Exemplary Professional Practice: Accountability, Competence and Autonomy

Transcription

1 Exemplary Professional Practice: Accountability, Competence and Autonomy EP16 Nurse autonomy is supported and promoted through the organization s governance structure for shared decision-making. EP16b: Provide an example, with supporting evidence, of organizational autonomy that demonstrates the authority and freedom of nurses to be involved in broader unit, service line, organization, or system decision-making processes pertaining to patient care, policies and procedures, or work environment. Introduction At Massachusetts General Hospital (MGH) all nurses are expected and encouraged to practice autonomously in the delivery of care. The MGH Department of Nursing & Patient Care Services (N&PCS) supports autonomous nursing practice in many ways. The evolution of a Professional Practice Model, introduced in 1996, supports the authority and freedom of nurses to be involved in broader decision-making processes by providing them with a framework that includes values, standards of practice, professional development, research, evidence-based practice, innovation, clinical recognition and advancement, collaborative decision-making, and teamwork. In 1997, an interdisciplinary model of Collaborative Governance was established as the communication and decision-making infrastructure for the department and placed authority, responsibility, and accountability for patient care in the hands of practicing clinicians. The importance of nurse autonomy is also highlighted in N&PCS orientation. Nurses at all levels in the organization have opportunities to be involved in decisionmaking processes pertaining to care, policies and procedures, and the work environment. MGH and its parent organization, Partners HealthCare (PHC), offer many shared decision-making opportunities for nurses through formal programs that support and develop leadership capacity and maximize the authority and freedom of nurses to influence key decisions about practice and quality of work life. The Partners Clinical Process Improvement Leadership Program (CPIP) is one such program. CPIP was developed in 2010 as an inter-professional, team-based educational program for nurses, physicians, other clinicians and administrators. The program admits two cohorts per year, in September and March. The aim of CPIP is to facilitate the development of skills and competencies needed to deliver high quality care with efficient use of clinical resources to actively lead and participate in clinical process improvement efforts. Projects focus on quality, efficiency, safety, patient experience or a combination thereof. Goals of CPIP are to: 1) identify gaps in quality and efficiency of care by examining current clinical processes 2) apply process improvement skills as a means to reduce unwarranted variation in clinical processes

2 3) apply skills of primary data collection, analysis, and interpretation to understand and improve clinical processes, and 4) develop leadership and communications skills required to assemble, manage and function within interdisciplinary teams in order to solve clinical process challenges. The following example provides evidence of how Anne Que, CRNA, MS, Certified Registered Nurse Anesthetist Team Leader for General Surgery at MGH, used her CPIP participation to influence organization and system decision-making processes to improve patient care and the work environment. Organizational Autonomy Que s scope of practice is outlined in Massachusetts 244 CMR 4.00, and includes, but is not limited to, advanced assessment, diagnosis, and treatment of patients undergoing anesthesia during the immediate perioperative period, defined as from the day before surgery to discharge from post-anesthesia care. Part of this advanced specialty practice with perioperative patients includes supporting life functions during anesthesia, such as intubation, monitoring blood loss and replacement, maintaining cardiovascular and respiratory function, and taking corrective action when patients have abnormal responses. As Advanced Practice Registered Nurses at MGH, CRNAs can order and administer transfusions of blood products (attachment EP 16b.a). Anesthesiologists and CRNAs at MGH are responsible for ordering blood and managing transfusions during surgery. Que noted that blood products were being prepared for elective procedures that incurred very low risk for blood loss. She believed that this practice was inefficient because it could result in unnecessary specimen collection for patients preoperatively and wasted blood products in the operating room. Que thought the use of a standard surgical blood ordering schedule (SSBOS), an algorithm developed by Steven M. Frank, M.D., and colleagues at the Johns Hopkins Medical Institutions [Hopkins], could help to reduce variation in ordering and preparing blood products prior to surgery and at the same time reduce costs and improve patient safety. The Hopkins algorithm to determine appropriate preoperative blood orders was developed using more than 2-years of data gleaned from their adult surgical patients concerning procedure types, estimated blood loss, transfusions, and orders for blood preparation, including Type & Screen and Type & Crossmatch. Que was encouraged to apply for CPIP to work on this issue. Her project, Decreasing Variability in Blood Transfusion Preparation for Laparoscopic Hysterectomy Procedures, was selected. Que participated in CPIP from March July 2015 (attachment EP 16b.b). CPIP is a fast-paced immersion program that gives participants the tools that they need to evaluate and improve a process. Que attended five1-2 day classes during the 4- month period that she was in the program. During participation in CPIP, Que was

3 introduced to key perioperative and clinical leaders around MGH and PHC who helped her achieve the goals of her project. In the final class, Que presented the results of her course project. She reported on the retrospective chart review of 616 patients undergoing laparoscopic hysterectomy performed between January 2014 and February She determined that 86% (n=529) of these patients had blood bank samples for typing and screening (T&S), while 22% (n=133) of the sample were typed and cross-matched (T&C) with blood prepared for the procedure. The rate of transfusion among the entire sample was, however, extremely rare at 0.97% (n=6). Findings demonstrated that preoperative preparation of blood products for low blood loss procedures, such as laparoscopic hysterectomy, may not be necessary. Que realized that because there were no existing guidelines for preoperative blood preparation at MGH, this was left up to individual providers to decide. These results further convinced Que that a SSBOS algorithm was worth pursuing to improve clinical efficiency and patient safety. Que s short-term goal became to adopt the existing Hopkins SSBOS algorithm for use at MGH. Her longer-term goal was to use internal data for all MGH surgical procedures to create a customized SSBOS for the system. Algorithm Adapted: The Authority and Freedom to be Involved in Organization and System Decision-Making As her CPIP participation came to an end in July 2015, Que began to use her CPIP network to expand her project through implementing the SSBOS algorithm beginning with CPIP faculty member, Elizabeth Mort, MD, Sr. Vice President of Quality and Safety at the MGH/MGPO, Chief Quality Officer MGH/MGPO and Sr. Medical Director for PHC. Mort facilitated an introduction for Que with David Chang, PhD, MPH, MBA, the Director of Healthcare Research and Policy Development in the Codman Center for Clinical Effectiveness in Surgery. Chang provided Que with access to a national surgical database and statistical consultation. Que also began working closely with Wilton Levine, MD, Associate Medical Director for Anesthesia, Critical Care and Pain Medicine. It was this connection that proved most fruitful for Que. Levine guided Que to find existing data and internal contacts who could help her advance her idea. He also suggested that Que become involved in the preparations for the new electronic health record, ecare, to make the SSBOS algorithm part of the new build in the OpTime module for the perioperative phases of care. ecare is PHC s version of the Epic Systems Corporation integrated, electronic health record that will be implemented across the entire Partners network by the end of Because ecare is a PHC-wide electronic medical record, any content developed for ecare integration must be reviewed and approved at the system level for all Partners entities that would be affected. The review panel for OpTime modifications is the Partners Perioperative Leadership Council (PLC). The PLC is composed of administrative and clinical leader representatives from all Partners entities that offer surgical services (MGH, North Shore Medical Center, Brigham and Women s Hospital, Brigham and Women s Faulkner Hospital, and Newton Wellesley), along with PHC ecare OpTime application leads.

4 Levine invited Que to present the SSBOS algorithm at the PLC quarterly meeting on September 21, 2015 (attachment EP 16b.c), where she received approval to proceed with integrating the Hopkins SSBOS algorithm into the new electronic health record. Levine then established a team for Que to work with to build the SSBOS algorithm into ecare s OpTime module for the April 2, 2016 go-live. Que was an integral member of the SSBOS team. An example of her participation on the SSBOS team can be found in attachment EP 16b.d. Que s involvement in developing the SSBOS algorithm as a decision-support tool in ecare meant that the impact of her work on perioperative blood preparation was health system-wide. The SSBOS algorithm was built to operate behind the user interface and suggests laboratory tests (Type & Screen; Type & Crossmatch; No Type & Screen or Type & Crossmatch) and the estimated number of units of blood needed for each surgical procedure. Typically, the next day s surgical cases are assigned to anesthesia providers each day by 3:00 pm. Since April 2, 2016, anesthesia providers log into ecare to review and prepare for the next day s schedule, where they see the SSBOS algorithm recommendations and patient preparation status. The screenshot below is from a test case of a patient scheduled for a colectomy. This image shows the view from ecare that anesthesia providers see when preparing for a case. When the anesthesia providers log into an assigned patient record, they are able to select SSBOS from a menu. The SSBOS screen (below) then appears and the suggested blood products for that patient are listed at the top (items in red outlined box). This particular patient was typed and screened in preparation for surgery with results appearing underneath the SSBOS, and two units of blood are listed as available at the bottom of the screen. ecare View of SSBOS Algorithm Recommendations for Anesthesia Providers SSBOS T&S Blood Order

5 Outcomes of CRNA Organizational Autonomy An example of Que applying the SBBOS in practice is seen in the anesthesia preprocedure view in ecare which highlights the individual autonomy of the CRNA in practice (attachment EP 16b.e). The surgical patient s physical assessment and the anesthesia plan for procedure are outlined and the use of the SSBOS to guide the plan is documented. Que s work to provide evidence-based guidelines to her CRNA colleagues has impacted their individual day-to-day practice of preprocedural blood preparation and ordering. In addition, Que s project to standardize surgical blood ordering and preparation has also demonstrated an impact at the MGH organization level. At the end of calendar year 2016, Que examined Blood Type & Screen order data from her CPIP project in patients undergoing laparoscopic hysterectomies from January 2014 to February 2015, comparing it with data for the same patient population and preoperative laboratory test following ecare implementation (April 2016 to November 2016) (attachment EP 16b.e). She found a dramatic decrease in the percentage of patients who had orders for Blood Type & Screen following the implementation of SSBOS in ecare. The frequency of Type & Screen orders for patients undergoing laparoscopic hysterectomy decreased from 86% to 27%. An additional benefit to this work is that there have been no serious adverse events related to transfusions in this surgical population since the algorithm was implemented.

6 As ecare is optimized, Que continues to work at the PHC system level to track surgical transfusion data as a process improvement project to analyze how the SSBOS algorithm results are being utilized. Planning is underway to educate additional departments, perioperative services, anesthesia and surgical teams in the consistent use of the SSBOS to make evidence-based transfusion preparation decisions for all common surgical procedures. Que persists in pursuing her system level long-term goal of optimizing the SSBOS algorithm using historical MGH transfusion rates to further improve patient care and the work environment by guiding clinician decision-making regarding the need for transfusions during surgery. The organizational autonomy that exists at the MGH enabled Que the autonomy and freedom to engage in a broad range of service line, organization, and system decision-making processes to improve patient care and evidence-based blood ordering and transfusion procedures across perioperative services in PHC.