Faculty Bibliography

BACKGROUND:NHS hospitals collect a wealth of administrative data covering accident and emergency (A&E) department attendances, inpatient and day case activity, and outpatient appointments. Such data are increasingly being used to compare units and services, but adjusting for risk is difficult. OBJECTIVES:To derive robust risk-adjustment models for various patient groups, including those admitted for heart failure (HF), acute myocardial infarction, colorectal and orthopaedic surgery, and outcomes adjusting for available patient factors such as comorbidity, using England’s Hospital Episode Statistics (HES) data. To assess if more sophisticated statistical methods based on machine learning such as artificial neural networks (ANNs) outperform traditional logistic regression (LR) for risk prediction. To update and assess for the NHS the Charlson index for comorbidity. To assess the usefulness of outpatient data for these models. MAIN OUTCOME MEASURES:Mortality, readmission, return to theatre, outpatient non-attendance. For HF patients we considered various readmission measures such as diagnosis-specific and total within a year. METHODS:We systematically reviewed studies comparing two or more comorbidity indices. Logistic regression, ANNs, support vector machines and random forests were compared for mortality and readmission. Models were assessed using discrimination and calibration statistics. Competing risks proportional hazards regression and various count models were used for future admissions and bed-days. RESULTS: = 0.73 for death following stroke. Calibration was often good for procedure groups but poorer for diagnosis groups, with overprediction of low risk a common cause. The machine learning methods we investigated offered little beyond LR for their greater complexity and implementation difficulties. For HF, some patient-level predictors differed by primary diagnosis of readmission but not by length of follow-up. Prior non-attendance at outpatient appointments was a useful, strong predictor of readmission. Hospital-level readmission rates for HF did not correlate with readmission rates for non-HF; hospital performance on national audit process measures largely correlated only with HF readmission rates. CONCLUSIONS:Many practical risk-prediction or casemix adjustment models can be generated from HES data using LR, though an extra step is often required for accurate calibration. Including outpatient data in readmission models is useful. The three machine learning methods we assessed added little with these data. Readmission rates for HF patients should be divided by diagnosis on readmission when used for quality improvement. FUTURE WORK:As HES data continue to develop and improve in scope and accuracy, they can be used more, for instance A&E records. The return to theatre metric appears promising and could be extended to other index procedures and specialties. While our data did not warrant the testing of a larger number of machine learning methods, databases augmented with physiological and pathology information, for example, might benefit from methods such as boosted trees. Finally, one could apply the HF readmissions analysis to other chronic conditions. FUNDING:The National Institute for Health Research Health Services and Delivery Research programme.

OBJECTIVES: To investigate the effect of providing patients online access to their electronic health record (EHR) and linked transactional services on the provision, quality and safety of healthcare. The objectives are also to identify and understand: barriers and facilitators for providing online access to their records and services for primary care workers; and their association with organisational/IT system issues. SETTING: Primary care. PARTICIPANTS: A total of 143 studies were included. 17 were experimental in design and subject to risk of bias assessment, which is reported in a separate paper. Detailed inclusion and exclusion criteria have also been published elsewhere in the protocol. PRIMARY AND SECONDARY OUTCOME MEASURES: Our primary outcome measure was change in quality or safety as a result of implementation or utilisation of online records/transactional services. RESULTS: No studies reported changes in health outcomes; though eight detected medication errors and seven reported improved uptake of preventative care. Professional concerns over privacy were reported in 14 studies. 18 studies reported concern over potential increased workload; with some showing an increase workload in email or online messaging; telephone contact remaining unchanged, and face-to face contact staying the same or falling. Owing to heterogeneity in reporting overall workload change was hard to predict. 10 studies reported how online access offered convenience, primarily for more advantaged patients, who were largely highly satisfied with the process when clinician responses were prompt. CONCLUSIONS: Patient online access and services offer increased convenience and satisfaction. However, professionals were concerned about impact on workload and risk to privacy. Studies correcting medication errors may improve patient safety. There may need to be a redesign of the business process to engage health professionals in online access and of the EHR to make it friendlier and provide equity of access to a wider group of patients. A1 SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO CRD42012003091.

BACKGROUND: Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive. OBJECTIVE: To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines. METHOD: We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars. RESULTS: We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowdsourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the "internet of things", and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources. CONCLUSIONS: Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.

OBJECTIVE: To identify risk factors for falls and generate two screening tools: an opportunistic tool for use in consultation to flag at risk patients and a systematic database screening tool for comprehensive falls assessment of the practice population. STUDY DESIGN AND SETTING: This multicenter cohort study was part of the quality improvement in chronic kidney disease trial. Routine data for participants aged 65 years and above were collected from 127 general practice (GP) databases across the UK, including sociodemographic, physical, diagnostic, pharmaceutical, lifestyle factors, and records of falls or fractures over 5 years. Multilevel logistic regression analyses were performed to identify predictors. The strongest predictors were used to generate a decision tree and risk score. RESULTS: Of the 135,433 individuals included, 10,766 (8%) experienced a fall or fracture during follow-up. Age, female sex, previous fall, nocturia, anti-depressant use, and urinary incontinence were the strongest predictors from our risk profile (area under the receiver operating characteristics curve = 0.72). Medication for hypertension did not increase the falls risk. Females aged over 75 years and subjects with a previous fall were the highest risk groups from the decision tree. The risk profile was converted into a risk score (range -7 to 56). Using a cut-off of >/=9, sensitivity was 68%, and specificity was 60%. CONCLUSION: Our study developed opportunistic and systematic tools to predict falls without additional mobility assessments.

BACKGROUND: Acquired adult-onset hearing loss is a common long-term condition for which the most common intervention is hearing aid fitting. However, up to 40% of people fitted with a hearing aid either fail to use it or may not gain optimal benefit from it. OBJECTIVES: To assess the long-term effectiveness of interventions to promote the use of hearing aids in adults with acquired hearing loss fitted with at least one hearing aid. SEARCH METHODS: We searched the Cochrane ENT Disorders Group Trials Register; CENTRAL; PubMed; EMBASE; CINAHL; Web of Science; Cambridge Scientific Abstracts; ICTRP and additional sources for published and unpublished trials. The date of the search was 6 November 2013. SELECTION CRITERIA: We included randomised controlled trials (RCTs) of interventions designed to improve or promote hearing aid use in adults with acquired hearing loss compared with usual care or another intervention. We excluded interventions that compared hearing aid technology. We classified interventions according to the 'chronic care model' (CCM). The primary outcomes were hearing aid use (measured as adherence or daily hours of use) and adverse effects (inappropriate advice or clinical practice, or patient complaints). Secondary patient-reported outcomes included quality of life, hearing handicap, hearing aid benefit and communication. Outcomes were measured over the short ( 12 to < 52 weeks) and long term (one year plus). DATA COLLECTION AND ANALYSIS: We used the standard methodological procedures expected by The Cochrane Collaboration. MAIN RESULTS: We included 32 studies involving a total of 2072 participants. The risk of bias across the included studies was variable. We judged the GRADE quality of evidence to be very low or low for the primary outcomes where data were available.The majority of participants were over 65 years of age with mild to moderate adult-onset hearing loss. There was a mix of new and experienced hearing aid users. Six of the studies (1018 participants) were conducted in a military veteran population. Six of the studies (287 participants) assessed long-term outcomes.All 32 studies tested interventions that could be classified as self management support (ways to help someone to manage their hearing loss and hearing aid(s) better by giving information, practice and experience at listening/communicating or by asking people to practise tasks at home) and/or delivery system design interventions (just changing how the service was delivered) according to the CCM. Self management support interventions We found no studies that investigated the effect of these interventions on adherence, adverse effects or hearing aid benefit. Two studies reported daily hours of hearing aid use but we were unable to combine these in a meta-analysis. There was no evidence of a statistically significant effect on quality of life over the medium term. Self management support reduced short- to medium-term hearing handicap (two studies, 87 participants; mean difference (MD) -12.80, 95% confidence interval (CI) -23.11 to -2.48 (0 to 100 scale)) and increased the use of verbal communication strategies in the short to medium term (one study, 52 participants; MD 0.72, 95% CI 0.21 to 1.23 (0 to 5 scale)). The clinical significance of these statistical findings is uncertain but it is likely that the outcomes were clinically significant for some, but not all, participants. Our confidence in the quality of this evidence was very low. No self management support studies reported long-term outcomes. Delivery system design interventions These interventions did not significantly affect adherence or daily hours of hearing aid use in the short to medium term, or adverse effects in the long term. We found no studies that investigated the effect of these interventions on quality of life. There was no evidence of a statistically or clinically significant effect on hearing handicap, hearing aid benefit or the use of verbal communication strategies in the short to medium term. Our confidence in the quality of this evidence was low or very low. Long-term outcome measurement was rare. Combined self management support/delivery system design interventions We found no studies that investigated the effect of complex interventions combining components of self management support and delivery system design on adherence or adverse effects. There was no evidence of a statistically or clinically significant effect on daily hours of hearing aid use over the long term, or the short to medium term. Similarly, there was no evidence of an effect on quality of life over the long term, or short to medium term. These combined interventions reduced hearing handicap in the short to medium term (13 studies, 485 participants, standardised mean difference (SMD) -0.27, 95% CI -0.49 to -0.06). This represents a small-moderate effect size but there is no evidence of a statistically significant effect over the long term. There was evidence of a statistically, but not clinically, significant effect on long-term hearing aid benefit (two studies, 69 participants, MD 0.30, 95% CI 0.02 to 0.58 (1 to 5 scale)), but no evidence of effect over the short to medium term. There was evidence of a statistically, but not clinically, significant effect on the use of verbal communication strategies in the short term (four studies, 223 participants, MD 0.45, 95% CI 0.15 to 0.74 (0 to 5 scale)), but not the long term. Our confidence in the quality of this evidence was low or very low.We found no studies that assessed the effect of other CCM interventions (decision support, the clinical information system, community resources or health system changes). AUTHORS' CONCLUSIONS: There is some low to very low quality evidence to support the use of self management support and complex interventions combining self management support and delivery system design in adult auditory rehabilitation. However, effect sizes are small and the range of interventions that have been tested is relatively limited. Priorities for future research should be assessment of long-term outcome a year or more after the intervention, development of a core outcome set for adult auditory rehabilitation and development of study designs and outcome measures that are powered to detect incremental effects of rehabilitative healthcare system changes over and above the provision of a hearing aid.

BACKGROUND: Increased prescribing of inhaled long-acting anti-muscarinic (LAMA) and combined inhaled long-acting beta2-agonist and corticosteroid (LABA+ICS) drugs for the treatment of chronic obstructive pulmonary disease (COPD) has led to hopes of reduced hospital admissions from this disease. AIMS: To investigate the impact of rising primary care prescribing of LAMA and LABA+ICS drugs on COPD admissions. METHODS: This retrospective cohort study of general practice COPD admission and prescribing data between 2007 and 2010 comprised a representative group of 806 English general practices (population 5,264,506). Outcome measures were practice rates of COPD patient admissions and prescription costs of LAMA and LABA+ICS. General practice characteristics were based on the UK quality and outcomes framework. RESULTS: Rates of COPD admissions remained stable from 2001 to 2010. Practice-prescribing volumes of LAMA per practice patient and LABA+ICS per practice patient increased by 61 and 26%, respectively, between 2007 and 2010. Correlation between costs of LAMA and those of LABA+ICS increased year on year, and was the highest in 2010 (Pearson's r=0.68; 95% confidence interval (CI) 0.64 to 0.72). Practice COPD admission rates were positively predicted by practice-prescribing volumes of LAMA (2010: B=1.23, 95% CI 0.61 to 1.85) and of LABA+ICS (2010: B=0.32, 95% CI 0.12 to 0.52) when controlling for practice list size, COPD prevalence and deprivation. CONCLUSION: The increase in the prescribing of LAMA and LABA+ICS inhalers was not associated with the predicted fall in hospital admission rates for COPD patients. The positive correlation between high practice COPD prescribing and high practice COPD admissions was not explained.

In breast cancer patients undergoing sentinel lymph node biopsy (SLNB) analysis using one-step nucleic acid amplification (OSNA), clarity is required as to the determinants of further metastasis risk upon completion axillary lymph node dissection (ALND). This study aims to identify whether the proportion of sentinel nodes containing metastases predicts risk of further axillary disease.