Technology Isn't the Half of It: Integrating Electronic Health Records and Infusion Pumps in a Large Hospital

The role of organizational culture in health information technology implementations: A scoping review

Introduction

The exponential growth in health information technology (HIT) presents an immense opportunity for facilitating the data-to-knowledge-to-performance loop which supports learning health systems. This scoping review addresses the gap in knowledge around HIT implementation contextual factors such as organizational culture and provides a current state assessment.

Methods

A search of 13 databases guided by Arskey and O'Malley's framework identified content on HIT implementations and organizational culture. The Consolidated Framework for Implementation Research (CFIR) was used to assess culture and to develop review criteria. Culture stress, culture effort, implementation climate, learning climate, readiness for implementation, leadership engagement, and available resources were the constructs examined. Rayyan and Qualtrics were used for screening and data extraction.

Results

Fifty two studies included were mainly conducted in Academic Health Centers (n = 18, 35%) and at urban locations (n = 50, 96%). Interviews frequently used for data collection (n = 26, 50%) and guided by multiple frameworks (n = 34). Studies mostly focused on EHR implementations (n = 23, 44%) followed by clinical decision support (n = 9, 17%). About two-thirds (n = 34, 65%) reflected culture stress theme and 62% (21 of 34) acknowledged it as a barrier. Culture effort identified in 27 studies and was a facilitator in most (78%, 21 of 27). Leadership engagement theme in majority studies (71%, n = 37), with 35% (n = 13) noting it as a facilitator. Eighty percent (42 studies) noted available resources, 12 of which identified this as barrier to successful implementation.

Conclusions

It is vital to determine the culture and other CFIR inner setting constructs that are significant to HIT implementation as facilitators or barriers. This scoping review presents a limited number of empirical studies in this topic highlighting the need for additional research to quantify the effects of culture. This will help build evidence and best practices that facilitate HIT implementations and hence serve as a platform to support robust learning health systems.

Policy parameters for optimising hospital ePrescribing: An exploratory literature review of selected countries of the Organisation for Economic Co-operation and Development

Objective

Electronic prescribing systems offer considerable opportunities to enhance the safety, effectiveness and efficiency of prescribing and medicines management decisions but, despite considerable investments in health IT infrastructure and healthcare professional training, realising these benefits continues to prove challenging. How systems are customised and configured to achieve optimal functionality is an increasing focus for policymakers. We sought to develop an overview of the policy landscape currently supporting optimisation of hospital ePrescribing systems in economically developed countries with a view to deriving lessons for the United Kingdom (UK).

Methods

We conducted a review of research literature and policy documents pertaining to optimisation of ePrescribing within hospitals across Organisation for Economic Co-operation and Development (OECD) countries on Embase, Medline, National Institute for Health (NIH), Google Scholar databases from 2010 to 2020 and the websites of organisations with international and national health policy interests in digital health and ePrescribing. We designed a typology of policies targeting optimisation of ePrescribing systems that provides an overview of evidence relating to the level at which policy is set, the aims and the barriers encountered in enacting these policies.

Results

Our database searches retrieved 11 relevant articles and other web resources mainly from North America and Western Europe. We identified very few countries with a national level strategy for optimisation of ePrescribing in hospitals. There were hotspots of digital maturity in relation to ePrescribing at institutional, specialisation, regional and national levels in the US and Europe. We noted that such countries with digital maturity fostered innovations such as patient involvement.

Conclusions

We found that, whilst helpful to achieve certain aims, coordinated strategies within and across countries for optimisation of ePrescribing systems are rare, even in countries with well-established ePrescribing and digital health infrastructures. There is at present little policy focus on maximising the utility of ePrescribing systems.

Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study

Background

At present, electronic health records (EHRs) are the central focus of clinical informatics given their role as the primary source of clinical data. Despite their granularity, the EHR data heavily rely on manual input and are prone to human errors. Many other sources of data exist in the clinical setting, including digital medical devices such as smart infusion pumps. When incorporated with prescribing data from EHRs, smart pump records (SPRs) are capable of shedding light on actions that take place during the medication use process. However, harmoniz-ing the 2 sources is hindered by multiple technical challenges, and the data quality and utility of SPRs have not been fully realized.

Objective

This study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication administration errors. Our overarching hypothesis is that SPRs would contribute unique information in the med-ication use process, enabling more comprehensive detection of discrepancies and potential errors in medication administration.

Methods

We evaluated the medication use process of 9 high-risk medications for patients admitted to the neonatal inten-sive care unit during a 1-year period. An automated algorithm was developed to align SPRs with their medica-tion orders in the EHRs using patient ID, medication name, and timestamp. The aligned data were manually re-viewed by a clinical research coordinator and 2 pediatric physicians to identify discrepancies in medication ad-ministration. The data quality of SPRs was assessed with the proportion of information that was linked to valid EHR orders. To evaluate their utility, we compared the frequency and severity of discrepancies captured by the SPR and EHR data, respectively. A novel concordance assessment was also developed to understand the detec-tion power and capabilities of SPR and EHR data.

Results

Approximately 70% of the SPRs contained valid patient IDs and medication names, making them feasible for data integration. After combining the 2 sources, the investigative team reviewed 2307 medication orders with 10,575 medication administration records (MARs) and 23,397 SPRs. A total of 321 MAR and 682 SPR dis-crepancies were identified, with vasopressors showing the highest discrepancy rates, followed by narcotics and total parenteral nutrition. Compared with EHR MARs, substantial dosing discrepancies were more commonly detectable using the SPRs. The concordance analysis showed little overlap between MAR and SPR discrepan-cies, with most discrepancies captured by the SPR data.

Conclusions

We integrated smart infusion pump information with EHR data to analyze the most error-prone phases of the medication lifecycle. The findings suggested that SPRs could be a more reliable data source for medication error detection. Ultimately, it is imperative to integrate SPR information with EHR data to fully detect and mitigate medication administration errors in the clinical setting.