Electronic reporting of all reference laboratory results: An important step toward a truly all-encompassing, integrated health record

Kratz, Alexander

doi:10.1177/1460458215569004

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…The lack of motivation and prioritisation by professionals to enter data was identified as key barriers that need to be overcome. As observed by Kratz, 5 it is expected that more and more technologies and novel approaches will become available to minimise the need for manual data entry. O'Brien et al 6 proposed the redesign of the documentation process for nurses, where they concluded that one can expect that the value of nursing data will increase in the future and can represent a key differentiator for the economic success of the healthcare institutions by higher effectiveness and lower costs.…”

Section: Introductionmentioning

confidence: 99%

Challenges associated with missing data in electronic health records: A case study of a risk prediction model for diabetes using data from Slovenian primary care

Štiglic¹,

Kocbek²,

Fijačko

et al. 2017

Health Informatics J

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The increasing availability of data stored in electronic health records brings substantial opportunities for advancing patient care and population health. This is, however, fundamentally dependant on the completeness and quality of data in these electronic health records. We sought to use electronic health record data to populate a risk prediction model for identifying patients with undiagnosed type 2 diabetes mellitus. We, however, found substantial (up to 90%) amounts of missing data in some healthcare centres. Attempts at imputing for these missing data or using reduced dataset by removing incomplete records resulted in a major deterioration in the performance of the prediction model. This case study illustrates the substantial wasted opportunities resulting from incomplete records by simulation of missing and incomplete records in predictive modelling process. Government and professional bodies need to prioritise efforts to address these data shortcomings in order to ensure that electronic health record data are maximally exploited for patient and population benefit.

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Section: Introductionmentioning

confidence: 99%

Challenges associated with missing data in electronic health records: A case study of a risk prediction model for diabetes using data from Slovenian primary care

Štiglic¹,

Kocbek²,

Fijačko

et al. 2017

Health Informatics J

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“…These findings speak to the importance of developing systems to integrate PGx test results into the EHR as discrete data. Although the challenges of integrating reference laboratory test results into EHRs have been welldocumented [16], doing so would help to facilitate recall of pertinent test results at the point-of-prescribing [17,18]. Our findings highlight the urgency to develop better systems both for electronic integration of reference laboratory results and clinical decision support to facilitate appropriate use of PGx test results longitudinally.…”

Section: Discussionmentioning

confidence: 84%

Early Adoption of Pharmacogenetic Testing for Veterans Prescribed Psychotropic Medications

et al. 2019

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Aim: Describe the characteristics of providers ordering, patients receiving, and clinical impact of a psychotropic pharmacogenetic test on veteran care. Patients & methods: Observational cohort study linking veterans' laboratory results to electronic health record data. Changes in psychotropic medication prescribing were measured as a function of test results. Results: A total of 38 providers tested 181 veterans between 10/6/2014 and 2/1/2018. Prescriptions for medications with severe gene–drug interactions decreased; however, 11 such medications were used after testing. For 43 patients, documentation of the results was missing. Conclusion: Most prescribing decisions were congruent with test results, but in a nontrivial number of cases, prescribers appeared not to act on the results. Poor result documentation impeded the potential of results to inform clinical care.

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“…Due to the complexity of the cases treated at our hospital, over 200,000 assays and panels are sent to over 60 di erent outside reference laboratories every year. [33] As of 2019, we worked with a structured database of 6.38 million patients that counts:…”

Section: Introductionmentioning

confidence: 99%

Simulating drug effects on blood glucose laboratory test time series with a conditional WGAN

Yahi

Tatonetti

2020

Preprint

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The unexpected effects of medications has led to more than 14 million drug adverse events reported to the Food and Drug Administration (FDA) over the past 10 years in the United States alone, with a little over 1.3 million of them linked to death, and represents a medical and financial burden on our healthcare. Laboratory tests have the potential to capture inter-individual variability in drug responses, but a significant portion of the patient population has unique treatment pathways that impedes forecasting and optimal decision making. Generative Adversarial Networks (GANs) are flexible implicit generative models that have demonstrated their ability to capture complex correlations in field like computer vision and natural language. Their latent representation capacity is an opportunity for drug effect simulation on laboratory test trajectories. In this paper, we developed and evaluated conditional GANs on glucose laboratory tests in patients exposed to drug combinations and showed a proof of concept for these models in the simulation of unseen drug combinations. By using conditional Wasserstein GANs (WGANs) to simulate drug effects in laboratory tests, we hope to pave the way for novel clinical decision support (CDM) systems and enable the development of better predictive models for rare cohorts of patients.

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Electronic reporting of all reference laboratory results: An important step toward a truly all-encompassing, integrated health record

Cited by 5 publications

References 8 publications

Challenges associated with missing data in electronic health records: A case study of a risk prediction model for diabetes using data from Slovenian primary care

Challenges associated with missing data in electronic health records: A case study of a risk prediction model for diabetes using data from Slovenian primary care

Early Adoption of Pharmacogenetic Testing for Veterans Prescribed Psychotropic Medications

Simulating drug effects on blood glucose laboratory test time series with a conditional WGAN

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