Driving Patient Care with Evidence-based Professional Practice Mary L. Hook, PhD, APRN, BC

Transcription

1 Automated Care Planning: Driving Patient Care with Evidence-based Professional Practice Mary L. Hook, PhD, APRN, BC

2 Program Objectives: Review the basic tenets of professional nursing. Describe how to identify current best evidence to support nursing practice. Share a vision for infusing evidence-based nursing content within the workflow to support clinical decision-making, populate data repositories, conduct analyses, and improve patient care across the health care continuum.

3 Current State of the Patient Care Environment Health care costs continue to rise Increasing pressure to link health care reimbursement to quality indictors Inefficient and ineffective use of our limited and most valuable resource: Nurses Much time is spent away from the bedside

4 Current State of the Patient Care Environment (continued) Competing demands for standardization vs. individualization Clinical information system (CIS) growing pains Data rich but interpretation poor Limited focus on patient s plan of care

5 Increasing Patient Complexity

6 Challenge for Nursing Leaders Where do you start

7 All who have accomplished great things have had a great aim, have fixed their gaze on a goal which was high, one which sometimes seemed impossible. Orison Swett Marden ( ) Founder of Success Magazine

8 Return to the Basics of Professional Nursing Practice Improve patient care (right thing to do) Help nurses to focus on most important things Achieve legal & regulatory requirements American Nurses Association (2004) Nursing*: Scope and Standards of Practice *Registered Nurses & Advanced Practice RNs

9 American Nurses Association (ANA, 2004) Standards of Practice for Nurses The science of nursing is based on a critical thinking framework, known as the nursing process... These steps serve as the foundation of clinical decisionmaking and are used to provide evidence-based practice. (ANA, 2004, p )

10 American Nurses Association (ANA, 2004) Standards of Practice for Nurses Registered nurses prepare themselves to be resourceful, to respond to the challenges of delivering nursing care to individuals and communities, to incorporate technology into their art of caring, and to remain visionaries as the future unfolds. (ANA, 2004, p. 17)

11 3 Key Tenets to Drive Change Standards for Practice: Nursing process Standards for Performance Evidence-based Practice

12 American Nurses Association (ANA, 2004) Standards of Practice for Nurses Six Standards of Practice Assessment Diagnosis (based on assessment data) Outcome Identification Planning Implementation Evaluation

13 American Nurses Association (ANA, 2004) Standards of Practice for Nurses Nine Standards of Professional Performance Quality of Practice Education Professional Practice Evaluation Collegiality Collaboration Ethics Research Resource Utilization Leadership

14 Technology must support Nurses to Provide Individualized Patient Care Assessments that drive diagnoses and the rest of the plan of care Decision support Retrievable data Real time documentation Computerized care planning

15 What is Evidence-Based Practice? Evidence-Based Practice (EBP) incorporates all the components for quality patient care: Best research evidence Clinical expertise Patient values Institute of Medicine. Crossing the Quality Chasm, (2001), p. 47.

16 Nurses Readiness to Engage in Evidence-Based Practice What does it take for Nurses to be READY? Awareness of the need for information Ability to identify needed information Ability to search available resources Ability to apply the information/evidence to practice Pravikoff, Pierce & Tanner. (2003)

17 A Dilemma... Finding the best referential evidence Copyright 2004 CINAHL Information Systems

18 Sources of Evidence Research (systematic, new knowledge) Synthesized evidence reviews Published consensus guidelines Expert opinion Practice-based evidence (quality improvement projects) Note: All sources must be evaluated for relevance, currency, & methodological quality

19 Evaluating the Evidence Sample (size, generalizability) Design Measures Analysis

20 Evidence Rating Systems Melnyk & Fineout-Overholt (2005, p. 10) Level I: Level II: Level III: Level IV: Level V: Level VI: Systematic reviews or meta-analyses of randomized control trials (RCTs) or clinical guideline based on systematic review of RCTs Evidence from at least one well-designed RCT Evidence from well-designed controlled trials without randomization Evidence from well-designed case-control or cohort studies Evidence from systematic reviews of descriptive and qualitative studies Evidence from single descriptive or qualitative study Level VII: Evidence:opinion of authorities &/or expert committees

21 Issues regarding the Application of Evidence to Drive Practice Example: Risk for Falling in Acute Care

22 Fall Prevention Research Issues Fall Prevention is a frequent topic in both practice and research literature; however, authors often mix evidence across venues 1 in 3 older adults over 65 yrs have fallen (community) Literature is focused on identifying at-risk patients Many tools with untested reliability and validity Missing links between risk assessment and intervention Limited intervention studies Primarily tested with older adults on extended stay units Studies are not designed to provide conclusive evidence (multi-factorial interventions, small sample size)

23 Fall Prevention Research: To Apply or Not Apply... To Practice Example Citation: Meade, C. M., Bursell, A. L., & Ketelsen, L. (2006). Effects of nursing rounds on patients' call light use, satisfaction, and safety. American Journal of Nursing, 106(9), 58-70; quiz Note: Author is using this paper to demonstrate how to systematically evaluate research results for application to practice.

24 An Overview of the Meade Study AIM: To determine the frequency of and reasons for patients call light use, the effects of 1-hour & 2- hour nursing rounds on patients use of the call light, and the effects of rounding on patient satisfaction and patient safety DESIGN: Quasi-experimental SAMPLE: 27 nursing units in 14 hospitals with non-random assignment (19 units excluded) INTERVENTION: Rounding Protocol (over 24 o ) OUTCOMES: Call light frequency, reasons for use, patient satisfaction, patient safety ( rate of falls measured as number of falls )

25 Analysis of the Study Conducted at the level of the nursing unit Design limitations (threats to validity) High rate of unit exclusion from analysis for poor adherence to protocol (19/46)

26 To Apply or Not Apply... To Practice Rounding protocol includes 6 items that have been recommended by fall prevention experts No previous research linking rounding with fall reduction No report of patient characteristics or fall risk assessment findings Safety outcome measure: - No mechanism to ensure accuracy of outcome - Outcome = Number of falls in 4 weeks prior to study vs. number during 4 week study, by rounding group

27 Conclusion: To Apply or Not Apply...? Meade, et al. (2006) was a quasi-experimental study and showed that rounding reduced call light use and increased patient satisfaction Study was not designed to evaluate fall outcomes Concerns: The evidence may not be strong enough No evidence to support use of rounding to reduce falls If implemented, fall risk & actual falls should be measured to determine if fall events are affected by rounding Evidence poses questions about the effect of routine 2 hour rounding (a commonly recommended, expert opinion-based fall reduction strategy) Good source of a structured protocol for replication research

28 VISION Think out a few years What does 2012 look like to you? Will we have leveraged science, information technology, and practice?

29 Aurora-Cerner-UWM Knowledge-Based Nursing Initiative A Partnership funded by: Aurora Health Care (A) Cerner Corporation (C) University of Wisconsin Milwaukee College of Nursing (W) Norma M. Lang, RN PhD FAAN FRCN Principal Investigator/ Project Leader Wisconsin Regent Distinguished Professor Aurora Professor of Health Care Quality and Informatics University of Wisconsin Milwaukee College of Nursing

30 The ACW Partnership Goal: To infuse research/evidence-based nursing content within the workflow to support clinical decision making, populate data repositories, conduct analyses, and improve patient care across all venues. Goal Knowledge-based Nursing Initiative Aurora Cerner UWM Integrated health system, nursing results Application solutions, knowledge tools Education, research and practice college University of Wisconsin & Aurora Health Care. Used with permission.

31 Creating Evidence that Nurses IMPACT Patient Outcomes Nursing management of patient problems (nursing process) Key outcomes driven by nurses: Quality Length of Stay Readmission Patient Satisfaction

32 Making the Nursing Process Visible in the Clinical Information System (CIS) Nursing Process (ANA) Location of Data in the CIS 1) Assessment Assessment 2) Diagnosis Diagnosis/Problem List 3) Outcome Identification Outcomes 6) Evaluation (Identify & Evaluate over time) 4) Planning Interventions 5) Implementation (Prescribe/Implement over time) University of Wisconsin & Aurora Health Care. Used with permission.

33 Conceptual Framework: Knowledge-Based Nursing Initiative (KBNI) Integrated Healthcare System & Community (Patients/ Clinicians) Actionable Interdisciplinary Knowledge Clinical Information System & Infrastructure (Decision Support / Documentation) Referential Interdisciplinary Knowledge Patient Assessment Nursing Diagnosis Nursing Intervention Nurse- Sensitive Outcome Clinical Knowledge Management Clinical Data Repository Research QI Reports Terminology Management Data Warehouse University of Wisconsin & Aurora Health Care. Used with permission.

34 Using KBNI as the Basis for Practice Key Features: Assessments drive clinical decision-making (diagnosis) and support nurses in using evidence, expertise, & patient preference to individualize care. Transformation involves: Redesigning nursing workflow Renewing focus on planning patient care Removing unnecessary and duplicative work Constructing nurse-sensitive elements to support data retrieval for evaluation & research University of Wisconsin & Aurora Health Care. Used with permission.

35 Gathering Referential Knowledge Evidence Table Format Citation Question / Topic, Sample, Setting Type of Evidence Findings re: Patient Assessment Key Findings related to Practice Findings re: Problem Nursing Identification Diagnosis / Nsg. Diag. Findings re: Nursing Intervention Findings re: Nurse-Sensitive Sensitive Outcome Findings re: Background Significance of Problem University of Wisconsin & Aurora Health Care. Used with permission.

36 Rating the Strength of Evidence Supporting Recommendations Level I Systematic review, meta-analysis, or practice guideline based on RCTs Level II Well-designed randomized clinical trial Level III Well-designed controlled trials without randomization (single/reviews) Level IV Well-designed case-control and cohort studies Level V Systematic review or meta-analysis of descriptive or qualitative studies Level VI Well-designed descriptive, qualitative, or psychometric studies Level VII Opinion of authorities or experts Level VIII Common practice (clinical articles or textbooks) Modified from the rating system by Melnyk & Fineout-Overholt (2005) by E.C. Devine (2007) University of Wisconsin & Aurora Health Care. Used with permission.

37 Developing Referential Knowledge Synthesis Summary Table with Key Recommendations Phenomenon of Concern: Patient assessment o Recommendation o Rationale o References Diagnosis/Problem Identification o Recommendation o Rationale o References Interventions o Recommendation o Rationale o References Nurse-Sensitive Outcomes o Recommendation o Rationale o References INTERVENTION RECOMMENDATION #1 For all patients who are determined to be high risk for falls using a valid and reliable fall risk screening tool, do... (when) Strength of Evidence Supporting Recommendation: Level IV Rationale: In studies that have been conducted in acute care settings with patients who are determined to be high risk for predicted physiological falls... this intervention has been tested... References (with type of evidence) University of Wisconsin & Aurora Health Care. Used with permission.

38 Designing & Embedding at the Point of Use Assessments Nursing Diagnosis Nursing Outcomes Nursing Interventions University of Wisconsin, Aurora Health Care & Cerner Corporation. Used with permission.

39 Designing & Embedding at the Point of Use Example: Documented Change in Assessment Triggers an Alert Assessment drives Reevaluation of Risk with Plan Update University of Wisconsin, Aurora Health Care & Cerner Corporation. Used with permission.

40 Lessons Learned: Overarching Principles for Redesign 1. Professional nursing is based on the nursing process for patient care 2. Terms and definitions must be standard (Best practice and retrievable/coded in CIS) 3. Data entry must be efficient at point of care 4. CIS must support clinical decision-making (not solely for documentation) 5. Clinical information system must support the retrieval of data 6. Data must be used to guide improvements

41 Identify Nursing Impact on Outcomes (Pay for Performance) Patient Assessment Nsg. Diagnosis/ Problem Identification Selection of Nursing Intervention Focused Assessment Related to PoC Nurse-Sensitive Outcome Assessment CMS/ JC / Premier/ ANA-NDNQI / NQF / IHI Discharge Instruction Mortality LOS Readmission Rate University of Wisconsin & Aurora Health Care. Used with permission.

42 Research Opportunities: Clinical Data Entry, Storing, Transfer, and Retrieval Patient Assessment Integrated Healthcare System (Patients/ Clinicians) Nursing Diagnosis Data Entry Nursing Intervention Nurse- Sensitive Outcome Data Retrieval Outcomes Evaluation, Research, QI, & Reports Data Retrieval Clinical Data Repository Data Transfer Data Warehouse Data Storing University of Wisconsin & Aurora Health Care. Used with permission.

43 The Challenge... It is an immense challenge to identify evidence-based knowledge, transform it for use in everyday practice and embed it in an electronic information system. It is how we will recognize and measure the value of nursing care as it impacts patient outcomes. Norma Lang, PhD, RN, FAAN, FRCN Distinguished Professor University of Wisconsin-Milwaukee Project Leader, ACW Knowledge-based Nursing Initiative

44 Acknowledgement & Thanks Many ACW team members have contributed to this effort: UWM College of Nursing Norma Lang Sally Lundeen Elizabeth Devine Tae Youn Kim Amy Coenen Lenore Wilkas Kay Jensen Cerner Corporation: Paul Gorup Ellen Harper Roy Simpson Jennifer Conner Sharon Massa Tera Watkins Laura Crozier Linda Peters Sue Ela Karlene Kerfoot Laura Burke Judy Murphy Mary Hook Beth Johnson Amy Olson Florence Mielcarek Judy Burke Lynn Germanson Sharon Traxel Lori Zareczny Sue Gradus Eileen Marks Cheryl Blascoe Caye Wendt Aurora Health Care Mary Hagle Karen Fiorelli Patti Senk Kathy Bobay Jan Mills Ken Uecker Adrienne Bancroft Kathleen Gall Deborah Segrin Mary Lou Hoffmann Lee Jeske Plus many others No part of this slide presentation may be duplicated, presented, published, or disseminated without expressed written permission. These slides are used with permission.

45 Thank You Questions?

46 References American Nurses Association. (2004). Scope and Standards of Practice. Washington, DC: Author. Devine, E.C. (2007). Evidence rating system in the Knowledge-Based Nursing Initiative Protocol. Unpublished manuscript. University of Wisconsin-Milwaukee. Hook, M. L., Devine, E. C., & Lang, N. M. (in press). Using a computerized fall risk assessment process to tailor interventions in acute care. In K. Henriksen, J. B. Battles, M. A. Keyes & D. I. Lewin (Eds.), Advances in Patient Safety: New Directions and Alternative Approaches. Washington, DC: Agency for Healthcare Research and Quality. Institute of Medicine. (2001). Crossing the Quality Chasm: A New Health System for the 21st Century. National Academies Press. Lang, N.M., Hook, M.L., Akre, et al. (2006). Translating knowledgebased nursing into referential and executable applications in an intelligent clinical information system (pages ). In C. Weaver, C. Delaney, P. Webber & R. Carr (Eds.). Nursing and Informatics for the 21st Century: An International Look at Practice, Trends and the Future. Chicago, IL: Healthcare Information and Management Systems Society (HIMSS).

47 References Meade, C. M., Bursell, A. L., & Ketelsen, L. (2006). Effects of nursing rounds on patients' call light use, satisfaction, and safety. American Journal of Nursing, 106(9), 58-70; quiz Melnyk, B., & Fineout-Overholt, E. (2005). Evidence-based Practice in Nursing & Healthcare. NY: Lippincott Williams and Wilkins. Pravikoff, D.S., Pierce, S.T., Tanner, A. (2003). Are nurses ready for evidence-based practice? American Journal of Nursing, 103: