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Record W2801232444 · doi:10.2196/medinform.8687

Capturing a Patient-Reported Measure of Physical Function Through an Online Electronic Health Record Patient Portal in an Ambulatory Clinic: Implementation Study

2018· article· en· W2801232444 on OpenAlexvenueno aff
Jing Li, Jinoos Yazdany, Laura Trupin, Zara Izadi, Milena Gianfrancesco, Sarah Goglin, Gabriela Schmajuk

Bibliographic record

VenueJMIR Medical Informatics · 2018
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesAgency for Healthcare Research and QualityNational Institutes of HealthPfizer
KeywordsMedicinePatient portalRheumatologyRheumatoid arthritisAmbulatoryPhysical therapyPatient-reported outcomeInternal medicineDocumentationMEDLINEElectronic health recordHealth careFamily medicineQuality of life (healthcare)Nursing

Abstract

fetched live from OpenAlex

BACKGROUND: Despite significant interest in the collection of patient-reported outcomes to make care more patient-centered, few studies have evaluated implementation efforts to collect patient-reported outcomes from diverse patient populations. OBJECTIVE: We assessed the collection of patient-reported outcomes from rheumatoid arthritis patients in an academic rheumatology clinic, using a paper and an online form through the electronic health record patient portal. METHODS: We identified patients seen between 2012-2016 with ≥2 face-to-face encounters with a rheumatology provider and International Classification of Diseases codes for RA, ≥30 days apart. In 2013, our clinic implemented a paper version of the Patient Reported Outcome Measurement Information System (PROMIS) physical function form that was administered to patients upon their check-in at the clinic. In 2015, an online version of the form became available by way of the electronic health record patient portal to patients with active portal accounts. We compared the proportion of visits with documented PROMIS scores across age, race and ethnicity, and language and examined trends over time using a control chart. RESULTS: We included 1078 patients with rheumatoid arthritis with 7049 in-person encounters at the rheumatology clinic over 4 years, with an average of 168 visits per month. Of the included patients, 80.4% of patients (867/1078) were female and the mean age was 58 (SD 16) years. The overall PROMIS physical function score documentation increased from 60.4% (1081/1791) of visits in 2013 to 74.4% (905/1217) of visits in 2016. Online score documentation increased from 10.0% (148/1473) in 2015 to 19.3% (235/1217) in 2016. African American patients were least likely to have a PROMIS physical function score recorded (55/88, 62.5% compared to 792/990, 80.0% for other racial or ethnic groups; P<.001). Compared with white patients, both African American and Hispanic patients were less likely to have active online electronic health record portal accounts (44/88, 50% and 90/157, 57.3% respectively, compared to 437/521, 83.9% of white patients; P<.001) and, once activated, less likely to use the online survey (6/44, 13.6% and 16/90, 17.8% respectively, compared to 135/437, 30.9% of white patients; P=.02). There was no significant difference in the proportion of any PROMIS physical function forms recorded between non-English vs English preferred patients. No significant differences were found across age or gender. CONCLUSIONS: PROMIS physical function form completion improved overall from 2012-2016 but lagged among racial and ethnic minorities and non-English preferred patients. Future studies should address issues of portal access, enrollment, satisfaction, and persistence and focus on developing PRO implementation strategies that accommodate the needs and preferences of diverse populations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.044
GPT teacher head0.392
Teacher spread0.348 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations17
Published2018
Admission routes1
Has abstractyes

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