According to the National Institute on Aging, the elderly constitute about 13% of the U.S. population but consume about 30% of all prescription drugs sold in the country. According to the 2009 national census, approximately 39.6 million Americans were aged over 65 years, and this number is projected to reach more than 70 million people by 2030 (American Agency on Aging, 2014). As people age, their immune system becomes weak therefore resulting in many health complications. Compared to young people, the bodies of the elderly metabolize drugs poorly (Fried et al., 2014). Although there is nothing wrong with taking more than one medication at the same time, it becomes a health issue when more than one drug is taken for the same health problem.
Considering the complexity of polypharmacy, I will use the mixed research design. Unlike other research designs, this particular design involves the use of both quantitative and qualitative (Corbin et al., 2014). As noted in the earlier sections of this project, polypharmacy among the elderly can be prevented within the healthcare setting and outside the healthcare setting. Researching how to prevent polypharmacy among the elderly can be quite challenging because the subjects cannot be arbitrarily assigned to get many medications. Any study relating to this subject must include both qualitative and quantitative data from different sources like hospital records, interviews with patients and physicians and also secondary sources.
The main reason why the mixed research design will be selected is that it taps into the strengths of both qualitative and quantitative research designs. For example, scholars accuse quantitative research of being weak when it comes to understanding the setting or context in which people behave; something that qualitative research does. Likewise, qualitative research is seen as wanting because of the challenges in generalizing findings and potential for bias; something which is uncommon with quantitative research. Therefore, the mixed research design will be adopted because it taps into the strengths of the quantitative and qualitative research methods.
The mixed research design will be preferred in this study because it gives the researcher freedom to use data from different sources. This is important because it helps come up with more conclusive and convincing conclusions and recommendations. Single- approach research designs are biased because they look at an issue from one perspective. Consequently, I will opt for the mixed research design to eliminate all biases associated with single approach designs (Sigstad, 2014).
The primary aim of this paper will be to come up with a framework for the reduction of polypharmacy among the elderly in healthcare settings. Within healthcare environment, polypharmacy can take place when physicians fail to gather all the information about the medical history of the patient and end up prescribing similar drugs. Data to be used in this research will be collected from physicians handling elderly patients, data from organizations like the American Agency on Aging, and elderly patients. Some of the variables that will be taken into consideration when selecting the research subjects are; age, sex, drug regiment, and geographic location.
Considering that the research will involve qualitative and quantitative data, I will run data analysis. This will involve breaking down large volumes of data to get useful information. As noted earlier, one of the sources of data to be used in this research will be prescription records of elderly patients in local hospitals. To establish a correlation between age polypharmacy, I will use data mining to analyze the data.
Population of Interest and Stakeholders
As noted from the onset, the main aim of this paper will be to suggest ways of preventing polypharmacy among the elderly. Currently, people over 65 years constitute over 12% of the American population according to the Administration on Aging (2017). This represents about 40 million people; marking a huge increase from about 30 million elderly Americans in 1990. Such statistics point to the fact that although polypharmacy among the elderly is already a concern, it will become a bigger problem in future (Maher et al., 2014). For inclusion in this study, one will need to be aged 65 years and over regardless of their gender. Being aged 65 years will be an important inclusion because of the metabolic changes and lower drug clearance that comes with aging. Additionally, participants will need to be suffering from a long-term health condition for which they will be getting 4 or more regular medications. For a person to be included in this study, they will need to have numerous comorbid medical conditions that require different types of medications to treat each of the conditions.
All elderly patients who will be in intensive care or emergency units will be excluded from the study even if they meet all requirements. This exclusion will be informed by the fact that such patients will not result in good health and mental condition to take part in the research. Any patients without a complete patient case sheet will be disqualified from the study. A patient case sheet is important in establishing the prescription history of a patient, and without it, it will be impossible to establish whether a participant is undergoing polypharmacy. The third exclusion criterion will be a malignancy. Patients suffering from cancer normally experience a lot of pain most of the time and therefore will not be involved in the study even if they will be qualified. Lastly, patients who will be died before the study took place will be automatically disqualified even if they will have qualified. One of the ways that will be used in gathering information will be questionnaires, and a dead patient cannot fill out questionnaires.
The research will involve semi-structured interviews and will include clinicians and patients. Based on this, it will take place in a hospital setting or any other convenient location. This is informed by the fact that some patients may feel uncomfortable speaking in front of their caregivers whereas clinicians may be hesitant talking in front of their patients. The reason why the participants will be given the freedom to choose the venue of the interview will be to ensure that they are as comfortable as possible. Before the commencement of the interviews in hospitals, permission will be sought three days before from the relevant authorities. The primary stakeholders in this research will be elderly patients, clinicians, immediate family members of the patients, and social workers who take care of elderly patients.
This project will use both qualitative and quantitative data. Qualitative data will be collected from clinicians and elderly patients using interviews and questionnaires. Additionally, the study will involve the use of quantitative data from patient records from hospital databases. It will include a critical analysis of the approach used by clinicians in addressing polypharmacy among the elderly population (Willis & Artino, 2013). Additionally, the study will look at how certain factors predispose some elderly patients to polypharmacy and how such factors can be addressed. Participants in the study will be recruited using the purposive sampling method. Purposive sampling technique is also known as selective or judgmental sampling and employs a non- probability sampling approach to identify participants to take part in the study.
Unlike other sampling techniques that are associated with both qualitative and quantitative types of data, the primary objective of selective sampling is to focus on a specific characteristic of the population of interest and not to randomly select a representative group from a population to create a sample. Selective sampling technique will be chosen because it fits with mixed research design. As pointed out earlier, the participants to be used in the study will be elderly people aged 65 years and over and must be suffering from a chronic illness and undergoing medication. Based on this, homogenous sampling technique will be used to identify a homogenous sample. This sampling technique is a type of purposive sampling whose main aim is to come up with a homogenous sample that shares certain traits or characteristics (Etikan et al., 2016). Participants will be contacted by phone, provided with a summary of the intended study, and sent a formal written invitation letter that expresses interests in receiving more information on polypharmacy. An information sheet will be attached to the invitation letter, which will be used by the respondents in their decision-making process. The study aims to recruit 25 respondents. The main responsibility of the participants will be to respond to the interview questions and questionnaires.
The data collected during the research will be evaluated and analyzed to ensure it is useful and valuable to the study. The primary data analysis tool that will be used to analyze the data from the survey is SPSS Statistics 17.0. I opted for this data analysis tool because of its ability to analyze and manipulate data in numerous ways. Apart from health sciences, other fields like social sciences also use SPSS
Hadlai Hull, Norman Nie, and Dale Bent developed SPSS. All of them were students at the University of Stanford. Initially, the software was meant for use within the university. However, the software proved popular around the university, and the three friends started developing it for IBM mainframe computers. As a company, SPSS Inc. was established in 1975 and was later acquired by IBM Corporation.
Some tests will be done on the collected data to ensure its validity. Checking data validity is important because it will ensure that the study achieves the expected goal. I will review both qualitative and quantitative data that I will use in the research for internal and external validity. SPSS will be used to test all data and ensure its validity during the experiment. This particular tool was preferred because it contains numerous data analysis and validation capabilities.
Steps in Data Validation
The first step in validating data using SPSS 17.0 will involve creating a Data Validation Rule. After creating the Data Validation rule, the next step will be creating an input message. The third step will include producing an error message. This message will be popping up whenever someone keys in an invalid figure. The last step in data validation will be displaying the outcomes of the validation process.
All data that will be used in the experiment will be checked for consistency. Data reliability is important because it will help support the final findings of the research. SPSS Statistics 17.0 will be used to test all data for reliability.
Data Collection Procedures
Data will be collected by reviewing the answered questionnaires, interviews, and patient records. Case sheets of all elderly patients admitted in hospitals with chronic diseases will be reviewed daily during the research period. These reviews of case sheets will be considered once for every patient during a single admission. Elderly patients who will be admitted more than once during the research period will be considered a separate admission. All information regarding participants like date of admission, name, age, date of diagnosis, number of drugs prescribed, and sex will be treated with utmost confidentiality.
Corbin, J., Strauss, A., & Strauss, A. L. (2014). Basics of qualitative research. Thousand Oak: CA, Sage.
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