Evidence map›Paper›PMID 30892274›Full record

ArticleJMIR mHealth and uHealth2019

Development and Implementation of a Person-Centered, Technology-Enhanced Care Model For Managing Chronic Conditions: Cohort Study.

Curtis L Petersen, William B Weeks, Olof Norin, James N Weinstein

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Article
  5. Review
  6. Balancing ideals and realities: health care professionals' perspectives of and attitudes toward digital patient-centered cancer care.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Observational
  14. Article
  15. Analysis of "Journal of diabetes science and technology · 2023
    Article
  16. Article
  17. Review
  18. Article
  19. Computerized migraine diagnostic tools: a systematic review.Therapeutic advances in chronic disease · 2022
    Article
  20. 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

4 authors.

Curtis L PetersenThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States.ORCID 0000-0002-7210-447X
William B WeeksThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States.ORCID 0000-0002-9918-1360
Olof NorinMedical Management Center, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-0199-601X
James N WeinsteinThe Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Lebanon, NH, United States.ORCID 0000-0001-6696-3246

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCaring for individuals with chronic conditions is labor intensive, requiring ongoing appointments, treatments, and support. The growing number of individuals with chronic conditions makes this support model unsustainably burdensome on health care systems globally. Mobile health technologies are increasingly being used throughout health care to facilitate communication, track disease, and provide educational support to patients. Such technologies show promise, yet they are not being used to their full extent within US health care systems.

objectiveThe purpose of this study was to examine the use of staff and costs of a remote monitoring care model in persons with and without a chronic condition.

methodsAt Dartmouth-Hitchcock Health, 2894 employees volunteered to monitor their health, transmit data for analysis, and communicate digitally with a care team. Volunteers received Bluetooth-connected consumer-grade devices that were paired to a mobile phone app that facilitated digital communication with nursing and health behavior change staff. Health data were collected and automatically analyzed, and behavioral support communications were generated based on those analyses. Care support staff were automatically alerted according to purpose-developed algorithms. In a subgroup of participants and matched controls, we used difference-in-difference techniques to examine changes in per capita expenditures.

resultsParticipants averaged 41 years of age; 72.70% (2104/2894) were female and 12.99% (376/2894) had at least one chronic condition. On average each month, participants submitted 23 vital sign measurements, engaged in 1.96 conversations, and received 0.25 automated messages. Persons with chronic conditions accounted for 39.74% (8587/21,607) of all staff conversations, with higher per capita conversation rates for all shifts compared to those without chronic conditions (P<.001). Additionally, persons with chronic conditions engaged nursing staff more than those without chronic conditions (1.40 and 0.19 per capita conversations, respectively, P<.001). When compared to the same period in the prior year, per capita health care expenditures for persons with chronic conditions dropped by 15% (P=.06) more than did those for matched controls.

conclusionsThe technology-based chronic condition management care model was frequently used and demonstrated potential for cost savings among participants with chronic conditions. While further studies are necessary, this model appears to be a promising solution to efficiently provide patients with personalized care, when and where they need it.

Indexed as

AdultAgedChronic DiseaseCohort StudiesDisease ManagementFemaleHumansMaleMiddle AgedMobile ApplicationsPatient-Centered CarePilot ProjectsSelf Carechronic conditionchronic diseasedigital biomarkermHealthmobile healthperson-centered caretelemedicine

Identifiers

PMID30892274
PMCPMC6446154

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.