Evidence map›Paper›PMID 32589161›Full record

ArticleJMIR mHealth and uHealth2020

Assessing the Impact of Patient-Facing Mobile Health Technology on Patient Outcomes: Retrospective Observational Cohort Study.

Courtenay R Bruce, Patricia Harrison, Tariq Nisar, Charlie Giammattei, Neema M Tan, Caitlin Bliven, Jamie Shallcross, Aroub Khleif, Nhan Tran, Sayali Kelkar and 15 more

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Article
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  5. Observational
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  15. The future is not just a 6-minute walk test.European heart journal. Digital health · 2021
    Article
  16. Article
  17. Article
  18. Article
  19. Improved FMEA Methods for Proactive Health Care Risk Assessment of the Effectiveness and Efficiency of COVID-19 Remote Patient Telemonitoring.American journal of medical quality : the official journal of the American College of Medical Quality
    Article
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

25 authors.

Courtenay R Bruce *System Quality & Patient Safety, Houston Methodist Hospital System, Houston, TX, United States.ORCID 0000-0002-9503-9834
Patricia HarrisonSystem Quality & Patient Safety, Houston Methodist Hospital System, Houston, TX, United States.ORCID 0000-0002-8832-2885
Tariq NisarCenter for Outcomes Research, Houston Methodist Research Institute, Houston, TX, United States.ORCID 0000-0003-2954-9825
Charlie GiammatteiCareSense, Philadelphia, PA, United States.ORCID 0000-0002-2776-7821
Neema M TanSystem Quality & Patient Safety, Houston Methodist Hospital System, Houston, TX, United States.ORCID 0000-0003-4976-985X
Caitlin BlivenCareSense, Philadelphia, PA, United States.ORCID 0000-0002-1430-4692
Jamie ShallcrossCareSense, Philadelphia, PA, United States.ORCID 0000-0002-2525-7852
Aroub KhleifInformation Technology Department, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0003-4388-3328
Nhan TranInformation Technology Department, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0002-8561-4874
Sayali KelkarSystem Quality & Patient Safety, Houston Methodist Hospital System, Houston, TX, United States.ORCID 0000-0003-0130-3380
Noreen TobiasInformation Technology Portfolio Management Office, Houston, TX, United States.ORCID 0000-0002-6915-0264
Ana E ChavezCardiovascular Surgery Associates, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0003-0199-7140
Dana RiveraHouston Methodist Orthopedic and Sports Medicine - The Woodlands, Houston Methodist The Woodlands, The Woodlands, TX, United States.ORCID 0000-0001-9440-4062
Angela LeongClinical Design and Planning, Houston Methodist Hospital System, Houston, TX, United States.ORCID 0000-0002-1460-7474
Angela RomanoHouston Methodist Specialty Physician Group, Houston Methodist Orthopedics & Sports Medicine, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0002-1738-9839
S Nicholas DesaiDepartment of Orthopedics, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0001-7695-4044
Josh R SolCenter for Innovation, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0003-2742-8819
Kayla GutierrezHouston Methodist Specialty Physician Group, Houston Methodist Orthopedics & Sports Medicine, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0001-6253-4938
Christopher RappelHouston Methodist Sugar Land Hospital, Houston, TX, United States.ORCID 0000-0003-1229-1565
Eric HaasDepartment of Surgery, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0002-6478-636X
Feibi ZhengDepartment of Surgery, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0001-7590-5566
Kwan J ParkDepartment of Orthopedics, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0003-4084-5676
Stephen JonesCenter for Outcomes Research, Houston Methodist Research Institute, Houston, TX, United States.ORCID 0000-0002-1106-171X
Paul BarachJefferson College of Population Health, Thomas Jefferson University, Philadelphia, PA, United States.ORCID 0000-0002-7906-698X
Roberta SchwartzCenter for Innovation, Houston Methodist Hospital, Houston, TX, United States.ORCID 0000-0003-3757-8765

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the growth of and media hype about mobile health (mHealth), there is a paucity of literature supporting the effectiveness of widespread implementation of mHealth technologies.

objectiveThis study aimed to assess whether an innovative mHealth technology system with several overlapping purposes can impact (1) clinical outcomes (ie, readmission rates, revisit rates, and length of stay) and (2) patient-centered care outcomes (ie, patient engagement, patient experience, and patient satisfaction).

methodsWe compared all patients (2059 patients) of participating orthopedic surgeons using mHealth technology with all patients of nonparticipating orthopedic surgeons (2554 patients). The analyses included Wilcoxon rank-sum tests, Kruskal-Wallis tests for continuous variables, and chi-square tests for categorical variables. Logistic regression models were performed on categorical outcomes and a gamma-distributed model for continuous variables. All models were adjusted for patient demographics and comorbidities.

resultsThe inpatient readmission rates for the nonparticipating group when compared with the participating group were higher and demonstrated higher odds ratios (ORs) for 30-day inpatient readmissions (nonparticipating group 106/2636, 4.02% and participating group 54/2048, 2.64%; OR 1.48, 95% CI 1.03 to 2.13; P=.04), 60-day inpatient readmissions (nonparticipating group 194/2636, 7.36% and participating group 85/2048, 4.15%; OR 1.79, 95% CI 1.32 to 2.39; P<.001), and 90-day inpatient readmissions (nonparticipating group 261/2636, 9.90% and participating group 115/2048, 5.62%; OR 1.81, 95% CI 1.40 to 2.34; P<.001). The length of stay for the nonparticipating cohort was longer at 1.90 days, whereas the length of stay for the participating cohort was 1.50 days (mean 1.87, SD 2 vs mean 1.50, SD 1.37; P<.001). Patients treated by participating surgeons received and read text messages using mHealth 83% of the time and read emails 84% of the time. Patients responded to 60% of the text messages and 53% of the email surveys. Patients were least responsive to digital monitoring questions when the hospital asked them to do something, and they were most engaged with emails that did not require action, including informational content. A total of 96% (558/580) of patients indicated high satisfaction with using mHealth technology to support their care. Only 0.40% (75/2059) patients opted-out of the mHealth technology program after enrollment.

conclusionsA novel, multicomponent, pathway-driven, patient-facing mHealth technology can positively impact patient outcomes and patient-reported experiences. These technologies can empower patients to play a more active and meaningful role in improving their outcomes. There is a deep need, however, for a better understanding of the interactions between patients, technology, and health care providers. Future research is needed to (1) help identify, address, and improve technology usability and effectiveness; (2) understand patient and provider attributes that support adoption, uptake, and sustainability; and (3) understand the factors that contribute to barriers of technology adoption and how best to overcome them.

Indexed as

TelemedicineAgedBiomedical TechnologyFemaleHumansMaleRetrospective StudiesTechnologycommunication programshospital staylength of staymHealthpatient activationpatient-centered carepatient empowermentpatient engagementpatient involvementpatient satisfaction

Identifiers

PMID32589161
PMCPMC7381069

What OpenQuestion holds

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LicenceCC BY
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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.