The Epital Care Model: A New Person-Centered Model of Technology-Enabled Integrated Care for People With Long Term Conditions
Bibliographic record
Abstract
BACKGROUND: There is worldwide recognition that the future provision of health care requires a reorganization of provision of care, with increased empowerment and engagement of patients, along with skilled health professionals delivering services that are coordinated across sectors and organizations that provide health care. Technology may be a way to enable the creation of a coherent, cocreative, person-centered method to provide health care for individuals with one or more long-term conditions (LTCs). It remains to be determined how a new care model can be introduced that supports the intentions of the World Health Organization (WHO) to have integrated people-centered care. OBJECTIVE: To design, pilot, and test feasibility of a model of health care for people with LTCs based on a cocreative, iterative, and stepwise process in a way that recognizes the need for person-centered care, and embraces the use of digital technology. METHODS: The overall research method was inspired by action research and used an agile, iterative approach. In 2012, a living lab was established in a Danish municipality which allowed for the freedom of redesigning health care processes. As the first step, a wide group of stakeholders was gathered to create a layout for the reorganization of services and development of technology, based on established principles for innovative management of people with chronic conditions. The next three steps were (1) a proof of concept in 2012, (2) a pilot study, and (3) a feasibility study from 2013 to 2015, in which a total of 93 chronic obstructive pulmonary disease (COPD) patients were enrolled. Citizens were provided a tablet-based solution for remote follow-up and communication purposes, and access to a 24/7 response and coordination center that coordinated both virtual and face-to-face support for COPD management. In step five the initial model was extended with elements that support continuity of care. Beginning in the autumn of 2013, 1102 frail elderly individuals were included and offered two additional services: an outgoing acute medical team and a local subacute bed function. RESULTS: Based on the findings from the iterative process, and evolving technology and workflow solutions, we propose a robust and feasible model that can provide a framework for developing solutions to support an active life with one or more LTCs. The resulting Epital Care Model (ECM) consists of six stages, and serves as a template for how a digitally-enhanced health service can be provided based on patients' medical needs. The model is designed to be a proactive, preventive, and monitoring health care system that involves individuals in the management of their own health conditions. CONCLUSIONS: The ECM is in accordance with WHO's framework for integrated people-centered health services, and may serve as a framework for the development of new technologies and provide a template for future reorganization.
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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".