Man Versus Machine: Comparing Double Data Entry and Optical Mark Recognition for Processing CAHPS Survey Data
| Autor: | Matthew Fifolt, Paul Wolff, Justin Blackburn, Aleena Bennett, Andrew C. Rucks, Shemeka Gillespie, David J. Rhodes |
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| Rok vydání: | 2017 |
| Předmět: |
Optical mark recognition
030213 general clinical medicine Health (social science) Leadership and Management Computer science Data entry Efficiency Organizational computer.software_genre 03 medical and health sciences 0302 clinical medicine Surveys and Questionnaires Data accuracy Statistics Humans Operational efficiency 030212 general & internal medicine Care Planning Receipt Database Data Collection Health Policy Depreciation Data Accuracy Patient Satisfaction Survey data collection CRITERION STANDARD computer |
| Zdroj: | Quality Management in Health Care. 26:131-135 |
| ISSN: | 1063-8628 |
| DOI: | 10.1097/qmh.0000000000000138 |
| Popis: | OBJECTIVE Historically, double data entry (DDE) has been considered the criterion standard for minimizing data entry errors. However, previous studies considered data entry alternatives through the limited lens of data accuracy. This study supplies information regarding data accuracy, operational efficiency, and cost for DDE and Optical Mark Recognition (OMR) for processing the Consumer Assessment of Healthcare Providers and Systems 5.0 survey. METHODS To assess data accuracy, we compared error rates for DDE and OMR by dividing the number of surveys that were arbitrated by the total number of surveys processed for each method. To assess operational efficiency, we tallied the cost of data entry for DDE and OMR after survey receipt. Costs were calculated on the basis of personnel, depreciation for capital equipment, and costs of noncapital equipment. RESULTS The cost savings attributed to this method were negated by the operational efficiency of OMR. There was a statistical significance between rates of arbitration between DDE and OMR; however, this statistical significance did not create a practical significance. CONCLUSIONS The potential benefits of DDE in terms of data accuracy did not outweigh the operational efficiency and thereby financial savings of OMR. |
| Databáze: | OpenAIRE |
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