As we analyze the factors contributing to health care costs we must find a solution that provides high-quality care for an aging population. Improvements to modern medicine are prolonging life causing a schism between a health care system oriented towards acute care and the increasing chronic care needs of older adults. Studies do show that health care costs for older Americans account for one third of all national health care expenditures. This being said the average expenditure for health care services for adults 65 and over is nearly four times the cost of those under 65. More significant changes need to be considered given the financial crisis our health care system faces. Health care costs are not solely due to longevity; consider increased utilization, new medical technologies, general inflation, fraud, and waste and abuse. This paper will discuss one article to be used in my final presentation on health care for anaging population. Data collection procedures
The study on chronic health conditions used a questionnaire presented to study participants by in-person and telephone interview using computer-assisted software. They also used the Statistics Canada Canadian Community Health Survey (CCHS) for age prevalence patterns and to show how chronic condition prevalence varies by age group. The use of the CCHS survey for historical data and comparisons is very appropriate for this study. The use of a questionnaire, while not ideal, is appropriate for the large number of participants. The survey sampled approximately 130,000 people aged 12 years or older. In-person interviews are the most reliable, but the downside to using telephone interviews using computer-assisted software is that participants may go through the questionnaire quickly or skip questions if they are unsure. Identity protection for research subjects
Confidentiality is the protection of information that an individual has trusted you with and disclosed to you for a particular reason. Informed consent is a process in which the researcher explains to the participant what steps are taken to keep their information confidential and what would happen if there were a data breach. The participant then has the information needed to determine if this is adequate and whether or not to continue with the project. The article does not discuss the steps taken to protect the identity of participants. There is no mention of patient record abstraction, personal information collected or informed consent. Reading the article, it is an assumption that the only information collected was the age and number and type of chronic conditions for each participant. Study reliability and validity
The reliability of this study, that is, the consistency and repeatability of the measure is high. A question related to the number and type of chronic conditions experienced by each participant is reliable and is measuring one topic. The questionnaire meets face validity – it is a common-sense assessment and the question measures exactly what they want to study. Data analysis procedures
To answer the research questions, the researchers used data from the CCHS survey to develop a baseline of the number of chronic conditions within certain age groups. That data was then projected for 25 years based on the target population which was derived from a model of the economic demographic system (MEDS) projection. The hypothesis, “The expectation is that, as the large baby boom cohort moves into older age categories, the overall proportion of the population with chronic conditions will increase” (Denton & Spencer, 2010), is best answered by projecting the number of people in each age group based on historical data and factoring in immigration, emigration, mortality, and fertility rates.
I believe this study is quantitative. It involves randomly selected participants, uses face-to-face and phone questionnaires, the data analysis is statistical and is presented in tables and graphs, and is used to recommend a final course of action. The study design is descriptive, also called observational. Validity is important in descriptive studies; the lower the validity, the more study participants you will need. “For an accurate estimate of the relationship between variables, a descriptive study usually needs a sample of hundreds or even thousands of subjects.” (Hopkins, 2000) Conclusion
In conclusion, the study shows that more than two-thirds of the population over the age of 12 has a chronic condition and 90% of them are over the age of 65. The researchers believe that as the participants move into higher age groups the prevalence of chronic conditions will increase, which this study proves. The prevalence rate in 2005 is 68.7% and the prevalence rate in 2030 is 71.9% which is an increase of 3.2%. But how does this affect health care utilization and cost? With a modest reduction in the prevalence of chronic conditions, one-third of the projected increase in health care spending could be cut by 2030. In this study, a modest reduction is described as reducing the number of chronic conditions by one. Those with three chronic conditions would be reduced to two, two would be reduced to one, and one would be reduced to none.
The strengths of this study are the high reliability and validity of the data recorded from the questionnaires. The data analysis and projections based on the target population, adjusted for emigration, immigration, mortality, and fertility was the best option for this type of study. The weaknesses of the study were the inability to abstract data on chronic conditions from the medical records of the participants, and the exclusion of participants in institutions which resulted in an under-estimation of chronic conditions in older populations. Another weakness noted by the researchers was that there was no record of the severity of the condition. This does not allow for accurate accounts of those cured of the chronic condition during the study period.
Denton, F.T., & Spencer, B.G. (2010). Chronic health conditions: Changing prevalence in an aging population and some implications for the delivery of health care services. Canadian Journal on Aging, 29(1), 11-21. Doi:http://dx/doi.org/10.1017/SO714980809990390 Hopkins, W.G. (2000). Quantitative Research Design. SportsScience, 4(1), retrieved online May 26, 2014 from http://www.sportsci.org/jour/0001/wghdesign.html