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Jibb LA, Khan JS, Seth P, Lalloo C, Mulrooney L, Nicholson K, Nowak DA, Kaur H, Chee-A-Tow A, Foster J, Stinson JN. Electronic Data Capture Versus Conventional Data Collection Methods in Clinical Pain Studies: Systematic Review and Meta-Analysis. J Med Internet Res 2020; 22:e16480. [PMID: 32348259 PMCID: PMC7351264 DOI: 10.2196/16480] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 01/21/2020] [Accepted: 03/22/2020] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND The most commonly used means to assess pain is by patient self-reported questionnaires. These questionnaires have traditionally been completed using paper-and-pencil, telephone, or in-person methods, which may limit the validity of the collected data. Electronic data capture methods represent a potential way to validly, reliably, and feasibly collect pain-related data from patients in both clinical and research settings. OBJECTIVE The aim of this study was to conduct a systematic review and meta-analysis to compare electronic and conventional pain-related data collection methods with respect to pain score equivalence, data completeness, ease of use, efficiency, and acceptability between methods. METHODS We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica Database (EMBASE), and Cochrane Central Register of Controlled Trials (CENTRAL) from database inception until November 2019. We included all peer-reviewed studies that compared electronic (any modality) and conventional (paper-, telephone-, or in-person-based) data capture methods for patient-reported pain data on one of the following outcomes: pain score equivalence, data completeness, ease of use, efficiency, and acceptability. We used random effects models to combine score equivalence data across studies that reported correlations or measures of agreement between electronic and conventional pain assessment methods. RESULTS A total of 53 unique studies were included in this systematic review, of which 21 were included in the meta-analysis. Overall, the pain scores reported electronically were congruent with those reported using conventional modalities, with the majority of studies (36/44, 82%) that reported on pain scores demonstrating this relationship. The weighted summary correlation coefficient of pain score equivalence from our meta-analysis was 0.92 (95% CI 0.88-0.95). Studies on data completeness, patient- or provider-reported ease of use, and efficiency generally indicated that electronic data capture methods were equivalent or superior to conventional methods. Most (19/23, 83%) studies that directly surveyed patients reported that the electronic format was the preferred data collection method. CONCLUSIONS Electronic pain-related data capture methods are comparable with conventional methods in terms of score equivalence, data completeness, ease, efficiency, and acceptability and, if the appropriate psychometric evaluations are in place, are a feasible means to collect pain data in clinical and research settings.
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Affiliation(s)
- Lindsay A Jibb
- Child Health Evaluative Sciences, Hospital for Sick Children, Toronto, ON, Canada
- Lawrence S Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada
| | - James S Khan
- Department of Anesthesia, Mount Sinai Hospital, Toronto, ON, Canada
- Department of Anesthesia, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Puneet Seth
- Department of Family Medicine, McMaster University, Hamilton, ON, Canada
| | - Chitra Lalloo
- Child Health Evaluative Sciences, Hospital for Sick Children, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Lauren Mulrooney
- Faculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada
| | - Kathryn Nicholson
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Dominik A Nowak
- Department of Family Medicine, McMaster University, Hamilton, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Harneel Kaur
- Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | | | - Joel Foster
- Office of Education, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Jennifer N Stinson
- Child Health Evaluative Sciences, Hospital for Sick Children, Toronto, ON, Canada
- Lawrence S Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
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