Evaluating information flow in medication management process in Australian acute care facilities: A multi-professional perspective

Over the years, various interventions have been introduced to improve the medication management process. While these interventions have addressed some aspects predisposing the process to inefficiencies, significant gaps are still prevalent across the process. Studies have suggested that the goal of optimal medication therapy is achievable when information flow integrates across the various medication management process phases, stakeholders and departments involved as the patient moves through the process. To provide a cross-sectional view of the process, this study utilised a systemic philosophy to evaluate the information flow integration across the process. The research approach adopted for this study takes a positivist paradigm, which is guided by the cause and effect (causality) belief. It explored numeric measures to evaluate the relationship between constructs that assessed information flow principles (accessibility, timeliness, granularity and transparency) within the medication process and the information integration. The research design was cross-sectional and analytical, and this ensures that findings are relevant to current situations across the Australian healthcare system. Data for this research was collected using an online self-administered survey and the data assessed information flow principles and technologies used in the medication management process. There were 88 participants in this study, including doctors, nurses and pharmacists. The questions and responses were coded for analysis and data analysis techniques used were frequency analysis, Pearson’s chi-square test and multivariate analysis. Findings from this study indicates that the constructs evaluating accessibility, transparency and granularity had moderate associations with the information integration in the medication management process. Further analysis highlighted accessibility as a significant principle in explaining an increase or decrease in information integration in the medication management process. The accessibility construct referring to information retrieval was significant across the two tests conducted. Accessibility is directly related to information sharing and the assessment and monitoring and evaluation phases in the medication management process were identified as having the highest challenges with information sharing. Furthermore, the hybrid (electronic and paper) channel was preferred to support information integration in the medication management process by the participants. Among the technologies evaluated for the medication process, computer-provider-order-entry was found to be statistically significant in explaining an increase in information integration. Overall, results from this study suggest that interventions for the medication management process in Australian acute care facilities should be directed towards improving accessibility, specifically information retrieval and the sharing of information with emphasis on the assessment and monitoring phases. Implementing strategies to address the gaps identified from this research can improve information integration across the process and thereby reducing medication errors, and improving patient care management. Furthermore, the technology adoption across the process highlights that technology adoption across participants’ facilities remains a challenge in Australia

Enhanced Information Systems Success Model for Patient Information Assurance

The current health information systems have many challenges such as lack of standard user interfaces, data security and privacy issues, inability to uniquely identify patients across multiple hospital information systems, probable misuse of patient data, high technological costs, resistance to technology deployments in hospital management, lack of data gathering, processing and analysis standardization. All these challenges, among others hamper either the acceptance of the health information systems, operational efficiency or expose patient information to cyber attacks. In this paper, an enhanced information systems success model for patient information assurance is developed using an amalgamation of Technology Acceptance Model (TAM) and Information Systems Success Model (ISS). This involved the usage of Linear Structured Relationship (LISREL) software to model a combination of ISS and Intention to Use (ITU), TAM and ITU, ISS and user satisfaction (US), and finally TAM and US. The sample size of 110 respondents was obtained based on the total population of 221 using the Conhrans formula. Thereafter, simple random sampling was employed to select members within each category of employees to take part in the study. The questionnaire as a research tool was checked for reliability via Cronbach’s Alpha. The results obtained showed that for ISS and ITU modeling, only perceived ease of use, system features, response time, flexibility, timeliness, accuracy, responsiveness and user training positively influenced the intention to use. However, for the TAM and ITU modeling, only TAM’s measures such as timely information, efficiency, increased transparency, and proper patient identification had a positive effect on intension to use. The ISS and US modeling revealed that perceived ease of use had the greatest impact on user satisfaction while response time had the least effect on user satisfaction. On its part, the TAM and US modeling showed that timely information, effectiveness, consistency, enhanced communication, and proper patients identification had a positive influence on user satisfaction

Analytical Methods for Planning and Scheduling Daily Work in Inpatient Care Settings: Opportunities for Research and Practice

This article identifies current challenges in the planning and execution of daily work in inpatient care settings. Inadequate planning of the processes and resources associated with inpatient care services may negatively affect their effectiveness. It may also lead to burnout of healthcare workers when the resulting work plan is unknowingly infeasible or does not incorporate the necessary human factors considerations. This paper provides with an overview of current research on inpatient care workflow planning, as well as with directions for researchers and practitioners to advance this problem using a combination of human factors engineering and analytical methods

Simulation and Modeling for Improving Access to Care for Underserved Populations

Indiana University-Purdue University Indianapolis (IUPUI)This research, through partnership with seven Community Health Centers (CHCs) in Indiana, constructed effective outpatient appointment scheduling systems by determining care needs of CHC patients, designing an infrastructure for meaningful use of patient health records and clinic operational data, and developing prediction and simulation models for improving access to care for underserved populations. The aims of this study are 1) redesigning appointment scheduling templates based on patient characteristics, diagnoses, and clinic capacities in underserved populations; 2) utilizing predictive modeling to improve understanding the complexity of appointment adherence in underserved populations; and 3) developing simulation models with complex data to guide operational decision-making in community health centers. This research addresses its aims by applying a multi-method approach from different disciplines, such as statistics, industrial engineering, computer science, health informatics, and social sciences. First, a novel method was developed to use Electronic Health Record (EHR) data for better understanding appointment needs of the target populations based on their characteristics and reasons for seeking health, which helped simplify, improve, and redesign current appointment type and duration models. Second, comprehensive and informative predictive models were developed to better understand appointment non-adherence in community health centers. Logistic Regression, Naïve Bayes Classifier, and Artificial Neural Network found factors contributing to patient no-show. Predictors of appointment non-adherence might be used by outpatient clinics to design interventions reducing overall clinic no-show rates. Third, a simulation model was developed to assess and simulate scheduling systems in CHCs, and necessary steps to extract information for simulation modeling of scheduling systems in CHCs are described. Agent-Based Models were built in AnyLogic to test different scenarios of scheduling methods, and to identify how these scenarios could impact clinic access performance. This research potentially improves well-being of and care quality and timeliness for uninsured, underinsured, and underserved patients, and it helps clinics predict appointment no-shows and ensures scheduling systems are capable of properly meeting the populations’ care needs.2021-12-2

Master of Science

thesisAnnually, 46 million patients, or 37% of patients seen in the emergency department (ED), receive laboratory testing in the U.S.; thus, making efficient lab order and result management critical to improving ED throughput, clinical efficacy, and safety. In order to manage labs and other processes, electronic emergency department tracking systems (EDTS) or electronic whiteboards have evolved features that support clinical, operational, and administrative needs. EDTSs have often augmented manual data entry with interfaces and/or integration with other systems such as registration, laboratory, radiology, and clinical information systems (CIS). One such integration evaluated in this study, EDTS/CIS context sharing, was added to automatically pass all necessary user, patient, and application parameters between the two systems in order to open the CIS lab module for a selected patient when the user is notified in the EDTS that laboratory test results for that patient are available for review. Therefore, context sharing eliminated multiple user steps needed to log-on, search, select, and navigate to the lab viewing module in order to view a patient's lab results. This study evaluates the effects of adding EDTS/CIS context sharing to an EDTS with lab notifications on ED process times. These effects were measured utilizing a pre- and post-intervention design for all ED encounters where specific common labs were resulted. A method of analyzing CIS audit logs in combination with EDTS and laboratory information system timestamps was implemented to measure patient management processes for quality improvement. After adding context sharing to lab notification features, the median interval between the availability of lab results and review of those results by the ordering provider decreased from 22.7 min., by 25% or 5.7 min. (p-value < 0.001), to 17.0 min. However, median time from resulting of labs to patient discharge were essentially unchanged, decreasing from 106.6 min. to 105.0 min. (p-value = 0.080). The proportion of lab results reviewed by physicians in the CIS integrated with the EDTS increased from 66% to 86% after the intervention (p-value < 0.001). EDTS/CIS context sharing and passive lab notification features improved the timeliness and completion of lab result review in the CIS and increased system adoption in this setting. However, reductions in the time intervals to review of lab results in the CIS did not result in an operationally or statistically significant improvement in time to discharge after the availability of results

Determining Care Delivery Model Feasibility Using Discrete-Event-Simulation

Background: The need for inpatient pediatric psychiatric services to address the growing issue of pediatric mental health in a multi-state integrated hospital enterprise is straining the system’s capacity to provide timely mental health care. Local Problem: Lack of access to specialty pediatric psychiatric treatment for dual diagnosis medi-psychiatric care management is a patient quality and safety issue. Insufficient capacity contributes to longer emergency room boarding times and inpatient length of stay for patients who have a mental illness. Methods: Use of digital simulation methodology to analyze the behavior of a dynamic event-driven care delivery workflow and to optimize quality patient outcomes by implementing a hub and spoke model of care. Interventions: A discrete event simulation model was built using retrospective data to evaluate existing resources and “what if” scenarios based on patient movement through a hub-and-spoke regional patient transfer structure. Results: Simulation of the patient flow determined that a decentralized hub-and-spoke model for management of pediatric dual diagnosis patient volume was unnecessary. Simulation modeling results revealed an average daily census of five indicating an ability to centralize all pediatric dual diagnosis volume into one hub hospital instead of three. Conclusions: Simulation was a cost effective, predictive, and innovative approach to evaluating alternative care models at the nurse executive level. The project demonstrated that prudent strategy for use of capital project resources can be enhanced at the beginning of the design phase in project management and clarity of scope realized at the macro, meso, and micro levels every project, every time

Electronic Health Records Communication among Team Members and Quality of Care and Costs for Patients with Cardiovascular Disease in Primary Care

This study determines how changes in electronic health record (EHR) communication patterns in primary care teams are related to quality of care and costs for patients with cardiovascular disease. Counts of EHR messages routed between any two team members were extracted from the EHR system, and flow betweenness, the proportion of information passed indirectly within the team, was calculated. The analysis related changes in team flow betweenness to changes in acute care visits and associated medical costs for the teams’ patients with cardiovascular disease. The results indicated that patient hospital visits increased by 7% (SE 3%) for every 1% increase in team EHR flow betweenness. Medical costs increased by $141 (SE$67) per patient for every 1% increase in team EHR flow betweenness. EHR team communication flow patterns may be an important avenue to explore for raising quality of care and lowering costs for primary care patients with cardiovascular disease

Optimizing Perioperative Decision Making: Improved Information for Clinical Workflow Planning

Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40–70% of hospital revenues and 30–40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction