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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 2 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 3 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 4 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 5 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 6 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 7 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 8 FOCUS • Non-adherence • 30% elders hospitalized • 125,000 deaths per year in US • Medicare publishes these rates • Typically 65 to qualify for Medicare 9 FOCUS • Preventable more than other situations • Race, past hospitalization, etc • Use technology to remember • Online, texting, audio cue reminder systems 10 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 11 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 12 SECOND CASE STUDY • 11 participants (mean age 83) • Use technology to improve non-adherence • Techniques similar to Aware Home • Sensors to track movement • • • • • Motion sensors in each room On refrigerator On phone line On watch worn by subject In bed • Pillbox sensors to record adherence 13 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 14 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 15 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 16 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 17 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) 18 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): 19 405-411. 20 SECONDS FOR QUESTIONS? 20