Evidence map›Paper›PMID 31730039›Full record

ArticleJMIR medical informatics2019

Impact on Readmission Reduction Among Heart Failure Patients Using Digital Health Monitoring: Feasibility and Adoptability Study.

Christopher Park, Emamuzo Otobo, Jennifer Ullman, Jason Rogers, Farah Fasihuddin, Shashank Garg, Sarthak Kakkar, Marni Goldstein, Sai Vishudhi Chandrasekhar, Sean Pinney and 1 more

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
5.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 66 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 1 institution in 1 country.

Christopher ParkIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0003-4791-8209
Emamuzo OtoboIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-1259-2803
Jennifer UllmanIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-3302-1305
Jason RogersIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-4127-1865
Farah FasihuddinIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-0343-0220
Shashank GargIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-9620-6446
Sarthak KakkarIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-7618-012X
Marni GoldsteinIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0003-0954-6133
Sai Vishudhi ChandrasekharIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-8882-4367
Sean PinneyIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-0268-7817
Ashish AtrejaIcahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID https://orcid.org/0000-0002-0628-4417
Icahn School of Medicine at Mount Sinai · US

Funding

Mount Sinai Institutes for Clinical and Translational SciencesUL1TR000067 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SAMPSON, HUGH A · 2012 to 2014
$16.5M
IBDPROMISE: A Web-based Patient-centric Model to Improve Quality and OutcomesK23DK097451 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ATREJA, ASHISH · 2013 to 2017
$900k
NCATS NIH HHS UL1 TR000067NIDDK NIH HHS K23 DK097451
6 · The paper itself

Abstract

backgroundHeart failure (HF) is a condition that affects approximately 6.2 million people in the United States and has a 5-year mortality rate of approximately 42%. With the prevalence expected to exceed 8 million cases by 2030, projections estimate that total annual HF costs will increase to nearly US $70 billion. Recently, the advent of remote monitoring technology has significantly broadened the scope of the physician's reach in chronic disease management.

objectiveThe goal of our program, named the Heart Health Program, was to examine the feasibility of using digital health monitoring in real-world home settings, ascertain patient adoption, and evaluate impact on 30-day readmission rate.

methodsA digital medicine software platform developed at Mount Sinai Health System, called RxUniverse, was used to prescribe a digital care pathway including the HealthPROMISE digital therapeutic and iHealth mobile apps to patients' personal smartphones. Vital sign data, including blood pressure (BP) and weight, were collected through an ambulatory remote monitoring system that comprised a mobile app and complementary consumer-grade Bluetooth-connected smart devices (BP cuff and digital scale) that send data to the provider care teams. Care teams were alerted via a Web-based dashboard of abnormal patient BP and weight change readings, and further action was taken at the clinicians' discretion. We used statistical analyses to determine risk factors associated with 30-day all-cause readmission.

resultsOverall, the Heart Health Program included 58 patients admitted to the Mount Sinai Hospital for HF. The 30-day hospital readmission rate was 10% (6/58), compared with the national readmission rates of approximately 25% and the Mount Sinai Hospital's average of approximately 23%. Single marital status (P=.06) and history of percutaneous coronary intervention (P=.08) were associated with readmission. Readmitted patients were also less likely to have been previously prescribed angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (P=.02). Notably, readmitted patients utilized the BP and weight monitors less than nonreadmitted patients, and patients aged younger than 70 years used the monitors more frequently on average than those aged over 70 years, though these trends did not reach statistical significance. The percentage of the 58 patients using the monitors at least once dropped from 83% (42/58) in the first week after discharge to 46% (23/58) in the fourth week.

conclusionsGiven the increasing burden of HF, there is a need for an effective and sustainable remote monitoring system for HF patients following hospital discharge. We identified clinical and social factors as well as remote monitoring usage trends that identify targetable patient populations that could benefit most from integration of daily remote monitoring. In addition, we demonstrated that interventions driven by real-time vital sign data may greatly aid in reducing hospital readmissions and costs while improving patient outcomes.

Indexed as

blood pressureblood pressure monitorsbody weightcell phoneheart failuremHealthmobile appsmobile phonepatient care managementpatient readmissionremote consultation

Identifiers

PMID31730039
PMCPMC6913758
OpenAlexW2969569798

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.