Difference between revisions of "Towards Meaningful Medication-Related Clinical Decision Support: Recommendations for an Initial Implementation"

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== Results ==
 
== Results ==
  
Using the Partners Healthcare knowledge base, the panelists were able to recommend a list of 27 starter sets for DDIs and categorized them into three levels. They also identified 16 drug classes for therapeutic duplication with an addition of three pairs of classes that were new and added to the Partners' CDS knowledge base.
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Using the Partners Healthcare [http://en.wikipedia.org/wiki/Partners_HealthCare] knowledge base, the panelists were able to recommend a list of 27 starter sets for DDIs and categorized them into three levels. They also identified 16 drug classes for therapeutic duplication with an addition of three pairs of classes that were new and added to the Partners' CDS knowledge base.
  
 
Final recommendations for DDIs:<ref name ="Medication-Related"></ref>
 
Final recommendations for DDIs:<ref name ="Medication-Related"></ref>

Revision as of 05:28, 8 March 2015

A review of the article titled "Towards Meaningful Medication-Related Clinical Decision Support: Recommendations for an Initial Implementation".[1]


Introduction

One of the main benefits in implementing a Clinical Decision Support) (CDS) system in healthcare organizations is the ability to integrate it with a computerized provider order entry (CPOE) system which can help prevent medication errors that may cause harm to patients and improve quality and efficiency. However, despite the benefits of CDS systems, healthcare organizations are still struggling to adopt and implement CDS systems, especially medication-related ones, because of the time and resources needed to develop and manage the knowledge within the system. The article concentrates on a study that was performed to help collect content and recommendations for the development and implementation of a medication-related decision support system, in which could be used across different systems. The study focuses on two main types of medication-related decision support: drug-drug interaction (DDI) checking and therapeutic duplication[1].

Method

A panel of seven (7) individuals with CDS expertise from different healthcare settings and with a variety of professional backgrounds were asked to come together to develop a list of recommendations on the content and policies related to implementation of medication-related CDS, using the list and categories classes that were employed at Partners Healthcare. The study used a two phase approach to gather information from its panel members, first with an online discussion forum, in which panelists were asked to comment on content related DDI interactions and therapeutic duplication alerts. Second, the panelists were to describe how these two types of decision support were implemented in their own respective organizations. The online discussion was held for 4 months, audio taped and transcribed.

Results

Using the Partners Healthcare [1] knowledge base, the panelists were able to recommend a list of 27 starter sets for DDIs and categorized them into three levels. They also identified 16 drug classes for therapeutic duplication with an addition of three pairs of classes that were new and added to the Partners' CDS knowledge base.

Final recommendations for DDIs:[1]

Level 1 Alerts - Hard stop alerts which physician cannot override.

1. Dextroamhetamine AND MAO Inhibitor

2. Linezolid AND Apraclonidine

3. Isosorbide Dinitrate AND Sildenafil

4. Linezolid AND Levodopa

5. Drotecogin Alfa (Activated) AND Warfarin

6. Tranylcypromine AND Furazolidone

7. Tranylcypromine AND Procarbazine

8. Ramelteon AND Fluvoxamine

9. Ciproflozacine AND Sotalol

Level 2 Alerts - Interruptive but the clinician can continue by providing a reason for ordering two interacting drugs.

1. Cyclobenzaprine AND Tramadol

2. Dofetilide AND Quinidine

3. Droperidol AND Cinoxacin

4. Droperidol AND Norfloxacin

5. Tizanidine AND Sotalol

6. Sibutramine AND Sumatriptan

7. Echothiophate AND Sucinylcholine

8. Indinavari AND Triazolam

9. Carbamazepine and Nevirapine

10. Phenytoin AND Fosamprenavir

Level 3 Alerts - Informational and non-interruptive.

1. Tramadol AND Fluphenazine

2. Tramadol AND Thiothizene

3. Rifampin AND Divalproex Sodium

4. Busalfan AND Itraconazole

5. Tracolimus AND Phenobarbital

6. Cyclosporine AND Foscarnet

7. Cabergoline AND Prochlorperzine

8. Warfarin AND Levothyroxine

Final recommended classes for therapeutic duplication:[1]

1. Angiotension-converting enzyme (ACE) Inhibitors

2. Aniotensin 2 Receptor Blockers (ARB)

3. Benzodiazepines

4. Beta Blockers

5. Calcium Channel Blockers

6. H2 blockers or H2 receptors agonists

7. 3-Hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitors

8. Hypnotics

9. Non-Steroidal anti-inflammatory drugs (NSAIDS) {Including COS-II Inhibitors}

10. Phenothiazine Antipsychotics

11. Proton Pump Inhibitors (PPIs)

12. Selective Serotonin Reuptake Inhibitors (SSRIs)

13. Sucralfates

14. Sulfonylurea Hypoglycemics

15. Tricyclic Antidepressants

16. Anticoagulants

Addition #1: Benzodiapzepine + Hypnotic

Addition #2: ACE Inhibitors + Angiotensin 2 Receptor Blockers

Addition #3: H2Blockers + Proton Pump Inhibitors

Comments

Healthcare organizations should seek CDS commercial vendors to purchase CDS system software to overcome medical knowledge creation. These vendors are more likely to have all the common and minimum and maximum references ranges for dose alerts and drug-allergy cross checking. However, there are those healthcare organizations have their own internal initiatives within their clinical information systems that require customization. The practice of custom CDS rules and alerts can be costly and time intensive, therefore it is not vastly used across acute care facilities but geared towards medical centers. In addition, alert fatigue is another common barrier for healthcare organizations when implementing CDS systems. Strategies to reduce alert fatigue is crucial to ensure CDS knowledge is being used effectively and clinicians are not overriding without considering all the medical information that is provided to them. Clinical Decision Support features with Computerized Physician Order entry can also help in the reduction of non-missed-dose medication errors.[2]

References

  1. The Impact of Computerized Physician Order Entry on Medicaiton Error Prevention.http://www.ncbi.nlm.nih.gov/pmc/articles/PMC61372/