| Literature DB >> 31432782 |
Maria M T Vreugdenhil1, Sander Ranke1, Yvonne de Man1, Maaike M Haan1, Rudolf B Kool1.
Abstract
BACKGROUND: In the Netherlands, the health care system and related information technology landscape are fragmented. Recently, hospitals have started to launch patient portals. It is not clear how these portals are used by patients and their health care providers (HCPs).Entities:
Keywords: patient access to records; patient participation; patient portals; professional-patient relations
Mesh:
Year: 2019 PMID: 31432782 PMCID: PMC6788335 DOI: 10.2196/13743
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 7.076
Characteristics of portal users versus nonusers.
| Characteristics | Patients who visited the hospital in 2016 (N=181,679) | Users of the portal (N=24,514) | Nonusers of the portal (N=157,165) | |
| Females, % | 55.90 | 54.80 | 54.49 | .29a |
| Age (years), mean (SD) | 50.4 (19.6) | 50.8 (16.8) | 50.3 (20.0) | <.001b |
| Number of medical specialist trajectories, median (range) | 1 (1-16) | 1 (1-15) | 1 (1-16) | <.001c |
| Number of open diagnoses, median (range) | 1 (0-28) | 2 (0-23) | 1 (0-28) | <.001c |
| Socioeconomic status score, median (range) | 0.19 (−5.38 to 3.02) | 0.26 (−5.38 to 3.02) | 0.18 (−5.38 to 3.02) | <.001c |
aχ2 test.
b2-sample t test.
cKolmogorov-Smirnov test.
Logistic regression analysis for females and males with dependent variable use of the portal.
| Covariates | Model A | Model B | |||||
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| Regression coefficient (SE) | ORa (95% CI) | Regression coefficient (SE) | OR (95% CI) | |||
|
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| Age group 45-75 yearsb | 0.5320 (0.0193) | 1.13 (1.09-1.17) | <.001 | 0.5489 (0.0199) | 1.73 (1.66-1.80) | <.001 |
|
| Age group >75 yearsb | −0.9427 (0.0338) | 0.26 (0.23-0.29) | <.001 | −0.9384 (0.0350) | 0.39 (0.20-0.77) | <.001 |
|
| ≥1 diagnosis | 0.4851 (0.0163) | 2.64 (2.48-2.81) | <.001 | 0.4847(0.0353) | 1.62 (1.51-1.74) | <.001 |
|
| ≥1 medical specialist trajectory | 0.1062 (0.0165) | 1.24 (1.16-1.32) | <.001 | 0.1071 (0.0347)c | 1.11 (1.04-1.19) | .001 |
|
| SESc | 0.1055 (0.0099) | 1.11 (1.09-1.13) | <.001 | 0.1065 (0.0099) | 1.11 (1.09-1.13) | <.001 |
|
| ≥1 medical specialist trajectory, age group 45-75 years | —d | — | — | 0.1487 (0.0376) | 1.16 (1.08-1.25) | <.001 |
|
| ≥1 medical specialist trajectory, age group >75 years | — | — | — | −0.0455 (0.0667) | 0.96 (0.84-1.09) | .47 |
|
| ≥1 diagnosis, age group 45-75 years | — | — | — | −0.1966 (0.0381) | 0.82 (0.76-0.88) | <.001 |
|
| ≥1 diagnosis, age group >75 years | — | — | — | 0.0242 (0.0679) | 1.02 (0.89-1.17) | .65 |
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| Age group 45-75 yearsb | 0.5068 (0.0171) | 1.72 (1.64-1.81) | <.001 | 0.5072 (0.0276) | 1.72 (1.64-1.81) | <.001 |
|
| Age group >75 yearsb | −0.4723 (0.0273) | 0.65 (0.59-0.71) | <.001 | −0.4732 (0.0171) | 0.65 (0.59-0.70) | <.001 |
|
| ≥1 diagnosis | 0.3344 (0.0204) | 1.95 (1.80-2.11) | <.001 | 0.3748 (0.0025) | 1.45 (1.44-1.46) | <.001 |
|
| ≥1 medical specialist trajectory | 0.1958 (0.0205) | 1.48 (1.37-1.60) | <.001 | 0.1558 (0.0250) | 1.12 (1.07-1.18) | <.001 |
|
| SES | 0.1053 (0.0112) | 1.11 (1.09-1.14) | <.001 | 0.1053 (0.0112) | 1.11 (1.09-1.14) | <.001 |
|
| ≥1 medical specialist trajectory, ≥1 diagnosis | — | — | — | 0.0788 (0.0250)c | 1.08 (1.03-1.13) | <.001 |
aOR: odds ratio.
bReference age group <45 years.
cSES: socioeconomic status.
dNot included in model A.
Characteristics of all participants of the qualitative study arms.
| Characteristics | Think-aloud observation participants (N=8) | Focus groups patients (N=12) | Focus groups hospital staff (N=17) | |
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| Male | 5 (63) | 7 (58) | 5 (29) |
|
| Female | 3 (38) | 5 (42) | 12 (71) |
| Age (years), median (range) | 59 (21-71) | 63 (34-79) | 46 (23-64) | |
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| Low | None | None | —a |
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| Medium | 4 (50) | 5 (42) | — |
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| High | 3 (38) | 6 (50) | — |
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| Unknown | 1 (13) | 1 (8) | — |
| Self-reported digital skills (1: very bad, 10: excellent), median (range) | 7 (5-10) | 7 (5-10) | 8 (7-9) | |
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| Medical specialist | — | — | 3 (17) |
|
| Medical specialist in training | — | — | 4 (24) |
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| Nurse | — | — | 4 (24) |
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| Doctor’s assistant | — | — | 1 (6) |
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| Administrative employee | — | — | 3 (18) |
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| Manager | — | — | 2 (12) |
aNot applicable.