Electronic medical record implementation in a large healthcare system from a leadership perspective.

BACKGROUND: Information on the use of change management models to guide electronic medical records (EMR) implementation is limited. This case study describes the leadership aspects of a large-scale EMR implementation using Kotter's change management model. METHODS: This case study presents the experience in implementing a new EMR system from the leadership perspective at King Abdulaziz Medical City, a large tertiary care hospital in Riyadh, Kingdom of Saudi Arabia. We described the process of implementation and outlined the challenges and opportunities, throughout the journey from the pre-implementation to the post-implementation phases. RESULTS: We described the corresponding actions to the eight domains of Kotter's change management model: creating a sense of urgency, building the guiding team, developing a change vision and strategy, understanding and buy-in, removing obstacles, creating short-term wins, building on the change and anchoring the changes in corporate culture. CONCLUSIONS: The case study highlights that EMR implementation is not a pure information technology project but rather is a technical-based complex social adaptive project that requires a specific set of leadership competencies that are central to its success. It demonstrates that change management models might be useful for large-scale EMR implementation.

Electronic early notification of sepsis in hospitalized ward patients: a study protocol for a stepped-wedge cluster randomized controlled trial.

BACKGROUND: To evaluate the effect of screening for sepsis using an electronic sepsis alert vs. no alert in hospitalized ward patients on 90-day in-hospital mortality. METHODS: The SCREEN trial is designed as a stepped-wedge cluster randomized controlled trial. Hospital wards (total of 45 wards, constituting clusters in this design) are randomized to have active alert vs. masked alert, 5 wards at a time, with each 5 wards constituting a sequence. The study consists of ten 2-month periods with a phased introduction of the intervention. In the first period, all wards have a masked alert for 2 months. Afterwards the intervention (alert system) is implemented in a new sequence every 2-month period until the intervention is implemented in all sequences. The intervention includes the implementation of an electronic alert system developed in the hospital electronic medical records based on the quick sequential organ failure assessment (qSOFA). The alert system sends notifications of "possible sepsis alert" to the bedside nurse, charge nurse, and primary medical team and requires an acknowledgment in the health information system from the bedside nurse and physician. The calculated sample size is 65,250. The primary endpoint is in-hospital mortality by 90 days. DISCUSSION: The trial started on October 1, 2019, and is expected to complete patient follow-up by the end of October 2021. TRIAL REGISTRATION: ClinicalTrials.gov NCT04078594 . Registered on September 6, 2019.

National Approach to Standardize and Improve Mechanical Ventilation.

NASAM (National Approach to Standardize and Improve Mechanical Ventilation) is a national collaborative quality improvement project in Saudi Arabia. It aims to improve the care of mechanically ventilated patients by implementing evidence-based practices with the goal of reducing the rate of ventilator-associated events and therefore reducing mortality, mechanical ventilation duration and intensive care unit (ICU) length of stay. The project plans to extend the implementation to a total of 100 ICUs in collaboration with multiple health systems across the country. As of March 22, 2019, a total of 78 ICUs have registered from 6 different health sectors, 48 hospitals, and 27 cities. The leadership support in all health sectors for NASAM speaks of the commitment to improve the care of mechanically ventilated patients across the kingdom.

The impact of health information technologies on quality improvement methodologies' efficiency, throughput and financial outcomes: a retrospective observational study.

BACKGROUND: To evaluate whether or not the utilization of Health Information Technologies (HITs) in Quality Improvement Methodologies (QIMs) has impacts on QIMs' efficiency, throughput and financial outcomes at healthcare organizations and physician practices in the United States. METHODS: This is a retrospective observational study that was conducted between the years of 2014 and 2015 and relied on two data sources: the Dorenfest Institute dataset and the Healthcare Information and Management Systems Society (HIMSS) Analytics data source. In addition, questionnaires were submitted to collect data about how healthcare settings in the United States had been utilizing QIMs in the last 10 years. The submitted questionnaire invitations yielded 144 responses from 134 hospitals and 10 physician practices. Descriptive statistics were used to assess the condition of the data. This involved the utilization of Box-Whisker plots to visualize the data shape, outliers and variation. The Gamma correlation analysis method was used to evaluate the statistical relationships between the QIM outcomes, efficiency, throughput and financial outcomes, and the employment of HIT systems in QIMs. RESULTS: The study found that 99.3% of the healthcare organizations and physician practices had implemented at least one QIM over the last 10 years. In the QIM implementations, the total numbers of reported utilization instances of manual data collection, electronic health records, lab information systems, pharmacy information systems, computerized provider order entry and radiology information systems were 387, 352, 205, 185, 180 and 158, respectively. Based on a 95% confidence limit, the Gamma statistical test has shown an inverse correlation between the exclusive utilization of manual data collection and the overall QIM efficiency (p = 0.047, Gamma = -0.388) and throughput (p = 0.012, Gamma = -0.593) outcomes. However, the overall QIM financial outcomes were found to have a statistically insignificant correlation (p = 0.159). CONCLUSIONS: The study has revealed statistically significant negative impacts on QIMs' efficiency and throughput outcomes when the manual data collection is the sole method used in QIM implementations. This also indicates a positive correlation between the QIMs' efficiency and throughput outcomes and the HIT utilization in QIMs.

Development and implementation of a clinical and business intelligence system for the Florida health data warehouse.

OBJECTIVE: To develop and implement a Clinical and Business Intelligence (CBI) system for the Florida Health Data Warehouse (FHDW) in order to bridge the gap between Florida's healthcare stakeholders and the health data archived in FHWD. MATERIALS AND METHODS: A gap analysis study has been conducted to evaluate the technological divide between the relevant users and FHWD health data, which is maintained by the Broward Regional Health Planning Council (BRHPC). The study revealed a gap between the health care data and the decision makers that utilize the FHDW data. To bridge the gap, a CBI system was proposed, developed and implemented by BRHPC as a viable solution to address this issue, using the System Development Life Cycle methodology. RESULTS: The CBI system was successfully implemented and yielded a number of positive outcomes. In addition to significantly shortening the time required to analyze the health data for decision-making processes, the solution also provided end-users with the ability to automatically track public health parameters. DISCUSSION: A large amount of data is collected and stored by various health care organizations at the local, state, and national levels. If utilized properly, such data can go a long way in optimizing health care services. CBI systems provide health care organizations with valuable insights for improving patient care, tracking trends for medical research, and for controlling costs. CONCLUSION: The CBI system has been found quite effective in bridging the gap between Florida's healthcare stake holders and FHDW health data. Consequently, the solution has improved in the planning and coordination of health care services for the state of Florida.