This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
Personal electronic health records (PEHRs) allow patients to view, generate, and manage their personal and medical data that are relevant across illness episodes, such as their medications, allergies, immunizations, and their medical, social, and family health history. Thus, patients can actively participate in the management of their health care by ensuring that their health care providers have an updated and accurate overview of the patients’ medical records. However, the uptake of PEHRs remains low, especially in terms of patients entering and managing their personal and medical data in their PEHR.
This scoping review aimed to explore the barriers and facilitators that patients face when deciding to review, enter, update, or modify their personal and medical data in their PEHR. This review also explores the extent to which patient-generated and -managed data affect the quality and safety of care, patient engagement, patient satisfaction, and patients’ health and health care services.
We searched the MEDLINE, Embase, CINAHL, PsycINFO, Cochrane Library, Web of Science, and Google Scholar web-based databases, as well as reference lists of all primary and review articles using a predefined search query.
Of the 182 eligible papers, 37 (20%) provided sufficient information about patients’ data management activities. The results showed that patients tend to use their PEHRs passively rather than actively. Patients refrain from generating and managing their medical data in a PEHR, especially when these data are complex and sensitive. The reasons for patients’ passive data management behavior were related to their concerns about the validity, applicability, and confidentiality of patient-generated data. Our synthesis also showed that patient-generated and -managed health data ensures that the medical record is complete and up to date and is positively associated with patient engagement and patient satisfaction.
The findings of this study suggest recommendations for implementing design features within the PEHR and the construal of a dedicated policy to inform both clinical staff and patients about the added value of patient-generated data. Moreover, clinicians should be involved as important ambassadors in informing, reminding, and encouraging patients to manage the data in their PEHR.
The beginning of most outpatient consultations is characterized by physicians going over the personal and medical information that is recorded in their patients’ personal electronic health records (PEHRs). This includes information about their patients’ current health problems and information about their vital signs, medication use, or known allergies. An up-to-date and accurate overview of this personal and medical information gives physicians a better sense of who is sitting in front of them and allows them to make appropriate and safe treatment-related decisions that correspond to their patients’ needs. In most cases, clinicians are responsible for updating their patients’ personal and medical data at the start of each consultation. However, this task can take up to 40% of the physicians’ time, which would rather be spent on direct patient care [
Over the past decade, identifying what determines whether patients are likely to engage with their PEHRs and how their engagement affects their clinical care has been a frequent topic of discussion [
Although previous syntheses of the literature have been valuable in identifying the scope and potential causes of patients’ disengagement [
To identify what may drive patients toward or prevent patients from taking on an active rather than a passive role when it comes to the management of their core medical data, we need to identify not only the type of data management activities patients perform within their portal but also the type of data that patients manage and how frequently they do so. Patients can engage differently with their PEHR depending on the personal and medical data they wish to share or update. Patients may be less inclined to share or update information about error-prone and sensitive data elements than to share or update personal and medical data that they are more confident or knowledgeable about. To date, it remains unknown whether the type of core medical information affects patients’ personal data management.
Active patient engagement in terms of patients generating and managing their personal and medical data throughout their care journey. This figure was partially replicated and adapted from Carman et al [
In this scoping review, we aimed to address the limitations of previous syntheses by exploring the barriers and facilitators that patients face when they decide to actively review, enter, update, or modify their core medical data in their PEHR throughout their care journey (
This scoping review was conducted and reported in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews [
Selection checklist for full articles.
Item | Inclusion | |
|
||
|
Type of publication | Practice briefs, fact sheets, white papers, and peer-reviewed publications and conference proceedings. Exclude when the articles are systematic or scoping reviews; meta-analyses |
|
Date of publication | Between 2000 and February 2020; MEDLINE: re-searched in March 2022 |
|
||
|
Type of study or intervention | All types of studies are allowed to be included in this review (eg, randomized controlled trial, nonrandomized controlled trial, evaluation/usability, experimental, cohort/longitudinal, developmental, and pre-post design) |
|
Type of health data being managed | Core medical data being managed in a personal electronic health record (eg, medication regimen, vaccinations, allergies, medical and family history, and intoxications) |
|
Population | Both patients and clinicians |
The flowchart for the inclusion of articles in the scoping review is presented in
Flowchart for the identification, screening, and inclusion of articles in this scoping review. PGHD: patient-generated health data; PEHR: personal electronic health record.
The general characteristics of the 37 included records are presented in
Study characteristics of the records included in the scoping review.
Number | Study | Country | Study aim | Sample | Type of data | Data activity | Portal | Data entry tools |
1 | Ali et al [ |
United States | Evaluating the usability of a portal | Patients or caretakers of patients (n=23) with chronic conditions (diabetes, cancer, ulcerative colitis, or thalassemia) | Medical history | Reviewing and entering data | myNYP | None |
2 | Ancker et al [ |
United States | Describing portal adoption rates and characteristics of patients who enter health data and their association with clinical outcomes | Patients with diabetes (n=53), of which 23 were pregnant and 30 were nonpregnant, and their physicians in obstetrics-gynecology (n=12) or internal medicine (n=4) | Blood glucose values | Entering data | Weill Cornell Connect (EpiCare) | None |
3 | Arsoniadis et al [ |
United States | Evaluating the quality of patient-generated health data with a health history tool accessible via the web or a tablet | Patients (n=146) with an appointment at a surgery clinic, of whom 50 completed the intervention | Medical history, surgical history, and social history (including questions related to tobacco use, alcohol consumption, illicit substance use, and sexual history) | Entering data | EpiCare | Questionnaires |
4 | Bajracharya et al [ |
United States | Evaluation of the family history module implemented in a patient portal and patients’ adoption of and experiences with the module | Patients (n=4223) | Family health history | Reviewing and entering and modifying data | PatientSite (electronic medical record of the Beth Israel Deaconess Medical Center) | Questionnaires |
5 | Bryce et al [ |
United States | Exploring the usability of patient portal features and users’ intentions to pay fees for portal use for a diabetes management portal | Patients (n=39) with diabetes, with 21 patients allocated to the preportal group and 18 to the portal users group | Vital signs (blood glucose values) | Entering data | HealthTrak | Calculator |
6 | Chrischilles et al [ |
United States | Exploring how patient-generated health data affects medication use safety among older adults | Nonclinical population (n=1075) with variety in medical backgrounds; most participants were experiencing stomach-related problems; 802 participants were allocated to use a patient portal, and 273 were allocated to a control group | List of allergies, medication list, problem list, and medical history | Entering data | Iowa PHRa (stand-alone patient portal) | None |
7 | Cohn et al [ |
United States | Evaluating the usability and analytic validity of the Health Heritage tool that helps patients to collect their family health history | Mixture of nonclinical and clinical participants (n=109), of which 54 were allocated to the intervention arm (Health Heritage) and 55 to the usual care arm | Family health history | Entering data | Health Heritage (stand-alone tool) | None |
8 | Polubriaginof and Pastore [ |
United States | Comparing the accuracy and completeness of a tablet-administered problem list questionnaire to a problem list that was self-reported by patients | Patients with variety in medical backgrounds (n=1472); details were given for patients with hypercholesterolemia and diabetes | Problem list, medical history, family health history, and risk factors | Entering data | LMRb | Tablet questionnaire administered via the Hughes RiskApps life cycle cost software |
9 | Dullabhet et al [ |
United States | Exploring how patients can be engaged to provide feedback on electronic health record content and how this feedback affects the accuracy of medical records | Patients (n=457) with chronic conditions (obstructive pulmonary disease, asthma, hypertension, diabetes, or heart failure); the number of providers and pharmacists interviewed is not provided | Medication list | Reviewing and modifying data | MyGeisinger (Geisinger Health System) | Web-based feedback forms |
10 | Eschler et al [ |
United States | Exploring the usability of a patient portal, whether and how it helps patients to remember important health tasks, and whether it enhances patient engagement and agency in managing a chronic illness | Patients with diabetes and parents managing asthma for child dependents (n=19) | Immunization record | Reviewing and entering data | Three paper prototypes that represented features of a regional health cooperative portal’s interface were used | None |
11 | Hanauer et al [ |
United States | Exploring the frequency, type, reasons, and outcomes of patient-initiated amendment requests | Patients (n=181) for whom amendment requests were made to various clinical departments and divisions but whose medical conditions were unspecified | Medical history, social history, intoxications, family health history, clinic notes, discharge summaries, and emergency department notes | Reviewing and modifying data | MyChart (Epic) | To initiate a chart amendment request, the patient had to contact the information management department by phone, by mail, fax or in person and obtain an amendment request form |
12 | Heyworth et al [ |
United States | Testing a medication reconciliation tool to improve medication safety among patients who were recently discharged from the hospital | Patients (n=25) with chronic conditions (eg, diabetes, hypertension, prior myocardial infarction or stroke, hyperlipidemia, and heart disease) | Medication list | Reviewing and entering and modifying data | My HealtheVet (The Veterans Health Administration) | Secure Messaging for Medication Reconciliation Tool within the portal |
13 | Hill et al [ |
United States | Exploring health care providers perceived advantages and disadvantages of PHR portal use | Health care providers (n=26) who treat patients with spinal cord injuries and disorders | Vital signs (blood pressure, pulse rate, and weight), medical history, immunization record, and medication list | Reviewing and entering data | My HealtheVet (The Veterans Health Administration) | None |
14 | Laranjo et al [ |
Portugal | Examining portal use, associated patient demographics, and clinical variables | Patients (n=109,619), of whom 18,504 were portal users | Vital signs (height, weight, blood pressure, glycemia, cholesterol, and triglycerides levels) and allergies | Entering data | Tethered PHR provided by the National Health Service | None |
15 | Lemke et al [ |
United States | Exploring primary care physicians’ experiences with the Genetic and Wellness Assessment tool for capturing patients’ family health history | Health care providers (n=24) who specialized in internal medicine, family medicine, or obstetrics/gynecology | Family health history | Entering data | Epic | Genetic and Wellness Assessment tool |
16 | Lesselroth et al [ |
United States | Exploring the extent to which kiosk technology improves the reporting of patients’ medication history | Patients (n=17,868) visiting a chemotherapy facility | Medication list and list of allergies | Reviewing and entering and modifying data | See Data Entry Tools | Automated Patient History Intake Device accessed via computer terminal kiosk in the clinical waiting room |
17 | Murray et al [ |
United States | To examine the capacity of 3 different electronic tools for collecting patients’ family health history | Patients (n=959) scheduled for an annual examination visit, of which 663 were allocated to the intervention arms (interactive voice response technology, patient portal, and waiting room laptop computer) | Family health history | Reviewing and entering data | Patient Gateway, LMR | The Surgeon General: My Family Health Portrait |
18 | Nagykaldi et al [ |
United States | Examining the behavior and experiences of patients and primary care clinicians with regard to the Wellness Portal | Patients in primary care (n=560) who were in the randomized controlled trial; 3 clinicians, 2 office staff, and 6 patients in the pilot testing of the portal | Vital signs (weight), preventive services (mammography, diabetes education, and smoking counseling), wellness plan, symptom diary, medical history, medication list, problem list, list of allergies, and immunization record | Reviewing and entering data | Wellness Portal linked to the Preventive Services Reminder System | None |
19 | Nazi et al [ |
United States | Exploring Veterans’ perspectives on receiving access to their personal medical information, which of its data elements they find most valuable, and how it affects their satisfaction, self-management, communication, and health care quality | Military service Veterans in the United States (n=688) | Medication list, list of allergies, and vital signs (eg, blood pressure, blood sugar, and cholesterol) | Entering data | MyHealth |
None |
20 | Park et al [ |
Korea | Evaluating how and which users are generating and managing their personal and medical data | Patients with diabetes (n=16,729) and general users of the app (n=1536) | Vital signs (blood pressure, blood glucose levels, and weight); the functions list of allergies, medical history, and medication list were excluded because the number of users was relatively small (n=116) | Entering data | Mobile PHR known as My Chart in My Hand | None |
21 | Powell and Deroche [ |
United States | Exploring the determinants of portal use among patients with multiple chronic conditions | Patients with multiple morbidities (n=500) with diabetes, heart failure, hypertension, and coronary artery disease | Vital signs (eg, weight and blood pressure) | Entering data | FollowMyHealth (AllScripts) | None |
22 | Prey et al [ |
United States | Exploring the extent to which an electronic home medication review tool engaged patients in the medication reconciliation process and how this affected medication safety during hospitalization | Patients (n=65) arriving at the emergency department and their health care providers (n=20) | Medication list | Reviewing and entering and modifying data | AllScripts | Internally developed home medication review tool |
23 | Raghu et al [ |
United States | Exploring the extent to which secure messaging helps patients to update their medication list in an ambulatory care setting | Patients (n=18,702) of a clinical practice that focused on surgical care for adults, of which 7818 had portal access | Medication list | Reviewing and entering data | Not specified | A secure messaging feature (alongside phone calls) was used by patients to update their medication list |
24 | Schnipper et al [ |
United States | Investigating the extent to which a PHR-linked medications review module affects medication accuracy and safety | Patients in primary care (n=541), of which 267 were in the intervention arm | Intervention arm: medication list, list of allergies, and diabetes management information; control arm: family health history | Reviewing and modifying data | Patient Gateway, LMR | Patient Gateway medications module; electronic journals |
25 | Seeber et al [ |
Germany | Validating the accuracy of VaccApp in helping parents to report their children’s vaccine history | Parents (n=456) of infants and children with suspected vaccine-preventable diseases (eg, influenza-like illness or infections of the central nervous system) | Immunization record | Reviewing and entering data | Vaccination app (VaccApp) | None |
26 | Sun et al [ |
United States | Exploring how patients with type 2 diabetes use their patient portals and what determines their portal use | Parents (n=456) of children with diabetes, of which 178 used the app | Medication list, list of allergies, and medical history | Reviewing and entering data | Epic | Questionnaire for recording medical history |
27 | Tsai et al [ |
United States | Exploring the characteristics of portal users and the activities that users perform within their patient portals | Patients (n=505,503), of which 109,200 were registered for a portal | Problem list, medication list, and list of allergies | Reviewing and entering and modifying data | MyChart (Epic) | None |
28 | Wald et al [ |
United States | Exploring patients’ and health care providers’ experiences of using previsit electronic journals to record core medical data and survey data | Patients in primary care (n=2027 in the intervention arm and n=2345 in the postintervention survey) and 84 physicians | Arm 1: medication list, list of allergies, and diabetes items; arm 2: health maintenance, personal history, and family health history | Reviewing and entering and modifying data | Patient Gateway, LMR | Previsit electronic journals with tailored and untailored questions |
29 | Yu et al [ |
United States | Exploring and identifying the needs and preferences of individuals with dexterity impairments when they use iMHere. | Patients with dexterity impairments (n=9) | Medication list and problem list | Entering reasons for taking medication and modifying medication reminders | Interactive mobile health and rehabilitation apps. iMHere is a system that connects smartphone apps to clinicians’ web-based portal. | MyMeds app (medication management) and SkinCare app (monitoring and reporting skin breakdown) |
30 | Zettel-Watson and Tsukerman [ |
United States | Exploring the use patterns among users of web-based health management tools and identifying barriers to use among nonusers | Nonclinical population (n=166) | Vital Signs (cholesterol, blood pressure, and glucose levels; uploading data from a monitoring device) | Reviewing and entering data | Most participants used tools provided by their physician’s office, hospital, or insurance company (type of records unspecified) | None |
31 | Siek et al [ |
United States | Testing the usability of an open source, web-based personal health app that provides older adults and their caregivers the ability to manage their personal health information during care transitions | Older adult patients with multiple morbidities (n=31) | Medication list | Reviewing and entering data | Colorado Care Tablet, personal health app | Pharmacy fulfillment and barcode scanning and a Prepare For Appointments wizard |
32 | Lober et al [ |
United States | Exploring the barriers that older adults and disabled persons face when using PHRs | Nonclinical population (n=38) specified as low-income older adults with disabilities residing in a publicly subsidized housing project | Family health history, list of allergies, medication list, medical history, and immunization record | Reviewing and entering and modifying data | Personal Health In- formation Management System | A nurse was available to help with data entry |
33 | Arar et al [ |
United States | To assess the facilitators of and barriers to Veterans’ use of the Surgeon General’s web-based tool to capture their family health history | Veterans (n=35) | Family health history | Entering data | My HealtheVet (The Veterans Health Administration) | The Surgeon General: My Family Health Portrait |
34 | Wu et al [ |
United States | Assessing the content and quality of the MeTree family health history tool | Patients in primary care (n=1184) | Family health history | Entering data | MeTree | None |
35 | Cimino et al [ |
United States | Exploring patients’ portal use, the cognitive effects of portal use and how it affects the patient–health care provider relationship | Patients (n=12) and health care providers (n=3) | Vital signs (height, weight, blood pressure, pulse, and temperature) and diabetes diary | Reviewing and entering data | Patient Clinical Information System, New York Presbyterian Hospital clinical data repository | None |
36 | Witry et al [ |
United States | Exploring family practice physician and staff views on the (dis)advantages of PHR use | Health care providers (n=28) of a family medicine department | Medical history, medication list, and vital signs (blood pressure and glucose levels) | Entering data | Not specified | None |
37 | Kim and Johnson [ |
United States | Exploring whether and how different types of data entry methods used by PHRs affect the accuracy of patient-generated data | Patients with disorders requiring treatment with thyroid hormone preparations (n=14) | Problem list and medication list | Reviewing and entering data | Password- protected website used to test data entry methods | Free-text entry (recall or abstraction) and selection methods |
aPHR: patient health record.
bLMR: longitudinal medical record.
Categorization of patient management papers and study type (N= 37).
Categories | Recordsa, n (%) | Study types and references | |||
Frequency of portal use | 27 (73) |
Observational [ Content analysis [ RCTb [ RTc [ NRTd [ Cohort [ Interview [ Usability [ Survey [ |
|||
|
|||||
|
Patient-related | 33 (89) |
Observational [ Content analysis [ RCT [ RT [ Cohort [ Interview [ Usability [ Prototype testing [ Survey [ |
||
|
Provider-related | 7 (19) |
Content analysis [ Interview [ RCT [ |
||
|
System-related | 28 (76) |
Observational [ Content analysis [ NRT [ RCT [ Cohort [ Interview [ Prototype testing [ Usability [ Survey [ |
||
Impact on patient care | 26 (70) |
Observational [ RCT [ NRT [ RT [ Cohort [ Interview [ Content analysis [ Usability [ Survey [ |
aThe total number of records exceeds the total number of included studies because records contributed to more than one category.
bRCT: randomized controlled trial.
cRT: randomized trial.
dNRT: nonrandomized trial.
Distribution of the core medical data components managed (entered, updated, and modified) by patients. PEHR: personal electronic health record.
Distribution of core medical data components managed and associated tasks across the included records.
Data component and activity, constrained or unconstrained by task demands | Records, n (%) | References | ||||
|
||||||
|
Constrained | 24 (64.8) | [ |
|||
|
Unconstrained | 13 (35.1) | [ |
|||
|
|
|||||
|
|
Constrained | 12 (32.4) | [ |
||
|
|
Unconstrained | 7 (18.9) | [ |
||
|
|
|||||
|
|
Constrained | 5 (13.5) | [ |
||
|
|
Unconstrained | 8 (21.6) | [ |
||
|
|
|||||
|
|
Constrained | 8 (21.6) | [ |
||
|
|
Unconstrained | 4 (10.8) | [ |
||
|
|
|||||
|
|
Constrained | 10 (27) | [ |
||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 5 (13.5) | [ |
||
|
|
Unconstrained | 6 (16.2) | [ |
||
|
|
|||||
|
|
Constrained | 4 (10.8) | [ |
||
|
|
Unconstrained | 2 (5.4) | [ |
||
|
|
|||||
|
|
Constrained | 5 (13.5) | [ |
||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 0 (0) | — | ||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 1 (2.7) | [ |
||
|
|
Unconstrained | 0 (0) | — | ||
|
|
|||||
|
|
Constrained | 1 (2.7) | [ |
||
|
|
Unconstrained | 0 (0) | — | ||
|
|
|||||
|
|
Constrained | 1 (2.7) | [ |
||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|
||||
|
|
Constrained | 1 (2.7) | [ |
||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 0 (0) | — | ||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
||||||
|
Constrained | 8 (21.6) | [ |
|||
|
Unconstrained | 2 (5.4) | [ |
|||
|
|
|||||
|
|
Constrained | 7 (18.9) | [ |
||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 2 (5.4) | [ |
||
|
|
Unconstrained | 0 (0) | — | ||
|
|
|||||
|
|
Constrained | 2 (5.4) | [ |
||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 4 (10.8) | [ |
||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 4 (10.8) | [ |
||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 0 (0) | — | ||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 1 (2.7) | [ |
||
|
|
Unconstrained | 0 (0) | — | ||
|
|
|||||
|
|
Constrained | 0 (0) | — | ||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 0 (0) | — | ||
|
|
Unconstrained | 1 (2.7) | [ |
||
|
|
|||||
|
|
Constrained | 0 (0) | — | ||
|
|
Unconstrained | 1 (2.7) | [ |
Of the 37 included studies, 23 (62%) provided information about the frequency of patients’ portal uptake [
We categorized the facilitators and barriers associated with patients actively managing their core medical data through a patient portal into one of the three categories: those dealing with patient characteristics, those dealing with health care provider characteristics, or those dealing with system characteristics. A brief overview of how the important factors affecting patients’ personal data management are related to each other is presented in
Patient-related, health care provider–related, and system-related factors affecting patients’ management of their personal and medical data.
We identified the following 6 themes that determined whether patients entered, updated, or modified their core medical data: patient demographics; digital and health literacy; concerns related to the accuracy, validity, privacy
There is little consensus on whether and how a patient’s age or sex influence active data management. While 6 retrospective studies indicated that younger patients are more likely to manage their core medical data [
A total of 5 (13.5%) retrospective studies showed that compared with inactive or less active users, active portal users are more likely to be privately insured [
Limited internet or computer access, digital illiteracy, and computer anxiety are barriers to patients entering and modifying their core medical data electronically [
An interesting factor that might explain whether patients manage their core medical data is their belief and reassurance that they are not bypassing clinical staff by directly entering or modifying their data in their record [
Concerns about data loss and breach of privacy further prevent patients from maintaining their medical records electronically [
(Mis)conceptions about the applicability and usefulness of patient-generated health data may also prevent patients from taking on a more active role in the management of their personal and medical data via a PEHR. As was mentioned by interviewed patients [
Encouraged use by health care providers and the patient-clinician relationship are identified as the 2 important factors determining whether patients actively manage their core medical data. However, we noticed that health care professionals’ recommendations to use the system are dependent on whether they believe that there are benefits associated with patient-entered data in terms of data quality and reliability and cost-effectiveness.
Being encouraged by health care providers to manage core medical data plays an important role in the adoption and continued use of PEHRs among patients. First, in both a qualitative content analysis of patient-initiated amendment requests [
We identified several beliefs that health care providers have about patient-generated and patient-managed medical data that may determine whether they are likely to encourage or assist their patients in managing their core medical data in their PEHR. First, health care providers are often unaware of the benefits that are associated with patients’ management of their own data [
Patients testing a medication reconciliation tool via a secure messaging feature within the portal indicated that they appreciated the possibility of communicating directly with health care providers when they had questions about their medications or wanted to request refills. Most (90%) users said they would use the tool again, frequently emphasizing how it allowed them to have instant access to their health care provider [
Patients’ satisfaction with the system used to collect and maintain their core medical data is an important factor that stimulates active data management [
A total of 4 studies stressed the importance of offering a level of customization to patient portals [
Patients’ (continued) use of their electronic patient portal to generate and update their core data depends on the perceived complexity and thus the usability of the system or tools used [
Unless patients are being asked to enter information about simple diagnoses or prescriptions, systems should use guided entry of data elements [
Implementing visual feedback facilitates data entry by patients and patients’ satisfaction with using the system. For instance, providing medication pictures alongside a selected medication assists patients’ medication reconciliation [
If reminded to do so, patients are more likely to use the portal before and after their outpatient visits [
Providing applications without charge [
This section describes the impact of patients’ data management on the quality and safety of patient care, psychological outcomes for patients, patient engagement, patient satisfaction, and clinical workflow.
Impact of patient-generated health data (PGHD) on patients’ health and health care–related services and how this impact is associated with the important concerns regarding PGHD raised by patients and health care providers.
Clinicians’ concerns about the quality and validity of patient-entered data seem to be unfounded. Observational [
Another theme we identified was a significant objective [
Insight into medical data might reduce anxiety and uncertainty in patients. This point was explicitly raised by interviewed health care providers who were evaluating a tool that helped the patients under their care to report on their family health history to identify possible genetic diseases [
We identified two themes in this subsection: (1) the extent to which patients’ data management improves patient-physician discussions and (2) feelings of ownership among patients and future patient participation.
Patients who update their core medical data before an outpatient visit, feel better informed [
Patients who generate and manage their own medical data feel that they have more control over their health care and health-related decisions [
Patients were generally satisfied with the tools that they used to update their medical data [
A study that interviewed health care providers who treated patients with spinal cord injuries and disorders found that health care providers believed that patient-generated health data collected via patient portals can improve the coordination of medical care, especially for those patients who receive health care in nonclinical settings [
We identified only 4 records that objectively measured the cost-effectiveness of patients’ data management. A retrospective cross-sectional study investigating the impact of patients updating their medication list via a secure message feature showed that its use did not significantly decrease the cost burden of outpatient clinics [
This synthesis of literature explored the barriers and facilitators that patients face when they decide to generate and manage their core medical data in (tools linked to) their PEHRs. First, we found that a minority of registered users entered, updated, or modified their personal and medical data. More specifically, less than half of the registered users entered their data and less than a quarter of users updated or modified their already recorded data; continued use further dropped to <10% of the user population as time increased. Patients preferred to take on a passive rather than an active role regarding the self-management of their health information, and they seemed to prefer tracking vital signs above more complex medical information, such as medications and their family health history. We identified both patients’ and health care professionals’ (positive) perceptions about the validity, applicability, and confidentiality of patient-generated data as well as patients’ digital and health literacy as important facilitators of patients’ active management of their personal and medical data. However, we also found that patients’ and health care providers’ concerns about the validity and applicability of patient-generated data seem to be unfounded. Patients accurately reported on their diagnoses, medications, immunizations, medical history, and family health history, making their medical records more complete. Moreover, patients who managed their medical data felt more knowledgeable, more in control of their own health care, and more adherent to their treatment than less active patients. Both patients and clinicians felt that active patients were also more prepared for their clinical visits because they knew which questions they wanted answered by their health care provider. In the following sections, we propose recommendations that health care practices can adopt for stimulating patient participation in the generation and management of their electronic core medical data.
Patients felt that they were bypassing clinical staff when they self-managed their medical data. Patients were concerned that they would provide their physicians with inaccurate information, especially when the nature of the medical information is complex and sensitive. Clear guidelines and information regarding the added value of patient-entered data for both patients and clinicians may reduce these concerns. Clinical staff are important ambassadors for informing their patients about the added value of patient-generated and management data and in reminding and encouraging their patients to prepare themselves for each visit by reviewing the medical data in their PEHRs. Moreover, we also found that self-management of medical data may be higher for those patients who feel that they are able to directly contact their provider for support. Design features within the PEHR systems that amplify the visibility of the health care providers’ availability for support and guidance as well as visual feedback elements in the PEHR system that indicate to the patients that their entered or modified data will be checked by a professional may reassure patients that they are not altering their medical record without their provider’s knowledge or approval.
We also found that patients were generally concerned that their medical data were unprotected against unauthorized access and could, therefore, be used for non–health care–related purposes. Stressing data confidentiality and allowing patients to give their informed consent on an opt-in and opt-out basis may diminish their potential unease about confidentiality. Furthermore, we have also seen that customization features may enhance the self-management of core medical data because they make the system more understandable and easier to use. Helping patients to remember medical information by using prepopulated forms or guided data entry might further aid and encourage them to record information that might be inaccurate. This may also address health care providers’ concerns that patients are not able to accurately report on their medical information.
On the basis of our findings and recommendations, we have outlined several priority questions for future studies (
1. The health care provider as ambassador and gatekeeper
What are the unmet needs of health care professionals with respect to encouraging and supporting their patients to share and manage their personal and medical data during their care journey?
What are the unmet needs of patients in terms of feeling encouraged and supported by their health care providers to share and manage their personal and medical data during their care journey?
2. Ethical and comprehensive by design
What do patients need in terms of assistance, support, and system requirements, to generate and manage their personal data during their care journey?
To what extent does the type of personal and medical data affect patients’ data management?
3. Stimulating the patient-provider partnership
When do patients consider themselves to be “active” managers of their personal and medical data, and to what extent does this correspond to health care professionals’ perspectives?
To what extent do patients’ perspectives on their personal data management activity and role preference affect their data management?
For fear of reporting inadequate information, patients prefer to report their core medical data in a structured, guided manner. Our review showed that this was the case for data that were perceived to be error-prone and sensitive, such as information about the types, names, and dosages of patients’ medications or information about patients’ family health history that would be used for genetic counseling. This finding corresponds to the findings of Esmaeilzadeh et al [
We have also shown that patients prefer to update and monitor data about their vital signs (eg, blood glucose levels and BMI) over updating information about their medications, allergies, intoxications, and social and family history. To the best of our knowledge, no studies to date have examined the reasons for these differences. On the basis of the findings of our review, we hypothesize that patients prefer to manage data about their vital signs to managing information about other core medical data because they are trackable over time and thereby give patients a more direct, visible insight into their health status compared with other core medical data. We encourage future studies to explore this explanation.
We have shown that the number of studies that focus on actual portal use—by exploring how patients use their portal, whether and when patients consider themselves to be active users, which data patients share, and how frequently they do this—remains scarce. Interestingly, it is not common practice for patient data management papers to describe in full detail whether, how, and how frequently and what type of medical information is entered, updated, or modified by patients. We believe that this is mainly caused by an undifferentiated definition of the term “active user.” In the retrieved literature, users were predominantly considered to be active based solely on whether they activated their account [
Our findings are in line with research that has investigated the extent to which patients participate in making decisions together with their physicians regarding treatment plans. Shared decision-making entails the collaborative exchange and discussion of health care information among patients and their health care providers, including information about patient preferences and the pros and cons of all possible treatment options [
This scoping review has some limitations. We retrieved a limited set of highly heterogeneous papers because they provided detailed information about patients’ actual data management activities. Despite the considerable heterogeneity in the study objectives, designs, and outcome measures used in these papers, we were able to identify key themes regarding the facilitators and barriers that patients face when they decide to generate and manage their medical data. In addition, this review concentrated on measurable uses of PEHRs (ie, entering, updating, and modifying data) to identify what stimulates or prevents patients’ use. Although patients who evaluate their core medical data and subsequently decide not to add or modify information are actively engaging with their PEHR, we chose not to include this group because we would then need to rely on log-in frequencies to determine the patients’ (level of) engagement with their health data. Not only may log-in frequencies be biased by false log-in data resulting from log-in problems, but they also do not inform us whether a log-in moment resulted in meaningful use of the portal. A promising endeavor for future studies would be to identify whether and how frequently patients review and approve of the core medical data recorded in their PEHR and which factors contribute to this type of use.
Most patients do not actively review and enter, update, or modify their medical data in a PEHR. Patients refrain from generating and managing their medical data, especially when medical information is complex and sensitive. The reasons for patients’ passive behavior are their concerns about the validity, applicability, and confidentiality of patient-generated data, although we found that patient-generated data are often accurate and helpful in stimulating patient engagement and satisfaction. We have offered recommendations for implementing design features within the (tools linked to) PEHRs and the creation of a dedicated policy to inform both clinical staff and patients about the added value of patient-generated data, with clinicians being involved as important ambassadors in informing, reminding, and encouraging patients to manage the data in their PEHR.
Filled-in PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist [
Search strategy for the MEDLINE, PsycINFO, CINAHL, Cochrane Library, Embase, Web of Science, and Google Scholar databases.
Data extraction form.
personal electronic health record
Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews
This scoping review is part of the research project Patient-Generated Health Data: Engaging Patients to Improve Shared Decision-making and to Optimize Electronic Health Record Content, funded by the We Care partnership between the Tilburg University and the Elisabeth-TweeSteden Hospital in the Netherlands.
All authors contributed to developing the aim of the scoping review and construing the study protocol. DJD took the lead by developing the search strategy, by retrieving and screening the identified records, by analyzing and interpretating the data for the article, and by drafting the first version of the manuscript. GGS, BM, and SP contributed by screening the identified records. All authors proofread the manuscript and approved the final version.
None declared.