Table 1: Analyses of predictors of health care hassles What ‘hassles’ do patients with multimorbidity report? Which patients report most ‘hassles’? Charles Adeniji, Peter Bower, Cassandra Kenning Centre for Primary Care, Institute of Population Health, University of Manchester Background ‘Hassles’ scale Table 1: Analyses of predictors of health care hassles Lack of information about my medical condition (55%) Lack of information about treatment options (60%) Lack of information about why my medication was prescribed (50 %) Problems getting my medication refilled on time (23%) Uncertainty about when or how to take my medications (18%) Side effect from my medications (48 %) Lack of information about referral to a specialist (24%) Having to wait a long time to get a specialist appointment (60%) Poor communication between different doctors or clinics (55 %) Disagreement between doctors about diagnosis or treatment (31%) Lack of information about why I need lab test or x-rays (32 %) Having to wait too long to find out results of lab tests or x-rays (42 %) Difficulty getting advice between appointments (46 %) Lack of time to discuss all my problems during appointments (43%) Having my concerns ignored or overlooked (36 %) Appointments that interfere with my work, family, or hobbies (24%) Primary care services are designed for single long term conditions, whereas many older patients have more than one (Salisbury 2011) Patients with multimorbidity experience ‘hassles’ in their care, including multiple appointments, poor co-ordination, and conflicting recommendations (Bayliss 2007;Fortin 2007; Smith 2012) There is limited quantitative evidence on the hassles that patients experience, or factors predicting hassles Conclusion References Methods Results The OPTIMUM study surveyed 1500 patients with multimorbidity from 4 practices in Greater Manchester Measures included demography, multimorbidity and ‘hassles’ using the Parchman scale The Parchman scale evaluates difficulties that patients experience during encounters with the health care system The next panel shows the items in the hassles scale As expected, increasing numbers of long-term conditions were associated with increasing reports of hassles It is not clear whether the associations with depression and age represent reporting issues, or more clinically important effects The study did suggest that frequent discussions with the GP may be important in reducing hassles New models of service delivery need to be tested to improve the experience of patients with multimorbidity Overall, 32% of patients completed the measures Most frequent hassles related to lack of information, poor communication, and poor access to specialist care Numbers of long-term conditions, current employment, and symptoms of depression predicted high levels of hassles Reports of a discussion with the GP about long-term conditions in the last 12 months and increasing age were associated with lower reported hassles Bayliss, E et al (2007) The Annals of Family Medicine, 5(5), 395-402 Fortin, M et al (2007) British Medical Journal, 334(7602), 1016 Parchman, M. et al (2005) Medical Care, 43(11), 1123-1129 Salisbury, C. et al (2011). British Journal of General Practice, 61(582), e12-e21 Smith, S. et al (2012). Cochrane Database Syst Rev, 4   Univariate Analysis Multivariate Analysis Clinical Number of conditions 7 , 2-20 0.055 0.011 0.219 0.000* 0.042 0.012 0.167 0.001* Depression (1=No, 2= Yes) No = 58.3%; Yes = 41.7% 0.340 0.074 0.210 -0.103 0.086 -0.064 0.233 Combined Anxiety and Depression (HADS) Baseline score (0-40) 13 ± 7.8, 0 - 40 0.005 0.400 0.038 0.006 0.352 Others How long had LTC? (grpd: less than 5 years and more than 5 years) less than 5 years = 15 .1% ; more than 5yrs = 84.9% 0.004 0.104 0.002 0.969 -0.099 0.098 -0.044 0.311 Overall health score (1=poor, 2=fair, 3=good, 4= very good, and 5=excellent) Poor=16%, fair=41.6%, good=32.9%, very good=7.8%, excellent=0.8%, missing=0.8% -0.207 -0.225 -0.021 0.049 -0.023 0.666 Discussed with GP in 12 month (1=No, 2= Yes) No = 21.8%; others = 78.2% -0.188 0.091 -0.096 0.038* -0.183 0.084 -0.095 0.030* Number of observations = 429, F change =10.224;R square change = .228 Charles.adeniji@postgrad.manchester.ac.uk www.manchester.ac.uk/lifesciences