Are online symptoms checkers useful for patients with inflammatory arthritis?

Powley, Lucy; McIlroy, Graham; Simons, Gwenda; Raza, Karim

doi:10.1186/s12891-016-1189-2

Cited by 79 publications

(84 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…As reported in previous studies [ 25 , 28 ], our work clearly shows that most patients regularly use the internet to retrieve medical information. In a previous study [ 3 ] published in 2016, 47% of the patients consulted the internet to investigate their symptoms. This proportion seems to be increasing, as in our study 67% and in another recent study [ 25 ] 95% of patients stated they did so.…”

Section: Discussionmentioning

confidence: 99%

“…Ideally, mHealth solutions, such as mobile apps and wearable sensors could empower patients, provide individual support, and lead to better outcomes than those available through standard care. Patients with chronic rheumatic diseases already have access to a broad range of mHealth solutions, starting from symptom checkers [ 3 ] or referral tools [ 4 ]. Once a diagnosis is established, mHealth tools enable patients to better monitor their symptoms passively through sensors [ 5 ] and actively by entering data [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study

Knitza¹,

Simón²,

Lambrecht³

et al. 2020

JMIR Mhealth Uhealth

152

119

View full text Add to dashboard Cite

Background Mobile health (mHealth) defines the support and practice of health care using mobile devices and promises to improve the current treatment situation of patients with chronic diseases. Little is known about mHealth usage and digital preferences of patients with chronic rheumatic diseases. Objective The aim of the study was to explore mHealth usage, preferences, barriers, and eHealth literacy reported by German patients with rheumatic diseases. Methods Between December 2018 and January 2019, patients (recruited consecutively) with rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis were asked to complete a paper-based survey. The survey included questions on sociodemographics, health characteristics, mHealth usage, eHealth literacy using eHealth Literacy Scale (eHEALS), and communication and information preferences. Results Of the patients (N=193) who completed the survey, 176 patients (91.2%) regularly used a smartphone, and 89 patients (46.1%) regularly used social media. Patients (132/193, 68.4%) believed that using medical apps could be beneficial for their own health. Out of 193 patients, only 8 (4.1%) were currently using medical apps, and only 22 patients (11.4%) stated that they knew useful rheumatology websites/mobile apps. Nearly all patients (188/193, 97.4%) would agree to share their mobile app data for research purposes. Out of 193 patients, 129 (66.8%) would regularly enter data using an app, and 146 patients (75.6%) would welcome official mobile app recommendations from the national rheumatology society. The preferred duration for data entry was not more than 15 minutes (110/193, 57.0%), and the preferred frequency was weekly (59/193, 30.6%). Medication information was the most desired app feature (150/193, 77.7%). Internet was the most frequently utilized source of information (144/193, 74.6%). The mean eHealth literacy was low (26.3/40) and was positively correlated with younger age, app use, belief in benefit of using medical apps, and current internet use to obtain health information. Conclusions Patients with rheumatic diseases are very eager to use mHealth technologies to better understand their chronic diseases. This open-mindedness is counterbalanced by low mHealth usage and competency. Personalized mHealth solutions and clear implementation recommendations are needed to realize the full potential of mHealth in rheumatology.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study

Knitza¹,

Simón²,

Lambrecht³

et al. 2020

JMIR Mhealth Uhealth

152

119

View full text Add to dashboard Cite

show abstract

“…The internet is an important source of information for both health care professionals and members of the public. Patients often check their symptoms online prior to seeing a rheumatologist [ 21 ]. Symptom checkers represent a professional alternative to search engines.…”

Section: The Value Of Current Symptom Checkers In Rheumatologymentioning

confidence: 99%

“…The use of symptom checkers in rheumatology has been explored only on a minor level. Powley et al [ 21 ] recently evaluated two freely available symptom checkers which included a broad variety of different diseases, and were thus not rheumatology-specific. The study showed that the help-seeking advice and diagnoses given by the symptom checkers tested was frequently inaccurate for rheumatic diseases, correctly identifying inflammatory arthritis in only 4 of 21 (19%) patients.…”

Section: The Value Of Current Symptom Checkers In Rheumatologymentioning

confidence: 99%

Toward Earlier Diagnosis Using Combined eHealth Tools in Rheumatology: The Joint Pain Assessment Scoring Tool (JPAST) Project

Knitza¹,

Knevel²,

Raza³

et al. 2020

JMIR Mhealth Uhealth

Self Cite

View full text Add to dashboard Cite

Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment, and a recognition of the need to monitor response to treatment and to titrate treatments accordingly. Diagnostic delay remains a major challenge for all stakeholders. The combination of electronic health (eHealth) and serologic and genetic markers holds great promise to improve the current management of patients with inflammatory rheumatic diseases by speeding up access to appropriate care. The Joint Pain Assessment Scoring Tool (JPAST) project, funded by the European Union (EU) European Institute of Innovation and Technology (EIT) Health program, is a unique European project aiming to enable and accelerate personalized precision medicine for early treatment in rheumatology, ultimately also enabling prevention. The aim of the project is to facilitate these goals while at the same time, reducing cost for society and patients.

show abstract

“…The approach adopted in other vignettes studies by [3,6,[20][21][22][23][24] has been to determine the percentage of all vignettes for which the app (or tested-GP) provided an appropriate conditionsuggestion -here this analysis method is referred to as the 'required-answer' approach. Results are shown in Fig.…”

Section: Suggested Conditions: the 'Required-answer' Approachmentioning

confidence: 99%

Original research: How accurate are digital symptom assessment apps for suggesting conditions and urgency advice?: a clinical vignettes comparison to GPs

Gilbert¹,

Mehl²,

Baluch³

et al. 2020

Preprint

View full text Add to dashboard Cite

Objectives To compare breadth of condition coverage, accuracy of suggested conditions and appropriateness of urgency advice of 8 popular symptom assessment apps with each other and with 7 General Practitioners.Design Clinical vignettes study.Setting 200 clinical vignettes representing real-world scenarios in primary care.Intervention/comparator Condition coverage, suggested condition accuracy, and urgency advice performance was measured against the vignettes' gold-standard diagnoses and triage level. Primary outcome measuresOutcomes included (i) proportion of conditions "covered" by an app, i.e. not excluded because the patient was too young/old, pregnant, or comorbid, (ii) proportion of vignettes in which the correct primary diagnosis was amongst the top 3 conditions suggested, : medRxiv preprint and, (iii) proportion of "safe" urgency level advice (i.e. at gold standard level, more conservative, or no more than one level less conservative).Results Condition-suggestion coverage was highly variable, with some apps not offering a suggestion for many users: in alphabetical order, Ada: 99.0%; Babylon: 51.5%; Buoy: 88.5%; K Health: 74.5%; Mediktor: 80.5%; Symptomate: 61.5%; Your.MD: 64.5%. The top-3 suggestion accuracy (M3) of GPs was on average 82.1±5.2%. For the apps it was -Ada: 70.5%; Babylon: 32.0%; Buoy: 43.0%; K Health: 36.0%; Mediktor: 36.0%; Symptomate: 27.5%; WebMD: 35.5%;Your.MD: 23.5%. Some apps exclude certain user groups (e.g. younger users) or certain conditions -for these apps condition-suggestion performance is generally greater with exclusion of these vignettes. For safe urgency advice, tested GPs had an average of 97.0±2.5%. For the vignettes with advice provided, only three apps had safety performance within 1 S.D. of the GPs (mean) -Ada: 97.0%; Babylon: 95.1%; Symptomate: 97.8%. One app had a safety performance within 2 S.D.s of GPs -Your.MD: 92.6%. Three apps had a safety performance outside 2 S.D.s of GPs -Buoy: 80.0% (p<0.001); K Health: 81.3% (p<0.001); Mediktor: 87.3% (p=1.3⨉10-3). ConclusionsThe utility of digital symptom assessment apps relies upon coverage, accuracy, and safety. While no digital tool outperformed GPs, some came close, and the nature of iterative improvements to software offers scalable improvements to care.

show abstract

Are online symptoms checkers useful for patients with inflammatory arthritis?

Cited by 79 publications

References 11 publications

Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study

Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study

Toward Earlier Diagnosis Using Combined eHealth Tools in Rheumatology: The Joint Pain Assessment Scoring Tool (JPAST) Project

Original research: How accurate are digital symptom assessment apps for suggesting conditions and urgency advice?: a clinical vignettes comparison to GPs

Contact Info

Product

Resources

About