Erica A. Abel, C. Brandt, R. Czlapinski, J. Goulet
{"title":"使用退伍军人健康管理局电子和行政数据源进行疼痛研究。","authors":"Erica A. Abel, C. Brandt, R. Czlapinski, J. Goulet","doi":"10.1682/JRRD.2014.10.0246","DOIUrl":null,"url":null,"abstract":"Health services researchers are using Veterans Health Administration (VHA) electronic health record (EHR) data sources to examine the prevalence, treatment, and outcomes of pain among Veterans in VHA care. Little guidance currently exists on using these data; thus, findings may vary depending on the methods, data sources, and definitions used. We sought to identify current practices in order to provide guidance to future pain researchers. We conducted an anonymous survey of VHA-affiliated researchers participating in a monthly national pain research teleconference. Thirty-two researchers (89%) responded: 75% conducted pain-focused research, 78% used pain intensity numeric rating screening scale (NRS) scores to identify pain, 41% used International Classification of Diseases-9th Revision codes, and 57% distinguished between chronic and acute pain using either NRS scores or pharmacy data. The NRS and pharmacy data were rated as the most valid pain data sources. Of respondents, 48% reported the EHR data sources were adequate for pain research, while 45% had published peer-reviewed articles based on the data. Despite limitations, VHA researchers are increasingly using EHR data for pain research, and several common methods were identified. More information on the performance characteristics of these data sources and definitions is needed.","PeriodicalId":50065,"journal":{"name":"Journal of Rehabilitation Research and Development","volume":"53 1 1","pages":"1-12"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1682/JRRD.2014.10.0246","citationCount":"7","resultStr":"{\"title\":\"Pain research using Veterans Health Administration electronic and administrative data sources.\",\"authors\":\"Erica A. Abel, C. Brandt, R. Czlapinski, J. Goulet\",\"doi\":\"10.1682/JRRD.2014.10.0246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Health services researchers are using Veterans Health Administration (VHA) electronic health record (EHR) data sources to examine the prevalence, treatment, and outcomes of pain among Veterans in VHA care. Little guidance currently exists on using these data; thus, findings may vary depending on the methods, data sources, and definitions used. We sought to identify current practices in order to provide guidance to future pain researchers. We conducted an anonymous survey of VHA-affiliated researchers participating in a monthly national pain research teleconference. Thirty-two researchers (89%) responded: 75% conducted pain-focused research, 78% used pain intensity numeric rating screening scale (NRS) scores to identify pain, 41% used International Classification of Diseases-9th Revision codes, and 57% distinguished between chronic and acute pain using either NRS scores or pharmacy data. The NRS and pharmacy data were rated as the most valid pain data sources. Of respondents, 48% reported the EHR data sources were adequate for pain research, while 45% had published peer-reviewed articles based on the data. Despite limitations, VHA researchers are increasingly using EHR data for pain research, and several common methods were identified. More information on the performance characteristics of these data sources and definitions is needed.\",\"PeriodicalId\":50065,\"journal\":{\"name\":\"Journal of Rehabilitation Research and Development\",\"volume\":\"53 1 1\",\"pages\":\"1-12\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1682/JRRD.2014.10.0246\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Rehabilitation Research and Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1682/JRRD.2014.10.0246\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Rehabilitation Research and Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1682/JRRD.2014.10.0246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q","JCRName":"Medicine","Score":null,"Total":0}
Pain research using Veterans Health Administration electronic and administrative data sources.
Health services researchers are using Veterans Health Administration (VHA) electronic health record (EHR) data sources to examine the prevalence, treatment, and outcomes of pain among Veterans in VHA care. Little guidance currently exists on using these data; thus, findings may vary depending on the methods, data sources, and definitions used. We sought to identify current practices in order to provide guidance to future pain researchers. We conducted an anonymous survey of VHA-affiliated researchers participating in a monthly national pain research teleconference. Thirty-two researchers (89%) responded: 75% conducted pain-focused research, 78% used pain intensity numeric rating screening scale (NRS) scores to identify pain, 41% used International Classification of Diseases-9th Revision codes, and 57% distinguished between chronic and acute pain using either NRS scores or pharmacy data. The NRS and pharmacy data were rated as the most valid pain data sources. Of respondents, 48% reported the EHR data sources were adequate for pain research, while 45% had published peer-reviewed articles based on the data. Despite limitations, VHA researchers are increasingly using EHR data for pain research, and several common methods were identified. More information on the performance characteristics of these data sources and definitions is needed.