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The Synergy Model: A solution for ratios

The Synergy Model: A solution for ratios. Rosalee Longmoore RN, SUN President CFNU ICN Workforce Forum 2012. The Ratio Debate. Research & Evidence. As a patient safety intervention, patient-to-nurse ratios of 4:1 are reasonably cost-effective (Rothberg, et al., 2005). .

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The Synergy Model: A solution for ratios

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  1. The Synergy Model: A solution for ratios Rosalee Longmoore RN, SUN President CFNU ICN Workforce Forum 2012

  2. The Ratio Debate

  3. Research & Evidence As a patient safety intervention, patient-to-nurse ratios of 4:1 are reasonably cost-effective (Rothberg, et al., 2005).

  4. Research & Evidence Hospitals may need to consider not only the ‘business case’ of increased costs for staffing but also the ‘social case’ in investing in additional nurse positions which are necessary for the quality caring of patients in order to reduce deaths, lengths‑of‑stay, and adverse patient outcomes (Needleman, et al., 2006).

  5. Research & Evidence Reduced patient mortality More time spent with patients Improved retention and recruitment (Aiken, 2010)

  6. Research & Evidence

  7. From the Nurse Perspective: • Inadequate staffing increases rate of burnout, job dissatisfaction & workplace injuries (McGillis-Hall, 2005) • 23% increase in nurse burnout for each patient above 1:4 ratio (hosp. average) • 15% increase in job dissatisfaction (Aiken, Clarke & Sloane, 2002)

  8. From Patient Perspective: • Lower MI mortality rates following implementation of mandated minimum ratios (increased RN hours/pt day) (Sochalski et al, 2008) • Each patient added to nurse’s workload resulted in: • 7% increase in “failure to rescue” • 7% increase in risk of mortality following common surgeries (Aiken, Clarke & Sloane, 2002)

  9. CFNU – Research to Action Nurse-Patient Ratio Project

  10. NPR Project Objectives • Maximize patient outcomes including safety & satisfaction • Maximize nursing & organizational outcomes, including enhanced retention & recruitment of nurses • Assess adequacy of daily staffing within a unit • Enable nurses to use professional judgment to help determine nurse-patient ratios • Provide opportunity for nurses to work at full competence/full scope • Improve the work environment to make SHR a “magnet” work environment • Create & test process for front-line nurses to develop & implement nurse-patient ratios • Establish mechanism ensuring nurse-patient ratio maintained & adjusted as required when patient needs/numbers change • Add to knowledge about impact of nurse-patient ratios

  11. Traditional Approach to Staffing • Based on habit, geography, intuition or task-based acuity tools “these systems typically include an inventory of tasks and the necessary amount of time required by nurses to accomplish each task.” (Curley, 2007, p. 14)

  12. Synergy Model

  13. Synergy Model • “describes a patient-nurse relationship that acknowledges the primary importance of nursing care based on the needs of the patients and their families” (Martha Curley 1998) • Recognizes that nursing is more that just tasks… context of nursing changes, the essence of nursing does not (Clifford, 2007. p. xxi)

  14. The Synergy Model has been used in… • Practice • Adult, pediatric and neonatal critical care practice & certification ACCN, 1998 • Guidance of Families Thorough System-Collopy, 1999 • CNS Practice Competencies-Moloney-Harmon, 1999 • Education • Facilitate Patient Outcomes by Link to Evidence-Kaplow & Hardin, 2007 • Evaluate Nose Competencies in Sedation Practices-Collins & Strother, 2008 • Curriculum base for Nurses and Nurse Practitioners-Pittsburg- Zungolo, 2004 • Administration • Link Nursing Care with Diagnostic Related Groups-Doble et al., 2000 • Create Magnet Hospitals -Kaplow & Reed, 2008 • Research • Compare CNS vs. NP Competencies- Brewer et al, 2007 • Study of spirituality in Nurses and Patients Smith, 2007 • PICU and NICU NP Competencies -Madden, 2009

  15. Synergy Model in Canada BCNU Provincial Nursing Workload Project • Dr. Maura MacPhee -lead academic for the project and developed a “toolkit” • Used patient characteristics to assess and respond to workload issues • Collected patient data to help inform staffing decisions • Began to develop guidelines around the decision making process (MacPhee et al, 2010. Nurs. Research) (BCNU Update, Feb, 2010)

  16. Patient Characteristics • Stability • Complexity • Vulnerability • Predictability • Resiliency • Participation in Care • Participation in Decisions • Resource Availability

  17. Stability • Ability to maintain a steady state of equilibrium physically and/or mentally including family or social stability • Includes response to therapies and health care interventions

  18. Stability • Level 1: Minimally Stable • Emergent interventions,recent, significant deterioration/change,not responding to treatments/interventions,labile &/or deteriorating v/s • Level 3: Moderately Stable • Urgent interventions,increased monitoring, subtle system changes, wavering V/S, some response to treatment • Level 5: Highly Stable • Constant (low risk of death), non-urgent interventions,low monitoring, improving systems, stable v/s, expected response to treatment

  19. Predictability • The expectation that a certain trajectory or path of events will occur during recovery from physically or psychologically based illness • Includes having complications resulting from underlying illness or treatments • Includes having diagnosis or therapies familiar to all staff involved in care

  20. Predictability • Level 1 Not Predictable • Uncommon pt population/illness,unusual/unexpected course, • Veered significantly from expected illness trajectory or pathway • Serious complications • Diagnosis is unfamiliar or unknown • Level 3 Moderate Predictability • Wavering,occasionally seen diagnosis/Pt population, • Some complications,diagnosis is not routine • Level 5 Highly Predictable • Common pt population/illness • No complications, following expected illness trajectory or pathway • Diagnosis is familiar and “routine” to staff

  21. Vulnerability • Susceptibility to actual or potential stressors that may adversely affect patient outcomes • Affected by physiological makeup, co-morbidities (underlying health problems or illnesses) or health promotion/health risk behaviours of the patient • Anticipatory assessment and management of risks impact recovery.

  22. Vulnerability • Level 1 Highly Vulnerable • Failure of compensation/coping, minimal reserves • Unable to mount a response (ex: malnourished, immunocompromised) • Unlikely to make fully recovery or return to baseline health/function • Inadequate or no social supports/coping mechanisms • Level 3 Moderately Vulnerable • Somewhat susceptible/somewhat protected • Some safety concerns, moderate risk for complications • Some social connections, some support access although difficult • Level 5 Minimally Vulnerable • Safe, out-of-the-woods, not fragile • Little to no risk of complications • Social connections, able to “take care of self”

  23. Resiliency • Patient’s capacity to return to a restorative level of functioning through use of physical and/or psychological compensatory coping mechanisms • Dependent upon their ability to rebound after an illness or injury • Can be influenced by many factors, including illness, age, co-morbidities, and intactness of compensatory mechanisms

  24. Resiliency • Level I: Minimally Resilient • unable to mount a response • failure of coping/compensation toward recovery • minimal reserves; brittle • Level 3: Moderately Resilient • Able to mount some response/compensation • some reserves • Slow recovery • Level 5 :Highly Resilient • Able to mount & maintain response /coping/compensation • Endurance • Good ability to rebound/recover

  25. Complexity • The intricate entanglement of 2 or more physiological or psychosocial systems of the patient, family dynamics, or environmental interactions • Includes co-morbidities or underlying/chronic illnesses • Includes how clearly an illness presents itself • Can include how complex the therapies involved in moving the patient towards recovery • The more systems involved, the more complexity affecting the patient

  26. Complexity • Level 1:Highly Complex • intricate, complex patient/family dynamics • atypical/vague presentation • multisystem involvement • Level 3:Moderately Complex • moderately involved patient/family dynamics • at least 2 systems involved • Level 5: Minimally complex: • straightforward; routine; simple/clear presentation • simple patient/family dramatics; single system involved

  27. Participation In Care • The level of engagement and capacity to participate in the delivery of care by a patient and their family • Influenced by the illness itself, understanding of illness or health promotion, resources available, personal experiences within health care, and information & teaching provided by the health care team

  28. Participation in Care • Level 1 No Participation • Pt/family unable to participate in care,“Total Care”, fully assisted ADL’s • needs extensive coaching, teaching, support to participate • family absent or cannot help,extensive discharge planning needed • Level 3 Moderate Participation • Pt/family need assistance with care,Assisted ADL’s,some coaching, • teaching, support needed to participate,some discharge planning needed • Level 5 Full Participation of Pt &/or family • Independent ADL’s,willing/available family,minimal coaching, teaching, support to participate,minimal discharge planning needed

  29. Participation in Decision Making • The level of engagement and capacity of the patient and/or their family to understand and make decisions • Influenced by understanding, life experiences, personal beliefs/values and inner strength and supports intimes of crisis

  30. Participation in Decision Making • Level 1: No participation • No capacity or desire to make decisions about health care • requires surrogacy from family and/or others for decisions about health care • Level 3:Moderate participation • limited capacity; seeks input/advice from others regarding health care decisions • Level 5:Full participation • full capacity and makes own decisions for health care

  31. Resource Availability • Extent of resources brought to the situation by the patient, family, and community • Can be technical, fiscal, personal, psychological, social, or supportive in nature • The more resources available, the greater the potential for a positive outcome

  32. Resource Availability • Level 1:Few resources: • knowledge, skills or finances not available • Minimal psychological supports • Few social system resources • Level 3: Moderate resources • Limited knowledge, skills or finances • Limited psychological supports • Limited social system resources • Level 5:Many resources • Extensive knowledge, skills or finances • Available and strong psychological supports • Strong social system (family/community) resources

  33. Nurse Characteristics • Clinical Judgment • Clinical Inquiry • Caring Practices • Response to Diversity • Advocacy • Facilitation of Learning • Collaboration • SystemsThinking

  34. Synergy-based Scoring Tools • Each patient scored every shift • by RN/LPN caring for them • Patient scores used to calculate • staffing needs & inform • patient assignments

  35. How will Synergy Staffing Tool work? • Take existing patient data…(things we talk about in report already)

  36. How will score link to staffing? • Patients with low scores have higher needs • More Acuity-experienced RN care • More complexity-takes more time • More vulnerability-needs continual surveillance (“nurse vigilance”) • Lack of Capacity-needs collaborative team • “extensive family nursing”

  37. Impact of RTA Project on Patients • Patient viewed holistically (Acuity & Capability) • Quicker, more accurate assessment • Assignments based on patient need • Increased safety • Appropriate care provider • Improved communication • Positive patient outcome trends noted

  38. Impact of Project on Nurses • Common language • Promoted critical thinking • Visible process for identifying staffing needs • Provided additional staff for patient volume/need • RTA Clinical Resource Nurse • Staff engagement in collaborative decisionmaking • Staff involvement & growth

  39. Resources • Aiken, L. H., Sloane, D. M., Cimiotti, J. P., Clarke, S. P., Flynn, L., Seago, J. A., Spetz, J. and Smith, H. L. (2010). Implications of the California Nurse Staffing Mandate for Other States. Health Services Research, 45: 904–921. • Aiken L. Economics of nursing. Policy, Politics & Nursing Practice. 2008;9(2):73–79. • Aiken, L.H., Clarke, S.P., Sloane, D.M., Sochalski, J., & Silber, J.H. (2002). Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. Journal of the American Medical Association, 288(16), 1987-1993. • Blegen, M.A., Goode, C.J., & Reed, L. (1998). Nurse staffing and patient outcomes. Nursing Research, 47(1), 43-50. • Bolton, L.B., Aydin, C.E., Donaldson, N., Brown, D.S., Sandhu, M., Fridman, M., & Aronow, H.U. (2007). Mandated nurse staffing ratios in California: A comparison of staffing and nursing-sensitive outcomes pre- and post-regulation. Policy,Politics and Nursing Practice, 8(4), 238–250.

  40. Resources • Cavouras. (2002) Nurse Staffing Levels in American Hospitals. Journal of emergency nursing: JEN : official publication of the Emergency Department Nurses Association 28(1), 40-3. • Curtin, L. (2003). An Integrated Analysis of Nurse Staffing and Related Variables: Effects on Patient Outcomes. Online Journal of Issues in Nursing 8(3). • Gordon S. Buchanan J. & Bretherton T. (2008). Safety in Numbers Cornell University Press. • Jawad, Scalzi, Sasichay-Akkadechanunt. (2003). The Relationship between Nurse Staffing and Patient Outcomes. The Journal of Nursing Administration, 33(9), 478-485. • Needleman, J., P. I. Buerhaus, M. Stewart et al. (2006). Nurse Staffing in Hospitals: Is There a Business Case for Quality?Health Affairs (Millwood) 25 (1): 204–11. •  Needleman, J., Buerhaus, P., Mattke, S, Stewart, M., & Zelevinsky, K. (2002) Nurse-staffing levels and the quality of care in hospitals. New England Journal of Medicine, 346, 1715-1722.

  41. Resources • New England Public Policy Center [NEPPC] & Massachusetts Health Policy Forum. (2005). Nurse-to- Patient Ratios: Research to Reality. Concert report series 05-1, July 2005. • Sales, A. et al. (2008). The association between nursing factors and patient mortality in the Veterans Health Administration: The view from the nursing unit level. Medical Care, 46(9), 938-945. • Seago, J. A., Spetz, J., Coffman, J., Rosenoff, E., & O'Neil, E. (2003). Minimum staffing ratios: the California workforce initiative survey. Nursing Economics, 21, 65-70. • Shuldham, C.; Parkin, C.; Firouzi, A.; Roughton, M.; Lau-Walker, M. The relationship between nurse staffing and patient outcomes: A case study. International Journal of Nursing Studies. 46(7), 986-992. • Sochalski J, Konetzka RT, Zhu J, Volpp K. (2008). Will Mandated Minimum Nurse Staffing Ratios Lead to Better Patient Outcomes? Med Care. 46(6):606-13.

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