Patient Identifiable Data Research Articles

Liaison psychiatry—measurement and evaluation of service types, referral patterns and outcomes (LP-MAESTRO): a protocol

IntroductionWe describe the protocol for a project that will use linkage of routinely collected NHS data to answer a question about the nature and effectiveness of liaison psychiatry services in...

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

Million Migrants study of healthcare and mortality outcomes in non-EU migrants and refugees to England: Analysis protocol for a linked population-based cohort study of 1.5 million migrants

Background: In 2017, 15.6% of the people living in England were born abroad, yet we have a limited understanding of their use of health services and subsequent health conditions. This linked population-based cohort study aims to describe the hospital-based healthcare and mortality outcomes of 1.5 million non-European Union (EU) migrants and refugees in England. Methods and analysis: We will link four data sources: first, non-EU migrant tuberculosis pre-entry screening data; second, refugee pre-entry health assessment data; third, national hospital episode statistics; and fourth, Office of National Statistics death records. Using this linked dataset, we will then generate a population-based cohort to examine hospital-based events and mortality outcomes in England between Jan 1, 2006, and Dec 31, 2017. We will compare outcomes across three groups in our analyses: 1) non-EU international migrants, 2) refugees, and 3) general population of England. Ethics and dissemination: We will obtain approval to use unconsented patient identifiable data from the Secretary of State for Health through the Confidentiality Advisory Group and the National Health Service Research Ethics Committee. After data linkage, we will destroy identifying data and undertake all analyses using the pseudonymised dataset. The results will provide policy makers and civil society with detailed information about the health needs of non-EU international migrants and refugees in England.

Million Migrants study of healthcare and mortality outcomes in non-EU migrants and refugees to England: Analysis protocol for a linked population-based cohort study of 1.5 million migrants.

Background: In 2017, 15.6% of the people living in England were born abroad, yet we have a limited understanding of their use of health services and subsequent health conditions. This linked population-based cohort study aims to describe the hospital-based healthcare and mortality outcomes of 1.5 million non-European Union (EU) migrants and refugees in England. Methods and analysis: We will link four data sources: first, non-EU migrant tuberculosis pre-entry screening data; second, refugee pre-entry health assessment data; third, national hospital episode statistics; and fourth, Office of National Statistics death records. Using this linked dataset, we will then generate a population-based cohort to examine hospital-based events and mortality outcomes in England between Jan 1, 2006, and Dec 31, 2017. We will compare outcomes across three groups in our analyses: 1) non-EU international migrants, 2) refugees, and 3) general population of England. Ethics and dissemination: We will obtain approval to use unconsented patient identifiable data from the Secretary of State for Health through the Confidentiality Advisory Group and the National Health Service Research Ethics Committee. After data linkage, we will destroy identifying data and undertake all analyses using the pseudonymised dataset. The results will provide policy makers and civil society with detailed information about the health needs of non-EU international migrants and refugees in England.

Considering Potential Unintended Consequences of Collecting Identified Patient Data to Guide Nonfatal Overdose Response

Considering Potential Unintended Consequences of Collecting Identified Patient Data to Guide Nonfatal Overdose Response

Following the crowd: patterns of crowdsourcing on Twitter among urologists.

To examine patterns of crowdsourcing on the social media platform Twitter among urologists. Urologists' public Twitter accounts were reviewed for original posts seeking clinical advice or feedback, and associated reply posts, before and after the 140-character-limit expansion in 2017. Predictors of responses to crowdsourcing requests were determined using multivariable regression. When patient data were posted, we noted whether consent was documented. A total of 276 posts in 23 crowdsourcing requests prior to character-limit expansion were analyzed. Reasons for crowdsourcing included requesting solutions to a clinical dilemma (82 posts, 30%); advice seeking about a surgical plan (77 posts, 28%); surveying colleagues' experiences with a new product (64 posts, 23%); and soliciting feedback about a proposed course of action (53 posts, 19%). Recent completion of training (as a proxy for inexperience) did not appear to disproportionately motivate crowdsourcing; authors' median time in practice was 7years, and authors practicing for ≤ 7years initiated 57% of requests. 22 (96%) crowdsourcing requests received ≥ 1 reply. Of 15 requests about a specific patient, eight included imaging, but only one cited patient consent. A second analysis of 184 posts in 17 crowdsourcing requests initiated after character-limit expansion demonstrated significantly more authors replying per request (P = 0.01), but no change in the frequency of patient-specific crowdsourcing or citation of consent. Urologists are leveraging Twitter for crowdsourcing clinical guidance and experiential knowledge. Nearly all requests were answered, suggesting low barriers to entry for novice users. Even after character-limit expansion, dissemination of potentially identifiable patient data remains a concern.

Interobserver Variation in Response Evaluation Criteria in Solid Tumors 1.1

Response Evaluation Criteria in Solid Tumors (RECIST 1.1) is the gold standard for imaging response evaluation in cancer trials. We sought to evaluate consistency of applying RECIST 1.1 between 2 conventionally trained radiologists, designated as A and B; identify reasons for variation; and reconcile these differences for future studies. The study was approved as an institutional quality check exercise. Since no identifiable patient data was collected or used, a waiver of informed consent was granted. Imaging case report forms of a concluded multicentric breast cancer trial were retrospectively reviewed. Cohen's kappa was used to rate interobserver agreement in Response Evaluation Data (target response, nontarget response, new lesions, overall response). Significant variations were reassessed by a senior radiologist to extrapolate reasons for disagreement. Methods to improve agreement were similarly ascertained. Sixty one cases with total of 82 data-pairs were evaluated (35 data-pairs in visit 5, 47 in visit 9). Both radiologists showed moderate agreement in target response (n = 82; ĸ = 0.477; 95% confidence interval [CI]: 0.314-0.640-), nontarget response (n = 82; ĸ = 0.578; 95% CI: 0.213-0.944) and overall response evaluation in both visits (n = 82; ĸ = 0.510; 95% CI: 0.344-0.676). Further assessment demonstrated "Prevalence effect" of Kappa in some cases which led to underestimation of agreement. Percent agreement of overall response was 74.39% while percent variation was 25.6%. Differences in interpreting RECIST 1.1 and in radiological image interpretation were the primary sources of variation. The commonest overall response was "Partial Response" (Rad A:45/82; Rad B:63/82). Inspite of moderate interobserver agreement, qualitative interpretation differences in some cases increased interobserver variability. Protocols such as Adjudication, to reduce easily avoidable inconsistencies are or should be a part of the Standard Operating Procedure in imaging institutions. Based on our findings, a standard checklist has been developed to help reduce the interpretation error-margin for future studies. Such check-lists may improve interobserver agreement in the preadjudication phase thereby improving quality of results and reducing adjudication per case ratio. Improving data reliability when using RECIST 1.1 will reflect in better cancer clinical trial outcomes. A checklist can be of use to imaging centers to assess and improve their own processes.

Impact on Patient Outcomes of Implementation of Ob Hemorrhage Safety Bundle With Multidisciplinary Simulations [16J

INTRODUCTION: Beaumont Hospital Dearborn Labor and Delivery unit serves a diverse population of pregnant patients, delivering 4000-4500 women annually. Approximately 40% are diagnosed as “high risk” based on medical or obstetric criteria. In 2016, we implemented a national (ACOG/SMFM) Obstetric hemorrhage safety bundle at Dearborn. Obstetric hemorrhage was defined as quantitative or estimated blood loss of 500 mL or greater, during the patient's delivery stay. We performed educational presentations to all obstetric nurses, obstetric and anesthesia physicians, CRNAs, CNMs, physician assistants and residents, as well as conducted sixteen multi-disciplinary simulations over three months to implement the safety bundle. These simulations took place from June 1 through August 31, 2016 and involved physically going through an obstetric hemorrhage scenario on labor and delivery complete with model patients, simulated blood, hemorrhage cart, and all instruments and supplies needed to conduct a hemorrhage response. All participants took a required on-line course post-test on the information presented after they completed the simulation. METHODS: This abstract represents Phase One of a two-phase study. The methods of both phases are presented here for the sake of completion. Phase One of the project evaluates the overall rates of obstetric hemorrhage diagnosed, the numbers of cases transfused, and the number of blood products used. This phase does not use identifiable patient data. The endpoint for Phase One is determination of the rates of diagnosis of postpartum hemorrhage and the rates of transfusion and blood products used expressed as percentages of deliveries. Phase Two of the project evaluates in detail all patients diagnosed with obstetric hemorrhage to assess interventions. This phase is a retrospective chart review that will involve examination of patients diagnosed with hemorrhage and de-identified patient data. The interventions include quantitative measurement of blood loss, administration of uterotonics, transfusion of blood products, and surgical interventions (e.g. insertion of Bakri Balloon, uterine curettage, laparotomy, use of uterine compressions sutures, ligation of hypogastric artery, and cesarean hysterectomy). This phase will study admission and discharge hemoglobin values, as well as rates of the above-stated interventions to assess the character and quality of the institution's response to obstetric hemorrhage. The end point for phase two is to determine which interventions were assimilated most and least effectively and if changes need to be made to our implementation of the safety bundle to optimize patient care. RESULTS: In 2016, 4212 patients were delivered at Beaumont Dearborn Hospital. Of those, 119 were diagnosed with obstetric hemorrhage (blood loss of 500 mL or greater). Implementation of the Obstetric Hemorrhage Safety bundle did not affect the rate of diagnosis of obstetric hemorrhage that averaged 2.83% (monthly range 1.12-4.02%), consistent with published national rates for obstetric hemorrhage at similar institutions. However, the number of cases meeting criteria for transfusion, expressed as a percentage of total deliveries, increased from 0.6% to 1.0% (5/1691 to 25/2521) before and after the obstetric hemorrhage simulations started in June 2016. The overall numbers of units of blood products transfused increased from 1.0% to 3.7% (10/1691 to 93/2521) prior to and after the commencement of the simulations. CONCLUSION: The percentage of patients identified as needing transfusion and the total numbers of blood products transfused increased substantially following the implementation of the obstetric hemorrhage safety bundle and the commencement of the simulations. Phase two will evaluate how well the hemorrhage protocol was adhered to and whether it impacted the morbidity and rates of more dramatic interventions such as return to operating room for additional procedures such as cesarean hysterectomy. Phase two will be used to assess if there is a need to adjust our implementation of the obstetric hemorrhage safety bundle, and if so, in which aspects.

Adoption of a novel surgical innovation into clinical practice: protocol for a qualitative systematic review examining surgeon views

IntroductionEfficient adoption of clinically effective novel surgical innovations has great potential benefits for patients. Factors affecting the adoption of surgical innovation are not well understood and proposed models of adoption...

A Framework of System Level Measures Promotes Alliancing and System Integration

Introduction: The New Zealand health system is organised by 20 District Health Boards (DHB) and 30 Primary Healthcare Organisations (PHO). In 2012, every DHB was required to enter into a district alliance with the PHOs serving their resident population. The NZ Ministry of Health has co-designed with health sector clinicians, analysts and managers a framework of System Level Measures (SLM) for continuous quality improvement and system integration. Method: Basic underlying principles for SLM were established to determine selection, principally that they were outcomes with a clear focus on health equity. Data had to be available, feasible and timely. Using a collaborative approach engaging Ministry of Health and sector clinicians, data analysts and managers, and consumers a set of six measures has been implemented: ASH rates in 0-4 year old children; Proportion of babies living in a smoke-free home; Patient experience of care; Acute hospital bed days per capita; Amenable mortality; and a Youth Health composite SLM. The SLMs are underpinned by a large set of contributory measures of health processes and activities. A measures library was established as a repository of data definitions and sources in order to standardise measurement nationally and allow comparative analysis. The Ministry of Health has made patient identifiable data held in national collections available down to practice level via secure servers, for local managers and clinicians to use for quality improvement. Each district alliance is required to develop a quality improvement plan based on their analysis of local data on SLM, service configuration and the needs of their local population. The alliance must set an improvement milestone for each SLM and detail the improvement activities it will implement using improvement science methodology. The plan also details the contributory measures that will be used to track local progress and contains signatures of all parties in the alliance. The Ministry of Health releases funding to PHOs for capacity and capability development as seed funding and on approval of the plans. A small incentive funding pool is applied to achievement of SLM milestones. Results: In the first year of implementation, all twenty district alliances submitted a plan by the due date setting improvement milestones for four SLMs. The framework stimulated primary and secondary care clinicians, PHO senior managers and DHB chairs to collaborate on quality improvement. The Ministry gained knowledge about the maturity of alliances and their capability and capacity for improvement science methodology and analytics. This was found highly variable between districts. In the second year, two developmental SLMs were added and the quality of plans improved. Conclusion: New Zealand has developed and implemented a framework of system level health outcome measures to stimulate alliances between primary healthcare and secondary care to engage in quality improvement activities taking a co-design and patient-centred approach. Early indications are promising that the framework can deliver improved outcomes both for the system and the patients.

Leveraging the electronic health record (EHR) to support survivorship care planning for bone marrow transplant (BMT) survivors.

57 Background: BMT survivors are underrepresented in survivorship research, yet are at high risk for complications. Practice guidelines are vague, non-BMT clinicians are inadequately informed, and communication between BMT and non-BMT clinicians is inconsistent. Our objective is to develop EHR-integrated survivorship care planning that is user-centered, supports non-BMT clinician and survivor needs, but does not adversely impact clinical workflow. Methods: A multidisciplinary team of clinicians (primary care, oncology, BMT), engineers, and EHR analysts used a systems engineering approach to identify barriers and facilitators to BMT survivorship care planning. The team identified patient data categories to include in BMT survivorship care plan (SCP) templates, as well as examined tasks, technology, workflows and individual roles and responsibilities necessary to support care planning. Results: Facilitators include: potential for EHR to discretely capture individual diagnosis and treatment data to create accurate SCPs addressing survivor and primary care information needs. Barriers are: lack of EHR inter-operability which prevents sharing of patient data outside the BMT center’s EHR system, reliance on manual entry of critical data elements into the SCP (i.e. majority of the 88 patient data categories, identified by the team, are non-discrete in the EHR), inefficient or absent survivorship workflows, lack of resources (including time, dedicated clinical staff, space, SCP content), poorly defined roles and responsibilities for survivorship care provision, and lack of evidence-based BMT survivorship guidelines. Conclusions: Work system barriers impede use of the EHR to support survivorship care planning. Steps to overcome barriers: design discrete fields in the EHR to support patient-level data capture, re-engineer existing workflows to support survivorship care planning, obtain BMT program consensus on SCP content, and evaluate user-centeredness of SCPs. This research has the potential to improve feasibility and sustainability of survivorship care planning activities, resulting in improved communication and care coordination for BMT survivors.

Operating Theatre Mannerisms & Etiquette: Revisited!

Operating Theatre Mannerisms & Etiquette: Revisited!

Perioperative experiences of anesthesia reported by children and parents.

The Sprint National Anaesthesia Project reported feedback from adults but not from children. We developed questionnaires for children and parents, and conducted a survey of perioperative anesthetic experiences in a large pediatric hospital. Patients undergoing elective general anesthesia were selected randomly each weekday over 10weeks. Parents and children were approached within 4hours after awakening, and were asked to complete a short questionnaire. Personal or patient identifiable data were not collected. Questionnaires were processed by optical mark reading technology and descriptive data analysis was performed. Seven hundred and forty parents and 250 children completed questionnaires. The most common symptoms reported by parents were thirst and hunger (76%), drowsiness (75%), sore throat (41%), and pain of the surgery (38%). Sixty-four percent of children felt worried or scared about something before the procedure: common worries were about the "anesthetic," "procedure," or "needles/cannula." Fifty-five percent reported postoperative pain. Thirty-nine children (15.6%) remembered something between going to sleep and waking up although distress was not reported; of these, the most common experiences remembered included hearing voices (34%), feeling sore (20%), and being worried (14%). Twenty-two parents (2.9%) had any complaint and most were about fasting instructions. Only 3 parents would not recommend the anesthetic service. This study shows that the experiences of children and their parents are similar to those of adults reported by the Sprint National Anaesthesia Project. Thirst (and hunger), anxiety, and pain continue to be common problems for many children. This feedback may help direct interventions and research to improve the pediatric patient and parent experience with anesthesia.

Innovative Solutions for Clinical Trial Follow-up: Adding Value from Nationally Held UK Data

Clinical trials provide the data that underpin evidence-based oncological practice. Over and above their primary outcome measures, collected and analysed by the clinical trials unit, trials provide an opportunity to generate a wide range of additional information over a prolonged period of time. Nationally held data have potential to facilitate longer term follow-up and explore associated toxicities and downstream consequences and in the UK include data from secondary care, including hospital episode statistics, national chemotherapy and radiotherapy datasets and primary care records. Specific to use in oncological practice, the National Cancer Data Repository contains linked data from a variety of sources for patients with a diagnosis of cancer, both cancer and non-cancer related. The challenge of using these data in clinical trials relates to the need to extract identifiable patient data, with the associated ethical and legal issues. The data access processes are time consuming and require evidence of information governance compliance.This overview article reviews the current data available, the current and potential uses both within and outside clinical trials and the challenges encountered in the process of acquiring data. We focus specifically on the use of nationally held data for non-cancer outcomes, including toxicity and associated conditions.

Enabling honest reflection: a review.

Reflective practice provides a backbone to professionalism, a commitment to lifelong learning and competency-based education in the form of reflective portfolios. Changes in health care culture have promoted a move towards openness and reflection on challenging clinical encounters. Engagement with reflection has historically proved challenging to clinical educators. This Faculty Development Review examines this using a case study from the UK in which a postgraduate trainee was asked to disclose their reflective portfolio by a patient's legal representation. Critics have consequently questioned whether the educational benefit of reflection warrants these potential legal implications. In the context of pressure from accrediting bodies to demonstrate evidence of reflection, how can learners face this potential conflict of professional versus legal repercussions? We combine professional guidance from the UK and educational rationale from international settings to produce a guide for good practice. We offer guidance on facilitating reflection for learners in an open and honest way without diluting educationally effective critical reflection. Themes of anonymity, taking a balanced approach, seeking senior advice, focusing on learning outcomes and role-modelling are discussed. How can learners face this potential conflict of professional versus legal repercussions? Integrating reflection within the curriculum improves engagement and is key to experiential learning. Clinical educators should be aware of legal and professional guidance applicable to their own context. Both educators and learners should be aware that written reflection is an educational not a clinical tool, and so requires little or no patient-identifiable data, thereby ensuring safer reflective practice.

SNAP-2 EPICCS: the second Sprint National Anaesthesia Project—EPIdemiology of Critical Care after Surgery: protocol for an international observational cohort study

IntroductionThe admission of high-risk patients to critical care after surgery is a recommended standard of care. Nevertheless, poor compliance against this recommendation has been repeatedly demonstrated in large epidemiological studies....

Methods, applications, interpretations and challenges of interrupted time series (ITS) data: protocol for a scoping review

ObjectivesInterrupted time series (ITS) design involves collecting data across multiple time points before and after the implementation of an intervention to assess the effect of the intervention on an outcome....

Associations between interarm differences in blood pressure and cardiovascular disease outcomes: protocol for an individual patient data meta-analysis and development of a prognostic algorithm

IntroductionIndividual cohort studies in various populations and study-level meta-analyses have shown interarm differences (IAD) in blood pressure to be associated with increased cardiovascular and all-cause mortality. However, key questions remain,...

Infrastructure and distributed learning methodology for privacy-preserving multi-centric rapid learning health care: euroCAT

Machine learning applications for personalized medicine are highly dependent on access to sufficient data. For personalized radiation oncology, datasets representing the variation in the entire cancer patient population need to be acquired and used to learn prediction models. Ethical and legal boundaries to ensure data privacy hamper collaboration between research institutes. We hypothesize that data sharing is possible without identifiable patient data leaving the radiation clinics and that building machine learning applications on distributed datasets is feasible.We developed and implemented an IT infrastructure in five radiation clinics across three countries (Belgium, Germany, and The Netherlands). We present here a proof-of-principle for future ‘big data’ infrastructures and distributed learning studies. Lung cancer patient data was collected in all five locations and stored in local databases. Exemplary support vector machine (SVM) models were learned using the Alternating Direction Method of Multipliers (ADMM) from the distributed databases to predict post-radiotherapy dyspnea grade ⩾2. The discriminative performance was assessed by the area under the curve (AUC) in a five-fold cross-validation (learning on four sites and validating on the fifth). The performance of the distributed learning algorithm was compared to centralized learning where datasets of all institutes are jointly analyzed.The euroCAT infrastructure has been successfully implemented in five radiation clinics across three countries. SVM models can be learned on data distributed over all five clinics. Furthermore, the infrastructure provides a general framework to execute learning algorithms on distributed data. The ongoing expansion of the euroCAT network will facilitate machine learning in radiation oncology. The resulting access to larger datasets with sufficient variation will pave the way for generalizable prediction models and personalized medicine.

Experience of living with cancer and comorbid illness: protocol for a qualitative systematic review

IntroductionThere are an increasing number of people living with and beyond cancer, whose experience is further complicated by additional long-term health conditions in the context of an ageing population. The...