# Presentation: 423188

## Working Environment and Adverse Patient Events in Home Healthcare: Issues and Findings

- Penny H. Feldman, Ph.D. - Principal InvestigatorRobert J. Rosati, Ph.D. - Investigator
**Supported by AHRQ Grant #R01 HS11962**
***Visiting Nurse Service of New York***

## Collaborators

- John Bridges, Ph.D. - Investigator
- Christopher Murtaugh, Ph.D. - Investigator
- Timothy Peng, Ph.D. - Research Associate
- Doreen Wang, M.A. - Programmer
- Lori King, B.A. - Research Assistant
***Visiting Nurse Service of New York***

## Study Aims

- To examine the variability of adverse events and organizational team characteristics across 86 care teams within one agency
- To examine the relationships between adverse patient events and:
- Patient characteristics
- Care team objective characteristics
- Care team subjective work environment

## Conceptual Model

**Organizational/Structural Characteristics**
- Communication Processes
- Governance
- Information Technology

**Group Behavior**
- Collaboration
- Consensus

**Supervision**
- Style
- Employee Recognition

**Quality Emphasis**
- Patient Centeredness
- Safety
- Innovation
- Outcome Measurement
- Evidence-based Practice

**Work Design**
- Staffing
- Resources/Training
- Rewards
- Autonomy

**Healthcare Worker Outcomes**
- Satisfaction
- Burnout
- Intention to Leave
- Organizational Identification

**Patient Outcomes**
- Patient Satisfaction
- Patient Safety
- Health and Function

**Leadership**
- Values
- Style
- Strategy

**Conceptual Model**

***Core***
***Structural***
***Domains***

***Process***
***Domains***

***Outcomes***

## Current Study

- Collaboration
- Consensus

**Supervision**
- Style
- Employee Recognition

**Quality Emphasis**
- Safety
- Patient Care

**Work Design**
- Staffing
- Resources/Training
- Rewards
- Autonomy

**Patient Outcomes**
- Patient Safety

**Current Study**

**Measures of  care team objective characteristics**
**and subjective work environment**** **

**Adverse Events**

## Study Context

- Largest non-profit home health care organization in the United States
- Average daily census is ~25,000 patients
- Diverse and complex patient population with post-acute and long-term care needs
- Disproportionately high numbers of African-American and Hispanic patients
- Decentralized workforce providing care in patients’ homes
- Patients are seen by over 100 different care teams (all programs) across seven counties

## Data Sources

- Outcomes Assessment Information Set (OASIS)
- Standardized patient assessment data
- Patients assessed at the beginning and end of each episode of care
- Employee survey
- Patient level service utilization data
- Human Resources employee data
- Other administrative data

## Employee Survey

- Mailed self-administered survey to acute and congregate care clinicians and front-line managers
- 46% response rate (1,027 surveys)
- 169 items compiled from work environment literature
- Approximately 30 minutes to complete
- The survey measured 15 constructs*:

- Teamwork (0.83)
- Leadership (0.90)
- Top-Down Communication (0.84)
- Perceived Quality (0.76)
- Safety Culture:
- General (0.81)
- Leadership (0.84)
- Communication (0.91)

- Manageable Workload (0.74)
- Job Demands (0.86)
- Autonomy (0.88)
- Equity (0.85)
- Access to Resources (0.68)
- Satisfaction (0.85)
- Staff/Patient Communication (0.72)
- Physician Relations (0.94)

- *Shown with team-level reliability coefficients (Chronbach’s alpha)

## Study Design

- We used a 2-stage regression model to analyze the relationship between the dependent variable—the risk-adjusted incidence of any CMS adverse event—and a set of independent objective and subjective variables (e.g., aspects of the team structure, staff beliefs about their team, etc.)
- The final results are based on how the dependent variable was related to each of the independent variables while “controlling for” (or taking into account) all the other variables included in the analysis

## Study Design (continued)

- Employee Survey Data

- Patient Episode Data

**Study Design ****(continued)**

## CMS Adverse Events

- The 13 CMS Home Healthcare defined adverse events serve as markers for potential problems in home care because of their negative nature and relatively low frequency
- Whether or not individual patient situations resulted from inadequate care provision can only be determined by investigating the actual care provided to specific patients
- An episode was considered to have an adverse event if ***one or more*** of the adverse events occurred
- For study purposes, we counted events at discharge/transfer and at the end of each 60-day episode

## 13 CMS Adverse Events

- _Emergent Care (EC) Events_
- EC for injury caused by fall or accident at home
- EC for wound infection or deteriorating wound status
- EC for improper medication administration or medication side effects
- EC for hypo/hyperglycemia

- _Significant Unmet Care Need_
- Unmet need for wound care or medication assistance
- Unmet need for toileting assistance
- Unmet need for management of behavioral problem

- _Significant Decline in Health or Function_
- Development of urinary tract infection
- Increase in number of pressure ulcers
- Substantial decline in 3 or more ADLs
- Substantial decline in management of medications

- _Serious Unexpected Event_
- Unexpected nursing home admission
- Unexpected death

## Characteristics of Patient Episodes

- The data set contained **51,560** episodes of care (6 months)
- The population’s average age was 71 years
- The majority of the group was female (67%)
- 40% lived alone; 30% had no primary caregiver
- The most common clinical diagnoses were diabetes (14%), hypertension (7%), and congestive heart failure (5%)
- The ethnicity of the population was:

## Characteristics of Survey Respondents

- The data set contained **951 **survey respondents
- Their average age was 45 years
- They had an average of 9.3 years of experience in the home care setting
- Their average tenure at the agency was 7.5 years
- 81% had a bachelor’s (or higher) degree

## Adverse Events Across Teams* 

- # of teams

- Variation in rates of adverse events across care teams

- *Episodes with any one CMS event over a 6-month time period (unadjusted mean approx. 7%)

## Results: Volume and Distribution of Work

**Results: ****Volume and Distribution of Work**

-  Volume **~R****2****=.010**
-  Concentration* of visits among nurses **~R****2****=.021**
-  Number of weekend admissions **~R****2****=.126**

- *The degree to which the team’s visits are evenly distributed across many nurses or concentrated among a few nurses is measured using a Herfindahl-Hirschman Index of team visits
- **Risk-adjusted based on a methodology developed by the health economist on our team

**Overall Model R-squared = .345**

- Note: The partial R-squared is displayed next to each variable

***lower*** rates of team-attributable adverse events**

**Notes:**
Overall R-squared for the model was .345 (moderate effect size)

Increased volume and more concentrated visits decreases adverse events.
More weekend admissions increases adverse events.

## Results:Workforce Characteristics

**Results:****Workforce Characteristics**

-  Experience **~R****2****=.039**

***lower*** rates of team-attributable adverse events

**Overall Model R-squared = .345**

- Note: The partial R-squared is displayed next to each variable

**Notes:**
Increased workforce experience decreases adverse events. 

## Results:Perceived Organizational Climate

**Results:****Perceived Organizational Climate**

-  Equity **~R****2****=. 011**
-  Teamwork **~R****2****=.019**
-  Supervisor Safety Culture* **~R****2****=. 022**
-  ManageableWorkload** **~R****2****=.046**

***lower*** rates of team-attributable adverse events

- *May be due in part to association of increased awareness of safety with increased reporting (identified in health care literature)
- **Possibly due to “complacency” or “burnout” factors

**Overall Model R-squared = .345 including all eight variables**

**Overall Model R-squared = .345**

- Note: The partial R-squared is displayed next to each variable

**Notes:**
More perceived equity and teamwork is associated with lower adverse events.

The higher the perceived supervisor safety culture and manageable workload the greater the number of adverse events.

## Summary of Results

- After controlling for patient case-mix severity, this study found that **work design, safety culture, teamwork, and workforce characteristics **all affected team-attributable adverse event rates.
- Specifically, adverse event rates were lower for teams that had:

- higher volume
- higher concentration of visits
- fewer weekend admissions
- more experienced clinicians

- greater perceived equity
- greater perceived teamwork
- lower perceived supervisorsafety culture*
- less workload manageability*

***Possibly due to a combination of “safety awareness,” “complacency,” and “burnout” factors**

## Summary of Results

| Variable | Weight | Partial R2 |
| --- | --- | --- |
| Volume | + | 0.010 |
| Concentration of visits  | + | 0.021 |
| Weekend admissions  | + | 0.126 |
| Experience | + | 0.039 |
| Equity | + | 0.011 |
| Teamwork | + | 0.019 |
| Supervisor Safety Culture | - | 0.022 |
| Manageable Workload | - | 0.046 |

**Overall Model R-squared = .345**

## Implications for Patient Safety

- Findings are consistent with other patient safety studies that:
- Link higher volume and greater experience to safer care
- Show higher rates of reported adverse events where safety culture is emphasized
- Show that managerial span of control and teamwork make a difference
- Association between better patient safety outcomes and less manageable workload:
- Raises questions about possible “burnout” among high performing teams or “complacency” among poorer performing teams
- Suggests the need for further investigation

## Next Steps

- Complete chart reviews to analyze the relationship between adverse events and specific types of patient care errors for two adverse events:
- Emergent care for wound infection or deteriorating wound status
- Emergent care for hypo/hyperglycemia
- Prepare study results for publication
- Pursue additional research:
- Assess the impact of quality/safety on team climate (“reverse causation”)
- Design and evaluate interventions to improve teamwork and reverse adverse events
- Develop a diagnostic tool to predict the likelihood of future adverse events

## Contact Information

**Center For Home Care Policy and Research**
**Visiting Nurse Service of New York**
**5 Penn Plaza, 11****th**** Floor**
**New York, NY 10001**
**(212) 609-5776**
**Robert.Rosati@vnsny.org**