POST 1 KELLY Utilizing conjoint analysis to explicate health care decision making by emergency department nurses

POST 1

KELLY

Utilizing conjoint analysis to explicate health care decision making by emergency department nurses: a feasibility study.

The goal of this study was to study the feasibility of using clinical simulation to understand proxy decision making by emergency department (ED) nurses for individuals with intellectual disability (ID) (Fishner, Orkin, & Frazer, 2008). The purpose was to enhance the comprehension of the complexities of services and supports that nurses are expected to provide (Fishner, Orkin, & Frazer, 2008). Conjoint analysis was used. Conjoin analysis is a measurement tool that uses simulation coupled with experimental design to mathematical model decision processes at the baseline of the individual decision maker (Fishner, Orkin, & Frazer, 2008). Most of the nurses were women, with an average of 7 years with ED experience (Fishner, Orkin, & Frazer, 2008). The results indicated that the nurses work site, age, education, and years of experience did not discriminate or alter these decision-making patters in the sample (Fishner, Orkin, & Frazer, 2008). The limitations of this study where the simulation only relies on an additive utility model of decision making that may not capture the complexity of a specific decision (Fishner, Orkinn, & Frazer, 2008). The conjoint analysis was a strength as it was proven to be robust. In my nursing practice complexity models and simulation tools have been used. Both tools benefited the selected facilities. The nurses were not sound in making optimal decisions regarding scheduling and patient care. The simulation would and complexity model would assist the nurse of how and when to schedule the patient. 

Development and Pilot Testing of Guidelines to Monitor High-Risk Medications in the

Ambulatory Setting

The goal of this study was to develop guidelines to monitor high-risk medications and to assess the prevalence of lab testing for medications among a multispecialty group practice (Tija et al., 2010). The study design selected was a safety intervention trial (Tija et al., 2010). Guidelines were developed for the laboratory monitoring of high-risk medications as part of a patient safety interventional trial (Tija et al, 2010). The experts selected a 2-round internet-based Delphi process to assist with the guideline medications based on the importance of monitoring for efficacy, safety, and drug to drug interactions (Tija et al., 2010). The results were achieved in 2 rounds. The results concluded that laboratory monitoring is vital, the prevalence of monitoring is highly variable (Tija et al., 2010). The limitations of the study were based off a single group practice. An important finding of the study indicated that patients using infrequently prescribe drugs were less likely to complete a recommended laboratory test (Tija et al., 2010). This tool would contribute to nurse practice. Being able to identify high-risk medications could prevent hospitalization and improve the overall quality of life. 

The statistical method that has been most frequently used are cross-sectional surveys. Additionally, I have discovered that some studies rely on data from a subset of journal and articles that have been previously written. It is my opinion that these methods are used opposed to others as it requires less time to find a conclusion.  Parametric methods are inappropriate to use for statistical analysis as they do not provide or offer accuracy of other statistical models. Nonparametric analysis is best suited when considering the order of something, meaning even if the numerical data changes, the results will likely not change (Grant & James, 2020). 

References:

Fishner, K., Orkin, F., & Frazer, C. (2008). Utilizing conjoining analysis to explicate health care 

            decision making by emergency department nurses: a feasibility study. Applied 

            Nursing Research, 23(1), 30-35. doi:10.1016/j/apnr.2008.03.004

Grant, M., & James, M. (2020). Nonparametric Statistics. Retrieved from: 

            https://investopedica.com/terms/n/nonparametric-statistics.asp

Tija, J., Field, T., Garber, L., Donovan, J., Kanaan, A., Raebel, M.,…Gurwitz, J. (2010).

            Development and pilot-testing of guidelines to monitor high-risk medications in the 

            ambulatory setting. American Journal of Managed Care, 16(7), 489-496. 

POST 2

Jacqueline

Utilizing conjoint analysis to explicate health care decision making by emergency department nurses: a feasibility study. 

        This study aimed to test the feasibility of conjoint analysis in studying the proxy decision-making process among emergency department (ED) nurses and ascertain their experiences with and perceptions of caring for individuals with Intellectual Disabilities ( Fisher et al., 2010). 

             The contingency tables with nonparametric tests (chi-square and Fisher’s exact tests) are used to explain the decision-making patterns associated with the nurses’ characteristics. Fisher’s exact test is a statistical significance test used in the analysis of contingency tables. In practice, it is usually employed when sample sizes are small ( Fisher et al., 2010).

            Alternately, there are Parametric tests such as the Anova test when testing more than two groups to find out if there is a difference between them, and the t-test, another parametric test, is a method that determines whether two populations are statistically different from each other. Hence, the parametric test is notappropriate for this study. 

           This multivariate statistical method -Conjoint analysis is a measurement technique that uses simulation coupled with a rigorous experimental design to mathematically model decision processes at individual decision-making level ( Fisher et al., 2010). Because of this design choice, the analysis is limited to the role of each factor at each factor level in decisions (“main effects”) and specifically cannot explore potential influences (“interactions”) of factors at given factor levels on one another ( Fisher et al., 2010).

             The sample size was insufficient to undertake a meaningful explanation of the observed decision-making patterns consisting of only twenty-three ED nurses. There are many disadvantages to having a small sample in the study; small samples lead to biases and create limited statistical power.

           A noted weakness in this study is that although conjoint analysis appears to be valid, it is not known if the nurses responded as they might have to an actual ED patient or if there would be a difference in their decision-making responses if they were providing care for the patient versus completing a simulation exercise. The conjoint analysis relies on an additive utility model of decision making that may not capture the complexity of a particular decision ( Fisher et al., 2010).

           One notably strength in the use of conjoint analysis in this study allows the researchers to ask questions that mimic real life. With conjoint analysis, the researcher can mimic the decision process of the participant.  As we know, the nurse’s role is ever-changing, with increasing demands on decision-making.

             Results from this study can not only provide information to the healthcare educators on what information the nurses as proxy decision-makers value, but it can also additionally allow the nurse herself to reflect on her thoughts and possible biases regarding decision making for this vulnerable population.

 Development and Pilot Testing of Guidelines to Monitor High-Risk Medications in the Ambulatory Setting 

            The purpose of this study is to develop guidelines to monitor high-risk medications and to assess the prevalence of laboratory testing for these medications among a multispecialty group practice (Tija et al. l, 2010).  

           The study design is a Safety intervention trial which beneficial. This study is conducted in a single multispecialty group practice, a small sample, so it may be more prone to testing biases. An advisory committee of national experts and local leaders used a 2-round Internet-based Delphi process to select guideline medications based on the importance of monitoring for efficacy, safety, and drug-drug interactions. One notable weakness in this method is that when more than 1 test was recommended for a selected medication, monitoring within a medication sometimes differed by greater than 50.0% (Tilia et al., 2010).  Moreover, If a drug was not used as often, it was not recommended for test monitoring- occasional use does not mean the drug is not a high-risk medication, and lastly, all guidelines recommendations were not assessed for this study.  A Nonparametric test is used in this study.

Medication safety is one of the National patient safety goals and monitoring the use of high-risk medications in a fast-paced ambulatory care setting have many difficulties. Although mistakes may or may not be more common with these drugs, the consequences of an error are more devastating to patients (Institute for Safety and Medication Practice [ISMP],2020. Results from this study will not only benefit patient outcomes but will improve overall medicationsafety throughout the system.

It is this researchers’ opinion that the most commonly used statistical method in my nursing practice area is the Analysis of Variance (ANOVA) and independent t-testing. 

Reference:

Fisher, K., Orkin, F., & Frazier, C. (2010). Utilizing conjoint analysis to explicate health care decision making by emergency department nurses: a feasibility study, Applied Nursing   Research,23 (1). pp. 30-35. https://doi.org/10.1016/j.apnr.2008.03.004.

The Institute for Safe Medication Practices; ISMP. (2010).

Tija, J., Field, T., Garber, L., Donovan, J., Kanaan, A., Raebel, M.,…Gurwitz, J. (2010).

            Development and pilot-testing of guidelines to monitor high-risk medications in the

            ambulatory setting. American Journal of Managed Care, 16(7), 489-496.

POST 3

LOLADE

Synthesize your previous experiences with consumer health literacy in your practice setting

            Patients in the modern world are high consumers of online health information. Generally, the majority of patients with psychiatric problems understand their health problems and the available treatment options due to online health information. An example of my experience with online health information is a patient with depression who had come for first clinical visit. The patient had an in-depth understanding of her condition, management, and psychological interventions that could be used to improve the outcomes of treatment. The patient was therefore ready to implement the treatment interventions that were prescribed to manage her symptoms of depression. 

Formulate strategies that you could use to assist patients in interpreting and applying online health information going forward. Include strategies for those patients that overuse medical websites or regularly misinterpret medical information found online

            One of the strategies that I will use to assist patients in interpreting and applying online health information is educating them on the importance of consulting a healthcare professional. The patients should be educated on the fact that not all of the online health information is accurate. In addition, the recommendations in the online health information only apply to patients with specific characteristics and not all patients suffering from a condition (Koutoukidis & Stainton, 2020). Therefore, patients should be educated on the importance of seeking advice from the healthcare providers prior to implementing online health information. The second strategy that I will use to assist the patients that apply online health information is educating them about the reliable websites that provide accurate health-related information. An example would be educating them to use information from websites of organizations such as the World Health Organization and American Medical Association. The information contained in these websites is reliable and safe for use (Linsley & Roll, 2020). I will also provide similar assistance to the patients who overuse medical websites or regularly misinterpret medical information that is found online. 

References

Koutoukidis, G., & Stainton, K. (2020). Tabbner’s Nursing Care: Theory and Practice. Elsevier Health Sciences.

Linsley, P., & Roll, C. (2020). Health Promotion for Nursing Students. SAGE

POST 4

MICHELLE

• Synthesize your previous experiences with consumer health literacy in your practice setting.

Understanding of consumer health literacy in my practice setting of gastroenterology has been both vast and minimal at the same time. Then need for patient education Patient education is so important to the crux of what health literacy truly means. However as described in the work from Misra et al., (2010) if patients cannot understand the education information it is not useful in any way. Gastroenterology has a unique set of issues that have complex terminology that are difficult to educate at the 4th grade level. The recommendations for consumer education has always been suggested to be at a simplified reading level. However when thinking about user interfaces with health information technology one might think that as long as we can present the information in a hand-held device format one might be able to interface with patients more readily as we become more technology driven. Utilizing an education format that avoids technical jargon and complicated communication styles or excessive information that confuses or clutters the education process as described by (Misra et al., 2010). Improving visuals such as the use of color to help communicate through different behavioral interactions such as the use of the color red to show what we do not want someone to do in the color green to show something that is a positive or the correct thing for a patient to do for their health. The use of reproducible education products for consumer health literacy has been a cost-effective means but that makes it very difficult to utilize a copy of a product in color because this has a higher cost per item than a black-and-white copy on a copy machine. My in counters with patient education includes simplified copies that can be written on and given to the patient at the time of their patient visit.  I can go over this education with them and answer questions write on the paper that they will take home with them and allowing for dialogue and then they can take that education information with them for referring back to it as the use it.

• Formulate strategies that you could use to assist patients in interpreting and applying online health information going forward. Include strategies for those patients that overuse medical websites or regularly misinterpret medical information found online.

The consideration of choosing different types of health education information based upon the patient’s age is an interesting concept discussed in the work of (Pak et al., 2009). Helping all patients to find safe and evidence-based data from websites is an incredibly important portion of what it is we do as healthcare providers. When thinking about improving that interface for my patience I have to superimpose this concept of different types of health information being offered to different age groups based upon the fact that some they rather have a computer-assisted education process where others may prefer a handwritten document like I have used in my current practice. As technology improves and technology interfaces income more commonplace y as described in this work prove that younger age groups and younger adults are definitely interfacing with computers at a much higher frequency. The older adults many need another type of education, and considering user interfaces that fit each age group’s preferences may be more realistic to allow the education we are trying to provide (Pak et al., 2009).

The older age populations are certainly on much higher likelihood for utilization of daily medications so the importance of teaching and finding a teaching method and interface that will give them the most amount of information about those medications so that they can monitor for levels of toxicity and/or interference. Identifying with those patients what their preference for health information consumption might be and ensure that you have options so if a patient requests computer-based visuals for that education you have that available to them (Pak et al., 2009).

            This is a common practice I have now but the educating of patients for which medical sites have founded researched and evidence-based answers and helping them to utilize those sites as opposed to just doing a Google search and getting whatever might pay the highest to be at the top of that list.

Misra, R., Mark, J. H., Khan, S., & Kukafka, R. (2010, November 13). Using design principles to foster understanding of complex health concepts in consumer informatics tools. AMIA … Annual Symposium proceedings. AMIA Symposium. https://www.ncbi.nlm.nih.gov/pubmed/21347027. 

Pak, R., Price, M. M., & Thatcher, J. (2009, November 16). Age-sensitive design of online health information: comparative usability study. Journal of medical Internet research. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2802567/.