Instruments
Each of the segments of the Doctor of Nursing Practice (DNP) project requires significant knowledge in nursing and research methodology. The project’s success depends on the conscious setting of goals, effective decision-making, a detailed analysis of the premises and data, as well as an understandable and proper formulation of the hypothesis, thesis statement, and results. Research instruments, data collection, and data analysis plan are also crucial elements for developing valid and reliable knowledge.
Patient satisfaction is a major qualitative indicator of the effectiveness of an intervention. This variable is crucial in chronic care management (CCM) because patients who use chronic care services constantly have to put up with adverse effects of their conditions. Their level of satisfaction shows how effective measures applied by health care providers are. Patient-Reported Outcome Measures (PROMs) are among the most effective assessment tools in healthcare that have recently begun to gain popularity in various areas of care, and CCM is no exception. According to Bingham III et al. (2019), “increasingly, PROs are used to screen across general areas of health to identify problems and needs.” (p. 138). Experts note that PROMs are “are standardized, validated surveys … used to study how you feel about your health status” (Patient-reported outcome measures, n.d., para. 3). Although it should be mentioned that PROMs are more of a principle according to which questionnaires and surveys are compiled than a research instrument.
Therefore, after a lengthy review of the different variations of PROMs, the Kansas City Cardiomyopathy Questionnaire (KCCQ) was chosen as the primary research instrument. According to the scientific community, “the Kansas City Cardiomyopathy Questionnaire is a 23-item, self-administered instrument that quantifies physical function, symptoms (frequency, severity and recent change), social function, self-efficacy and knowledge, and quality of life” (The Kansas City cardiomyopathy questionnaire, 2015, para. 2). Professionals note that it is “the most sensitive, specific, and responsive health-related quality of life measure for heart failure” (The Kansas City cardiomyopathy questionnaire, 2015, para. 1). Moreover, Napier et al. (2018) argue that it has significant internal consistency, its Cronbach’s alpha in terms of a clinical summary is 0.91, and in terms of quality of life, it is 0.87. The available evidence shows that KCCQ, being one of the best tools for the qualitative assessment of patients with heart diseases, is effective and has excellent practical potential (Bingham III et al., 2019). However, the researchers warn that there are some difficulties motivating patients to take PROMs questionnaires regularly and implementing the findings into new and innovative healthcare practices.
Data Collection Procedures
As mentioned above, the correct choice of data collection methods is crucial for the entire DNP project. The wrong approach can fatally affect the study results and conclusions, and the time spent on the intervention will be wasted. One of the main rules for choosing data collection methods is that the procedures should be appropriate for the nature of the research and the research instruments. The upcoming study is qualitative as it focuses on the satisfaction level of geriatric patients in remote patient monitoring (RPM) and CCM settings. The assessment tool is also qualitative; therefore, the methods of data collection should also be so. There are three data gathering methods that are suitable for the setting and terms of the NPD draft. These are textual and visual analysis and observation.
It is also necessary to identify which specific demographic variables will be used and which demographic groups will be given special attention. Key indicators will be “the physical function, symptom (frequency and severity), social function and quality of life” (The Kansas City cardiomyopathy questionnaire, 2015, para. 4). Particular attention will be paid to non-Hispanic Black geriatric patients as this ethnic group has the highest mortality rate from heart disease (Health, 2019). Non-Hispanic white elderly patients are the next most important group of patients.
Data Analysis
It is no secret that successful data collection is not the final stage; gathered data must be interpreted. The data collected is valuable, but it is the analysis that allows the researcher to turn evidence into practice. After the geriatric patient has remotely completed all regular KCCQs within a certain period, the textual data and the information obtained during observations will be analyzed. It will be done following the bivariate analysis rules. According to Bertani et al. (2018), “bivariate analysis explores how the dependent (“outcome”) variable depends or is explained by the independent (“explanatory”) variable (asymmetrical analysis)” (p. 1133). It will allow finding out what effect remote patient monitoring using modern digital technologies has on patient satisfaction in chronic care.
When discussing data analysis, it is necessary to define inferential and descriptive statistics in the context of the research. There, the descriptive statistics will be how patients feel in terms of the abovementioned specific variables and their level of satisfaction with the intervention. Inferential statistics will be a general conclusion about the effectiveness of the intervention, confirmation or refutation of the efficiency of PROMs in the CCM and RPM, and the effectiveness of RPM using modern digital online technologies.
References
Bertani, A., Di Paola, G., Russo, E., & Tuzzolino, F. (2018). How to describe bivariate data. Journal of Thoracic Disease, 10(2), 1133-1137.
Bingham III, C. O., Noonan, V. K., Auger, C., Feldman, D. E., Ahmed, S., & Bartlett, S. J. (2017). Montreal Accord on Patient-Reported Outcomes (PROs) use series – paper 4: Patient-reported outcomes can inform clinical decision making in chronic care. Journal of clinical epidemiology, 89, 136-141.
Health, United States – infographics. (2019). Centers for Disease Control and Prevention. Web.
Napier, R., McNulty, S., Eton, D. T., Redfield, M. M., AbouEzzeddine, O., & Dunlay, S. M. (2017). Comparing measures to assess health-related quality of life in patients with heartfailure with preserved ejection fraction. Journal of Cardiac Failure, 23(8), 552-560. Web.
Patient-reported outcome measures (PROMs). (n.d.). Hospital for Special Surgery. Web.
The Kansas City cardiomyopathy questionnaire. (2015). CV Outcomes, Inc. Web.