Critical Appraisal Of Research Article Using CASP Tool

Randomization and Sample Size

Discuss About The Critical Appraisal Article Using CASP Tool.

Randomisation refers to the process of randomly allocating individuals or sample for a particular research activity or across particular intervention or treatment groups (Hróbjartsson et al. 2014). The study design was a pragmatic one that was based on a randomized controlled trial, with the aim of evaluating the effects of nurse practitioner service. The patients who presented symptoms related to pain were randomly assigned in the research study in two different groups namely, standard ED medical care and NP care. Randomisation of 260 patients resulted in allotment of 128 patients to the standard care group, and 130 to the NP care group. Use of a computer random number generator facilitated the process of random sampling and helped in removing selection bias between the two different patient groups.

Concealed allocation encompasses the procedure that is often implemented in randomized controlled trials, which involves blinding of individuals who screen and separate the candidates into two or more groups (Pocock 2013). The primary investigators who played an essential role in data analysis were blinded to the intervention allocation. There was no mention of concealing the sequence from the patients or the researchers. The researches indicated that both the staff involved in treating the sample, and all participants were completely aware of the intervention procedure. Thus, adequate efforts were not taken to prevent selection bias.

Randomised controlled trials are often stopped early if the researchers identify limited likelihood of identifying eventual success of the intervention or treatment (Hróbjartsson et al. 2013). Furthermore, randomized controlled trials are also stopped earlier than the proposed time for apparent benefits that are found to receive greater attention, thereby affecting clinical practice. The primary outcome measure of the trial related to evaluating patient proportion who received analgesia within 30 minutes, of being attended by the care givers. There was no mention of stopping the trial early or reducing the time that was initially proposed for implementation of the intervention.

In the research study, the researchers compared the recruited sample in terms of the two groups to which the participants were randomly assigned. The final outcomes made a comparison of the patients who had received analgesia, 30 minutes after being visited by the standard care group, and that of the NP group. Thus, the participants or patients were analysed in the two groups to which random allocation had initially taken place.

Concealed Allocation

The basic purpose of randomizing participants or patients can be attributed to the fact that these patients are often comparable for the known and unknown factors or parameters, present at the beginning of a particular trial (Hirst et al. 2014). This helps in attributing all forms of differences that are encountered at the end of the trial, to the intervention under investigation. In the research, the participants who were allocated to different groups at the start of the trial belonged to the same cohort and were recruited from adult tertiary care ED. Moreover, all patients who reported similar complaints of pain were selected for the study, followed by their randomization. Furthermore, both the treatment groups were balanced in regards to the baseline demographic characters such as, sex, age, and time of presentation, mode of transport, and pain score based on the Australian Triage Scale (Ebrahimi et al. 2015). Thus, it can be stated that there were no differences in the demographic features of the patients that might have influenced the outcomes. The sample size was quite large, in addition to presence of a robust randomization method. This probably contributed to similar features of the patients in both the groups, thereby preventing selection bias.

While the primary objective of the study was to compare the effectiveness of standard medical care and nurse practitioner services in Australia, the two groups were not treated equally. It is essential to treat the groups equally except for presence of major differences between the intervention and treatment that is currently being investigated (Chan et al. 2013). This is generally accomplished by blinding the study personnel and the health workers, with regards to the intervention. Furthermore, the treatment applications and the schedules of follow up should also have been identical. While the medical officers who provided assistance to the patients allotted to the standard care group had a minimum experience of 3 years, those belonging to the NP group had experience of 1-4 years. Thus, differences in medical experience might have resulted in bias in the outcomes.

An effect size refers to statistical calculation that is generally utilized for comparing the effectiveness of a range of agents, usually accomplished by quantifying sizes of the differences that exist between the proposed intervention and treatments (Kühberger, Fritz and Scherndl 2014). Hence, gaining an estimate about the effect size helps in providing a deeper understanding of magnitude and direction of a proposed intervention (Lakens 2013). The primary outcome measures were related to the proportion of participants or patients who had received analgesia, within 30 minutes of getting attended by healthcare professionals. The time was consistent with the Australian National Emergency Access Target (Maumill et al. 2013). The major secondary outcome measures were related to evaluation of the time taken to administer analgesia to the patients, upon their arrival at the ED. All kinds of alteration in pain scores, followed by their appropriate documentation were other secondary outcomes. Recordings were made regarding the time taken for analgesia administration, from being visited by the care givers. It was considered as the time that was taken from early assessment of the patients to have analgesia administered to them, by their care providers. Furthermore, the time to analgesia, upon arrival at the ED was defined as time taken by registration of the patients till analgesia administration. Hence, the primary outcome is mentioned adequately.

Treatment Equality

Reliability of the results refers to the degree by which a particular assessment tool can give rise to consistent and stable results. Thus, it acts as an essential measure of the observing similar outcomes, on repeating the set of experiments. Upon data analysis, it was found that the 49.2% (n = 64) of the sample who had received analgesia treatment, upon 30 minutes of being visited by the care providers, in the NP group. Approximately 29.7% (n = 38) patients present in the standard care group, had received analgesia after being attended. This accounted for a 19.5% difference between the two groups (95% CI = 7.9% to 31.2%; p = 0.001). Confidence interval refers to the interval estimates that are computed after observing the data. It helps in determining the frequency of similar results that will be observed for an infinite number of times, if the experiment is repeated (Zhang and Zhang 2014). Presence of 95% confidence interval in the results indicate that if the samples were again taken, followed by performing the same research on them, there was a 95% probability of obtaining results that would match these findings (LoBiondo-Wood and Haber 2014). Hence, it can be stated that the treatment effect was quite large.

Generalisation refers to the act that encompasses reasoning, which in turn helps in drawing relevant inferences from a range of particular findings or observations (Parker and Northcott 2016). Thus, generalization can be defined as a major quality standard that is used in research. It can be stated that there are several limitations in generalizing the results to patients admitted to the ED in a wider population. Differences might arise due to variations in patient census that has been conducted at a target population. Furthermore, the local population might display discrepancies in the staffing models. Failure to appropriately record patient documentation and extract relevant patient information in the ED might also contribute to wrong results. Hence, further investigation is required before deriving conclusions about the results, with regards to a larger population.

While the researchers failed to provide a mention of the intervention, in regards to the costs, there is an likelihood of the benefits of the research being worth the harms and the costs. The findings of the study helped in showing that emergency nurse practitioners (NP) were successful in demonstrating a reduction in time to administration of analgesia, thereby enhancing the quality of life. A delay in access to emergency care facilities might be detrimental for the patients and lead to deterioration of their optimal health outcomes, thereby affecting their capability to meet the pre-determined clinical performance targets. However, these adverse effects might not arise at all possible situations. Thus, it can be stated that the benefits or the treatment or intervention were worth of the harms and associated costs.

References

Chan, A.W., Tetzlaff, J.M., Gøtzsche, P.C., Altman, D.G., Mann, H., Berlin, J.A., Dickersin, K., Hróbjartsson, A., Schulz, K.F., Parulekar, W.R. and Krleža-Jeri?, K., 2013. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. Bmj, 346, p.e7586.

Ebrahimi, M., Heydari, A., Mazlom, R. and Mirhaghi, A., 2015. The reliability of the Australasian Triage Scale: a meta-analysis. World journal of emergency medicine, 6(2), p.94.

Hirst, J.A., Howick, J., Aronson, J.K., Roberts, N., Perera, R., Koshiaris, C. and Heneghan, C., 2014. The need for randomization in animal trials: an overview of systematic reviews. PLoS One, 9(6), p.e98856.

Hróbjartsson, A., Emanuelsson, F., Skou Thomsen, A.S., Hilden, J. and Brorson, S., 2014. Bias due to lack of patient blinding in clinical trials. A systematic review of trials randomizing patients to blind and nonblind sub-studies. International journal of epidemiology, 43(4), pp.1272-1283.

Hróbjartsson, A., Thomsen, A.S.S., Emanuelsson, F., Tendal, B., Hilden, J., Boutron, I., Ravaud, P. and Brorson, S., 2013. Observer bias in randomized clinical trials with measurement scale outcomes: a systematic review of trials with both blinded and nonblinded assessors. Canadian Medical Association Journal, pp.cmaj-120744.

Jennings, N., Gardner, G., O’reilly, G. and Mitra, B., 2015. Evaluating emergency nurse practitioner service effectiveness on achieving timely analgesia: a pragmatic randomized controlled trial. Academic Emergency Medicine, 22(6), pp.676-684.

Kühberger, A., Fritz, A. and Scherndl, T., 2014. Publication bias in psychology: a diagnosis based on the correlation between effect size and sample size. PloS one, 9(9), p.e105825.

Lakens, D., 2013. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in psychology, 4, p.863.

LoBiondo-Wood, G. and Haber, J., 2014. Reliability and validity. Nursing research-ebook: Methods and critical appraisal for evidencebased practice. Missouri: Elsevier Mosby, pp.289-309.

Maumill, L., Zic, M., Esson, A.A., Geelhoed, G.C., Borland, M.M., Johnson, C., Aylward, P. and Martin, A.C., 2013. The National Emergency Access Target (NEAT): can quality go with timeliness?. The Medical Journal of Australia, 198(3), pp.153-157.

Parker, L.D. and Northcott, D., 2016. Qualitative generalising in accounting research: concepts and strategies. Accounting, Auditing & Accountability Journal, 29(6), pp.1100-1131.

Pocock, S.J., 2013. Clinical trials: a practical approach. John Wiley & Sons, pp.50-65.

Zhang, C.H. and Zhang, S.S., 2014. Confidence intervals for low dimensional parameters in high dimensional linear models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 76(1), pp.217-242.