Lean Management Principles to the Creation of Postpartum Hemorrhage Care Bundles

Postpartum hemorrhage (PPH) is the number one cause of pregnancy-related death in the US. The Maternity local improvement team (LIT), co-led by an Obstetrician and Board Certified Clinical Nurse Specialist found that each month the maternity unit averages 40 PPHs with 1-2 resulting in an emergency. Over a 6-month period, the LIT decreased response time for emergencies significantly. Supply retrieval time decreased by 99.9%, MD response time decreased by 81%, and Family Centered Care increased by 100%. They recently turned their attention to prevention. Given the lack of literature on preventing PPH in postpartum units, the team developed a PPH prevention bundle-a small set of evidence-based interventions enhancing teamwork and communication to improve patient outcomes. Dr. Crowe as the national lead for benchmarking obstetrical adverse events in the Solutions for Patient Safety collaborative will track the success of the PPH bundle, which could become the first national standard in prevention of PPH requiring a blood transfusion. The team targeted 100% compliance to bundle elements, with an ultimate goal of decreasing need for transfusion. Many problems have been encountered along the way, such as RN handoffs from Labor and Delivery as well as having appropriate staff to help new mothers to the bathroom for the first time, but the team has worked through them one-by-one. Through simulation training over a 6-month period, 100 RNs, MDs, and family representatives simulated the bundle approach. The PPH Prevention Bundle could become the first national standard in prevention of PPHs on a postpartum unit

State strategies for preventing pregnancy-related deaths : a guide for Moving Maternal Mortality Review Committee data to action

Maternal mortality is a devastating tragedy that no family or community should have to endure. Opportunities to eliminate maternal mortality can be best identified by multidisciplinary Maternal Mortality Review Committees (MMRCs) at the stateor jurisdiction-level (hereafter referred to as state), inclusive of representation by clinical and non-clinical experts that serve populations disproportionately affected by maternal mortality. MMRCs provide an understanding of factors that contribute to maternal mortality within the unique contexts of the states and communities where these persons lived. MMRC data can be a driving force for prioritizing recommendations and formulating strategies that can prevent maternal mortality.Suggested citation: Centers for Disease Control and Prevention. (2022). State Strategies for Preventing Pregnancy-Related Deaths: A Guide for Moving Maternal Mortality Review Committee Data to Action. Atlanta, GA: National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention.State-Strategies-508.pdf20221163

Simulation modelling as a tool for knowledge mobilisation in health policy settings: a case study protocol

Background: Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making. Methods/Design: The study design will use mixed methods to achieve the objectives. Policy, clinical practice and research experts will work collaboratively to develop, test and validate a simulation model of GDM in the Australian Capital Territory (ACT). The model will be applied to support evidence-informed policy dialogues with diverse stakeholders for the management of GDM in the ACT. Qualitative methods will be used to evaluate simulation modelling as an evidence synthesis tool to support evidence-based decision-making. Interviews and analysis of workshop recordings will focus on the participants’ engagement in the modelling process; perceived value of the participatory process, perceived commitment, influence and confidence of stakeholders in implementing policy and program decisions identified in the modelling process; and the impact of the process in terms of policy and program change. Discussion: The study will generate empirical evidence on the feasibility and potential value of simulation modelling to support knowledge mobilisation and consensus building in health settings

The impact of training on self-reported performance in reproductive, maternal, and newborn health service delivery among healthcare workers in Tanzania: a baseline- and endline-survey

Background: Delivery of quality reproductive health services has been documented to depend on the availability of healthcare workers who are adequately supported with appropriate training. However, unmet training needs among healthcare workers in reproductive, maternal, and newborn health (RMNH) in low-income countries remain disproportionately high. This study investigated the effectiveness of training with onsite clinical mentorship towards self-reported performance in RMNH among healthcare workers in Mwanza Region, Tanzania. Methods: The study used a quasi-experimental design with pre-and post-intervention evaluation strategy. The baseline was compared with two endline groups: those with intervention (training and onsite mentorship) and those without. The differences among the three groups in the sociodemographic characteristics were analyzed by using chi-square test for categorical variables, independent-sample t-test for continuous variables and Mann-Whitney U test for ordinal or skewed continuous data. The independent sample t-test was used to determine the effect of the intervention by comparing the computed self-reported performance on RMNH services between the intervention and control groups. The paired-samples t-test was used to measure the differences between before and after intervention groups. Significance was set at a 95% confidence interval with p ≤ 0.05. Results: The study included a sample of 216 participants with before and after intervention groups comprising of 95 (44.0%) and 121 (56.0%) in the control group. The comparison between before and after intervention groups revealed a statistically significant difference (p ≤ 0.05) in all the dimensions of the self-reported performance scores. However, the comparison between intervention groups and controls indicated a statistical significant difference on intra-operative care (t = 3.10, df = 216, p = 0.002), leadership skills (t = 1.85, df = 216, p = 0.050), Comprehensive emergency obstetric and newborn care (CEMONC) (t = 34.35, df = 216, p ≤ 0.001), and overall self-reported performance in RMNH (t = 3.15, df = 216, p = 0.002). Conclusions: This study revealed that the training and onsite clinical mentorship to have significant positive changes in self-reported performance in a wide range of RMNH services especially on intra-operative care, leadership skills and CEMONC. However, further studies with rigorous designs are warranted to evaluate the long-term effect of such training programs on RMNH outcomes

Addressing Interprofessional Competence in Interpretation of Electronic Fetal Monitor Tracings

Interpretation of electronic fetal monitor (EFM) tracings is a critical clinical practice skill nurses and physicians perform during the intrapartum stage of pregnancy. However, if performed inaccurately can potentially jeopardize the well-being of the neonate. This risk is present because if concerning EFM tracings are not interpreted accurately, preventative care interventions to promote the well-being of the unborn child do not occur. The project was initiated by completing a scoping literature review on the methods for training and evaluating EFM interpretation competence, which revealed current EFM interpretation training and evaluation methods are lacking. A concept analysis defined nurse competence in diagnostic healthcare technologies. The analysis included examining surrogate terms, related concepts, attributes, antecedents, and consequences. This dissertation evaluated the feasibility and effectiveness of a Simulation-Based Mastery Learning intervention on clinical interprofessional team members’ EFM interpretation competence and self-efficacy compared to clinical experience alone. In addition, it determined how participants’ characteristics affect baseline EFM interpretation scores. The study was a randomized longitudinal design with participants recruited from a convenience sample of interprofessional healthcare team members from a large research hospital in the southeastern United States. Randomization procedures placed recruited participants into either an intervention or clinical experience alone group, with competence evaluations for both groups occurring at baseline, immediately post-intervention, and three months post-intervention. Once completed, add results and conclusion here

The Second International Conference on Health Information Technology Advancement

TABLE OF CONTENTS I. Message from the Conference Co-Chairs B. Han and S. Falan …………………………....….……………. 5 II. Message from the Transactions Editor H. Lee …...………..………….......………….……….………….... 7 III. Referred Papers A. Emerging Health Information Technology and Applications The Role of Mobile Technology in Enhancing the Use of Personal Health Records Mohamed Abouzahra and Joseph Tan………………….……………. 9 Mobile Health Information Technology and Patient Care: Methods, Themes, and Research Gaps Bahae Samhan, Majid Dadgar, and K. D. Joshi…………..…. 18 A Balanced Perspective to Perioperative Process Management Jim Ryan, Barbara Doster, Sandra Daily, and Carmen Lewis…..….…………… 30 The Impact of Big Data on the Healthcare Information Systems Kuo Lane Chen and Huei Lee………….…………… 43 B. Health Care Communication, Literacy, and Patient Care Quality Digital Illness Narratives: A New Form of Health Communication Jofen Han and Jo Wiley…..….……..…. 47 Relationships, Caring, and Near Misses: Michael’s Story Sharie Falan and Bernard Han……………….…..…. 53 What is Your Informatics Skills Level? -- The Reliability of an Informatics Competency Measurement Tool Xiaomeng Sun and Sharie Falan.….….….….….….…. 61 C. Health Information Standardization and Interoperability Standardization Needs for Effective Interoperability Marilyn Skrocki…………………….…….………….… 76 Data Interoperability and Information Security in Healthcare Reid Berryman, Nathan Yost, Nicholas Dunn, and Christopher Edwards.…. 84 Michigan Health Information Network (MiHIN) Shared Services vs. the HIE Shared Services in Other States Devon O’Toole, Sean O’Toole, and Logan Steely…..……….…… 94 D. Health information Security and Regulation A Threat Table Based Approach to Telemedicine Security John C. Pendergrass, Karen Heart, C. Ranganathan, and V.N. Venkatakrishnan …. 104 Managing Government Regulatory Requirements for Security and Privacy Using Existing Standard Models Gregory Schymik and Dan Shoemaker…….…….….….… 112 Challenges of Mobile Healthcare Application Security Alan Rea………………………….……………. 118 E. Healthcare Management and Administration Analytical Methods for Planning and Scheduling Daily Work in Inpatient Care Settings: Opportunities for Research and Practice Laila Cure….….……………..….….….….… 121 Predictive Modeling in Post-reform Marketplace Wu-Chyuan Gau, Andrew France, Maria E. Moutinho, Carl D. Smith, and Morgan C. Wang…………...…. 131 A Study on Generic Prescription Substitution Policy as a Cost Containment Approach for Michigan’s Medicaid System Khandaker Nayeemul Islam…….…...……...………………….… 140 F. Health Information Technology Quality Assessment and Medical Service Delivery Theoretical, Methodological and Practical Challenges in Designing Formative Evaluations of Personal eHealth Tools Michael S. Dohan and Joseph Tan……………….……. 150 The Principles of Good Health Care in the U.S. in the 2010s Andrew Targowski…………………….……. 161 Health Information Technology in American Medicine: A Historical Perspective Kenneth A. Fisher………………….……. 171 G. Health Information Technology and Medical Practice Monitoring and Assisting Maternity-Infant Care in Rural Areas (MAMICare) Juan C. Lavariega, Gustavo Córdova, Lorena G Gómez, Alfonso Avila….… 175 An Empirical Study of Home Healthcare Robots Adoption Using the UTUAT Model Ahmad Alaiad, Lina Zhou, and Gunes Koru.…………………….….………. 185 HDQM2: Healthcare Data Quality Maturity Model Javier Mauricio Pinto-Valverde, Miguel Ángel Pérez-Guardado, Lorena Gomez-Martinez, Martha Corrales-Estrada, and Juan Carlos Lavariega-Jarquín.… 199 IV. A List of Reviewers …………………………..…….………………………208 V. WMU – IT Forum 2014 Call for Papers …..…….…………………20