, there has been an increase in the political will to proceed with this vision of interoperable EHRs and all of the potential benefits.

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Conclusion Clinical Decision Support System (CDSS) is an important factor in the world of healthcare because it helps the physicians and other health professionals(pharmacist) at the point of care in decision-making and selecting the safest and most effective therapies for their patient. CDSS is their tool to determine diagnosis and analysis of patient data which improve the health and life of patient.

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Reference Osheroff JA, Pifer EA, Teich JM, et al. improving Outcomes with Clinical Decision Support: An implementer’s Guide. Chicagao, IL: HIMSS; 2005. Berner ES, ed. Clinical decision Support Systems: theory and Practice. Health Informatics Series. 2 nd ed. New York: Springer Science+Business Media, LLC; 2007. Weiner JP,Kfuri T, Chan K, et al. e-Iatrogenesis: The most critical unintended consequences of CPOE and other HIT. Am Med Inform Assoc. 2007;14:38-388 Shortliffe EH, Cinimo JJ, eds. Biomedical Informatics: Computer Application in Health Care and Biomedicine. 3 rd ed. New York: Springer Science+Business Media, LLC; 2006 Wyatt J, Spiegelhalter D. Field trials of medical decision-aids: potential problems and solutions. Proc Annu Symp Comput Appl Med Care. 1991;3-7 Wright L, Grisso AG, Feldott GC, et al. Using computerized provider order entry to implement action of the pharmacy and therapeutics committee. Hosp Pharm.2007;42(8):763-766 Kawamoto K, Houlihan CA, Balas EA, Lobach Df. Improving clinical practice using clinical.

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