Impact of a continuing medical education meeting on the use and timing of urgent cancer referrals among general practitioners - a before-after study

Berit Skjødeberg Toftegaard, Flemming Bro, Alina Zalounina Falborg, Peter Vedsted, Berit Skjødeberg Toftegaard, Flemming Bro, Alina Zalounina Falborg, Peter Vedsted

Abstract

Background: Detection of cancer in general practice is challenging because symptoms are diverse. Even so-called alarm symptoms have low positive predictive values of cancer. Nevertheless, appropriate referral is crucial. As 85% of cancer patients initiate their cancer diagnostic pathway in general practice, a Continuing Medical Education meeting (CME-M) in early cancer diagnosis was launched in Denmark in 2012. We aimed to investigate the effect of the CME-M on the primary care interval, patient contacts with general practice and use of urgent cancer referrals.

Methods: A before-after study was conducted in the Central Denmark Region included 396 general practices, which were assigned to one of eight geographical clusters. Practices were invited to participate in the CME-M with three-week intervals between clusters. Based on register data, we calculated urgent referral rates and patient contacts with general practice before referral. Information about primary care intervals was collected by requesting general practitioners to complete a one-page form for each urgent referral during an 8-month period around the time of the CME-Ms. CME-M practices were compared with non-participating reference practices by analysing before-after differences.

Results: Forty percent of all practices participated in the CME-M. There was a statistically significant reduction in the number of total contacts with general practice from urgently referred patients in the month preceding the referral and an increase in the proportion of patients who waited 14 days or more in general practice from the reported date of symptom presentation to the referral date from before to after the CME-M in the CME-M group compared to the reference group.

Conclusions: We found a reduced number of total patient contacts with general practice within the month preceding an urgent referral and an increase in the reported primary care intervals of urgently referred patients in the CME-M group. The trend towards higher urgent referral rates and longer primary care intervals may suggest raised awareness of unspecific cancer symptoms, which could cause the GP to register an earlier date of first symptom presentation. The standardised CME-M may contribute to optimising the timing and the use of urgent cancer referral.

Trial registration: NCT02069470 on ClinicalTrials.gov. Retrospectively registered, 1/29/2014.

Keywords: Behavioural change; Continuing medical education meeting; Denmark; Diagnosis; Early detection of cancer; General practice; Primary care interval; Referral rate; Use of health care.

Figures

Fig. 1
Fig. 1
Time periods used for classifying patient populations. The cluster-specific time period used for identifying urgently referred patients in the primary care referral database (light boxes = time before CME-M; dark boxes = time after CME-M). The method at the top was applied for evaluating CME-M effect on referral rates and patient contacts with general practice. The method at the bottom was used for evaluating CME-M effect on primary care intervals

References

    1. Coleman MP, Forman D, Bryant H, Butler J, Rachet B, Maringe C, et al. Cancer survival in Australia, Canada, Denmark, Norway, Sweden, and the UK, 1995–2007 (the International cancer benchmarking partnership): an analysis of population-based cancer registry data. Lancet. 2011;377(9760):127–38. doi: 10.1016/S0140-6736(10)62231-3.
    1. Ferlay J, Steliarova-Foucher E, Lortet-Tieulent J, Rosso S, Coebergh JW, Comber H, et al. Cancer incidence and mortality patterns in Europe: estimates for 40 countries in 2012. Eur J Cancer. 2013;49(6):1374–403. doi: 10.1016/j.ejca.2012.12.027.
    1. Allgar VL, Neal RD. Delays in the diagnosis of six cancers: analysis of data from the national survey of NHS patients: cancer. Br J Cancer. 2005;92(11):1959–70. doi: 10.1038/sj.bjc.6602587.
    1. Hansen RP, Vedsted P, Sokolowski I, Sondergaard J, Olesen F. Time intervals from first symptom to treatment of cancer: a cohort study of 2,212 newly diagnosed cancer patients. BMC Health Serv Res. 2011;11(1):284. doi: 10.1186/1472-6963-11-284.
    1. Richards MA, Smith P, Ramirez AJ, Fentiman IS, Rubens RD. The influence on survival of delay in the presentation and treatment of symptomatic breast cancer. Br J Cancer. 1999;79(5):858–64. doi: 10.1038/sj.bjc.6690137.
    1. Neal RD, Tharmanathan P, France B, Din NU, Cotton S, Fallon-Ferguson J, et al. Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic review. Br J Cancer. 2015;112(Suppl):S92–S107. doi: 10.1038/bjc.2015.48.
    1. Torring ML, Frydenberg M, Hansen RP, Olesen F, Vedsted P. Evidence of increasing mortality with longer diagnostic intervals for five common cancers: A cohort study in primary care. Eur J Cancer. 2013;49(9):2187–98. doi: 10.1016/j.ejca.2013.01.025.
    1. Moller H, Gildea C, Meechan D, Rubin G, Round T, Vedsted P. Use of the English urgent referral pathway for suspected cancer and mortality in patients with cancer: cohort study. BMJ. 2015;351:h5102. doi: 10.1136/bmj.h5102.
    1. Hamilton W. Cancer diagnosis in primary care. Br J Gen Pract. 2010;60(571):121–8. doi: 10.3399/bjgp10X483175.
    1. Nielsen TN, Hansen RP, Vedsted P. Symptom presentation in cancer patients in general practice. Ugeskr Laeger. 2010;172(41):2827–31.
    1. Shapley M, Mansell G, Jordan JL, Jordan KP. Positive predictive values of >5% in primary care for cancer: systematic review. Br J Gen Pract. 2010;60(578):e366–77. doi: 10.3399/bjgp10X515412.
    1. Jones R, Latinovic R, Charlton J, Gulliford MC. Alarm symptoms in early diagnosis of cancer in primary care: cohort study using general practice research database. BMJ. 2007;334(7602):1040. doi: 10.1136/.
    1. Hamilton W. The CAPER studies: five case–control studies aimed at identifying and quantifying the risk of cancer in symptomatic primary care patients. Br J Cancer. 2009;101(Suppl 2):S80-6.
    1. Christensen KG, Fenger-Gron M, Flarup KR, Vedsted P. Use of general practice, diagnostic investigations and hospital services before and after cancer diagnosis - a population-based nationwide registry study of 127,000 incident adult cancer patients. BMC Health Serv Res. 2012;12:224–6963. doi: 10.1186/1472-6963-12-224.
    1. Jensen H, Torring ML, Olesen F, Overgaard J, Fenger-Gron M, Vedsted P. Diagnostic intervals before and after implementation of cancer patient pathways - a GP survey and registry based comparison of three cohorts of cancer patients. BMC Cancer. 2015;15:308–015. doi: 10.1186/s12885-015-1317-7.
    1. Sundhedsstyrelsen. Kræftplan III Styrket indsats på kræftområdet - et sundhedsfagligt oplæg. København; 2010. Available from: . Accessed 2 Nov 2016.
    1. Toftegaard B, Bro F, Vedsted P. A geographical cluster randomised stepped wedge study of continuing medical education and cancer diagnosis in general practice. Implement Sci. 2014;9(1):159. doi: 10.1186/s13012-014-0159-z.
    1. Toftegaard BS, Bro F, Falborg AZ, Vedsted P. Impact of continuing medical education in cancer diagnosis on GP knowledge, attitude and readiness to investigate - a before-after study. BMC Fam Pract. 2016 Jul 26;17:10.1186/s12875,016-0496-x.
    1. National Board of Health Data [in Danish: Sundhedsdatastyrelsen] The Cancer Registry 2013. Available from: . Accessed 6 Jun 2016.
    1. Pedersen KM, Andersen JS, Sondergaard J. General practice and primary health care in Denmark. J Am Board Fam Med. 2012;25(Suppl 1):S34–8.
    1. Cancer fast-track pathways [in Danish: Pakkeforløb på Kræftområdet]. Available from: . Accessed 2 Nov 2016.
    1. Probst HB, Hussain ZB, Andersen O. Cancer patient pathways in Denmark as a joint effort between bureaucrats, health professionals and politicians-a national Danish project. Health Policy. 2012;105(1):65–70. doi: 10.1016/j.healthpol.2011.11.001.
    1. Pedersen CB. The Danish civil registration system. Scand J Public Health. 2011;39(7):22–5. doi: 10.1177/1403494810387965.
    1. Hamilton W, Peters TJ, Bankhead C, Sharp D. Risk of ovarian cancer in women with symptoms in primary care: population based case–control study. BMJ. 2009;339(0959–535):b2998. doi: 10.1136/bmj.b2998.
    1. Jensen H, Nissen A, Vedsted P. Quality deviations in cancer diagnosis: prevalence and time to diagnosis in general practice. Br J Gen Pract. 2014;64(619):e92–8. doi: 10.3399/bjgp14X677149.
    1. Lyratzopoulos G, Vedsted P, Singh H. Understanding missed opportunities for more timely diagnosis of cancer in symptomatic patients after presentation. Br J Cancer. 2015;112(Suppl 1):S84–91. doi: 10.1038/bjc.2015.47.
    1. Quekel LG, Kessels AG, Goei R, van Engelshoven JM. Miss rate of lung cancer on the chest radiograph in clinical practice. Chest. 1999;115(3):720–4. doi: 10.1378/chest.115.3.720.
    1. Stapley S, Sharp D, Hamilton W. Negative chest X-rays in primary care patients with lung cancer. Br J Gen Pract. 2006;56(529):570–3.
    1. Rubin G, Berendsen A, Crawford SM, Dommett R, Earle C, Emery J, et al. The expanding role of primary care in cancer control. Lancet Oncol. 2015;16(12):1231–72. doi: 10.1016/S1470-2045(15)00205-3.
    1. Weller D, Vedsted P, Rubin G, Walter FM, Emery J, Scott S, et al. The Aarhus statement: improving design and reporting of studies on early cancer diagnosis. Br J Cancer. 2012;106(7):126210–1267. doi: 10.1038/bjc.2012.68.
    1. Toftegaard BS, Guldbrandt LM, Flarup KR, Beyer H, Bro F, Vedsted P. Development of an algorithm to identify urgent referrals for suspected cancer from the Danish primary care referral database. Clin Epidemiol. 2016;8:751–9. doi: 10.2147/CLEP.S114721.
    1. Gjerstorff ML. The Danish cancer registry. Scand J Public Health. 2011;39(7):42–5. doi: 10.1177/1403494810393562.
    1. WHO. International Classification of Diseases (ICD). Available from: . Accessed 2 Nov 2016.
    1. Olivarius NF, Hollnagel H, Krasnik A, Pedersen PA, Thorsen H. The Danish national health register. A tool for primary health care research. Dan Med Bull. 1997;44(4):449–53.
    1. Storm HH, Michelsen EV, Clemmensen IH, Pihl J. The Danish cancer registry-history, content, quality and use. Dan Med Bull. 1997;44:535–9.
    1. Timmermans B. The Danish integrated database for labor market research: towards demystification for the English speaking audience. Aalborg: Aalborg University; 2010.
    1. Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173(6):676–82. doi: 10.1093/aje/kwq433.
    1. Lidegaard O, Hammerum MS. The national patient registry as a tool for continuous production and quality control. Ugeskr Laeger. 2002;164(38):4420–3.
    1. Lyratzopoulos G, Saunders CL, Abel GA, McPhail S, Neal RD, Wardle J, et al. The relative length of the patient and the primary care interval in patients with 28 common and rarer cancers. Br J Cancer. 2015;112(Suppl 1):S35–40. doi: 10.1038/bjc.2015.40.
    1. Cameron A, Trivedi P. Regression analysis of count data. Econometric Society Monograph. 53. Cambridge: Cambridge University Press; 2013.
    1. Fitzmaurice G, Laird N, Ware J. Applied Longitudinal Analysis. 2. New York: Wiley; 2004.
    1. StataCorp. 2013. Stata: Release 13. Statistical Software. College Station, TX: StataCorp LP. Available from: . Accessed 2 Nov 2016.
    1. Hamilton W, Green T, Martins T, Elliott K, Rubin G, Macleod U. Evaluation of risk assessment tools for suspected cancer in general practice: a cohort study. Br J Gen Pract. 2013;63(606):e30–6. doi: 10.3399/bjgp13X660751.
    1. Green T, Martins T, Hamilton W, Rubin G, Elliott K, Macleod U. Exploring GPs’ experiences of using diagnostic tools for cancer: a qualitative study in primary care. Fam Pract. 2015;32(1):101–5. doi: 10.1093/fampra/cmu081.
    1. Dikomitis L, Green T, Macleod U. Embedding electronic decision-support tools for suspected cancer in primary care: a qualitative study of GPs’ experiences. Prim Health Care Res Dev. 2015;16(6):548–55. doi: 10.1017/S1463423615000109.
    1. Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: medical research council guidance. BMJ. 2015;350:h1258. doi: 10.1136/bmj.h1258.
    1. Ribe AR, Fenger-Gron M, Vedsted P, Bro F, Kaersvang L, Vestergaard M. Several factors influenced general practitioner participation in the implementation of a disease management programme. Dan Med J. 2014;61(9):A4901.
    1. Ross S, Grant A, Counsell C, Gillespie W, Russell I, Prescott R. Barriers to participation in randomised controlled trials: a systematic review. J Clin Epidemiol. 1999;52(12):1143–56. doi: 10.1016/S0895-4356(99)00141-9.
    1. Rogers EM. Diffusions of innovations. New York: Simon & Schuster Ltd; 2013.
    1. Robinson G. Do general practitioners’ risk-taking propensities and learning styles influence their continuing medical education preferences? Med Teach. 2002;24(1):71–8. doi: 10.1080/01421590120091078.

Source: PubMed

3
订阅