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Micromedex Solutions

MicromedexSolutions

Abstract

Adecision support system (DSS) uses stored data to provide guidance oninformed evidence based decisions. Inherently, is a suitable DSS due to the fact that it employs a computer databasecontaining vast data about drugs, toxicology, and diagnoses amongother things this makes it important for guiding decisions regardingthe diagnosis and treatment of illnesses. Effectively, the targetusers for Micromedex are the doctors and nurses however, they willwork in collaboration with the management to ensure a successfulimplementation of the DSS. This paper presents the implementationand evaluation plans for using as a DSS forimproving the quality of patient care in the organization.

MicromedexSolutions

Adecision support system (DSS) is an interactive computer system thatcombines various raw data, personal knowledge, documents, and evenbusiness models in order to help decision makers take the rightcourse of action the DSS works through a set of related computerprograms that operate in concert to facilitate analysis and decisionmaking. Inherently, a DSS can take the form of a database, text, orspreadsheet in addition, decision support systems range from simpleapplications to complex systems that use artificial intelligence(Bennet, 2011). In health care, a clinical decision support system(CDSS) provides clinical information, usually at the point of care,to help practitioners make informed decisions about a patient’scare. Inherently, there are two types of CDSSs those that use aknowledge base and the ones that do not (Kesselheim et al., 2011). Inessence, the former work by applying a set of rules to patient data,usually through the help of an inference engine and displaying theresults to the end user. Contrarily, the latter rely purely onmachine learning to analyze data in clinical settings (Kortteisto etal., 2012). is an evidence based online databaseoffered by Tavern Health Analytics it provides information abouttoxicity, drugs, alternative medicine, and acute care in order toallow health care practitioners to make the most informed decisionsin the diagnosis and treatment of various illnesses (Anooj, 2012).Correspondingly, is a suitable decision supportsystem that health practitioners in any part of the world can use inorder to make informed diagnoses and provide the most appropriatetreatment to patients.

ImplementationApproach

Asmentioned earlier, the DSS of choice in this case is MicromedexSolutions. In inherently, Micromedex is intended to increase theefficiency of clinical diagnosis and treatment at the clinicalfacility, which are often slowed down and complicated by largepatient numbers. In addition, the DSS is intended to reduce thenumber of misdiagnoses that occur within a hospital setting. In thefield of medicine, there exist various diseases, which manifestthemselves through similar symptoms correspondingly, this increasesthe probability of diagnosing an illness wrongly. This in turnincreases the probability of prescribing the wrong drugs to thepatient and this could have detrimental side effects such asdiarrhea, nausea, or death.

Notably,Micromedex is a type of CDSS that uses a knowledge base to guide caregivers and physicians on the best clinical decisions. Particularly,Micromedex employs a computer database that contains in-linereferenced records of drugs, diseases, toxicology, alternativemedicine, and acute treatment (Afifi et al., 2013). Inherently, thesystem matches multiple symptoms provided by the user andcross-references them with its data in order to determine the diseaseand the drugs that can be most suitable for treating it, helpingpractitioners to make the most informed decisions regarding theirpatients’ treatment. It can be accessed to an informationtechnology (IT) platform that is available on the internet,particularly through the Micromedex website.

RegardingDSS type, the system of choice is a combination of data-driven,knowledge-driven, and model-driven DSSs. Inherently, Micromedex isdata-driven due to the fact that it relies on individual patientinformation in order to make the correct diagnosis and recommend themost suitable treatment (Power, 2008). At the same time, the new DSSwill take into account various nursing models, such as the hierarchyof needs model, in order help the users to make the most informeddecisions in regard to improving patients’ quality of care. Lastly,Micromedex is knowledge-driven due to the fact that it allows usersto customize their experience using new patient information, as wellas their desired treatment models.

Theselection of DSS vendor and type will be guided by online userreviews this is bound to determine the DSS package that most usersare satisfied with. In addition, looking for information about theDSS on the internet is bound to help the users determine the mostsuitable means of accessing the database. Notably, payment forMicromedex can be done via subscribing to the DSS on the Micromedexcompany website this is powered by Truven Health Analytics.

Inherently,the hospital’s management will be in charge of paying for the mostdesirable Micromedex Solution package subscriptions differ on thebasis that the more access a buyer wants, the more they must pay forit. Effectively, the hospital’s IT specialists will be in charge ofmanaging the DSS for the facility. In addition, the hospital’sadministration will facilitate implementation by training nurses anddoctors, who constitute the users, on how best to use the Micromedexplatform to determine the most appropriate diagnoses and treatmentfor patients.

ImplementationGoals

Fundamentally,Micromedex possesses several characteristics that make it a suitableDSS. First, the system is computerized which makes it a quick methodof making evidence-based decisions. Besides, its technological naturemakes it capable of storing large amounts of clinical data, leadingto more informed clinical decisions. Another important characteristicof the Micromedex DSS is that it is real-time which makes itpossible to incorporate the system into a normal clinical workflow,further making it effective at ensuring care focus, pharmaceuticalinterventions, and the prevention of infections. Moreover, thereal-time nature of the system allows doctors to quickly identifyat-risk patients and candidates for clinical intervention, as well asprovide patient-centered decision assistance during the point ofcare. Micromedex also uses a single, consistent technology, whichsimplifies data deposition and referencing, as well as the provisionof support in clinical decisions. Furthermore, the DSS is offeredthrough a digital IT platform, making it remotely accessible through24 hours every day from both mobile and desktop devices. Also worthnoting is that the data in Micromedex is automatically integrated inan independent database, protecting it from the detrimental effectsof electronic health record (HER) downtime this further guaranteesthat its constant availability.

Inprinciple, the Micromedex is a suitable DSS due to the fact that itfacilitates the improvement of patient outcomes with more targetedtherapies, can reduce healthcare related infections, as well asreduce the prevalence of adverse drug events. Additionally,Micromedex is capable of costs of treatment and outcomes via highrates of IV to PO conversions. Moreover, the system is simple andinformative enough to allow core measure and the compliance ofclinical quality. Furthermore, the DSS employs complex programminginstructions to facilitate regulatory compliance in a timely mannerwhile maintaining a user-friendly interface. In such a manner, thegoals of using Micromedex as a DSS involve accomplishing all theaforementioned functions in the clinical setting.

Inorder to ensure the connectivity and integration of Micromedex toother enterprise systems, the new DSS will be linked with keyorganizational processes such as outpatient services. Inherently,integrating the new DSS into the clinical workflow will make itrelevant to other operational processes within the organization.

Inprospect, data management will be an easy process since Micromedex iscomputerized and employs databases to store data, retrieve it, andmake relevant relationships between various data sets, in order todetermine the most appropriate clinical decision at a particularpoint of care. Model management will also be computerized afterMicromedex is customized using the parameter of the relevant clinicalmodel, it will use it in the evaluation of all clinical data hence,model management will be automated. Correspondingly, Micromedex has auser-friendly database that uses a series of forms to collectinformation from the user and match it through the database toprovide evidence-based guidance on decision making. Moreover, thesystem contains knowledge-management subsystems that allow the entryof new patient information in order to customize the system to thespecific needs of the patient.

ImplementationPlan

Essentially,the first task of implementing the DSS will involve studying allexisting process in the hospital and determine the ones that need tobe redesigned in order allow successful system integration, as wellas improve the quality of patient care. Fundamentally, a gooddecision support system must consider both the existing and newprocesses that will be affected by the proposed system (Kesselheim etal., 2011). Correspondingly, interviewing, observation, and the useof historical records will be used to determine the process that needto be changed or modified to improve the quality of care. The endusers, in this case the doctors and nurses, can be interviewed inorder to establish the processes, which, when integrated into the newDSS, will make their work easier.

Afterdiagnosing and describing the current decision making processes, anorm for how decisions should be made will be developed this will bedone with a consideration that there can be no limitations to theprocesses. The next step will entail determining the type of systemthat will be employed after that, a visualization of the desirablechanges will be made to the target processes with respect to the typeof DSS that is deemed most suitable. Finally, the clinical processeswill be redesigned to include the new DSS (Micromedex), and this willconclude the implementation plan.

Severalfactors will be required to guarantee the successful implementationof the DSS these are technology, user behavior, and issue resolutionduring implementation. First, any facility intending to use a DSSmust possess up-to-date technology to host the DSS. For instance,computers, as well as a private or public network are needed toensure all authorized users access the DSS. Once purchased, the DSScan be installed in the main hospital server from where users canaccess the Micromedex database using the appropriateauthentication/login details. Secondly, the efficiency of the DSSrelies on how well the members of staff use it to for decisionsupport. In such a manner, it is vital to train all medicalpractitioners on the proper use of the DSS to improve both thediagnosis of diseases and treatment outcomes. As with theimplementation of any digital program, it is wise to expect technicalissues during system integration. This is especially important inthis case due to the fact that Micromedex is integrated into aclinical facility’s normal workflow this differs betweenorganizations, hence there is a need for tweaking or configuration ofthe system to customize it to the needs of the target institution.Failure to conduct such adjustments prevents the system fromachieving optimal efficiency in such a way, issue resolution duringimplementation is essential for a successful setup of the DSS.

Notably,implementing the DSS will be a collaborative effort, since themanagement needs to work closely with the users to ensure they useMicromedex appropriately. To guarantee collaboration, frequentmeetings will be held between the management and prospective DSSusers (nurses and doctors). The purpose of the meetings will befostering cooperation between the parties in order to ensure thatthey all help each other where necessary to improve the efficiency ofthe new DSS. In addition, communication between the management andusers will be improved using emails and internal memos in which themanagement will provide guidance on how its staff can best utilizeMicromedex. Lastly, group decision support systems will be used togather the opinions of the clinical faculty on how best to implementthe new system. A suitable group decision support system is thecompany website forum, which presents a platform on which theorganization’s stakeholders can discuss various issues affectingtheir practice.

Evaluation:Approach, Goals, and Plan

Notably,DSS evaluation is essential in order to assess whether the user’sneeds are properly met, the system is capable of handling essentialtasks, and the users achieve improved results with the new system.Moreover, system evaluation allows scholars to gain insight that canbe used to improve the system in the future. The cost/benefitanalysis is the most common evaluation method for most DSSsnevertheless, this method is not very effective for qualitativemeasurements. In this case, the main purpose of the DSS was toimprove the quality of patient care though optimizing the processesof diagnosis and treatment. In such a manner, a value analysis andmulti-attribute utility value approach will be used to evaluate theefficiency of the Micromedex system implementation. Another goal ofthe evaluation is determining defective processes in the system inorder to improve them and lead to the optimization of the quality ofcare guaranteed by the new system.

Fundamentally,the value analysis assesses a DSS as a research and developmentventure, instead of a capital generating one (Lauriks et al., 2014).It will be executed by first creating an operational list of therequired benefits, such as improving the quality of care, followed bythe determination of the maximum costs of the identified benefits.The resulting information will then be used to develop a prototypeDSS that determines the benefits and costs of Micromedex, but withmore focus on the benefits. Contrarily, the multi-attribute utilityvalue approach will entail evaluating the final perceptions of theend users (doctors and nurses) regarding the overall value of theDSS. Essentially, the feedback of the users is crucial forunderstanding whether the system was successful or not. Notably, thisfeedback can be obtained by interviewing the management and usersabout how the system has helped in their clinical activities.Correspondingly, the feedback will be used to modify theorganizational processes that employ the Micromedex DSS in order tomake it more effective and satisfactory to the management and endusers.

Conclusively,Micromedex is a suitable decision support system for any health carefacility. It provides a database of various drugs, toxicology,diagnoses, and therapies among other things in order to provide userswith evidence-based guidance regarding the diagnosis and treatment ofvarious diseases. Essentially, Micromedex is accessed throughsubscription and can be used remotely from an internet-enableddesktop or mobile device. In such a manner, it serves as acommendable decision support system for improving the quality of carein any health care facility.

References

Afifi,A. A., Rice, T. H., Andersen, R. M., Rosenstock, L., &amp Kominski,G. F. (2013).&nbspChangingthe U.S. health care system: Key issues in health services policy andmanagement.San Francisco, Calif: Jossey-Bass.

Anooj,P. K. (2012). Clinical decision support system: Risk level predictionof heart disease using weighted fuzzy rules.&nbspJournalof King Saud University-Computer and Information Sciences,&nbsp24(1),27-40.

Bennett,C. C. (2011). Clinical productivity system – A decision supportmodel. InternationalJournal of Productivity and Performance Management,&nbsp60(3),311-319.

Kesselheim,A. S., Cresswell, K., Phansalkar, S., Bates, D. W., &amp Sheikh, A.(2011). Clinical decision support systems could be modified to reduce`alert fatigue` while still minimizing the risk of litigation.&nbspHealthAffairs,&nbsp30(12),2310-2317.

Kortteisto,T., Komulainen, J., Mäkelä, M., Kunnamo, I., &amp Kaila, M.(2012). Clinical decision support must be useful, functional is notenough: A qualitative study of computer-based clinical decisionsupport in primary care.&nbspBMCHealth Services Research,&nbsp12,349.

Lauriks,S., de Wit, M. A., , S., Buster, M. C., A., Fassaert, T. J., . . .Klazinga, N. S. (2014). The use of the Dutch self-sufficiency matrix(SSM-D) to inform allocation decisions to public mental health carefor homeless people.&nbspCommunityMental Health Journal,&nbsp50(7),870-878.

Power,D. J. (2008). Decision support systems: A historical overview.In&nbspHandbookon Decision Support Systems 1&nbsp(pp.121-140). Springer Berlin Heidelberg.