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HSYP806 Systems Science In Healthcare

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HSYP806 Systems Science In Healthcare

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HSYP806 Systems Science In Healthcare

0 Download9 Pages / 2,116 Words

Course Code: HSYP806
University: Macquarie University

MyAssignmentHelp.com is not sponsored or endorsed by this college or university

Country: Australia

Question:

What is a case study?
A case study is a description of a real-life problem or situation which requires you to analyse the main issues involved. These issues need to be discussed and related to the academic literature and/or research findings on the topic and conclusions then drawn about why the situation occurred and how best to respond to it.
Why do we write case study responses?
A case study is a way to apply the theoretical knowledge gained from the academic literature to real life situations that you may encounter in your work.
Writing a case study response enables you to

analyse the issues in a real-life situation,
apply the knowledge gained from your academic reading and research and
draw conclusions about how to respond as a professional to that situation.

How to write a case study response
Before you start writing, you need to carefully read the case study and make a note of the main issues and problems involved as well as the main stakeholders (persons or groups of persons who have an interest in the case).
A case study response would include the following elements:
Write a brief description of the case under discussion giving an outline of the main issues involved. Always assume that your reader knows nothing of the assignment task and provide enough information to give a context for your discussion of the issues.
Discuss the issues raised one by one, using information gained from your research of the academic literature. Your discussion may include:

an outline of the issue and its implications for or relationship to different stakeholders
how that issue links to theories or research in the academic literature
suggested solutions or ideas
evaluation of the solutions or ideas for this particular case

Finally, sum up the conclusions that you have come to and give recommendations to resolve the case. Give reasons for your recommendations.

Carefully read the case and noted the main issues and stakeholders in the case?
Written a brief description of the case to give your readers a context for the main issues?
Discussed each issue with reference to the academic literature?
Evaluated the solutions or ideas for each issue to find the ones most suitable?
Made final recommendations of how to resolve the case?
Used a well-structured introduction, body and conclusion?
Cited and referenced all of the work by other people?
Used correct grammar, spelling and punctuation, clear presentation and appropriate reference style?

Answer:

Discussion

Over confidence in Electronic Health Care systems

Most hospitals and offices of physicians have fully adopted Electronic Health Record (EHR) systems, a trend that is steadily growing, and the traditional paper-based record keeping systems have been taken over. Adoption of these systems has redefined the roles of various stakeholders in the health care industry and in some cases invited new stakeholders into the medical scene. For example, software designers in this tech-savvy age are key stakeholders in the health care industry. In fact, technology is as a key driver of the health care services, and with some areas of health care service delivery automated, the health sector would be greatly imprecated without technology. However, managing patients only through the lens of health care smart systems has been the cause of the most grievous mistakes that have been recorded in the medical industry5. When not rightly used, health care decision support systems could be the source of problems in the medical industry.
When practitioners put all their confidence to decision support systems, they forget that the systems are programed rather than trained, and so they are always liable to make errors. Furthermore, decision support systems in the health care setting could be taking away the professionalism from the medical industry, leading to a dry and unbecoming system that is abhorred by patients. For one reason, medical practitioners who are charged with taking care of patients have been forced to use these systems without a proper knowledge on their usage1. Hence, it is thus that in the given case study, Dr. Stanley made a grievous error in diagnosis of Zoya, which transcended to a wrong drug prescription.
 For some practitioners, Electronic Medical Records have become the equivalent of drive-texting in the medical profession, as they spend a lot of time behind computer screens at the expense of attending to the patient personally. In so saying, Electronic Medical Records (EMRs) tend to pull away health care professionals from patients, and the desired personal interaction with the patients is replaced with a thousand clicks of the mouse2. Every health care practitioner well knows that giving the patients an attentive ear is the foundation of proper diagnosis and treatment. Heath practitioners have spent years and years learning to parse the clues they get from patients, only for Electronic Medical Records to suck the professionalism out of them. Overdependence and overconfidence in Electronic Medical Records is the issue here which needs to be addressed1.
To remedy this situation, clinicians and hospital administration should work harmoniously to demand ameliorated products from software designers and implore the government to formulate tolerable laws to govern the use of Electronic Medical Records. Social Network Analyses of complex system3.

Lack of Integration of Health care Decision Support Systems

It is agreeable to everybody that proper health care of patients fundamentally relies on proper coordination between clinicians and the administration of the hospital. This coordination is also necessary for the effective working of electronic medical system in information retrieval and giving of diagnosis reports. Lack of an integrated Electronic Medical Record system to harmonize patient information from various hospitals is a serious shortcoming. Many errors that have been made by practitioners in the medical field could have been avoided had the Electronic Medical Record systems been standardized in Australia. Since one EHR system cannot communicate with another, serious errors are made that would otherwise have been prevented with the integration of all Health Electronic Records (HER) systems in the country5. A key benefit of integrating HER systems would be improvisation of the quality of communication with other health care providers which will lead to enhancement of prescription refilling capacities and improvement of online interfaces to more pharmacists. In so doing, errors in the system would be easily noticed, and failure in one system will be easily captured in another system. The interdependence that will be created in due process will do away with all system redundancies and promote effective patient report processing. Furthermore, decision support would be enhanced with more participants giving additional recommendations for analysis of the patient condition at hand. This will enhance a greater participation of more health care participants into the EHRs interoperable systems as opposed to the standalone EMRs6.

Health Care Systems are not Resilient

Resilience in health care systems is at the foundation of the full recovery of the health systems’ capacity to absorb shocks of mis-handlings and negligence’s in the medical practice. Health care systems often fail in presenting a consistent and seamless continuum to ensure effective patient transitions, which has led to gaps in consistent patient care and thereby threatening the wellbeing of patients. These gaps in the continuity of patient care is an evidence that the current health care systems are practically unable to sufficiently meet the demand of the disturbances they receive. A lack of system resilience in many EMRs and EHRs has seen the medical industry expend financially in unnecessary compensations to families in the case of patient deaths as a result of misdiagnosis or wrong drug prescription4. Therefore, clinicians and the hospital management should demand resilient EMRs and EHRs from the software designers. Resilience is viewed as the ability of health care systems to absorb disturbances and yet remain stable. However, in the medical practice, system resilience incorporates health system reengineering to anticipate absorption of future failures, while taking into consideration the growing complexity in the emergence of new diseases and complications that require agility and intensive responses7.

Poor quality of Data

Issues regarding the quality of data as outputted by EMRs have become relevant in the recent years as adoption of these electronic databases has been ever increasing. Data quality can be viewed as the ‘appropriateness of data,’ that is the fitness of data for use in executing a certain task. When it comes to electronic medical databases, care should be taken in evaluating the appropriateness of a database to a particular situation. For example, some databases perform better in analyzing of patient data as opposed to dispensing clinical information. Negligence in patient care can be reduced by re-evaluating the medical databases that are put in use in medical health centers7.
For data to be described as quality, it should have accurate, relevant, and timely details that are appropriate and fit for each and every situation at hand. It is important to note that an integrated clinical coding system can only be implemented by designing a uniform clinical database. Hence, to solve this issue, maintaining a standard clinical database is the only solution. This is the case because health centers in different hospitals use different disease labelling criteria depending on the setting2. This often poses a problem when a patient transfers to a new hospital and their report conflicts with the hospitals labeling criterion, thereby creating confusion which may end up in creating complications in drug prescription, in case the patient had some reactions to some drugs.
Recommendations  and Conclusion
Negligence in patient care and medication errors can be prevented by implementation of the solutions for the issues already identified. The issues that have been identified in the medical practice, are worthy of attention, for negligences in the medical practice has always been expensive. To enhance the prevention of medication errors and the reactions from adverse drugs, the clinical decision support systems can be optimized in a manner as to make them resilient, not just smart8.
While implementation of decision support systems in the health care system has an evidence of improving patient care, it should not be entirely substituted for personal attendance to patients. There is a tendency to have overconfidence in the decision support systems that always comes with a gross presumption that the EHR and EMR systems can work independently. Most practitioners seldom make use of their professional skills and end up relying on these smart systems for almost the entire process of attending to patients. This issue can be addressed by encouraging an ethical and balanced implementation of the medical decision support systems to encourage professionalism while attending to patients3.
Integration of all electronic medical records will also help in preventing common errors that are often made during diagnosis and drug prescriptions. Integrating electronic medical records and will help in creating a standard database for common diseases and complications that are neglected or labelled differently in different settings9. For example in the case of Zoya, had the EMR systems been integrated, there would have been a system hard stop on the basis of the inference that cephalosporin should not be prescribed to a patient who has a history of an allergic reaction to penicillin. While the standalone system in the hospital may not have captured the error, an integrated information system using a standardized database would have prevented the error through the network2.
To reduce drug prescription errors and misdiagnosis as in the case of Zoya, the decision support system in the hospital, had it been resilient, should have prevented Dr. Stanley from making such a gross error. The electronic record clearly indicated that Zoya had an allergic reaction to cephalexin but the doctor to observe the entry. This warranted the death of the patient, despite of the system’s knowledge of the condition. This is an evidence that the decision support systems in the medical industry need not only be smart, but also resilient.  Above all other industries, the decision support systems in the health care industry should be most optimized for resilience10.
Quality of data that is inputted to or outputted from a decision support system is key in determining safety of the patient. This is true both in hospitals and in pharmacies. For example in the case study, the pharmacist who dispensed the ‘killer drug’ to Zoya, had he/she consulted an EHR system instead of relying on Zoya’s explanation would have saved her life. Furthermore, in the case whereby a hybrid electronic system is used like in the given case study, care should be taken such that patient information is clearly recorded so as to be properly transferred into the system without error9.  Although patient results are confirmed by general practitioners before being entered into the health care system database, it is often the case that the clinical conditions and allergies of the patients are not always updated in a systematic way into the system, which encourages gaps that may lead to negligence as in the case of Zoya7.
In conclusion, it is important to note that a lack of resilience in the decision support systems is the largest contributor of practitioner-related patient deaths. It is worthy to note that the decision support systems in the health care setting can greatly prevent potential diagnosis errors and prescription of adverse drug events. However, these decision support systems can only be effective as they are rightly optimized to be resilient. As in the given case study, Dr. Stanley’s error could have been prevented had the electronic system been re-engineered for resilience6. This is evidenced by the fact that the system failed to come to a hard stop, since the feature was not implemented. Hence, I recommend that all decision support systems in the health care system be re-engineered for resilience optimization.
Reference List

Abul-Husn NS, Manickam K, Jones LK, Wright EA, Hartzel DN, Gonzaga-Jauregui C, O’Dushlaine C, Leader JB, Kirchner HL, D’Andra ML, Barr ML. Genetic identification of familial hypercholesterolemia within a single US health care system. Science. 2016 Dec 23;354(6319):aaf7000.
Betancourt JR, Green AR, Carrillo JE, Owusu Ananeh-Firempong II. Defining cultural competence: a practical framework for addressing racial/ethnic disparities in health and health care. Public health reports. 2016 Nov 15.
Boulware LE, Cooper LA, Ratner LE, LaVeist TA, Powe NR. Race and trust in the health care system. Public health reports. 2016 Nov 15.
Chase MW. The Journal Of Physical and Chemical Reference Data. 2016 Aug 26.
Chambers DA, Feero WG, Khoury MJ. Convergence of implementation science, precision medicine, and the learning health care system: a new model for biomedical research. Jama. 2016 May 10;315(18):1941-2.
Dumais S, Cutrell E, Cadiz JJ, Jancke G, Sarin R, Robbins DC. Stuff I’ve seen: a system for personal information retrieval and re-use. InACM SIGIR Forum 2016 Jan 29 (Vol. 49, No. 2, pp. 28-35). ACM.
Fisher ES, Shortell SM, Savitz LA. Implementation science: a potential catalyst for delivery system reform. Jama. 2016 Jan 26;315(4):339-40.
Frerichs L, Lich KH, Dave G, Corbie-Smith G. Integrating systems science and community-based participatory research to achieve health equity. American Journal of Public Health. 2016 Feb;106(2):215-22.
Makary MA, Daniel M. Medical error—the third leading cause of death in the US. Bmj. 2016 May 3;353:i2139.
Nelson R, Staggers N. Health Informatics-E-Book: An Interprofessional Approach. Elsevier Health Sciences; 2016 Dec 8.

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