Capturing the Impact of Patient Portals Based on the Quadruple Aim and Benefits Evaluation Frameworks: Scoping Review
Bibliographic record
Abstract
BACKGROUND: Despite extensive and continuing research in the area of patient portals, measuring the impact of patient portals remains a convoluted process. OBJECTIVE: This study aims to explore what is known about patient portal evaluations and to provide recommendations for future endeavors. The focus is on mapping the measures used to assess the impact of patient portals on the dimensions of the Quadruple Aim (QA) framework and the Canada Health Infoway's Benefits Evaluation (BE) framework. METHODS: A scoping review was conducted using the methodological framework of Arksey and O'Malley. Reporting was guided by the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) extension for scoping reviews. A systematic and comprehensive search was conducted using the Ovid platform, and the following databases were searched: Ovid MEDLINE (R) ALL (including epub ahead of print, in-process, and other nonindexed citations), EMBASE, and PsycINFO. CINAHL on the EBSCO platform and Web of Science were searched for studies published between March 2015 and June 2020. A systematic gray literature search was conducted using the Google search engine. Extracted data were tabulated based on a coding template developed to categorize the literature into themes and areas of interest. RESULTS: A total of 96 studies were included for data extraction. The studies were categorized based on the QA dimensions, with strict adherence to the definitions for each dimension. From the patients' perspective, it was determined that most evaluations focused on benefits and barriers to access, access to test results, medication adherence, condition management, medical notes, and secure messaging. From the population perspective, the evaluations focused on the increase in population outreach, decrease in disparities related to access to care services, and improvement in quality of care. From the health care workforce perspective, the evaluations focused on the impact of patients accessing medical records, impact on workflow, impact of bidirectional secure messaging, and virtual care. From the health system perspective, the evaluations focused on decreases in no-show appointments, impact on office visits and telephone calls, impact on admission and readmission rates and emergency department visits, and impact on health care use. Overall, 77 peer-reviewed studies were mapped on the expanded version of the BE framework. The mapping was performed using subdimensions to create a more precise representation of the areas that are currently explored when studying patient portals. Most of the studies evaluated more than one subdimension. CONCLUSIONS: The QA and BE frameworks provide guidance in identifying gaps in the current literature by providing a way to show how an impact was assessed. This study highlights the need to appropriately plan how the impact will be assessed and how the findings will be translated into effective adaptations.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.097 | 0.339 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.031 | 0.029 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".