Nurse Staffing and Patient Outcomes
Study Workgroup – Workgroup Summary
Overview
In October 2013, the Minnesota Department of Health (MDH) convened a workgroup to consult with
MDH on the legislatively required study of the correlation between nurse staffing and patient outcomes.
MDH sought advice in these main areas:
• Study methodology (including whether the study is conducted across patient groups or across
institutions, whether and how to control for external factors such as acuity, etc.);
• Metrics of patient outcomes to be considered in the study;
• Data necessary and reasonably available for analysis; and
• Level of data granularity (such as shift, unit, or daily averages) and licensure levels.
The workgroup met five times from October 2013 to March 2014, providing MDH with expertise and
perspective that helped MDH shape the study. This document provides a high-level summary of the
workgroup’s discussions and advice 1. The summary provided here does not represent consensus among
all workgroup members—consensus was not the goal of the group’s work. In fact, MDH benefited from
the diversity of perspective and wide range of advice provided by the group.
MDH thanks the workgroup members for their work and for their shared commitment to quality and
patient outcomes.
Workgroup Members
Workgroup members represented a range of perspectives and areas of expertise. Members included:
Ms. Shirley Brekken, RN, Executive Director - Minnesota Board of Nursing
Dr. Connie Delaney, PhD, RN, Dean - University of Minnesota School of Nursing
Ms. Marie Dotseth, MHA, Executive Director - Minnesota Alliance for Patient Safety
Ms. Linda Hamilton, RN, President/RN - Minnesota Nurses Association/Minneapolis Children's
Hospital – NICU
Ms. Betsy Jeppesen, RN, Vice President, Program Integrity - Stratis Health
Dr. Sandra "Mac" McCarthy, DNP, Chief Nursing Officer - Essentia Health - East Region
Dr. Christine Milbrath, RN, EdD, Assoc. Professor, Graduate Programs Director - Metropolitan
State University
Dr. Steven Mulder, MD, President and CEO - Hutchinson Health
Ms. Maribeth Olson, MA, Chief Nursing Officer - Mercy Hospital - Allina Health
Mr. Robert Pandiscio, RN, Staff Specialist - Minnesota Nurses Association
Dr. Sandy Potthoff, PhD, Associate Professor - University of Minnesota School of Public Health
Mr. Eric Tronnes, RN, Staff nurse, Ortho/Board member - Abbott Northwestern/M Nurses
Association
Ms. Vonda Vaden Bates, Senior Consultant, Patient Representative
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Additional information about the workgroup is available at
http://www.health.state.mn.us/divs/hpsc/hep/nursestudy/wkgrpmeetings.html.
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Workgroup Process
The Nurse Staffing Levels and Patient Outcomes Study Workgroup began its work in the fall of 2013.
The group was comprised of individuals who brought a strong background and expertise on
methodological issues, held operational knowledge, and had a deep understanding of data that might be
useful for the study of nurse staffing and patient outcomes. MDH retained a professional facilitator to
assist in developing the workgroup process and to facilitate the group’s meetings.
The group used the five meetings and the time between meetings to enrich their understanding of the
study complexities, provide information and resources, and to advise MDH on the study. The group
process was divergent for the most part—much of the workgroup’s time was spent identifying the
complexities of nurse staffing outcomes, confounding factors, and patient outcomes.
The work of the group began with review of the workgroup charter authored by MDH. The charter
facilitated a shared understanding of the study considerations and the workgroup’s scope. Along with
the charter, MDH shared a timeline showing how the timing of the workgroup aligned with the research
and writing necessary to complete the legislative report.
To illustrate the complexity and connections of the data components relevant to the study, MDH drafted
a conceptual framework. This framework became the foundation for the work of the workgroup
through the first few meetings. The workgroup formed three subgroups to discuss how to best
represent the components in the study.
1. Administrative: unit of measurement and type of nursing staff
2. Patient care: patient acuity, demographics, coverage
3. Patient outcomes: patient turn over, other workload factors and nurse sensitive hospital care
indicators & other hospital quality indicators
After considering the components of the conceptual framework, the group heard from two presenters.
The first presenter was Diane Twedell, DNP, RN, CENP, Chief Nursing Officer of the Mayo Clinic Health
System (MCHS), Southeast MN Region. Ms. Twedell presented on the MCHS patient acuity system and
how MCHS utilizes the system to manage their nurse staffing. Second, the group heard from Mark
Sonnenborn, MS, FACHE, VP, Information Services of the Minnesota Hospital Association (MHA). Mr.
Sonnenborn presented information on how the MHA intended to report nurse staffing plan data to
meet the requirements of the 2013 Staffing Plan Disclosure Act.
While considering the advice provided by the workgroup (described below), MDH researched the
availability of data for the study. MDH presented information to the group regarding the availability of
data on staffing and patient outcomes, data about confounding factors, and differences in chronological
alignment of staffing data and outcome data. MDH proposed a staged study approach to the workgroup.
The proposed study contained three phases, with different data options for each stage:
1. Short term (April – June 2014)
Part 1: Preliminary description of nurse staffing variation in Minnesota
Part 2: Preliminary analysis of the relationship between staffing and patient outcomes data
2. Medium term (July – October 2014)
Part 1: Further description of nurse staffing variation in Minnesota
Part 2: Nurse staffing & patient outcomes: important related factors & analytical options
3. Potential long term (2015 and beyond)
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Members were asked to provide their advice to MDH on the proposed study approach and on the
different options for data within each phase. Their advice is summarized below.
Advice on data sources and other considerations
The legislation requiring the MDH study presents this research question: “What is the relationship
between nurse staffing and patient outcomes?” Though this formulation suggests that a connection
between data on staffing and data on patient outcomes could be relatively straightforward, MDH and
the workgroup agreed that there are many potential questions about the basic data elements and many
potentially confounding variables.
Sources of nurse staffing data
The workgroup offered several potential sources for nurse staffing data:
• Payroll systems, unit schedules, or staffing plans
• EMR systems (which may offer proxy measures of staffing)
• Minnesota Hospital Association (MHA) staffing plan data
• Hospital Annual Reports
• Bargaining units
Sources of outcomes data
The workgroup discussed several options for patient outcome data (some are sources of existing data;
some are frameworks for collection of data):
• Hospital claims data
• Hospital Adverse Events Data; Hospital Administrative Discharge Data
• Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS)
• Quality measures, such as those developed by:
o Agency for Healthcare Research and Quality
o American Nurses Association database of Nurse Quality Indicators
o National Quality Forum
o MHA Hospital Engagement Network
Other important factors that contribute to patient outcomes
The workgroup identified many factors—in addition to staffing patterns—that impact patient outcomes.
The group generally agreed that these confounding variables are important but may be difficult to
incorporate in the present study.
Variations among patients
• Demographics
• Differences in patients and families as people (health history, social dynamics, etc.)
• Patient distribution, flow, turnover, and readmissions vary widely
• Patient acuity (and these differences may not be adequately captured by electronic systems)
Variations among hospitals (and units within hospitals)
• Organizational culture
• Geography (urban, rural, suburban)
• Physical space and layout
• Available technologies (both patient care and administrative)
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Organizational structure and hierarchy
Administrative practices, including use of float nurses
Available supports and specialties (such as wound care consults, therapy teams, transport
teams)
Use of rapid response teams instead of nurses stationed on the floor
Work environment (including risk awareness, patient safety awareness, nurse autonomy, and
teamwork)
Approach to staffing and scheduling—the method may be in an experienced scheduler’s head or
run through an acuity system
Variation among individual nurses (including the amount of experience, education, and
expertise)
Considerations regarding data sources
The workgroup discussed these considerations:
• Averages or overall staffing ratios can mask wide variation in staffing practices.
• The distinction between RNs and other staff is important.
• The whole care team is relevant to patient care.
• Shift variation is relevant (both in terms of length of shifts and workload patterns on shifts).
• The type of work a nurse does on the floor can be different on any given day.
• National standards for data collection for some important elements (nurse experience and unit
types, as examples) are in development.
• Using case-mix data could help adjust staffing data.
• Analysis of diagnostic codes can help determine patient complexity.
Key challenges
In their first months of work, the workgroup reflected on several important issues for the study (these
are topic areas that the group discussed, not consensus positions of the workgroup):
• It will be challenging to connect staffing data to outcome data in a meaningful way. Examples:
o Staffing data would be by unit, but data on outcomes are often reported at the hospital
level.
o Adverse health events are relatively infrequent, so it may be difficult to develop a large
enough data set for comparison to staffing patterns.
• Alignment of timing of outcomes data (nurse sensitive indicators) and staffing data will be a
challenge.
• Some reported outcomes may have no connection to the patient’s current or discharge unit (a
skin problem, for example); some serious conditions develop over time.
• Data on staffing, outcomes, and patient acuity are inconsistent across hospitals (particularly
with regard to level of detail of data and criteria for collecting and reporting data).
• The Minnesota Hospital Association data will be aggregated, which may impede detailed
analysis of staffing and outcome data.
• Common benchmark data points may not account for all relevant activities. For example, a
nurse’s work on after-care plans may not be captured by data.
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There is a gap between the ideal and the feasible, but the study should still aim to contribute to
knowledge on this topic.
Advice on Study Approach
At the March 25, 2014 workgroup meeting, MDH presented options for data sources that could be used
in each of the study phases. Workgroup members discussed these options at the meeting and provided
additional feedback via email.
Assessment of staffing variation
As an initial step in the study, MDH planned to evaluate levels of staffing variation across Minnesota
hospitals. Workgroup members had different opinions about the value of this analysis. Some members
indicated that this is a necessary step: if there are not meaningful differences in staffing patterns in
Minnesota hospitals, then that finding would inform methods used for the other phases of the study.
Other members urged MDH to focus solely on the connection of nurse staffing to patient outcomes, not
on staffing variation.
Analytical options for nurse staffing and patient outcomes
For the comparison of nurse staffing data to patient outcomes, MDH identified three options:
Option 1: Analyze concurrent data for the first quarter of 2014 (MHA staffing reports and newly
collected hospital discharge data).
Option 2: Analyze historical data for patient outcomes and other factors (2010-2013) and
staffing data from the first quarter of 2014 (hospital discharge data and MHA staffing reports,
respectively).
Option 3: Analyze historical data for 2010 – 2013 (hospital discharge data, plus newly collected
staffing data)
Many workgroup members expressed concerns that comparing data from different time periods (Option
2) would not yield meaningful results, or that an analysis of only three months of data (Option 1) would
be unreliable.
Some members recommended using a hybrid approach: looking at a way to combine Options 1 & 3 or
utilizing data from the assessment of staffing variation to inform Option 2.
Some members advocated for Option 2 because the data is available and will allow MDH to complete
the study by the January 15 deadline.
To overcome the chronological problems (short time periods or misaligned data periods), while also
minimizing the burden of new data collection, some members advocated combining existing outcomes
data with detailed staffing data from a sample of hospitals (a variation of Option 1).
Constraints, limitations, and need for balance
Members discussed the constraints and limitations MDH faces as it conducts the study. These
constraints include potentially limited data sources, resources available to analyze existing data, and the
deadline for the study. Specific comments and suggestions included:
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Several members encouraged MDH to continue to look at research done by other states on this
issue.
Most members suggested that MDH include information about limitations of data in its report.
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Some members advocated that MDH recommend to the legislature that additional data be
collected and studied, or that a community of practice be established to explore acuity systems
and other data.
Other members recommended that MDH note the limitations of data but discouraged any
extension of the study beyond the current report.
Some members agreed that there are limitations to the data, but urged MDH to balance the
need for data against the burdens placed on hospitals who may be asked to supply new data.
Summary prepared by:
Management Analysis & Development, Minnesota Management & Budget
July 25, 2014
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