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Record W2567712898 · doi:10.2196/resprot.6580

Substitution of Usual Perioperative Care by eHealth to Enhance Postoperative Recovery in Patients Undergoing General Surgical or Gynecological Procedures: Study Protocol of a Randomized Controlled Trial

2016· article· en· W2567712898 on OpenAlexvenueno aff
Eva van der Meij, Judith A.F. Huirne, Esther V.A. Bouwsma, Johanna M. van Dongen, Caroline B. Terwee, Peter M. van de Ven, Chantal M den Bakker, Suzan van der Meij, W.M. van Baal, Wouter K. G. Leclercq, Peggy M. A. J. Geomini, Esther C. J. Consten, Steven E. Schraffordt Koops, P. J. M. van Kesteren, Hein B.A.C. Stockmann, A Dorien ten Cate, P. H. P. Davids, Piet C. Scholten, Baukje van den Heuvel, Frederieke Schaafsma, W. J. H. J. Meijerink, H. Jaap Bonjer, Johannes R. Anema

Bibliographic record

VenueJMIR Research Protocols · 2016
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsnot available
FundersZonMw
KeywordsMedicineRandomized controlled trialProtocol (science)PerioperativeeHealthHealth carePhysical therapyEmergency medicineSurgeryAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Due to the strong reduction in the length of hospital stays in the last decade, the period of in-hospital postoperative care is limited. After discharge from the hospital, guidance and monitoring on recovery and resumption of (work) activities are usually not provided. As a consequence, return to normal activities and work after surgery is hampered, leading to a lower quality of life and higher costs due to productivity loss and increased health care consumption. OBJECTIVE: With this study we aim to evaluate whether an eHealth care program can improve perioperative health care in patients undergoing commonly applied abdominal surgical procedures, leading to accelerated recovery and to a reduction in costs in comparison to usual care. METHODS: This is a multicenter randomized, single-blinded, controlled trial. At least 308 patients between 18 and 75 years old who are on the waiting list for a laparoscopic cholecystectomy, inguinal hernia surgery, or laparoscopic adnexal surgery for a benign indication will be included. Patients will be randomized to an intervention or control group. The intervention group will have access to an innovative, perioperative eHealth care program. This intervention program consists of a website, mobile phone app, and activity tracker. It aims to improve patient self-management and empowerment by providing guidance to patients in the weeks before and after surgery. The control group will receive usual care and will have access to a nonintervention (standard) website consisting of the digital information brochure about the surgical procedure being performed. Patients are asked to complete questionnaires at 5 moments during the first 6 months after surgery. The primary outcome measure is time to return to normal activities based on a patient-specific set of 8 activities selected from the Patient-Reported Outcomes Measurement Information System (PROMIS) physical functioning item bank version 1.2. Secondary outcomes include social participation, self-rated health, duration of return to work, physical activity, length of recovery, pain intensity, and patient satisfaction. In addition, an economic evaluation alongside this randomized controlled trial will be performed from the societal and health care perspective. All statistical analyses will be conducted according to the intention-to-treat principle. RESULTS: The enrollment of patients started in September 2015. The follow-up period will be completed in February 2017. Data cleaning and analyses have not begun as of the time this article was submitted. CONCLUSIONS: We hypothesize that patients receiving the intervention program will resume their normal activities sooner than patients in the control group and costs will be lower. CLINICALTRIAL: Netherlands Trial Registry NTC4699; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4699 (Archived by WebCite at http://www.webcitation.org/6mcCBZmwy).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.189
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.496
Teacher spread0.433 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2016
Admission routes1
Has abstractyes

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