Standard pediatric oncology data and information technology: necessities for cancer care management

Abstract Cancer is the second leading cause of death in children and survivors require life time follow-up. There is a growing recognition of the need to base cancer control policies on accurate, detailed and timely information on cancer management and outcomes. Coordination and central documentation ensure quality of treatment and permit clinical and scientific investigations. The combined data thus obtained create a comprehensive picture of disease, leading to more effective prevention and cure. Medical information can be gathered, processed and analyzed in different ways and the importance of precise language cannot be overestimated. All medical activity arises from the ability to observe and communicate intelligibly and a lack of standardized documentation leads to insufficient integration of clinical work. The Minimal Standard data set is the result of a global effort to establish a common structure and vocabulary for electronic reports. In addition, information technology combines research aspects of decision support and clinical documentation, allowing formal representation of general protocols, calculating of a particular therapy for a patient, data acquisition in the clinics. Our aim in this papers is to stress the need for standard pediatric oncology data and information technology as an approach to cancer care management

Clinical governance: striking a balance between checking and trusting

Clinical governance emerged as one of the big ideas central to the latest round of health reforms. It places with health care managers, for the first time, a statutory duty for quality of care on an equal footing with the pre-existing duty of financial responsibility (Warden 1998). Clinical governance tries to encourage an appropriate emphasis on the quality of clinical services by locating the responsibility for that quality along defined lines of accountability. This paper explores some of the implications of clinical governance using the economic perspective of principal-agent theory. It examines the ways in which principals seek to overcome the potential for agent opportunism either by reducing asymmetries of information (for example, by using performance data) or by aligning objective functions (for example, by creation of a shared quality culture). As trust and mutuality (or their absence) underpin all principal-agent relationships these issues lie at the heart of the discussion. The analysis emphasises the need for a balance between techniques that seek to compel performance improvements (through externally applied measurement and management), and approaches that trust to intrinsic professional motivation to deliver high quality services. Of crucial importance in achieving this balance is the creation and maintenance of the right organisational culture.governance

Predictive analytics for hospital discharge flow determination

In recent years, hospitals around the world are faced with large patient flows, which negatively affect the quality of patient care and become a crucial factor to consider in inpatient management. The main objective of this management is to maximize the number of available beds, using efficient planning. Intensive Care Units (ICU) are hospital units with a higher monetary consumption, and the importance of indicators that allow the achievement of useful information for a correct management is critical. This study allowed the prediction of the Length of Stay (LOS) based on their demographic data, information collected at the time of admission and clinical conditions, which can help health professionals in conducting a more assertive planning and a better quality service. The results obtained show that Machine Learning (ML) models, using demographic information simultaneously with the patient's pathway, as well as clinical data, drugs, tests and analysis, introduce a greater predictive ability for LOS.FCT -Fundação para a Ciência e a Tecnologia(DSAIPA/DS/0084/2018

Identifying barriers and facilitators to improving prehospital care of asthma: views of ambulance clinicians

Background: In 2008/09 there were nearly 80,000 emergency hospital admissions for asthma. Current UK guidelines emphasise the importance of evidence-based prehospital assessment and treatment of asthma for improving patient outcomes and reducing hospitalisation, morbidity and mortality. National benchmarking of ambulance clinical performance indicators for asthma has revealed important unexplained variations in care across ambulance services. Little research has been undertaken to understand the reasons for poor levels of care. Objective: The aim of this study was to gather data on ambulance clinicians’ perceptions and beliefs around prevailing and best practice for management of asthma. This was used to identify the factors which prevent or enable better asthma care in ambulance services. Methods: We used a phenomenological qualitative approach, which addresses how individuals use their experiences to make sense of their world, focusing on participants’ lived experiences of care delivery for asthma. We used focus groups of ambulance clinicians to gather data on barriers and facilitators to better asthma care. Recordings and notes were taken, transcribed and then analysed using QSR NVivo 8. A coding framework was developed based on a priori concepts but with emergent themes added during the analysis. Results: Two focus groups were conducted with eight and five participants respectively. A number of preliminary themes and subthemes were identified. The study identified issues relating to clarity of ambulance guidelines, conflicts between training and guidance, misconceptions about the importance of objective assessment and over reliance on non-objective assessment. Some practitioners believed that hospital staff were not interested in prehospital peak flow assessments. Conclusion: Our findings will inform improved systems of care for asthma and the effect on indicators will be measured using time series methods. This approach could be used more widely to improve management of specific clinical conditions where quality of care is demonstrated to be suboptimal

A systematic review of quality components of patients’ medical record in Iranian Hospital

Background: Quality of patients’ medical records is important in patient management, safety, decision making and continuation of care. Patients’ medical record data are also used in clinical research, health system services and management, medical forensic management, quality improvement, health care financial management, and risk management. Objective: The aims of the study were to determine the quality of the components of hospital patients’ medical records. Methods: The criteria selected for systematic searching were published articles in English from 1995 to 2014 for patient medical record quality components. The search terms were hospital patient medical record, reliability, accuracy, completeness, availability and accessibility. The study was carried out from 2013 to 2014 using public domain databases which include PubMed, Cochrane and CINHAL. Results: Over 2600 citations from the databases were extracted. Based on the criteria of the study 344 articles were selected for review. Subsequently, 7 articles were selected for reliability, 11 for accuracy, 18 for completeness and 9 for availability and accessibility. These articles were subjected to an in-depth review. Reliability of data in patients’ medical record is a requisite for accuracy and completeness of clinical data. The reliability scores of the studies reviewed ranged from 49% to 99%, while accuracy of patients’ medical record ranged from 73% to 95%. The reviewed studies also showed completeness of patients’ medical record ranging from 41.5% to 93%, while availability and accessibility scores ranged from 58% to 94.3%. Conclusion: This review had contributed to a better understanding of the quality of patients’ medical record. Reliability, accuracy, completeness and accessibility of patient medical record showed a wide range of quality of patients’ medical record. Good quality of patients’ medical record is essential for patient care and through preventing medical error. This review also revealed the importance of intervention to improve quality of patient medical record

METRICS FOR LEVERAGING MORE IN CLINICAL DATA MANAGEMENT: PROOF OF CONCEPT IN THE CONTEXT OF VACCINE TRIALS IN AN INDIAN PHARMACEUTICAL COMPANY

The clinical trials data is of critical importance in providing evidence to support a drug or biologic product efficacy and safety. Quality data, productivityand lower product costs are key considerations in drug development process and to maintain competitive edge.  Clinical Data Management(CDM) is a multistage process where various activities must be considered and decision taken in synergy and not sequentially; planned and executed according to the GCP (Good Clinical Practices) guidelines with highest standards.  During the course of development, implementation and standardization of CDM procedures in the context of vaccine trialsin an Indian pharmaceutical company, it emerged that multi-factormetrics based performancemonitoring of critical procedural stepshave synergistic impact in boosting overall in-time progression of the projectand meeting desired data quality.It is important to acknowledge domain knowledge in developing performance metrics by involvingmembers of cross-functional teams. This report summarizes possible methodologies which if adopted are likely to keep the team members updated with the project advancement. The proof of concept, createdin the form of metrics designed to drive performance improvement through appropriate levels of internal controls and characterizing progress made under each criteria, is expected to improve overall productivity by accomplishing the aim with desired quality and within stipulated time-frameby mitigating the errors.Key-words:Clinical Data Management (CDM), Indian Good Clinical Practices(GCP), CDM Metric

Big Data in Studying Acute Pain and Regional Anesthesia

The digital transformation of healthcare is advancing, leading to an increasing availability of clinical data for research. Perioperative big data initiatives were established to monitor treatment quality and benchmark outcomes. However, big data analyses have long exceeded the status of pure quality surveillance instruments. Large retrospective studies nowadays often represent the first approach to new questions in clinical research and pave the way for more expensive and resource intensive prospective trials. As a consequence, the utilization of big data in acute pain and regional anesthesia research has considerably increased over the last decade. Multicentric clinical registries and administrative databases (e.g., healthcare claims databases) have collected millions of cases until today, on which basis several important research questions were approached. In acute pain research, big data was used to assess postoperative pain outcomes, opioid utilization, and the efficiency of multimodal pain management strategies. In regional anesthesia, adverse events and potential benefits of regional anesthesia on postoperative morbidity and mortality were evaluated. This article provides a narrative review on the growing importance of big data for research in acute postoperative pain and regional anesthesia

Application of Multiple imputation in Analysis of missing data in a study of Health-related quality of life

When a new treatment has similar efficacy compared to standard therapy in medical or social studies, the health-related quality of life (HRQL) becomes the main concern of health care professionals and can be the basis for making a decision in patient management. National Surgical Adjuvant Breast and Bowel Protocol (NSABP) C-06 clinical trial compared two therapies: intravenous (IV) fluorouracil (FU) plus Leucovorin (LV) and oral uracil/ftorafur (UFT) plus LV, in treatment of colon cancer. However, there was a high proportion of missing values among the HRQL measurements that only 481 (59.8%) UFT patients and 421 (52.4%) FU patients submitted the forms at all time points. Ignoring the missing data issue often leads to inefficient and sometime biased estimates. The primary objective of this thesis is to evaluate the impact of missing data on the estimated the treatment effect. In this thesis, we analyzed the HRQL data with missing values by multiple imputation. Both model-based and nearest neighborhood hot-deck imputation methods were applied. Confidence intervals for the estimated treatment effect were generated based on the pooled imputation analysis. The results based on multiple imputation indicated that missing data did not introduce major bias in the earlier analyses. However, multiple imputation was worthwhile since the most estimation from the imputation datasets are more efficient than that from incomplete data. These findings have public health importance: they have implications for development of health policies and planning interventions to improve the health related quality of life for those patients with colon cancer

CLINICIAN’S VIEW ON THE IMPORTANCE OF RADIOLOGY REPORT IN THEIR DAILY PRACTICE

Bacground: A radiology report is a medicolegal document and formal communication between a radiology radiologist and referring physician/clinician. The failure of radiologists to communicate good quality reports often occurs in the process of patient diagnosis. This study aims to determine the clinician’s view on the importance of radiology reports in patient management of their daily practice in Papua and West Papua. Method: One hundred and eighty-four general practitioners and internship doctors answered an online questionnaire distributed randomly. Forty-five indicators assessed the accessibility to radiology reports, the importance of radiology reports, attached clinical information, clinician satisfaction, structure, and content of radiology reports. This study has seven variables with six paths tested using the Structural Equation Modeling (PLS-SEM) analysis method based on Partial Least Squares based using SmartPLS. Result: Data analysis showed that radiology reports, clinical information, clinician satisfaction, and structure of radiology reports had a positive and significant effect on patient management, while accessibility and content of radiology reports had no significant effect on patient management. Conclusion: Clinicians thought the radiology report was an important medical document that has a role in patient management of their daily practice

Use of Novel Strategies to Develop Guidelines for Management of Pyogenic Osteomyelitis in Adults: A WikiGuidelines Group Consensus Statement.

Importance Traditional approaches to practice guidelines frequently result in dissociation between strength of recommendation and quality of evidence. Objective To construct a clinical guideline for pyogenic osteomyelitis management, with a new standard of evidence to resolve the gap between strength of recommendation and quality of evidence, through the use of a novel open access approach utilizing social media tools. Evidence Review This consensus statement and systematic review study used a novel approach from the WikiGuidelines Group, an open access collaborative research project, to construct clinical guidelines for pyogenic osteomyelitis. In June 2021 and February 2022, authors recruited via social media conducted multiple PubMed literature searches, including all years and languages, regarding osteomyelitis management; criteria for article quality and inclusion were specified in the group's charter. The GRADE system for evaluating evidence was not used based on previously published concerns regarding the potential dissociation between strength of recommendation and quality of evidence. Instead, the charter required that clear recommendations be made only when reproducible, prospective, controlled studies provided hypothesis-confirming evidence. In the absence of such data, clinical reviews were drafted to discuss pros and cons of care choices. Both clear recommendations and clinical reviews were planned with the intention to be regularly updated as new data become available. Findings Sixty-three participants with diverse expertise from 8 countries developed the group's charter and its first guideline on pyogenic osteomyelitis. These participants included both nonacademic and academic physicians and pharmacists specializing in general internal medicine or hospital medicine, infectious diseases, orthopedic surgery, pharmacology, and medical microbiology. Of the 7 questions addressed in the guideline, 2 clear recommendations were offered for the use of oral antibiotic therapy and the duration of therapy. In addition, 5 clinical reviews were authored addressing diagnosis, approaches to osteomyelitis underlying a pressure ulcer, timing for the administration of empirical therapy, specific antimicrobial options (including empirical regimens, use of antimicrobials targeting resistant pathogens, the role of bone penetration, and the use of rifampin as adjunctive therapy), and the role of biomarkers and imaging to assess responses to therapy. Conclusions and Relevance The WikiGuidelines approach offers a novel methodology for clinical guideline development that precludes recommendations based on low-quality data or opinion. The primary limitation is the need for more rigorous clinical investigations, enabling additional clear recommendations for clinical questions currently unresolved by high-quality data