Variation in the recording of common health conditions in routine hospital data: study using linked survey and administrative data in New South Wales, Australia

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.

Mental illness comorbidity significantly impacts surgical outcomes for emergency surgical patients

BACKGROUND

Whilst both mental illness comorbidity and the delivery of emergency surgery are commonplace in Australia, there is little evidence investigating any link between them. As such, this study examines the emergency surgical outcomes for patients with mental illness compared to other surgical patients within the Australian public surgical system.

METHODS

Retrospective cohort study involving adult emergency and elective surgical patients treated at three public hospitals in Sydney, Australia between 2018 and 2019. Patients were identified using ICD-10 diagnosis codes, and grouped by those with decompensated mental illness, chronic depression, or those without mental illness. Outcome measures included those within the emergency department (ED), along with in-hospital mortality and surgical outcomes.

RESULTS

Of 48 338 total patients, 31 890 (66.0%) had elective and 16 448 (34.0%) had emergency surgery. For patients with decompensated mental illness, only 228 (0.7%) had elective whilst 425 (2.6%) had emergency surgery. Their outcomes for this surgery type included being triaged significantly higher (Cat 1 or 2, 34% vs. 15%) and longer ED stays (8.3 vs. 6.6 h). They also had significantly more post-operative complications (26% vs. 8%) and total days in hospital (33.8 vs. 8.5 days). There was no significant difference for in-hospital mortality.

CONCLUSION

Patients with mental illness are significantly more likely to have emergency surgery including presenting to the ED with more acute physical illness and to experience worse surgical outcomes compared to other surgical patients for every measure analyzed except mortality. There is considerable opportunity to further investigate how these differences might be improved.

Incidence and Predictors of Readmissions to Non-Index Hospitals After Transcatheter Aortic Valve Implantation in the Contemporary Era in New South Wales, Australia

BACKGROUND

In Australia, transcatheter aortic valve implantation (TAVI) is only performed in a limited number of specialised metropolitan centres, many of which are private hospitals, making it likely that TAVI patients who require readmission will present to another (non-index) hospital. It is important to understand the impact of non-index readmission on patient outcomes and healthcare resource utilisation.

METHOD

We analysed linked hospital and death records for residents of New South Wales, Australia, aged ≥18 years, who had an emergency readmission within 90 days following a TAVI procedure in 2013-2022. Mixed-effect, multi-level logistic regression models were used to evaluate predictors of non-index readmission, and associations between non-index readmission and readmission length of stay, 90-day mortality, and 1-year mortality.

RESULTS

Of 4,198 patients (mean age, 82.7 years; 40.6% female) discharged alive following TAVI, 933 (22.2%) were readmitted within 90 days of discharge. Over three-quarters (76.0%) of those readmitted returned to a non-index hospital, with no significant difference in readmission principal diagnosis between index hospital and non-index hospital readmissions. Among readmitted patients, independent predictors of non-index readmission included: residence in regional or remote areas, lower socio-economic status, having a pre-procedure transfer, and a private index hospital. Readmission length of stay (median, 4 days), 90-day mortality (adjusted odds ratio [OR] 1.04, 95% confidence interval [CI] 0.56-1.96) and 1-year mortality (adjusted OR 1.01, 95% CI 0.64-1.58) were similar between index and non-index readmissions.

CONCLUSIONS

Non-index readmission following TAVI was highly prevalent but not associated with increased mortality or healthcare utilisation. Our results are reassuring for TAVI patients in regional and remote areas with limited access to return to index TAVI hospitals.

The validity of electronic health data for measuring smoking status: a systematic review and meta-analysis

BACKGROUND

Smoking is a risk factor for many chronic diseases. Multiple smoking status ascertainment algorithms have been developed for population-based electronic health databases such as administrative databases and electronic medical records (EMRs). Evidence syntheses of algorithm validation studies have often focused on chronic diseases rather than risk factors. We conducted a systematic review and meta-analysis of smoking status ascertainment algorithms to describe the characteristics and validity of these algorithms.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. We searched articles published from 1990 to 2022 in EMBASE, MEDLINE, Scopus, and Web of Science with key terms such as validity, administrative data, electronic health records, smoking, and tobacco use. The extracted information, including article characteristics, algorithm characteristics, and validity measures, was descriptively analyzed. Sources of heterogeneity in validity measures were estimated using a meta-regression model. Risk of bias (ROB) in the reviewed articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.

RESULTS

The initial search yielded 2086 articles; 57 were selected for review and 116 algorithms were identified. Almost three-quarters (71.6%) of algorithms were based on EMR data. The algorithms were primarily constructed using diagnosis codes for smoking-related conditions, although prescription medication codes for smoking treatments were also adopted. About half of the algorithms were developed using machine-learning models. The pooled estimates of positive predictive value, sensitivity, and specificity were 0.843, 0.672, and 0.918 respectively. Algorithm sensitivity and specificity were highly variable and ranged from 3 to 100% and 36 to 100%, respectively. Model-based algorithms had significantly greater sensitivity (p = 0.006) than rule-based algorithms. Algorithms for EMR data had higher sensitivity than algorithms for administrative data (p = 0.001). The ROB was low in most of the articles (76.3%) that underwent the assessment.

CONCLUSIONS

Multiple algorithms using different data sources and methods have been proposed to ascertain smoking status in electronic health data. Many algorithms had low sensitivity and positive predictive value, but the data source influenced their validity. Algorithms based on machine-learning models for multiple linked data sources have improved validity.

Readmission to a non-index hospital following total joint replacement

Aims

It is unclear whether mortality outcomes differ for patients undergoing total hip arthroplasty (THA) or total knee arthroplasty (TKA) surgery who are readmitted to the index hospital where their surgery was performed, or to another hospital.

Methods

We analyzed linked hospital and death records for residents of New South Wales, Australia, aged ≥ 18 years who had an emergency readmission within 90 days following THA or TKA surgery between 2003 and 2022. Multivariable modelling was used to identify factors associated with non-index readmission and to evaluate associations of readmission destination (non-index vs index) with 90-day and one-year mortality.

Results

Of 394,248 joint arthroplasty patients (THA = 149,456; TKA = 244,792), 9.5% (n = 37,431) were readmitted within 90 days, and 53.7% of these were admitted to a non-index hospital. Non-index readmission was more prevalent among patients who underwent surgery in private hospitals (60%). Patients who were readmitted for non-orthopaedic conditions (62.8%), were more likely to return to a non-index hospital compared to those readmitted for orthopaedic complications (39.5%). Factors associated with non-index readmission included older age, higher socioeconomic status, private health insurance, and residence in a rural or remote area. Non-index readmission was significantly associated with 90-day (adjusted odds ratio (aOR) 1.69; 95% confidence interval (CI) 1.39 to 2.05) and one-year mortality (aOR 1.31; 95% CI 1.16 to 1.47). Associations between non-index readmission and mortality were similar for patients readmitted with orthopaedic and non-orthopaedic complications (90-day mortality aOR 1.61; 95% CI 0.98 to 2.64, and aOR 1.67; 95% CI 1.35 to 2.06, respectively).

Conclusion

Non-index readmission was associated with increased mortality, irrespective of whether the readmission was for orthopaedic complications or other conditions.

Reducing rate of total colectomies for ulcerative colitis but higher morbidity in the biologic era: an 18-year linked data study from New South Wales Australia

BACKGROUND

This study aims to investigate the trends in UC surgery in New South Wales (NSW) at a population level.

METHODS

A retrospective data linkage study of the NSW population was performed. Patients of any age with a diagnosis of UC who underwent a total abdominal colectomy (TAC) ± proctectomy between Jul-2001 and Jun-2019 were included. The age adjusted population rate was calculated using Australian Bureau of Statistics data. Multivariable linear regression modelled the trend of TAC rates, and assessed the effect of infliximab (listed on the Pharmaceutical Benefits Scheme for UC in Apr-2014).

RESULTS

A total of 1365 patients underwent a TAC ± proctectomy (mean age 47.0 years (±18.6), 59% Male). Controlling for differences between age groups, the annual rate of UC TACs decreased by 2.4% each year (95% CI 1.4%-3.4%) over the 18-year period from 1.30/100000 (2002) to 0.84/100000 (2019). An additional incremental decrease in the rate of TACs was observed after 2014 (OR 0.83, 95% CI 0.69-1.00). There was no change in the proportion of TACs performed emergently over the study period (OR 1.02, 95% CI 0.998-1.04). The odds of experiencing any perioperative surgical complication (aOR 1.54, 95% CI 1.01-2.33, P = 0.043), and requiring ICU admission (aOR 1.85, 95% CI 1.24-2.76, P = 0.003) significantly increased in 2014-2019 compared to 2002-2007.

CONCLUSIONS

The rate of TACs for UC has declined over the past two decades. This rate decrease may have been further influenced by the introduction of biologics. Higher rates of complications and ICU admissions in the biologic era may indicate poorer patient physiological status at the time of surgery.

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.

A spatiotemporal analysis of the association between carbon productivity, socioeconomics, medical resources and cardiovascular diseases in southeast rural China

Introduction

With China's rapid industrialization and urbanization, China has been increasing its carbon productivity annually. Understanding the association between carbon productivity, socioeconomics, and medical resources with cardiovascular diseases (CVDs) may help reduce CVDs burden. However, relevant studies are limited.

Objectives

The study aimed to describe the temporal and spatial distribution pattern of CVDs hospitalization in southeast rural China and to explore its influencing factors.

Methods

In this study, 1,925,129 hospitalization records of rural residents in southeast China with CVDs were analyzed from the New Rural Cooperative Medical Scheme (NRCMS). The spatial distribution patterns were explored using Global Moran's I and Local Indicators of Spatial Association (LISA). The relationships with influencing factors were detected using both a geographically and temporally weighted regression model (GTWR) and multiscale geographically weighted regression (MGWR).

Results

In southeast China, rural inpatients with CVDs increased by 95.29% from 2010 to 2016. The main groups affected were elderly and women, with essential hypertension (26.06%), cerebral infarction (17.97%), and chronic ischemic heart disease (13.81%) being the leading CVD subtypes. The results of LISA shows that central and midwestern counties, including Meilie, Sanyuan, Mingxi, Jiangle, and Shaxian, showed a high-high cluster pattern of CVDs hospitalization rates. Negative associations were observed between CVDs hospitalization rates and carbon productivity, and positive associations with per capita GDP and hospital beds in most counties (p < 0.05). The association between CVDs hospitalization rates and carbon productivity and per capita GDP was stronger in central and midwestern counties, while the relationship with hospital bed resources was stronger in northern counties.

Conclusion

Rural hospitalizations for CVDs have increased dramatically, with spatial heterogeneity observed in hospitalization rates. Negative associations were found with carbon productivity, and positive associations with socioeconomic status and medical resources. Based on our findings, we recommend low-carbon development, use of carbon productivity as an environmental health metric, and rational allocation of medical resources in rural China.

Artificial Intelligence as a Diagnostic Tool in Non-Invasive Imaging in the Assessment of Coronary Artery Disease

Coronary artery disease (CAD) remains a leading cause of mortality and morbidity worldwide, and it is associated with considerable economic burden. In an ageing, multimorbid population, it has become increasingly important to develop reliable, consistent, low-risk, non-invasive means of diagnosing CAD. The evolution of multiple cardiac modalities in this field has addressed this dilemma to a large extent, not only in providing information regarding anatomical disease, as is the case with coronary computed tomography angiography (CCTA), but also in contributing critical details about functional assessment, for instance, using stress cardiac magnetic resonance (S-CMR). The field of artificial intelligence (AI) is developing at an astounding pace, especially in healthcare. In healthcare, key milestones have been achieved using AI and machine learning (ML) in various clinical settings, from smartwatches detecting arrhythmias to retinal image analysis and skin cancer prediction. In recent times, we have seen an emerging interest in developing AI-based technology in the field of cardiovascular imaging, as it is felt that ML methods have potential to overcome some limitations of current risk models by applying computer algorithms to large databases with multidimensional variables, thus enabling the inclusion of complex relationships to predict outcomes. In this paper, we review the current literature on the various applications of AI in the assessment of CAD, with a focus on multimodality imaging, followed by a discussion on future perspectives and critical challenges that this field is likely to encounter as it continues to evolve in cardiology.

Uptake of prescription smoking cessation pharmacotherapies after hospitalization for major cardiovascular disease

AIMS

We determined the prevalence of prescription smoking cessation pharmacotherapy (SCP) use after hospitalization for major cardiovascular disease (MCD) among people who smoke and whether this varies by sex.

METHODS AND RESULTS

We conducted a population-based cohort study including all people hospitalized in New South Wales, Australia, between July 2013 and December 2018 (2017 for private hospitals) with an MCD diagnosis. For patients who also had a diagnosis of current tobacco use, we used linked pharmaceutical dispensing records to identify prescription SCP dispensings within 90 days post-discharge. We determined the proportion who were dispensed an SCP within 90 days, overall and by type of SCP. We used logistic regression to estimate the odds of females being dispensed an SCP relative to males. Of the 150 758 patients hospitalized for an MCD, 20 162 (13.4%) had a current tobacco use diagnosis, 31% of whom were female. Of these, 11.3% (12.4% of females, 10.9% of males) received prescription SCP within 90 days post-discharge; 3.0% were dispensed varenicline, and 8.3% were dispensed nicotine replacement therapy patches. Females were more likely than males to be dispensed a prescription SCP [odds ratio (OR) 1.16, 95% confidence interval (CI) 1.06-1.27)]; however, this was not maintained after adjusting for potential confounders (adjusted OR 1.04, 95% CI 0.94-1.15).

CONCLUSION

Very few females and males who smoke use prescription SCPs after hospitalization for an MCD. The use of varenicline, the SCP with the highest efficacy, was particularly low. This represents a missed opportunity to increase smoking cessation in this high-risk population, thereby reducing their risk of recurrent cardiovascular events.

Patient-reported experiences and outcomes following hospital care are associated with risk of readmission among adults with chronic health conditions

This study quantifies the association between patient reported measures (PRMs) and readmission to inform efforts to improve hospital care. A retrospective, cross-sectional study was conducted with adults who had chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF) and were admitted for acute care in a public hospital in New South Wales, Australia for any reason (n = 2394 COPD and 2476 CHF patients in 2018-2020). Patient- level survey data were linked with inpatient data for one year prior to risk-adjust outcomes and after discharge to detect all cause unplanned readmission to a public or private hospital. Ninety-day readmission rates for respondents with COPD or CHF were 17% and 19%. Crude rates for adults with COPD were highest among those who reported that hospital care and treatment helped "not at all" (28%), compared to those who responded, "to some extent" (20%) or "definitely" (15%). After accounting for patient characteristics, adults with COPD or CHF who said care and treatment didn't help at all were at twice the risk of readmission compared to those who responded that care and treatment helped "definitely" (Hazard ratio for COPD 1.97, CI: 1.17-3.32; CHF 2.07, CI 1.25-3.42). Patients who offered the most unfavourable ratings of overall care, understandable explanations, organised care, or preparedness for discharge were at a 1.5 to more than two times higher risk of readmission. Respect and dignity, effective and clear communications, and timely and coordinated care also matter. PRMs are strong predictors of readmission even after accounting for risk related to age and co-morbidities. More moderate ratings were associated with attenuation of risk, and the most positive ratings were associated with the lowest readmission rate. These results suggest that increasing each patient's positive experiences progressively reduces the risk of adults with chronic conditions returning to acute care.

Estimating incidence rates of periprosthetic joint infection after hip and knee arthroplasty for osteoarthritis using linked registry and administrative health data

AIMS

The aim of this study was to estimate the 90-day periprosthetic joint infection (PJI) rates following total knee arthroplasty (TKA) and total hip arthroplasty (THA) for osteoarthritis (OA).

METHODS

This was a data linkage study using the New South Wales (NSW) Admitted Patient Data Collection (APDC) and the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR), which collect data from all public and private hospitals in NSW, Australia. Patients who underwent a TKA or THA for OA between 1 January 2002 and 31 December 2017 were included. The main outcome measures were 90-day incidence rates of hospital readmission for: revision arthroplasty for PJI as recorded in the AOANJRR; conservative definition of PJI, defined by T84.5, the PJI diagnosis code in the APDC; and extended definition of PJI, defined by the presence of either T84.5, or combinations of diagnosis and procedure code groups derived from recursive binary partitioning in the APDC.

RESULTS

The mean 90-day revision rate for infection was 0.1% (0.1% to 0.2%) for TKA and 0.3% (0.1% to 0.5%) for THA. The mean 90-day PJI rates defined by T84.5 were 1.3% (1.1% to 1.7%) for TKA and 1.1% (0.8% to 1.3%) for THA. The mean 90-day PJI rates using the extended definition were 1.9% (1.5% to 2.2%) and 1.5% (1.3% to 1.7%) following TKA and THA, respectively.

CONCLUSION

When reporting the revision arthroplasty for infection, the AOANJRR substantially underestimates the rate of PJI at 90 days. Using combinations of infection codes and PJI-related surgical procedure codes in linked hospital administrative databases could be an alternative way to monitor PJI rates.Cite this article: Bone Joint J 2022;104-B(9):1060-1066.

The Hospital Frailty Risk Score Identifies Fewer Cases of Frailty in a Community-Based Cohort of Older Men Than the FRAIL Scale and Frailty Index

OBJECTIVES

The recently developed Hospital Frailty Risk Score (HFRS) allows ascertainment of frailty from administrative data. We aimed to compare the HFRS against the widely used FRAIL Scale and Frailty Index.

DESIGN

Population-based cohort study linked to Western Australian Hospital Morbidity Data Collection and Death Registrations.

SETTING AND PARTICIPANTS

The Health in Men Study with frailty determined at Wave 2 (2001/2004), mortality in the 1-year period following Wave 2, and disability at Wave 3 (2008). Participants were 4228 community-based men aged ≥75 years, followed until Wave 3.

MEASUREMENTS

We used multivariable regression to determine the association between each frailty measure and outcomes of length of stay (LOS), death, and disability. We also determined if the additional cases of frailty identified by one measure over the other was associated with these outcomes.

RESULTS

Of 4228 men studied, the HFRS (n = 689) identified fewer men as frail than the FRAIL Scale (n = 1648) and Frailty Index (n = 1820). In the fully adjusted models, all 3 frailty measures were associated with longer LOS and mortality, whereas only the FRAIL Scale and Frailty Index were significantly associated with disability. The additional cases of frailty identified by the FRAIL Scale and Frailty Index had longer LOS and greater risks of death and disability. The fully adjusted hazard ratio for death among the additional cases of frailty identified by the FRAIL Scale (compared to being not frail on both HFRS and FRAIL Scale) was 2.14 (95% CI 1.48-3.08).

CONCLUSIONS AND IMPLICATIONS

The HFRS is associated with adverse outcomes. However, it identified approximately 60% fewer men who were frail than the FRAIL Scale and Frailty Index, and the additional cases identified were also at high risks of adverse outcomes. Users of the HFRS should be aware of the differences with other frailty measures.

Factors associated with long intensive care unit (ICU) admission among inpatients with and without diabetes in South Western Sydney public hospitals using the New South Wales admission patient data collection (2014-2017)

BACKGROUND

Long stay in intensive care unit (ICU) is associated with poor outcomes, particularly in people with diabetes. It increases the financial burden of care and this is a challenge to the South Western Sydney region, which is already a hotspot for diabetes in Australia. This study compared ICU admission characteristics of people with and without diabetes and the factors associated with long ICU stay among patients admitted to public hospitals in this metropolitan health district from 2014 to 2017.

METHODS

Cross-sectional datasets on 187,660, including all ICU admissions in the New South Wales Admitted Patient Data Collection (APDC) from June 2014 - July 2017 in public hospital were extracted. Data on demographic and health insurance status, primary admission diagnosis using ICD-10, comorbidities including death among hospital inpatients aged ≥18 years residing in SWS were analysed. The ICU length of stay was the outcome variable and were classified into short stay (≤48 h) and long stay (> 48 h), and were examined against potential confounding factors using bivariate and multiple logistic regression analyses.

RESULTS

Our results showed higher ICU admissions in patients with diabetes than in those without diabetes (5% vs. 3.3%, P < 0.001) over three years. The median and interquartile range (IQR) of length of the ICU stay were similar in both groups [diabetes: 40 h, IQR = 16-88 h vs. non-diabetes: 43 h, IQR = 19-79 h]. The prevalence of long ICU stays among people with and without diabetes were 44.9% [95% CI 42.1, 47.7%] and 43.6% [95% CI 42.2, 44.9%], respectively. For both groups, increased odds of long ICU stay were associated with death and circulatory system disease admissions, while musculoskeletal disease admissions were associated with lower risk of long ICU stay. In the non-diabetes group, male sex, nervous system disease admissions and living in peri-urban areas were associated with higher odds of long ICU stay.

CONCLUSIONS

The rate of ICU admissions among inpatients remain higher in people with diabetes. One in every two admissions to ICU had a long stay. Additional care for those admitted with circulatory system diseases are needed to reduce long ICU stay related deaths in SWS.

Analysis of in-hospital mortality among people with and without diabetes in South Western Sydney public hospitals (2014-2017)

BACKGROUND

Diabetes is a major public health problem affecting about 1.4 million Australians, especially in South Western Sydney, a hotspot of diabetes with higher than average rates for hospitalisations. The current understanding of the international burden of diabetes and related complications is poor and data on hospital outcomes and/or what common factors influence mortality rate in people with and without diabetes in Australia using a representative sample is lacking. This study determined in-hospital mortality rate and the factors associated among people with and without diabetes.

METHODS

Retrospective data for 554,421 adult inpatients was extracted from the population-based New South Wales (NSW) Admitted Patient Data over 3 financial years (from 1 July 2014-30 June 2015 to 1 July 2016-30 June 2017). The in-hospital mortality per 1000 admitted persons, standardised mortality ratios (SMR) were calculated. Binary logistic regression was performed, adjusting for potential covariates and co-morbidities for people with and without diabetes over three years.

RESULTS

Over three years, 8.7% (48,038 people) of admissions involved people with diabetes. This increased from 8.4% in 2014-15 to 8.9% in 2016-17 (p = 0.007). Across all age groups, in-hospital mortality rate was significantly greater in people with diabetes (20.6, 95% Confidence intervals CI 19.3-21.9 per 1000 persons) than those without diabetes (11.8, 95%CI 11.5-12.1) and more in men than women (23.1, 95%CI 21.2-25.0 vs 17.9, 95%CI 16.2-19.8) with diabetes. The SMR for those with and without diabetes were 3.13 (95%CI 1.78-4.48) and 1.79 (95%CI 0.77-2.82), respectively. There were similarities in the factors associated with in hospital mortality in both groups including: older age (> 54 years), male sex, marital status (divorced/widowed), length of stay in hospital (staying longer than 4 days), receiving intensive care in admission and being admitted due to primary respiratory and cardiovascular diagnoses. The odds of death in admission was increased in polymorbid patients without diabetes (28.68, 95%CI 23.49-35.02) but not in those with diabetes.

CONCLUSIONS

In-patients with diabetes continue to have higher mortality rates than those without diabetes and the Australian population. Overall, similar factors influenced mortality rate in people with and without diabetes, but significantly more people with diabetes had two or more co-morbidities, suggesting that hospital mortality may be driven by those with pre-existing health/comorbidities. Urgent measures in primary care to prevent admissions among people with multiple co-morbidities are needed.

Reliability of patient-reported comorbidities: a systematic review and meta-analysis

Self-reported questionnaires have become a widely adopted method of reviewing patients in clinical practice. This systematic review aimed to determine the reliability of patient-reported comorbidities and to identify which patient factors influence the reliability. Included studies assessed the reliability of at least one patient-reported comorbidity against their medical record or clinical assessment as gold standard. Twenty-four eligible studies were included in the meta-analysis. Only endocrine diseases (Cohen's Kappa Coefficient (CKC) 0.81 (95% CI 0.76 to 0.85)), consisting of diabetes mellitus (CKC 0.83 (95% CI 0.80 to 0.86)) and thyroid disease (CKC 0.68 (95% CI 0.50 to 0.86)), showed good-to-excellent reliability. Factors most frequently reported to influence concordance included age, sex and educational level.This systematic review demonstrated poor-to-moderate reliability for most systems, except for endocrine which showed good-to-excellent reliability. Although patient self-reporting can be a useful guide to clinical management, several patient factors were demonstrated to affect reliability therefore it should be avoided as a standalone measure.

Does a Prescription-based Comorbidity Index Correlate with the American Society of Anesthesiologists Physical Status Score and Mortality After Joint Arthroplasty? A Registry Study

BACKGROUND

When analyzing the outcomes of joint arthroplasty, an important factor to consider is patient comorbidities. The presence of multiple comorbidities has been associated with longer hospital stays, more postoperative complications, and increased mortality. The American Society of Anesthesiologists (ASA) physical status classification system score is a measure of a patient's overall health and has been shown to be associated with complications and mortality after joint arthroplasty. The Rx-Risk score is another measure for determining the number of different health conditions for which an individual is treated, with a possible score ranging from 0 to 47.

QUESTIONS/PURPOSES

For patients undergoing THA or TKA, we asked: (1) Which metric, the Rx-Risk score or the ASA score, correlates more closely with 30- and 90-day mortality after TKA or THA? (2) Is the Rx-Risk score correlated with the ASA score?

METHODS

This was a retrospective analysis of the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) database linked to two other national databases, the National Death Index (NDI) database and the Pharmaceutical Benefits Scheme (PBS), a dispensing database. Linkage to the NDI provided outcome information on patient death, including the fact of and date of death. Linkage to the PBS was performed to obtain records of all medicines dispensed to patients undergoing a joint replacement procedure. Patients were included if they had undergone either a THA (119,076 patients, 131,336 procedures) or TKA (182,445 patients, 215,712 procedures) with a primary diagnosis of osteoarthritis, performed between 2013 and 2017. We excluded patients with missing ASA information (THA: 3% [3055 of 119,076]; TKA: 2% [4095 of 182,445]). This left 127,761 primary THA procedures performed in 116,021 patients (53% [68,037 of 127,761] were women, mean age 68 ± 11 years) and 210,501 TKA procedures performed in 178,350 patients (56% [117,337 of 210,501] were women, mean age 68 ± 9 years) included in this study. Logistic regression models were used to determine the concordance of the ASA and Rx-Risk scores and 30-day and 90-day postoperative mortality. The Spearman correlation coefficient (r) was used to estimate the correlation between the ASA score and Rx-Risk score. All analyses were performed separately for THAs and TKAs.

RESULTS

We found both the ASA and Rx-Risk scores had high concordance with 30-day mortality after THA (ASA: c-statistic 0.83 [95% CI 0.79 to 0.86]; Rx-Risk: c-statistic 0.82 [95% CI 0.79 to 0.86]) and TKA (ASA: c-statistic 0.73 [95% CI 0.69 to 0.78]; Rx-Risk: c-statistic 0.74 [95% CI 0.70 to 0.79]). Although both scores were strongly associated with death, their correlation was moderate for patients undergoing THA (r = 0.45) and weak for TKA (r = 0.38). However, the median Rx-Risk score did increase with increasing ASA score. For example, for THAs, the median Rx-Risk score was 1, 3, 5, and 7 for ASA scores 1, 2, 3, and 4, respectively. For TKAs, the median Rx-Risk score was 2, 4, 5, and 7 for ASA scores 1, 2, 3, and 4, respectively.

CONCLUSION

The ASA physical status and RxRisk were associated with 30-day and 90-day mortality; however, the scores were only weakly to moderately correlated with each other. This suggests that although both scores capture a similar level of patient illness, each score may be capturing different aspects of health. The Rx-Risk may be used as a complementary measure to the ASA score.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Increased chronic disease prevalence among the younger generation: Findings from a population-based data linkage study to inform chronic disease ascertainment among reproductive-aged Australian women

BACKGROUND

Chronic disease represents an ongoing public health challenge in Australia with women disproportionately affected and at younger ages compared to men. Accurate prevalence and ascertainment of chronic disease among women of reproductive age at the population level is essential for meeting the family planning and reproductive health challenges that chronic diseases pose. This study estimated the prevalence of chronic disease among younger Australian women of reproductive age, in order to ascertain key conditions that would benefit from targeted family planning support strategies.

METHODS AND FINDINGS

Population-level survey data from the 1973-78 and 1989-95 cohorts of the Australian Longitudinal Study on Women's Health were linked to health service use, pharmaceutical, cancer and cause of death data to ascertain the prevalence and chronic disease trends for ten chronic health conditions associated with poor maternal and foetal outcomes. Individual chronic disease algorithms were developed for each chronic disease of interest using the available linked datasets. Lifetime prevalence of chronic disease varied substantially based on each individual data source for each of the conditions of interest. When all data sources were considered, all conditions with the exception of mental health conditions were higher among women in the 1973-78 cohort. However, when focused on point prevalence at similar ages (approximately 25-30 years), the chronic disease trend for women in the 1989-95 cohort was substantially higher, particularly for mental health conditions (70.4% vs 23.6%), diabetes (4.5% vs 1.3%) and multimorbidity (17.9% vs 9.1%).

CONCLUSIONS

Given the low concordance between individual data sources, the use of multiple data sources are recommended for chronic disease research focused on women of reproductive age. In order to reduce the increasing chronic disease and multimorbidity trend among women, strategic chronic disease interventions are required to be implemented in childhood and adolescence to ensure the long-term health of not only current but also future generations.

Interdisciplinary community-based participatory health research across the industrial region of the Étang de Berre : The EPSEAL Fos Crau study

BACKGROUND

We conducted a community-based participatory environmental health study in three towns: two in the heart of Marseille's industrial zone (Fos-sur-Mer and Port-Saint-Louis-du-Rhône), and one on the periphery located about 30 km away (Saint-Martin-de-Crau).

METHODS

We first conducted a cross-sectional survey of a random sample of residents in each of the three towns. We asked study participants to self-report a wide variety of health issues (Port-Saint-Louis: n = 272, Fos-sur-Mer: n = 543, Saint-Martin-de-Crau: n = 439). We then conducted focus groups with residents and other stakeholders to share preliminary data in order to propose areas of reflection and collaboratively produce contextually-situated knowledge of their health and environment. We directly standardized the prevalences (by age and gender) to the French metropolitan population to make our results more comparable.

RESULTS

Study participants who lived closer to the core industrial zone (residents of Fos-sur-Mer and Port-Saint-Louis-du-Rhone) had higher prevalences of eye irritation, nose and throat problems, chronic skin problems and headaches than people who lived further away (residents of Saint-Martin-de-Crau). Residents also offered diverse qualitative insights about their environment and health experiences.

DISCUSSION

We observed elevated prevalences of diseases that affected residents across the industrial zone (Fos-sur-Mer and Port-Saint-Louis-du-Rhône) compared to those living outside (Saint-Martin-de-Crau), and qualitative evidence of how residents made sense of their health experiences strengthening an understanding of their own empirical observations which helps to produce knowledge about health in an industrial context. The results of the workshops show an important benefit from the co-production of local knowledge.

CONCLUSION

We encourage future researchers to do in-depth, community-based research to comprehensively describe the health of residents in other heavily polluted zones, product local knowledge and to help identify policy solutions, engender trust among the local people, and identify opportunities for intervention.

Nutritional Care of Patients Admitted to Hospital for Alcohol Withdrawal: A 5-Year Retrospective Audit

AIM

The aim of this study was to describe the characteristics and the nutritional approaches implemented with patients undergoing alcohol withdrawal.

METHODS

A retrospective analysis of medical records for patients admitted to a tertiary hospital for alcohol withdrawal was completed over a 5-year period 2013-2017. Data on nutrition-related assessment and management were extracted and descriptively analysed.

RESULTS

A total of 109 medical records were included (M = 73, F = 36), with the mean age of patients 47.3 years (SD ± 11.2, range 22-70). The average length of stay was 3.7 days (SD ± 3.9, range 0.70-27.8). Approaches towards nutritional care emerged from micronutrient assessment and supplementation and/or dietetic consultation. Nutrition-related biochemistry data was available for most patients, notably serum levels of sodium, urea and creatinine (102 patients; 93.5%) and magnesium and phosphate (66 patients, 60.5%). There was evidence of some electrolyte abnormalities on admission to hospital. Eight patients had serum micronutrient status assessed; no patients had serum thiamine levels assessed. Parenteral thiamine was provided to 96 patients (88.0%) for 1.9 days (SD ± 1.1, range 1.0-6.0) with a mean dose of 2458.7 mg (SD ± 1347.6, range 300-6700 mg). Multivitamin supplementation was provided to 24 patients (22.0%). Only 23 patients (21.2%) were seen by a dietician of whom 16 underwent a comprehensive nutritional assessment and 3 were screened using the malnutrition screening tool.

CONCLUSION

Inconsistent nutritional assessment and management practices were identified across a diverse population group, whilst nutritional professionals were underutilized. Future research should benchmark current guidelines and multidisciplinary approaches considering the role of nutritional specialists in the team.

How does parent/self-reporting of common respiratory conditions compare with medical records among Aboriginal and Torres Strait Islander (Indigenous) children and young adults?

AIM

Self-reporting and/or data from medical records are frequently used in studies to ascertain health history. Data on the discrepancies between these information sources is lacking for Indigenous Australians. This study reports such data for selected respiratory and atopic conditions common among Indigenous Australians.

METHODS

Data were extracted from the Indigenous respiratory reference value study, a multicentre cross-sectional study of Indigenous children and young adults (3-25 years) between June 2015 and November 2017. Only those living in rural/remote regions were included. Self-reported history was collected from parents (if participants <18 years) or participants. Medical records were manually reviewed. Participants with incomplete data (missing self-reported and/or medical record information) were excluded. Agreement between sources was examined using Cohen's kappa.

RESULTS

Of 1097 participants, 889 (97.1% <18 years) had sufficient self-reported and medical record histories for comparison. Asthma was self-reported by 15.7% of participants and was reported in medical records for 10.3% (κ = 0.53, 95% confidence interval (CI) 0.45-0.61). For bronchiectasis, the reported rates were 1.5 and 0.7% (κ = 0.52, 95% CI 0.25-0.80), pneumonia 1.1 and 5.8% (κ = 0.15, 95% CI 0.02-0.27), allergic rhinitis 6.6 and 0.6% (κ = 0.05, 95% CI -0.03, 0.13) and eczema 5.8 and 6.2% (κ = 0.30, 95% CI 0.18-0.42).

CONCLUSIONS

Within our cohort, agreement was moderate for asthma and bronchiectasis, fair for eczema and poor for pneumonia and allergic rhinitis. These results highlight the challenges associated with how best to obtain an accurate health history within Australian Indigenous rural/remote communities. Generalisability of findings and contributions of poor health knowledge and/or poor medical record documentation need further exploration.

Multimorbidity among Aboriginal people in New South Wales contributes significantly to their higher mortality

OBJECTIVES

To compare the prevalence of multimorbidity and its impact on mortality among Aboriginal and non-Aboriginal Australians who had been hospitalised in New South Wales in the previous 10 years.

DESIGN, SETTING AND PARTICIPANTS

Cohort study analysis of linked NSW hospital (Admitted Patient Data Collection) and mortality data for 5 437 018 New South Wales residents with an admission to a NSW hospital between 1 March 2003 and 1 March 2013, and alive at 1 March 2013.

MAIN OUTCOME MEASURES

Admissions for 30 morbidities during the 10-year study period were identified. The primary outcome was the presence or absence of multimorbidity during the 10-year lookback period; the secondary outcome was mortality in the 12 months from 1 March 2013 to 1 March 2014.

RESULTS

31.5% of Aboriginal patients had at least one morbidity and 16.1% had two or more, compared with 25.0% and 12.1% of non-Aboriginal patients. After adjusting for age, sex, and socio-economic status, the prevalence of multimorbidity among Aboriginal people was 2.59 times that for non-Aboriginal people (95% CI, 2.55-2.62). The prevalence of multimorbidity was higher among Aboriginal people in all age groups, in younger age groups because of the higher prevalence of mental morbidities, and from age 60 because of physical morbidities. The age-, sex- and socio-economic status-adjusted hazard of one-year mortality (Aboriginal v non-Aboriginal Australians) was 2.43 (95% CI, 2.24-2.62), and 1.51 (95% CI, 1.39-1.63) after also adjusting for morbidity count.

CONCLUSIONS

The prevalence of multimorbidity was higher among Aboriginal than non-Aboriginal patients, and this difference accounted for much of the difference in mortality between the two groups. Evidence-based interventions for reducing multimorbidity among Aboriginal and Torres Strait Islander Australians must be a priority.

The role of medical data in efficient patient care delivery: a review

Background

Implementing accurate data management systems ensure safe and efficient transfer of confidential health care data. However, health care professionals overlooked their important tasks of medical data processing. Hence, using high-quality electronic health record (EHR) applications in health care is important to minimize medical errors. Therefore, this review tries to indicate the roles of EHR in advancing quality health care service provisions.

Methods

The keywords identified were EHR, EMR, medical data processing, medical data retention, medical data destruction, health care, and patient care, and a few related terms with different combinations. PubMed (National Library of Medicine), Google Scholar, and Google search engine were used to search for articles from those databases. Searching was done using boolean words “AND”, “OR”, and “NOT” using all [All fields] and [MeSH Terms] searching strategies.

Results

Articles were screened using the title, checked by their abstract, and the remaining related full-text materials were included or excluded by two individuals deciding its eligibility. Finally, 73 materials issued from 2013–2018 were used for qualitatively synthesizing and reconciling the idea to produce this review article.

Conclusion

Poor medical data processing systems are the key reasons for medical errors. Employing standardized data management systems reduce errors and associated sufferings. Therefore, using electronic tools in the health care institution ensures safe and efficient data management. Therefore, it is important to establish appropriate medical data management systems for efficient health care delivery.

Accuracy of inter-hospital transfer information in Australian hospital administrative databases

Inter-hospital transfers improve care delivery for which sending and receiving hospitals both accountable for patient outcomes. We aim to measure accuracy in recorded patient transfer information (indication of transfer and hospital identifier) over 2 years across 121 acute hospitals in New South Wales, Australia. Accuracy rate for 127,406 transfer-out separations was 87 per cent, with a low variability across hospitals (10% differences); it was 65 per cent for 151,978 transfer-in admissions with a greater inter-hospital variation (36% differences). Accuracy rate varied by departure and arrival pathways; at receiving hospitals, it was lower for transfer-in admission via emergency department (incidence rate ratio = 0.52, 95% confidence interval: 0.51-0.53) versus direct admission. Transfer-out data were more accurate for transfers to smaller hospitals (incidence rate ratio = 1.06, 95% confidence interval: 1.03-1.08) or re-transfers (incidence rate ratio > 1.08). Incorporation of transfer data from sending and receiving hospitals at patient level in administrative datasets and standardisation of documentation across hospitals would enhance accuracy and support improved attribution of hospital performance measures.

Transcatheter aortic valve implantation and surgical aortic valve replacement among hospitalized patients with and without type 2 diabetes mellitus in Spain (2014-2015)

Background

Type 2 diabetes mellitus (T2DM) is strongly related to the in-hospital and short-term prognosis in patients with cardiovascular diseases needing surgical or invasive interventions. How T2DM might influence the treatment of aortic stenosis (AS) has not been completely elucidated for surgical aortic valve replacement (SAVR) or transcatheter aortic valve implantation (TAVI). The aims of this study were: (1) to describe the use of aortic valve replacement procedures (TAVI and SAVR) among hospitalized patients with and without T2DM; and (2) to identify factors associated with in hospital mortality (IHM) among patients undergoing these procedures.

Methods

We analyzed data from the Spanish National Hospital Discharge Database between January 1, 2014 and December 31, 2015 for patients aged ≥ 40 years. We selected patients whose medical procedures included TAVI (ICD-9-CM codes 35.05, 35.06) and SAVR (ICD-9-CM codes 35.21, 35.22). We stratified each cohort by diabetes status: T2DM (ICD-9-CM codes 250.x0, 250.x2) and no diabetes. We retrieved data about specific comorbidities, risk factors, procedures, and specific in-hospital postoperative complications. Hospital outcome variables included IHM, and length of hospital stay (LOHS).

Results

We identified a total of 2141 and 16,013 patients who underwent TAVI (n = 715; 33.39% with T2DM) and SAVR (n = 4057; 25.33% with T2DM). In patients who underwent TAVI we found no differences in IHM (3.64% in T2DM vs. 5.12% in non-T2DM, p = 0.603). In the cohort of SAVR, mean LOHS was significantly lower in patients with T2DM than in non-diabetic patients (13.77 vs. 17.27 days). IHM was lower in patients with T2DM (4.36% vs. 6.31%, p < 0.01). After multivariable adjustment for both procedures, patients with T2DM had significantly lower IHM than patients without diabetes (adjusted OR 0.60; IC 95% 0.37–0.99 for TAVI and adjusted OR 0.80; IC 95% 0.66-0-96 for SAVR).

Conclusions

T2DM diabetic patients with AS undergoing a valvular replacement procedure through SAVR or TAVI did not have a worse prognosis compared to non-diabetic patients during hospitalization, showing lower IHM after multivariable adjustment. However, given the limitations of administrative data more prospective studies and clinical trials aimed at evaluating the influence of these procedures in diabetic patients with AS are needed.

Electronic supplementary material

The online version of this article (10.1186/s12933-017-0631-6) contains supplementary material, which is available to authorized users.

Association of type 2 diabetes with in-hospital complications among women undergoing breast cancer surgical procedures. A retrospective study using the Spanish National Hospital Discharge Database, 2013-2014

OBJECTIVES

To compare the type of surgical procedures used, comorbidities, in-hospital complications (IHC) and in-hospital outcomes between women with type 2 diabetes mellitus (T2DM) and age-matched women without diabetes who were hospitalised with breast cancer. In addition, we sought to identify factors associated with IHC in women with T2DM who had undergone surgical procedures for breast cancer.

DESIGN

Retrospective study using the National Hospital Discharge Database, 2013-2014.

SETTING

Spain.

PARTICIPANTS

Women who were aged ≥40 years with a primary diagnosis of breast cancer and who had undergone a surgical procedure. We grouped admissions by T2DM status. We selected one matched control for each T2DM case.

MAIN OUTCOME MEASURES

The type of procedure (breast-conserving surgery (BCS) or mastectomy), clinical characteristics, complications, length of hospital stay and in-hospital mortality.

RESULTS

We identified 41 458 admissions (9.23% with T2DM). Overall, and in addition to the surgical procedure, we found that comorbidity, hypertension and obesity were more common among patients with T2DM. We also detected a higher incidence of mastectomy in women with T2DM (44.69% vs 42.42%) and a greater rate of BCS in patients without T2DM (57.58% vs 55.31%). Overall, non-infectious complications were more common among women with T2DM (6.40% vs 4.56%). Among women who had undergone BCS or a mastectomy, IHC were more frequent among diabetics (5.57% vs 3.04% and 10.60% vs 8.24%, respectively). Comorbidity was significantly associated with a higher risk of IHC in women with diabetes, independent of the specific procedure used.province CONCLUSIONS: Women with T2DM who undergo surgical breast cancer procedures have more comorbidity, risk factors and advanced cancer presentations than matched patients without T2DM. Mastectomies are more common in women with T2DM. Moreover, the procedures among women with T2DM were associated with greater IHC. Comorbidity was a strong predictor of IHC in women with T2DM.

Record linkage study of the pathogen-specific burden of respiratory viruses in children

Background

Reliance on hospital discharge diagnosis codes alone will likely underestimate the burden of respiratory viruses.

Objectives

To describe the epidemiology of respiratory viruses more accurately, we used record linkage to examine data relating to all children hospitalized in Western Australia between 2000 and 2012.

Patients/Methods

We extracted hospital, infectious disease notification and laboratory data of a cohort of children born in Western Australia between 1996 and 2012. Laboratory records of respiratory specimens collected within 48 hours of admission were linked to hospitalization records. We calculated the frequency and rates of virus detection. To identify groups where under‐ascertainment for respiratory viruses was greatest, we used logistic regression to determine factors associated with failure to test.

Results and conclusions

Nine percentage of 484 992 admissions linked to a laboratory record for respiratory virus testing. While 62% (n = 26 893) of laboratory‐confirmed admissions received respiratory infection diagnosis codes, 38% (n = 16 734) had other diagnoses, notably viral infection of unspecified sites. Of those tested, incidence rates were highest for respiratory syncytial virus (247 per 100 000 child‐years) followed by parainfluenza (63 per 100 000 child‐years). Admissions among older children and those without a respiratory diagnosis were associated with failure to test for respiratory viruses. Linked data can significantly enhance diagnostic codes when estimating the true burden of disease. In contrast to current emphasis on influenza, respiratory syncytial virus and parainfluenza were the most common viral pathogens among hospitalized children. By characterizing those failing to be tested, we can begin to quantify the under‐ascertainment of respiratory viruses.

Impact of type 2 diabetes mellitus on in-hospital-mortality after major cardiovascular events in Spain (2002-2014)

BACKGROUND

Diabetes mellitus has long been associated with cardiovascular events. Nevertheless, the higher burden of traditional cardiovascular risk factors reported in high-income countries is offset by a more widespread use of preventive measures and revascularization or other invasive procedures. The aim of this investigation is to describe trends in number of cases and outcomes, in-hospital mortality (IHM) and length of hospital stay (LHS), of hospital admissions for major cardiovascular events between type 2 diabetes (T2DM) and matched non-diabetes patients.

METHODS

Retrospective study using National Hospital Discharge Database, analyzed in 4 years 2002, 2006, 2010, 2014, in Spain. We included patients (≥ 40 years old) with a primary diagnosis of myocardial infarction, ischemic and hemorrhagic stroke, aortic aneurysm and dissection and acute lower limb ischemia in people with T2DM. Cases were matched with controls (without T2DM) by ICD-9-CM codes, sex, age, province of residence and year.

RESULTS

We selected 130,011 matched couples (50,427 with myocardial infarction, 60,236 with stroke, 2599 with aortic aneurysm and dissection and 16,749 with acute lower limb ischemia. Among T2DM patients we found increasing numbers of admissions overtime for stroke (10,794 in 2002 vs 17,559 in 2014), aortic aneurysm and dissection (390 vs 841) and acute lower limb ischemia (3854 vs. 4548). People were progressively older (except for myocardial infarction), had more comorbidities (especially T2DM patients), and were more frequently coded overtime for cardiovascular risk factors (smoking, obesity, hypertension, lipid disorders) and renal diseases. LHS and IHM declined overtime, though IHM only did it significantly in T2DM patients. Multivariable adjustment showed that T2DM patients had a significantly 15% higher mortality rate during admission for myocardial infarction, a 6% higher mortality for stroke, and a 6% higher mortality rate for "all cardiovascular events combined", than non-diabetic matched controls.

CONCLUSIONS

The number of hospital admissions for stroke, aortic aneurysm and dissection and acute lower limb ischemia increased overtime, but remained stable for myocardial infarction. T2DM is associated to higher IHM after major cardiovascular events. Further research is needed to help us understand the reasons for an apparently increased mortality in T2DM patients when admitted to hospital for some major cardiovascular events.

Self-reported versus health administrative data: implications for assessing chronic illness burden in populations. A cross-sectional study

BACKGROUND

Various data sources may be used to document the presence of chronic medical conditions. This study examined the agreement between self-reported and health administrative data.

METHODS

A randomly selected cohort of participants aged 25-75 years recruited by telephone from the general population of Quebec reported on the presence of 1 or more chronic conditions from a candidate list of 12 conditions: diabetes, hypertension, thyroid disorder, any cardiac disease, cancer diagnosis in the previous 5 years (including melanoma but excluding other skin cancers), asthma, osteoarthritis, rheumatoid arthritis or lupus, osteoporosis, chronic obstructive pulmonary disease, intestinal disease and hypercholesterolemia. We also used health administrative data from Quebec's universal health insurance provider to identify participants' chronic conditions. Unique identifiers allowed linkage of both data sources to the individual participant. The frequencies of the 12 conditions and the prevalence of multimorbidity (≥ 2, ≥ 3 and ≥ 4 conditions) were analyzed for each data source.

RESULTS

We analyzed data for 1177 participants (mean age 53 [standard deviation 12.4] yr; 684 women [58.1%]). We found low (but varied) agreement between the 2 data sources, with the poorest agreement for hypercholesterolemia (κ = 0.04 [95% confidence interval (CI) 0.01 to 0.07]) and the best for diabetes (κ = 0.82 [95% CI 0.76 to 0.88]). Prevalence estimates of multimorbidity obtained with health administrative data were lower than those obtained with self-reported data regardless of the operational definition used. Most participants with multimorbidity were identified by self-report.

INTERPRETATION

We argue for the use of self-reported chronic conditions in the study of multimorbidity, as health administrative data based on the billing system in Quebec seem to underestimate the prevalence of many chronic conditions, which results in biased estimates of multimorbidity.

Multimorbidity in Australia: Comparing estimates derived using administrative data sources and survey data

Background

Estimating multimorbidity (presence of two or more chronic conditions) using administrative data is becoming increasingly common. We investigated (1) the concordance of identification of chronic conditions and multimorbidity using self-report survey and administrative datasets; (2) characteristics of people with multimorbidity ascertained using different data sources; and (3) whether the same individuals are classified as multimorbid using different data sources.

Methods

Baseline survey data for 90,352 participants of the 45 and Up Study—a cohort study of residents of New South Wales, Australia, aged 45 years and over—were linked to prior two-year pharmaceutical claims and hospital admission records. Concordance of eight self-report chronic conditions (reference) with claims and hospital data were examined using sensitivity (Sn), positive predictive value (PPV), and kappa (κ).The characteristics of people classified as multimorbid were compared using logistic regression modelling.

Results

Agreement was found to be highest for diabetes in both hospital and claims data (κ = 0.79, 0.78; Sn = 79%, 72%; PPV = 86%, 90%). The prevalence of multimorbidity was highest using self-report data (37.4%), followed by claims data (36.1%) and hospital data (19.3%). Combining all three datasets identified a total of 46 683 (52%) people with multimorbidity, with half of these identified using a single dataset only, and up to 20% identified on all three datasets. Characteristics of persons with and without multimorbidity were generally similar. However, the age gradient was more pronounced and people speaking a language other than English at home were more likely to be identified as multimorbid by administrative data.

Conclusions

Different individuals, with different combinations of conditions, are identified as multimorbid when different data sources are used. As such, caution should be applied when ascertaining morbidity from a single data source as the agreement between self-report and administrative data is generally poor. Future multimorbidity research exploring specific disease combinations and clusters of diseases that commonly co-occur, rather than a simple disease count, is likely to provide more useful insights into the complex care needs of individuals with multiple chronic conditions.

Comparing routine administrative data with registry data for assessing quality of hospital care in patients with myocardial infarction using deterministic record linkage

Background

Assessment of quality of care in patients with myocardial infarction (MI) should be based on data that effectively enable determination of quality. With the need to simplify measurement techniques, the question arises whether routine data can be used for this purpose. We therefore compared data from a German sickness fund (AOK) with data from the Berlin Myocardial Infarction Registry (BMIR).

Methods

We included patients hospitalised for treatment of MI in Berlin from 2009-2011. We matched 2305 patients from AOK and BMIR by using deterministic record linkage with indirect identifiers. For matched patients we compared the frequency in documentation between AOK and BMIR for quality assurance variables and calculated the kappa coefficient (KC) as a measure of agreement.

Results

There was almost perfect agreement in documentation between AOK and BMIR data for matched patients for: catheter laboratory (KC: 0.874), ST elevation MI (KC: 0.826), diabetes (KC: 0.818), percutaneous coronary intervention (KC: 0.860) and hospital mortality (KC: 0.952). The remaining variables compared showed moderate or less than moderate agreement (KC < 0.6), and were grouped in Category II with less frequent documentation in AOK for risk factors and aspects of patients’ history; in Category III with more frequent documentation in AOK for comorbidities; and in Category IV for medication at and after hospital discharge.

Conclusions

Routine data are primarily collected and defined for reimbursement purposes. Quality assurance represents merely a secondary use. This explains why only a limited number of variables showed almost perfect agreement in documentation between AOK and BMIR. If routine data are to be used for quality assessment, they must be constantly monitored and further developed for this new application. Furthermore, routine data should be complemented with registry data by well-established methods of record linkage to realistically reflect the situation – also for those quality-associated variables not collected in routine data.

Incidences and variations of hospital acquired venous thromboembolism in Australian hospitals: a population-based study

BACKGROUND

Data on hospital-acquired venous thromboembolism (HA-VTE) incidence, case fatality rate and variation amongst patient groups and health providers is lacking. We aim to explore HA-VTE incidences, associated mortality, trends and variations across all acute hospitals in New South Wales (NSW)-Australia.

METHODS

A population-based study using all admitted patients (aged 18-90 with a length of stay of at least two days and not transferred to another acute care facility) in 104 NSW acute public and private hospitals during 2002-2009. Poisson mixed models were used to derive adjusted rate ratios (IRR) in presence of patient and hospital characteristics.

RESULTS

Amongst, 3,331,677 patients, the incidence of HA-VTE was 11.45 per 1000 patients and one in ten who developed HA-VTE died in hospital. HA-VTE incidence, initially rose, but subsequently declined, whereas case fatality rate consistently declined by 22 % over the study period. Surgical patients were 128 % (IRR = 2.28, 95 % CI: 2.19-2.38) more likely to develop HA-VTE, but had similar case fatality rates compared to medical patients. Private hospitals, in comparison to public hospitals had a higher incidence of HA-VTE (IRR = 1.76; 95 % CI: 1.42-2.18) for medical patients. However, they had a similar incidence (IRR = 0.91; 95 % CI: 0.75-1.11), but a lower mortality (IRR = 0.59; 95 % CI: 0.47-0.75) amongst surgical patients. Smaller public hospitals had a lower HA-VTE incidence rate compared to larger hospitals (IRR < 0.68) but a higher case fatality rate (IRR > 1.71). Hospitals with a lower reported HA-VTE incidence tended to have a higher HA-VTE case fatality rate.

CONCLUSION

Despite the decline in HA-VTE incidence and case fatality, there were large variations in incidents between medical and surgical patients, public and private hospitals, and different hospital groups. The causes of such differences warrant further investigation and may provide potential for targeted interventions and quality improvement initiatives.

Effect of change in coding rules on recording diabetes in hospital administrative datasets

AIM

During 2008-2011 Australian Coding Standards mandated a causal relationship between diabetes and inpatient care as a criterion for recording diabetes as a comorbidity in hospital administrative datasets. We aim to measure the effect of the causality mandate on recorded diabetes and associated inter-hospital variations.

METHOD

For patients with diabetes, all admissions between 2004 and 2013 to all New South Wales acute public hospitals were investigated. Poisson mixed models were employed to derive adjusted rates and variations.

RESULTS

The non-recorded diabetes incidence rate was 20.7%. The causality mandate increased the incidence rate four fold during the change period, 2008-2011, compared to the pre- or post-change periods (32.5% vs 8.4% and 6.9%). The inter-hospital variation was also higher, with twice the difference in the non-recorded rate between hospitals with the highest and lowest rates (50% vs 24% and 27% risk gap). The variation decreased during the change period (29%), while the rate continued to rise (53%). Admission characteristics accounted for over 44% of the variation compared with at most two per cent attributable to patient or hospital characteristics. Contributing characteristics explained less of the variation within the change period compared to pre- or post-change (46% vs 58% and 53%). Hospital relative performance was not constant over time.

CONCLUSION

The causality mandate substantially increased the non-recorded diabetes rate and associated inter-hospital variation. Longitudinal accumulation of clinical information at the patient level, and the development of appropriate adoption protocols to achieve comprehensive and timely implementation of coding changes are essential to supporting the integrity of hospital administrative datasets.

Total caseload of a colorectal surgical unit: baseline measurement and identification of areas for efficiency gains

PURPOSE

Resource limitations are a concern in most modern public hospital systems. The aim of this study is to prospectively quantify the total caseload of a tertiary colorectal surgery unit to identify areas of redundancy.

METHODS

Data was collected prospectively at all points of clinical care (outpatient clinic, inpatient referrals, operating theatre and endoscopy) between March 2014 and March 2015 using specifically designed templates. The final data was analysed using descriptive statistics.

RESULTS

During the study period, 4012 patient episodes were recorded: 2871 in outpatient clinic, 186 as emergency patient referrals, 541 at colonoscopy and 414 at surgery. The largest component of the caseload was made up primarily of colonoscopy results follow-up, protocol review for previous cancer or polyps and post-operative review. Sixty-eight percent of these episodes did not result in any active intervention such as further tests or surgery. Most new outpatient referrals were undifferentiated, with the most common indications being minor rectal bleeding, non-specific gastrointestinal symptoms, and minor non-bleeding anorectal problems. Of the new referrals, 56 % were booked for a colonoscopy, and only 13.3 % were booked directly for elective surgery.

CONCLUSION

A large component of the caseload of a tertiary colorectal surgery unit is made up of post-colonoscopy, post-operative, and surveillance protocol follow-up, with a significant proportion of patients not requiring any active intervention. The majority of new referrals are undifferentiated and result in a low rate of direct booking for operative intervention. Rationalisation of this resource using evidence-based methods could reduce redundancy, workload, and cost.

The extra resource burden of in-hospital falls: a cost of falls study

OBJECTIVE

To quantify the additional hospital length of stay (LOS) and costs associated with in-hospital falls and fall injuries in acute hospitals in Australia.

DESIGN, SETTING AND PARTICIPANTS

A multisite prospective cohort study conducted during 2011-2013 in the control wards of a falls prevention trial (6-PACK). The trial included all admissions to 12 acute medical and surgical wards of six Australian hospitals. In-hospital falls data were collected from medical record reviews, daily verbal reports by ward nurse unit managers, and hospital incident reporting and administrative databases. Clinical costing data were linked for three of the six participating hospitals to calculate patient-level costs.

OUTCOME MEASURES

Hospital LOS and costs associated with in-hospital falls and fall injuries for each patient admission.

RESULTS

We found that 966 of a total of 27 026 hospital admissions (3.6%) involved at least one fall, and 313 (1.2%) at least one fall injury, a total of 1330 falls and 418 fall injuries. After adjustment for age, sex, cognitive impairment, admission type, comorbidity and clustering by hospital, patients who had an in-hospital fall had a mean increase in LOS of 8 days (95% CI, 5.8-10.4; P < 0.001) compared with non-fallers, and incurred mean additional hospital costs of $6669 (95% CI, $3888-$9450; P < 0.001). Patients with a fall-related injury had a mean increase in LOS of 4 days (95% CI, 1.8-6.6; P = 0.001) compared with those who fell without injury, and there was also a tendency to additional hospital costs (mean, $4727; 95% CI, -$568 to $10 022; P = 0.080).

CONCLUSION

Patients who experience an in-hospital fall have significantly longer hospital stays and higher costs. Programs need to target the prevention of all falls, not just the reduction of fall-related injuries.

Incidence and Variation of Discrepancies in Recording Chronic Conditions in Australian Hospital Administrative Data

Diagnostic data routinely collected for hospital admitted patients and used for case-mix adjustment in care provider comparisons and reimbursement are prone to biases. We aim to measure discrepancies, variations and associated factors in recorded chronic morbidities for hospital admitted patients in New South Wales (NSW), Australia. Of all admissions between July 2010 and June 2014 in all NSW public and private acute hospitals, admissions with over 24 hours stay and one or more of the chronic conditions of diabetes, smoking, hepatitis, HIV, and hypertension were included. The incidence of a non-recorded chronic condition in an admission occurring after the first admission with a recorded chronic condition (index admission) was considered as a discrepancy. Poisson models were employed to (i) derive adjusted discrepancy incidence rates (IR) and rate ratios (IRR) accounting for patient, admission, comorbidity and hospital characteristics and (ii) quantify variation in rates among hospitals. The discrepancy incidence rate was highest for hypertension (51% of 262,664 admissions), followed by hepatitis (37% of 12,107), smoking (33% of 548,965), HIV (27% of 1500) and diabetes (19% of 228,687). Adjusted rates for all conditions declined over the four-year period; with the sharpest drop of over 80% for diabetes (47.7% in 2010 vs. 7.3% in 2014), and 20% to 55% for the other conditions. Discrepancies were more common in private hospitals and smaller public hospitals. Inter-hospital differences were responsible for 1% (HIV) to 9.4% (smoking) of variation in adjusted discrepancy incidences, with an increasing trend for diabetes and HIV. Chronic conditions are recorded inconsistently in hospital administrative datasets, and hospitals contribute to the discrepancies. Adjustment for patterns and stratification in risk adjustments; and furthermore longitudinal accumulation of clinical data at patient level, refinement of clinical coding systems and standardisation of comorbidity recording across hospitals would enhance accuracy of datasets and validity of case-mix adjustment.

Lower hazard ratio for death in women with cerebral hemorrhage

OBJECTIVES

The aim of the study was to clarify the hazard ratio for death within 30 days after stroke comparing women to men.

MATERIAL AND METHODS

We reviewed all stroke patients registered in the Kyoto Stroke Registry (from January 1999 to December 2009) in Japan. Hazard ratio (HR) for death and 95% confidence interval were calculated by the Cox regression in stroke and in each stroke subtype: cerebral infarction (CI), cerebral hemorrhage, (CH) and subarachnoid hemorrhage (SAH). We also evaluated HR for death in women in each consciousness level at the onset of stroke: the Japan Coma Scale (JCS) 0 (alert), JCS 1-digit code (disoriented but awake), JCS 2-digit code (arousable with stimulation), and JCS 3-digit code (unarousable).

RESULTS

A total of 13,788 patients were analyzed. HR for death comparing women to men were 1.04 (0.88-1.23, P = 0.66 in stroke as a whole), 0.91 (0.69-1.21, P = 0.51 in CI), 0.53 (0.41-0.71, P < 0.01 in CH), and 0.89 (0.60-1.30, P = 0.535 in SAH) after adjustment for age and histories of hypertension, arrhythmia, diabetes mellitus and hyperlipemia and uses of tobacco and alcohol. Stratified by JCS, HR for death in women with CH were 0.32 (0.11-0.94 in JCS0), 0.48 (0.28-0.82 in JCS1), 0.49 (0.28-0.83 in JCS2), and 0.79 (0.65-0.97 in JCS3), respectively. HR for death in women with CI in JCS3 was significantly lower than in men (0.71; 0.52-0.98).

CONCLUSION

We evaluated HR for death comparing men to women in stroke and in each stroke subtype. Women with CH had lower HR for death within 30 days after stroke than men.