Evidence map›Paper›PMID 26367235›Full record

ReviewBone marrow transplantation2016

Next-generation long-term transplant clinics: improving resource utilization and the quality of care through health information technology.

M J Rioth, J Warner, B N Savani, M Jagasia

Abstract readReview
In one paragraph

Review in Bone marrow transplantation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Artificial Intelligence Approaches in Hematopoietic Cell Transplantation: A Review of the Current Status and Future DirectionsTurkish journal of haematology : official journal of Turkish Society of Haematology · 2018
    Review
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

M J RiothDivision of Hematology/Oncology, Vanderbilt University Medical Center, Nashville, TN, USA.
J WarnerDivision of Hematology/Oncology, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID http://orcid.org/0000-0002-2851-7242
B N SavaniDivision of Hematology/Oncology, Vanderbilt University Medical Center, Nashville, TN, USA.
M JagasiaDivision of Hematology/Oncology, Vanderbilt University Medical Center, Nashville, TN, USA.

Funding

Vanderbilt Biomedical Informatics Training ProgramT15LM007450 · NLM · VANDERBILT UNIVERSITY · PI Jessica S. Ancker, Bradley A. Malin · 2002 to 2026
$19.7M
NLM NIH HHS T15 LM007450
6 · The paper itself

Abstract

By the year 2020, potentially one-half a million hematopoietic cell transplant (HCT) recipients will need long-term follow-up care to address not only chronic GvHD but also multiple other late consequences of transplant. Despite this increase in patients, there will not be a concomitant increase in the HCT workforce. Thus, the future of long-term patient management will require a new 'next-generation' clinical model that utilizes technological solutions to make the care of the HCT patient efficient, safe and cost-effective. Guideline-based decision support will be embedded in clinical workflows. Documentation requirements will be reduced as automated data collection from electronic medical records (EMRs) will populate registries and provide feedback for a rapid learning health system. Interoperable EMRs will disseminate treatment protocols to multiple care providers in a distributed long-term clinic model, such that providers outside of the transplant center can provide services closer to the patient. Patients will increase their participatory role through patient portals and mobile devices. At Vanderbilt, we have responded to some of these future challenges by embedding guideline-based decision support, structuring clinical documentation and being early adopters of communication technology. This manuscript describes the current state of some of these innovations, and a vision for the future of the long-term transplant clinic.

Indexed as

Hematopoietic Stem Cell TransplantationMedical InformaticsQuality of Health CareAllograftsHigh-Throughput Nucleotide SequencingHumans

Identifiers

PMID26367235
PMCPMC4915825

What OpenQuestion holds

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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.