Chapter Three: Methodology
The set goal of the proposed evidence-based Quality improvement project is to reduce the rate of patients LWBS at the selected healthcare organization by introducing a clinical interprofessional team in triage in order to decrease patient wait time from door to physician.(Chapter Three of the DPI Project on LWBS)
Population and Sample Selection
The QIP that is a scholarly EBP happened at a healthcare organization going by the name Best Quality Healthcare Hospital (BQHH) Emergency Department in the Northwestern United States. The healthcare facility serves a cosmopolitan area with a total of 233 beds, belongs to a non- profit organization. Its ED has 26 beds and records 24047 annual visits. The selected population covered patients who sought care at the BQHH during the four weeks of the intervention. Patients of all ages are attended to whether having traumatic, medical, obstetrics, or psychiatric. The selected convenience sample comprises of patients who presented at the ED from Monday to Sunday between 12:00 pm and 11:00 pm. Patients seen in triage but referred to other departments for further examination were excluded in the convenience sample.(Chapter Three of the DPI Project on LWBS)
Instrumentation or Sources of Data
Stover et al. (2018) mention observation, interviews, and questionnaires as some of the instruments used to collect data, whether as the primary source or the secondary source. The instrumentation herein referring to the process involved in developing, testing, and using the various instruments used to collect data comprises of researcher completed instruments like time-motion logs, observation logs, interview schedules, and guides. The DPI has a quality assurance consultant who extracted pre-intervention data one month before the project could be implemented using MEDITECH, which happens to be the electronic health record (EHR ) commonly used within ED. The data collected includes the average door to physician times, the rate of LWBS patients, and the length of stay. The quality assurance analyst also collected the same data after the CITiT was implemented, the analyst collected the same data as he had done before the implementation. On the other hand, there were subject completed instruments like the self- checklists and questionnaires.(Chapter Three of the DPI Project on LWBS)
Validity and Reliability
Validity refers to the extent that an instrument measures what it is intended to measure and perform as it is designed to perform. Considering that, it is not possible to have an instrument that is 100% valid. The instruments to collect the data have external validity and allow for generalizability since the sample is representative of the ED patient population from Monday to Sunday for four weeks. The Emergency Severity Index is both valid and reliable since it measures the LWBS rates during the peak patient flow from 12:01 pm to 10:59 pm. Additionally, the questionnaire used to collect some of the data was reliable in that every question elicits only one answer relating to the research question while every question met the level of the respondent’s understanding.(Chapter Three of the DPI Project on LWBS)
Data Collection Procedures-The Six Steps
A general overview of how the data were collected begins with the researcher identifying the opportunities for data collection (Kabir, 2016). The researcher conducts an internal as well as external assessment in order to fathom the events occurring within and outside of the chosen facility. Step 2involves the selection of a priority issue for collecting the data collection then outlining the goals as well as objectives. Step three entails the organization deciding on who will be surveyed, the method to be used in collecting the data, the data sources to be used amongst other aspects. In step four, the researcher must be aware of the best practices together with practical considerations for tackling logistical challenges the organizations encounter at this stage. The considerations range from the need to secure buy-ins and the establishment of a steering committee to consider a pilot phase or test period to let the researcher improve and modify the data collection methods. Step 5 captures the analysis and interpretation of data collected, either quantitatively or qualitatively. The sixth d last step demands that once the data collected has been analyzed and results interpreted, and then it can decide to act on the data by implementing the project, collect more data or modify its approach to data collection. Conventionally, an action plan is then formulated.(Chapter Three of the DPI Project on LWBS)
Data Analysis Procedures-The Six Steps
According to Banon (2013), data analysis procedures commence with data extraction followed by data transformation, where the collected information is aggregated. Step three entails the researcher visualizing the data, building gainful insights from it before building a hypothesis with step four having a statistical data analysis conducted. Step 5 involves hypothesis testing or the generation of statistic models, which ultimately ends with model development. Finally, the author makes recommendations premised on the statistical and clinical significance of the findings. For example, in this case, to aid in data analysis, the IBM Statistical Packagev.25 for the Social sciences (SPSS) was utilized. The patients’ ages and ESI levels for all individuals who underwent the triage process prior and after the intervention had descriptive data explored. Age variables included infants (below 12months), minors (1- 18 years) adults (19-65 years), and the elderly above 65 years. The measurable outcomes were the rate of LWBS expressed as a percentage and the average door to physician time’s measure in minutes before and after the CITiT intervention.(Chapter Three of the DPI Project on LWBS)
Ethical Consideration
To secure the protection of the participants’ rights, the Direct Practice Project team sought approval of the University’s Institutional Review Board, which approved the proposed project. At the same time, the IRB of BQHH reviewed the DPI, whereupon both the healthcare organization and the University approved the project. The participants’ information collected was de-identified and stored anonymously with codes used as identifiers. Only one person, the lead researcher, had access to the data stored with a password secured to protect. Others wishing access had to be authorized to access the participant’s information.(Chapter Three of the DPI Project on LWBS)
As you continue, premiumacademicaffiates.com has the top and most qualified writers to help with any of your assignments. All you need to do is place an order with us. (Chapter Three of the DPI Project on LWBS)
Chapter Three of the DPI Project on LWBSLimitations
One of the study limitations attributed to the use of Kurt Lewin’s change management model is that the framework fosters insecurity amongst the hospital staff. The staff working at the ED get concerned about their performance the moment they hear of an impending or novel change. Uncertainty clouds their perspective as they wonder whether they will be able to execute their duties or not under a new dispensation effectively. At the same time, another limitation stems from the refreezing stage since much time is needed to freeze and have the new changes settled. There the fact that change is implemented within the context of challenging environments means the organization will not have time to get used to the changes adequately. The far-reaching impact of these limitations is that the impact of the rate of LWBS negatively. As such, there are of decrease for patients whose LWBS would decrease by an even higher margin, were it not for Lewin’s Change model limitations.(Chapter Three of the DPI Project on LWBS)
References
Bannon, W. M. (2013). The seven steps of data analysis. New York: Stats Whisperer.
Kabir, S. M. S. (2016). Methods of data collection. Book Zone Publication.(Chapter Three of the DPI Project on LWBS)
Stover, B., Lubega, F., Namubiru, A., Bakengesa, E., Luboga, S. A., Makumbi, F., & Lim, T. (2018). Conducting a large public Health data collection project in Uganda: methods, tools, and lessons learned. Journal of research practice, 14(1).(Chapter Three of the DPI Project on LWBS)
Sullivan, L. M. (2018). Essentials of biostatistics in public health (3rd ed.). Burlington, MA: Jones & Bartlett Learning
https://www.ncbi.nlm.nih.gov/
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