ArticleEGEMS (Washington, DC)2018
Data Management for Applications of Patient Reported Outcomes.
Article in EGEMS (Washington, DC), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Measuring Multimorbidity: Selecting the Right Instrument for the Purpose and the Data Source.Medical care · 2021Article
- Opportunities and challenges to advance the use of electronic patient-reported outcomes in clinical care: a report from AMIA workshop proceedings.JAMIA open · 2019Article
- Effect of In-Utero Antibiotic Exposure on Childhood Outcomes: Methods and Baseline Data of the Fetal Antibiotic EXposure (FAX) Cohort Study.JMIR research protocols · 2019Article
- Using Self-Reported Data to Segment Older Adult Populations with Complex Care Needs.EGEMS (Washington, DC) · 2019Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
contextPatient reported outcomes (PROs) are one means of systematically gathering meaningful subjective information for patient care, population health, and patient centered outcomes research. However, optimal data management for effective PRO applications is unclear. CASE DESCRIPTION: Delivery systems associated with the Health Care Systems Research Network (HCSRN) have implemented PRO data collection as part of the Medicare annual Health Risk Assessment (HRA). A questionnaire assessed data content, collection, storage, and extractability in HCSRN delivery systems.
findingsResponses were received from 15 (83.3 percent) of 18 sites. The proportion of Medicare beneficiaries completing an HRA ranged from less than 10 to 42 percent. Most sites collected core HRA elements and 10 collected information on additional domains such as social support. Measures for core domains varied across sites. Data were collected at and prior to visits. Modes included paper, clinician entry, patient portals, and interactive voice response. Data were stored in the electronic health record (EHR) in scanned documents, free text, and discrete fields, and in summary databases. MAJOR THEMES: PRO implementation requires effectively collecting, storing, extracting, and applying patient-reported data. Standardizing PRO measures and storing data in extractable formats can facilitate multi-site uses for PRO data, while access to individual PROs in the EHR may be sufficient for use at the point of care.
conclusionCollecting comparable PRO data elements, storing data in extractable fields, and collecting data from a higher proportion of eligible respondents represents an optimal approach to support multi-site applications of PRO information.
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What OpenQuestion holds
Registered trials
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.