Public Health Intelligence

Clinical information within the primary care EHR can inform public health action and service improvement. A coherent research effort is needed to derive robust and validated procedures for handling and analysing these data.

Our multidisciplinary team has established a programme of musculoskeletal health intelligence research using local and national databases and international collaboration. This has included:

  • Rigorous derivation of musculoskeletal health and care indicators;
  • Harmonising code lists across databases/countries;
  • Validation studies using linked cohort datasets/expert consensus;
  • Testing/implementing procedures for describing trends in occurrence;
  • Application in hypothesis-generating and hypothesis-testing observational studies and primary care intervention studies;
  • Dissemination to policymakers, practitioners and public.

We have used clear definitions of prevalence and incidence of morbidity to highlight how common morbidities and symptoms are in primary care and to allow comparison between databases both nationally and internationally. This has included cross-mapping of Read Codes to ICD10 codes.

Example publications:

  • Partington RJ, Muller S, Helliwell T, et al. Incidence, prevalence and treatment burden of polymyalgia rheumatica in the UK over two decades: a population-based study Annals of the Rheumatic Diseases 2018;77:12:1750-1756.
  • Yu D, Jordan KP, Bedson, J, Englund M, Blyth F, Turkiewicz A, Prieto-Alhambra D, Peat G. Population trends in the incidence and initial management of osteoarthritis: age-period-cohort analysis of the Clinical Practice Research Datalink, 1992-2013, Rheumatology 2017;56:11:1902-17
  • Jordan KP, Jöud A, Bergknut C, Croft P, Edwards JJ, Peat G, Petersson IF, Turkiewicz A,  Wilkie R, Englund M. International comparisons of the prevalence of health care for musculoskeletal disorders using population-based health care data from England and Sweden. Annals of the Rheumatic Diseases 2014;73:1:212-218.

We have categorised hundreds of pain medications available for GPs to prescribe into six groups: from basic analgesia through increasingly potent opioids and NSAIDs. This has allowed us to describe the management of painful musculoskeletal conditions and assess the impact of directives and guidelines on primary care prescribing.

  • Ndlovu M, Bedson J, Jones PW, Jordan KP. Pain medication management of musculoskeletal conditions at first presentation in primary care: analysis of routinely collected medical record data. BMC Musculoskeletal Disorders, 2014;15:418.
  • Bedson J, Belcher J, Martino OI, Ndlovu M, Rathod T, Walters K, Dunn KM, Jordan KP. The effectiveness of national guidance in changing analgesic prescribing in primary care from 2002 to 2009: an observational database study. European Journal of Pain, 2013;17:434-443.

We have derived quality indicators for the primary health care of osteoarthritis through an extensive systematic review. The indicators were then included in a pop-up electronic template for use during consultations. This has allowed us to measure and change the quality of care for osteoarthritis.

  • See: Keele's OAE template 
  • Edwards JJ, Jordan KP, Peat G, Bedson J, Croft PR, Hay EM, Dziedzic KS. Quality of Care for osteoarthritis: the effect of a point-of-care consultation recording template. Rheumatology, 2015;54:5:844-53.
  • Edwards J, Khanna M, Jordan JL, Jordan KP, Bedson J, Dziedzic K. Quality indicators for the primary care of osteoarthritis: a systematic review. Annals of the Rheumatic Diseases, 2015;74;3:490-8.

We are developing patient-reported outcome measures, developing and evaluating screening and prognostic indicators embedded in the primary care record, and using innovative approaches to obtaining regular measurements of patient symptoms.

We have disseminated to policymakers, practitioners and public through peer-reviewed publications, collaborative publications with Versus Arthritis.

We have a Collaborative Agreement with the Office for Health Improvement and Disparities which supports our intelligence research in musculoskeletal health.