Jens Foell1, Dawn Carnes1, Kate Homer1, Stephanie Taylor1. 1. NIHR Clinical Lecturer,The Blizard Institute,Centre for Primary Care and Public Health,Barts and The London School of Medicine and Dentistry,Queen Mary University of London,London,UK.
Abstract
BACKGROUND: Identifying patients with chronic musculoskeletal pain using database searches is difficult, as chronic pain is not represented with a unique diagnostic code in electronic primary care records. Aim This paper describes the development and implementation of a search strategy to identify patients with chronic musculoskeletal pain in primary care databases to invite them to participate in a randomised controlled trial. METHODS: We used an exploratory, iterative approach. The first phase involved consultations with IT specialists, practice managers and doctors to gain an understanding about the processes and issues of electronic coding. In the second and third phases, we determined the most appropriate search terms and strategies. In the final phase, we tested, modified and re-tested the search strategy until the quantity and quality of the output appeared good enough to be used in general practices with different IT systems. This strategy was then implemented to recruit participants for a trial. Findings We identified three main search 'domains': prescribing, coding and attendance. We found the most useful identifier for chronic pain was the use of repeat medication. Wide variations in coding terms for chronic pain were seen between practices and individuals. Understanding 'coding cultures' were necessary to inform the electronic searches. In the case of chronic pain, searching on repeat medication for analgesia, low dose antidepressants and carefully selected coding terms captured most relevant patients.
BACKGROUND: Identifying patients with chronic musculoskeletal pain using database searches is difficult, as chronic pain is not represented with a unique diagnostic code in electronic primary care records. Aim This paper describes the development and implementation of a search strategy to identify patients with chronic musculoskeletal pain in primary care databases to invite them to participate in a randomised controlled trial. METHODS: We used an exploratory, iterative approach. The first phase involved consultations with IT specialists, practice managers and doctors to gain an understanding about the processes and issues of electronic coding. In the second and third phases, we determined the most appropriate search terms and strategies. In the final phase, we tested, modified and re-tested the search strategy until the quantity and quality of the output appeared good enough to be used in general practices with different IT systems. This strategy was then implemented to recruit participants for a trial. Findings We identified three main search 'domains': prescribing, coding and attendance. We found the most useful identifier for chronic pain was the use of repeat medication. Wide variations in coding terms for chronic pain were seen between practices and individuals. Understanding 'coding cultures' were necessary to inform the electronic searches. In the case of chronic pain, searching on repeat medication for analgesia, low dose antidepressants and carefully selected coding terms captured most relevant patients.
Authors: Dawn Carnes; Kate Homer; Martin Underwood; Tamar Pincus; Anisur Rahman; Stephanie J C Taylor Journal: BMJ Open Date: 2013-11-14 Impact factor: 2.692
Authors: Stephanie J C Taylor; Dawn Carnes; Kate Homer; Brennan C Kahan; Natalia Hounsome; Sandra Eldridge; Anne Spencer; Tamar Pincus; Anisur Rahman; Martin Underwood Journal: PLoS Med Date: 2016-06-14 Impact factor: 11.069