Usability characteristics of self-administered computer-assisted interviewing in the emergency department

Herrick, Daniel B.; Nakhasi, Atul; Nelson, Brian K.; Rice, Sarah E.; Abbott, Patricia; Tehrani, Ali S. Saber; Rothman, Richard E.; Lehmann, Harold P.; Newman‐Toker, David E.

doi:10.4338/aci-2012-09-ra-0034

Cited by 23 publications

(34 citation statements)

References 22 publications

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“…These results are consistent with those of prior studies of data entry using tablet computers, which found worse data accuracy in older individuals and differences based on race and prior technology use. 6,7 Fifty-one percent of older adults in the current study were willing to use a tablet, and many of those had difficulty providing correct responses, with 32% correctly answering all questions. Of participants with mild or no cognitive impairment, 45% were willing to try to use the tablet, and 32% answered all questions correctly.…”

Section: Discussionmentioning

confidence: 90%

“…Level of formal education, which has been shown to affect performance on electronic questionnaires, was not assessed. 6,7 Study subjects were predominantly white, which may limit generalizability to more ethnically diverse populations. Delirium, 23,24 which may have been present in some participants and may have contributed to unwillingness or inability to use the tablet, was not assessed for.…”

Section: Discussionmentioning

confidence: 99%

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Willingness and Ability of Older Adults in the Emergency Department to Provide Clinical Information Using a Tablet Computer

Brahmandam

Holland

Mangipudi

et al. 2016

J American Geriatrics Society

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OBJECTIVES To estimate the proportion of older adults in the emergency department (ED) who are willing and able to use a tablet computer to answer questions. DESIGN Prospective, ED-based cross-sectional study. SETTING Two U.S. academic EDs. PARTICIPANTS Individuals aged 65 and older. MEASUREMENTS As part of screening for another study, potential study participants were asked whether they would be willing to use a tablet computer to answer eight questions instead of answering questions orally. A custom user interface optimized for older adults was used. Trained research assistants observed study participants as they used the tablets. Ability to use the tablet was assessed based on need for assistance and number of questions answered correctly. RESULTS Of 365 individuals approached, 248 (68%) were willing to answer screening questions, 121 of these (49%) were willing to use a tablet computer; of these, 91 (75%) were able to answer at least six questions correctly, and 35 (29%) did not require assistance. Only 14 (12%) were able to answer all eight questions correctly without assistance. Individuals aged 65 to 74 and those reporting use of a touchscreen device at least weekly were more likely to be willing and able to use the tablet computer. Of individuals with no or mild cognitive impairment, the percentage willing to use the tablet was 45%, and the percentage answering all questions correctly was 32%. CONCLUSION Approximately half of this sample of older adults in the ED was willing to provide information using a tablet computer, but only a small minority of these were able to enter all information correctly without assistance. Tablet computers may provide an efficient means of collecting clinical information from some older adults in the ED, but at present, it will be ineffective for a significant portion of this population.

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Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Willingness and Ability of Older Adults in the Emergency Department to Provide Clinical Information Using a Tablet Computer

Brahmandam

Holland

Mangipudi

et al. 2016

J American Geriatrics Society

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“…Also, we allowed patients to skip individual questions by pressing a next button. On average, the response times for our patient population exceeded those previously reported for a self-administered non-audio electronic survey system [15]; however, direct comparisons are complicated by differences in instruments, patient populations, and possibly network speed.…”

Section: Discussionmentioning

confidence: 51%

Implementation of an Audio Computer-Assisted Self-Interview (ACASI) System in a General Medicine Clinic

et al. 2015

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Summary Background: Routine implementation of instruments to capture patient-reported outcomes could guide clinical practice and facilitate health services research. Audio interviews facilitate self-interviews across literacy levels. Objectives: To evaluate time burden for patients, and factors associated with response times for an audio computer-assisted self interview (ACASI) system integrated into the clinical workflow. Methods: We developed an ACASI system, integrated with a research data warehouse. Instruments for symptom burden, self-reported health, depression screening, tobacco use, and patient satisfaction were administered through touch-screen monitors in the general medicine clinic at the Cook County Health & Hospitals System during April 8, 2011-July 27, 2012. We performed a cross-sectional study to evaluate the mean time burden per item and for each module of instruments; we evaluated factors associated with longer response latency. Results: Among 1,670 interviews, the mean per-question response time was 18.4 [SD, 6.1] seconds. By multivariable analysis, age was most strongly associated with prolonged response time and increased per decade compared to < 50 years as follows (additional seconds per question; 95% CI): 50–59 years (1.4; 0.7 to 2.1 seconds); 60–69 (3.4; 2.6 to 4.1); 70–79 (5.1; 4.0 to 6.1); and 80–89 (5.5; 4.1 to 7.0). Response times also were longer for Spanish language (3.9; 2.9 to 4.9); no home computer use (3.3; 2.8 to 3.9); and, low mental self-reported health (0.6; 0.0 to 1.1). However, most interviews were completed within 10 minutes. Conclusions: An ACASI software system can be included in a patient visit and adds minimal time burden. The burden was greatest for older patients, interviews in Spanish, and for those with less computer exposure. A patient’s self-reported health had minimal impact on response times. Citation: Trick WE, Deamant C, Smith J, Garcia D, Angulo F. Implementation of an audio computer-assisted self-interview (ACASI) system in a general medicine clinic – patient response burden. Appl Clin Inf 2015; 6: 148–162http://dx.doi.org/10.4338/ACI-2014-09-RA-0073

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“…The behaviour of Mediktor in the classification of severity levels is close to what is expected with the percentage of hospital admission (Level 3: 76.5%, Level 4: 11.8% and Level 5: 11.8%). The scope of Mediktor in the collection of data is greater, so a different classification model is expected, although without statistically significant differences in this sample size based on a study that used case simulations [26] when not finding similar studies.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, in the original publication [12] it was not valued independently in the different levels of classification, so we did not have previous data of its possible applicability to the group of less complexity studied and, therefore, with lower forecast of need for hospital admission In our project we used a nurse to feed the system with the patient's answers and answer their questions, without interfering with the symptoms that the patient wanted to expose. Herrick et al (26), in a study on the usability of a self-administered questionnaire for emergency diagnosis, found that 86% did not require assistance. Those who needed help were older (54 ± 19) years.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of a Diagnostic Decision Support System for the Triage of Patients in a Hospital Emergency Department

Arancibia¹,

Sanchez²,

Rey-Mejías³

et al. 2019

IJIMAI

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One of the biggest challenges for the management of the emergency department (ED) is to expedite the management of patients since their arrival for those with low priority pathologies selected by the classification systems, generating unnecessary saturation of the ED. Diagnostic decision support systems (DDSS) can be a powerful tool to guide diagnosis, facilitate correct classification and improve patient safety. Patients who attended the ED of a tertiary hospital with the preconditions of Manchester Triage system level of low priority (levels 3, 4 and 5), and with one of the five most frequent causes for consultation: dyspnea, chest pain, gastrointestinal bleeding, general discomfort and abdominal pain, were interviewed by an independent researcher with a DDSS, the Mediktor system. After the interview, we compare the Manchester triage and the final diagnoses made by the ED with the triage and diagnostic possibilities ordered by probability obtained by the Mediktor system, respectively. In a final sample of 214 patients, the urgency assignment made by both systems does not match exactly, which could indicate a different classification model, but there were no statistically significant differences between the assigned levels (S = 0.059, p = 0.442). The diagnostic accuracy between the final diagnosis and any of the first 10 Mediktor diagnoses was of 76.5%, for the first five diagnoses was 65.4%, for the first three diagnoses was 58%, and the exact match with the first diagnosis was 37.9%. The classification of Mediktor in this segment of patients shows that a higher level of severity corresponds to a greater number of hospital admissions, hospital readmissions and emergency screenings at 30 days, although without statistical significance. It is expected that this type of applications may be useful as a complement to the triage, to accelerate the diagnostic approach, to improve the request for appropriate complementary tests in a protocolized action model and to reduce waiting times in the ED.

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Usability characteristics of self-administered computer-assisted interviewing in the emergency department

Cited by 23 publications

References 22 publications

Willingness and Ability of Older Adults in the Emergency Department to Provide Clinical Information Using a Tablet Computer

Willingness and Ability of Older Adults in the Emergency Department to Provide Clinical Information Using a Tablet Computer

Implementation of an Audio Computer-Assisted Self-Interview (ACASI) System in a General Medicine Clinic

Evaluation of a Diagnostic Decision Support System for the Triage of Patients in a Hospital Emergency Department

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