Advanced Data Analytics for Improved Decision-Making at a Veterans Affairs Medical Center

Mahajan, Anupama; Madhani, Parag; Chitikeshi, Sanjeevi; Selvaganesan, Padmini; Russell, Alex; Mahajan, Preeti

doi:10.1097/jhm-d-17-00164

Cited by 4 publications

(4 citation statements)

References 11 publications

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“… Admin. – Assessing hospital activities 20 Mahajan et al (2019) [ 73 ] Develop a data-driven methodology for decision-making supported by the use of quarterly strategic analytics for improvement and learning (SAIL) reports to visualize data, study trends and provide actionable recommendations. Admin.…”

Section: Resultsmentioning

confidence: 99%

The path from big data analytics capabilities to value in hospitals: a scoping review

Brossard

Minvielle

Sicotte

2022

BMC Health Serv Res

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Background As the uptake of health information technologies increased, most healthcare organizations have become producers of big data. A growing number of hospitals are investing in the development of big data analytics (BDA) capabilities. If the promises associated with these capabilities are high, how hospitals create value from it remains unclear. The present study undertakes a scoping review of existing research on BDA use in hospitals to describe the path from BDA capabilities (BDAC) to value and its associated challenges. Methods This scoping review was conducted following Arksey and O’Malley’s 5 stages framework. A systematic search strategy was adopted to identify relevant articles in Scopus and Web of Science. Data charting and extraction were performed following an analytical framework that builds on the resource-based view of the firm to describe the path from BDA capabilities to value in hospitals. Results Of 1,478 articles identified, 94 were included. Most of them are experimental research (n=69) published in medical (n=66) or computer science journals (n=28). The main value targets associated with the use of BDA are improving the quality of decision-making (n=56) and driving innovation (n=52) which apply mainly to care (n=67) and administrative (n=48) activities. To reach these targets, hospitals need to adequately combine BDA capabilities and value creation mechanisms (VCM) to enable knowledge generation and drive its assimilation. Benefits are endpoints of the value creation process. They are expected in all articles but realized in a few instances only (n=19). Conclusions This review confirms the value creation potential of BDA solutions in hospitals. It also shows the organizational challenges that prevent hospitals from generating actual benefits from BDAC-building efforts. The configuring of strategies, technologies and organizational capabilities underlying the development of value-creating BDA solutions should become a priority area for research, with focus on the mechanisms that can drive the alignment of BDA and organizational strategies, and the development of organizational capabilities to support knowledge generation and assimilation.

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Section: Resultsmentioning

confidence: 99%

The path from big data analytics capabilities to value in hospitals: a scoping review

Brossard

Minvielle

Sicotte

2022

BMC Health Serv Res

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“…Finally, our cost analysis was based in the VHA, which is a large, integrated healthcare system. Stakeholders at VHA may have different incentives compared to non-VHA healthcare systems to implement external facilitation programs, and our findings may not be generalizable to all non-VHA institutions [ 66 ]. For example, VHA uses clinical pharmacists differently than other health care systems.…”

Section: Discussionmentioning

confidence: 99%

Costs of implementing a multi-site facilitation intervention to increase access to medication treatment for opioid use disorder

Garcia,

Bounthavong,

Gordon

et al. 2023

Implement Sci Commun

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Background The United States has been grappling with the opioid epidemic, which has resulted in over 75,000 opioid-related deaths between April 2020 and 2021. Evidence-based pharmaceutical interventions (buprenorphine, methadone, and naltrexone) are available to reduce opioid-related overdoses and deaths. However, adoption of these medications for opioid use disorder has been stifled due to individual- and system-level barriers. External facilitation is an evidence-based implementation intervention that has been used to increase access to medication for opioid use disorder (MOUD), but the implementation costs of external facilitation have not been assessed. We sought to measure the facility-level direct costs of implementing an external facilitation intervention for MOUD to provide decision makers with estimates of the resources needed to implement this evidence-based program. Methods We performed a cost analysis of the pre-implementation and implementation phases, including an itemization of external facilitation team and local site labor costs. We used labor estimates from the Bureau of Labor and Statistics, and sensitivity analyses were performed using labor estimates from the Veterans Health Administration (VHA) Financial Management System general ledger data. Results The average total costs for implementing an external facilitation intervention for MOUD per site was $18,847 (SD 6717) and ranged between $11,320 and $31,592. This translates to approximately $48 per patient with OUD. Sites with more encounters and participants with higher salaries in attendance had higher costs. This was driven mostly by the labor involved in planning and implementation activities. The average total cost of the pre-implementation and implementation activities were $1031 and $17,816 per site, respectively. In the sensitivity analysis, costs for VHA were higher than BLS estimates likely due to higher wages. Conclusions Implementing external facilitation to increase MOUD prescribing may be affordable depending on the payer’s budget constraints. Our study reported that there were variations in the time invested at each phase of implementation and the number and type of participants involved with implementing an external facilitation intervention. Participant composition played an important role in total implementation costs, and decision makers will need to identify the most efficient and optimal number of stakeholders to involve in their implementation plans.

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“…Big data analytics is being leveraged in support of decision-making in different ways in this data-driven decision-making era. In their study, Mahajan et al [11] reported on the impact of data-driven methods in improving decision-making with the Veterans Affairs medical center for a specified 30-day standardized mortality ratio. Furthermore, McKinley [13] focuses on using data analytics and predictive analytics to support and address the decision-making needs of clinicians who remain valuable contributors to quality in the healthcare space.…”

Section: Big Data Analytics and Machine Learning Integration In Decis...mentioning

confidence: 99%

Improving the Performance of Machine Learning Model Selection for Electricity Cost Forecasting in Homebased Small Businesses via Exploratory Data Analysis

Qu¹,

Agbor²

2023

EJECE

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An Exploratory Data Analysis (EDA) remains a major tool proving a better understanding of the time series dataset with assumptions that could culminate in obvious errors being eliminated. Yet this step during modeling is often done in a less exhaustive manner. This has resulted in assumptions without effective uncovering of the relationships and structure of the underlying dataset. Besides, possible trends and patterns that might not be readily apparent are often not exposed due to the lack of a comprehensive EDA. The primary step to forecasting entails the selection of the appropriate forecasting approach which remains a major challenge for analysts performing the forecasts. This challenge is the reason why many researchers continue to propose new approaches with the objective of forecasting accuracy enhancements. This study examines the impact of applying a robust EDA in improving Machine Learning model selection for electricity cost forecasting in home-based small businesses.

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Advanced Data Analytics for Improved Decision-Making at a Veterans Affairs Medical Center

Cited by 4 publications

References 11 publications

The path from big data analytics capabilities to value in hospitals: a scoping review

The path from big data analytics capabilities to value in hospitals: a scoping review

Costs of implementing a multi-site facilitation intervention to increase access to medication treatment for opioid use disorder

Improving the Performance of Machine Learning Model Selection for Electricity Cost Forecasting in Homebased Small Businesses via Exploratory Data Analysis

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