1. Chronic Conditions

2. Questions for Faculty
Does your use of the data have to be hypothesis-driven, or do you create a hypothesis based on trends you observe after performing some data analyses?
Is it best to look at averages, ranges, or individual data points when working with such a large data set?
The HCUP training prohibited researchers from contacting institutes and individuals whose data were used in the HSR. Are there exceptions to this rule?
When looking at a dataset of this magnitude, what are some basic variables that we should always measure?
Are there ways to compute categorical data into numerical, or vice versa?
What is the most valuable way to go about finding a significant figure in raw data? ie mean, median, mode, other

3. Comments on your slides
Great job using language of correlation, rather than language of causation:
“…has a positive correlation with…”
It takes some playing around to figure out the way of presenting data that answers the question you are trying to ask.

4. There is a higher prevalence of smoking among those with no further than a high school education than those with any years of college education
# of people who currently smoke
Years of Education
#2 Rita, Erin, Nadine

5. Care Attainment by Income:Income is not a good predictor for attaining care when needed
Got care when needed for illness or
Injury:

6. Amount Paid in Private Insurance (in dollars) with respect to Years of Education

7. Graph #3 (Samantha and Tayler)

8. Questions
Are there ever reasons to explore data without a hypothesis or research question?
What biases could arise from people letting the data drive research questions?
Do you think those biases are out there in the health services research literature?
Are there ways of avoiding these biases?

9. Thoughts on research with data
Research questions evolve as you interact with data.
Some great research questions have to be abandoned because you don’t find specific trends.
“You can’t prove a negative.” -Bias in research.
Managing data is a big part of research. (Grunt work).

10. Hot Spotters

11. What did you learn from “Hot Spotters”?
(Come up with a list of key points).

12. Hot Spotters Discussion Questions
How should the system handle super utilizers like those discussed in the article?
Should the system target high cost or more complex patients and treat them separately?
To what extent should we use health coaches (with no medical training) in the management of complex patients?
What ethical issues need to be taken into consideration if expanding initiatives like Brenner and Fernandouple?

14. Worksheet

15. Chronic Quadrangle

17. Accountable Care Organizations (ACOs)
Who?
Doctors
Hospitals
Other providers
NOT insurers (Otherwise it would be an HMO)
Goals:
Coordination
Reduction of costs
Improvement in qualities
Requirements and incentives under Affordable Care Act:
Must experiment with pay-for-performance
Must have coordination
Shared savings: Any savings in total patient care (from reduced hospital usage, reduced surgeries, etc) will be shared with the ACO (e.g. they keep 60% of those savings)
3-minute video:

18. Multiple Chronic Condition Patients

20. Problems Faced by Multiple Chronic Condition Patients
Medical research: They are excluded from randomized controlled trials and medical research.
Coordination of Care: The health care system does not coordinate well across different types of doctors.

21. Source: Wikimedia Commons, the free media repository
Author: Unknown

22. Patient with multiple chronic conditions
Depression
Psychiatrist
Heart disease
Asthma
Cardiologist
Pulmonologist
Stick figure site:
Diabetes
Endocrinologist

23. Countries with stronger primary care systems tend to have better health outcomes and lower costs.
Costs by country