Length of comorbidity lookback period affected regression model performance of administrative health data

Advanced Heart Failure Characteristics and Outcomes in Women and Men

BACKGROUND

The epidemiology and pathophysiology of heart failure (HF) differ in women and men. Whether these differences extend to the subgroup of patients with advanced HF is not well defined.

METHODS AND RESULTS

This is a retrospective cohort study of all adult Olmsted County, Minnesota residents with advanced HF (European Society of Cardiology criteria) from 2007 to 2017. Differences in survival and hospitalization risks in women and men following advanced HF development were examined using Cox proportional hazard regression and Andersen-Gill models, respectively. Of 936 individuals with advanced HF, 417 (44.6%) were women and 519 (55.4%) were men (self-reported sex). Time from development of HF to advanced HF was similar in women and men (median 3.2 versus 3.6 years). Women were older at diagnosis (mean age 79 versus 75 years), less often had coronary disease and hyperlipidemia, but more often had hypertension and depression (P<0.05 for each). Advanced HF with preserved ejection fraction was more prevalent in women than men (60% versus 30%, p<0.001). There were no differences in adjusted risks of all-cause mortality (hazard ratio [HR], 0.89 [95% CI, 0.77-1.03]), cardiovascular mortality (HR, 0.85 [95% CI, 0.70-1.02]), all-cause hospitalizations (HR, 1.04 [95% CI, 0.90-1.20]), or HF hospitalizations (HR, 0.91 [95% CI, 0.75-1.11]) between women and men. However, adjusted cardiovascular mortality was lower in women versus men with advanced HF with reduced ejection fraction (HR, 0.72 [95% CI, 0.56-0.93]).

CONCLUSIONS

Women more often present with advanced HF with preserved ejection fraction and men with atherosclerotic disease and advanced HF with reduced ejection fraction. Despite these differences, survival and hospitalization risks are largely comparable in women and men with advanced HF.

Identifying key health system components associated with improved outcomes to inform the re-configuration of services for adults with rare autoimmune rheumatic diseases: a mixed-methods study

BACKGROUND

Adults with rare autoimmune rheumatic diseases face unique challenges and struggles to navigate health-care systems designed to manage common conditions. Evidence to inform an optimal service framework for their care is scarce. Using systemic vasculitis as an exemplar, we aimed to identify and explain the key service components underpinning effective care for rare diseases.

METHODS

In this mixed-methods study, data were collected as part of a survey of vasculitis service providers across the UK and Ireland, interviews with patients, and from organisational case studies to identify key service components that enable good care. The association between these components and patient outcomes (eg, serious infections, mortality) and provider outcomes (eg, emergency hospital admissions) were examined in a population-based data linkage study using routine health-care data obtained from patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis from national health datasets in Scotland. We did univariable and multivariable analyses using Bayesian poisson and negative binomial regression to estimate incident rate ratios (IRRs), and Cox proportional hazards models to estimate hazard ratios (HRs). People with lived experiences were involved in the research and writing process.

FINDINGS

Good care was characterised by service components that supported timely access to services, integrated care, and expertise. In 1420 patients with ANCA-associated vasculitis identified from national health datasets, service-reported average waiting times for new patients of less than 1 week were associated with fewer serious infections (IRR 0·70 [95% credibility interval 0·55-0·88]) and fewer emergency hospital admissions (0·78 [0·68-0·92]). Nurse-led advice lines were associated with fewer serious infections (0·76 [0·58-0·93]) and fewer emergency hospital admissions (0·85 [0·74-0·96]). Average waiting times for new patients of less than 1 week were also associated with reduced mortality (HR 0·59 [95% credibility interval 0·37-0·93]). Cohorted clinics, nurse-led clinics, and specialist vasculitis multi-disciplinary team meetings were associated with fewer serious infections (IRR 0·75 [0·59-0·96] for cohorted clinics; 0·65 [0·39-0·84] for nurse-led clinics; 0·72 [0·57-0·90] for specialist vasculitis multi-disciplinary team meetings) and emergency hospital admissions (0·81 [0·71-0·91]; 0·75 [0·65-0·94]; 0·86 [0·75-0·96]). Key components were characterised by their ability to overcome professional tensions between specialties.

INTERPRETATION

Key service components associated with important health outcomes and underpinning factors were identified to inform initiatives to improve the design, delivery, and effectiveness of health-care models for rare autoimmune rheumatic diseases.

FUNDING

Versus Arthritis.

Survival of patients who had cancer diagnosed through an emergency hospital admission: A retrospective matched case-comparison study in Australia

BACKGROUND

Individuals diagnosed with cancer via emergency admission are likely to have poor outcomes. This study aims to identify cancer diagnosed through an emergency hospital admission and examine predictors associated with mortality within 12-months.

METHOD

A population-based retrospective 1:1 propensity-matched case-comparison study of people who had an emergency versus a planned hospital admission with a principal diagnosis of cancer during 2013-2020 in New South Wales, Australia using linked hospital, cancer registry and mortality records. Conditional logistic regression examined predictors of mortality at 12-months.

RESULTS

There were 28,502 matched case-comparisons. Individuals who had an emergency admission were four times more likely to die within 12-months (Odds Ratio (OR) 3.93; 95 % confidence interval (CI) 3.75-4.13) compared to individuals who had a planned admission for cancer. Older individuals, diagnosed with lung (OR 1.89; 95 %CI 1.36-2.63) or digestive organ, excluding colorectal (OR1.78; 95 %CI 1.30-2.43) cancers, where the degree of spread was metastatic (OR 3.61; 95 %CI 2.62-4.50), who had a mental disorder diagnosis (OR 2.08; 95 %CI 1.89-2.30), lived in rural (OR 1.27; 95 %CI 1.17-1.37) or more disadvantaged neighbourhoods had a higher likelihood of death within 12-months following an unplanned admission compared to referent groups. Females (OR 0.87; 95 %CI 0.81-0.93) had an 13 % lower likelihood of mortality within 12-months compared to males.

CONCLUSIONS

While some emergency cancer admissions are not avoidable, the importance of preventive screening and promotion of help-seeking for early cancer symptoms should not be overlooked as mechanisms to reduce emergency admissions related to cancer and to improve cancer survival.

Multimorbidity prevalence and health outcome prediction: assessing the impact of lookback periods, disease count, and definition criteria in health administrative data at the population-based level

BACKGROUND

Health administrative databases play a crucial role in population-level multimorbidity surveillance. Determining the appropriate retrospective or lookback period (LP) for observing prevalent and newly diagnosed diseases in administrative data presents challenge in estimating multimorbidity prevalence and predicting health outcome. The aim of this population-based study was to assess the impact of LP on multimorbidity prevalence and health outcomes prediction across three multimorbidity definitions, three lists of diseases used for multimorbidity assessment, and six health outcomes.

METHODS

We conducted a population-based study including all individuals ages > 65 years on April 1st, 2019, in Québec, Canada. We considered three lists of diseases labeled according to the number of chronic conditions it considered: (1) L60 included 60 chronic conditions from the International Classification of Diseases (ICD); (2) L20 included a core of 20 chronic conditions; and (3) L31 included 31 chronic conditions from the Charlson and Elixhauser indices. For each list, we: (1) measured multimorbidity prevalence for three multimorbidity definitions (at least two [MM2+], three [MM3+] or four (MM4+) chronic conditions); and (2) evaluated capacity (c-statistic) to predict 1-year outcomes (mortality, hospitalisation, polypharmacy, and general practitioner, specialist, or emergency department visits) using LPs ranging from 1 to 20 years.

RESULTS

Increase in multimorbidity prevalence decelerated after 5-10 years (e.g., MM2+, L31: LP = 1y: 14%, LP = 10y: 58%, LP = 20y: 69%). Within the 5-10 years LP range, predictive performance was better for L20 than L60 (e.g., LP = 7y, mortality, MM3+: L20 [0.798;95%CI:0.797-0.800] vs. L60 [0.779; 95%CI:0.777-0.781]) and typically better for MM3 + and MM4 + definitions (e.g., LP = 7y, mortality, L60: MM4+ [0.788;95%CI:0.786-0.790] vs. MM2+ [0.768;95%CI:0.766-0.770]).

CONCLUSIONS

In our databases, ten years of data was required for stable estimation of multimorbidity prevalence. Within that range, the L20 and multimorbidity definitions MM3 + or MM4 + reached maximal predictive performance.

Comparison of comorbidities of stroke collected in administrative data, surveys, clinical trials and cohort studies

BACKGROUND

Administrative data are used extensively for research purposes, but there remains limited information on the quality of these data for identifying comorbidities related to stroke.

OBJECTIVE

To compare the prevalence of comorbidities of stroke identified using International Classification Diseases, Australian Modification (ICD-10-AM) or Anatomical Therapeutic Chemical codes, with those from (i) self-reported data and (ii) published studies.

METHOD

The cohort included patients with stroke or transient ischaemic attack admitted to hospitals (2012-2016; Victoria and Queensland) in the Australian Stroke Clinical Registry (N = 26,111). Data were linked with hospital and pharmaceutical datasets to ascertain comorbidities using published algorithms. The sensitivity, specificity, and positive predictive value of these comorbidities were compared with survey responses from 623 patients (reference standard). An indirect comparison was also performed with clinical data from published stroke studies.

RESULTS

The sensitivity of hospital ICD-10-AM data was poor for most comorbidities, except for diabetes (93.0%). Specificity was excellent for all comorbidities (87-96%), except for hypertension (70.5%). Compared to published stroke studies (3 clinical trials and 1 incidence study), the prevalence of diabetes and atrial fibrillation in our cohort was similar using ICD-10-AM codes, but lower for dyslipidaemia and anxiety/depression. Whereas in the pharmaceutical dispensing data, the sensitivity was excellent for dyslipidaemia (94%) and modest for anxiety/depression (77%). In the pharmaceutical data, specificity was modest for hypertension (78%) and anxiety or depression (76%), but specificity was poor for dyslipidaemia (19%) and heart disease (46%).

CONCLUSION

Variation was observed in the reporting of comorbidities of stroke in administrative data, and consideration of multiple sources of data may be necessary for research. Further work is needed to improve coding and clinical documentation for reporting of comorbidities in administrative data.

Potentially burdensome care at the end-of-life for cancer decedents: a retrospective population-wide study

BACKGROUND

Variation persists in the quality of end-of-life-care (EOLC) for people with cancer. This study aims to describe the characteristics of, and examine factors associated with, indicators of potentially burdensome care provided in hospital, and use of hospital services in the last 12 months of life for people who had a death from cancer.

METHOD

A population-based retrospective cohort study of people aged ≥ 20 years who died with a cancer-related cause of death during 2014-2019 in New South Wales, Australia using linked hospital, cancer registry and mortality records. Ten indicators of potentially burdensome care were examined. Multinominal logistic regression examined predictors of a composite measure of potentially burdensome care, consisting of > 1 ED presentation or > 1 hospital admission or ≥ 1 ICU admission within 30 days of death, or died in acute care.

RESULTS

Of the 80,005 cancer-related deaths, 86.9% were hospitalised in the 12 months prior to death. Fifteen percent had > 1 ED presentation, 9.9% had > 1 hospital admission, 8.6% spent ≥ 14 days in hospital, 3.6% had ≥ 1 intensive care unit admission, and 1.2% received mechanical ventilation on ≥ 1 occasion in the last 30 days of life. Seventeen percent died in acute care. The potentially burdensome care composite measure identified 20.0% had 1 indicator, and 10.9% had ≥ 2 indicators of potentially burdensome care. Compared to having no indicators of potentially burdensome care, people who smoked, lived in rural areas, were most socially economically disadvantaged, and had their last admission in a private hospital were more likely to experience potentially burdensome care. Older people (≥ 55 years), females, people with 1 or ≥ 2 Charlson comorbidities, people with neurological cancers, and people who died in 2018-2019 were less likely to experience potentially burdensome care. Compared to people with head and neck cancer, people with all cancer types (except breast and neurological) were more likely to experience ≥ 2 indicators of potentially burdensome care versus none.

CONCLUSION

This study shows the challenge of delivering health services at end-of-life. Opportunities to address potentially burdensome EOLC could involve taking a person-centric approach to integrate oncology and palliative care around individual needs and preferences.

Any infection among patients with hip fracture: Predictive ability of Charlson, Elixhauser, Rx-Risk, and Nordic comorbidity indices

BACKGROUND

In studies on infection after hip fracture surgery, a common and serious complication, it remains unknown which comorbidity index is best for case-mix confounder adjustment. We evaluated the predictive ability of Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index (ECI), Rx-Risk Index (Rx-Risk), and Nordic Multimorbidity Index (NMI) for any infection up to 1 year from discharge after hip fracture surgery.

METHODS

Using Danish medical registries, we included 92,600 patients (mean age 83 years) surgically treated for hip fracture between 2004 and 2018. Comorbidity-index scores were calculated using prevalence of diagnosis codes, prescription codes, or both. Lookback periods of 1, 5, and 10 years were applied. Logistic regression was used to calculate c-index to assess discrimination of comorbidity indices individually and in combination with a base model of age and sex. Outcome was any infection (not only surgical site infection) in-hospital and 1 year after discharge.

RESULTS

At 10-year lookback period, the c-index for individual comorbidity indices for in-hospital infections varied from 0.53 to 0.56, similar to base model alone (0.56). The predictive ability of comorbidity indices in combination with base model varied from 0.56 to 0.57. Within 1 year after discharge, NMI in combination with base model had best predictive ability for infection (c-index = 0.62), followed by CCI and ECI (c-index = 0.60) and Rx-Risk (c-index = 0.58). Discrimination was similar for all lookback periods.

CONCLUSIONS

Comorbidity indices have low predictive ability for any infection up to 1 year after hip fracture surgery, similar to that of age and sex alone. For case-mix adjustment, evaluated comorbidity indices are of equal value.

Beta-blocker use and survival after pancreatic cancer surgery: A nationwide population-based cohort study

PURPOSE

We examined the association between use of beta-blockers and survival in pancreatic cancer patients after curative-intent surgery.

METHODS

Using Danish healthcare registries, we conducted a population-based cohort study of all patients undergoing curative-intent surgery for pancreatic cancer in Denmark 1997-2021. We defined beta-blocker use according to exposure before surgery as current (≤90 days), recent (91-365 days), or former (366-730 days) use, requiring at least one filled prescription. Patients were followed from the date of surgery for up to 5 years. We used Cox regression to compute hazard ratios (HRs) of deaths with 95% confidence intervals (CIs), adjusting for age, sex, year of diagnosis, cardiovascular disease, diabetes, liver disease, alcohol, and smoking. We also conducted an active comparator analysis, where we used angiotensin-converting enzyme inhibitors/angiotensin-receptor blockers as comparators instead of nonusers.

RESULTS

We included 2592 patients, of which 16.7% were beta-blocker users. Median survival for the entire population was 24.4 months. Beta-blocker use was associated with increased mortality (adjusted HR: 1.18; 95% CI: 1.04-1.34). This was evident in current (adjusted HR: 1.19; 95% CI: 1.02-1.38) and recent (adjusted HR: 1.29; 95% CI: 1.04-1.59) but not former (adjusted HR: 0.91; 95% CI: 0.64-1.43) users. In the active comparator analysis, the association between beta-blocker exposure and mortality attenuated slightly (adjusted HR: 1.12; 95% CI: 0.93-1.35).

CONCLUSIONS

We observed an association between beta-blocker use and increased mortality in patients operated for pancreatic cancer. Findings are likely explained by confounding by indication.

Disparities in rheumatoid arthritis outcomes for North American Indigenous populations

Advances in rheumatoid arthritis (RA) management have significantly improved clinical outcomes of this disease; however, some Indigenous North Americans (INA) with RA have not achieved the high rates of treatment success observed in other populations. We review factors contributing to poor long-term outcomes for INA with RA. We conducted a narrative review of studies evaluating RA in INA supplemented with regional administrative health and clinical cohort data on clinical outcomes and health care utilisation. We discuss factors related to conducting research in INA populations including studies of RA prevention. NA with RA have a high burden of genetic and environmental predisposing risk factors that may impact disease phenotype, delayed or limited access to rheumatology care and advanced therapy. These factors may contribute to the observed increased rates of persistent synovitis, premature end-stage joint damage and mortality. Novel models of care delivery that are culturally sensitive and address challenges associated with providing speciality care to patients residing in remote communities with limited accessibility are needed. Progress in establishing respectful research partnerships with INA communities has created a foundation for ongoing initiatives to address care gaps including those aimed at RA prevention. This review highlights some of the challenges of diagnosing, treating, and ultimately perhaps preventing, RA in INA populations.

Frailty predicts increased risk of reintervention in the 2 years after arteriovenous fistula creation

INTRODUCTION

Frailty is associated with adverse survival and increased hospital use in patients with end-stage kidney disease (ESKD). Dialysis access failure is an important source of morbidity and mortality for these patients. There is limited evidence about the interactions between frailty and haemodialysis access failure. This population-based cohort study aimed to determine if haemodialysis access reintervention was predicted by frailty.

METHODS

Routinely-collected hospital data linked with death records were analyzed for all patients with ESKD who had a new arteriovenous fistula or graft (AVF) created between 2010 and 2012 in New South Wales, Australia. Frailty risk was assigned by the Hospital Frailty Risk Score. Multivariate Cox-proportional hazard ratios (HR), adjusted for patient and procedural variables, quantified if frailty was prognostic for adverse haemodialysis access outcomes in the 2 years after AVF creation.

RESULTS

Almost one quarter of the 2302 patients who had a new AVF created during the study period were classified as high frailty risk (554, 24.1%). Compared to low frailty risk patients, patients with high frailty had a significantly greater risk of reintervention for AVF failure in the 2 years after creation (HR 1.68; 95% CI 1.45-1.96), adjusted for age, sex and prior AVFs. Frailer patients were also more likely to have perioperative complications, longer hospital length of stay and readmission to hospital. Frailty was associated with a higher risk of mortality at 2 years after AVF creation (adjusted HR 2.65; 95% CI 1.72-4.10).

CONCLUSION

Frailty predicted adverse haemodialysis access outcomes, with frailer patients having higher rates of AVF reinterventions. These results can assist clinicians engaging in shared decision-making discussions about dialysis access risks and help personalize dialysis access decisions.

Fracture Risk Increases After Stroke or Transient Ischemic Attack and Is Associated With Reduced Quality of Life

BACKGROUND

Fractures are a serious consequence following stroke, but it is unclear how these events influence health-related quality of life (HRQoL). We aimed to compare annualized rates of fractures before and after stroke or transient ischemic attack (TIA), identify associated factors, and examine the relationship with HRQoL after stroke/TIA.

METHODS

Retrospective cohort study using data from the Australian Stroke Clinical Registry (2009-2013) linked with hospital administrative and mortality data. Rates of fractures were assessed in the 1-year period before and after stroke/TIA. Negative binomial regression, with censoring at death, was used to identify factors associated with fractures after stroke/TIA. Respondents provided HRQoL data once between 90 and 180 days after stroke/TIA using the EuroQoL 5-dimensional 3-level instrument. Adjusted logistic regression was used to assess differences in HRQoL at 90 to 180 days by previous fracture.

RESULTS

Among 13 594 adult survivors of stroke/TIA (49.7% aged ≥75 years, 45.5% female, 47.9% unable to walk on admission), 618 fractures occurred in the year before stroke/TIA (45 fractures per 1000 person-years) compared with 888 fractures in the year after stroke/TIA (74 fractures per 1000 person-years). This represented a relative increase of 63% (95% CI, 47%-80%). Factors associated with poststroke fractures included being female (incidence rate ratio [IRR], 1.34 [95% CI, 1.05-1.72]), increased age (per 10-year increase, IRR, 1.35 [95% CI, 1.21-1.50]), history of prior fracture(s; IRR, 2.56 [95% CI, 1.77-3.70]), and higher Charlson Comorbidity Scores (per 1-point increase, IRR, 1.18 [95% CI, 1.10-1.27]). Receipt of stroke unit care was associated with fewer poststroke fractures (IRR, 0.67 [95% CI, 0.49-0.93]). HRQoL at 90 to 180 days was worse among patients with prior fracture across the domains of mobility, self-care, usual activities, and pain/discomfort.

CONCLUSIONS

Fracture risk increases substantially after stroke/TIA, and a history of these events is associated with poorer HRQoL at 90 to 180 days after stroke/TIA.

The effect of general practice contact on cancer stage at diagnosis in Aboriginal and non-Aboriginal residents of New South Wales

PURPOSE

Older age, risks from pre-existing health conditions and socio-economic disadvantage are negatively related to the prospects of an early-stage cancer diagnosis. With older Aboriginal Australians having an elevated prevalence of these underlying factors, this study examines the potential for the mitigating effects of more frequent contact with general practitioners (GPs) in ensuring local-stage at diagnosis.

METHODS

We compared the odds of local vs. more advanced stage at diagnosis of solid tumours according to GP contact, using linked registry and administrative data. Results were compared between Aboriginal (n = 4,084) and non-Aboriginal (n = 249,037) people aged 50 + years in New South Wales with a first diagnosis of cancer in 2003-2016.

RESULTS

Younger age, male sex, having less area-based socio-economic disadvantage, and fewer comorbid conditions in the 12 months before diagnosis (0-2 vs. 3 +), were associated with local-stage in fully-adjusted structural models. The odds of local-stage with more frequent GP contact (14 + contacts per annum) also differed by Aboriginal status, with a higher adjusted odds ratio (aOR) of local-stage for frequent GP contact among Aboriginal people (aOR = 1.29; 95% CI 1.11-1.49) but not among non-Aboriginal people (aOR = 0.97; 95% CI 0.95-0.99).

CONCLUSION

Older Aboriginal Australians diagnosed with cancer experience more comorbid conditions and more socioeconomic disadvantage than other Australians, which are negatively related to diagnosis at a local-cancer stage. More frequent GP contact may act to partly offset this among the Aboriginal population of NSW.

Time to interval cholecystectomy and associated outcomes in a population aged 50 and above with mild gallstone pancreatitis

BACKGROUND

Cholecystectomy on index admission for mild gallstone pancreatitis (GSP) is recommended, although not always feasible. This study examined rates and outcomes of people aged ≥ 50 years who underwent interval (delayed) cholecystectomy at increasing time points.

METHODS

Hospitalisation and death data were linked for individuals aged ≥ 50 years admitted to hospital in New South Wales, Australia with mild GSP between 2008-2018. Primary outcome was interval cholecystectomy timing. Secondary outcomes included mortality, emergency readmission for gallstone-related disease (GSRD) (28 and 180-day), and length of stay (LOS) (index admission and total six-month GSRD).

RESULTS

3,003 patients underwent interval cholecystectomy: 861 (28.6%) at 1-30, 1,221 (40.7%) at 31-90 and 921 (30.7%) at 91-365 days from index admission. There was no difference in 365-day mortality between groups. Longer delay to cholecystectomy was associated with increased 180-day emergency GSRD readmission (17.5% vs 15.8% vs 19.9%, p < 0.001) and total six-month LOS (5.9 vs 8.4 vs 8.3, p < 0.001). Endoscopic retrograde cholangiopancreatography (ERCP) was increasingly required with cholecystectomy delay (14.5% vs 16.9% vs 20.4%, p < 0.001), as were open cholecystectomy procedures (4.8% vs 7.6% vs 11.3%, p < 0.001). Extended delay was associated with patients of lower socioeconomic status, regional/rural backgrounds or who presented to a low volume or non-tertiary hospital (p < 0.001).

CONCLUSION

Delay to interval cholecystectomy results in increased rates of emergency readmission, overall LOS, risks of conversion to open surgery and need for ERCP. Index admission cholecystectomy is still recommended, however when not possible, interval cholecystectomy should be performed within 30 days to minimise patient risk and healthcare burden.

Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease

OBJECTIVE

To develop and validate a tool to predict patients with ischaemic heart disease (IHD) at risk of excessive healthcare resource utilisation.

DESIGN

A retrospective cohort study.

SETTING

We identified patients through the State of Florida Agency for Health Care Administration (N=586 518) inpatient dataset.

PARTICIPANTS

Adult patients (at least 40 years of age) admitted to the hospital with a diagnosis of IHD between 1 January 2007 and 31 December 2016.

PRIMARY OUTCOME MEASURES

We identified patients whose healthcare utilisation is higher than presumed (analysis of residuals) and used logistic regression (binary and multinomial) in estimating the predictive models to classify individual as high-need, high-care (HNHC) patients relative to inpatient visits (frequency of hospitalisation), cost and hospital length of stay. Discrimination power, prediction accuracy and model improvement for the binary logistic model were assessed using receiver operating characteristic statistic, the Brier score and the log-likelihood (LL)-based pseudo-R2, respectively. LL-based pseudo-R2 and Brier score were used for multinomial logistic models.

RESULTS

The binary logistic model had good discrimination power (c-statistic=0.6496), an accuracy of probabilistic predictions (Brier score) of 0.0621 and an LL-based pseudo-R2 of 0.0338 in the development cohort. The model performed similarly in the validation cohort (c-statistic=0.6480), an accuracy of probabilistic predictions (Brier score) of 0.0620 and an LL-based pseudo-R2 of 0.0380. A user-friendly Excel-based HNHC risk predictive tool was developed and readily available for clinicians and policy decision-makers.

CONCLUSIONS

The Excel-based HNHC risk predictive tool can accurately identify at-risk patients for HNHC based on three measures of healthcare expenditures.

Days alive and at home after hip fracture: a cross-sectional validation of a patient-centred outcome measure using routinely collected data

BACKGROUND

Days alive and at home (DAH) is a patient centered outcome measureable in routinely collected health data. The validity and minimally important difference (MID) in hip fracture have not been evaluated.

OBJECTIVE

We assessed construct and predictive validity and estimated a MID for the patient-centred outcome of DAH after hip fracture admission.

METHODS

This is a cross-sectional observational study using linked health administrative data in Ontario, Canada. DAH was calculated as the number of days alive within 90 days of admission minus the number of days hospitalised or institutionalised. All hospital admissions (2012-2018) for hip fracture in adults aged >50 years were included. Construct validity analyses used Bayesian quantile regression to estimate the associations of postulated patient, admission and process-related variables with DAH. The predictive validity assessed was the correlation of DAH in 90 days with the value from 91 to 365 days; and the association and discrimination of DAH in 90 days predicting subsequent mortality. MID was estimated by averaging distribution-based and clinical anchor-based estimates.

RESULTS

We identified 63 778 patients with hip fracture. The median number of DAH was 43 (range 0-87). In the 90 days after admission, 8050 (12.6%) people died; a further 6366 (10.0%) died from days 91 to 365. Associations between patient-level and admission-level factors with the median DAH (lower with greater age, frailty and comorbidity, lower if admitted to intensive care or having had a complication) supported construct validity. DAH in 90 days after admission was strongly correlated with DAH in 365 days after admission (r=0.922). An 11-day MID was estimated.

CONCLUSION

DAH has face, construct and predictive validity as a patient-centred outcome in patients with hip fracture, with an estimated MID of 11 days. Future research is required to include direct patient perspectives in confirming MID.

Targeted care navigation to reduce hospital readmissions in 'at-risk' patients

BACKGROUND

Care navigation is commonly used to reduce preventable hospitalisation. The use of Electronic Health Record-derived algorithms may enable better targeting of this intervention for greater impact.

AIMS

To evaluate if community-based Targeted Care Navigation, supported by an Electronic Health Record-derived readmission risk algorithm, is associated with reduced rehospitalisation.

METHODS

A propensity score matching cohort (5 comparison to 1 intervention cohort ratio) study was conducted in an 850-bed Victorian public metropolitan health service, Australia, from May to November 2017. Admitted acute care patients with a non-surgical condition, identified as at-risk of hospital readmission using an Electronic Health Record-derived readmission risk algorithm provide by the state health department, were eligible. Targeted Care Navigation involved telephone follow-up support provided for 30 days post-discharge by a registered nurse. The hazard ratio for hospital readmission was calculated at 30, 60 and 90 days post-discharge using multivariable Cox Proportional Hazards regression.

RESULTS

Sixty-five recipients received care navigation and were matched to 262 people who did not receive care navigation. Excellent matching was achieved with standardised differences between groups being <0.1 for all 11 variables included in the propensity score, including the readmission risk score. The Targeted Care Navigation group had a significantly reduced hazard of readmission at 30 days (hazard ratio 0.34; 95% confidence interval: 0.12, 0.94) compared with the comparison group. The effect size was reduced at 60 and 90 days post-discharge.

CONCLUSION

We provide preliminary evidence that Targeted Care Navigation supported by an Electronic Health Record-derived readmission risk algorithm may reduce 30-day hospital readmissions.

All-Cause Readmission or Potentially Avoidable Readmission: Which Is More Predictable Using Frailty, Comorbidities, and ADL?

Background and Objectives

Readmission-related health care reforms have shifted their focus from all-cause readmissions (ACR) to potentially avoidable readmissions (PAR). However, little is known about the utility of analytic tools from administrative data in predicting PAR. This study determined whether 30-day ACR or 30-day PAR is more predictable using tools that assess frailty, comorbidities, and activities of daily living (ADL) from administrative data.

Research Design and Methods

This retrospective cohort study was conducted at a large general acute care hospital in Tokyo, Japan. We analyzed patients aged ≥70 years who had been admitted to and discharged from the subject hospital between July 2016 and February 2021. Using administrative data, we assessed each patient's Hospital Frailty Risk Score, Charlson Comorbidity Index, and Barthel Index on admission. To determine the influence of each tool on readmission predictions, we constructed logistic regression models with different combinations of independent variables for predicting unplanned ACR and PAR within 30 days of discharge.

Results

Among 16 313 study patients, 4.1% experienced 30-day ACR and 1.8% experienced 30-day PAR. The full model (including sex, age, annual household income, frailty, comorbidities, and ADL as independent variables) for 30-day PAR showed better discrimination (C-statistic: 0.79, 95% confidence interval: 0.77-0.82) than the full model for 30-day ACR (0.73, 0.71-0.75). The other prediction models for 30-day PAR also had consistently better discrimination than their corresponding models for 30-day ACR.

Discussion and Implications

PAR is more predictable than ACR when using tools that assess frailty, comorbidities, and ADL from administrative data. Our PAR prediction model may contribute to the accurate identification of at-risk patients in clinical settings who would benefit from transitional care interventions.

Patient-Reported Symptom Burden and Supportive Care Needs of Patients With Stage II-III Colorectal Cancer During and After Adjuvant Systemic Treatment: A Real-World Evidence Study

PURPOSE

Patients with colorectal cancer (CRC) experience a range of physical and psychologic symptoms, and supportive care needs throughout the illness trajectory. We used patient-reported outcomes and administrative health data to describe symptom burden and supportive care needs during and after adjuvant treatment and determine factors associated with changes to symptom burden.

METHODS

A retrospective population-based cohort study of patients who were newly diagnosed with stage II-III CRC in Alberta, Canada, between January 1, 2016, and January 31, 2019. Adults age 18 years or older who completed a patient-reported outcomes survey (Edmonton Symptom Assessment System) and supportive care needs (Canadian Problem Checklist) within 3 months after starting adjuvant treatment (during treatment) and > 7 months after starting treatment (after treatment) were included. Changes to symptom severity were stratified as stable, improved, or deteriorated. Multivariable logistic regression was used to evaluate factors associated with these changes.

RESULTS

We included 303 patients (median age 60 years, 62% male, 84.5% stage III, 51.2% rectal v colon). Prevalent symptoms included tiredness (80.5%), pain (50.8%), and poor well-being (50%) during treatment, and tiredness (71.3%), pain (44.2%), and poor well-being (62.1%) after treatment. The results were heterogeneous with respect to improvements, stability, or deterioration. Pain worsened for 25% of the cohort, tiredness for 28%, and depression, anxiety, and well-being for 21%, 22%, and 31%, respectively. Deterioration of some symptoms was associated with older age, stage II, comorbidities, rural setting, and higher income.

CONCLUSION

We demonstrated symptom severity was generally low and most symptoms remained stable or improved after treatment. Particular groups of patients were at greater risk for more severe and/or more persistent symptoms. Ongoing assessments and interventions to address physical and psychologic symptoms, and supportive care needs in patients with CRC during and after treatment are needed.

Impact of comorbidities on survival following major injury across different types of road users

BACKGROUND

While comorbidities and types of road users are known to influence survival in people hospitalised with injury, few studies have examined the association between comorbidities and survival in people injured in road traffic crashes. Further, few studies have examined outcomes across different types of road users with different types of pre-existing comorbidities. This study aims to examine differences in survival within 30 days of admission among different road user types with and without different pre-existing comorbidities.

METHOD

Retrospective cohort study using data for all major road trauma cases were extracted from the NSW Trauma Registry Minimum Dataset (1 January 2013 - 31 July 2019) and linked to the NSW Admitted Patient Data Collection, and the NSW Registry of Births, Deaths and Marriages - death dataset. Pre-existing comorbidities and road user types were identified by the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) codes and Charlson Comorbidity Index in the Trauma Registry, hospital admission, and death datasets. Logistic regression was used to assess the associations between six types of road users (pedestrian, pedal cycle, two- and three-wheel motorcycle, car and pick-up truck, heavy vehicle and bus, and other types of vehicle) and death within 30 days of hospital admission while controlling for comorbidities. All models used 'car and pick-up truck driver/passenger' as the road user reference group and adjusted for demographic variables, injury severity, and level of impaired consciousness.

RESULTS

Within 6253 traffic injury person-records (all aged ≥15 years old, ISS>12), and in final models, injured road users with major trauma who had a history of cardiovascular diseases (including stroke), diabetes mellitus, and higher Charlson Comorbidity Index score, were more likely to die, than those without pre-existing comorbidities. Furthermore, in final models, pedestrians were more likely to die than car occupants (OR: 1.68 - 1.77, 95CI%: 1.26 - 2.29 depending on comorbidity type).

CONCLUSIONS

This study highlights the need to prioritize enhanced management of trauma patients with comorbidities, given the increasing prevalence of chronic medical conditions globally, together with actions to prevent pedestrian crashes in strategies to reach Vision Zero.

Occurrence of comorbidity with colorectal cancer and variations by age and stage at diagnosis

BACKGROUND

While age and stage at diagnosis are known to affect treatment choices and survival from colorectal cancer (CRC), few studies have investigated the extent to which these effects are influenced by comorbidity. In this study, we describe the occurrence of comorbidity in CRC cases in South Australia and associations of comorbidity with age, stage and the age-stage relationship. Furthermore, we report on the association of individual comorbidities with age and stage at diagnosis.

METHODS

The South Australian Cancer Registry (SACR) provided CRC data (C18-C20, ICD-10) for 2004-2013 diagnoses. CRC data were linked with comorbidity data drawn from hospital records and health insurance claims. Logistic regression was used to model associations of comorbidity with age and stage.

RESULTS

For the 8462 CRC cases in this study, diabetes, peptic ulcer disease, and previous cancers were the most commonly recorded co-existing conditions. Most comorbidities were associated with older age, although some presented more frequently in younger people. Patients at both ends of the age spectrum (<50 and 80 + years) had an increased likelihood of CRC diagnosis at an advanced stage compared with other ages (50-79 years old). Adjusting for comorbidities moderated the association of older age with advanced stage. Conditions associated with advanced stage included dementia (OR = 1.25 (1.01-1.55)), severe liver disease (OR = 1.68 (1.04-2.70)), and a previous cancer (OR = 1.18 (1.08-1.28)).

CONCLUSION

Comorbidities are prevalent with CRC, especially in older people. These comorbidities differ in their associations with age at diagnosis and stage. Dementia and chronic heart failure were associated with older age whereas inflammatory bowel disease and alcohol access were associated with younger onset of the disease. Severe liver disease and dementia were associated with more advanced stage and rheumatic disease with less advanced stage. Comorbidities also interact with age at diagnosis and appear to vary the likelihood of advanced-stage disease. CRC patient have different association of age with stage depending on their comorbidity status.

Seasonality in hip fracture among hemodialysis patients and kidney transplant recipients in South Korea

BACKGROUND

The seasonality of hip fracture in hemodialysis (HD) patients and kidney transplant recipients (KTRs) have not been reported. We assessed seasonal variations in hip fractures among patients with end-stage kidney disease who undergo maintenance HD and KTRs.

METHODS

Using the Korean National Health Insurance System database from January 2012 to December 2017, monthly counts of hip fracture were calculated among HD patients (n = 77,420) and KTRs (n = 8,921). The 6-year normalized monthly fraction and seasonal fractions of hip fractures were calculated. A cosinor analysis was performed to determine the seasonality of the monthly incidence of hip fractures.

RESULTS

The 6-year average monthly fraction of hip fractures was lowest in June and highest in October in HD patients, and lowest in February and highest in November in KTRs. The 6-year average seasonal fraction among HD patients was lowest in summer and highest in winter, and lowest in summer and highest in autumn among KTRs, but there was no significant difference. The incidence ratio of hip fractures was lowest in June and highest in January in HD patients, and lowest in August and highest in November in KTRs. On cosinor analysis, HD patients showed significant seasonality in hip fracture incidence, with a trough in summer and a peak in winter (P = 0.031), whereas KTRs did not exhibit a significant trend (P = 0.44).

CONCLUSION

Hip fractures occurred more frequently in winter and less frequently in summer in patients undergoing HD, whereas KTRs did not show a seasonal trend.

Smoking Status, Nicotine Medication, Vaccination, and COVID-19 Hospital Outcomes: Findings from the COVID EHR Cohort at the University of Wisconsin (CEC-UW) Study

INTRODUCTION

Available evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown.

METHODS

Electronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission.

RESULTS

Current (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97).

CONCLUSIONS

Former but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers.

IMPLICATIONS

Prior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.

Does a History of Cancer Influence the Effectiveness of Statins on Outcomes After Stroke?

BACKGROUND

Evidence is growing on anticancer effects of statins. We investigated whether the effectiveness of treatment with statins after ischemic stroke on mortality is influenced by a history of cancer.

METHODS

Analyses of 90-day survivors of ischemic stroke (2012-2016; 45 hospitals) using linked registry and administrative data. Dispense of statins within 90 days postdischarge was determined from pharmaceutical records. Participants were followed from 91 days postdischarge until death or June 30, 2018. History of cancer was determined from hospital data. Propensity score-adjusted Cox proportional hazards regression model was used to determine the association between being dispensed statins and survival. The influence of history of cancer on this association was assessed based on the concepts of (1) statistical interaction and (2) biological interaction using 3 indices: relative excess risk due to interaction>0, attributable proportion due to interaction >0, or synergy index >1.

RESULTS

Among 9948 eligible participants (median age=72 years, 42% female), there were 1463 deaths. In adjusted analyses, there was no statistical interaction between being dispensed statins and history of cancer on mortality (P=0.156). However, being dispensed statins had a significant positive biological interaction with having a history of cancer on mortality: relative excess risk due to interaction, 2.80 (95% CI, 1.56-5.05), attributable proportion due to interaction, 0.45 (95% CI, 0.23-0.66), and synergy index, 2.14 (95% CI, 1.32-3.49).

CONCLUSIONS

Treatment with statins after ischemic stroke may confer additional survival benefits for people who also have had cancer.

Cholecystectomy for people aged 50 years or more with mild gallstone pancreatitis: predictors and outcomes of index and interval procedures

Objectives

To estimate the proportions of people aged 50 years or more with mild gallstone pancreatitis who undergo index cholecystectomy (during their initial hospital admission) or interval cholecystectomy (during a subsequent admission); to compare outcomes following index and interval cholecystectomy; and to identify factors associated with undergoing interval cholecystectomy.

Design, setting, participants

Analysis of linked hospitalisation and deaths data for all people aged 50 years or more with mild gallstone pancreatitis who underwent cholecystectomy in New South Wales within twelve months of their index admission, 1 July 2008 ‒ 30 June 2018.

Main outcome measures

Cholecystectomy classification (index or interval). Secondary outcomes: all‐cause mortality (30‒365 days), emergency re‐admissions with gallstone‐related disease (within 28 or 180 days of discharge); hospital lengths of stay (index admission, and all admissions with gallstone‐related disease over six months).

Results

A total of 1836 patients underwent index cholecystectomy (37.9%) and 3003 interval cholecystectomy (62.1%). Mortality to twelve months was similar in the two groups. Larger proportions of people who underwent interval cholecystectomy were re‐admitted within 28 days (246, 8.2% v 23, 1.3%) or 180 days (527, 17.6% v 59, 3.2%), or required open cholecystectomy (238, 7.9% v 69, 3.8%). Mean index admission length of stay was longer for index than interval cholecystectomy (7.7 [SD, 4.7] days v 5.3 [SD, 3.9] days), but six‐month total length of stay was similar (8.2 [SD, 5.6] days v 7.9 [SD, 5.8] days). Interval cholecystectomy was more likely for patients with three or more comorbid conditions (adjusted odds ratio [aOR], 1.29; 95% CI, 1.08‒1.55) or private health insurance (aOR, 1.31; 95% CI, 1.13‒1.51), and for those admitted to low surgical volume hospitals (aOR, 1.84; 95% CI, 1.03‒3.31).

Conclusions

Most NSW people over 50 with mild gallstone pancreatitis did not undergo index cholecystectomy, despite recommendations in international guidelines. Delayed cholecystectomy was associated with more frequent open cholecystectomy procedures and gallstone disease‐related emergency re‐admissions, as well as with low or medium hospital surgical volume, comorbidity, and having private insurance.

Identifying multimorbidity clusters in an unselected population of hospitalised patients

Multimorbidity (multiple coexisting chronic health conditions) is common and increasing worldwide, and makes care challenging for both patients and healthcare systems. To ensure care is patient-centred rather than specialty-centred, it is important to know which conditions commonly occur together and identify the corresponding patient profile. To date, no studies have described multimorbidity clusters within an unselected hospital population. Our aim was to identify and characterise multimorbidity clusters, in a large, unselected hospitalised patient population. Linked inpatient hospital episode data were used to identify adults admitted to hospital in Grampian, Scotland in 2014 who had ≥ 2 of 30 chronic conditions diagnosed in the 5 years prior. Cluster analysis (Gower distance and Partitioning around Medoids) was used to identify groups of patients with similar conditions. Clusters of conditions were defined based on clinical review and assessment of prevalence within patient groups and labelled according to the most prevalent condition. Patient profiles for each group were described by age, sex, admission type, deprivation and urban–rural area of residence. 11,389 of 41,545 hospitalised patients (27%) had ≥ 2 conditions. Ten clusters of conditions were identified: hypertension; asthma; alcohol misuse; chronic kidney disease and diabetes; chronic kidney disease; chronic pain; cancer; chronic heart failure; diabetes; hypothyroidism. Age ranged from 51 (alcohol misuse) to 79 (chronic heart failure). Women were a higher proportion in the chronic pain and hypothyroidism clusters. The proportion of patients from the most deprived quintile of the population ranged from 6% (hypertension) to 14% (alcohol misuse). Identifying clusters of conditions in hospital patients is a first step towards identifying opportunities to target patient-centred care towards people with unmet needs, leading to improved outcomes and increased efficiency. Here we have demonstrated the face validity of cluster analysis as an exploratory method for identifying clusters of conditions in hospitalised patients with multimorbidity.

Quality of Care and One-Year Outcomes in Patients with Diabetes Hospitalised for Stroke or TIA: A Linked Registry Study

OBJECTIVES

To evaluate key quality indicators for acute care and one-year outcomes following acute ischaemic stroke (IS), intracerebral haemorrhage (ICH), or transient ischaemic attack (TIA) by diabetes status.

MATERIALS AND METHODS

Observational cohort study (2009-2013) using linked data from the Australian Stroke Clinical Registry and hospital records. Diabetes was ascertained through review of hospital records. Multilevel regression models were used to evaluate the association between diabetes and outcomes, including discharge destination, and mortality and hospital readmissions within one-year of stroke/TIA.

RESULTS

Among 14,132 patients (median age 76 years, 46% female), 22% had diabetes. Compared to patients without diabetes, those with diabetes were equally likely to receive stroke unit care, but were more often discharged on antihypertensive agents (79% vs. 68%) or with a care plan (50% vs. 47%). In patients with TIA, although 86% returned directly home after acute care, those with diabetes more often had a different discharge destination than those without diabetes. Diabetes was associated with greater all-cause mortality (hazard ratio 1.13, 95% CI 1.04-1.23) in patients with IS/ICH; and with both greater all-cause (1.81, CI 1.35-2.43) and CVD mortality (1.75, CI 1.06-2.91) in patients with TIA. Similarly, diabetes was associated with greater rates of all-cause readmission in both patients with IS/ICH and TIA.

CONCLUSIONS

Despite good adherence to best care standards for acute stroke/TIA, patients with comorbid diabetes had worse outcomes at one-year than those without comorbid diabetes. Associations of diabetes with poorer outcomes were more pronounced in patients with TIA than those with IS/ICH.

The psychological symptom burden in partners of pancreatic cancer patients: a population-based cohort study

PURPOSE

Pancreatic cancer (PC) has high morbidity and mortality and is stressful for patients and their partners. We investigated the psychological symptom burden in partners of PC patients.

METHODS

We followed 5774 partners of PC patients diagnosed from 2000 to 2016 up for first redeemed prescriptions of antidepressants or hospital admission, anxiolytics, and hypnotics as proxies for clinical depression, anxiety, and insomnia and compared them with 59,099 partners of cancer-free spouses. Data were analysed using Cox regression and multistate Markov models.

RESULTS

The cumulative incidence proportion of first depression was higher in partners of PC patients compared to comparisons. The highest adjusted HR of first depression was seen the first year after diagnosis (HR 3.2 (95% CI: 2.9; 3.7)). Educational level, chronic morbidity, and bereavement status were associated with an increased risk of first depression. There was a significantly higher first acute use (1 prescription only) of both anxiolytics and hypnotics and chronic use (3+ prescriptions) of hypnotics in partners of PC patients than in comparisons.

CONCLUSION

Being a partner to a PC patient carries a substantial psychological symptom burden and increases the risk for first depression and anxiolytic use and long-term use of hypnotics. Attention should be given to the psychological symptom burden of partners of PC patients, as this may pose a barrier for the optimal informal care and support of the PC patient, as well as a risk for non-optimal management of symptoms in the partner.

Does identifying frailty from ICD-10 coded data on hospital admission improve prediction of adverse outcomes in older surgical patients? A population-based study

BACKGROUND

frailty is a major contributor to poor health outcomes in older people, separate from age, sex and comorbidities. This population-based validation study evaluated the performance of the International Classification of Diseases, 10th revision, coded Hospital Frailty Risk Score (HFRS) in the prediction of adverse outcomes in an older surgical population and compared its performance against the commonly used Charlson Comorbidity Index (CCI).

METHODS

hospitalisation and death data for all individuals aged ≥50 admitted for surgery to New South Wales hospitals (2013-17) were linked. HFRS and CCI scores were calculated using both 2- and 5-year lookback periods. To determine the influence of individual explanatory variables, several logistic regression models were fitted for each outcome of interest (30-day mortality, prolonged length of stay (LOS) and 28-day readmission). Area under the receiving operator curve (AUC) and Akaike information criterion (AIC) were assessed.

RESULTS

of the 487,197 patients, 6.8% were classified as high HFRS, and 18.3% as high CCI. Although all models performed better than base model (age and sex) for prediction of 30-day mortality, there was little difference between CCI and HFRS in model discrimination (AUC 0.76 versus 0.75), although CCI provided better model fit (AIC 79,020 versus 79,910). All models had poor ability to predict prolonged LOS (AUC range 0.62-0.63) or readmission (AUC range 0.62-0.65). Using a 5-year lookback period did not improve model discrimination over the 2-year period.

CONCLUSIONS

adjusting for HFRS did not improve prediction of 30-mortality over that achieved by the CCI. Neither HFRS nor CCI were useful for predicting prolonged LOS or 28-day unplanned readmission.

Impact of comorbidity assessment methods to predict non-cancer mortality risk in cancer patients: a retrospective observational study using the National Health Insurance Service claims-based data in Korea

BACKGROUND

Cancer patients' prognoses are complicated by comorbidities. Prognostic prediction models with inappropriate comorbidity adjustments yield biased survival estimates. However, an appropriate claims-based comorbidity risk assessment method remains unclear. This study aimed to compare methods used to capture comorbidities from claims data and predict non-cancer mortality risks among cancer patients.

METHODS

Data were obtained from the National Health Insurance Service-National Sample Cohort database in Korea; 2979 cancer patients diagnosed in 2006 were considered. Claims-based Charlson Comorbidity Index was evaluated according to the various assessment methods: different periods in washout window, lookback, and claim types. The prevalence of comorbidities and associated non-cancer mortality risks were compared. The Cox proportional hazards models considering left-truncation were used to estimate the non-cancer mortality risks.

RESULTS

The prevalence of peptic ulcer, the most common comorbidity, ranged from 1.5 to 31.0%, and the proportion of patients with ≥1 comorbidity ranged from 4.5 to 58.4%, depending on the assessment methods. Outpatient claims captured 96.9% of patients with chronic obstructive pulmonary disease; however, they captured only 65.2% of patients with myocardial infarction. The different assessment methods affected non-cancer mortality risks; for example, the hazard ratios for patients with moderate comorbidity (CCI 3-4) varied from 1.0 (95% CI: 0.6-1.6) to 5.0 (95% CI: 2.7-9.3). Inpatient claims resulted in relatively higher estimates reflective of disease severity.

CONCLUSIONS

The prevalence of comorbidities and associated non-cancer mortality risks varied considerably by the assessment methods. Researchers should understand the complexity of comorbidity assessments in claims-based risk assessment and select an optimal approach.

More than two-dozen prescription drug-based risk scores are available for risk adjustment: A systematic review

OBJECTIVE

While several prescription drug-based risk indices have been developed, their design, performance, and application has not previously been synthesized.

STUDY DESIGN AND SETTING

We searched Ovid MEDLINE, CINAHL and Embase from inception through March 3, 2020 and included studies that developed or updated a prescription drug-based risk index. Two reviewers independently performed screening and extracted information on data source, study population, cohort sizes, outcomes, study methodology and performance. Predictive performance was evaluated using C statistics for binary outcomes and R² for continuous outcomes. The PROSPERO ID for this review is CRD42020165498.

RESULTS

Of 19,112 articles that were retrieved, 124 were full-text screened and 25 were included, each of which represented a de novo or updated drug-based index. The indices were customized to varied age groups and clinical populations and most commonly evaluated outcomes including mortality (36%), hospitalization (24%) and healthcare costs (24%). C statistics ranged from 0.62 to 0.92 for mortality and 0.59 to 0.72 for hospitalization, while adjusted R² for healthcare costs ranged from 0.06 to 0.62. Seven of the 25 risk indices included used global drug classification algorithms.

CONCLUSIONS

More than two-dozen prescription drug-based risk indices have been developed and they differ significantly in design, performance and application.

Multimorbidity in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: Results From a Longitudinal, Multicenter Data Linkage Study

OBJECTIVE

Antineutrophil cytoplasmic antibody-associated vasculitis (AAV) is considered a chronic, relapsing condition. To date, no studies have investigated multimorbidity in AAV nationally. This study was undertaken to characterize temporal trends in multimorbidity and report excess health care expenditures associated with multimorbidities in a national AAV cohort from Scotland.

METHODS

Eligible patients with AAV were diagnosed between 1997 and 2017. Each patient was matched with up to 5 general population controls. Linked morbidity and health care expenditure data were retrieved from a Scottish national hospitalization repository and from published national cost data. Multimorbidity was defined as the development of ≥2 disorders. Prespecified morbidities, individually and together, were analyzed for risks and associations over time using modified Poisson regression, discrete interval analysis, and chi-square test for trend. The relationship between multimorbidities and health care expenditure was investigated using multivariate linear regression.

RESULTS

In total, 543 patients with AAV (median age 58.7 years [range 48.9-68.0 years]; 53.6% male) and 2,672 general population controls (median age 58.7 years [range 48.9-68.0 years]; 53.7% male) were matched and followed up for a median of 5.1 years. AAV patients were more likely to develop individual morbidities at all time points, but especially <2 years after diagnosis. The highest proportional risk observed was for osteoporosis (adjusted incidence rate ratio 8.0, 95% confidence interval [95% CI] 4.5-14.2). After 1 year, 23.0% of AAV patients and 9.3% of controls had developed multimorbidity (P < 0.0001). After 10 years, 37.0% of AAV patients and 17.3% of controls were reported to have multimorbidity (P < 0.0001). Multimorbidity was associated with disproportionate increases in health care expenditures in AAV patients. Health care expenditure was highest for AAV patients with ≥3 morbidities (3.89-fold increase in costs, 95% CI 2.83-5.31; P < 0.001 versus no morbidities).

CONCLUSION

These findings emphasize the importance of holistic care in patients with AAV, and may identify a potentially critical opportunity to consider early screening.

Identification of risk factors of 30-day readmission and 180-day in-hospital mortality, and its corresponding relative importance in patients with Ischemic heart disease: a machine learning approach

Background: The primary objective of this study is to identify non-laboratory predictors for 30-day hospital readmission and 180-day in-hospital mortality rates among patients hospitalized with ischemic heart disease (IHD).Research design and methods: This is a retrospective cohort study of hospitalized patients (≥ 40 years) with a primary diagnosis of IHD. Data were extracted from the Florida Agency for Health Care Administration dataset from 2006 to 2016. A machine learning approach was used to identify predictors of 30-day hospital readmission and 180-day in-hospital mortality.Results: 346,390 patient records for incident IHD cases were identified. The top two predictors of 30-day readmission were the length of stay and the Elixhauser comorbidity index for readmission [ECI] (Area Under the Curve [AUC]=88%) using decision tree algorithms. For in-hospital mortality, the top two predictors were LOS and ECI (AUC=92%) using gradient boosting regressors. The cumulative 30-day readmission and the 180-day probability of mortality rates were 9.82% and 4.6% respectively.Conclusions: Risk factors of 30-day readmission and 180-day mortality in hospitalized IHD patients identified by machine learning and their relative importance (value) will help pharmacists and other health care providers to prioritize their disease management strategies as they improve the care provided to IHD patients.

Surgical repair of parastomal bulging: a retrospective register-based study on prospectively collected data

AIM

The aim of this work was to examine (1) the incidence of primary repair, (2) the incidence of recurrent repair and (3) the types of repair performed in patients with parastomal bulging.

METHOD

Prospectively collected data on parastomal bulging from the Danish Stoma Database were linked to surgical data on repair of parastomal bulging from the Danish National Patient Register. Survival statistics provided cumulative incidences and time until primary and recurrent repair.

RESULTS

In the study sample of 1016 patients with a permanent stoma and a parastomal bulge, 180 (18%) underwent surgical repair. The cumulative incidence of a primary repair was 9% [95% CI (8%; 11%)] within 1 year and 19% [95% CI (17%; 22%)] within 5 years after the occurrence of a parastomal bulge. We found a similar probability of undergoing primary repair in patients with ileostomy and colostomy. For recurrent repair, the 5-year cumulative incidence was 5% [95% CI (3%; 7%)]. In patients undergoing repair, the probability was 33% [95% CI (21%; 46%)] of having a recurrence requiring repair within 5 years. The main primary repair was open or laparoscopic repair with mesh (43%) followed by stoma revision (39%). Stoma revision and repair with mesh could precede or follow one another as primary and recurrent repair. Stoma reversal was performed in 17% of patients.

CONCLUSION

Five years after the occurrence of a parastomal bulge the estimated probability of undergoing a repair was 19%. Having undergone a primary repair, the probability of recurrent repair was high. Stoma reversal was more common than expected.

Hospital Presentations in Long-Term Survivors of Stroke: Causes and Associated Factors in a Linked Data Study

BACKGROUND AND PURPOSE

A comprehensive understanding of the long-term impact of stroke assists in health care planning. We aimed to determine changes in rates, causes, and associated factors for hospital presentations among long-term survivors of stroke.

METHODS

Person-level data from the AuSCR (Australian Stroke Clinical Registry) during 2009 to 2013 were linked with state-based health department emergency department and hospital admission data. The study cohort included adults with first-ever stroke who survived the first 6 months after discharge from hospital. Annualized rates of hospital presentations (nonadmitted emergency department or admission)/person/year were calculated for 1 to 12 months prior, and 7 to 12 months (inclusive) after hospitalization. Multilevel, negative binomial regression was used to identify associated factors after adjustment for prestroke hospital presentations and stratification for perceived impairment status. Perceived impairments to health were defined according to the subscales and visual analog health status scores on the 5-Dimension European Quality of Life Scale.

RESULTS

There were 7183 adults with acute stroke, 7-month survivors (median age 72 years; 56% male; 81% ischemic, and 42% with impairment at 90-180 days) from 39 hospitals included in this landmark analysis. Annualized presentations/person increased from 0.88 (95% CI, 0.86-0.91) to 1.25 (95% CI, 1.22-1.29) between the prestroke and poststroke periods, with greater rate increases in those with than without perceived impairment (55% versus 26%). Higher presentation rates were most strongly associated with older age (≥85 versus 65 years, incidence rate ratio, 1.52 [95% CI, 1.27-1.82]) and greater comorbidity score (incidence rate ratio, 1.06 [95% CI, 1.02-1.10]), whereas reduced rates were associated with greater social advantage (incidence rate ratio, 0.71 [95% CI, 0.60-0.84]). Poststroke hospital presentations (7-12 months) were most frequently related to recurrent cardiovascular and cerebrovascular events and sequelae of stroke.

CONCLUSIONS

A large increase in annualized hospital presentation rates after stroke indicates the potential for improved community management and support for this vulnerable patient group.

The association between general practitioner regularity of care and 'high use' hospitalisation

Background

In Australia, as in many high income countries, there has been a movement to improve out-of-hospital care. If primary care improvements can yield appropriately lower hospital use, this would improve productive efficiency. This is especially important among ‘high cost users’, a small group of patients accounting for disproportionately high hospitalisation costs. This study aimed to assess the association between regularity of general practitioner (GP) care and ‘high use’ hospitalisation.

Methods

This retrospective, cohort study used linked administrative and survey data from the 45 and Up Study, conducted in New South Wales, Australia. The exposure was regularity of GP care between 1 July 2005 and 30 June 2009, categorised by quintile (lowest to highest). Outcomes were ‘high use’ of hospitalisation (defined as ≥3 and ≥ 5 admissions within 12 months), extended length of stay (LOS, ≥30 days), a combined metric (≥3 hospitalisations in a 12 month period where ≥1 hospitalisation was ≥30 days) and 30-day readmission between 1 July 2009 and 31 December 2017. Associations were assessed using multivariable logistic regression. Potential for outcome prevention in a hypothetical scenario where all individuals attain the highest GP regularity was estimated via the population attributable fraction (PAF).

Results

Of 253,500 eligible participants, 15% had ≥3 and 7% had ≥5 hospitalisations in a 12-month period. Five percent of the cohort had a hospitalisation lasting ≥30 days and 25% had a readmission within 30 days. Compared with lowest regularity, highest regularity was associated with between 6% (p < 0.001) and 11% (p = 0.027) lower odds of ‘high use’. There was a 7–8% reduction in odds for all regularity levels above ‘low’ regularity for LOS ≥30 days. Otherwise, there was no clear sequential reduction in ‘high use’ with increasing regularity. The PAF associated with a move to highest regularity ranged from 0.05 to 0.13. The number of individuals who could have had an outcome prevented was estimated to be between 269 and 2784, depending on outcome.

Conclusions

High GP regularity is associated with a decreased likelihood of ‘high use’ hospitalisation, though for most outcomes there was not an apparent linear association with regularity.

Combining Charlson and Elixhauser scores with varying lookback predicated mortality better than using individual scores

OBJECTIVE

To investigate variation in the presence of secondary diagnosis codes in Charlson and Elixhauser comorbidity scores and assess whether including a 1-year lookback period improved prognostic adjustment by these scores individually, and combined, for 30-day mortality.

STUDY DESIGN AND SETTING

We analyzed inpatient admissions from January 1, 2007 to May 18, 2018 in Oxfordshire, UK. Comorbidity scores were calculated using secondary diagnostic codes in the diagnostic-dominant episode, and primary and secondary codes from the year before. Associations between scores and 30-day mortality were investigated using Cox models with natural cubic splines for nonlinearity, assessing fit using Akaike Information Criteria.

RESULTS

The 1-year lookback improved model fit for Charlson and Elixhauser scores vs. using diagnostic-dominant methods. Including both, and allowing nonlinearity, improved model fit further. The diagnosis-dominant Charlson score and Elixhauser score using a 1-year lookback, and their interaction, provided the best comorbidity adjustment (reduction in AIC: 761 from best single score model).

CONCLUSION

The Charlson and Elixhauser score calculated using primary and secondary diagnostic codes from 1-year lookback with secondary diagnostic codes from the current episode improved individual predictive ability. Ideally, comorbidities should be adjusted for using both the Charlson (diagnostic-dominant) and Elixhauser (1-year lookback) scores, incorporating nonlinearity and interactions for optimal confounding control.

Health impacts and economic costs of residential fires (RESFIRES study): protocol for a population-based cohort study using linked administrative data

INTRODUCTION

Residential fires remain a significant global public health problem. It is recognised that the reported number of residential fires, fire-related injuries and deaths significantly underestimate the true number. Australian surveys show that around two-thirds of respondents who experience a residential fire are unwilling to call the fire service, and international studies highlight that many individuals who access medical treatment for fire-related injuries do not have an associated fire incident report. The objectives of this study are to quantify the incidence, health impacts, risk factors and economic costs of residential fires in New South Wales (NSW), Australia.

METHODS AND ANALYSIS

The RESFIRE cohort will include all persons living at an NSW residential address which experienced a fire over the period 2005-2014. Nine data sources will be linked to provide a comprehensive picture of individual trajectories from fire event to first responder use (fire and ambulance services), emergency department presentations, hospital admissions, burn out-patient clinic use and death. These data will be used to describe the circumstances and characteristics of residential fires, provide a profile of fire-related injuries, examine trends over time, and explore the relationship between fire circumstance, emergency and health services utilisation, and health outcomes. Regression modelling, including multilevel modelling techniques, will be used to explore factors that impact on these relationships. Costing models will be constructed.

ETHICS AND DISSEMINATION

Ethical approval for this study has been obtained from the NSW Population and Health Service Research Ethics Committee and Western Sydney University Human Research Ethics Committee. The study reference group comprises key stakeholders including Fire and Rescue NSW, policy agencies, health service providers and burns clinicians ensuring wide dissemination of results and translation of data to inform practice and identify areas for targeted prevention. Summary reports in formats designed for policy audiences in parallel with scientific papers will be produced.

The Australian Injury Comorbidity Indices (AICIs) to predict in-hospital complications: A population-based data linkage study

Background

Hospital-admitted patients are at risk of experiencing certain adverse outcomes during their hospital-stay. Patients may need to be admitted to the intensive care unit or be placed on the ventilator while there is also a possibility for complications to develop. Pre-existing comorbidity could increase the risk of these outcomes. The Charlson Comorbidity Index (CCI) and the Elixhauser Comorbidity Measure (ECM), originally derived for mortality outcomes among general medical populations, are widely used for assessing these in-hospital complications even among specific injury populations. This study derived indices to specifically capture the effect of comorbidity on intensive care unit and ventilator use as well as hospital-acquired complications for injury patients.

Methods

Retrospective data on injury hospital-admissions from July 2012 to June 2014 (161,334 patients) for the state of Victoria, Australia was analysed. Results from multivariable regression analysis were used to derive the Australian Injury Comorbidity Indices (AICIs) for intensive care unit and ventilator hours and hospital-acquired complications. The AICIs, CCI and ECM were validated on data from Victoria and two other Australian states.

Results

Five comorbidities were significantly associated with intensive care unit hours, two with ventilator hours and fifteen with hospital-acquired complications for hospitalised injury patients. Not all diseases listed in the CCI or ECM were found to be associated with these outcomes. The AICIs performed equally well in terms of predictive ability to the long-listed ECM and in most instances outperformed the CCI.

Conclusions

Associations between outcomes and comorbidities vary based on the type of outcome measure. The new comorbidity indices developed in this study provide a relevant, parsimonious and up-to-date method to capture the effect of comorbidity on in-hospital complications among admitted injury patients and is better suited for use in that context compared to the CCI and ECM.

Associations between comorbidity and quality of life outcomes after total joint replacement

PURPOSE

We examined associations between self-reported and clinician-assessed comorbidity and quality of life (QOL) outcomes after hip and knee replacement.

METHODS

This is a cross-sectional, questionnaire-based national survey. Participants aged 45 years or older (n = 409) were recruited from the New Zealand Joint Registry six months after a total hip (THR), total knee (TKR) or unicompartmental knee replacement (UKR). The main outcome QOL was measured using an 8-item short form of the World Health Organisation Quality of Life (WHOQOL-Bref) questionnaire six months following joint replacement surgery. The WHOQOL is a generic and non-health condition specific measure of QOL.

RESULTS

Participants were on average 68 years of age, with more men (54%) than women (46%). Number of coexisting conditions and body mass index were correlated with age, pain and function scores, and QOL (p < 0.01), but not with each other. Linear regression analyses showed that comorbidities such as number of comorbid conditions and BMI had moderate associations with QOL outcomes.

CONCLUSION

This study showed that general QOL outcomes following hip and knee joint replacement, while generally high, were associated with comorbidity burden and BMI. Future prospective research examining change in QOL before and following surgery would help to advance understandings of the various factors that contribute to patient satisfaction with their joint replacement.

Excess Mortality Among Adults Hospitalized With Traumatic Brain Injury in Australia: A Population-Based Matched Cohort Study

OBJECTIVE

To quantify and describe excess mortality attributable to traumatic brain injury (TBI) during the 12 months after hospitalization.

DESIGN

Population-based matched cohort study using linked hospital and mortality data.

SETTING

Australia.

PARTICIPANTS

Individuals 18 years and older who were hospitalized with a principal diagnosis of TBI in 2009 (n = 6929) and matched noninjured individuals randomly selected from the electoral roll (n = 6929).

MAIN MEASURES

Survival distributions were compared using a Kaplan-Meier plot with a log-rank test. Mortality rate ratios (MRRs) were computed using Cox proportional hazard regression with and without controlling for demographic characteristics and preexisting health status.

RESULTS

Individuals with TBI experienced significantly worse survival during the 12 months after hospitalization (χ = 640.9, df = 1, P < .001), and were more than 7.5 times more likely to die compared with their noninjured counterparts (adjusted MRR, 7.76; 95% confidence interval, 6.07-9.93). TBI was likely to be a contributory factor in 87% of deaths in the TBI cohort. Excess mortality was higher among males, younger age groups, and those with more severe TBI.

CONCLUSION

Excess mortality is high among individuals hospitalized with TBI and most deaths are attributable to the TBI. Increased primary and secondary preventive efforts are warranted to reduce the mortality burden of TBI.

Initiation of adjuvant chemotherapy and trastuzumab for human epidermal growth receptor 2-positive early invasive breast cancer in a population-based cohort study of older women in England

BACKGROUND

Clinical guidance on recommended treatment for older patients with breast cancer is often ambiguous, particularly in the context of comorbidities and poor functional status. Older patients, aged 70 years and over, account for a substantial proportion of women with breast cancer yet are underrepresented in randomized controlled trials. This paper investigates the initiation of adjuvant chemotherapy and trastuzumab in older patients in routine care.

MATERIALS AND METHODS

Women, aged 50 years and over, newly diagnosed with human epidermal growth receptor 2 (HER2)-positive early invasive breast cancer from January 2014 to December 2017 were identified from the England Cancer Registry. Chemotherapy and trastuzumab use was obtained from the Systemic Anti-Cancer Therapy (SACT) dataset. Patient and tumor characteristics influential in treatment decision-making were included in multilevel mixed-effects logistic regression models.

RESULTS

10% of women had HER2-positive tumors. Initiation of adjuvant chemotherapy and trastuzumab decreased with age from ≥70% among women aged 50-64 years to <15% among women aged 80+ years. Initiation varied additionally by tumor characteristics and number of comorbidities. Age remained a factor in treatment decisions despite favorable other factors, with lower use among women aged 70+ years. There was also marked variation across geographical regions.

CONCLUSIONS

In women with operable HER2-positive early invasive breast cancer, adjuvant chemotherapy plus trastuzumab was started less frequently as age increased, regardless of tumor characteristics or comorbidity burden. There was substantial variation in the proportion of women who started these treatments across the country.

Measuring stroke outcomes for 74 501 patients using linked administrative data: System-wide estimates and validation of 'home-time' as a surrogate measure of functional status

AIMS

Administrative data offer cost-effective, whole-of-population stroke surveillance yet the lack of validated measures of functional status is a shortcoming. The number of days spent living at home after stroke ('home-time') is a patient-centred outcome that can be objectively ascertained from administrative data. Population-based validation against both severity and outcome measures and for all subtypes is lacking. We aimed to report representative 'home-time' estimates and validate 'home-time' as a surrogate measure of functional status after stroke.

METHODS

Stroke hospitalisations from a state-wide census in New South Wales, Australia, from January 1, 2005 to March 31, 2014 were linked to prehospital data, poststroke admissions and deaths. We correlated 90-day 'home-time' with Glasgow Coma Scale (GCS) scores, measured upon a patient's initial contact with paramedics and Functional Independence Measure (FIM) scores, measured upon entry to rehabilitation after the acute hospital stroke admission. Negative binomial regressions identified predictors of 'home-time'.

RESULTS

Patients with stroke (N = 74 501) spent a median of 53 days living at home 90 days after the event. Median 'home-time' was 60 days after ischaemic stroke, 49 days after subarachnoid haemorrhage and 0 days after intracerebral haemorrhage. GCS and FIM scores significantly correlated with 'home-time' (P < .001). Women spent significantly less time at home compared with men after stroke, although being married increased 'home-time' after ischaemic stroke and subarachnoid haemorrhage.

CONCLUSIONS

These findings underscore the immediate and adverse impact of stroke. 'Home-time' measured using administrative data is a robust, replicable and valid patient-centred outcome enabling inexpensive population-based surveillance and system-wide quality assessment.

Frequent general practitioner visits are protective against statin discontinuation after a Pharmaceutical Benefits Scheme copayment increase

Objective This study assessed the effect of the frequency of general practitioner (GP) visitation in the 12 months before a 21% consumer copayment increase in the Pharmaceutical Benefits Scheme (PBS; January 2005) on the reduction or discontinuation of statin dispensing for tertiary prevention. Methods The study used routinely collected, whole-population linked PBS, Medicare, mortality and hospital data from Western Australia. From 2004 to 2005, individuals were classified as having discontinued, reduced or continued their use of statins in the first six months of 2005 following the 21% consumer copayment increase on 1 January 2005. The frequency of GP visits was calculated in 2004 from Medicare data. Multivariate logistic regression models were used to determine the association between GP visits and statin use following the copayment increase. Results In December 2004, there were 22495 stable statin users for tertiary prevention of prior coronary heart disease, prior stroke or prior coronary artery revascularisation procedure. Following the copayment increase, patients either discontinued (3%), reduced (12%) or continued (85%) their statins. Individuals who visited a GP three or more times in 2004 were 47% less likely to discontinue their statins in 2005 than people attending only once. Subgroup analysis showed the effect was apparent in men, and long-term or new statin users. The frequency of GP visits did not affect the proportion of patients reducing their statin therapy. Conclusions Patients who visited their GP at least three times per year had a lower risk of ceasing their statins in the year following the copayment increase. GPs can help patients maintain treatment following rises in medicines costs. What is known about the topic? Following the 21% increase in medication copayment in 2005, individuals discontinued or reduced their statin usage, including for tertiary prevention. What does this paper add? Patients who visited their GP at least three times per year were less likely to discontinue their statin therapy for tertiary prevention following a large copayment increase. What are the implications for practitioners? This paper identifies the important role that GPs have in maintaining the continued use of important medications following rises in medicines costs.

Prevalence of secondary care multimorbidity in mid-life and its association with premature mortality in a large longitudinal cohort study

OBJECTIVES

Multimorbidity is the coexistence of two or more health conditions in an individual. Multimorbidity in younger adults is increasingly recognised as an important challenge. We assessed the prevalence of secondary care multimorbidity in mid-life and its association with premature mortality over 15 years of follow-up, in the Aberdeen Children of the 1950s (ACONF) cohort.

METHOD

A prospective cohort study using linked electronic health and mortality records. Scottish ACONF participants were linked to their Scottish Morbidity Record hospital episode data and mortality records. Multimorbidity was defined as two or more conditions and was assessed using healthcare records in 2001 when the participants were aged between 45 and 51 years. The association between multimorbidity and mortality over 15 years of follow-up (to ages 60-66 years) was assessed using Cox proportional hazards regression. There was also adjustment for key covariates: age, gender, social class at birth, intelligence at age 7, secondary school type, educational attainment, alcohol, smoking, body mass index and adult social class.

RESULTS

Of 9625 participants (51% males), 3% had multimorbidity. The death rate per 1000 person-years was 28.4 (95% CI 23.2 to 34.8) in those with multimorbidity and 5.7 (95% CI 5.3 to 6.1) in those without. In relation to the reference group of those with no multimorbidity, those with multimorbidity had a mortality HR of 4.5 (95% CI 3.4 to 6.0) over 15 years and this association remained when fully adjusted for the covariates (HR 2.5 (95% CI 1.5 to 4.0)).

CONCLUSION

Multimorbidity prevalence was 3% in mid-life when measured using secondary care administrative data. Multimorbidity in mid-life was associated with premature mortality.

Construction of the secondary care administrative records frailty (SCARF) index and validation on older women with operable invasive breast cancer in England and Wales: a cohort study

OBJECTIVES

Studies that use national datasets to evaluate the management of older women with breast cancer are often constrained by a lack of information on patient fitness. This study constructed a frailty index for use with secondary care administrative records and evaluated its ability to improve models of treatment patterns and overall survival in women with breast cancer.

DESIGN

Retrospective cohort study.

PARTICIPANTS

Women aged ≥50 years with oestrogen receptor (ER) positive early invasive breast cancer diagnosed between 2014 and 2017 in England.

METHODS

The secondary care administrative records frailty (SCARF) index was based on the cumulative deficit model of frailty, using International Statistical Classification of Diseases, Injuries and Causes of Death, 10th revision codes to define a set of deficits. The index was applied to administrative records that were linked to national cancer registry datasets. The ability of the SCARF index to improve the performance of regression models to explain observed variation in the rate of surgery and overall survival was evaluated using Harrell's c-statistic and decision curve analysis. External validation was performed on a dataset of similar women diagnosed in Wales.

RESULTS

The SCARF index captured 32 deficits that cover functional impairment, geriatric syndromes, problems with nutrition, cognition and mood, and medical comorbidities. In the English dataset (n=67 925), the prevalence of frailty in women aged 50-69, 70-79 and ≥80 years was 15%, 28% and 47%, respectively. Adding a frailty measure to regression models containing age, tumour characteristics and comorbidity improved their ability to: (1) discriminate between whether a woman was likely to have surgery and (2) predict overall survival. Similar results were obtained when the models were applied to the Welsh cohort (n=4 230).

CONCLUSION

The SCARF index provides a simple and consistent method to identify frailty in population level data and could help describe differences in breast cancer treatments and outcomes.

Time protective effect of contact with a general practitioner and its association with diabetes-related hospitalisations: a cohort study using the 45 and Up Study data in Australia

OBJECTIVES

To evaluate the relationship between the proportion of time under the potentially protective effect of a general practitioner (GP) captured using the Cover Index and diabetes-related hospitalisation and length of stay (LOS).

DESIGN

An observational cohort study over two 3-year time periods (2009/2010-2011/2012 as the baseline and 2012/2013-2014/2015 as the follow-up).

SETTING

Linked self-report and administrative health service data at individual level from the 45 and Up Study in New South Wales, Australia.

PARTICIPANTS

A total of 21 965 individuals aged 45 years and older identified with diabetes before July 2009 were included in this study.

MAIN OUTCOME MEASURES

Diabetes-related hospitalisation, unplanned diabetes-related hospitalisation and LOS of diabetes-related hospitalisation and unplanned diabetes-related hospitalisation.

METHODS

The average annual GP cover index over a 3-year period was calculated using information obtained from Australian Medicare and hospitalisation. The effect of exposure to different levels of the cover on the main outcomes was estimated using negative binomial models weighted for inverse probability of treatment weight to control for observed covariate imbalance at the baseline period.

RESULTS

Perfect GP cover was observed among 53% of people with diabetes in the study cohort. Compared with perfect level of GP cover, having lower levels of GP cover including high (incidence rate ratio (IRR) 2.8, 95% CI 2.6 to 3.0), medium (IRR 3.2, 95% CI 2.7 to 3.8) and low (IRR 3.1, 95% CI 2.0 to 4.9) were significantly associated with higher number of diabetes-related hospitalisation. Similar association was observed between the different levels of GP cover and other outcomes including LOS for diabetes-related hospitalisation, unplanned diabetes-related hospitalisation and LOS for unplanned diabetes-related hospitalisation.

CONCLUSIONS

Measuring longitudinal continuity in terms of time under cover of GP care may offer opportunities to optimise the performance of primary healthcare and reduce secondary care costs in the management of diabetes.

Patient-reported symptom burden and supportive care needs at cancer diagnosis: a retrospective cohort study

PURPOSE

Patient-reported outcomes (PROs) are used to assess patients' symptoms and supportive care needs. While PROs are increasingly employed in clinical practice, research utilizing these data remains limited. Our goal was to evaluate PROs from a provincial cancer program.

METHODS

A retrospective, population-based cohort study using administrative health data of patients in Alberta, Canada, diagnosed with cancer between January 1, 2016, and October 23, 2017. Adults who completed PROs (Edmonton Symptom Assessment System, ESAS) and supportive care needs inventory (Canadian Problem Checklist)) within ± 60 days of diagnosis were included. Patients were stratified by tumor types (breast, colorectal, lung, prostate, hematological, or other). Descriptive statistics were used to characterize symptom burden and supportive care needs. Multivariate logistic regression was used to evaluate factors associated with higher symptom severity.

RESULTS

We included 1310 patients (mean age 64 years; 51% female), the majority of whom had breast (19%), lung (25%), or other cancers (26%). For the cohort, severity of symptoms based on ESAS was low, but prevalence of specific symptoms was high including tiredness (84%), anxiety (60%), pain (60%), and low well-being (80%). Seventy percent of the cohort reported at least one supportive care need. The highest-ranking problems were fears and worries and needing information about illness/treatment. There were differences across tumor types with respect to symptoms and supportive care needs. Comorbidity and having a high number of supportive care needs were associated with higher symptom severity.

DISCUSSION

Our results underscore the need to develop and implement tumor-specific supportive care interventions.

Administrative and Claims Data Help Predict Patient Mortality in Intensive Care Units by Logistic Regression: A Nationwide Database Study

Background

Increasing attention has been paid to the predictive power of different prognostic scoring systems for decades. In this study, we compared the abilities of three commonly used scoring systems to predict short-term and long-term mortalities, with the intention of building a better prediction model for critically ill patients. We used the data from the National Health Insurance Research Database (NHIRD) in Taiwan, which included information on patient age, comorbidities, and presence of organ failure to build a new prediction model for short-term and long-term mortalities.

Methods

We retrospectively collected the medical records of patients in the intensive care unit of a regional hospital in 2012 and linked them to the claims data from the NHIRD. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Elixhauser Comorbidity Index (ECI), and Charlson Comorbidity Index (CCI) were compared for their predictive abilities. Multiple logistic regression tests were performed, and the results were presented as receiver operating characteristic curves and C-statistic.

Results

The APACHE II score has the best predictive power for inhospital mortality (0.79; C − statistic = 0.77 − 0.83) and 1-year mortality (0.77; C − statistic = 0.74 − 0.79). The ECI and CCI alone have poorer predictive power and need to be combined with other variables to be comparable to the APACHE II score, as predictive tools. Using CCI together with age, sex, and whether or not the patient required mechanical ventilation is estimated to have a C-statistic of 0.773 (95% CI 0.744-0.803) for inhospital mortality, 0.782 (95% CI 0.76-0.81) for 30-day mortality, and 0.78 (95% CI 0.75-0.80) for 1-year mortality.

Conclusions

We present a new prognostic model that combines CCI with age, sex, and mechanical ventilation status and can predict mortality, comparable to the APACHE II score.