General practitioner workforce planning: assessment of four policy directions

<p>Abstract</p> <p>Background</p> <p>Estimating the supply of GPs into the future is important in forecasting shortages. The lengthy training process for medicine means that adjusting supply to meet demand in a timely fashion is problematic. This study uses Ireland as a case study to determine the future demand and supply of GPs and to assess the potential impact of several possible interventions to address future shortages.</p> <p>Methods</p> <p>Demand was estimated by applying GP visit rates by age and sex to national population projections. Supply was modelled using a range of parameters derived from two national surveys of GPs. A stochastic modelling approach was adopted to determine the probable future supply of GPs. Four policy interventions were tested: increasing vocational training places; recruiting GPs from abroad; incentivising later retirement; increasing nurse substitution to enable practice nurses to deliver more services.</p> <p>Results</p> <p>Relative to most other European countries, Ireland has few GPs per capita. Ireland has an ageing population and demand is estimated to increase by 19% by 2021. Without intervention, the supply of GPs will be 5.7% less than required in 2021. Increasing training places will enable supply to meet demand but only after 2019. Recruiting GPs from overseas will enable supply to meet demand continuously if the number recruited is approximately 0.8 per cent of the current workforce per annum. Later retirement has only a short-term impact. Nurse substitution can enable supply to meet demand but only if large numbers of practice nurses are recruited and allowed to deliver a wide range of GP services.</p> <p>Conclusions</p> <p>A significant shortfall in GP supply is predicted for Ireland unless recruitment is increased. The shortfall will have numerous knock-on effects including price increases, longer waiting lists and an increased burden on hospitals. Increasing training places will not provide an adequate response to future shortages. Foreign recruitment has ethical considerations but may provide a rapid and effective response. Increased nurse substitution appears to offer the best long-term prospects of addressing GP shortages and presents the opportunity to reshape general practice to meet the demands of the future.</p

Pharmaceutical cost and multimorbidity with type 2 diabetes mellitus using electronic health record data

© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.[EN] Background: The objective of the study is to estimate the frequency of multimorbidity in type 2 diabetes patients classified by health statuses in a European region and to determine the impact on pharmaceutical expenditure. Methods: Cross-sectional study of the inhabitants of a southeastern European region with a population of 5,150,054, using data extracted from Electronic Health Records for 2012. 491,854 diabetic individuals were identified and selected through clinical codes, Clinical Risk Groups and diabetes treatment and/or blood glucose reagent strips. Patients with type 1 diabetes and gestational diabetes were excluded. All measurements were obtained at individual level. The prevalence of common chronic diseases and co-occurrence of diseases was established using factorial analysis. Results: The estimated prevalence of diabetes was 9.6 %, with nearly 70 % of diabetic patients suffering from more than two comorbidities. The most frequent of these was hypertension, which for the groups of patients in Clinical Risk Groups (CRG) 6 and 7 was 84.3 % and 97.1 % respectively. Regarding age, elderly patients have more probability of suffering complications than younger people. Moreover, women suffer complications more frequently than men, except for retinopathy, which is more common in males. The highest use of insulins, oral antidiabetics (OAD) and combinations was found in diabetic patients who also suffered cardiovascular disease and neoplasms. The average cost for insulin was 153€ and that of OADs 306€. Regarding total pharmaceutical cost, the greatest consumers were patients with comorbidities of respiratory illness and neoplasms, with respective average costs of 2,034.2€ and 1,886.9€. Conclusions: Diabetes is characterized by the co-occurrence of other diseases, which has implications for disease management and leads to a considerable increase in consumption of medicines for this pathology and, as such, pharmaceutical expenditure.This study was financed by a grant from the Fondo de Investigaciones de la Seguridad Social Instituto de Salud Carlos III, the Spanish Ministry of Health (FIS PI12/0037).Sancho Mestre, C.; Vivas Consuelo, DJJ.; Alvis, L.; Romero, M.; Usó Talamantes, R.; Caballer Tarazona, V. (2016). Pharmaceutical cost and multimorbidity with type 2 diabetes mellitus using electronic health record data. BMC Health Services Research. 16(394):1-8. https://doi.org/10.1186/s12913-016-1649-2S1816394Whiting DR, Guariguata L, Weil C, Shaw J. IDF Diabetes Atlas: Global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract. 2011;94:311–21. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22079683Soriguer F, Goday A, Bosch-Comas A, Bordiu E, Calle-Pascual A, Carmena R, et al. Prevalence of diabetes mellitus and impaired glucose regulation in Spain: the [email protected] Study. Diabetologia. 2012;55:88–93. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21987347WHO | Rio Political Declaration on Social Determinants of Health. WHO. World Health Organization; 2011. Available from: http://www.who.int/sdhconference/declaration/Rio_political_declaration.pdf?ua=1Fortin M, Soubhi H, Hudon C, Bayliss EA, van den Akker M. Multimorbidity’s many challenges. BMJ. 2007;334:1016–7. BMJ Group [cited 2016 Aug 4]. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17510108Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for understanding health and health services. Ann Fam Med. 2009;7:357–63. [cited 2016 Aug 4]. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19597174Sundararajan V, Henderson T, Perry C, Muggivan A, Quan H, Ghali WA. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol. 2004;57:1288–94. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15617955Glynn LG, Valderas JM, Healy P, Burke E, Newell J, Gillespie P, et al. The prevalence of multimorbidity in primary care and its effect on health care utilization and cost. Fam Pract. 2011;28:516–23. [Internet]. 2011 [cited 2016 Aug 4]. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21436204Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380:37–43. [cited 2014 Nov 5] Available from: http://www.ncbi.nlm.nih.gov/pubmed/22579043Holden L, Scuffham PA, Hilton MF, Muspratt A, Ng SK, Whiteford HA. Patterns of multimorbidity in working Australians. Popul Heal Metr. 2011;9:15. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21635787Starfield B. Threads and yarns: weaving the tapestry of comorbidity. Ann Fam Med. 2006;4:101–3. [cited 2016 Aug 4]. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16569711Abdul-Rahim HF, Holmboe-Ottesen G, Stene LCM, Husseini A, Giacaman R, Jervell J, et al. Obesity in a rural and an urban Palestinian West Bank population. Int J Obes. 2003;27:140–6. Available from: http://dx.doi.org/10.1038/sj.ijo.0802160Boutayeb A, Boutayeb S, Boutayeb W. Multi-morbidity of non communicable diseases and equity in WHO Eastern Mediterranean countries. Int J Equity Heal. 2013;12:60. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23961989Teljeur C, Smith SM, Paul G, Kelly A, O’Dowd T. Multimorbidity in a cohort of patients with type 2 diabetes. Eur J Gen Pract. 2013;19:17–22. Available from: http://informahealthcare.com/doi/abs/10.3109/13814788.2012.714768 , http://www.ncbi.nlm.nih.gov/pubmed/23432037Hughes JS, Averill RF, Eisenhandler J, Goldfield NI, Muldoon J, Neff JM, et al. Clinical Risk Groups (CRGs): a classification system for risk-adjusted capitation-based payment and health care management. Med Care. 2004;42:81–90. [cited 2016 Feb 29]. Available from: http://www.ncbi.nlm.nih.gov/pubmed/14713742Vivas-Consuelo D, Alvis-Estrada L, Uso-Talamantes R, Caballer-Tarazona V, Buigues-Pastor L, Sancho-Mestre C. Multimorbidity Pharmaceutical Cost of Diabetes Mellitus. Value in Health. 2014;17:A341–2. Elsevier [cited 2016 Apr 21]. Available from: http://www.sciencedirect.com/science/article/pii/S1098301514026102Inoriza JM, Pérez M, Cols M, Sánchez I, Carreras M. Análisis de la población diabética de una comarca : perfil de morbilidad, utilización de recursos, complicaciones y control metabólico. Aten Primaria. 2016;45. Available from: http://www.sciencedirect.com/science/article/pii/S0212656713001340Vivas-Consuelo D, Usó-Talamantes R, Trillo-Mata JL, Caballer-Tarazona M, Barrachina-Martínez I, Buigues-Pastor L. Predictability of pharmaceutical spending in primary health services using Clinical Risk Groups. Health Policy. 2014;116:188–95. Available from: http://www.sciencedirect.com/science/article/pii/S0168851014000256Kho AN, Hayes MG, Rasmussen-Torvik L, Pacheco JA, Thompson WK, Armstrong LL, et al. Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study. J Am Med Inform Assoc. 2016;19:212–8. [cited 2016 Feb 18]. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3277617&tool=pmcentrez&rendertype=abstractPrados-Torres A, Poblador-Plou B, Calderón-Larrañaga A, Gimeno-Feliu LA, González-Rubio F, Poncel-Falcó A, et al. Multimorbidity patterns in primary care: interactions among chronic diseases using factor analysis. PLoS One. 2012;7:e32190. Public Library of Science [cited 2016 Apr 21]. Available from: http://dx.doi.org/10.1371/journal.pone.0032190Islam MM, Valderas JM, Yen L, Dawda P, Jowsey T, McRae IS. Multimorbidity and comorbidity of chronic diseases among the senior Australians: prevalence and patterns. PLoS One. 2014;9:e83783. Public Library of Science [cited 2016 Mar 25]. Available from: http://dx.doi.org/10.1371/journal.pone.0083783Fortin M, Bravo G, Hudon C, Lapointe L, Dubois MF, Almirall J. Psychological distress and multimorbidity in primary care. Ann Fam Med. 2006;4:417–22. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17003141Nuttall M, van der Meulen J, Emberton M. Charlson scores based on ICD-10 administrative data were valid in assessing comorbidity in patients undergoing urological cancer surgery. J Clin Epidemiol. 2006;59:265–73. Available from: http://www.ncbi.nlm.nih.gov/pubmed/16488357Klompas M, Eggleston E, McVetta J, Lazarus R, Li L, Platt R. Automated detection and classification of type 1 versus type 2 diabetes using electronic health record data. Diabetes Care. 2013;36:914–21. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23193215Alonso-Moran E, Orueta JF, Fraile Esteban JI, Arteagoitia Axpe JM, Luz Marques Gonzalez M, Toro Polanco N, et al. The prevalence of diabetes-related complications and multimorbidity in the population with type 2 diabetes mellitus in the Basque Country. BMC Public Health. 2014;14. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4197247/Pantalone KM, Hobbs TM, Wells BJ, Kong SX, Kattan MW, Bouchard J, et al. Clinical characteristics, complications, comorbidities and treatment patterns among patients with type 2 diabetes mellitus in a large integrated health system. BMJ open diabetes Res Care. 2015;3:e000093. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4513350&tool=pmcentrez&rendertype=abstractAlonso-Moran E, Satylganova A, Orueta JF, Nuno-Solinis R. Prevalence of depression in adults with type 2 diabetes in the Basque Country: relationship with glycaemic control and health care costs. BMC Public Health. 2014;14. Available from: http://bmcpublichealth.biomedcentral.com/articles/10.1186/1471-2458-14-769Kilzieh N, Rastam S, Maziak W, Ward KD. Comorbidity of depression with chronic diseases: a population-based study in Aleppo, Syria. Int J Psychiatry Med. 2008;38:169–84. Available from: http://www.ncbi.nlm.nih.gov/pubmed/18724568Almawi W, Tamim H, Al-Sayed N, Arekat MR, Al-Khateeb GM, Baqer A, et al. Association of comorbid depression, anxiety, and stress disorders with Type 2 diabetes in Bahrain, a country with a very high prevalence of Type 2 diabetes. J Endocrinol Invest. 2008;31:1020–4. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19169060Giralt Muiña P, Gutiérrez Ávila G, Ballester Herrera MJ, Botella Romero F, Angulo Donado JJ. Prevalencia de diabetes y diabetes oculta en adultos de Castilla-La Mancha. TITLEREVISTA. 2011;137:484–90. Available from: http://zl.elsevier.es/es/revista/medicina-clinica-2/prevalencia-diabetes-diabetes-oculta-adultos-castilla-la-mancha-90028329-originales-2011Mata-Cases M, Roura-Olmeda P, Berengué-Iglesias M, Birulés-Pons M, Mundet-Tuduri X, Franch-Nadal J, et al. Fifteen years of continuous improvement of quality care of type 2 diabetes mellitus in primary care in Catalonia, Spain. Int J Clin Pract. 2012;66:289–98. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3584513&tool=pmcentrez&rendertype=abstractEgede LE, Gebregziabher M, Zhao Y, Dismuke CE, Walker RJ, Hunt KJ, et al. Differential Impact of Mental Health. 2015;21:535–44. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26295353Huber CA, Diem P, Schwenkglenks M, Rapold R, Reich O. Estimating the prevalence of comorbid conditions and their effect on health care costs in patients with diabetes mellitus in Switzerland. Diabetes Metab Syndr Obes. 2014;7:455–65. Dove Press [cited 2016 Aug 4]. Available from: https://www.dovepress.com/estimating-the-prevalence-of-comorbid-conditions-and-their-effect-on-h-peer-reviewed-article-DMS