H3IT Logo

Home Healthcare, Hospice, and Information Technology Innovations Conference

Innovations in Home Healthcare, Hospice, and Information Technology

A forum towards achieving evidence-based diffusion and implementation of innovations

Fri, Nov 3, 2017
Friday, Nov 3, 2017, Washington - D.C.
H3IT: Home Healthcare, Hospice, and Information Technology Conference Nashville, TN, 2015
Using Telehealth to Reduce All-Cause 30-Day
Hospital Readmissions among Heart Failure
Melissa O’Connor, PhD, MBA, RN, COS-C
, Mary Louise Dempsey, BSN, RN
, Ann Huenberger, DBA, RN, NEA-BC
1, 2
Anne Norris, MD, PMC
ver 5.7 million Americans aged 20 years or older suer from heart failure (HF) with an expected increase of
46% by 2030. Hospital discharges with a primary diagnosis of HF rose from 877,000 in 1996 to 1,023,000 in
2010. Estimated total cost of HF in the United States exceeded $30 billion in 2012 and is pro jected to be
$70 billion by 2030.
Heart failure is the primary diagnosis for 4.3% of home health episodes
and is among
the top ten most common diagnoses related groups for Medicare beneciaries discharged from an acute care setting to home
CMS implemented the Hospital Readmissions Reduction Program to reduce payment to hospitals with excess Medi-
care beneciary 30-day readmissions for HF.
Approximately 25% of HF patients are readmitted to a hospital within 30 days
of discharge
making the reduction of HF patient readmission rates a national priority. Prior research shows varied results on
patient outcomes, however, a recent meta-analysis indicates TH reduces HF related hospital admissions compared to usual
This presentation will describe the launch of this program, how operations were centralized and future directions.
Reducing 30-day readmissions was and continues to be a health system-wide objective.
Methods: A telehealth, remote monitoring program was initiated in September of 2010 at Penn Care at Home, a skilled
home health agency aliated with the University of Pennsylvania Health System. The TH program is intended to reduce HF
patient readmission rates within the health system. Program processes were continually monitored and continue to evolve
contributing to this program’s success. Potential candidates have to speak English, be able to stand on a scale and be
agreeable to TH. Initial equipment employed was moderate sized TH unit reliant upon a landline telephone or wireless card.
In 2014 all TH equipment was converted to a 4G tablet based system collects patient vital signs and systems and is preloaded
with patient education related to maintaining a healthy lifestyle and self-care (automated device-based). The software also
includes instructional videos and individualized care plans. The recorded data is transmitted to the TH team, located within
the health system’s teleICU on a daily basis, who collaborate with patients and providers to identify goals and strategies
to avoid a hospital readmission if possible. Data related to admissions is captured via the health system’s electronic health
record which alerts TH personnel. Nearly 200 patients receive TH each year.
Results: Year one all-cause 30 day readmission rate was 19.3% (scal year 2011-2012) among HF patients. Current rate is
5.2% (scal year 2014-2015), a reduction of over 14% in three years.
Discussion: TH was associated with reduced all-cause 30-day readmission among HF patients receiving skilled home health
services. Vigilant clinicians and ecient processes, including collaboration with the health system’s existing teleICU program,
have contributed signicantly to the programs’ success. Limitations include only one home health agency, one health system
and that eorts to reduce 30-day readmission was a health system-wide objective which could contribute to this programs
Conclusion: Penn Care at Home’s all-cause 30-day readmission rate has steadily declined since the program’s inception
and has become an integral part of the University of Pennsylvania Health Systems’ 30-day readmission reduction eorts.
[1] Mozaarian, D., Benjamin, E. J., Go, A. S., Arnett, D. K., Blaha, M. J., Cushman, M., ... Turner, M. B. (2015).
Heart disease and stroke statistics—2015 update: A report from the American Heart Association. Retrieved from
http://circ.aha journals.org/content/early/2014/12/18.
[2] Carey, C., Sengupta, M. Moss, A., Harris-Kojetin, L. & Valverde, R. (2011). Home health care and discharge hos-
pice care patients: United States, 2000 and 2007. National Health Statics Report, 38: 1-27.
[3] Centers for Medicare and Medicaid Services (2012). Chronic conditions among Medicare beneciaries: Chartbook
2012. Retrieved from https://www.cms.gov/research-statistics-data-and-systems/statistics-trends-and-reports/chronic- con-
Penn Care at Home, University of Pennsylvania Health System
PENN E-LER Telemedicine Program, University of Pennsylvania Health Syste
Infectious Diseases Division, Department of Medicine, University of Pennsylvania Perelman School of Medi
Copyright © 2015 by Maryland Health Information Technology LLC Creative Commons License cbnd 30
H3IT: Home Healthcare, Hospice, and Information Technology Conference Nashville, TN, 2015
ditions/downloads/2012chartbook.pdf Medicare Payment and Advisory Commission (2013).
[4] Krumholz, H. M., Merrill, A. R., Schone, E. M., Schreiner, G. M., Chen, J., Bradley, E. H., ... Drye, E. E. (2009).
Patterns of hospital performance in acute myocardial infarction and heart failure 30-day mortality and readmission. Circu-
lation: Cardiovascular and Quality Outcomes, 2: 407-413.
[5] Kitsiou, S., Pare, G. & Jaana, M. (2015). Eects of home telemonitoring interventions on patients with chronic heart
failure: An overview of systematic reviews. Journal of Medical Internet Research, 17(3):e63.
Copyright © 2015 by Maryland Health Information Technology LLC Creative Commons License c b n d 31