Evidence map›Paper›PMID 28062391›Full record

SynthesisJournal of medical Internet research2017

Personal Health Records: A Systematic Literature Review.

Alex Roehrs, Cristiano André da Costa, Rodrigo da Rosa Righi, Kleinner Silva Farias de Oliveira

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
102citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

102 citing papers in PubMed, 8 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Blockchain Personal Health Records: Systematic Review.Journal of medical Internet research · 2021
    Pooled it
  7. Pooled it
  8. Pooled it
  9. Trial
  10. Effects of a Personal Health Record in Maternity Care: A Stepped-Wedge Trial.International journal of environmental research and public health · 2021
    Trial
  11. Trial
  12. Trial
  13. Trial
  14. Trial
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

42 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Alex RoehrsPrograma de Pós-Graduação em Computação Aplicada, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil.ORCID 0000-0003-0312-1310
Cristiano André da CostaPrograma de Pós-Graduação em Computação Aplicada, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil.ORCID 0000-0003-3859-6199
Rodrigo da Rosa RighiPrograma de Pós-Graduação em Computação Aplicada, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil.ORCID 0000-0001-5080-7660
Kleinner Silva Farias de OliveiraPrograma de Pós-Graduação em Computação Aplicada, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil.ORCID 0000-0003-1891-3580

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInformation and communication technology (ICT) has transformed the health care field worldwide. One of the main drivers of this change is the electronic health record (EHR). However, there are still open issues and challenges because the EHR usually reflects the partial view of a health care provider without the ability for patients to control or interact with their data. Furthermore, with the growth of mobile and ubiquitous computing, the number of records regarding personal health is increasing exponentially. This movement has been characterized as the Internet of Things (IoT), including the widespread development of wearable computing technology and assorted types of health-related sensors. This leads to the need for an integrated method of storing health-related data, defined as the personal health record (PHR), which could be used by health care providers and patients. This approach could combine EHRs with data gathered from sensors or other wearable computing devices. This unified view of patients' health could be shared with providers, who may not only use previous health-related records but also expand them with data resulting from their interactions. Another PHR advantage is that patients can interact with their health data, making decisions that may positively affect their health.

objectiveThis work aimed to explore the recent literature related to PHRs by defining the taxonomy and identifying challenges and open questions. In addition, this study specifically sought to identify data types, standards, profiles, goals, methods, functions, and architecture with regard to PHRs.

methodsThe method to achieve these objectives consists of using the systematic literature review approach, which is guided by research questions using the population, intervention, comparison, outcome, and context (PICOC) criteria.

resultsAs a result, we reviewed more than 5000 scientific studies published in the last 10 years, selected the most significant approaches, and thoroughly surveyed the health care field related to PHRs. We developed an updated taxonomy and identified challenges, open questions, and current data types, related standards, main profiles, input strategies, goals, functions, and architectures of the PHR.

conclusionsAll of these results contribute to the achievement of a significant degree of coverage regarding the technology related to PHRs.

Indexed as

Electronic Health RecordsHealth Records, PersonalInternetHumanselectronic health recordsmobile healthpatient access to recordspersonal health recordstaxonomy

Identifiers

PMID28062391
PMCPMC5251169

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.