Dataset Information

A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses.

ABSTRACT: Patient online health searching is now commonplace, however, the accuracy of patient generated differentials for new symptoms and potential for patient anxiety are concerns. We aimed primarily to determine the accuracy of patient generated differentials for new symptoms with and without online searching, and secondarily, to evaluate the impact of searching on anxiety levels. In the waiting room prior to seeing a clinician, 300 patients with new symptoms were randomly assigned 1:1:1 to Google searching with health related features including a symptom search tool vs Google searching with health related features disabled vs no searching. Participants were 18 years or older and presenting to the emergency department of an urban academic medical center with new low-acuity symptoms that were not due to exacerbation of a chronic condition. Search groups received access on a tablet/smartphone to Google searching with or without health related features. Both search groups could access any websites; health related features led the patient to common diagnoses and physician-validated information. The primary outcome was accuracy of the patient generated differential assessed by matching at least two of the top three diagnoses on the clinician's differential. A secondary outcome was anxiety by a visual analogue scale. Patients were a median of 33.1 (IQI 26.2-45.9) years old, 60% women, 63% black, 82% had a high school education or less, and 45.7% reported having performed an online search prior to presentation. Search group patients spent a median of 3.82 (2.53-5.72) minutes searching online. Similar proportions of patients in each group matched at least two of three clinician diagnoses: 27.0% and 28.3% for Google searching with and without health related features vs 23.8% in the no search group. Patients in the search groups had a similar odds of matching ?2/3 diagnoses as the no search group [OR (95% CI): 1.23 (0.70-2.13), p?=?0.47]. Anxiety was unchanged with online searching. In conclusion, brief online searching in the waiting room did not improve accuracy of patient generated differential diagnoses for new symptoms. The absence of an increase in patient anxiety provides reassurance for subsequent work to refine and investigate online symptom search tools.

SUBMITTER: Martin SS

PROVIDER: S-EPMC6848180 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses.

Martin Seth S SS Quaye Emmanuel E Schultz Sarah S Fashanu Oluwaseun E OE Wang Jane J Saheed Mustapha O MO Prem Ramaswami de Freitas Hermes H Ribeiro-Neto Berthier B Parakh Kapil K

NPJ digital medicine 20191111

Patient online health searching is now commonplace, however, the accuracy of patient generated differentials for new symptoms and potential for patient anxiety are concerns. We aimed primarily to determine the accuracy of patient generated differentials for new symptoms with and without online searching, and secondarily, to evaluate the impact of searching on anxiety levels. In the waiting room prior to seeing a clinician, 300 patients with new symptoms were randomly assigned 1:1:1 to Google sea ...[more]

PMID: 31728417

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Project description:ImportanceBecause more patients are presenting with self-guided research of symptoms, it is important to assess the capabilities and limitations of these available health information tools.ObjectiveTo determine the accuracy of the most popular online symptom checker for ophthalmic diagnoses.Design, setting, and participantsIn a cross-sectional study, 42 validated clinical vignettes of ophthalmic symptoms were generated and distilled to their core presenting symptoms. Cases were entered into WebMD symptom checker by both medically trained and nonmedically trained personnel blinded to the diagnosis. Output from the symptom checker, including the number of symptoms, ranking and list of diagnoses, and triage urgency were recorded. The study was conducted on October 13, 2017. Analysis was performed between October 15, 2017, and April 30, 2018.Main outcomes and measuresAccuracy of the top 3 diagnoses generated by the online symptom checker.ResultsThe mean (SD) number of symptoms entered was 3.6 (1.6) (range, 1-8). The median (SD) number of diagnoses generated by the symptom checker was 26.8 (21.8) (range, 1-99). The primary diagnosis by the symptom checker was correct in 11 of 42 (26%; 95% CI, 12%-40%) cases. The correct diagnosis was included in the online symptom checker's top 3 diagnoses in 16 of 42 (38%; 95% CI, 25%-56%) cases. The correct diagnosis was not included in the symptom checker's list in 18 of 42 (43%; 95% CI, 32%-63%) cases. Triage urgency based on the top diagnosis was appropriate in 7 of 18 (39%; 95% CI, 14%-64%) emergent cases and 21 of 24 (88%; 95% CI, 73%-100%) nonemergent cases. Interuser variability for the correct diagnosis being in the top 3 listed was at least moderate (Cohen κ = 0.74; 95% CI, 0.54-0.95).Conclusions and relevanceThe most popular online symptom checker may arrive at the correct clinical diagnosis for ophthalmic conditions, but a substantial proportion of diagnoses may not be captured. These findings suggest that further research to reflect the real-life application of internet diagnostic resources is required.

Project description:ImportanceAsthma is one of the most burdensome chronic illnesses in the US. Despite widespread dissemination of evidence-based guidelines, more than half of the adults with asthma have uncontrolled symptoms.ObjectiveTo examine the efficacy of an online tool designed to improve asthma control.Design12-month single blind randomized controlled trial of the online tool (Intervention condition, IC) versus an active control tool (CC).SettingPatients enrolled in an insurance plan.ParticipantsParticipants were 408 adults (21-60 years of age) with persistent asthma.InterventionAt least once each month and before provider visits, participants in the IC answered questions online about their asthma symptoms, asthma medications and asthma care received from providers, such as an asthma management plan. The tool then provided tailored feedback to remind patients 1) to ask health care providers specific questions that may improve asthma control (e.g., additional controller medications) and 2) to consistently perform specific self-care behaviors (e.g., proper inhaler technique). Participants in the CC received similar questions and feedback, yet focused instead on preventive services unrelated to asthma control (e.g., cancer screening).Main outcome measuresThe main outcome measure was asthma control, as assessed by the 5-question Asthma Control Test (ACT). Secondary outcomes included quality of life, medication use and healthcare utilization (e.g., emergency department visits).ResultsAfter 12 months, 323 participants completed follow-up measures (79.2%). Participants in the IC reported a greater mean improvement in the ACT score than participants in the CC (2.3 vs. 1.2; p = 0.02) and 9 of 11 individual asthma control survey items showed non-significant improvements favoring the IC. No differences were observed in medication adherence, number of asthma controller medications or health care utilization.Conclusion and relevanceSimple and brief online patient reminders improved asthma control among insured patients. Although future studies are needed to understand the mechanism of the improvement, the magnitude of the effect on asthma control was similar to the addition of an additional controller medication. Given the widespread use of the Internet, simple tools such as this may be useful for improving the control of other chronic diseases as well.Trial registrationThis study is registered at clinicaltrials.gov, NCT00921401, "Improving the Quality of Asthma Care Using the Internet".

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A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses.

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A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses.

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