1,350 research outputs found

    Missing Pieces in Health Services Cost Analysis: Consensus on Modeling, Magnitude, and Micro-Costing

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    Cost and cost savings have become an important focus for health policy administrators. However, there are missing pieces in our approach to cost analysis; there is no consensus on multivariable methods, no indicators of minimally acceptable values, and no specification of process costing. In this dissertation, I propose to fill the gaps in the literature by 1) identifying which methods are appropriate for large claims data, 2) examine existing methods to establish minimally important difference (MID) in health outcomes to identify MID in costs, and 3) determine differences in sick visit clinic costs using a modified micro-costing method. Most models that were compared to the generalized linear models Gamma distribution with log link found it to be the superior model in both simulated data and real administrative data. We recommend that in cases where acceptable anchors are not available to establish an MID, both the Delphi and the distribution-method of MID for costs be explored for convergence. Our micro-costing approach is feasible to use under virtual working conditions; requires minimal provider time; and generates detailed cost estimates that have “face validity” with providers and are relevant for economic evaluation

    Resistance of multiple stakeholders to e-health innovations: Integration of fundamental insights and guiding research paths

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    Consumer/user resistance is considered a key factor responsible for the failure of digital innovations. Yet, existing scholarship has not given it due attention while examining user responses to e-health innovations. The present study addressed this need by consolidating the existing findings to provide a platform to motivate future research. We used a systematic literature review (SLR) approach to identify and analyze the relevant literature. To execute the SLR, we first specified a stringent search protocol with specific inclusion and exclusion criteria to identify relevant studies. Thereafter, we undertook an in-depth analysis of 72 congruent studies, thus presenting a comprehensive structure of findings, gaps, and opportunities for future research. Specifically, we mapped the relevant literature to elucidate the nature and causes of resistance offered by three key constituent groups of the healthcare ecosystem—patients, healthcare organizational actors, and other stakeholders. Finally, based on the understanding acquired through our critical synthesis, we formulated a conceptual framework, classifying user resistance into micro, meso, and macro barriers which provide context to the interventions and strategies required to counter resistance and motivate adoption, continued usage, and positive recommendation intent. Being the first SLR in the area to present a multi-stakeholder perspective, our study offers fine-grained insights for hospital management, policymakers, and community leaders to develop an effective plan of action to overcome barriers that impede the diffusion of e-health innovations.publishedVersionPaid open acces

    The Use of ISBARED/ISHAPED and Elimination of Reviewing Patients’ Chart before Handoff to Decrease Incremental Overtime

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    Problem: Incremental overtime was found to majorly impact the financial well-being of a stroke unit. From an allocated budget of 22 hours per pay period, the unit’s incremental overtime averaged 40 hours. The stroke unit had skilled-mix competencies, further complicating handoffs. The absence of a standard reporting method means that reviewing patients’ charts takes approximately 10 to 15 minutes, extending what should be a quick, but thorough nurse knowledge exchange. Context: The body of evidence reviewed indicated that pertinent information to patient care is not left out or missed when a standardized tool is used during handoff. Based on Lean methodology principles, focus was given to wasteful processes and the use of the evidence-based handoff tool ISBARED/ISHAPED, an SBAR derivative. The unit budget contributes to the overall healthcare spending of an organization. This is where services are rendered and metrics that matter are focused on the patients. It is also where finances matter in terms of waste and savings. As such, processes that are wasteful or redundant need to be reviewed and eliminated so that flow is smooth and care costs are minimized at all times. IOT takes a large bite from the unit budget due to suboptimal management of resources (time, money, or processes). Intervention: This project did small tests of change indicating how this evidence-based tool could facilitate better flow at shift change and eliminate the 5-minute review of patients’ charts. ISBARED/ISHAPED has the potential to facilitate better flow at shift change; however, work ethics was acknowledged in this process. Small modifications exposed the intricacies of working in a unionized skilled-mix unit, the work culture, and the readiness for change. This project also intensified the Gemba walk of nurse leaders allowing nurses to concentrate on performance expectations, roles, and accountability in financial stewardship. Measures: As an outcome measure, IOT per PP was monitored and represented as a graph. The process measures of IOT and NKE were the drivers for the project and were reviewed based on the number of nurses complying with the mandate through nurse leaders Gemba Walk. Chart reviews before handoff, NKE and IOT processes became an integral part of it. Huddle time between two shifts was also monitored to see how it affects IOT. The balancing measure is aimed at evaluating nurses’ engagement, participation, and readiness for the change. Results: Generally, there was a decrease in IOT. The ISBARED/ISHAPED tool did not significantly make an impact to decrease IOT because only a few nurses were chosen to use it. However, based on their comments a greater impact would have been felt if all used it and prepared one for incoming shifts. This process would have eliminated the 5-minute review of patients’ charts and easily facilitate handoff, but the 5-minute review of charts was kept due to union agreements. The tool, however, demonstrated how this evidence-based tool can improve flow at the change of shift and provide a comprehensive communication tool for the NKE. On the other hand, the Gemba walk that tackled huddle time, coaching and supporting individual nurses, NKE and IOT processes made a great impact on processes, awareness, roles, accountability and collaboration to decrease IOT. Conclusion: The ISBARED/ISHAPED handoff tool is an effective means to address the flow of information during nurse knowledge exchanges at the bedside, as it is an evidence-based, standardized form. However, its success requires purposeful use that can prove difficult when doing so challenges existing work processes and/or work culture

    Time is of the essence: an observational time-motion study of internal medicine residents while they are on duty

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    Background: The effects of changes to resident physician duty hours need to be measureable. This time-motion study was done to record internal medicine residents’ workflow while on duty and to determine the feasibility of capturing detailed data using a mobile electronic tool.Methods: Junior and senior residents were shadowed by a single observer during six-hour blocks of time, covering all seven days. Activities were recorded in real-time. Eighty-nine activities grouped into nine categories were determined a priori.Results: A total of 17,714 events were recorded, encompassing 516 hours of observation. Time was apportioned in the following categories: Direct Patient Care (22%), Communication (19%), Personal tasks (15%), Documentation (14%), Education (13%), Indirect care (11%), Transit (6%), Administration (0.6%), and Non-physician tasks (0.4%). Nineteen percent of the education time was spent in self-directed learning activities. Only 9% of the total on duty time was spent in the presence of patients. Sixty-five percent of communication time was devoted to information transfer. A total of 968 interruptions were recorded which took on average 93.5 seconds each to service.Conclusion: Detailed recording of residents’ workflow is feasible and can now lead to the measurement of the effects of future changes to residency training. Education activities accounted for 13% of on-duty time.

    Organizational Improvement Readiness Assessment (OIRA) Tool Evaluation

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    Background: Research shows that despite an increase in the number of organizational improvement initiatives there is a lack of consistent, sustained outcomes. Organizations struggle with how to reliably and accurately measure their readiness to drive and sustain outcomes. A search of the literature failed to identify a comprehensive, evidence-based tool that has been developed or evaluated to assess organizational improvement readiness. The objective of this project was to evaluate a newly developed Organizational Improvement Readiness Assessment (OIRA) Tool. Project Design: Guided by two theoretical models, Delphi-Based Systems Architecting Framework (DB-SAF) and the Rogers Diffusion of Innovation Model, a 3-round, modified Delphi nominal group method was utilized. An evaluation panel of 13 organizational improvement subject matter experts (SMEs) was recruited, with 11 SMEs completing all 3 evaluation rounds. The relevancy and clarity of the OIRA Tool competencies was evaluated using an item-level content validity index (I-CVI) and a scale-level content validity index (S-CVI). Additionally, the tool was evaluated from a usability perspective using Google Analytics. Results: The OIRA Tool was found to be clear, understandable, and relevant for organizations evaluating their readiness to drive and sustain outcomes improvements (S-CVI index of 0.92 and I-CVI indices ranging from 0.82 to 1.0). The final version of the tool included 22 competencies, modified based on expert consensus from the original 25. Usability test results confirmed the OIRA Tool, a web-based tool, is easy to use and well designed as measured by exit rates (15.44%), bounce rates (51.81%), and conversion rates (14%), all of which were significantly better than industry benchmarks. Recommendations and Conclusions: Results of this project provide evidence of the content validity and usability of the OIRA Tool. The tool has the potential to help healthcare organizations assess their readiness to sustain organizational improvements and to identify gaps in leadership and culture, processes, technologies, and standards. The OIRA Tool provides the foundation for future analytics modeling and additional studies to test the theory and the advancement of outcomes improvement science

    Contextualized clinical decision support to detect and prevent adverse drug events

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    A safer surgical ward: real-time patient safety risk assessment for the post-operative care environment

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    The inpatient ward environment is the basic unit of a healthcare facility. Both intrinsic and extrinsic influences on this unit often dictate the quality and safety of care. For surgical patients, although significant focus has been given to care quality in the peri-operative phase, it has become increasingly evident that the overall outcome is determined during the post-operative period of care on the surgical ward. This is demonstrated through the concept of failure to rescue, where stark differences in mortality rates between institutions are seen despite similar complication rates. Research to identify the drivers of these variations often focus on specific themes, rather than evaluating the surgical ward as a system. Furthermore, much of the research examines large administrative datasets with analysis conducted at the institutional, rather than unit level. This thesis assesses the degree of variation that exists on surgical wards and identifies contributors to error that span the Donabedian model; this considers how processes are performed and how structural factors may influence outcomes. A close examination at the grassroots level has facilitated the identification of granular new metrics with direct relevance to day-to-day care at the ward level. With this approach, the potential for real-time risk assessment of this environment has been proposed, along with future directions to realise this objective. This has been achieved via a sequence of studies that utilise a range of methods. Following a review of the current literature, a semi-structured interview study was conducted across multiple sites. The experiences of surgical patients, nurses, doctors and managers was explored through 51 interviews. Stakeholders were acutely aware that some surgical wards were safer than others and were able to identify errors within a number of processes, such as the conduction of ward rounds, communication among healthcare staff and medication administration. Furthermore, the development of potential errors was seen as embedded in complex structural influences; the effective performance of processes was impacted by factors such as staffing shortages, organisational bed pressures (i.e., leading to outlier patients) and a potentially challenging physical environment, with layout and lack of space presented as a potential obstacle to safe care. Participants were also able to propose a range of quality markers that reflected the range of influences at play on the ward. This was followed with a Delphi Consensus study which organised the wide range of factors identified in the previous study and prioritised those deemed to have the most influence on the delivery of safe care on the surgical ward. An international panel of experts in patient safety and patient advocates considered multiple facets of this environment. Sixty-four of the 85 statements in the final questionnaire achieved consensus, highlighting the inherent complexity of the surgical ward. This led to an ethnographic observational study of surgical wards, with the aim to assess the degree of variability and measurability of these prioritised factors. Three broad domains were observed – processes of care, the care environment and organisational health. Alongside this observation, patients and nurses also completed validated questionnaires that measure safety culture. There was a high degree of disparity with respect to how a ward behaves as a system from day-to-day. Variation in timings and features of the ward round as well as timeliness of clinical and nursing task completion was demonstrated. Organisational influences (e.g., staffing levels, skill mix, use of temporary staffing, ward occupancy, outlier patients etc) were highly dynamic. The final study establishes an association between measurable factors identified in the observational study and patient outcomes and presents the feasibility of using these as real-time measures of safe care on the surgical ward. Many of these risk factors are retrievable from routinely collected data and were extracted from electronic health records and duty rostering programmes. The patient outcomes identified were also available from the same data sources, namely wrong time medication errors and clinical deterioration. Preliminary statistical models of harm are presented in this study, thus demonstrating that local routinely collected data may have a role in predictive modelling of the risk of harm within a specific setting. Local teams may be able to harness their own data to predict their own risk. This could help guide future policies and improvement strategies. In conclusion, this thesis has comprehensively explored the entirety of the surgical ward as a system of care delivery, examined the complex array of factors at play as well as their potential interactions with one another and proposed new granular safety metrics that have a role for predictive modelling of the risk of harm at the local level. Further work is needed to develop these predictive models further, such as establishing methods to measure those factors that are not currently available through routinely collated data. This will allow future iterations of the predictive model to incorporate a wider range of factors that are potentially influencing care quality on the surgical ward, with the aim of enhancing sensitivity and applicability of the final model.Open Acces

    A Consensus-based Data Quality Assessment Model for Patient Reported Outcome Information in Digital Quality Measurement Programs

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    Quality measurement has been evolving to become more patient-focused and more meaningful in supporting quality improvement. Recent advancements in digital data and measurement standards have made this evolution possible, but this move to digital measurement presents several challenges despite its many benefits. Digital quality measures (dQMs) substantially reduce the computational burden of generating “quality” knowledge and improve the reliability of the measure scores they generate, however they rely on a very specific presentation of the electronic data to achieve the aforementioned benefits. Newer dQMs based on patient-reported outcomes (PROs) measured using patient-reported outcome measures (PROMs) have been gaining attention as they generate valuable insight into a person’s perception of their own health status. Reliably capturing these insights is challenging however, as the information does not often exist in a format that can be processed by a dQM. This lack of standardization has resulted in the formation of clinical data repositories (CDRs) for the explicit purpose of extracting, transforming, and loading (ETL) PROM data from patients’ medical records into a format that can support digital quality measurement. These ETL processes are subject to rigorous evaluation to ensure that, as the information is being transformed, the integrity of the original information is being preserved. These evaluations inform decisions regarding data fitness for the specific purpose of using the data to measure quality of care. These “fit for purpose” decisions are not guided by a uniform set of expectations or requirements to assure consistency in decision-making, rather they frequently rely upon a variety of statistical and operational test results that can often present seemingly inconsistent information that requires substantial expertise to interpret and reconcile. A uniform, well-defined list of data quality concepts pertinent to using patient-reported outcome measures for the purpose of quality measurement would provide much needed guidance and enhance the consistency and reliability of data fitness decision-making. This research confirmed the scarcity of access to effective guidance for assessing fitness of PROM data and that there is a desire for a standard PROM-based data quality assessment (DQA) model to support decision making

    Electronic Medical Records (EMR): An Empirical Testing of Factors Contributing to Healthcare Professionals’ Resistance to Use EMR Systems

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    The benefits of using electronic medical records (EMRs) have been well documented; however, despite numerous financial benefits and cost reductions being offered by the federal government, some healthcare professionals have been reluctant to implement EMR systems. In fact, prior research provides evidence of failed EMR implementations due to resistance on the part of physicians, nurses, and clinical administrators. In 2010, only 25% of office-based physicians have basic EMR systems and only 10% have fully functional systems. One of the hindrances believed to be responsible for the slow implementation rates of EMR systems is resistance from healthcare professionals not truly convinced that the system could be of substantive use to them. This study used quantitative methods to measure the relationships between six constructs, namely computer self-efficacy (CSE), perceived complexity (PC), attitude toward EMR (ATE), peer pressure (PP), anxiety (AXY), and resistance to use of technology (RES), are predominantly found in the literature with mixed results. Moreover, they may play a significant role in exposing the source of resistance that exists amongst American healthcare professionals when using Electronic Medical Records (EMR) Systems. This study also measured four covariates: age, role in healthcare, years in healthcare, gender, and years of computer use. This study used Structural Equation Modeling (SEM) and an analysis of covariance (ANCOVA) to address the research hypotheses proposed. The survey instrument was based on existing construct measures that have been previously validated in literature, however, not in a single model. Thus, construct validity and reliability was done with the help of subject matter experts (SMEs) using the Delphi method. Moreover, a pilot study of 20 participants was conducted before the full data collection was done, where some minor adjustments to the instrument were made. The analysis consisted of SEM using the R software and programming language. A Web-based survey instrument consisting of 45 items was used to assess the six constructs and demographics data. The data was collected from healthcare professionals across the United States. After data cleaning, 258 responses were found to be viable for further analysis. Resistance to EMR Systems amongst healthcare professionals was examined through the utilization of a quantitative methodology and a cross-sectional research measuring the self-report survey responses of medical professionals. The analysis found that the overall R2 after the SEM was performed, the model had an overall R2 of 0.78, which indicated that 78% variability in RES could be accounted by CSE, PC, ATE, PP, and AXY. The SEM analysis of AXY and RES illustrated a path that was highly significant (β= 0.87, p \u3c .001), while the other constructs impact on RES were not significant. No covariates, besides years of computer use, were found to show any significance differences. This research study has numerous implications for practice and research. The identification of significant predictors of resistance can assist healthcare administrators and EMR system vendors to develop ways to improve the design of the system. This study results also help identify other aspects of EMR system implementation and use that will reduce resistance by healthcare professionals. From a research perspective, the identification of specific attitudinal, demographic, professional, or knowledge-related predictors of reference through the SEM and ANCOVA could provide future researchers with an indication of where to focus additional research attention in order to obtain more precise knowledge about the roots of physician resistance to using EMR systems
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