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Patient Health Record Systems Scope and Functionalities: Literature Review and Future Directions.

Lina Bouayad1,2, Anna Ialynytchev2, Balaji Padmanabhan3

  • 1Department of Information Systems and Business Analytics, Florida International University, Miami, FL, United States.

Journal of Medical Internet Research
|November 17, 2017
PubMed
Summary

Patient health record (PHR) systems are evolving, incorporating new data types and functionalities like automated assessment. Further research is needed to enhance data quality, integrity, and functionality for improved health outcomes.

Keywords:
data analyticselectronic health recordshealth platformshealth records, personalmedical informaticsmultiorganizational systemspatient-centered carepersonal health record systemsreviewultralarge systems

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Area of Science:

  • Health Informatics
  • Digital Health
  • Patient-Centered Care

Background:

  • Emerging user-centric patient health record (PHR) systems empower patients and enhance provider communication.
  • These systems aim to improve health outcomes and reduce healthcare costs.
  • The evolution of PHRs presents new data and capabilities, offering both opportunities and challenges.

Purpose of the Study:

  • To assess patient health record (PHR) data types and functionalities through a literature review.
  • To inform the health care informatics community.
  • To provide recommendations for PHR design, research, and practice.

Main Methods:

  • Conducted a literature review of PHR data types and functionalities.
  • Searched PubMed, Embase, and MEDLINE databases (1966-2015).
  • Selected 106 articles from 1822 for detailed review of PHR data content.

Main Results:

  • Identified new PHR data sources (e.g., tracking devices) and data types (e.g., time-series data).
  • Demonstrated an evolution in PHR functionalities over time, from data access to automated assessment and prediction.
  • Presented a functional taxonomy and chronological analysis of PHR data types and functionalities.

Conclusions:

  • Improve PHR data quality via patient-centered design and standardized guidelines for patient-generated data.
  • Enhance data integrity by consolidating diverse data types and sources.
  • Advance PHR functionality using novel data analytics and establish metrics for evaluating clinical outcomes and costs.