Barriers to Bar-Code Medication Administration - Research Paper Example

Database PLAN: BARRIERS TO BAR MEDICATION ADMINISTRATION Number: Lecturer: Introduction The systems of medication administration using bar codes were developed with an aim of reducing drug administration errors a long side associated costs as well as to enhance patient safety. This is possible via safe medication administration which is essential to guarantee quality healthcare. The errors or accidental processes can occur as a result of work created by nurses (Barbara, 2012). The rest of this paper is organized in to barriers to medication problems, conceptual data model for the planned database. The entities planned for the database, entity identifiers and relationships and concluding summary in that order. The respective Entity relationship diagram and illustration of relationships are shown at the appendix after references. Barriers to Bar-Code Medication Administration There are various barriers that affect Bar-Code medication Administration (BCMA). First is the lack of system or technology acceptance by users who are nurses in this case. The acceptance of technology is normally a prerequisite for the adoption of technology such as bar code medication implementation. This technology acceptance is based on ease of use as well as usefulness. Another issue is that the implementation of this kind of technology for bar code medication can easily disrupt work routines, thus making it difficult for the administration part of it (Taliercio et al., 2014). Next is the lack of involvement by nurses/users during implementation process. This reduces their chance of understanding how the bar code system works. As a result, they end up having a negative attitude towards it. Failure to understand a new technology and its operations implies high probability of making errors or inefficient usage by the respective users. There is also lack of effective and efficient communication amid those involved. This makes it difficult to analyze the problem of implementation part of bar code technology to be used for medical administration in addition to weaknesses and solutions involved (Taliercio et al., 2014). Lack of thorough analysis or examination or the existing norms, standards and work culture involved can also make the bar code medical administration system to fail in terms of how to administer its operations. Since the introduction, of such technology leads to the change of workflow as mentioned above, failure to redesign the workflow can also result to implementation failure, thus making medical administration hard. Other barriers include lack of good support as a way of making users such as super-user nurses feel comfortable during implementation process. There is also lack of sufficient knowledge about using the system as well as lack of training which is very significant to the adoption process of bar code medical administration system (Taliercio et al., 2014). Some barriers also come as a result medication errors that takes place during prescription, dispensing, prescribing, prescription auditing, transcribing among other processes that are conducted by nurses. These errors can be grouped into medication administration errors and near misses errors. Medication administration errors are those that reach the patient and pose risk to the safety of patient while near misses. Bar code medication administration system can be used to reduce a number of these errors to a given level. Nevertheless, the system of bar codes may at times fail to identify and reduce these errors to the acceptable level depending on the error type and magnitude, contrary to the capability of the system. A good example are the omission errors, wrong patient error, preparation error and dosing time error among others which are the leading type errors that originate from nurses according to past research(Wang et al., 2015). In general, it is thus the problem of equipment such as computers and scanners used those results to these problems. The problem with the equipment is perhaps the way in which they are designed. The equipment may be working but poorly designed in such a way that users cannot comfortably use them without making errors unless they are well traimed or guided. The conceptual data model for the planned data base Conceptual data model will consist of six classes of information namely Patient particulars, drug information, payment information, manpower information, Institution, unit information and treatment information. There is also the summary part of information that contains a combination of selected information from the mentioned six classes. Patient particulars will comprise of Patient Id, Patient Name, Age and gender attributes. The manpower information includes physician, Nurse and other clinical or hospital staff each with its own specific attributes. Each class will exist in form of one or more tables in the database with unique identifier keys. The management of information in all tables within the database will be made easier by relating all the tables using the most suitable type of relationship. The illustration of this conceptual model of the planned database is shown in appendix 1. Entities planned for the database Entities in this case are objects from which medical data are to be created. In other words, they represent names of things to be describes using various attributes within relational tables of the planned database. They include Patient, Nurses, Physician, Hospital unit/department, treatment/medication, payment, staff and drugs. E-R diagram for each entity The entity relationship diagram consists of attributes that describes the associated entity and its relationship cardinality with other entities. The Patient entity will comprise of attributes such as Patient Name, Age, gender and Patient Id will be used in this case. The entity relationship diagram for Nurse will have descriptive attributes such as work Id, Name and their units/ department of work. The drug entity will consists of drug Id, price, drug type and dosage. Hospital unit, labeled as unit comprises of attributes which include number of patients (labeled as NoOfPatients) unit Id and department. Physician attributes include work Id and name while payment consists of amount, receipt number (laled as receiptNo) and pay-Date. Patient will be identified by patient Id, unit by unit Id, drug by drug Id, Nurse and physician by Work Id and staff by staff Id. Payment is identified by receiptNo attribute and treatment by TreatNo. The illustration of these entity relationships diagram (ERD) is as shown in appendix 2. Relationships between entities There are various types of relationship that may exist amid entities in this case. They include one to one (1:1), one-to-many (1: M) / Many to one (M: 1) and many to many relationship (M: M) relationship. In this case Patient and Nurse will be associated through one-to- many relationships, implying that one patient is assigned to two or more nurses. Drug is associated with payment through many-to-one relationship. This means that several types of drugs can be paid for at once through a single payment by the patient. The physician is also related with patient entity on one-to-one basis, implying that one physician attends only to one patient at a time. The same physician is associated with treatment on a one-to-many relationship whereby one physician can record several treatments. There is also a one-to-many relationship between patient and drug where one patient can pay for several types of drug. A one to one relationship signifies that one entity in a relational database of records is related to another one entity in a different table of the same database. One to many, also called many to one relationship is where one entity in one table of a relational database associates with several entities in a different table of the same database. On the other hand, many- to -many relationship involves one entity in say table (A relating to one entity in table (B) while at the same time one entity in table (B) relating to one entity in table (A) within a relational database. Summary and conclusion The barriers with bar code medical administration (BCMA) come as a result of nurses bypassing bar code BCMA due to equipment issues. The main equipment being computer and scanning devices are the problems in that nurses are lacks sufficient know how on how to use the equipment. This also happens because of lack of adequate training for users (nurses). Therefore lack of knowhow becomes the major cause of all these barriers mentioned above to larger extent. The issues of insufficient know how for the use of equipment makes it apparent that it not really the problems with NDC number on the medication is not being correct to result users’ failure in scanning the medication. Therefore, a database model has been created consisting of relevant entities for the purpose of solving the barriers mentioned above. References Barbara Voshall, D. N. P. (2012). Barcode Medication Administration Work-Arounds: A Systematic Review and Implications for Nurse Executives. Diabetes. Taliercio, V., Schachner, B., Borbolla, D., Luna, D., Villalba, E., & Quiros, F. (2014). The expectations of nurses about the implementation of a barcoded medication administration system: a qualitative study. Studies in health technology and informatics, 205, 191. Wang, X., Luo, Y., Shang, M., Li, Z., Zhang, M., & Sun, Z. (2015, January). Application of Mobile Nursing Information System in High-quality Nursing. In International Conference on Education, Management, Commerce and Society (EMCS-15). Atlantis Press. Appendices Appendix1: Conceptual data model Appendix 2: Entity Relationship Diagram (ERD) Read More