Improving Communication Between Patients and Providers Using Health Information Technology and Other Quality Improvement Strategies: Focus on Low-Income Children

2010 ◽  
Vol 67 (5_suppl) ◽  
pp. 246S-267S ◽  
Author(s):  
Quyen Ngo-Metzger ◽  
Gillian R. Hayes ◽  
Yunan Chen ◽  
Ralph Cygan ◽  
Craig F. Garfield
2016 ◽  
Vol 5 (2) ◽  
pp. 62 ◽  
Author(s):  
John Cantiello ◽  
Panagiota Kitsantas ◽  
Shirley Moncada ◽  
Sabiheen Abdul

Objective: Quality improvement in the healthcare industry has evolved over the past few decades. In recent years, an increased focus on coordination of care efforts and the introduction of health information technology has been of high importance in improving the quality of patient care.Methods: In this review, we present a history of quality improvement efforts, discuss quality improvement in the healthcare industry, and examine quality improvement strategies with a focus on patient-centered care and information technology applications via patient registries.Results: Evidence shows that the key to quality improvement efforts in the healthcare industry is the coordination of patient care efforts through better data evaluation processes. By utilizing patient registries that can be linked to electronic health records (EHRs) and the Patient-Centered Medical Home (PCMH) framework, the quality of care provided to patients can be improved.Conclusions: While many healthcare organizations have quality improvement departments or teams in place that may be able to handle these types of efforts, it is important for organizations to be familiar with processes and frameworks that employees at different levels of the organization can be involved in. In order to ensure successful outcomes from quality improvement initiatives, managers and clinicians should work together in identifying problems and developing solutions.


2015 ◽  
Vol 11 (3) ◽  
pp. e421-e427 ◽  
Author(s):  
Jeff Luck ◽  
Laura S. York ◽  
Candice Bowman ◽  
Randall C. Gale ◽  
Nina Smith ◽  
...  

A combination of user-driven tool creation and centralized toolkit development seems to be effective for leveraging health information technology to spread disease-specific quality improvement tools within an integrated health care system.


CJEM ◽  
2019 ◽  
Vol 21 (S1) ◽  
pp. S110
Author(s):  
A. Taher ◽  
E. Bunker ◽  
L. Chartier ◽  
H. Ovens ◽  
B. Davis ◽  
...  

Introduction: Emergency department (ED) return visits are used for quality monitoring. Health information technology (HIT) has historically supported return visit programs in the same hospital or hospital system. The Emergency Department Return Visit Quality Program (EDRVQP) is a novel population level continuous quality improvement (QI) program connecting EDs across Ontario that leverages HIT. We sought to describe the EDRVQP HIT architecture, experience of participants, enabling program factors and barriers. Methods: The Informatics Stack conceptual framework was used to describe the HIT architecture. A literature review of peer-reviewed background literature, and stakeholder organization reports was conducted. Purposive sampling identified key informants. Semi-structured interviews were conducted until saturation. Common themes were identified by inductive qualitative thematic analysis. Results: Twenty-three participants from 15 organizations were interviewed. The EDRVQP architecture description is presented across the Informatics Stack. The levels from most comprehensive to most basic are world, organization, perspectives/roles, goals/functions, workflow/behaviour/adoption, information systems, modules, data/information/knowledge/algorithms, and technology. Enabling factors were a high rate of EHR adoption, provincial legislative mandate for data collection and program membership, use of functional and data standards, local variability, phased deployment, and QI and patient safety culture. Two main barriers were increased case turnaround time and privacy legislation. Conclusion: The Informatics Stack framework provides a robust approach to thoroughly describe the HIT architecture of this population health programs. The EDRVQP is a population health program that illustrates the pragmatic use of continuous QI methodology across a population (provincial) level.


2015 ◽  
Vol 23 (e1) ◽  
pp. e125-e130 ◽  
Author(s):  
Nerissa S Bauer ◽  
Aaron E Carroll ◽  
Chandan Saha ◽  
Stephen M Downs

Abstract Objective Clinicians at our institution typically respond to about half of the prompts they are given by the clinic’s computer decision support system (CDSS). We sought to examine factors associated with clinician response to CDSS prompts as part of a larger, ongoing quality improvement effort to optimize CDSS use. Methods We examined patient, prompt, and clinician characteristics associated with clinician response to decision support prompts from the Child Health Improvement through Computer Automation (CHICA) system. We asked pediatricians who were nonusers of CHICA to rate decision support topics as “easy” or “not easy” to discuss with patients and their guardians. We analyzed these ratings and data, from July 1, 2009 to January 29, 2013, utilizing a hierarchical regression model, to determine whether factors such as comfort with the prompt topic and the length of the user’s experience with CHICA contribute to user response rates. Results We examined 414 653 prompts from 22 260 patients. The length of time a clinician had been using CHICA was associated with an increase in their prompt response rate. Clinicians were more likely to respond to topics rated as “easy” to discuss. The position of the prompt on the page, clinician gender, and the patient’s age, race/ethnicity, and preferred language were also predictive of prompt response rate. Conclusion This study highlights several factors associated with clinician prompt response rates that could be generalized to other health information technology applications, including the clinician’s length of exposure to the CDSS, the prompt’s position on the page, and the clinician’s comfort with the prompt topic. Incorporating continuous quality improvement efforts when designing and implementing health information technology may ensure that its use is optimized.


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