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Objective: This study aimed to investigate the predictive capabilities of historical patient records to predict patient adverse outcomes such as mortality, readmission, and prolonged length of stay (PLOS). Methods: Leveraging a de-identified dataset from a tertiary care university hospital, we developed an eXplainable Artificial Intelligence (XAI) framework combining tree-based and traditional machine learning (ML) models with interpretations and statistical analysis of predictors of mortality, readmission, and PLOS. Results: Our framework demonstrated exceptional predictive performance with a notable area under the receiver operating characteristic (AUROC) of 0.9625 and an area under the precision-recall curve (AUPRC) of 0.8575 for 30-day mortality at discharge and an AUROC of 0.9545 and AUPRC of 0.8419 at admission. For the readmission and PLOS risk, the highest AUROC achieved were 0.8198 and 0.9797, respectively. The tree-based models consistently outperformed the traditional ML models in all 4 prediction tasks. The key predictors were age, derived temporal features, routine laboratory tests, and diagnostic and procedural codes. Conclusion: The study underscores the potential of leveraging medical history for enhanced hospital predictive analytics. We present an accurate and intuitive framework for early warning models that can be easily implemented in the current and developing digital health platforms to predict adverse outcomes accurately.

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Introduction Tourniquets are vital devices in orthopaedic surgery that aid in creating a bloodless field. While they reduce operative time and outcomes, improper use can lead to severe complications. The British Orthopaedic Association Standards for Trauma (BOAST) offers guidelines for safe intraoperative tourniquet usage, emphasising proper application and accurate documentation. With the push for a paperless National Health Service (NHS), orthopaedic units across the UK are transitioning to electronic patient records (EPR). In this audit, we aim to evaluate the impact of electronic patient records (EPR) implementation on tourniquet documentation and subsequent interventions to enhance guideline adherence. Methods This closed-loop audit evaluated 159 emergency trauma cases at a single UK-based district general hospital across three different cycles. The first cycle (n=50) was collected before the trust-wide adoption of an EPR system (EPIC HIVE). Upon collecting the second cycle (n=59), local intraoperative tourniquet usage results compared to BOAST were presented at a departmental audit meeting. A specialised smart phrase template was subsequently shared with the department and the results were re-audited in the third cycle (n=50). Statistical analyses were performed to compare the cycles. Results Following the introduction of the EPR, compliance with documentation standards (fully and partially adhered to) initially declined from 38.0% to 17.0%. Post-intervention, compliance increased to 62.0% (p=0.0005). Individual aspects of documentation revealed notable improvements, including increases in skin assessment pre- and post-tourniquet application (0% to 56% and 0% to 60%, respectively, p<0.0001), isolation method (0% to 60%, p<0.0001), exsanguination method (2% to 24%, p=0.0003), tourniquet pressure (39% to 76%, p=0.0001) and tourniquet time (59% to 94%, p=0.0001). Lower limb tourniquet pressures significantly decreased between audit cycles (mean: 287.06 vs mean: 265.91, p=0.007) while upper limb pressures remained relatively stable (mean: 236.67 vs mean: 236.56, p=0.993). No tourniquet-related complications were reported across all audit cycles. Conclusion While the introduction of new EPR systems may initially present challenges in upholding accurate operative records, the incorporation of specialised electronic templates and active staff engagement has shown to be instrumental in improving tourniquet safety and enhancing care standards.

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Objective: To integrate long-term daily continuous glucose monitoring (CGM) device data with electronic health records (EHR) for patients with type 1 and type 2 diabetes (T1D and T2D) in the national Veterans Affairs Healthcare System to assess real-world patterns of CGM use and the reliability of EHR-based CGM information. Research Design and Methods: This observational study used Dexcom CGM device data linked with EHR (from 2015 to 2020) for a large national cohort of patients with diabetes. We tracked the initiation and consistency of CGM use, assessed concordance of CGM use and measures of glucose control between CGM device data and EHR records, and examined results by age, ethnicity, and diabetes type. Results: The time from pharmacy release of CGM to patients to initiation of uploading CGM data to Dexcom servers averaged 3 weeks but demonstrated wide variation among individuals; importantly, this delay decreased markedly over the later years. The average daily wear time of CGM exceeded 22 h over nearly 3 years of follow-up. Patterns of CGM use were generally consistent across age, race/ethnicity groups, and diabetes type. There was strong concordance between EHR-based estimates of CGM use and Dexcom CGM wear time and between estimates of glucose control from both sources. Conclusions: The study demonstrates our ability to reliably integrate CGM devices and EHR data to provide valuable insights into CGM use patterns. The results indicate in the real-world environment that CGM is worn consistently over many years for both patients with T1D and T2D within the Veterans Affairs Healthcare System and is similar across major race/ethnic groups and age-groups.

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BACKGROUND: Medication review practices have evolved internationally in a direction in which not only physicians but also other healthcare professionals conduct medication reviews according to agreed practices. Collaborative practices have increasingly highlighted the need for electronic joint platforms where information on medication regimens and their implementation can be documented, kept updated, and shared. OBJECTIVE: The aim of this study was to harmonize the definition of medication reviews and create a unified conceptual basis for their collaborative implementation and documentation in electronic patient records (definition appellation: collaborative medication review). METHODS: The study was conducted using the Delphi consensus survey with three interprofessional expert panel rounds in September-December 2020. The consensus rate was set at 80%. Experts assessed the proposed definition of collaborative medication review based on an international and national inventory of medication review definitions. The expert panel (n = 41) involved 12 physicians, 13 pharmacists, 10 nurses, and six information management professionals. The range of response rates for the rounds was 63-88%. RESULTS: The experts commented on which of the pre-selected items (n = 75) characterizing medication reviews should be included in the definition of collaborative medication review. The items were divided into the following five themes and 51 of them reached consensus: 1) Actions included in the collaborative medication review (n = 24/24), 2) Settings where the review should be conducted (n = 5/5), 3) Situations where the review should be considered as needed and carried out (n = 10/11), 4) Prioritization of top five benefits to be achieved by the review and 5) Prioritization of top five patient groups to whom the review should be targeted. CONCLUSIONS: A strong interprofessional consensus was reached on the definition of collaborative medication review. The most challenging was to identify individual patient groups benefiting from the review.

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Background: Organisational change is an important part of development and growth. Transitioning from paper-based hospital records to electronic health records improves efficiency and patient safety by streamlining data access and reducing the risk of errors, ultimately leading to enhanced patient care and outcomes. In October 2020, a large NHS trust underwent the transition from paper notes to a fully electronic health records system. Therefore, the purpose of this study was to monitor staff morale during this organisational change; to highlight any issues arising that may impact on the smooth transition; to encourage feedback. Methods: A questionnaire was distributed to all members of the maxillofacial outpatients department on a regular basis. The qualitative responses were analysed using NVivo, following a framework analysis model. Results: The analysis generated 1319 codes, which were placed into 68 groups. The three main themes were 'Transformational Advancements in Healthcare Delivery'; 'Obstacles to Seamless EHR Integration; 'Navigating the Transition and Evolving Perceptions'. Discussion: Regular monitoring of morale and staff opinion allows for smoother transition in a large-scale organisational change. The results of this project will help future hospitals and trusts undergoing similar transitions.

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The aging global patient population with multimorbidity and concomitant polypharmacy is at increased risk for acute and chronic kidney disease, particularly with severe additional disease states or invasive surgical procedures. Because from the expertise of more than 58,600 self-reviewed medications, adverse drug reactions, drug interactions, inadequate dosing, and contraindications all proved to cause or exacerbate the worsening of renal function, we analyzed the association of an electronic patient record- and Summaries of Product Characteristics (SmPCs)-based comprehensive individual pharmacotherapy management (IPM) in the setting of 14 daily interdisciplinary patient visits with the outcome: further renal impairment with reduction of eGFR ≥ 20 mL/min (redGFR) in hospitalized trauma patients ≥ 70 years of age. The retrospective clinical study of 404 trauma patients comparing the historical control group (CG) before IPM with the IPM intervention group (IG) revealed a group-match in terms of potential confounders such as age, sex, BMI, arterial hypertension, diabetes mellitus, and injury patterns. Preexisting chronic kidney disease (CKD) > stage 2 diagnosed as eGFR < 60 mL/min/1.73 m2 on hospital admission was 42% in the CG versus 50% in the IG, although in each group only less than 50% of this was coded as an ICD diagnosis in the patients' discharge letters (19% in CG and 21% in IG). IPM revealed an absolute risk reduction in redGFR of 5.5% (11 of 199 CG patients) to 0% in the IPM visit IG, a relative risk reduction of 100%, NNT 18, indicating high efficacy of IPM and benefit in improving outcomes. There even remained an additive superimposed significant association that included patients in the IPM group before/beyond the 14 daily IPM interventions, with a relative redGFR risk reduction of 0.55 (55%) to 2.5% (5 of 204 patients), OR 0.48 [95% CI 0.438-0.538] (p < 0.001). Bacteriuria, loop diuretics, allopurinol, eGFR ≥ 60 mL/min/1.73 m2, eGFR < 60 mL/min/1.73 m2, and CKD 3b were significantly associated with redGFR; of the latter, 10.5% developed redGFR. Further multivariable regression analysis adjusting for these and established risk factors revealed an additive, superimposed IPM effect on redGFR with an OR 0.238 [95% CI 0.06-0.91], relative risk reduction of 76.2%, regression coefficient -1.437 including patients not yet visited in the IPM period. As consequences of the IPM procedure, the IG differed from the CG by a significant reduction of NSAIDs (p < 0.001), HCT (p = 0.028) and Würzburger pain drip (p < 0.001), and significantly increased prescription rate of antibiotics (p = 0.004). In conclusion, (1) more than 50% of CKD in geriatric patients was not pre-recognized and underdiagnosed, and (2) the electronic patient records-based IPM interdisciplinary networking strategy was associated with effective prevention of further periinterventional renal impairment and requires obligatory implementation in all elderly patients to urgently improve patient and drug safety.

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BACKGROUND: Epidemiological research may require linkage of information from multiple organizations. This can bring two problems: (1) the information governance desirability of linkage without sharing direct identifiers, and (2) a requirement to link databases without a common person-unique identifier. METHODS: We develop a Bayesian matching technique to solve both. We provide an open-source software implementation capable of de-identified probabilistic matching despite discrepancies, via fuzzy representations and complete mismatches, plus de-identified deterministic matching if required. We validate the technique by testing linkage between multiple medical records systems in a UK National Health Service Trust, examining the effects of decision thresholds on linkage accuracy. We report demographic factors associated with correct linkage. RESULTS: The system supports dates of birth (DOBs), forenames, surnames, three-state gender, and UK postcodes. Fuzzy representations are supported for all except gender, and there is support for additional transformations, such as accent misrepresentation, variation for multi-part surnames, and name re-ordering. Calculated log odds predicted a proband's presence in the sample database with an area under the receiver operating curve of 0.997-0.999 for non-self database comparisons. Log odds were converted to a decision via a consideration threshold θ and a leader advantage threshold δ. Defaults were chosen to penalize misidentification 20-fold versus linkage failure. By default, complete DOB mismatches were disallowed for computational efficiency. At these settings, for non-self database comparisons, the mean probability of a proband being correctly declared to be in the sample was 0.965 (range 0.931-0.994), and the misidentification rate was 0.00249 (range 0.00123-0.00429). Correct linkage was positively associated with male gender, Black or mixed ethnicity, and the presence of diagnostic codes for severe mental illnesses or other mental disorders, and negatively associated with birth year, unknown ethnicity, residential area deprivation, and presence of a pseudopostcode (e.g. indicating homelessness). Accuracy rates would be improved further if person-unique identifiers were also used, as supported by the software. Our two largest databases were linked in 44 min via an interpreted programming language. CONCLUSIONS: Fully de-identified matching with high accuracy is feasible without a person-unique identifier and appropriate software is freely available.

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Purpose: A transition from paper to Electronic Health Records has numerous benefits, including better communication and information exchange and decreased errors by medical staff. However, if managed poorly, it can result in frustration, causing errors in patient care and reduced patient-clinician interaction. Furthermore, a drop in staff morale and clinician burnout due to familiarising themselves with the technology has been mentioned in previous studies. Therefore, the aim of this project is to monitor the change in morale of staff of the Oral and Maxillofacial Department in a hospital which underwent the change in October 2020. Objectives: To observe staff morale during transition from paper to Electronic Health Records; to encourage feedback. Methods: After carrying out a Patient & Public Involvement consultation and receiving local research and development approval, a questionnaire was distributed to all members of the maxillofacial outpatients department on a regular basis. Results: On average, around 25 members responded to the questionnaire during each collection. There was a noticeable divergence in responses week on week according to job role and age, but minimal difference is noted from gender point of view after the first week. The study emphasised the position that not all members were happy with the new system but only a small minority would want to return to paper notes. Conclusion: Staff members adapt to change at different rates, which are multifactorial in nature. A change of this scale should be monitored closely to allow for a smoother transition and ensure staff burnout is minimised.

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BACKGROUND: Electronic alerts (e-alerts) for Acute Kidney Injury (AKI) have been implemented into a variety of different Electronic Health Records (EHR) systems worldwide in order to improve recognition and encourage early appropriate management of AKI. We were interested in the impact on patient safety, specialist referral and clinical management. METHODS: All patients admitted to our institution with AKI were included in the study. We studied AKI progression, dialysis dependency, length of hospital stay, emergency readmission, ICU readmission, and death, before and after the introduction of electronic alerts. The impact on prescription of high risk drugs, fluid administration, and referral to renal services was also analysed. RESULTS: After the introduction of the e-alert, progression to higher AKI stage, emergency readmission to hospital and death during admission were significantly reduced. More prescriptions were stopped for drugs that adversely affect renal function in AKI and there was a significant increase in the ICU admissions and in the number of patients having dialysis, especially in earlier stages. Longer term mortality, renal referrals, and fluid alteration did not change significantly after the AKI e-alert introduction. CONCLUSIONS: AKI e-alerts can improve clinical outcomes in hospitalised patients.

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BACKGROUND: The storage of patient records in electronic media is one of the most outstanding developments of the 21st century. This transformation in health required the teaching staff and students in nursing to adapt to this change. OBJECTIVES: To determine nurse educators' and students' views and experiences about electronic patient records. METHODS: A multiple-method approach was used in the study. The research sample consisted of 133 nurse educators and 366 nursing students from three public and three non-profit private universities in Ankara during the fall term of the 2019-2020 academic year. In the quantitative stage, data were collected with a data collection form prepared by the researcher. Data were obtained via semi-structured interviews with 14 nurse educators and 14 students at the qualitative stage. Descriptive statistics (number, percentage) were used to analyze quantitative data, and the content analysis method was used to analyze the qualitative data. RESULTS: 91 % of the nurse educators and 96.4 % of the students stated that they learned about electronic patient records through observation in a clinical setting. >70 % of the participants noted that including subject matters about electronic patient records in the nursing curriculum would be beneficial. In the qualitative phase, most nurse educators and students (n > 9) reported that they could not access the system because they did not have credentials. They stated that their experiences depended on the current users and were limited to observation; therefore, regulations regarding access to electronic patient records should be made. CONCLUSIONS: The views and experiences of the nurse educators and students about the electronic medical record system were limited to getting help from observing clinical nurses since they could not be registered users in the system. Therefore, it is recommended to expand the teaching related to electronic patient records in the nursing education program, develop educational software, and make arrangements to provide access to electronic data during clinical applications.

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Here, we illustrate the clinical and technical implementation of interoperable health data for direct care from the viewpoint of practicing clinicians using examples from primary care. Interoperability allows people involved in the provision and receipt of care to seamlessly exchange and use the coded, free text and documentary data they need to inform care decisions. The pathway toward NHS interoperability to support direct care has been long, but substantial progress has been made. GP computer systems and data-recording standards, national infrastructure and hospital trusts have come a long way on the journey to fully interoperable records. GPs can now receive and utilise laboratory data; via GP2GP, they can transfer full electronic patient records when patients move practice; share health data with other health organisations through GP Connect to support patient care; and provide patients with online access to their full GP record, a cornerstone of person-centred care. Here, we describe the effective technical assets and standards that have been developed to enable electronic patient record data to be shared reliably and securely.

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OBJECTIVES: To evaluate the effectiveness of an antimicrobial guideline for vancomycin prescribing deployed using electronic prescribing aid and web/phone-based app. To define factors associated with guideline compliance and drug levels, and to investigate if antimicrobial dosing recommendations can be refined using routinely collected electronic healthcare record data. METHODS: We used data from Oxford University Hospitals between 01-January-2016 and 01-June-2021 and multivariable regression models to investigate factors associated with dosing compliance, drug levels and acute kidney injury (AKI). RESULTS: 3767 patients received intravenous vancomycin for ≥24 h. Compliance with recommended loading and initial maintenance doses reached 84% and 70% respectively; 72% of subsequent maintenance doses were correctly adjusted. However, only 26% first and 32% subsequent levels reached the target range, and for patients with ongoing vancomycin treatment, 55-63% achieved target levels at 5 days. Drug levels were independently higher in older patients. Incidence of AKI was low (5.7%). Model estimates were used to propose updated age, weight and eGFR specific guidelines. CONCLUSION: Despite good compliance with guidelines for vancomycin dosing, the proportion of drug levels achieving the target range remained suboptimal. Routinely collected electronic data can be used at scale to inform pharmacokinetic studies and could improve vancomycin dosing.

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Electronic Patient Records (EPRs) are valuable data resources for clinical and operational research. The heterogeneity of medical software coupled with the changing data formats and long lifespan of the patient datasets stored in EPRs results in data inconsistencies that hinder operational activities and increase personnel efforts for data lookup and cleaning. This study presents an approach for automated data quality reporting that was developed and tested within a real-world hospital setting at Royal Surrey County Hospital NHS Foundation Trust in 2020. 81 data quality tests configurable via spreadsheets were defined and executed to yield standardised human-readable reports in comma-separated value format. The data evaluation and reporting routines provided manyfold improvement over existing data quality reporting mechanisms.

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Insights on end-of-life care decisions, such as do not attempt resuscitation (DNAR), vary between institutions and individual health care professionals. At the era of electronic patient records (EPR), the information of DNAR order may still be recorded in multiple locations making it difficult to find and interpret. A link to a structured web-based questionnaire was sent to all physicians and nurses working in Tampere University Hospital special responsibility area covering a catchment area of 900 000 Finns. Perceptions on DNAR order and documentation was surveyed. In total 934 subjects responded, of which 727 (77%) were nurses and 219 (23%) physicians covering all specialties. We found substantial variation in DNAR order interpretation and documentation among all health care professionals possibly causing information breakdown and compromised end-of-life care.

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INTRODUCTION: This study aims to provide insight into the prevalence of health problems and the frequency of general practitioner (GP) contacts in cohabiting partners of persons with dementia, during the year prior to the dementia diagnosis and up to 3 years after the diagnosis. METHODS: Partners of persons with dementia and a matched control group of partners of persons without dementia were identified in the routinely recorded electronic health records of 451 Dutch general practices in 2008-2015. These data were used to examine the prevalence of the partners' health problems. Differences between these partners and comparison partners in the prevalence of 16 groups of health problems (diagnostic chapters) and in the frequency of GP contacts were examined using generalized estimating equation models. RESULTS: 1,711 partners of persons with dementia and 6,201 comparison partners were included in the analyses. Social problems, more specifically problems related to the illness and/or the loss of the partner, were significantly more prevalent in partners than in comparison partners across the years (p < 0.01), as were musculoskeletal problems (p < 0.01). Respiratory and psychological problems increased over time in partners and remained stable in comparison partners. Across the years, partners contacted their GP more often than comparison partners (p < 0.01). DISCUSSION/CONCLUSION: Having a cohabiting partner with dementia has consequences for caregiver's physical and psychosocial health. The specific health problems found in this study and the increase in GP contacts might be relevant indicators of overburdening in partners of persons with dementia.

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Background: Protocols are an essential document for conducting randomised controlled trials (RCTs). However, the completeness of the information provided is often inadequate. To help improve the content of trial protocols, an international group of stakeholders published the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) Initiative in 2013. Presently, there is increasing use of cohorts and routinely collected data (RCD) for RCTs because these data have the potential to improve efficiencies by facilitating recruitment, simplifying, and reducing the cost of data collection. Reporting guidelines have been shown to improve the quality of reporting, but there is currently no specific SPIRIT guidance on protocols for trials conducted using cohorts and RCD. This protocol outlines steps for developing SPIRIT-ROUTINE, which aims to address this gap by extending the SPIRIT guidance to protocols for trials conducted using cohorts and RCD.  Methods: The development of the SPIRIT-ROUTINE extension comprises five stages. Stage 1 consists of a project launch and a meeting to finalise the membership of the steering group and scope of the extension. In Stage 2, a rapid review will be performed to identify possible modifications to the original SPIRIT 2013 checklist. Other key reporting guidelines will be reviewed to identify areas where additional items may be needed, such as the Consolidated Standards of Reporting Trials (CONSORT) extension for trials conducted using cohorts and RCD (CONSORT-ROUTINE). Stage 3 will involve an online Delphi exercise, consisting of two rounds and involving key international stakeholders to gather feedback on the preliminary checklist items. In Stage 4, a consensus meeting of the SPIRIT-ROUTINE steering group will finalise the items to include in the extension. Stage 5 will involve the publication preparation and dissemination of the final checklist.  Conclusion: The SPIRIT-ROUTINE extension will contribute to improving design of trials using cohorts and RCD and transparency of reporting.

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BACKGROUND: Secondary use of data via integrated health information technology is fundamental to many healthcare policies and processes worldwide. However, repurposing data can be problematic and little research has been undertaken into the everyday practicalities of inter-system data sharing that helps explain why this is so, especially within (as opposed to between) organisations. In response, this article reports one of the most detailed empirical examinations undertaken to date of the work involved in repurposing healthcare data for National Clinical Audits. METHODS: Fifty-four semi-structured, qualitative interviews were carried out with staff in five English National Health Service hospitals about their audit work, including 20 staff involved substantively with audit data collection. In addition, ethnographic observations took place on wards, in 'back offices' and meetings (102 h). Findings were analysed thematically and synthesised in narratives. RESULTS: Although data were available within hospital applications for secondary use in some audit fields, which could, in theory, have been auto-populated, in practice staff regularly negotiated multiple, unintegrated systems to generate audit records. This work was complex and skilful, and involved cross-checking and double data entry, often using paper forms, to assure data quality and inform quality improvements. CONCLUSIONS: If technology is to facilitate the secondary use of healthcare data, the skilled but largely hidden labour of those who collect and recontextualise those data must be recognised. Their detailed understandings of what it takes to produce high quality data in specific contexts should inform the further development of integrated systems within organisations.

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BACKGROUND: Second primary cancers (SPC) account for 18% of all cancers. We used the enhanced medical/health data mining tool ConSoRe to search aggregated data, analyze electronic patient records (EPR), and better characterize patients with SPC. METHODS: This retrospective cohort study used ConSoRe to identify EPRs from patients with SPC referred to the regional cancer center Leon Bérard from 1993 to 2017, and examined characteristics of patients with SPC, frequencies of first primary cancer (FPC) localization in the global population of patients with SPC, and time to SPC. Data set was extracted on January 1, 2018. RESULTS: Among 296,530 EPRs, we identified 157,187 patients with FPC, including 13,002 (8%) patients with SPC. Between 2000 and 2010, the rate of SPC was 34%, and 52% of SPC were identified in the last years (2010-2017). In men, main cancers were head and neck cancer, lymphoma, and prostate carcinoma accounting for 15.6%, 12.8%, and 10.5% of FPC, while the three most common SPC were head and neck cancer (13.2%), lung cancer (11.8%) and lymphoma (9.2%). In women, breast cancers, lymphoma, and skin cancers accounted for 48.8%, 8%, and 5.1% of first cancers, and for 31.1%, 7% and 6% of SPC. CONCLUSION: The data mining tool ConSoRe contributes to access to real world data, and to better characterize patients with SPC. Expanding such approach to any comprehensive center will allow a global overview of the follow-up of patients with cancer, and help to improve long-term management and adapt surveillance.

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BACKGROUND: Many women receiving substance use treatment services are mothers. Despite this, research has not proved whether substance use treatment services are addressing the specific needs of mothers. This study explored differences in sociodemographic, psychological, patterns of substance use, and treatment characteristics between mothers and women without children, and between mothers whose children were in alternative care. METHOD: The study extracted data from electronic patient records (EPRs) of women who attended South London and Maudsley (SLaM) National Health Services (NHS) Foundation Trust addiction services between 2013 and 2020 (N = 4370). RESULTS: The study identified 1730 participants (39.6%) as mothers, of whom 1340 (77.4%) had dependent children. The average number of births was 1.83 (SD = 1.0). Of the participants, 54.3% of mothers did not disclose whether their dependent child(ren) was under their care and 37.5% of mothers indicated that at least one of their child(ren) was in alternative care. Alcohol was the most reported type of substance used in the past 28 days. Mothers also highly reported suicide attempts and hospitalization due to mental health problems. Compared to women without children, mothers were more likely to be young, experience housing problems, use opioids and/or crack-cocaine in the past 28 days and experience lifetime domestic violence victimizations. Mothers were also less likely to have alcohol-related problems, experience overdose, and social isolation than women without children. CONCLUSION: The study highlights the need for substance use services to invest in approaches to improve mothers' disclosure of parenting and childcare issues. It also demonstrates that EPRs can identify key characteristics of mothers.

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BACKGROUND: The use of electronic patient records for assessing outcomes in clinical trials is a methodological strategy intended to drive faster and more cost-efficient acquisition of results. The aim of this manuscript was to outline the data collection and management considerations of a maternity and perinatal clinical trial using data from electronic patient records, exemplifying the DESiGN Trial as a case study. METHODS: The DESiGN Trial is a cluster randomised control trial assessing the effect of a complex intervention versus standard care for identifying small for gestational age foetuses. Data on maternal/perinatal characteristics and outcomes including infants admitted to neonatal care, parameters from foetal ultrasound and details of hospital activity for health-economic evaluation were collected at two time points from four types of electronic patient records held in 22 different electronic record systems at the 13 research clusters. Data were pseudonymised on site using a bespoke Microsoft Excel macro and securely transferred to the central data store. Data quality checks were undertaken. Rules for data harmonisation of the raw data were developed and a data dictionary produced, along with rules and assumptions for data linkage of the datasets. The dictionary included descriptions of the rationale and assumptions for data harmonisation and quality checks. RESULTS: Data were collected on 182,052 babies from 178,350 pregnancies in 165,397 unique women. Data availability and completeness varied across research sites; each of eight variables which were key to calculation of the primary outcome were completely missing in median 3 (range 1-4) clusters at the time of the first data download. This improved by the second data download following clarification of instructions to the research sites (each of the eight key variables were completely missing in median 1 (range 0-1) cluster at the second time point). Common data management challenges were harmonising a single variable from multiple sources and categorising free-text data, solutions were developed for this trial. CONCLUSIONS: Conduct of clinical trials which use electronic patient records for the assessment of outcomes can be time and cost-effective but still requires appropriate time and resources to maximise data quality. A difficulty for pregnancy and perinatal research in the UK is the wide variety of different systems used to collect patient data across maternity units. In this manuscript, we describe how we managed this and provide a detailed data dictionary covering the harmonisation of variable names and values that will be helpful for other researchers working with these data. TRIAL REGISTRATION: Primary registry and trial identifying number: ISRCTN 67698474 . Registered on 02/11/16.

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