| Course | HLTH 4205 Introduction to Research Methods and Analysis |
|---|---|
| Week | Week 7 |
| Paper type | Discussion post with two peer replies |
| Length | About 540 words, 3 pages |
| Format | Discussion post, APA 7 citations |
| School | Walden University |
| Program | BS in Healthcare Administration |
| Updated | October 2026 |
Free sample paper for HLTH 4205 Week 7
Week 7 Discussion: Initial Post
Opening the 40% Number: What Oregon's Emergency Department Finding Counts, Compares and Supports
The statistic I chose appeared in many headlines in early 2014: Medicaid coverage increased emergency department visits by 40%. It comes from the Oregon lottery study, and it surprised people who expected that giving low-income adults insurance would move them from emergency rooms to clinics. Here is what I found when I opened it.
What it counts. The number counts emergency department visits recorded at twelve Portland-area hospitals over about eighteen months, taken from hospital records rather than from people's memories (Taubman et al., 2014). That is a strength: self-reported visits would be less reliable. It also means visits to hospitals outside that area were not counted.
What it is divided by. The 40% is a relative increase. The study estimated that coverage increased visits by about 0.41 per person over the period, compared with an average of about one visit per person in the control group (Taubman et al., 2014). In absolute terms, that is a little under one additional visit for every two people covered, over a year and a half. The headline percentage is accurate, but the absolute figure gives a better sense of scale for a hospital planning its staffing.
What comparison gives it meaning. The comparison is between people who won the lottery and people who did not, adjusted for the fact that not all winners enrolled. Because the lottery was random, the two groups were similar at the start, so the difference can be attributed to coverage. That is what made the finding hard to dismiss.
Whether it supports the sentence beside it. Some headlines said Medicaid makes people overuse the emergency room. The study supports that coverage increased visits, including visits for conditions that might have been treated in a clinic. It does not show that the visits were unnecessary or harmful, and it does not tell us whether the effect lasts once people establish care elsewhere. The same study population also showed more use of outpatient care and less financial strain in the first year (Finkelstein et al., 2012) and lower rates of depression two years in (Baicker et al., 2013), so the finding is one part of a larger picture, not a verdict on the program.
Reply to Hannah S.
Hannah, the readmission figure you chose, that a hospital's readmissions fell by half after a new discharge program, is a good one to open. My first question would be the denominator: half of what, over what period, compared with which months? A fall from 20 readmissions to 10 in a small unit could easily be chance, while the same percentage across thousands of discharges would be impressive. Did the report say how many discharges were behind the figure?
Reply to Omar F.
Omar, you said you no longer trust any statistic in the news. I understand the feeling, but I think the Oregon number shows why opening a statistic is better than rejecting it. Once we asked what it counted and what it was compared with, the 40% turned out to be well measured and fairly compared; the problem was only in some of the sentences written around it. Distrust everything and you lose the good numbers along with the bad.
References
Baicker, K., Taubman, S. L., Allen, H. L., Bernstein, M., Gruber, J. H., Newhouse, J. P., Schneider, E. C., Wright, B. J., Zaslavsky, A. M., & Finkelstein, A. N. (2013). The Oregon experiment: Effects of Medicaid on clinical outcomes. New England Journal of Medicine, 368(18), 1713-1722. https://doi.org/10.1056/NEJMsa1212321
Finkelstein, A., Taubman, S., Wright, B., Bernstein, M., Gruber, J., Newhouse, J. P., Allen, H., Baicker, K., & Oregon Health Study Group. (2012). The Oregon Health Insurance Experiment: Evidence from the first year. The Quarterly Journal of Economics, 127(3), 1057-1106. https://doi.org/10.1093/qje/qjs020
Taubman, S. L., Allen, H. L., Wright, B. J., Baicker, K., & Finkelstein, A. N. (2014). Medicaid increases emergency-department use: Evidence from Oregon's Health Insurance Experiment. Science, 343(6168), 263-268. https://doi.org/10.1126/science.1246183
The Walden HLTH 4205 Week 7 instructions
Statistics threads in a methods course commonly ask you to take one reported number and examine it. Choose a figure that appeared in the news or in a report. Ask what it counts and where the data came from. Ask what it is divided by, and whether it is a relative or absolute change. Ask what comparison gives it meaning, and whether that comparison is fair. Finally, ask whether the number supports the sentence written next to it. Keep the tone curious; the aim is understanding, not debunking. In replies, ask the same questions of classmates' numbers, and respond to blanket skepticism by showing what opening a statistic can reveal.
How the HLTH 4205 Week 7 example is put together
The opening introduces the 40% headline and the surprise it caused. The count paragraph explains that visits came from hospital records at twelve hospitals, citing Taubman and colleagues. The denominator paragraph converts the relative figure to about 0.41 visits per person over eighteen months. The comparison paragraph explains the lottery and the adjustment for enrollment. The final paragraph separates what the study supports from headlines claiming overuse, and places the finding beside Finkelstein and colleagues and Baicker and colleagues on outpatient use, finances and depression. The reply to Hannah asks what a halved readmission figure was divided by. The reply to Omar argues that opening statistics is better than distrusting all of them.
HLTH 4205 Week 7 rubric: what earns full marks
Graders look for a single statistic opened systematically: what it counts, what it is divided by, what comparison gives it meaning and whether it supports the claim beside it. Converting a relative change to an absolute one, or the reverse, shows understanding that earns credit. Identifying the data source and the fairness of the comparison demonstrates methods knowledge applied to a real case. A curious tone is part of the expectation; posts that mock the number or its reporters lose credit even when their points are right. Replies earn marks for applying the same questions to a classmate's figure and for engaging skepticism constructively. Accurate citations of the original study complete the expectations.
Common HLTH 4205 Week 7 mistakes, and how to avoid them
Posts on statistics often declare a number misleading without explaining how, or accept it without asking what it was divided by. Others focus on whether they agree with the policy the number is used to support. Some never find the original study. Trace the number back to its source, which is usually a journal article or government report, and read how it was calculated. Then write four short answers: what it counts, what it is divided by, what it is compared with and whether the headline matches. When your thread asks about a different figure, a writer from our team can draft a post that opens it the same way and keeps a curious tone.
Get a HLTH 4205 Week 7 example written to your instructions
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HLTH 4205 Week 7 questions, answered
Where can I find a free HLTH 4205 Week 7 sample paper?
The post that opens the 40% statistic, with both replies, is free to read right here.
What statistic does the HLTH 4205 Week 7 post examine?
The finding that Medicaid coverage increased emergency department visits by 40% in the Oregon Health Insurance Experiment.
What does the 40% count and divide by?
Emergency visits from hospital records at twelve Portland-area hospitals over about eighteen months, relative to about one visit per person in the control group.
What is the absolute size of the increase?
About 0.41 additional visits per person over the period, a little under one extra visit for every two people covered.
Does the number support headlines about overuse?
It supports an increase in visits, including some treatable in clinics, but not that the visits were unnecessary or that the effect would last.