Gary A. Abel

Variation in number of general practitioner consultations before hospital referral for cancer: findings from the 2010 National Cancer Patient Experience Survey in England

BACKGROUND Information from patient surveys can help to identify patient groups and cancers with the greatest potential for improvement in the experience and timeliness of cancer diagnosis. We aimed to examine variation in the number of pre-referral consultations with a general practitioner between patients with different cancers and sociodemographic characteristics. METHODS We analysed data from 41,299 patients with 24 different cancers who took part in the 2010 National Cancer Patient Experience Survey in England. We examined variation in the number of general practitioner consultations with cancer symptoms before hospital referral to diagnose cancer. Logistic regression was used to identify independent predictors of three or more pre-referral consultations, adjusting for cancer type, age, sex, deprivation quintile, and ethnic group. FINDINGS We identified wide variation between cancer types in the proportion of patients who had visited their general practitioner three or more times before hospital referral (7·4% [625 of 8408] for breast cancer and 10·1% [113 of 1124] for melanoma; 41·3% [193 of 467] for pancreatic cancer and 50·6% [939 of 1854] for multiple myeloma). In multivariable analysis, with patients with rectal cancer as the reference group, those with subsequent diagnosis of multiple myeloma (odds ratio [OR] 3·42, 95% CI 3·01-3·90), pancreatic cancer (2·35, 1·91-2·88), stomach cancer (1·96, 1·65-2·34), and lung cancer (1·68, 1·48-1·90) were more likely to have had three or more pre-referral consultations; conversely patients with subsequent diagnosis of breast cancer (0·19; 0·17-0·22), melanoma (0·34, 0·27-0·43), testicular cancer (0·47, 0·33-0·67), and endometrial cancer (0·59, 0·49-0·71) were more likely to have been referred to hospital after only one or two consultations. The probability of three or more pre-referral consultations was greater in young patients (OR for patients aged 16-24 years vs 65-74 years 2·12, 95% CI 1·63-2·75; p<0·0001), those from ethnic minorities (OR for Asian vs white 1·73, 1·45-2·08; p<0·0001; OR for black vs white 1·83, 1·51-2·23; p<0·0001), and women (OR for women vs men 1·28, 1·21-1·36; p<0·0001). We identified strong evidence of interactions between cancer type and age group and sex (p<0·0001 for both), and between age and ethnicity (p=0·0013). The model including these interactions showed a particularly strong sex effect for bladder cancer (OR for women vs men 2·31, 95% CI 1·98-2·69) and no apparent ethnic group differences in young patients aged 16-24 years, whilst the only cancers without an apparent age gradient were testicular cancer and mesothelioma. INTERPRETATION Our findings could help to prioritise and stratify early diagnosis initiatives and research, focusing on patients with cancers and sociodemographic characteristics with the largest potential for improvement. FUNDING None.

The effect of physical multimorbidity, mental health conditions and socioeconomic deprivation on unplanned admissions to hospital: a retrospective cohort study

Background: Multimorbidity, the presence of more than 1 long-term disorder, is associated with increased use of health services, but unplanned admissions to hospital may often be undesirable. Furthermore, socioeconomic deprivation and mental health comorbidity may lead to additional unplanned admissions. We examined the association between unplanned admission to hospital and physical multimorbidity, mental health and socioeconomic deprivation. Methods: We conducted a retrospective cohort study using data from 180 815 patients aged 20 years and older who were registered with 40 general practices in Scotland. Details of 32 physical and 8 mental health morbidities were extracted from the patients’ electronic health records (as of Apr. 1, 2006) and linked to hospital admission data. We then recorded the occurrence of unplanned or potentially preventable unplanned acute (nonpsychiatric) admissions to hospital in the subsequent 12 months. We used logistic regression models, adjusting for age and sex, to determine associations between unplanned or potentially preventable unplanned admissions to hospital and physical multimorbidity, mental health and socioeconomic deprivation. Results: We identified 10 828 (6.0%) patients who had at least 1 unplanned admission to hospital and 2037 (1.1%) patients who had at least 1 potentially preventable unplanned admission to hospital. Both unplanned and potentially preventable unplanned admissions were independently associated with increasing physical multimorbidity (for ≥ 4 v. 0 conditions, odds ratio [OR] 5.87 [95% confidence interval (CI) 5.45–6.32] for unplanned admissions, OR 14.38 [95% CI 11.87–17.43] for potentially preventable unplanned admissions), mental health conditions (for ≥ 1 v. 0 conditions, OR 2.01 [95% CI 1.92–2.09] for unplanned admissions, OR 1.80 [95% CI 1.64–1.97] for potentially preventable unplanned admissions) and socioeconomic deprivation (for most v. least deprived quintile, OR 1.56 [95% CI 1.43–1.70] for unplanned admissions, OR 1.98 [95% CI 1.63–2.41] for potentially preventable unplanned admissions). Interpretation: Physical multimorbidity was strongly associated with unplanned admission to hospital, including admissions that were potentially preventable. The risk of admission to hospital was exacerbated by the coexistence of mental health conditions and socioeconomic deprivation.

Reducing emergency admissions: are we on the right track?

Most attempts to reduce emergency hospital admissions are focused on people at high risk. Martin Roland and Gary Abel highlight the misconceptions behind this approach and suggest what to do about them

Measures of promptness of cancer diagnosis in primary care: secondary analysis of national audit data on patients with 18 common and rarer cancers

Background:Evidence is needed about the promptness of cancer diagnosis and associations between its measures.Methods:We analysed data from the National Audit of Cancer Diagnosis in Primary Care 2009–10 exploring the association between the interval from first symptomatic presentation to specialist referral (the primary care interval, or ‘interval’ hereafter) and the number of pre-referral consultations.Results:Among 13 035 patients with any of 18 different cancers, most (82%) were referred after 1 (58%) or 2 (25%) consultations (median intervals 0 and 15 days, respectively) while 9%, 4% and 5% patients required 3, 4 or 5+ consultations (median intervals 34, 47 and 97 days, respectively) (Spearman’s r=0.70). The association was at least moderate for any cancer (Spearman’s r range: 0.55 (prostate)−0.77 (brain)). Patients with cancers with a higher proportion of three or more pre-referral consultations typically also had longer median intervals (e.g., multiple myeloma) and vice versa (e.g., breast cancer).Conclusion:The number of pre-referral consultations has construct validity as a measure of the primary care interval. Developing interventions to reduce the number of pre-referral consultations can help improve the timeliness of cancer diagnosis, and constitutes a priority for early diagnosis initiatives and research.

Is polypharmacy always hazardous?: A retrospective cohort analysis using linked electronic health records from primary and secondary care

AIMS Prescribing multiple medications is associated with various adverse outcomes, and polypharmacy is commonly considered suggestive of poor prescribing. Polypharmacy might thus be associated with unplanned hospitalization. We sought to test this assumption. METHODS Scottish primary care data for 180 815 adults with long-term clinical conditions and numbers of regular medications were linked to national hospital admissions data for the following year. Using logistic regression (age, gender and deprivation adjusted), we modelled the association of prescribing with unplanned admission for patients with different numbers of long-term conditions. RESULTS Admissions were more common in patients on multiple medications, but admission risk varied with the number of conditions. For patients with one condition, the odds ratio for unplanned admission for four to six medications was 1.25 (95% confidence interval 1.11-1.42) vs. one to three medications, and 3.42 (95% confidence interval 2.72-4.28) for ≥10 medications vs. one to three medications. However, this effect was greatly reduced for patients with multiple conditions; amongst patients with six or more conditions, those on four to six medications were no more likely to have unplanned admissions than those taking one to three medications (odds ratio 1.00; 95% confidence interval 0.88-1.14), and those taking ≥10 medications had a modestly increased risk of admission (odds ratio 1.50; 95% confidence interval 1.31-1.71). CONCLUSIONS Unplanned hospitalization is strongly associated with the number of regular medications. However, the effect is reduced in patients with multiple conditions, in whom only the most extreme levels of polypharmacy are associated with increased admissions. Assumptions that polypharmacy is always hazardous and represents poor care should be tempered by clinical assessment of the conditions for which those drugs are being prescribed.

Socio-demographic inequalities in stage of cancer diagnosis: evidence from patients with female breast, lung, colon, rectal, prostate, renal, bladder, melanoma, ovarian and endometrial cancer

Background Understanding socio-demographic inequalities in stage at diagnosis can inform priorities for cancer control. Patients and methods We analysed data on the stage at diagnosis of East of England patients diagnosed with any of 10 common cancers, 2006–2010. Stage information was available on 88 657 of 98 942 tumours (89.6%). Results Substantial socio-demographic inequalities in advanced stage at diagnosis (i.e. stage III/IV) existed for seven cancers, but their magnitude and direction varied greatly by cancer: advanced stage at diagnosis was more likely for older patients with melanoma but less likely for older patients with lung cancer [odds ratios for 75–79 versus 65–69 1.60 (1.38–1.86) and 0.83 (0.77–0.89), respectively]. Deprived patients were more likely to be diagnosed in advanced stage for melanoma, prostate, endometrial and (female) breast cancer: odds ratios (most versus least deprived quintile) from 2.24 (1.66–3.03) for melanoma to 1.31 (1.15–1.49) for breast cancer. In England, elimination of socio-demographic inequalities in stage at diagnosis could decrease the number of patients with cancer diagnosed in advanced stage by ∼5600 annually. Conclusions There are substantial socio-demographic inequalities in stage at diagnosis for most cancers. Earlier detection interventions and policies can be targeted on patients at higher risk of advanced stage diagnosis.

Is polypharmacy always hazardous

AIMS Prescribing multiple medications is associated with various adverse outcomes, and polypharmacy is commonly considered suggestive of poor prescribing. Polypharmacy might thus be associated with unplanned hospitalization. We sought to test this assumption. METHODS Scottish primary care data for 180 815 adults with long-term clinical conditions and numbers of regular medications were linked to national hospital admissions data for the following year. Using logistic regression (age, gender and deprivation adjusted), we modelled the association of prescribing with unplanned admission for patients with different numbers of long-term conditions. RESULTS Admissions were more common in patients on multiple medications, but admission risk varied with the number of conditions. For patients with one condition, the odds ratio for unplanned admission for four to six medications was 1.25 (95% confidence interval 1.11-1.42) vs. one to three medications, and 3.42 (95% confidence interval 2.72-4.28) for ≥10 medications vs. one to three medications. However, this effect was greatly reduced for patients with multiple conditions; amongst patients with six or more conditions, those on four to six medications were no more likely to have unplanned admissions than those taking one to three medications (odds ratio 1.00; 95% confidence interval 0.88-1.14), and those taking ≥10 medications had a modestly increased risk of admission (odds ratio 1.50; 95% confidence interval 1.31-1.71). CONCLUSIONS Unplanned hospitalization is strongly associated with the number of regular medications. However, the effect is reduced in patients with multiple conditions, in whom only the most extreme levels of polypharmacy are associated with increased admissions. Assumptions that polypharmacy is always hazardous and represents poor care should be tempered by clinical assessment of the conditions for which those drugs are being prescribed.

Drivers of overall satisfaction with primary care: evidence from the English General Practice Patient Survey

To determine which aspects of primary care matter most to patients, we aim to identify those aspects of patient experience that show the strongest relationship with overall satisfaction and examine the extent to which these relationships vary by socio‐demographic and health characteristics.

Accuracy of routinely recorded ethnic group information compared with self-reported ethnicity: evidence from the English Cancer Patient Experience survey

Objective To describe the accuracy of ethnicity coding in contemporary National Health Service (NHS) hospital records compared with the ‘gold standard’ of self-reported ethnicity. Design Secondary analysis of data from a cross-sectional survey (2011). Setting All NHS hospitals in England providing cancer treatment. Participants 58 721 patients with cancer for whom ethnicity information (Office for National Statistics 2001 16-group classification) was available from self-reports (considered to represent the ‘gold standard’) and their hospital record. Methods We calculated the sensitivity and positive predictive value (PPV) of hospital record ethnicity. Further, we used a logistic regression model to explore independent predictors of discordance between recorded and self-reported ethnicity. Results Overall, 4.9% (4.7–5.1%) of people had their self-reported ethnic group incorrectly recorded in their hospital records. Recorded White British ethnicity had high sensitivity (97.8% (97.7–98.0%)) and PPV (98.1% (98.0–98.2%)) for self-reported White British ethnicity. Recorded ethnicity information for the 15 other ethnic groups was substantially less accurate with 41.2% (39.7–42.7%) incorrect. Recorded ‘Mixed’ ethnicity had low sensitivity (12–31%) and PPVs (12–42%). Recorded ‘Indian’, ‘Chinese’, ‘Black-Caribbean’ and ‘Black African’ ethnic groups had intermediate levels of sensitivity (65–80%) and PPV (80–89%, respectively). In multivariable analysis, belonging to an ethnic minority group was the only independent predictor of discordant ethnicity information. There was strong evidence that the degree of discordance of ethnicity information varied substantially between different hospitals (p<0.0001). Discussion Current levels of accuracy of ethnicity information in NHS hospital records support valid profiling of White/non-White ethnic differences. However, profiling of ethnic differences in process or outcome measures for specific minority groups may contain a substantial and variable degree of misclassification error. These considerations should be taken into account when interpreting ethnic variation audits based on routine data and inform initiatives aimed at improving the accuracy of ethnicity information in hospital records.

Variation in promptness of presentation among 10,297 patients subsequently diagnosed with one of 18 cancers: evidence from a National Audit of Cancer Diagnosis in Primary Care.

Cancer awareness public campaigns aim to shorten the interval between symptom onset and presentation to a doctor (the ‘patient interval’). Appreciating variation in promptness of presentation can help to better target awareness campaigns. We explored variation in patient intervals recorded in consultations with general practitioners among 10,297 English patients subsequently diagnosed with one of 18 cancers (bladder, brain, breast, colorectal, endometrial, leukaemia, lung, lymphoma, melanoma, multiple myeloma, oesophageal, oro‐pharyngeal, ovarian, pancreatic, prostate, renal, stomach, and unknown primary) using data from of the National Audit of Cancer Diagnosis in Primary Care (2009–2010). Proportions of patients with ‘prompt’/‘non‐prompt’ presentation (0–14 or 15+ days from symptom onset, respectively) were described and respective odds ratios were calculated by multivariable logistic regression. The overall median recorded patient interval was 10 days (IQR 0–38). Of all patients, 56% presented promptly. Prompt presentation was more frequent among older or housebound patients (p < 0.001). Prompt presentation was most frequent for bladder and renal cancer (74% and 70%, respectively); and least frequent for oro‐pharyngeal and oesophageal cancer (34% and 39%, respectively, p <.001). Using lung cancer as reference, the adjusted odds ratios of non‐prompt presentation were 2.26 (95% confidence interval 1.57–3.25) and 0.42 (0.34–0.52) for oro‐pharyngeal and bladder cancer, respectively. Sensitivity analyses produced similar findings. Routinely recorded patient interval data reveal considerable variation in the promptness of presentation. These findings can help to prioritise public awareness initiatives and research focusing on symptoms of cancers associated with greater risk of non‐prompt presentation, such as oro‐pharyngeal and oesophageal cancer.