Joao H. Bettencourt-Silva

On Creating a Patient-centric Database from Multiple Hospital Information Systems

BACKGROUND The information present in Hospital Information Systems (HIS) is heterogeneous and is used primarily by health practitioners to support and improve patient care. Conducting clinical research, data analyses or knowledge discovery projects using electronic patient data in secondary care centres relies on accurate data collection, which is often an ad-hoc process poorly described in the literature. OBJECTIVES This paper aims at facilitating and expanding on the process of retrieving and collating patient-centric data from multiple HIS for the purpose of creating a research database. The development of a process roadmap for this purpose illustrates and exposes the constraints and drawbacks of undertaking such work in secondary care centres. METHODS A data collection exercise was carried using a combined approach based on segments of well established data mining and knowledge discovery methodologies, previous work on clinical data integration and local expert consultation. A case study on prostate cancer was carried out at an English regional National Health Service (NHS) hospital. RESULTS The process for data retrieval described in this paper allowed patient-centric data, pertaining to the case study on prostate cancer, to be successfully collected from multiple heterogeneous hospital sources, and collated in a format suitable for further clinical research. CONCLUSIONS The data collection exercise described in this paper exposes the lengthy and difficult journey of retrieving and collating patient-centric, multi-source data from a hospital, which is indeed a non-trivial task, and one which will greatly benefit from further attention from researchers and hospital IT management.

Impact of Hemoglobin Levels and Anemia on Mortality in Acute Stroke: Analysis of UK Regional Registry Data, Systematic Review, and Meta‐Analysis

Background The impact of hemoglobin levels and anemia on stroke mortality remains controversial. We aimed to systematically assess this association and quantify the evidence. Methods and Results We analyzed data from a cohort of 8013 stroke patients (mean±SD, 77.81±11.83 years) consecutively admitted over 11 years (January 2003 to May 2015) using a UK Regional Stroke Register. The impact of hemoglobin levels and anemia on mortality was assessed by sex‐specific values at different time points (7 and 14 days; 1, 3, and 6 months; 1 year) using multiple regression models controlling for confounders. Anemia was present in 24.5% of the cohort on admission and was associated with increased odds of mortality at most of the time points examined up to 1 year following stroke. The association was less consistent for men with hemorrhagic stroke. Elevated hemoglobin was also associated with increased mortality, mainly within the first month. We then conducted a systematic review using the Embase and Medline databases. Twenty studies met the inclusion criteria. When combined with the cohort from the current study, the pooled population had 29 943 patients with stroke. The evidence base was quantified in a meta‐analysis. Anemia on admission was found to be associated with an increased risk of mortality in both ischemic stroke (8 studies; odds ratio 1.97 [95% CI 1.57–2.47]) and hemorrhagic stroke (4 studies; odds ratio 1.46 [95% CI 1.23–1.74]). Conclusions Strong evidence suggests that patients with anemia have increased mortality with stroke. Targeted interventions in this patient population may improve outcomes and require further evaluation.

Hyponatremia predicts mortality after stroke

Background Hyponatremia, the commonest electrolyte imbalance encountered in clinical practice, is associated with adverse outcomes. Despite this, understanding of the association between hyponatremia and stroke mortality outcome is limited. Aims To investigate the association between admission serum sodium and mortality at various time-points after stroke. Methods Cases of acute stroke admitted to Norfolk and Norwich University Hospital consecutively from January 2003 until June 2013 were included, with mortality outcomes ascertained until the end of December 2013. Odds ratios or hazards ratios for death were constructed for various time-points (within seven-days, 8-30 days, within one-year, and over full follow-up). Results There were 8540 participants included (47.4% male, mean age 77.3 (±12.0) years). Point prevalence of hypernatremia and hyponatremia were 3.3% and 13.8%, respectively. In fully adjusted models controlling for age, gender, prestroke modified Rankin score, stroke type, Oxford community stroke project class, and laboratory biochemical and hematological results, the odds ratio (up to one-year)/hazards ratio (for full follow-up) for the above time-points were 1.00, 1.11, 1.03, 1.05 for mild hyponatremia; 1.97, 0.78, 1.11, 1.2 for moderate hyponatremia; 3.31, 1.57, 2.45, 1.67 for severe hyponatremia; and 0.47, 1.23, 1.30, 1.10 for hypernatremia. When stratified by age groups, outcomes were poorer in younger hyponatremic patients (aged <75 years). Conclusion Hyponatremia is prevalent in acute stroke admissions and is independently associated with higher mortality in patients <75 years).

Building Data-Driven Pathways From Routinely Collected Hospital Data: A Case Study on Prostate Cancer

Background Routinely collected data in hospitals is complex, typically heterogeneous, and scattered across multiple Hospital Information Systems (HIS). This big data, created as a byproduct of health care activities, has the potential to provide a better understanding of diseases, unearth hidden patterns, and improve services and cost. The extent and uses of such data rely on its quality, which is not consistently checked, nor fully understood. Nevertheless, using routine data for the construction of data-driven clinical pathways, describing processes and trends, is a key topic receiving increasing attention in the literature. Traditional algorithms do not cope well with unstructured processes or data, and do not produce clinically meaningful visualizations. Supporting systems that provide additional information, context, and quality assurance inspection are needed. Objective The objective of the study is to explore how routine hospital data can be used to develop data-driven pathways that describe the journeys that patients take through care, and their potential uses in biomedical research; it proposes a framework for the construction, quality assessment, and visualization of patient pathways for clinical studies and decision support using a case study on prostate cancer. Methods Data pertaining to prostate cancer patients were extracted from a large UK hospital from eight different HIS, validated, and complemented with information from the local cancer registry. Data-driven pathways were built for each of the 1904 patients and an expert knowledge base, containing rules on the prostate cancer biomarker, was used to assess the completeness and utility of the pathways for a specific clinical study. Software components were built to provide meaningful visualizations for the constructed pathways. Results The proposed framework and pathway formalism enable the summarization, visualization, and querying of complex patient-centric clinical information, as well as the computation of quality indicators and dimensions. A novel graphical representation of the pathways allows the synthesis of such information. Conclusions Clinical pathways built from routinely collected hospital data can unearth information about patients and diseases that may otherwise be unavailable or overlooked in hospitals. Data-driven clinical pathways allow for heterogeneous data (ie, semistructured and unstructured data) to be collated over a unified data model and for data quality dimensions to be assessed. This work has enabled further research on prostate cancer and its biomarkers, and on the development and application of methods to mine, compare, analyze, and visualize pathways constructed from routine data. This is an important development for the reuse of big data in hospitals.

Changes in antiplatelet use prior to incident ischaemic stroke over 7 years in a UK centre and the association with stroke subtype

BACKGROUND guidelines have changed in relation to the indication of antiplatelet therapy for the primary and secondary prevention of stroke. Of interest is how the proportion of patients who had or had not taken antiplatelet agents prior to an incident stroke has changed over time, whether the type of antiplatelet agents used has altered and whether prior antiplatelet use is associated with a particular ischaemic stroke subtype. METHODS a stroke register was retrospectively examined. All ischaemic stroke patients admitted between January 2004 and March 2011 to a single University Hospital with a catchment population of ∼750,000 were included. We excluded those who were on anticoagulants prior to the ischaemic stroke. RESULTS a total of 4,307 ischaemic stroke patients [male 47.5%, mean age 77.6 (SD 11.7) years] were included. Of them, 54.7% (SD 2.2%) were not on any antiplatelet therapy prior to their incident stroke. The type and pattern of antiplatelet use prior to stroke did not change significantly during the 7-year study period, and there were no statistically significant differences between different ischaemic stroke subtypes with regards to prior antiplatelet use. CONCLUSIONS our findings highlight the requirement to improve currently available risk prediction scores as well as the potential clinical impact of antiplatelet resistance within the at risk population who are already on antiplatelets. These findings also indicate that targeting of multiple risk factors may be very important in stroke prevention.

Applying Clustering Analysis to Heterogeneous Data Using Similarity Matrix Fusion SMF

We define a heterogeneous dataset as a set of complex objects, that is, those defined by several data types including structured data, images, free text or time series. We envisage this could be extensible to other data types. There are currently research gaps in how to deal with such complex data. In our previous work, we have proposed an intermediary fusion approach called SMF which produces a pairwise matrix of distances between heterogeneous objects by fusing the distances between the individual data types. More precisely, SMF aggregates partial distances that we compute separately from each data type, taking into consideration uncertainty. Consequently, a single fused distance matrix is produced that can be used to produce a clustering using a standard clustering algorithm. In this paper we extend the practical work by evaluating SMF using the k-means algorithm to cluster heterogeneous data. We used a dataset of prostate cancer patients where objects are described by two basic data types, namely: structured and time-series data. We assess the results of clustering using external validation on multiple possible classifications of our patients. The result shows that the SMF approach can improved the clustering configuration when compared with clustering on an individual data type.

A 6-Point TACS Score Predicts In-Hospital Mortality Following Total Anterior Circulation Stroke

Background and Purpose Little is known about the factors associated with in-hospital mortality following total anterior circulation stroke (TACS). We examined the characteristics and comorbidity data for TACS patients in relation to in-hospital mortality with the aim of developing a simple clinical rule for predicting the acute mortality outcome in TACS. Methods A routine data registry of one regional hospital in the UK was analyzed. The subjects were 2,971 stroke patients with TACS (82% ischemic; median age=81 years, interquartile age range=74–86 years) admitted between 1996 and 2012. Uni- and multivariate regression models were used to estimate in-hospital mortality odds ratios for the study covariates. A 6-point TACS scoring system was developed from regression analyses to predict in-hospital mortality as the outcome. Results Factors associated with in-hospital mortality of TACS were male sex [adjusted odds ratio (AOR)=1.19], age (AOR=4.96 for ≥85 years vs. <65 years), hemorrhagic subtype (AOR=1.70), nonlateralization (AOR=1.75), prestroke disability (AOR=1.73 for moderate disability vs. no symptoms), and congestive heart failure (CHF) (AOR=1.61). Risk stratification using the 6-point TACS Score [T=type (hemorrhage=1 point) and territory (nonlateralization=1 point), A=age (65–84 years=1 point, ≥85 years=2 points), C=CHF (if present=1 point), S=status before stroke (prestroke modified Rankin Scale score of 4 or 5=1 point)] reliably predicted a mortality outcome: score=0, 29.4% mortality; score=1, 46.2% mortality [negative predictive value (NPV)=70.6%, positive predictive value (PPV)=46.2%]; score=2, 64.1% mortality (NPV=70.6, PPV=64.1%); score=3, 73.7% mortality (NPV=70.6%, PPV=73.7%); and score=4 or 5, 81.2% mortality (NPV=70.6%, PPV=81.2%). Conclusions We have identified the key determinants of in-hospital mortality following TACS and derived a 6-point TACS Score that can be used to predict the prognosis of particular patients.

Incidentally raised cardiac Troponin I has a worse prognosis in older patients compared to those with normal cardiac Troponin I and patients with Acute Coronary Syndrome:A Cohort Study

Background: Incidentally elevated cardiac troponin I (cTnI) levels are common in acutely unwell older patients. However, little is known about how this impacts on the prognosis of these patients. Objective: We aimed to investigate whether incidentally elevated cTnI levels (group 1) are associated with poorer outcome when compared to age- and sex-matched patients without an elevated cTnI level (group 2), and to patients diagnosed with acute coronary syndrome (group 3). Patients and Methods: This prospective, matched cohort study placed patients ≥75 years old who were admitted to a University teaching hospital into groups 1-3, based on the cTnI levels and underlying diagnosis. Outcomes were compared between the groups using mixed-effects regression models and adjusted for renal function and C-reactive protein. All-cause mortality at discharge, at 1 month and 3 months, alongside the length of hospital stay (LOS), were recorded. Results: In total, 315 patients were included, with 105 patients in each of the 3 groups. The mean age was 84.8 ± 5.5 years, with 41.9% males. All patients were followed up for 3 months. The percent all-cause mortality at discharge and the LOS for groups 1, 2 and 3 were 12.4, 3.8 and 8.6% and 11.2, 8.5 and 7.7 days, respectively. Group 1 had significantly increased mortality at 3 months [odds ratio (OR) 2.80, 95% confidence interval (CI) 1.12-6.96; p = 0.040] and LOS (OR 1.39, 95% CI 1.08-1.79; p = 0.008) compared to group 2 and did not differ significantly when compared to 3-month mortality (OR 2.39, 95% CI 0.91-6.29; p = 0.079) or LOS (OR 1.26, 95% CI 0.96-1.66; p = 0.097) in group 3. Conclusion: There is a significant association between an incidental rise in cTnI level with mortality and LOS in older patients. Further research is required to evaluate whether a more systematic management of these patients would improve the prognosis.

The ideal timing of ureteric stent removal in transplantation patients

Dear Sirs, With great interest, we read the paper by Alberts et al. [1], in which the authors report the results of their systematic review of urological complications following various ureterovesical anastomotic techniques. The authors included a subanalysis of the effect of stenting on outcomes from various ureterovesical anastomotic techniques. The authors compared the impact of stenting and nonstenting to assess the amount of bias, and this may have contributed to the rates of urological complications between different ureterovesical anastomotic techniques. These analyses did not show significant differences between the outcomes for both stented and nonstented groups. However, we feel that it is an oversimplification to cohort all studies using ureteric stents together as the duration of ureteric stent in situ is a significant factor in longer-term morbidity and it may obscure differences in outcomes between shorterand longer-term stent durations. The authors note that there were different durations of ureteric stenting within the stented study group and that there is a risk of urinary tract infection (UTI) with stents in situ for longer periods. However, they did not conduct a subanalysis based on ureteric stent duration in situ. The ideal timing of stent removal post-transplantation is a contentious issue. The authors have explained that there were not enough data in the included studies to assess the effect of ureteric stenting on UTIs and so we have collated our centres’ longer-term data on this topic to contribute our experience of ureteric stenting. The guideline at our institution is for ureteric stent removal at 6 weeks post-operatively. We investigated how the rates of UTI varied on the duration of ureteric stent in situ. We conducted a retrospective observational study on all patients who had ureteric stents inserted postrenal transplantation between January 2009 and March 2013 at our centre. A total of 404 patients were included. The average age of the cohort was 47.8 years (SD 12.7) of which 51 patients (14%) had UTIs. A large proportion of patients (26%) had their stent removed 7–8 weeks post-operatively. The reasons for late removal were pragmatic; however, there was no increase in UTI rate in this cohort compared with patients who had their stent removed before 7 weeks (Table 1). The average age of patients who had complications was 50.2 years (SD 12.5). Several studies have concluded that early stent removal at 1 week [2,3], 2 weeks [4,5], 4 weeks [6] and 4–6 weeks [7] is beneficial. However, these studies have not assessed UTI risk in stents as long as 6–8 weeks in situ [2,8], and our cohort is the largest study on longer-duration stents and shows that this risk appears to tail off over time (Table 1) and is not linearly related to the duration of stent in situ as previously perceived [3]. It is clear that the duration of stents is important for UTIs, and so, it may be equally important when considering urological complications from different anastomotic techniques. It may be possible that the outcomes from the stented group described by Alberts et al. [1] may be confounded if outcomes from studies with longer-duration stents are obscured by results from studies with

Impact of stroke-associated pneumonia on mortality, length of hospitalization and functional outcome

Stroke‐associated pneumonia (SAP) is common and associated with adverse outcomes. Data on its impact beyond 1 year are scarce.