discovering and shaping a career in public health and health policy jack needleman, phd faan...
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Discovering and shaping a career in public health and health policy
Jack Needleman, PhD FAANDepartment of Health Policy and Management
UCLA Fielding School of Public Health
October 15, 2013
A brief bio
Education BS, City College, 1969, Political Science MA, Syracuse University, 1972, Political Science PhD, Harvard University, 1995, Public Policy
Employment Lewin and Associates, 1973-1990
Health Policy research and consulting firm Harvard School of Public Health, 1995-2003
Department of Health Policy and Management University of California Los Angeles SPH, 2003-Present
Along the way
17 years in health policy consulting Adjunct teacher at Georgetown U and American U 3 first authored articles designated patient safety classics
by US Agency for Healthcare Research and Quality Additional patient safety classic 100+ journal publications
First AcademyHealth Health Services Research Impact Award for research on quality of care and nurse staffing
Asked to evaluate process improvement initiative Honorary Fellow of American Academy of Nursing Elected member of the Institute of Medicine Extensive experience on advisory committees for National
Quality Forum, Joint Commission, Centers for Medicare and Medicaid Services and others
Partly planning, much serendipity
Three first authored patient safety classics
Needleman, Buerhaus et al., “Nurse Staffing-Levels and Quality of Care in Hospitals,” New England Journal of Medicine, 2002
Needleman, Buerhaus et al., “Nurse Staffing in Hospitals: Is there a Business Case for Nursing,” Health Affairs, 2006
Needleman, Buerhaus et al., “Nurse Staffing and Inpatient Hospital Mortality,” New England Journal of Medicine, 2011
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NURSING MATTERSNurses Impacts on Patient Outcomes
Nurses’ work is core function of hospital care Have outpatient surgery, imaging, labs, therapy Only reason patient is hospitalized is they need nursing care
Range of outcomes influenced by nurse staffing reflect range of nurses’ work Delivering ordered care Assessment and monitoring Timely and appropriate intervention Coordination and patient management Patient education
Because nurses involved in all aspects of care, interacting with other care givers, identifying the contribution of nursing to care, safety, quality, efficiency is difficult to parse out
Sample: Low and High Staffed Hospitals Needleman/Buerhaus
Low High
Hospitals 399 400
Beds 201 252
Census 126 149
Licensed hours per day 7.5 10.4
Aide hours per day 2.3 2.6
RN as % Licensed 84% 90%
Staffing Specifications
5 Models * 2 (With & without interactions)
RN hours LPN hours Aide hours (+interact’ns)
Total hours RN %, LPN %
Total hours RN% Aide %
Lic’d (RN+LPN) hrs RN%Lic Aide hrs
RN hrs NonRN hrs Aide%NonRN
When appropriate model is uncertain, look for robustness in results
Outcomes Associated with NursingNeedleman/Buerhaus simulation results
Outcome Models Impact of High RN
Impact of High All
LOS 8 of 10 3-6% 3-12%
Urinary Tract Infection 6 of 10 4-12% 4-25%
Pneumonia 3 of 10 3-8% 2-17%
Upper GI Bleed All 5% 3-10%
Shock 4 of 10 6-10% 7-13%
Failure to Rescue (Surg)
5 of 10 4-6% 2-12%
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The Business Case for Quality
Discussions of the business case key off Leatherman, Berwick et al, Health Affairs, 2003
“A business case for a health care improvement intervention exists if the entity that invests in the intervention realizes a financial return on its investment in a reasonable time frame, using a reasonable rate of discounting. This may be realized as “bankable dollars” (profit), a reduction in losses for a given program or population, or avoided costs. In addition, a business case may exist if the investing entity believes that a positive indirect effect on organizational function and sustainability will accrue within a reasonable time frame.”
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Needleman, Buerhaus, Business Case for Nursing
Needleman, Buerhaus, NEJM, 2002 examined two dimensions of staffing Hours/patient day RN/LPN mix
Wide variation across hospitals Robust association of staffing variables and outcomes for:
Medical patients: length of stay, urinary tract infection, pneumonia, upper GI bleeding
Surgical patients: failure to rescue Incorporated results into business case analysis in Health
Affairs, 2006 by estimating impact of moving lower staffed hospitals up
Updated in Needleman, PPNP, 2008, “Is What's Good For The Patient Good For The Hospital? Aligning Incentives And The Business Case For Nursing”
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Avoided Days and Adverse Outcomes Associated with Raising Nurse Staffing to 75th PercentileEstimates from Needleman/Buerhaus, Health Affairs, 2006
Raise RN
Proportion
RaiseLicensed
Hours Do Both
Avoided Days 1,507,493 2,598,339 4,106,315
Avoided Adverse OutcomesCardiac arrest and shock, pneumonia, upper gastrointestinal
bleeding, deep vein thrombosis, urinary tract infection 59,938 10,813 70,416
Avoided Deaths 4,997 1,801 6,754
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SOCIAL AND BUSINESS CASE FOR NURSINGNet Cost of Increasing Nurse Staffing Estimates from Needleman/Buerhaus, Health Affairs, 2006
Raise RN Proportion
Raise Licensed
Hours Both
Cost of higher nursing $ 811 Million $ 7.5 Billion $ 8.5 Billion
Avoided costs (full cost) $ 2.6 Billion $ 4.3 Billion $ 6.9 Billion
Long term cost increase ($ 1.8 Billion) $ 3.2 Billion $ 1.6 Billion
As % of hospital costs -0.5% 0.8% 0.4%
Short term cost increase (save 40% of average) ($ 2.4 Billion) $ 5.8 Billion $ 5.7 Billion
As % of hospital costs -0.1% 1.5% 1.4%
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Conclusions from this analysis
Increasing proportion of RNs without increasing hours recovers its costs, even considering only variable costs Economic case Whether business case depends on whether hospital retains
savings For other two options, net costs are not recovered via
direct patient care savings But cost increases are relatively small, 1.5% if only variable
costs recovered, 0.4-0.8% if fixed costs recovered Context: MedPAC suggested 1-2% of Medicare payments
be set aside for performance incentives
Objectives
Address concerns raised about prior studies that questioned relationship of staffing and patient outcomes, including mortality: Cross-sectional studies comparing high and low staffed
hospitals Not clear that adverse outcomes associated with nursing
or unmeasured variables correlated to nursing Rough match to concept of “short staffed”
Imprecise nurse staffing measurement Lack of adjustments for patient acuity
Funded by the Agency for HealthCare Research & Quality
We address these challenges by
Examining association between mortality and day-to-day, shift-to-shift variations in staffing at the unit level and individual patient experience of “low” staffing
Conducting study in a single institution that has: lower-than-expected mortality high average nurse staffing levels recognized for high quality by the Dartmouth Atlas, rankings
in U.S. News and World Report, and Magnet hospital designation.
Including extensive controls for potential sources of an increased risk of death Patient diagnosis and surgical status Patient demographics Unit admitted to
Key findings – Patient Mortality
Increased risk of patient mortality significantly associated with: Patient’s exposure to shifts 8 hours or more below target
2% increase in risk/below target shift Patients exposure to high turnover units
4% increase in risk/high turnover shift Robust to alternative specifications
Even in a high quality hospital that generally meets its’ targets and manages patient turnover, and extensive controls for the influence of other factors, we still could detect the effects of staffing and high pt turnover
Implications for Hospital Management
No free passes for hospitals with high average staffing Need to strive to hit targets every shift
Findings should also apply to hospitals less successful in routinely meeting nursing needs of patients Patients at higher average risk
Operational implications Nursing service line, not just cost center Need systems for:
Identifying target staffing Managing staffing against target Staffing for anticipated turnover Smoothing turnover