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

Patients

Melissa O’Connor, PhD, MBA, RN, COS-C

, Mary Louise Dempsey, BSN, RN

, Ann Huﬀenberger, DBA, RN, NEA-BC

1, 2

Anne Norris, MD, PMC

ver 5.7 million Americans aged 20 years or older suﬀer 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 beneﬁciaries discharged from an acute care setting to home

health.

CMS implemented the Hospital Readmissions Reduction Program to reduce payment to hospitals with excess Medi-

care beneﬁciary 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

care.

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 aﬃliated 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% (ﬁscal year 2011-2012) among HF patients. Current rate is

5.2% (ﬁscal 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 eﬃcient processes, including collaboration with the health system’s existing teleICU program,

have contributed signiﬁcantly to the programs’ success. Limitations include only one home health agency, one health system

and that eﬀorts to reduce 30-day readmission was a health system-wide objective which could contribute to this programs

success.

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 eﬀorts.

References:

[1] Mozaﬀarian, 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] Caﬀrey, 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 beneﬁciaries: 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-LERT® Telemedicine Program, University of Pennsylvania Health Syste

Infectious Diseases Division, Department of Medicine, University of Pennsylvania Perelman School of Medi

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). Eﬀects of home telemonitoring interventions on patients with chronic heart

failure: An overview of systematic reviews. Journal of Medical Internet Research, 17(3):e63.