Browsing by Author "Azar, Jose"

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    Agile Innovation to transform healthcare: innovating in complex adaptive systems is an everyday process, not a light bulb event
    (BMJ, 2021) Holden, Richard J.; Boustani, Malaz A.; Azar, Jose; Medicine, School of Medicine
    Innovation is essential to transform healthcare delivery systems, but in complex adaptive systems innovation is more than ‘light bulb events’ of inspired creativity. To achieve true innovation, organisations must adopt a disciplined, customer-centred process. We developed the process of Agile Innovation as an approach any complex adaptive organisation can adopt to achieve rapid, systematic, customer-centred development and testing of innovative interventions. Agile Innovation incorporates insights from design thinking, Agile project management, and complexity and behavioural sciences. It was refined through experiments in diverse healthcare organisations. The eight steps of Agile Innovation are: (1) confirm demand; (2) study the problem; (3) scan for solutions; (4) plan for evaluation and termination; (5) ideate and select; (6) run innovation development sprints; (7) validate solutions; and (8) package for launch. In addition to describing each of these steps, we discuss examples of and challenges to using Agile Innovation. We contend that once Agile Innovation is mastered, healthcare delivery organisations can habituate it as the go-to approach to projects, thus incorporating innovation into how things are done, rather than treating innovation as a light bulb event.
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    Development and Validation of a 30-Day In-hospital Mortality Model Among Seriously Ill Transferred Patients: a Retrospective Cohort Study
    (Springer, 2021) Mahendraker, Neetu; Flanagan, Mindy; Azar, Jose; Williams, Linda S.; Medicine, School of Medicine
    Background Predicting the risk of in-hospital mortality on admission is challenging but essential for risk stratification of patient outcomes and designing an appropriate plan-of-care, especially among transferred patients. Objective Develop a model that uses administrative and clinical data within 24 h of transfer to predict 30-day in-hospital mortality at an Academic Health Center (AHC). Design Retrospective cohort study. We used 30 putative variables in a multiple logistic regression model in the full data set (n = 10,389) to identify 20 candidate variables obtained from the electronic medical record (EMR) within 24 h of admission that were associated with 30-day in-hospital mortality (p < 0.05). These 20 variables were tested using multiple logistic regression and area under the curve (AUC)–receiver operating characteristics (ROC) analysis to identify an optimal risk threshold score in a randomly split derivation sample (n = 5194) which was then examined in the validation sample (n = 5195). Participants Ten thousand three hundred eighty-nine patients greater than 18 years transferred to the Indiana University (IU)–Adult Academic Health Center (AHC) between 1/1/2016 and 12/31/2017. Main Measures Sensitivity, specificity, positive predictive value, C-statistic, and risk threshold score of the model. Key Results The final model was strongly discriminative (C-statistic = 0.90) and had a good fit (Hosmer-Lemeshow goodness-of-fit test [X2 (8) =6.26, p = 0.62]). The positive predictive value for 30-day in-hospital death was 68%; AUC-ROC was 0.90 (95% confidence interval 0.89–0.92, p < 0.0001). We identified a risk threshold score of −2.19 that had a maximum sensitivity (79.87%) and specificity (85.24%) in the derivation and validation sample (sensitivity: 75.00%, specificity: 85.71%). In the validation sample, 34.40% (354/1029) of the patients above this threshold died compared to only 2.83% (118/4166) deaths below this threshold. Conclusion This model can use EMR and administrative data within 24 h of transfer to predict the risk of 30-day in-hospital mortality with reasonable accuracy among seriously ill transferred patients.
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    The Indiana Learning Health System Initiative: Early experience developing a collaborative, regional learning health system
    (Wiley, 2021-07) Schleyer, Titus; Williams, Linda; Gottlieb, Jonathan; Weaver, Christopher; Saysana, Michele; Azar, Jose; Sadowski, Josh; Frederick, Chris; Hui, Siu; Kara, Areeba; Ruppert, Laura; Zappone, Sarah; Bushey, Michael; Grout, Randall; Embi, Peter J.; Medicine, School of Medicine
    Introduction Learning health systems (LHSs) are usually created and maintained by single institutions or healthcare systems. The Indiana Learning Health System Initiative (ILHSI) is a new multi-institutional, collaborative regional LHS initiative led by the Regenstrief Institute (RI) and developed in partnership with five additional organizations: two Indiana-based health systems, two schools at Indiana University, and our state-wide health information exchange. We report our experiences and lessons learned during the initial 2-year phase of developing and implementing the ILHSI. Methods The initial goals of the ILHSI were to instantiate the concept, establish partnerships, and perform LHS pilot projects to inform expansion. We established shared governance and technical capabilities, conducted a literature review-based and regional environmental scan, and convened key stakeholders to iteratively identify focus areas, and select and implement six initial joint projects. Results The ILHSI successfully collaborated with its partner organizations to establish a foundational governance structure, set goals and strategies, and prioritize projects and training activities. We developed and deployed strategies to effectively use health system and regional HIE infrastructure and minimize information silos, a frequent challenge for multi-organizational LHSs. Successful projects were diverse and included deploying a Fast Healthcare Interoperability Standards (FHIR)-based tool across emergency departments state-wide, analyzing free-text elements of cross-hospital surveys, and developing models to provide clinical decision support based on clinical and social determinants of health. We also experienced organizational challenges, including changes in key leadership personnel and varying levels of engagement with health system partners, which impacted initial ILHSI efforts and structures. Reflecting on these early experiences, we identified lessons learned and next steps. Conclusions Multi-organizational LHSs can be challenging to develop but present the opportunity to leverage learning across multiple organizations and systems to benefit the general population. Attention to governance decisions, shared goal setting and monitoring, and careful selection of projects are important for early success.
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    Major Surgery and Long Term Cognitive Outcomes: The Effect of Postoperative Delirium on Dementia in the Year Following Discharge
    (Elsevier, 2022) Mohanty, Sanjay; Gillio, Anna; Lindroth, Heidi; Ortiz, Damaris; Holler, Emma; Azar, Jose; Boustani, Malaz; Zarzaur, Ben; Surgery, School of Medicine
    Background: Delirium is among the most common complications following major surgery. Delirium following medical illness is associated with the development of chronic cognitive decline. The objective of this study was to determine the association of postoperative delirium with dementia in the year following surgery. Materials and methods: This was a retrospective cohort study in a large health network (January 2013 to December 2019). All patients over age 50 undergoing surgery requiring an inpatient stay were included. Our main exposure was an episode of delirium. The primary outcome was a new dementia diagnosis in the 1 y following discharge. Secondary outcomes included hospital length of stay, non-home discharge destination, mortality and rehospitalizations in 1 y. Results: There were 39,665 patients included, with a median age of 66. There were 4156 of 39,665 emergencies (10.5%). Specialties were general surgery (12,285/39,665, 31%) and orthopedics (11,503/39,665, 29%). There were 3327 (8.4%) patients with delirium. Delirious patients were older and were more likely to have comorbid conditions and undergone complex procedures. There were 1353 of 39,665 (3.5%) patients who developed dementia in the year following their surgery; 4930 of 39,665 (12.4%) who died; and 8200 of 39,665 (20.7%) who were readmitted. Delirium was associated with a new dementia diagnosis after adjusting for baseline characteristics (Odds ratio [OR] 13.9; 95% CI, 12.2-15.7). Similarly, delirium was also associated with 1 y mortality (OR 3.1; 95% CI 2.9-3.4) and readmission (OR 1.9, 95% CI 1.7-2.0). Conclusions: Postoperative delirium is the strongest factor associated with development of dementia in the year following a major operation. Strategies to prevent, identify, and treat delirium in the postoperative setting may improve long-term cognitive recovery.
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    Nurse perceptions of a nurse family liaison implemented during the COVID-19 pandemic: A qualitative thematic analysis
    (Elsevier, 2022-06) Keen, Alyson; George, Annie; Stuck, B.T.; Snyder, Colby; Fleck, Kyle; Azar, Jose; Kara, Areeba; Medicine, School of Medicine
    Objective: Stress among family members of hospitalised intensive care unit patients may be amplified in the context of a global pandemic and strict visitor restrictions. A nurse family liaison role in the COVID-19 units was implemented to serve as a connection between the care team and a designated family member. Our objective was to describe the experience of a nurse family liaison role implemented during the COVID-19 pandemic from the perspective of nurses who functioned in the liaison role and intensive care nurses who worked with the liaisons. Research method/design: This was a qualitative study using thematic analysis involving a one-time semi-structured interview. A convenience sample of nurses were invited to participate. The analytic approach involved (1) becoming familiar with the data; (2) finding meaning in the data; (3) organising meaningful statements into patterns to generate themes. Setting/participants: Nurses who functioned in the liaison role and intensive care nurses who worked with the liaisons in an adult academic health center in the Midwest United States. Main outcome measure: To describe the psychosocial experience of nurse family liaison role implementation. Findings: The sample (n = 11) mean age was 36 years (range 26-49) and the majority were female (n = 10; 90%), White/non-Hispanic (n = 11; 100%), Bachelor prepared (n = 10; 90%), and had an average of 10 years of experience as a nurse (range 4-25). The major themes identified by participants were living in a pandemic, establishing the role and workflow and experiencing human connection. Conclusion: Hospital organisations should consider how they can provide family-centred care, specifically within the context of a global crisis such as a pandemic. Participant descriptions of the role indicate that liaison implementation alleviated nurse moral distress and fostered development of close family connections. Findings can help inform implementation of similar roles in hospital settings.