[Management System of Implantable Medical Device in Accordance with JCI Standard Based on HRP System].

JCI standard is the most professional and authoritative certification standard of medical quality and safety system in the world. HRP information system is a systematic hospital resource management platform which integrates the existing hospital information resources and establishes a set of unified, efficient, interconnected and information sharing operation and management of the hospital. In order to meet the requirements of closed-loop management of implantable medical devices in the JCI standard, our hospital has established a set of standards which based on the HRP system platform, including access permission, purchase application, entering and leaving the warehouse, bookkeeping charge, cost accounting and postoperative traceability of implanted medical device management system. HRP system improves the management level of implantable medical devices, and realizes the closed-loop management of the whole process of implantable medical devices.

Human resource technology disruptions and their implications for human resources management in healthcare organizations.

Concern among the public and policymakers about current and future major staff shortages is increasing. Strengthening Human Resource (HR) practices and adopting HR technologies such as Human Resource Information Systems (HRIS), that can collect, store and report workforce data are often described as a potential solution to this problem. Indeed, examples from other industries show that HRIS can help to launch or manage, as well as provide ongoing insights concerning the whole career cycle of an employee. However, few of the existing studies that discuss technology or its impacts on the future of work have focused on health organizations, and those that do have not received sufficient attention in health literature. Furthermore, such contributions as there have been have either prioritized a particular type of technology or focused mainly on the effect of automation on health professionals' work. They have thus overlooked the full range of possible uses of these technologies and, specifically, have neglected the topic of HR for Health (HRH) management in health organizations. The primary aim of this paper is to address this lacuna, with specific reference to the existing categorization of HR technological disruptions. To conclude, health organizations and the health and HR professionals who work within them need to use HRIS responsibly, finding a balance between the drive for innovation, productivity and efficiency and respect for all potential legal, ethical and compliance issues, as well as taking account of the importance of HRH wellbeing and satisfaction.

'Fit-for-purpose?' - challenges and opportunities for applications of blockchain technology in the future of healthcare.

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin - the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as 'revolutionary' and 'disruptive', is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is 'fit-for-purpose' is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

Characterization of the Selective Recording of Workplace Exposure Measurements into OSHA's IMIS Databank.

Objectives: The Integrated Management Information System (IMIS) is the largest multi-industry source of exposure results available in North America. In 2010, the Occupational Safety and Health Administration (OSHA) released the Chemical Exposure Health Data (CEHD) that contains analytical results of samples collected by OSHA inspectors. However, the two databanks only partially overlap, raising suspicion of bias in IMIS data. We investigated the factors associated with selective recording of CEHD results into the IMIS databank. Methods: This analysis was based on personal exposure measurements of 24 agents from 1984 to 2009. The association between nine variables (level of exposure coded as detected versus non-detected (ND), whether a sampling result was part of a panel of chemicals, duration of sampling, issuance of a citation, presence of other detected levels during the same inspection, year, OSHA region, amount of penalty, and establishment size) and a CEHD sampling result being reported in IMIS was analyzed using modified Poisson regression. Results: A total of 461900 CEHD sampling results were examined. The proportion of CEHD sampling results recorded into IMIS was 38% (51% for detected and 28% for ND measurements). In the models, the detected sampling results were associated with a higher probability of recording into IMIS than ND sampling results, and this difference was similar for panel versus non-panel samples. Probability of recording remained constant from 1984 to 2009 for sampling results measured on panels but increased for sampling results of single determinations of an agent. Some OSHA regions had probability of recording two times higher than others. No other variables that we examined were associated with a CEHD sampling result being reported in IMIS. Conclusions: Our results indicate that the under-reporting of sampling results in IMIS is differential: ND results (especially those determined from the panels) seem less likely to be recorded in IMIS than other results. It is important to consider both IMIS and CEHD data in order to reduce bias in evaluation of exposures in workplaces inspected by OSHA.

Upgrading Supply Chain Management Systems to Improve Availability of Medicines in Tanzania: Evaluation of Performance and Cost Effects.

BACKGROUND: To address challenges in public health supply chain performance, Tanzania invested in a national logistics management unit (LMU) and a national electronic logistics management information system (eLMIS). This evaluation examined the impact of those 2 key management upgrades approximately 1 year after they were introduced. METHODS: We used a nonexperimental pre-post study design to compare the previous system with the upgraded management system. We collected baseline data from August to November 2013. We conducted round 1 of post-implementation data collection during April and May 2015, about 1 year after implementation of the upgrades. We evaluated key indicators of data use and reporting; supply chain management practices such as storage and supervision; supply chain performance including stock-out and expiry rates; and supply chain cost and savings. We analyzed the data using a range of techniques including statistical testing of baseline and round-1 results, and cost, cost-effectiveness, and return on investment analysis. RESULTS: The upgrades were associated with improvements in data use, accessibility, visibility, and transparency; planning, control, and monitoring; support for quantification; stock-out rates; stock-out duration; commodity expiry; and forecast error. The upgraded system was more costly, but it was also more efficient, particularly when adjusting for the performance improvements. The upgrades also generated substantial savings that defrayed some, but not all, of the investment costs. CONCLUSION: Upgrades to Tanzania's supply chain management systems created multiple and complex pathways to impact. One year after implementation, the LMU and eLMIS brought about performance improvements through better data use and through improvements in some, but not all, management practices. Furthermore, the upgrades-while not inexpensive-contributed to greater system efficiency and modest savings.

Quantitative metrics for evaluating the phased roll-out of clinical information systems.

OBJECTIVES: We introduce a novel quantitative approach for evaluating the order of roll-out during phased introduction of clinical information systems. Such roll-outs are associated with unavoidable risk due to patients transferring between clinical areas using both the old and new systems. METHODS: We proposed a simple graphical model of patient flow through a hospital. Using a simple instance of the model, we showed how a roll-out order can be generated by minimising the flow of patients from the new system to the old system. RESULTS: The model was applied to admission and discharge data acquired from 37,080 patient journeys at the Churchill Hospital, Oxford between April 2013 and April 2014. The resulting order was evaluated empirically and produced acceptable orders. DISCUSSION: The development of data-driven approaches to clinical Information system roll-out provides insights that may not necessarily be ascertained through clinical judgment alone. Such methods could make a significant contribution to the smooth running of an organisation during the roll-out of a potentially disruptive technology. CONCLUSION: Unlike previous approaches, which are based on clinical opinion, the approach described here quantitatively assesses the appropriateness of competing roll-out strategies. The data-driven approach was shown to produce strategies that matched clinical intuition and provides a flexible framework that may be used to plan and monitor Clinical Information System roll-out.

Placenta, cord and membranes: a dual center validation study of midwives' classifications and notifications to the Medical Birth Registry of Norway.

INTRODUCTION: A validation of data regarding the placenta, cord and membranes in Medical Birth Registry of Norway (MBRN) is lacking. Here we investigate the inter- and intra-observer agreement of observations regarding the placenta, cord and membranes to the MBRN in two institutions. MATERIAL AND METHODS: We conducted a dual center validation study of data regarding placenta, cord and membranes. In the inter-observer study, 196 placentas in two institutions were examined by the attending midwife and a blinded colleague, whereas in the intra-observer study registrations by the attending midwife on 195 placentas were compared with her own registrations to the MBRN. In a separate sample consisting of 51 placental pathology reports, midwives' registrations to the MBRN were compared with the pathology report. For categorical and continuous variables, agreement was assessed by kappa value and paired sample t-test, respectively. RESULTS: Inter-observer agreement between two midwives for cord insertion site and bi-placenta, cord knots and vessel anomalies were good (kappa values >0.79 and >0.96, respectively). The inter- and intra-observer study showed no significant differences regarding placental weight and cord length (p = 0.31 and 0.28, p = 0.71 and 0.39, respectively). The inter-observer agreement between the pathology reports and midwives' registrations was good for gross placental and cord variants (kappa 0.73-1.0), but there were significant differences in placental weight and cord length (p < 0.0001). CONCLUSIONS: The results suggest that the validity of data regarding placenta and cord in the MBRN is sufficiently high to justify future large-scale epidemiologic research based on this database.

Web Validation Service for Ensuring Adherence to the DICOM Standard.

The DICOM Standard has been fundamental for ensuring the interoperability of Picture Archive and Communications Systems (PACS). By compiling rigorously to the standard, medical imaging equipment and applications from different vendors can share their data, and create integrated workflows which contributes to better quality healthcare services. However, DICOM is a complex, flexible and very extensive standard. Thus, it is difficult to attest the conformity of data structures produced by DICOM applications resulting in unexpected behaviors, errors and malfunctions. Those situations may be critical for regular PACS operation, resulting in serious losses to the healthcare enterprise. Therefore, it is of paramount importance that application vendors and PACS administrators are confident that their applications follow the standard correctly. In this regard, we propose a method for validating the compliance of PACS application with the DICOM Standard. It can capture the intricate dependency structure of DICOM modules and data elements using a relatively simple description language. The modular nature of our method allows describing each DICOM module, their attributes, and dependencies on a re-usable basis. As a result, our validator is able to encompass the numerous modules present in DICOM, as well as keep up with the emergence of new ones.

[The current state-of-the-art of the expert evaluation of medical documentation pertaining to the cases of death from an injury inflicted in a healthcare facility in the late; post-traumatic period].

This article presents a concise review of the literature data concerning the modern methods for the expert evaluation of medical documentation as an object of forensic medical examination. The authors lay special emphasis on the practical significance of this issue for the scientifically sound substantiation of the results of forensic medical expertise carried out for the elucidation of the causes of death and the relationship between the injury and the outcome of the medical aid provided for its treatment. The expert evaluation of medical documentation is equally important for the assessment of the harm to health and the cause of death as a consequence of a thermal and/or mechanical injury inflicted during the hospital stay and in the late post-traumatic period.

Quality of Health Management Information System for Maternal & Child Health Care in Haryana State, India.

BACKGROUND: Despite increasing importance being laid on use of routine data for decision making in India, it has frequently been reported to be riddled with problems. Evidence suggests lack of quality in the health management information system (HMIS), however there is no robust analysis to assess the extent of its inaccuracy. We aim to bridge this gap in evidence by assessing the extent of completeness and quality of HMIS in Haryana state of India. METHODS: Data on utilization of key maternal and child health (MCH) services were collected using a cross-sectional household survey from 4807 women in 209 Sub-Centre (SC) areas across all 21 districts of Haryana state. Information for same services was also recorded from HMIS records maintained by auxiliary nurse midwives (ANMs) at SCs to check under- or over-recording (Level 1 discordance). Data on utilisation of MCH services from SC ANM records, for a subset of the total women covered in the household survey, were also collected and compared with monthly reports submitted by ANMs to assess over-reporting while report preparation (Level 2 discordance) to paint the complete picture for quality and completeness of routine HMIS. RESULTS: Completeness of ANM records for various MCH services ranged from 73% for DPT1 vaccination dates to 94.6% for dates of delivery. Average completeness level for information recorded in HMIS was 88.5%. Extent of Level 1 discordance for iron-folic acid (IFA) supplementation, 3 or more ante-natal care (ANC) visits and 2 Tetanus toxoid (TT) injections was 41%, 16% and 2% respectively. In 48.2% cases, respondents from community as well as HMIS records reported at least one post-natal care (PNC) home visit by ANM. Extent of Level 2 discordance ranged from 1.6% to 6%. These figures were highest for number of women who completed IFA supplementation, contraceptive intra-uterine device insertion and provision of 2nd TT injection during ANC. CONCLUSIONS: HMIS records for MCH services at sub-centre level in Haryana state were satisfactory in terms of completeness. However, there were significant differences in terms of reported and evaluated coverage of MCH services. Quality of HMIS needs to be improved in order to make it relevant for public health program planning and research.

Trends in OSHA Compliance Monitoring Data 1979-2011: Statistical Modeling of Ancillary Information across 77 Chemicals.

OBJECTIVES: The Integrated Management Information System (IMIS) is the largest multi-industry source of exposure measurements available in North America. However, many have suspected that the criteria through which worksites are selected for inspection are related to exposure levels. We investigated associations between exposure levels and ancillary variables in IMIS in order to understand the predictors of high exposure within an enforcement context. METHODS: We analyzed the association between nine variables (reason for inspection, establishment size, total amount of penalty, Occupational Safety and Health Administration (OSHA) plan, OSHA region, union status, inspection scope, year, and industry) and exposure levels in IMIS using multimodel inference for 77 agents. For each agent, we used two different types of models: (i) logistic models were used for the odds ratio (OR) of exposure being above the threshold limit value (TLV) and (ii) linear models were used for exposure concentrations restricted to detected results to estimate percent increase in exposure level, i.e. relative index of exposure (RIE). Meta-analytic methods were used to combine results for each variable across agents. RESULTS: A total of 511,047 exposure measurements were modeled for logistic models and 299,791 for linear models. Higher exposures were measured during follow-up inspections than planned inspections [meta-OR = 1.61, 95% confidence interval (CI): 1.44-1.81; meta-RIE = 1.06, 95% CI: 1.03-1.09]. Lower exposures were observed for measurements collected under state OSHA plans compared to measurements collected under federal OSHA (meta-OR = 0.82, 95% CI: 0.73-0.92; meta-RIE = 0.86, 95% CI: 0.81-0.91). A 'high' total historical amount of penalty relative to none was associated with higher exposures (meta-OR = 1.54, 95% CI: 1.40-1.71; meta-RIE = 1.18, 95% CI: 1.13-1.23). CONCLUSIONS: The relationships observed between exposure levels and ancillary variables across a vast majority of agents suggest that certain elements of OSHA's process of selecting worksites for inspection influence the exposure levels that OSHA inspectors encounter. Nonetheless, given the paucity of other sources of exposure data and the lack of a more demonstrably representative data source, our study considers the use of IMIS data for the estimation of exposures in the broader universe of worksites in the USA.

Medicaid Program; Mechanized Claims Processing and Information Retrieval Systems (90/10). Final rule.

This final rule will extend enhanced funding for Medicaid eligibility systems as part of a state's mechanized claims processing system, and will update conditions and standards for such systems, including adding to and updating current Medicaid Management Information Systems (MMIS) conditions and standards. These changes will allow states to improve customer service and support the dynamic nature of Medicaid eligibility, enrollment, and delivery systems.

Improving timeliness in reporting, data sharing and utilization: a pilot roll-out of the district health management information system at health center IVs in Luwero District

OBJECTIVE: To pilot scale-up of district health management software (DHIS2) to health center fours (HCIVs) in Luwero district to improve timeliness in reporting, data sharing and utilization. DESIGN AND METHODS: This was a pre-and post-implementation study conducted between April-September, 2014 at three HCIVs in Luwero district. Qualitative and quantitative methods were used to collect the data. During pre-implementation, we assessed health worker’s knowledge, attitude and practices towards data sharing and utilization, and a total of 112 health workers (HWs) responded to the questionnaire while 6 key informant interviews were conducted to provide data on potential gaps that would hinder roll-out of DHIS2. After roll-out of the intervention, an evaluation was conducted after four months using a questionnaire with the same respondents. Qualitative data were analyzed manually following a thematic framework approach while quantitative data were analyzed using STATA statistical software. Timeliness reporting rates were extracted from the DHIS2 system for both before and after the implementation. RESULTS: Knowledge on data sharing and utilization increased from 68% to 96% and 45% to 95% respectively. Similarly, proportion of HWs with poor attitude on data sharing and utilization decreased from 20% to 3% and 18% to 4% respectively within the same period while 90% adhered to the set procedures in governing data access and 100% to the use of the electronic tool. Almost all HWs appreciated the fact that use of DHIS2 had lessened the burden for data sharing and utilization. Timeliness in reporting increased from 58% to 84% while inadequate equipment, limited internet and insufficient computing skills were reported. CONCLUSION: In summary, scale-up of DHIS2 to HC IVs was possible and roll-out will contribute to improved timeliness in reporting, data sharing and utilization at HCIVs.

Towards IHE profiles for e-supply in the healthcare domain.

Procurement and supply belong to the crucial supporting processes in hospitals. By providing the right products at the right time in the right quantity in the right place, these processes are of major importance for patient safety and the success of the primary hospital process cure and care. Though of such an importance, the hospital's internal and external procurement and supply processes are still not performed seamlessly by information systems, due to a variety of electronic standards for procurement and supply. These different standards and missing guidelines for electronic procurement and supply in the healthcare domain lead to little or no interoperability between the participating procurement and supply systems. Consequences can be delayed or wrong supply, and increased costs. To overcome this deficiency this work describes the derivation of a common guideline for the implementation of electronically enabled supply processes in the healthcare domain based upon the identification of commonly used electronic standards and detailed specifications of procurement processes in hospital facilities.

Development of model for assessing the acceptance level of users in rural healthcare system of Tamilnadu, India.

BACKGROUND: HMIS will incorporate a paradigm shift in health such as removing manual records and transformation of data through the complex structure of health departments in Tamilnadu. Thus developing a model of technology acceptance in HMIS contest is important and necessary in order to promote usage of the HMIS in rural health care system. OBJECTIVE: The papers purpose is to formulate a model of technology acceptance of Health Management Information System (HMIS) by generating and validating a research model that best describes rural health care workers usage behavior and behavior intention. METHODS: This research proposes a theoretical framework which is comprised of key determinants that influence usage behavior of HMIS together with moderator. It has been tested through different parametric test and confirmatory factor analysis. RESULTS: Data analysis shows that health workers innovativeness and voluntariness have a direct and positive influence on Technology Acceptance level and that the basic TAM hypotheses are fulfilled. HMIS usage behavior and behavior intention can be increased with factors that are effecting the successful implementation of HMIS when it remains high. CONCLUSIONS: This research enables health departments to know which aspects of their HMIS components and variables to improve. This shows that HMIS usage and health workers/staffs acceptance level are key tools in the success of HMIS. This research has seemed to be done at the right time and in the right place to the best of its kind.