Supporting Pharmacovigilance Signal Validation and Prioritization with Analyses of Routinely Collected Health Data: Lessons Learned from an EHDEN Network Study

Introduction: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals. Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process. Methods: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals. Results: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15–60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development. Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost–benefit of integrating these analyses at this stage of signal management requires further research

Comparative Effectiveness Research (CER) ‒ A Case Study

Background: The Australian healthcare system is complex. Assessing the quality of the care provided in the management of acute coronary syndromes (ACS) is problematic because of disparate systems that constrain an integrated reporting approach. Registry data reported within a comparative effectiveness research (CER) framework establishes the case for clinical process indicators to measure and report hospital performance. Objectives: To aggregate data from The Global Registry of Acute Coronary Events (GRACE) and the Cooperative National Registry of Acute Coronary Care Guideline Adherence and Clinical Events (CONCORDANCE) to describe temporal trends in the management of ACS and associations with in-hospital events, hospital readmission and six month mortality; to develop a composite score of hospital performance quality; to determine associations between adherence to the quality composite score and in-hospital events, hospital readmission and six month mortality and develop a benchmarked stakeholder hospital performance report. Methods: A single case study embedding three units of analysis was used to explore and explain how data reported in a CER framework measures hospital performance in the management of ACS. Analysis: Descriptive analyses of prospectively collected data on the management and outcomes of over 7000 patients admitted to 46 hospitals from 1999 to 2016. Findings: The first Unit of Analysis reports temporal trends in the management of ACS across 11 hospitals in the GRACE registry from 2000 to 2007 which informed the design of the CONCORDANCE registry; The second Unit of Analysis combines both GRACE and CONCORDANCE registries and reports on the management of ST-elevation acute myocardial infarction (STEMI ) from 1999 to 2016 revealing gains in pre-hospital care and fewer in-hospital clinical events, and readmission for urgent revascularisation without a significant reduction in in-hospital or six month mortality. The third Unit of Analysis reports the observed and risk-adjusted association between adherence to the quality composite score and reduced in-hospital events, and increased survival at hospital discharge and at six months post discharge. Conclusion: Case-study analysis of CER in the context of ACS registries provides evidence on adherence to evidence-based care and a quality composite measure of hospital performance in the management of ACS

Alcohol, assault and licensed premises in inner-city areas

This report contains eight linked feasibility studies conducted in Cairns during 2010. These exploratory studies examine the complex challenges of compiling and sharing information about incidents of person-to-person violence in a late night entertainment precinct (LNEP). The challenges were methodological as well as logistical and ethical. The studies look at how information can be usefully shared, while preserving the confidentiality of those involved. They also examine how information can be compiled from routinely collected sources with little or no additional resources, and then shared by the agencies that are providing and using the information.Although the studies are linked, they are also stand-alone and so can be published in peer-reviewed literature. Some have already been published, or are ‘in press’ or have been submitted for review. Others require the NDLERF board’s permission to be published as they include data related more directly to policing, or they include information provided by police.The studies are incorporated into the document under section headings. In each section, they are introduced and then presented in their final draft form. The final published form of each paper, however, is likely to be different from the draft because of journal and reviewer requirements. The content, results and implications of each study are discussed in summaries included in each section.Funded by the National Drug Law Enforcement Research Fund, an initiative of the National Drug StrategyAlan R Clough (PhD) School of Public Health, Tropical Medicine and Rehabilitation Sciences James Cook UniversityCharmaine S Hayes-Jonkers (BPsy, BSocSci (Hon1)) James Cook University, Cairns.Edward S Pointing (BPsych) James Cook University, Cairns

Temporal trends of cause-specific mortality after diagnosis of atrial fibrillation.

BACKGROUND AND AIMS: Reports of outcomes after atrial fibrillation (AF) diagnosis are conflicting. The aim of this study was to investigate mortality and hospitalisation rates following AF diagnosis over time, by cause, and by patient features. METHODS: Individuals aged ≥16 years with a first diagnosis of AF were identified from the UK Clinical Practice Research Datalink-GOLD dataset from Jan 1, 2001 to Dec 31, 2017. The primary outcomes were all-cause and cause-specific mortality and hospitalisation at 1 year following diagnosis. Poisson regression was used to calculate rate ratios (RRs) for mortality and incidence rate ratios (IRRs) for hospitalisation and 95% confidence intervals (CIs) comparing 2001/02 and 2016/17, adjusted for age, sex, region, socioeconomic status and 18 major comorbidities. RESULTS: Of 72 412 participants, mean (SD) age was 75.6 (12.4) years and 44 762 (61.8%) had ≥3 comorbidities. All-cause mortality declined (RR 2016/17 vs 2001/02 0.72; 95% CI 0.65-0.80), with large declines for cardiovascular (RR 0.46; 95% CI 0.37-0.58) and cerebrovascular mortality (RR 0.41; 95% CI 0.29-0.60) but not for non-cardio/cerebrovascular causes of death (RR 0.91; 95% CI 0.80-1.04). By 2016/17 deaths from dementia (67, 8.0%), outstripped deaths from acute myocardial infarction, heart failure and acute stroke combined (56, 6.7%, p < 0.001). Overall hospitalisation rates increased (IRR 2016/17 vs 2001/02 1.17; 95% CI, 1.13-1.22), especially for non-cardio/cerebrovascular causes (IRR 1.42; 95% CI 1.39-1.45). Older, more deprived, and hospital-diagnosed AF patients experienced higher event rates. CONCLUSIONS: After AF diagnosis, cardio/cerebrovascular mortality and hospitalisation has declined, whilst hospitalisation for non-cardio/cerebrovascular disease has increased

Electronic Information Sharing to Improve Post-Acute Care Transitions

Hospitals frequently transfer patients to skilled nursing facilities (SNFs) for post-acute care; information sharing between these settings is critical to ensure safe and effective transitions. Recent policy and payer initiatives have encouraged hospitals and SNFs to work together towards improving these care transitions, and associated patient outcomes such as avoidable re-hospitalizations. Exchanging information electronically, through health information exchange (HIE), can help facilitate information transfer, and has shown benefits to patient care in other contexts. But, it is unclear whether this evidence translates to the post-acute care context given the vulnerability of this patient population and complexities specific to coordination between acute and post-acute care settings. Chapter One estimates the national prevalence of hospital’s engagement in HIE with post-acute providers, and explores potential factors prompting this investment. 56% of hospitals report some level of HIE with post-acute care providers. This investment appears strategically to be more incidental than intentional; hospitals’ overall level of sophistication and investment in electronic health records and HIE strongly predicts whether HIE is occurring in the post-acute transition context. However, we see some evidence of association between participation in delivery and payment reforms and hospital use of HIE with post-acute providers. This suggests that HIE may increasingly be considered part of a comprehensive strategy to improve coordination between hospitals and post-acute care providers, though may lack the necessary customization to achieve meaningful value in this context. Chapter Two utilizes a difference-in-differences approach to assess HIE impact on patient outcomes in the post-acute context, exploiting one focal hospital’s selective implementation of HIE with just three partnering local SNFs. I find no measurable effect of HIE implementation on patient likelihood of re-hospitalization, relative to patients discharged to SNFs without HIE. However, log files that capture when and how these SNF providers use available HIE technology reveal significant variation in usage patterns. HIE was more often utilized following discharge situations where transitional care workflows may not be particularly robust, such as discharge from the ED or observation rather than an inpatient unit. However, the system was less likely to be used for more complex patients, and for patients discharged on the weekend – when SNFs operate at reduced staffing and may not have the bandwidth to leverage available technology. When we connect variation in usage patterns to likelihood of readmission, realizing patient care benefits depended on the timing (relative to patient transfer) and intensity (depth of information retrieved) of use. Chapter Three employs qualitative methods – semi-structured interviews with the focal hospital and five proximate SNFs – to better understand hospital-to-SNF transitions, and perceived opportunities and challenges in using HIE functionality to address information gaps. We capture five specific dimensions of information discontinuity; utilizing IT to address these issues is hindered by lack of process optimization from a sociotechnical perspective. Some SNFs lacked workflows to connect those with HIE access to the staff seeking information. Further, all facilities struggled with physician-centric transition processes that restricted availability of critical nursing and social work documentation, and promoted organizational changes that strengthened physician-to-physician handoff while unintentionally weakening inter-organizational transitional care processes. HIE has the potential to address information discontinuity that compromises post-acute transitions of care. These findings facilitate targeted efforts to help hospitals and SNFs pursue HIE in ways that are most likely to result in improved care quality and patient outcomes.PHDHealth Services Organization & PolicyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146031/1/dacross_1.pd

Identifying and appraising promising sources of UK clinical, health and social care data for use by NICE

This report aimed to aid the National Institute of Health and Care Excellence (NICE) in identifying opportunities for greater use of real-world data within its work. NICE identified five key ways in which real-world data was currently informing its work, or could do so in the future through: (i) researching the effectiveness of interventions or practice in real-world (UK) settings (ii) auditing the implementation of guidance (iii) providing information on resource use and evaluating the potential impact of guidance (iv) providing epidemiological information (v) providing information on current practice to inform the development of NICE quality standards. This report took a broad definition of ‘real-world’ data and created a map of UK sources, informed by a number of experts in real-world data, as well as a literature search, to highlight where some of the opportunities may lie for NICE within its clinical, public health and social care remit. The report was commissioned by the NICE, although the findings are likely to be of wider interest to a range of stakeholders interested in the role of real-world data in informing clinical, social care and public health decision-making. Most of the issues raised surrounding the use and appraisal of real-world data are likely to be generic, although the choice of datasets that were profiled in-depth reflected the interests of NICE. We discovered 275 sources that were named as real-world data sources for clinical, social care or public health investigation, 233 of which were deemed as active. The real-world data landscape therefore is highly complex and heterogeneous and composed of sources with different purposes, structures and collection methods. Some real-world data sources are purposefully either set-up or re-developed to enhance their data linkages and to examine the presence/absence/effectiveness of integrated patient care; however, such sources are in the minority. Furthermore, the small number of real-world data sources that are designed to enable the monitoring of care across providers, or at least have the capability to do so at a national level, have been utilised infrequently for this purpose in the literature. Data that offer the capacity to monitor transitions between health and social care do not currently exist at a national level, despite the increasing recognition of the interdependency between these sectors. Among the data sources we included, it was clear that no one data source represented a panacea for NICE’s real world data needs. This does highlight the merits and importance of data linkage projects and is suggestive of a need to triangulate evidence across different data, particularly in order to understand the feasibility and impact of guidance. There exists no overall catalogue or repository of real-world data sources for health, public health and social care, and previous initiatives aimed at creating such a resource have not been maintained. As much as there is a need for enhanced usage of the data, there is also a need for taking stock, integration, standardisation, and quality assurance of different sources. This research highlights a need for a systematic approach to creating an inventory of sources with detailed metadata and the funding to maintain this resource. This would represent an essential first step to support future initiatives aimed at enhancing the use of real-world data

Patient safety in English general practice : the role of routinely collected data in detecting adverse events

The use of routinely collected, or administrative, data for measuring and monitoring patient safety in primary care is a relatively new phenomenon. With increasing availability of data from different sources and care settings, their application for adverse event surveillance needs evaluation. In this thesis, I demonstrated that data routinely collected from primary care and secondary care can be applied for internal monitoring of adverse events at the general practice-level in England, but these data currently have limited use for safety benchmarking in primary care. To support this statement, multiple approaches were adopted. In the first part of the thesis, the nature and scope of patient safety issues in general practice were defined by evidence from a literature review and informal consultations with general practitioners (GPs). Secondly, using these two methods, measures of adverse events based on routinely collected healthcare data were identified. Thirdly, clinical consensus guided the selection of three candidate patient safety indicators for investigation; the safety issues explored in this thesis were recorded incidents with designated adverse event diagnostic codes and complications associated with two common diseases, emergency admissions for diabetic hyperglycaemic emergencies (diabetic ketoacidosis, DKA and hyperglycaemic hyperosmolar state, HHS) and cancer. In the second part of the thesis, the contributions of routinely collected data to new knowledge about potentially preventable adverse events in England were considered. Data from a primary care trust (NHS Brent), national primary care data (from the General Practice Research Database, GPRD) and secondary care data (Hospital Episode Statistics, HES) were used to explore the epidemiology of, and patient characteristics associated with, coded adverse events and emergency admissions for diabetic hyperglycaemic emergencies and cancer. Low rates of adverse events were found, with variation by individual patient factors. Finally, recommendations were made on extending the uses of routinely collected data for patient safety monitoring in general practice