Impact of deprivation and comorbidity on outcomes in emergency general surgery: an epidemiological study

Discussion

This study has demonstrated, using population-level data, that increased levels of comorbidity and, to a lesser extent, socioeconomic deprivation significantly affect outcomes of EGS admissions in a free at the point of care healthcare system. Not only is this a novel finding, it is methodologically unique from a public health perspective in that we examined the whole population of EGS admissions over 20 years instead of examining the impact on a specific diagnosis or operation over a shorter time period.

These findings have implications for public health policy and service delivery planning. Patients with multimorbidity are at increased risk of in-hospital, short-term and medium-term mortality.19 They are also at higher risk of discharge to a non-home environment. Early identification of those individuals who are likely to require further care needs may need to be explored in order to ensure patient movement through the acute sectors of NHS care. Our data also show that the need for further support structures is greatest in the deprived regions.

There are also clinical applications from this work: clinicians need to better appreciate (and quantify) the impact that comorbidity and, to a lesser extent, socioeconomic deprivation have on LOS, discharge destination and both in-hospital and post-discharge mortality. This pertains to the very nature of patient–provider discussion in setting the expectations for length of hospital admissions, the likelihood of being discharged home directly or the likelihood of inpatient or post-discharge death, regardless of operative intervention. While it is not possible to suggest a 'comorbidity threshold' for involving services such as physiotherapy, occupational therapy, social work or geriatrics, clinicians should be aware that, compared with patients with no comorbidity, patients with minor comorbidity (CCI 1 to 2) are half as likely to be discharged home (all patients OR 0.57, operative patients OR 0.49), and patients with major comorbidity (CCI >4) are only one-third as likely to be discharged home (all patients OR 0.38, operative patients OR 0.37) (table 3). Interestingly, the number of patients who are discharged home is the same in both the operative and non-operative groups. This finding suggests that the barriers to discharge are not related to treatment.

Other studies have shown associations between socioeconomic deprivation and health outcomes. The Whitehall studies of British civil servants identified increased morbidity and cardiovascular risk among those working in lower employment grades, and this effect was observed to be sustained for over a decade.1 Packard et al showed that socioeconomic adversity in children negatively affects their health and cognition in adult life.2 Overall mortality was higher in the deprived population compared with the affluent population (HR 1.36, 95% CI 1.09 to 1.69) for patients who underwent resection for colorectal cancer in Scotland between 1991 and 1994.3 Deprivation was associated with increased major and minor complications following ileostomy reversal in a Scottish population.4 Socioeconomic deprivation was independently associated with higher mortality rates after kidney transplantation, with the least deprived having reduced 5-year mortality (HR 0.65, 95% CI 0.54 to 0.77).5 Taylor et al showed that, in patients undergoing coronary artery bypass graft, deprivation was independently associated with increased risk of postoperative myocardial infarction, stroke, death and prolonged hospital stay.6 Wrigley et al showed that socioeconomic deprivation was adversely associated with survival in patients with colorectal cancer,7 with HR for mortality from colorectal cancer in the most deprived areas of 1.12 (95% CI 1.00 to 1.25) and all-cause mortality 1.18 (95% CI 1.07 to 1.30). Symons et al showed that high-risk EGS patients with Carstairs score 5 (most deprived) compared with Carstairs score 1 (least deprived) had a higher 30-day mortality risk with OR 1.22 (95% CI 1.18 to 1.27).8

The relatively small effect of deprivation on outcomes may be explained by Scotland’s single-payer healthcare system. Healthcare is delivered free at the point of care, including primary care (general practitioners) and secondary/tertiary care (hospital specialists), both in the elective and emergency setting. This may reduce some financial barriers to receiving healthcare, thereby increasing access for those who in other healthcare systems may struggle to receive emergency medical care.

There is evidence in the literature that comorbidities affect the outcome of patients undergoing EGS, but most focus on patients who have had operative procedures. Patients undergoing EGS procedures who had a higher CCI had increased 30-day mortality postoperatively (adjusted OR 1.39, 95% CI 1.11 to 1.73).10 Another study showed that this effect was even greater for patients undergoing high-risk EGS procedures, as those patients with CCI >2 had a higher 30-day mortality (OR 2.61, 95% CI 2.56 to 2.67).8 Many studies have focused on elderly EGS patients, and concluded that frailty was a significant predictor of outcomes including perioperative complications, length of hospital stay,11 mortality, institutional discharge and cost.12 Frailty and comorbidity are related, in that frail patients have a higher CCI score,12 but they are not synonymous. Recent efforts have focused on these factors; in particular, the National Emergency Laparotomy Audit (NELA) identified that nearly half of all emergency laparotomies are performed on patients over 70, that their mortality rate, LOS, comorbidity and frailty are much higher than younger patients, and that only 3% of hospitals provide regular proactive assessments from geriatricians.20–22 Similarly, in Scotland, 49% of emergency laparotomies were performed in patients aged >65 years and 16% of these were frail, scoring >4 in the Rockwood Clinical Frailty Score,23 and it has been suggested that we build 'clinical relationships with geriatricians to develop targeted frailty pathways'. The UK-wide Emergency Laporatomy and Frailty study reported that, of patients aged >65 years undergoing laparotomy, 20% are frail, which is associated with increased postoperative mortality, morbidity, length of critical care stay and LOS.24

The information collected at routine assessment at time of admission (the ‘clerking in’ of patients) could be better used to inform the likely hospital course. An area of future research could be to develop a prediction score at admission based on factors which predict likelihood of various outcomes, such as LOS, discharge destination and mortality. This has been done for perioperative mortality (P-POSSUM)25 and could have clinical relevance—for example, to trigger patients’ needs assessments (physiotherapy, occupational therapy, social care requirements), review by a geriatrician, or early discussions/decisions about ceilings of care with the patient and their families.

We defined EGS as those patients who were admitted to a Scottish hospital under the care of a consultant (attending) general surgeon.9 18 19 26 There have been other methods of defining EGS,27 however this is the most pragmatic definition in the context of the UK as it defines the actual service delivered instead of only including the patients whose coded diagnosis at discharge falls within the remit of the general surgical specialism (‘ideal’ definition). This is an important distinction for two reasons: (1) because the nature of EGS service is such that diagnoses are often dependent on laboratory and radiological services, which may take time, and thus many admissions result in diagnoses which would not normally be looked after by general surgeons; and (2) clinical resources should be allocated based on actual demand, not ideal situations.

This study has strengths and limitations. Its greatest strength is the large number of hospital episodes included. The population-wide data have great advantages in that there are very few missing data, but there is also a lack of granularity. This limited the variables which could be controlled for, and thus limited interpretations of findings. For example, there is no information on the specific comorbidities which contribute to make up the CCI, so for any individual admission we do not know whether the outcome was influenced by specific comorbidities (cardiac, respiratory, immunological, extremes of body mass index, frailty) or other factors including presenting physiology, case severity, or clinical and radiological findings. Therefore, although there is little bias introduced in the dataset and the confidence intervals are narrow given the very large sample size, detailed associations related to underlying conditions could not be determined. There is also a risk of confounding factors which could not be controlled for, given the limited breadth of the dataset. Another limitation is that SIMD describes deprivation within post code regions, therefore not all individuals within a particular data zone will have the same characteristics. Data providers quality assure data for all indicators before providing them to the Office of the Chief Statistician and Performance, which then performs further checks on indicators and domains.14 Data are correlated with previous years, investigated and considered for amendment if they have changed dramatically.14 Therefore, despite not being tailored for the individual, SIMD is likely the most reliable method of characterising deprivation in Scotland. As a multicenter study, it would have been pertinent to study clustering effects by facility, but we did not have a facility variable or field in the database so it could not be performed. Further work on a representative sample of these patients using more detailed data could provide prognostic information at the point of admission, augmenting the prognostic work resulting in the NELA score and P-POSSUM score for emergency laparotomy.22 25

The generalizability of these results may be wide. Although the data came from a single nation (Scotland), it was a population-wide sample over the course of 20 years, with very few missing data, and therefore may compare to similar populations (highly developed Western nations). Lastly, because we included data from the last 20 years, if there had been a change in the direction of any effect over time the conclusions generated may be misleading.

In conclusion, increased levels of comorbidity and, to a lesser extent, socioeconomic deprivation significantly adversely affects EGS outcomes including mortality, discharge destination and length of hospital stay. Further work is warranted to determine whether prognostic scoring at EGS admission could be developed, which can help guide treatment pathways for patients.