How prescribers can use technology to improve patient care

2019 ◽  
Vol 1 (4) ◽  
pp. 198-203
Author(s):  
Sam Shah ◽  
James Coughlan
Keyword(s):  
Primary Care ◽  
Patient Outcomes ◽  
Information Technologies ◽  
Mobile Apps ◽  
Clinical Decision Support Systems ◽  
Improve Patient Care ◽  
Clinical Decision ◽  
Electronic Prescribing ◽  
Health Information Technologies ◽  
Improve Patient

Health information technologies (HITs) have become increasingly used in the NHS and offer prescribers the opportunity to prescribe in a more consistent and reliable way. There is a growing use of electronic prescribing systems, especially in primary care. This will likely reduce prescription errors, but evidence is unclear if it will improve patient outcomes. Clinical decision support systems can reduce variability and alert clinicians when prescriptions could cause patients harm; however, automation bias can create new errors to prescribers who over-rely on the system. HITs can better communication by improving discharge letters, facilitating telehealth appointments and supporting those working in remote settings. Mobile apps offer a way to engage patients in their own care and allow remote monitoring of chronic conditions in primary care, and acute conditions in emergency care settings. There are challenges in realising these benefits, with inconsistent infrastructure and a 10-year delay in realising predicted efficiency savings.

scholarly journals Computerized Clinical Decision Support: Contributions from 2014

2015 ◽  
Vol 24 (01) ◽  
pp. 119-124 ◽  
Author(s):  
V. Koutkias ◽  
J. Bouaud ◽  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Information Technologies ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Editorial Team ◽  
Bibliographic Databases ◽  
Health Information Technologies ◽  
Selection Of

Summary Objective: To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook.Method: A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results: Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions: As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term.

A tactical framework for EMR adoption

2019 ◽  
Vol 32 (3) ◽  
pp. 148-152
Author(s):  
James Lambley ◽  
Craig Kuziemsky
Keyword(s):  
Information Technologies ◽  
Implementation Strategies ◽  
Improve Patient Care ◽  
Theoretical Models ◽  
Clinical Settings ◽  
Human Diversity ◽  
Health Information Technologies ◽  
Emr Adoption ◽  
Legacy Information Systems ◽  
Improve Patient

Hospitals and other health settings across Canada are transitioning from paper or legacy information systems to Electronic Medical Records (EMR) systems to improve patient care and service delivery. The literature speaks to benefits of EMR systems, but also challenges, such as adverse patient events and provider workflow interruptions. Theoretical models have been proposed to help understand the complex interaction between health information technologies and the healthcare environment, but a shortcoming is the transition from conceptual models to actual clinical settings. The health ecosystem is filled with human diversity and organizational culture considerations that cannot be separated from technical implementation strategies. This paper analyzes literature on EMR implementation and adoption to develop a tactical framework for EMR adoption. The framework consists of six categories, each with a set of seed questions to consider when leading technology adoption projects.

scholarly journals Best Paper Selection

2018 ◽  
Vol 27 (01) ◽  
pp. 082-082 ◽  
Keyword(s):  
Participatory Design ◽  
Information Technologies ◽  
Clinical Decision ◽  
Electronic Prescribing ◽  
Experimental Comparison ◽  
User Centered Design ◽  
Record System ◽  
Health Information Technologies ◽  
Safety Risks ◽  
User Centered

Ancker JS, Edwards A, Nosal S, Hauser D, Mauer E, Kaushal R, with the HITEC Investigators. Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Med Inform Decis Mak 2017 Apr 10;17(1):36 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5387195/ Blijleven V, Koelemeijer K, Wetzels M, Jaspers M. Workarounds emerging from electronic health record system usage: consequences for patient safety, effectiveness of care, and efficiency of care. JMIR Hum Factors 2017 Oct 5;4(4):e27 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/28982645/ Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Safety risks associated with the lack of integration and interfacing of hospital health information technologies: a qualitative study of hospital electronic prescribing systems in England. BMJ Qual Saf 2017 Jul;26(7):530-41 http://qhc.bmj.com/cgi/pmidlookup?view=long&pmid=27037303 Dufendach KR, Koch S, Unertl KM, Lehmann CU. A randomized trial comparing classical participatory design to VandAID, an interactive crowdsourcing platform to facilitate user-centered design. Methods Inf Med 2017 Oct 26;56(5):344-9 http://www.thieme-connect.com/DOI/DOI?10.3414/ME16-01-0098 Luna DR, Rizzato Lede DA, Otero CM, Risk MR, González Bernaldo de Quirós F. User-centered design improves the usability of drug-drug interaction alerts: experimental comparison of interfaces. J Biomed Inform 2017 Feb;66:204-13 https://linkinghub.elsevier.com/retrieve/pii/S1532-0464(17)30009-6

scholarly journals Applicability of Clinical Decision Support in Management among Patients Undergoing Cardiac Surgery in Intensive Care Unit: A Systematic Review

2021 ◽  
Vol 11 (6) ◽  
pp. 2880
Author(s):  
Miguel Pereira ◽  
Patricia Concheiro-Moscoso ◽  
Alexo López-Álvarez ◽  
Gerardo Baños ◽  
Alejandro Pazos ◽  
...  
Keyword(s):  
Cardiac Surgery ◽  
Intensive Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Web Of Science ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Real Time Information ◽  
Time Information ◽  
Improve Patient

The advances achieved in recent decades regarding cardiac surgery have led to a new risk that goes beyond surgeons' dexterity; postoperative hours are crucial for cardiac surgery patients and are usually spent in intensive care units (ICUs), where the patients need to be continuously monitored to adjust their treatment. Clinical decision support systems (CDSSs) have been developed to take this real-time information and provide clinical suggestions to physicians in order to reduce medical errors and to improve patient recovery. In this review, an initial total of 499 papers were considered after identification using PubMed, Web of Science, and CINAHL. Twenty-two studies were included after filtering, which included the deletion of duplications and the exclusion of titles or abstracts that were not of real interest. A review of these papers concluded the applicability and advances that CDSSs offer for both doctors and patients. Better prognosis and recovery rates are achieved by using this technology, which has also received high acceptance among most physicians. However, despite the evidence that well-designed CDSSs are effective, they still need to be refined to offer the best assistance possible, which may still take time, despite the promising models that have already been applied in real ICUs.

Computerized Clinical Decision Support Systems for Prescribing in Primary Care: Main Characteristics and Implementation Impact. Protocol of an Evidence and Gap Map.

2021 ◽  
Author(s):  
Hector Acosta-Garcia ◽  
Ingrid Ferrer-López ◽  
Juan Ruano-Ruiz ◽  
Bernardo Santos-Ramos ◽  
Teresa Molina-López
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Literature Search ◽  
Support Systems ◽  
Grey Literature ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Cochrane Library

Abstract Background Computerized clinical decision support systems are used by clinicians at the point-of-care to improve quality of healthcare processes (prescribing error prevention, adherence to clinical guidelines...) and clinical outcomes (preventive, therapeutic, and diagnostics). Attempts to summarize results of computerized clinical decision support systems to support prescription in primary care have been challenging, and most systematic reviews and meta-analyses failed due to an extremely high degree of heterogeneity present among the included primary studies. The aim of our study will be to synthesize the evidence, considering all methodological factors that could explain these differences, and to build an evidence and gap map to identify important remaining research questions. Methods A literature search will be conducted from January 2010 onwards in Medline, Embase, The Cochrane Library and Web of Science databases. Two reviewers will independently screen all citations, full-text and abstract data. The study methodological quality and risk of bias will be appraised using appropriate tools if applicable. A flow diagram with the screened studies will be presented, and all included studies will be displayed using interactive evidence and gap maps. Results will be reported in accordance with recommendations from The Campbell Collaboration on the development of evidence and gap maps. Discussion Evidence behind computerized clinical decision support systems to support prescription use in primary care, has so far been difficult to be synthesized. Evidence and gap maps represent an innovative approach that has emerged and is increasingly being used to address a broader research question, where multiple types of intervention and outcomes reported may be evaluated. Broad inclusion criteria have been chosen with regards to study designs, in order to collect all available information. Regarding the limitations we will only include English and Spanish language studies from the last 10 years, we will not perform a grey literature search, and we will not carry out a meta-analysis due to the predictable heterogeneity of available studies. Systematic Review registration: This study is registered in Open Science Framework https://bit.ly/2RqKrWp

scholarly journals Capturing Relevant Patient Data in Clinical Encounters Through Integration of an Electronic Patient-Reported Outcome System Into Routine Primary Care in a Boston Community Health Center: Development and Implementation Study (Preprint)

2019 ◽  
Author(s):  
Stephanie Loo ◽  
Chris Grasso ◽  
Jessica Glushkina ◽  
Justin McReynolds ◽  
William Lober ◽  
...  
Keyword(s):  
Primary Care ◽  
Community Health ◽  
Health Center ◽  
Community Health Centers ◽  
Community Health Center ◽  
Improve Patient Care ◽  
Patient Reported Outcome ◽  
Patient Reported ◽  
Patient Provider Communication ◽  
Improve Patient

BACKGROUND Electronic patient-reported outcome (ePRO) systems can improve health outcomes by detecting health issues or risk behaviors that may be missed when relying on provider elicitation. OBJECTIVE This study aimed to implement an ePRO system that administers key health questionnaires in an urban community health center in Boston, Massachusetts. METHODS An ePRO system that administers key health questionnaires was implemented in an urban community health center in Boston, Massachusetts. The system was integrated with the electronic health record so that medical providers could review and adjudicate patient responses in real-time during the course of the patient visit. This implementation project was accomplished through careful examination of clinical workflows and a graduated rollout process that was mindful of patient and clinical staff time and burden. Patients responded to questionnaires using a tablet at the beginning of their visit. RESULTS Our program demonstrates that implementation of an ePRO system in a primary care setting is feasible, allowing for facilitation of patient-provider communication and care. Other community health centers can learn from our model in terms of applying technological innovation to streamline clinical processes and improve patient care. CONCLUSIONS Our program demonstrates that implementation of an ePRO system in a primary care setting is feasible, allowing for facilitation of patient-provider communication and care. Other community health centers can learn from our model for application of technological innovation to streamline clinical processes and improve patient care.

scholarly journals Right Care, First Time: Developing a Theory-Based Automated Protocol to Help Clinically Stage Young People Based on Severity and Persistence of Mental Illness

2021 ◽  
Vol 9 ◽  
Author(s):  
Frank Iorfino ◽  
Vanessa Wan Sze Cheng ◽  
Shane P. Cross ◽  
Hannah F. Yee ◽  
Tracey A. Davenport ◽  
...  
Keyword(s):  
Mental Disorders ◽  
Information Technologies ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Base ◽  
Clinical Staging ◽  
Health Information Technologies ◽  
Staging Model ◽  
Automated Protocol ◽  
First Time

Most mental disorders emerge before the age of 25 years and, if left untreated, have the potential to lead to considerable lifetime burden of disease. Many services struggle to manage high demand and have difficulty matching individuals to timely interventions due to the heterogeneity of disorders. The technological implementation of clinical staging for youth mental health may assist the early detection and treatment of mental disorders. We describe the development of a theory-based automated protocol to facilitate the initial clinical staging process, its intended use, and strategies for protocol validation and refinement. The automated clinical staging protocol leverages the clinical validation and evidence base of the staging model to improve its standardization, scalability, and utility by deploying it using Health Information Technologies (HIT). Its use has the potential to enhance clinical decision-making and transform existing care pathways, but further validation and evaluation of the tool in real-world settings is needed.

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