K Jordan1, B N Ong, P Croft. 1. Primary Care Sciences Research Centre, Keele University, Keele, UK. k.p.jordan@keele.ac.uk
Abstract
STUDY OBJECTIVE: There has been little prospective investigation of what predicts general practice consultation. The objective of this study was to investigate the extent to which previous primary care consultation and self reported health status are predictors of future primary care consultation. DESIGN: Population based cohort study in two phases. Firstly, a baseline survey (1995/96) to identify the cohort and to obtain self reported health status using the UK census limiting long term illness (LLI) question and the Short Form-36 (SF-36) health profile. Secondly, analysis of general practice medical records for two years (1994/1995) before the survey and for two years (1997/1998) after the survey. Analysis was performed on: (a) all contacts coded by the GP, (b) the subgroup of contacts given a diagnostic morbidity code by the GP. SETTING: One general practice in North Staffordshire, UK. PARTICIPANTS: 738 survey respondents who had consented to viewing of medical records including all those who reported LLI together with an age-gender matched control group of those who reported no LLI. MAIN RESULTS: High frequency consulters in 1994/95 were more likely than non-consulters or average consulters in that year to be high consulters in 1997/98 (odds ratio 5.6, 95% confidence interval 3.82 to 8.25, for all contacts; 4.4 for diagnostic coded consultations). Self reported role disability and physical limitation from the SF-36 at baseline increased the probability of being a future high consulter but the effects were weaker than for previous consultation. Previous consultation within a diagnostic group was the main predictor for future consultation within that group with weaker but significant prediction by self reported health status. CONCLUSIONS: Reliable morbidity coding in general practice provides the best available basis for predicting future demand in primary care. Self reported health status survey instruments add to this information but on their own are weaker predictors of future consultation.
STUDY OBJECTIVE: There has been little prospective investigation of what predicts general practice consultation. The objective of this study was to investigate the extent to which previous primary care consultation and self reported health status are predictors of future primary care consultation. DESIGN: Population based cohort study in two phases. Firstly, a baseline survey (1995/96) to identify the cohort and to obtain self reported health status using the UK census limiting long term illness (LLI) question and the Short Form-36 (SF-36) health profile. Secondly, analysis of general practice medical records for two years (1994/1995) before the survey and for two years (1997/1998) after the survey. Analysis was performed on: (a) all contacts coded by the GP, (b) the subgroup of contacts given a diagnostic morbidity code by the GP. SETTING: One general practice in North Staffordshire, UK. PARTICIPANTS: 738 survey respondents who had consented to viewing of medical records including all those who reported LLI together with an age-gender matched control group of those who reported no LLI. MAIN RESULTS: High frequency consulters in 1994/95 were more likely than non-consulters or average consulters in that year to be high consulters in 1997/98 (odds ratio 5.6, 95% confidence interval 3.82 to 8.25, for all contacts; 4.4 for diagnostic coded consultations). Self reported role disability and physical limitation from the SF-36 at baseline increased the probability of being a future high consulter but the effects were weaker than for previous consultation. Previous consultation within a diagnostic group was the main predictor for future consultation within that group with weaker but significant prediction by self reported health status. CONCLUSIONS: Reliable morbidity coding in general practice provides the best available basis for predicting future demand in primary care. Self reported health status survey instruments add to this information but on their own are weaker predictors of future consultation.
Authors: Tess Harris; Derek G Cook; Christina R Victor; Carole Beighton; Stephen Dewilde; Iain M Carey Journal: Br J Gen Pract Date: 2004-12 Impact factor: 5.386
Authors: Aaron Jones; Susan E Bronskill; Connie Schumacher; Hsien Seow; David Feeny; Andrew P Costa Journal: Ann Fam Med Date: 2020-09 Impact factor: 5.166
Authors: Sandra Hollinghurst; Joanna Coast; John Busby; Annette Bishop; Nadine E Foster; Angelo Franchini; Sean Grove; Jeanette Hall; Cherida Hopper; Surinder Kaur; Alan A Montgomery; Chris Salisbury Journal: BMJ Open Date: 2013-10-03 Impact factor: 2.692