Transcript Overview of Readmissions - Georgia Institute of Technology

OVERVIEW OF
READMISSIONS
WITH FOCUS ON ELDERLY POPULATION WITH
MULTIPLE MEDICATIONS
Tiffany A. Formby
Healthcare Design of the Future
September 29, 2011
READMISSION DEFINED
• Returning to hospital within specified
time period original admission
• CMS time period focus is 30 days
• Normally for the same issue
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READMISSION IMPORTANCE
• Hospital has to cover costs for
readmission
• Theory: their fault for patient returning?
• Balance– longer stays in hopes for  rate
• Readmission rate important
• Quality care metric
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SUBGROUPS
Patients who:
• Were hospitalized for heart failure
• 6 month readmission rate as high as 50%
• Have multiple conditions
• 1.17 odds with stroke, 1.17 with diabetes
• Stayed in hospital longer than 7 days
• 1.52 odds
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SUBGROUPS
Patients who:
• Are taking 3 or more prescriptions
• Adherence problems increase exponentially
• Are elderly patients who fail to adhere
to prescription plans
• Attribute to 30% of hospital admissions
• Went to teaching hospitals
• Study completed shows no significant
impact
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SUBGROUPS
Patients who:
• Received individualized care plan
• Decrease in readmission rate in 7 studies
• Were confused by discharge
instructions
• Or not given instructions at all
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SUBGROUPS
• Factors and criteria contribute to higher likelihood
• Combined, even higher likelihood!
• Odds ratio (following heart failure admission)
• Race
• Caucasian
• African American
• Other
1.0 (baseline)
1.05
1.17
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FOR EXAMPLE…
Example:
Non-white/ African American (1.17)
& LOS >7 days (1.52)
& hospitalized in last 6 months (1.67)
& pre-existing diabetes (1.13)
=3.35 odds! (just the last three conditions alone = 2.87
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FOCUS
• Non-adherence
• 30% elders hospitalized
• 125,000 deaths per year in US
• Medicare publishes these rates
• Typically 65 to qualify for Medicare
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FOCUS
• Preventable more than other situations
• Race, past hospitalization, etc
• Use technology to remember
• Online, texting, audio cue reminder systems
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CASE STUDY
• Why elders forget to take medication?
• Which reminding system is most effective?
• Visual-pervasive
• Audio-portable
• Text-wearable
Take
your
pill!
(Lundell, Kimel, et al.)
study supported by National Institute on Aging grants
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CASE STUDY RESULTS
• 10 participants
• With reminding systems, adherence increase from
typical 50-80% to 96%
• Common reasons for other 4%
•
•
•
•
•
Away from home without medication
Had company over
Overslept
Slept in
Busy: on the phone, in the yard
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SECOND CASE STUDY
• 11 participants (mean age 83)
• Use technology to improve non-adherence
• Techniques similar to Aware Home
• Sensors to track movement
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•
•
•
•
Motion sensors in each room
On refrigerator
On phone line
On watch worn by subject
In bed
• Pillbox sensors to record adherence
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SECOND CASE STUDY
• This time- Rules for Reminders
• Prompt at closest location
• Don’t prompt if in bed
• Wait until off phone
68.1% no reminders
73.5% time-based reminder
92.3% context-based reminder
(Hayes, et al.)
study supported by National Institutes of Health grants
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MY SOLUTION
• Initial idea for a pill dispenser alarm clock
• Similar to solutions in literature, Aware home
• Elderly normally sleep in consistent bed
• Issues- most pills taken twice a day
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MY SUGGESTIONS
• Complete similar case with reminder systems
• Increase number of participants
• Track among age groups
• Under 65 would appreciate a reminder system
• Is context-based improvement worth investment in
sensors, etc
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MY SUGGESTIONS
• Introduce whichever successful product in
hospitals
• Sell to hospital as part of care package to send
home with patients on multiple medications
• Charge as a hospital supply on patient bill?
• Begin familiarizing patients with technology
• Program timing to normal lifestyle (not hospital
time) to get in habit
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CONCLUSIONS
• Cost of readmissions in spotlight
• $$$ on the mind
• Address subgroups
Identify key attributors in each
situation
Elder population
 those taking multiple meds
Which are preventable?
Patient who forget to take them
Eliminate majority of preventable
readmissions
80% with time programmed
reminding systems
After completing for all groups,
look at detailed issues
Other 20% what went wrong
(anomalies)
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REFERENCES
Aranda, J. M., J. W. Johnson, et al. (2009). "Current Trends in Heart Failure Readmission Rates: Analysis of
Medicare Data." Clinical Cardiology 32(1): 47-52.
Batty, C. (2010). "Systematic Review: Interventions Intended to Reduce Admission to Hospital of Older
People." International Journal of Therapy & Rehabilitation 17(6): 310-322.
Hayes, T. L., K. Cobbinah, et al. (2009). "A Study of Medication-Taking and Unobtrusive, Intelligent
Reminding." Telemedicine Journal and E-Health 15(8): 770-776.
Kimel, J. and J. Lundell (2007). "Exploring the nuances of Murphy's Law---long-term deployments of
pervasive technology into the homes of older adults." interactions 14(4): 38-41.
Lundell, J., T. L. Hayes, et al. (2007). Continuous activity monitoring and intelligent contextual prompting to
improve medication adherence. 2007 Annual International Conference of the Ieee Engineering in
Medicine and Biology Society, Vols 1-16: 6287-6290.
Lundell, J., J. Kimel, et al. (2006). Why elders forget to take their meds: A probe study to inform a smart
reminding system, IOS Press.
Minott, J. (2008). "Reducing Hospital Readmissions." accessed on April 8: 2009.
Press, M. J., Jeffrey H Silber, Amy K Rosen, Patrick S Romano, Kamal M; F Itani, Jingsan Zhu, Yanli Wang, Orit
Even-shoshan, Michael J Halenar, and Kevin G Volpp (2011). "The Impact of Resident Duty Hour Reform on
Hospital Readmission Rates Among Medicare Beneficiaries." Journal of General Internal Medicine 26(4):
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405-411.
20 SECONDS FOR QUESTIONS?
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