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Journal of Applied Gerontology2014, V ol 33(1) 24 –50© The Author(s) 2012

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DOI: 10.1177/0733464812449903jag.sagepub.com

449903 JAG33110.1177/0733464812449903Castle et al.Journal of Applied Gerontology

Manuscript received: June 08, 2011; final revision received: March 02, 2012; accepted: April 23, 2012.

1University of Pittsburgh, Pittsburgh, PA, USA 2New York University, New York

Corresponding Author:Nicholas Castle, University of Pittsburgh, A610 Crabtree Hall, Pittsburgh, PA 15261, USA. Email: [email protected]

Hand Hygiene Deficiency Citations in Nursing Homes

Nicholas Castle1, Laura Wagner2, Jamie Ferguson1, and Steven Handler1

Abstract

Hand hygiene (HH) is recognized as an effective way to decrease transmission of infections. Little research has been conducted surrounding HH in nursing homes (NHs). In this research, deficiency citations representing potential problems with HH practices by staff as identified in the certification process conducted at almost all US NHs were examined. The aims of the study were to identify potential relationships between these deficiency citations and characteristics of the NH and characteristics of the NH environment. We used a panel of 148,900 observations with information primarily coming from the 2000 through 2009 Online Survey, Certification, And Reporting data (OSCAR). An average of 9% of all NHs per year received a deficiency citation for HH. In the multivariate analyses, for all three caregivers examined (i.e., nurse aides, Licensed Practical Nurses, and Registered Nurses) low staffing levels were associated with receiv-ing a deficiency citation for HH. Two measures of poor quality (i.e., [1] Quality of care deficiency citations and [2] J, K, or L deficiency citations, that is deficiency citations with a high extent of harm and/or more residents affected) were also associ-ated with receiving a deficiency citation for HH. Given the percentage of NHs receiving deficiency citations for potential problems with HH identified in this research, more attention should be placed on this issue.

Keywords

citations, infection control, nursing homes (NHs)

Article

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Castle et al. 25

Introduction

Hand hygiene (HH) is recognized as essential to decreasing transmission of infections (Centers for Disease Control [CDC], 2002); however, little research has been conducted surrounding HH in nursing homes (NHs). In this research, deficiency citations for HH in a nationally representative sample of NHs are examined. These deficiency citations represent potential problems with HH prac-tices by staff as identified in the certification process conducted at almost all U.S. NHs. Using a large panel of observations (N=148,900) from 2000 through 2009, and Generalized Linear Models, the aims of this study were to identify potential relationships between these deficiency citations and characteristics of the NH (e.g., staffing levels, quality, ownership) and characteristics of the NH environ-ment (e.g., competition, reimbursement rates).

Prevention and management of infections in NH settings is an important, yet underexamined, resident safety concern (Rust, Wagner, Hoffman, Rowe, & Neumann, 2008). Healthcare Associated Infections (HAIs) are the leading cause of morbidity and mortality in the 1.7 million NH residents with between 1.6 and 3.8 million infections and almost 388,000 deaths occurring annually in this set-ting (Richards, 2002). Infections are the reason for one fourth of all hospitaliza-tions from long-term care (LTC) facilities (Ahlbrecht, Shearen, Degelau, & Guay, 1999; Richards, 2007). The costs associated with infections in NH settings have a significant impact on the healthcare system with annual estimates ranging from US$38 to US$137 million for antimicrobial therapy and US$673 million to US$2 billion for hospitalizations (Barker et al., 1994; Hu, 1990). Furthermore, the importance of HH in NHs extends beyond just these facilities; as millions of NH residents every year are transferred to and from acute care settings and can poten-tially spread pathogens between settings (Mody, 2009).

Although there are a number of ways to decrease transmission of infections (i.e., vaccinations, skin testing, use of antimicrobials), HH is recognized as one of the simplest and the most cost effective ways to do so (CDC, 2002; Fendleret al., 2002; Mody, 2009; Smith, Carusone, & Loeb, 2008). When performed correctly, HH can reduce HAIs by up to 30% (Boyce & Pittet, 2002). Improving HH prac-tices has also been identified as a patient safety goal by TJC (i.e., The Joint Commission) and has also been targeted by the World Health Organization (WHO) as the first global patient safety challenge entitled “Clean Care is Safer Care” (Pittet & Donaldson, 2005; WHO, 2009).

Resident infection rates are often associated with HH techniques and use of appropriate HH techniques have been shown to decrease infection rates among NH residents (Richards, 2007). Infection control standards and guidelines are underdeveloped in the NH industry. Regulations stipulate that infection control



26 Journal of Applied Gerontology 33(1)

activities should be performed; but, provide few details. NH infection control specialists (such as infection control nurses) are not mandated. In addition, the infection control specialists that do exist in NHs often lack training in specialized areas of microbiology or epidemiology (Otero, 1993).

BackgroundPrior Literature

As noted above, examining HH in NHs is important; however, little research has been conducted surrounding HH in NHs (12 publications during the past 9 years). Our review of these publications is summarized in Table 1. This review shows that few empirical studies have been conducted specifically in NHs; and, those that exist have a small sample size and likely poor generalizability. Moreover, few studies have examined factors of NHs associated with HH practices. Overall, our knowledge of HH practices in NHs is limited, and as noted by Juthani-Mehta and Quagliarello (2010), this topic is “vastly understudied” (p. 935). The study pre-sented here is the first nationally representative examination of HH in NHs and is the first to present characteristics of the NH and characteristics of the NH environ-ment that may influence HH practices. However, we note that the analyses are limited to secondary data and include failure to follow HH requirements only as identified by surveyors as part of the annual inspection through the Centers for Medicare and Medicaid Services (CMS).

NH Certification and Deficiency CitationsCMS requires NHs to be certified before they can receive reimbursement for Medicare and/or Medicaid residents. The Medicare and Medicaid programs con-stitute major payers for care, thus almost all NHs in the United States (i.e., 96%) participate in this process. As part of this certification process deficiency cita-tions can be issued in specific areas of care (these are often called F-tags). That is, if NHs do not meet certain minimum health and safety standards, deficiency citation(s) can be issued. The current certification process is described in detail by CMS (www.cms.hhs.gov).

The Nursing Home Reform Act (NHRA) is considered to be highly influential in this regulatory process. The NHRA was included in the Omnibus Budget Reconciliation Act (OBRA) of 1987 (P.L. 100-203). Of most significance to this research, the NHRA mandated that NHs were to have a functioning infection con-trol program in place (Goldrick, 1999). The programs were to include surveil-lance, outbreak investigations, isolation procedures, educational programs for



27

Tabl

e 1.

HH

Stu

dies

in L

TC

Set

tings

.

Aut

hor(

s)Se

ttin

gTy

peN

Mea

sure

(s)

Out

com

e(s)

Ash

raf e

t al

. (20

10)

NH

sSu

rvey

749

empl

oyee

s; 6

NH

sC

ompl

ianc

e an

d kn

owle

dge

of

hand

was

hing

bas

ed o

n th

e C

DC

gui

delin

es.

Nee

d fo

r m

ore

hand

was

hing

ed

ucat

ion

to a

ll em

ploy

ees

and

decr

easi

ng t

he n

umbe

r of

bar

rier

s to

han

dwas

hing

.R

umm

ukai

nen,

Jako

bsso

n,

Kar

ppi,

Kau

tiain

en, &

Ly

ytik

äine

n (2

009)

LTC

faci

litie

sSi

te v

isits

with

st

ruct

ured

su

rvey

123

faci

litie

sU

se o

f ABH

R a

nd o

ngoi

ng

syst

emat

ic a

ntim

icro

bial

s.O

ne y

ear

afte

r si

te v

isits

, us

e of

ABH

R in

crea

sed

and

antim

icro

bial

s fo

r pr

even

tion

of u

rina

ry t

ract

in

fect

ions

dec

reas

ed.

Aie

llo, M

alin

is, K

napp

, &

Mod

y (2

009)

NH

sC

ross

-sec

tiona

l su

rvey

of

HC

Ws

392

HC

Ws;

4 N

Hs

HH

; alc

ohol

rub

use

; fin

gern

ails

; glo

ve u

se;

know

ledg

e of

CD

C H

H

guid

elin

es.

Posi

tive

resp

onse

s to

HH

pr

actic

es; a

ppro

pria

te

glov

e us

e an

d fin

gern

ail

char

acte

rist

ics;

need

for

furt

her

educ

atio

n of

HH

gu

idel

ines

.R

ao e

t al

. (20

09)

NH

sC

lust

er

rand

omiz

ed

tria

l

12 N

Hs;

565

resi

dent

sO

bser

ved

infe

ctio

n co

ntro

l m

easu

res

(i.e.

, HH

fa

cilit

ies;

envi

ronm

enta

l cl

eanl

ines

s; sa

fe d

ispo

sal

of c

linic

al w

aste

) an

d th

en in

trod

uced

im

prov

ed in

fect

ion

cont

rol m

easu

res

to t

he

inte

rven

tion

grou

p.

Low

com

plia

nce

rate

s of

H

H; i

mpr

oved

com

plia

nce

with

saf

e di

spos

al o

f cl

inic

al w

aste

.

(con

tinue

d)



28

Aut

hor(

s)Se

ttin

gTy

peN

Mea

sure

(s)

Out

com

e(s)

Smith

et

al. (

2008

)LT

C fa

cilit

ies

Cro

ss-s

ectio

nal

stud

y45

9 H

H

oppo

rtun

ities

; 2

LTC

fa

cilit

ies

HH

mon

itori

ng in

stru

men

t to

exa

min

e H

H

com

plia

nce.

Low

HH

com

plia

nce.

Pan

et a

l. (2

008)

LTC

faci

lity

Obs

erva

tionl

st

udy

308

HH

op

port

uniti

esH

H c

ompl

ianc

e (i.

e.,

Han

dwas

hing

and

Glo

ve

Use

).

HH

com

plia

nce

low

and

co

mpa

rabl

e to

acu

te c

are

sett

ings

.M

acke

nzie

, Jam

es, S

mith

, Ba

rnar

d, &

Rob

inso

n (2

008)

Men

tal

heal

th c

are

sett

ings

fo

r ol

der

peop

le

Surv

ey11

4 st

aff

Han

dwas

hing

ass

ista

nce

prov

ided

to

patie

nts

by

staf

f.

Staf

f do

not

ofte

n as

sist

pa

tient

s in

han

dwas

hing

.

Ric

hard

s (2

007)

LTC

faci

litie

sLi

tera

ture

re

view

N/A

Uri

nary

tra

ct

infe

ctio

ns; r

espi

rato

ry

trac

t in

fect

ions

; ga

stro

inte

stin

al

infe

ctio

ns; s

kin

infe

ctio

ns;

antim

icro

bial

-res

ista

nt

infe

ctio

ns.

Eval

uatio

ns; i

nfec

tion

cont

rol

prog

ram

s; im

mun

izat

ion;

an

timic

robi

al p

resc

ribi

ng;

HH

.

Hua

ng &

Wu

(200

8)N

Hs

Inte

rven

tion

with

sel

f re

port

ing

40 N

As

Impa

ct o

f a t

rain

ing

prog

ram

in H

H fo

r N

As.

An

inte

nse

trai

ning

pro

gram

im

prov

ed k

now

ledg

e an

d co

mpl

ianc

e of

HH

and

a

redu

ctio

n in

res

iden

t in

fect

ion

rate

s.

(con

tinue

d)

Tabl

e 1.

(co

ntin

ued)



29

Aut

hor(

s)Se

ttin

gTy

peN

Mea

sure

(s)

Out

com

e(s)

Mod

y, La

nga,

Sain

t, &

Br

adle

y (2

005)

NH

sSe

lf- adm

inis

tere

d qu

estio

nnai

re

35 N

Hs

Infe

ctio

n co

ntro

l pra

ctic

es;

imm

uniz

atio

n pr

actic

es;

role

of I

CP

and

infe

ctio

n co

ntro

l act

iviti

es.

Vary

ing

infe

ctio

n co

ntro

l gu

idel

ines

; diff

eren

t de

finiti

ons

of in

fect

ions

; va

ryin

g im

mun

izat

ion

com

plia

nce;

sm

all n

umbe

r of

full

time

empl

oyed

ICP.

Fend

ler

et a

l. (2

002)

ECF

Infe

ctio

n ra

tes

275-

bed

ECF;

265

em

ploy

ees

Effe

ct o

f alc

ohol

gel

sa

nitiz

ers

on in

fect

ion

rate

s.

Alc

ohol

gel

san

itize

r ca

n re

duce

infe

ctio

n ra

tes.

Gol

dric

k (1

999)

Skill

ed

nurs

ing

LTC

fa

cilit

ies

Des

crip

tive

stud

y13

6 fa

cilit

ies

Infe

ctio

n co

ntro

l pro

gram

s; ef

fect

iven

ess

of in

fect

ion

cont

rol a

ctiv

ities

.

Low

er in

fect

ion

surv

eilla

nce

and

cont

rol;

low

ha

ndw

ashi

ng c

ompl

ianc

e.

Not

e: A

BHR

= a

lcoh

ol-b

ased

han

d ru

bs; C

DC

= C

ente

rs fo

r D

isea

se C

ontr

ol; E

CF

= e

xten

ded

care

faci

lity;

HH

=ha

nd h

ygie

ne; I

CP

= in

fect

ion

con-

trol

pra

ctiti

oner

; NA

= N

urse

Aid

es; N

H=

nurs

ing

hom

e; L

TC

= lo

ng-t

erm

car

e.

Tabl

e 1.

(co

ntin

ued)




both employees and residents, and reporting procedures (Ahlbrecht et al., 1999). However, details on implementing each of these programs were generally lack-ing. For example, educational programs for nurse aides are likely highly impor-tant for infection control (Juthani-Mehta & Quagliarello, 2010). Nevertheless, educational programs are considered to be ill-defined and insufficient, and are not mandated as part of the 75 hrs of training nurse aides receive (Juthani-Mehta & Quagliarello, 2010).

The staff hand washing after direct resident contact deficiency citation is examined in this research (i.e., F-Tag 444). Specifically, CMS guidelines state workers are expected to wash their hands before and after direct resident contact (for which HH is indicated by acceptable professional practice); performing any invasive procedure (e.g., fingerstick blood sampling); entering isolation precau-tion settings; eating or handling food (hand washing with soap and water); assist-ing a resident with meals; assisting a resident with personal care (e.g., oral care, bathing); handling peripheral vascular catheters and other invasive devices; inserting indwelling catheters; assisting a resident with toileting (hand washing with soap and water); and changing a dressing. In addition, after coming in con-tact with a resident’s intact skin (e.g., when taking a pulse or blood pressure, and lifting a resident); personal use of the toilet (hand washing with soap and water); contact with a resident with infectious diarrhea including, but not limited to infec-tions caused by norovirus, salmonella, shigella, and Clostridium difficile (hand washing with soap and water); blowing or wiping nose; contact with a resident’s mucous membranes and body fluids or excretions; handling soiled or used linens, dressings, bedpans, catheters and urinals; handling soiled equipment or utensils; performing personal hygiene (hand washing with soap and water); and, removing gloves or aprons; and, when hands are visibly soiled (hand washing with soap and water). Also: when coming on duty and after completing duty (CMS Manual System, 2009a).

CMS also gives guidelines on recommended techniques for washing hands. This includes the following: with soap and water include wetting hands first with clean, running warm water, applying the amount of product recommended by the manufacturer to hands, and rubbing hands together vigorously for at least 15 seconds covering all surfaces of the hands and fingers; then rinsing hands with water and drying thoroughly with a disposable towel; and turning off the faucet on the hand sink with the disposable paper towel (CMS Manual System, 2009a). In addition, CMS states that except for situations where hand washing is specifi-cally required, antimicrobial agents such as alcohol-based hand rubs (ABHR) are also appropriate for cleaning hands and can be used for direct resident care. Recommended techniques for performing HH with an ABHR include applying



Castle et al. 31

product to the palm of one hand and rubbing hands together, covering all surfaces of hands and fingers, until the hands are dry. In addition, gloves or the use of baby wipes are not a substitute for HH (CMS Manual System, 2009a).

From 1997 to 2009, an average of approximately 1,000 NHs per year received a deficiency citation for this F-tag (i.e., F-Tag 444). This was the 24th most fre-quently used F-tag (from approximately 190 available). This F-tag was examined in the research presented here, as it was the only deficiency citation available that specifically addressed hand washing.

Conceptual FrameworkThis research was guided by the conceptual framework presented in Figure 1 (Mody, 2009). This conceptual framework is proposed as a means of understand-ing the potential relationships between HH, deficiency citations, and resident outcomes. It was also used as a means for guiding variable selection for the

RESIDENT RISK FACTORS- Age^- Chronic Diseases^- Indwelling Devices^- Decreased Immunity^- Care Processes (contact with medical

devices and group activities)^FACILITY RISK FACTORSInternal Factors- Nurse aide staffing- LPN staffing- RN staffing- Resident case-mix- Restraint use- Psychiatric condition- DementiaOrganizational Factors- Quality of care citations- J, K, or L citations- Medicaid resident occupancy- Medicaid resident occupancy XMedicaid reimbursement rate- For-profit ownership- Size- Chain membership- Occupancy rateEXTERNAL RISK FACTORS- Medicaid reimbursement rate- Competition- Elderly in county- Per capita income

HAND HYGIENEHEALTHCARE

ACQUIRED INFECTIONS^

DEATH^

HOSPITALIZATION^Deficiency Citation HAND HYGIENE(F-tag 444)

Figure 1. Conceptual Framework for Examining Deficiency Citations for Hand Hygiene in Nursing Homes.Source: Conceptual framework was modified from the work of Mody (2009, p. 411)Note: RNs = Registered Nurses; LPNs = Licensed Practical Nurses.^Not examined in the empirical analyses.




empirical analyses. This conceptual framework consists of resident (e.g., age and decreased immunity) and facility (e.g., staffing levels and quality) risk factors as well characteristics of the NH environment (e.g., competition and reimbursement rates).

NH residents are typically older and more susceptible to acquiring infections, and this can lead to hospitalizations or even death (Mody et al., 2011). Risk fac-tors associated with NH residents’ susceptibility to acquiring infections include malnutrition and functional impairments. In addition, while in the NH, there are a number of risk factors for residents coming in contact with and/or spreading infections. These risk factors include care processes such as contact with medical devices and group activities (i.e., physical therapy, dining facilities, and bathing areas) (Richards, 2007). Resident risk factors and potential resident outcomes were initially combined in a conceptual framework by Mody (2009). That is, based on existing literature, these resident risk factors and HH practices were proposed to influence healthcare acquired infections, and in turn healthcare acquired infections were proposed to influence resident outcomes such as death and hospitalization. In this research, we modify this initial conceptual framework to include NH internal, organizational, and external factors, as well as the defi-ciency citation for HH (F-Tag 444). This is shown in Figure 1.

Internal factors are operating characteristics of the facility, such as staffing levels; organizational factors are characteristics of the facility itself, such as the number of beds; and external factors are characteristics generally outside of the influence of the organization, such as competition from other providers. Including these factors is useful, because many internal, organizational, and external factors are believed to influence care in NHs.

One often-cited important internal characteristic, for example, is the staffing level of nurse aides. High nurse aide staffing levels have been shown to be associ-ated with better quality in many prior NH studies (Castle, 2008). One often-cited important organizational characteristic, for example, is the ownership of the facility. For-profit facilities are thought to provide lower quality of care than not-for-profit NHs (Comondore et al., 2009). One often-cited important external characteristic, for example, is the Medicaid reimbursement rate. High rates have been shown to be associated with better quality in many prior NH studies (Hyer et al., 2009). These factors may also be associated with whether or not a facility receives a deficiency citation for HH.

This conceptual model is used, first because based on data availability the NH is used as the unit of observation. Thus, an organization-based conceptual framework was appropriate. Second, a similar conceptual framework was used previously in NH analyses examining deficiency citations (Castle, Wagner, Ferguson-Rome, Men, & Handler, 2011; Castle, Wagner, Ferguson,



Castle et al. 33

& Handler, 2011). A complete list of the factors used in the analyses and their definitions are provided in Table 4. Given the large number of factors examined, and given the paucity of research in this area, this study is presented as an explor-atory analysis. Thus, specific hypotheses for the potential relationships between factors and deficiency citations for HH were not developed.

MethodSecondary data (described below) from 2000 to 2009 are used in the analyses. These data were combined into a panel consisting of a total of 148,900 NH observations. Descriptive analyses and multivariate analyses are used to examine characteristics (i.e., internal, organizational, and external factors) associated with receiving deficiency citations for HH (F-444).

Data SourcesDeficiency citations are recorded in the Online Survey, Certification, And Reporting (OSCAR) data. Moreover, the OSCAR also includes aggregate resi-dent information (e.g., number of residents with dementia, with psychiatric conditions, etc.), staffing information (e.g., number of full-time equivalent (FTE) nurse aides, etc.), and facility information (e.g., ownership characteristics, bed size, etc.). Thus, all of the internal and organizational factors examined in this research came from the OSCAR data.

The OSCAR data are publicly available from CMS (i.e., Centers for Medicare & Medicaid Services). The OSCAR is the only readily available data source that represents a national sample of NHs and includes resident, staffing, facility, and deficiency citation information over time. The reliability of many variables is well established (such as ownership characteristics; Kash, Hawes, & Phillips, 2007; Kash, Naufal, Cortés, & Johnson, 2010); but, this should not be overstated as no comprehensive psychometric analyses of the data are available, and opin-ions vary as to the overall reliability of this data (Kash et al., 2007). Details regarding the variables included in the OSCAR and how the data are collected is provided by Kash et al. (2007).

A limited number of variables included in the analyses came from the area resource file (ARF). Specifically, variables used as external factors (i.e., per cap-ita income in the market and the number of elderly in the market). Extensive details regarding the ARF can be found at www.arfsys.com.

In addition, Medicaid reimbursement levels (a variable used as an external fac-tor) came from primary data collected by the authors. This followed a process previously used by others (Grabowski, Feng, Intrator, & Mor, 2004). This primary




data collection included contacting representatives in each state, validating responses with information from other sources (when available), and adjusting the Medicaid reimbursement levels using the overall consumer price index (CPI). Extensive details regarding this data collection methodology is provided by Grabowski et al. (2004).

Analytic ApproachThe OSCAR data for each NH are available on a yearly basis (as the certifica-tion process occurs approximately yearly). Moreover, each facility has a unique ID number. Using these ID numbers, the OSCAR data for each NH from 2000 through 2009 were combined to create a longitudinal panel data source. The period 2000 through 2009 was used because these data were avail-able to the authors, and the data were used in a longitudinal panel format that allows more accurate inference of the included model parameters (Hsiao, Mountain, & Ho-Illman, 1995). ZIP codes are included in the OSCAR that were used to identify counties in which NHs were located and match facilities with the ARF data.

In the baseline year (i.e., 2000) 16,745 NHs were identified. Subsequently, 10% (N=1,855) of these NHs were excluded because they could not be identified in a subsequent year up to 2009. Thus, combined for the analyses 148,900 NH observations were used in this analysis (i.e., 14,890 NHs × 10 years).

AnalysesDescriptive statistics for the deficiency citation for HH (F-444) are presented. This includes the percentage of NHs receiving this deficiency citation; this cita-tion as a percentage of all deficiency citations given; and, the rank of this citation of all deficiency citations used, for each year from 2000 to 2009.

Twelve categories (labeled “A” through “L”) are used for each deficiency citation. These categories vary in scope and severity (i.e., the greater the letter, the more severe the citation). The severity depends on the extent of harm to the resident and the scope depends on the number of residents affected (these desig-nations are further defined in Table 2). Using all years of data (2000 through 2009), the percentage and number of NHs receiving each category of the defi-ciency citation for HH (F-444) is presented.

Descriptive statistics (means and percentages) for the internal, organizational, and external factors used in the analyses are presented. These are stratified by NHs receiving a deficiency citation for HH (F-444) in 2000, or not. These descriptive statistics are provided for the baseline year of 2000 for parsimony.



Castle et al. 35

Table 2. Nursing Homes Receiving Deficiency Citationsa for Hand Hygiene (F-tag 444) From 2000 to 2009.

Year

Percentage of Nursing Homes

With an F-Tag 444 Deficiency Citation

F-Tag 444 Deficiency Citations as a

Percentage of All Citations Given

Rank of F-Tag 444 Deficiency Citations

of All Deficiency Citations Given

2000 7.37 1.17 312001 7.38 1.18 322002 7.31 1.40 262003 8.64 1.46 252004 9.06 1.51 232005 9.97 1.54 222006 10.75 1.55 222007 11.56 1.64 202008 11.65 1.67 192009 11.98 1.75 19Summary (all years) 9.06 1.63 24

Note: aA nursing home deficiency citation is defined as “a finding that a nursing home failed to meet one or more federal or state requirements” (Department of Health and Human Services [DHHS], 2004, p. 34).

To examine internal, organizational, and external factors of NHs associated with receiving deficiency citation for HH (F-444) multivariate analyses were used. Thus, multicollinearity and collinearity levels among the variables using the variance inflation factor (VIF) test were first measured (SAS Institute, 1999).

The multivariate analyses used consisted of Generalized Linear Models. Specifically, generalized estimating equations (GEE) with a logit link were used (Zeger & Liang, 1992). GEE controls for the biases that can occur in data consist-ing of repeat observations (i.e., in this case, NHs with repeat observations from 2000 to 2009). The logit link was used because the variable of interest was dichotomous (e.g., deficiency citation F-444 or no deficiency citation). SAS® version 9.13 was used for all statistical analyses.

ResultsResults of the Descriptive Analyses

From 2000 to 2009 an average of approximately 9% of all NHs per year received an HH deficiency citation (F-444; see Table 2). An upward trend is evident, with




an average yearly percentage increasing from 7.37% (in 2000) to 11.98% (in 2009). On average, these are the 24th most frequently used deficiency citation (from 190 available); although, as shown in Table 2, the use of these citations does vary slightly per year from the 32nd most frequently used (in 2001) to the 19th (in 2008 and 2009). In addition, the use of deficiency citations for HH (F-444) varies by state. In some states, such as Pennsylvania, an average of 6% of facilities were given this deficiency citation in 2009; whereas, in other states such as Michigan, an average of 15% of facilities were given this deficiency citation in 2009. The tercile distribution of these deficiency citations by state is shown in Figure 2.

Table 3 shows the percentage of HH deficiency citations (F-444) from 2000 to 2009 given by scope and severity. This shows that almost no NHs received defi-ciency citations in the most severe categories (i.e., J, K, and L). Most deficiency citations (i.e., 66.3%) were at the “D” level (representing potential for more than minimal harm [severity] and isolated cases [scope]).

Descriptive statistics of the variables used in the analysis for the baseline period of the year 2000 are presented in Table 4. A total of 1,828 NHs received this deficiency citation (F-444) in the year 2000. Compared to those NHs that did not receive a deficiency citation for HH, the bivariate analyses show higher rates of both more quality of care deficiency citations (addresses how well the facility renders services provided and supervised by nursing staff) and J, K, or L defi-ciency citations.

Figure 2. Tercile distribution of deficiency citations for Hand Hygiene (F-444) are presented. The figure represents the average number of these deficiency citations given per nursing home in each state.



Castle et al. 37

Table 3. Scope and Severity Classifications Used for Medicare/Medicaid Certification Survey Deficiencies and Percentage of Nursing Homes Receiving Deficiency Citations for Hand Hygiene (F-tag 444) From 2000 to 2009.

Scope

Severity Isolated Pattern Widespread

Potential for minimal harm A(NR)

B(n=241

2%)

C(n=430.5%)

Potential for more than minimal harm D(n=5,843

66%)

E(n=2,561

29%)

F(n=1261.5%)

Other actual harm G (n=10.01%)

H(0)

I (0)

Actual or potential for death/serious injury J(0) K(0)

L(n=10.0%)

Note: Number in parentheses is the number of citations for hand hygiene (F-tag 444) from 2000 to 2009 (total number of these citations = 8,816). Severity is the extent of harm to the resident. Scope is the number of residents affected (Isolated defined as affecting a single or very limited number of residents; Pattern defined as affecting more than a very limited number of residents; Widespread defined as affecting a large portion or all resi-dents). Thus, A deficiency citations are the least problematic and L are the most problem-atic. For example, an A-level deficiency citation may be given if one nurse aide was observed to not wash her hands adequately; whereas, a C-level deficiency citation may be given if numerous nurse aides were observed to not wash her hands adequately. If one nurse aide was observed to not wash her hands adequately with a resident known to have norovirus a D-level deficiency citation may be given.NR, not recorded in the OSCAR.

Results of the Multivariate Analyses

Based on the commonly used threshold value of 0.8, the variables showed no problems of collinearity and no VIF score exceeded 2.5. Results from the GEE marginal models with a logit link are shown in Table 5.

For the internal factors all of the staffing level factors were significant at con-ventional levels (see Table 5). That is, for nurse aides high staffing levels were associated with low deficiency citations for HH (Adjusted Odds Ratios (AOR) = 0.965; p>=.01); high staffing levels of LPNs were associated with low deficiency citations for HH (AOR = 0.978; p>=.05); and, high RN staffing levels were asso-ciated with low deficiency citations for HH (AOR = 0.976; p>=.01).

For the organizational factors examined (see Table 5), facilities with quality of care deficiency citations were significantly associated with a high likelihood of



38

Tabl

e 4.

Des

crip

tive

Stat

istic

s of

NH

s R

ecei

ving

and

Not

Rec

eivi

ng D

efic

ienc

y C

itatio

ns fo

r H

H (

F-ta

g 44

4).

Faci

litie

s R

ecei

ving

F-t

ag

444

Cita

tions

aFa

cilit

ies

Not

Rec

eivi

ng

F-ta

g 44

4 C

itatio

nsb

Vari

able

sM

ean

(or

%)

Stan

dard

D

evia

tion

Mea

n (o

r %

)St

anda

rd

Dev

iatio

nO

pera

tiona

l Def

initi

on o

f Var

iabl

e

Inte

rnal

fact

ors

Nur

se a

ide

staf

fing

(FT

Es

per

resi

dent

)0.

330.

130.

320.

14FT

E nu

rse

aide

s pe

r re

side

nt.

LPN

sta

ffing

(FT

Es p

er

resi

dent

)0.

120.

090.

120.

09FT

E LP

Ns

per

resi

dent

.

RN

sta

ffing

(FT

Es p

er

resi

dent

)0.

060.

090.

070.

11FT

E R

Ns

per

resi

dent

.

Res

iden

t ca

se-m

ix (

AD

L sc

ore)

0.12

0.26

0.12

0.26

The

sco

re fo

r th

ree

AD

Ls (

eatin

g, to

iletin

g, an

d tr

ansf

erri

ng)

cons

truc

ted

by g

ivin

g a

scor

e of

1

for

low

ass

ista

nce,

2 fo

r m

oder

ate

assi

stan

ce,

and

3 fo

r hi

gh n

eed

for

assi

stan

ce s

umm

ed fo

r ea

ch A

DL.

Res

trai

nt u

se0.

100.

120.

100.

12Pr

opor

tion

of r

esid

ents

in p

hysi

cal r

estr

aint

s.Ps

ychi

atri

c co

nditi

on0.

170.

150.

160.

17Pr

opor

tion

of r

esid

ents

dia

gnos

ed w

ith

psyc

hiat

ric

cond

ition

s.D

emen

tia0.

440.

200.

430.

20Pr

opor

tion

of r

esid

ents

dia

gnos

ed w

ith

dem

entia

(de

fined

as

an IC

D-9

cod

e in

dica

ting

a sp

ecifi

c de

men

ting

illne

ss).

(con

tinue

d)



39

Faci

litie

s R

ecei

ving

F-t

ag

444

Cita

tions

aFa

cilit

ies

Not

Rec

eivi

ng

F-ta

g 44

4 C

itatio

nsb

Vari

able

sM

ean

(or

%)

Stan

dard

D

evia

tion

Mea

n (o

r %

)St

anda

rd

Dev

iatio

nO

pera

tiona

l Def

initi

on o

f Var

iabl

e

Org

aniz

atio

nal f

acto

rsQ

ualit

y of

car

e de

ficie

ncy

cita

tions

3.09

*2.

421.

591.

84D

efic

ienc

y ci

tatio

ns r

epre

sent

ing

the

sum

of 1

9 di

ffere

nt d

efic

ienc

y ci

tatio

ns (

F-ta

gs a

re: 3

09,

310,

311

, 312

, 314

, 316

, 317

, 318

, 319

, 321

, 322

, 32

3, 3

24, 3

25, 3

28, 3

29, 3

30, 3

33, 3

53).

With

in-

stat

e ra

nkin

gs (

perc

entil

es)

used

for

anal

yses

.J,

K, o

r L

defic

ienc

y ci

tatio

ns0.

08*

0.46

0.04

0.38

Any

def

icie

ncy

cita

tion

at J,

K, o

r L

leve

l (se

e Ta

ble

2). W

ithin

-sta

te r

anki

ngs

(per

cent

iles)

us

ed fo

r th

e an

alys

es.~

Med

icai

d re

side

nt

occu

panc

y64

%23

%63

%26

%Pe

rcen

t of

res

iden

ts w

ith M

edic

aid

as p

ayor

.

Size

(nu

mbe

r of

bed

s)11

074

109

73N

umbe

r of

bed

s in

the

nur

sing

hom

e.Fo

r-pr

ofit

owne

rshi

p70

%*

–65

%–

For-

prof

it or

not

-for-

prof

it (in

clud

ing

gove

rnm

ent

owne

d) o

wne

rshi

p.C

hain

mem

ber

60%

*–

56%

–W

heth

er m

embe

r of

a n

ursi

ng h

ome

chai

n or

no

t.O

ccup

ancy

rat

e82

%16

%83

%17

%Pe

rcen

t of

bed

s oc

cupi

ed b

y re

side

nts.

(con

tinue

d)

Tabl

e 4.

(co

ntin

ued)



40

Faci

litie

s R

ecei

ving

F-t

ag

444

Cita

tions

aFa

cilit

ies

Not

Rec

eivi

ng

F-ta

g 44

4 C

itatio

nsb

Vari

able

sM

ean

(or

%)

Stan

dard

D

evia

tion

Mea

n (o

r %

)St

anda

rd

Dev

iatio

nO

pera

tiona

l Def

initi

on o

f Var

iabl

e

Ext

erna

l fac

tors

Med

icai

d re

imbu

rsem

ent

rate

(U

S$)1

125.

05*

27.1

413

2.40

31.6

2T

he s

tate

ave

rage

dai

ly (

i.e.,

per

diem

) pa

ymen

t ra

te fo

r M

edic

aid

resi

dent

s (U

S$).

The

rat

es

wer

e ad

just

ed t

o co

nsta

nt 2

000

dolla

rs u

sing

th

e C

onsu

mer

Pri

ce In

dex

(CPI

).C

ompe

titio

n (H

erfin

dahl

In

dex)

d2,

216

2,47

72,

076

2,38

4H

erfin

dahl

Inde

x. E

ach

faci

lity’s

per

cent

age

shar

e of

bed

s in

the

cou

nty

/ squ

ared

mar

ket

shar

es

of a

ll fa

cilit

ies

in t

he c

ount

y (0

-1).

Hig

her

valu

es in

dica

te a

less

com

petit

ive

mar

ket.

Elde

rly

per

squa

re m

ile2

81*

174

146

419

Ave

rage

num

ber

of e

lder

ly p

er s

quar

e m

ile (

age

65 a

nd a

bove

) in

the

cou

nty.

Per

capi

ta in

com

e (U

S$)2

26,5

03*

6,23

727

,324

7,96

6A

vera

ge in

com

e (U

S$)

for

all c

ount

y re

side

nts

Not

e: a N

= 1

,828

faci

litie

s (b

ased

on

2000

dat

a); b N

= 1

2,37

2 fa

cilit

ies

(bas

ed o

n 20

00 d

ata)

.A

DL

= a

ctiv

ities

of d

aily

livi

ng; F

TE

= fu

ll-tim

e eq

uiva

lent

; HH

= h

and

hygi

ene;

LPN

s =

Lic

ense

d Pr

actic

al N

urse

s; LT

C =

long

-ter

m c

are;

NH

= n

urs-

ing

hom

es; R

Ns

= R

egis

tere

d N

urse

s.*D

iffer

ence

bet

wee

n re

ceiv

ing

defic

ienc

y ci

tatio

n fo

r H

H a

nd n

ot s

igni

fican

t at

p<

0.00

1.1.

The

uni

t of

ana

lysi

s fo

r th

is v

aria

ble

is t

he s

tate

(un

less

oth

erw

ise

note

d, fo

r al

l oth

er v

aria

bles

the

faci

lity

is t

he u

nit

of a

naly

sis)

.2.

The

uni

t of

ana

lysi

s fo

r th

is v

aria

ble

is t

he c

ount

y.~

Vari

atio

n in

the

use

of n

ursi

ng h

ome

defic

ienc

y ci

tatio

ns is

kno

wn

to o

ccur

from

sta

te t

o st

ate.

Usi

ng t

he p

erce

ntile

dis

trib

utio

n of

def

icie

ncy

cita

-tio

ns w

ithin

eac

h st

ate

give

s to

a m

ore

cons

iste

nt c

ompa

riso

n of

def

icie

ncy

cita

tions

acr

oss

stat

es.

(A).

vari

able

s pr

imar

ily c

ame

from

the

Onl

ine

Surv

ey, C

ertif

icat

ion,

And

Rep

ortin

g (O

SCA

R);

with

eld

erly

in t

he c

ount

y an

d pe

r ca

pita

inco

me

com

-in

g fr

om t

he A

rea

Res

ourc

e Fi

le (

AR

F); a

nd, M

edic

aid

reim

burs

emen

t ra

tes

com

ing

from

pri

mar

y da

ta; (

B). t

he fi

gure

s pr

esen

ted

are

for

the

base

line

2000

dat

a. T

he b

asel

ine

figur

es a

re p

rese

nted

for

pars

imon

y.

Tabl

e 4.

(co

ntin

ued)



Castle et al. 41

Table 5. Multivariate Results of Nursing Homes Receiving and Not Receiving Deficiency Citations for Hand Hygiene (F-tag 444) From 2000 to 2009.

AOR 95% CI

Internal factors Nurse aide staffing 0.965 (0.961 –0.983) ** LPN staffing 0.978 (0.941 –0.993) * RN staffing 0.976 (0.938 –0.989) ** Resident case-mix (ADL score) 1.007 (1.039 –1.111) *** Restraint use 1.017 (0.989 –1.046) Psychiatric condition 1.063 (0.992 –1.035) Dementia 1.031 (1.002 –1.062) **Organizational factors Quality of care citations 1.137 (1.133 –1.142) *** J, K, or L citations 0.826 (0.779 –0.876) *** Medicaid resident occupancy 0.942 (0.927 –0.956) *** Medicaid resident occupancy × Medicaid reimbursement ratea

0.980 (0.921 –0.997) *

For-profit ownership 1.005 (0.945 –1.068) Size 1.021 (0.994 –1.049) Chain membership 0.935 (0.887 –0.986) ** Occupancy rate 1.004 (0.975 –1.035) External factors Medicaid reimbursement rate 0.922 (0.911 –0.989) ** Competition (Herfindahl Index)

1.013 (0.982 –1.045)

Elderly in county 0.976 (0.942 –1.018) Per capita income 0.993 (0.959 –1.029) Intercept 0.074 (0.0367 –0.149) ***

Note: N = 148,900 observations.*Statistically significant at p=0.05 level or better; ** Statistically significant at p=0.01 level or better; *** Statistically significant at p=0.001 level or better. Analyses also include 49 state and year dummy variables (not shown). Results reported using generalized estimating equations (GEE).FTE = full-time equivalent, ADL = activities of daily living, RNs = Registered Nurses, LPNs = Licensed Practical Nurses, AOR = Adjusted Odds Ratio; CI = Confidence Interval.aAdjusted Odds Ratios were manually calculated by using the mean levels of the variables (Medicaid reimbursement rate and Medicaid resident occupancy [i.e., a and b] and the variance/covariance matrix [Ai & Norton, 2003]).

receiving a deficiency citation for HH (AOR = 1.137; p <=.001); however, those with J, K, or L level deficiency citations were significantly associated with a low likelihood of receiving a deficiency citation for HH (AOR = 0.826 p <=.001).




Also, facilities that are members of a chain were significantly associated with a low likelihood of receiving a deficiency citation for HH (AOR = 0.935 p <=.01).

For the external factors examined (see Table 5), facilities located in states with higher Medicaid reimbursement rates were significantly associated with a low likelihood of receiving a deficiency citation for HH (AOR = 0.922; p <=.01).

DiscussionHAIs are the leading cause of morbidity and mortality amongst NH residents. NH residents are particularly susceptible to HAIs because they are frail, have multiple chronic comorbidities, and take antibiotics that are often inappropriately prescribed leading to greater susceptibility of antibiotic-resistant organisms (Bradley, 2009; Mody et al., 2011). HH can be an extremely influential practice in infection control management to prevent transmission of infectious disease in NHs (Mody et al., 2011). The research presented here is significant in that it gives a nationally representative picture of deficiency citations for HH (i.e., F-tag 444) in NHs. That is, in this study we examined relationships between these deficiency citations and characteristics of the NH and characteristics of the NH environment.

Overall, the conceptual framework used seemed appropriate for examining these deficiency citations. However, we note that the conceptual framework was modified from the initial work of Mody (2009) and the potential relationships indicating HH influencing healthcare acquired infections, death and hospitaliza-tion were not examined in the research presented here (see Figure 1). The major-ity of factors included in the conceptual framework and resulting analyses were significant in the multivariate analyses. This was especially true for the internal and organizational factors. That is, 5 of the 7 internal factors were statistically significant (i.e., nurse aide staffing, LPN staffing, RN staffing, resident case-mix, and dementia) and 5 of the 8 organizational factors (i.e., quality of care citations, J, K, or L citations, Medicaid resident occupancy, Medicaid resident occupancy × Medicaid reimbursement rate, and chain membership) were statistically signifi-cant. The external factors performed less well, with 1 of the 4 factors significant (i.e., Medicaid reimbursement rate) in the multivariate analyses. Thus, further modification of these external factors may be warranted in subsequent iterations and development of this conceptual framework.

With an average of approximately 9% of all NHs per year receiving a HH defi-ciency citation (see Table 2), our results confirm previous survey-based research that HH measures are not uniformly used in NHs ( Aiello et al., 2009; Ashraf et al., 2010). The results show an increasing percentage of NHs with an F-tag 444 defi-ciency citation and a reduction in rank of F-tag 444 deficiency citations of all



Castle et al. 43

deficiency citations given (see Table 2). Thus, HH deficiency citations are becom-ing more common over time. We are not able to determine the cause(s) of this trend. We speculate that one reason may be greater awareness of surveyors to issues of infection control. A second potential reason may be a more difficult oper-ating environment for NHs. Resident case-mix has increased over time, while rev-enues have remained flat (Hyer et al., 2009). While providing more care with the same (or less) resources appropriate infection control may be sacrificed.

The issue of staffing appears very prominent in our findings (see Table 5). For all three caregivers examined (i.e., nurse aides, LPNs, and RNs) low staffing levels were associated with receiving a deficiency citation for HH (F-444). With low staffing levels, these caregivers are likely hurried, and may not have the time to use appropriate HH techniques. Empirical research has identified inadequate staffing levels to exist in many NHs (e.g., Hyer, Temple, & Johnson, 2009) and to be highly associated with quality of care (Castle, 2008; Castle & Ferguson, 2010). Our findings show one further consequence of low staffing: potential poor HH practices. We note that other staffing related reasons for poor HH likely exist. For example, poor HH practices could result from limited time for effective supervi-sion, high turnover, or from less peer support. Given the prominent findings for staffing identified in this research, it would be worth exploring some of these other staffing-related factors further.

Given the current inhospitable financial and reimbursement climate in which NHs operate, staffing levels are unlikely to improve in the near future. Therefore, HH-specific training may be one answer to improve compliance especially for nurse aides who provide 80%-90% of resident care (Beck, Ortigara, Mercer, & Shue, 1999). However, studies show that HH training in LTC facilities may be inadequate (Leinbach & English, 1995). To enhance HH training, facilities could do more to educate staff that contaminated hands are one of the most common ways to transmit infections, provide 1:1 coaching on how to wash hands appro-priately, describe the pros and cons of handwashing vs. alcohol-based hand sani-tizer products, and the need for handwashing (rather than the use of alcohol-based hand sanitizer products) when hands are soiled or there may be the presence of C. difficile infection for example.

Still, potential training and education solutions to address this deficiency cita-tion necessitate that we further understand why staff are not washing their hands as frequently as the guidelines recommend. It could be that the underlying behavior is influenced by the culture or attitudes of staff. Or it could be that staff does not have sufficient access to alcohol gel (for example). Training and education approaches should be informed by a more detailed understanding of reasons for poor HH.

Institutional policies and procedures could be developed to routinize HH as a required process for all staff, followed by internal quality improvement audits




(similar to state surveyor audits) to determine HH compliance. It has also been recognized that healthcare workers should receive feedback to ensure proper HH practices (Ahlbrecht et al., 1999). We speculate that a lack of such feedback may also be reflected in the findings. That is, with low staffing levels of RNs in a leadership position (who would typically provide this feedback), this process may be weak or nonexistent.

Our findings also show that receiving a deficiency citation for HH (F-444) is associated with poor quality in general (i.e., with quality of care deficiency cita-tions). This may be due to the notion that HH practices and quality of care are influenced by similar operating and environmental conditions. Nevertheless, HH deficiency citations are associated with lower levels of the worst lapses in quality of care deficiency citations (i.e., J, K, and L deficiency citations, which represent deficiency citations with a high extent of harm and/or more residents affected). These contradictory findings should be investigated further. We speculate that this may reflect the known orthogonality of quality indicators. That is, NHs often perform poorly in one area at the same time as they perform better in a different area (Castle & Ferguson, 2010).

The findings show that states with lower Medicaid reimbursement rates had higher rates of deficiency citations for HH. Low Medicaid reimbursement rates are also a characteristic of the NH industry (Grabowski et al., 2004). These low rates are associated with many negative NH outcomes such as high staff turnover and poor quality of care (Grabowski et al., 2004). That is, Medicaid reimburse-ment rates can influence the operation of NHs.

Presumably, the HH lapses resulting in deficiency citations by surveyors rep-resent observed cases of problems, and not lapses of reporting and documentation problems (which is a criticism of many other deficiency citations). As such, the use of deficiency citations for HH (similar to citations given for other observed problems such as medication errors; F-329) likely underestimate the potential HH problems in NHs. One would assume that staff would be following clinical care protocols (including HH) when surveyors are observing care. Thus, the potential problems with HH are likely much larger than we report here.

Interventions to improve HH need to be multifactorial in nature since multi-modal interventions are more effective at improving HH compliance rates over single employed approaches. The multifactorial approach should include three areas improving knowledge of HH through education (Laustsen, Bibby, Kristensen, Møller, & Thulstrup, 2009); reinforcing behavior through quality improvement activities (Pittet et al., 2000); motivating the HH behavior through introducing products such as personal bottles or wall mounted–alcohol hand rubs; changing the culture through increasing administrative support; and using reminders (Pittet et al., 2000).



Castle et al. 45

Limitations and Suggestions for Future Research

One limitation of examining deficiency citations for HH is that they do not necessarily represent actual resident outcomes. The literature would suggest that when caregivers have poor HH practices this is detrimental to residents, but this cannot be substantiated in our analysis. Future research examining the influence of HH practices on resident outcomes is needed. Other sources of data could be used for such analyses, including the minimum data set (MDS), which provides a somewhat comprehensive evaluation of each resident (Castle & Ferguson, 2010).

From the information available in the OSCAR, it is not possible to present a more fine-grained analysis of specific breakdowns in HH requirements. That is, if the errors occur with specific residents or at specific locations. A more fine-grained analysis of some of the differences that exist between states may also be useful. As shown in Figure 2, considerable differences exist between states. These may be associated with specific state incentives or policies that could be further investigated.

Some of these more fine-grained analyses would also seem warranted given the recent changes in F-tags. In late 2009, F-tags 441, 442, 443, 444, and 445 were all collapsed in F-441 (CMS, 2009b). This enables aggregate “infection control” deficiency citations to be examined; but, is limited in that it is no longer possible to examine specific components of infection control, such as HH.

ConclusionsAs noted above, deficiency citations have several limitations when investigating HH. However, no prior research has presented a longitudinal analysis of a national sample of NHs examining these deficiency citations. With HH defi-ciency citations increasing over time and with an average of approximately 9% of all NHs per year receiving an HH deficiency citation, our findings provide tentative evidence that HH may be a problem in NHs. By examining relation-ships between these deficiency citations and characteristics of the NH and char-acteristics of the NH environment, we identify many of these factors (such as staffing) to be potentially important. This research may foster more interest in further elaborating influential determinants in this area of care; with the impor-tant objective of improving resident care and resident outcomes.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.




Funding

The author(s) received no financial support for the research, authorship, and/or pub-lication of this article.

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Author Biographies

Nicholas Castle is a professor with the University of Pittsburgh in the Department of Health Policy & Management. His research examines the quality of nursing homes. Previous research initiatives include examining staffing levels, staff turnover, top management, resident satisfaction, and safety culture. Dr. Castle is a Fellow of the Gerontological Society of America.

Laura Wagner is an assistant professor with the New York University College of Nursing in the Hartford Institute for Geriatric Nursing. Her research examines improving patient safety care processes in nursing homes. Previous research has focused on physical restraint and siderail reduction, improving adverse event report-ing and disclosure, and safety culture assessment.


www.uky.edu/ComputingCenter/SSTARS/MulticollinearityinLogisticRegression.htm



Jamie C. Ferguson-Rome is a project director with the University of Pittsburgh in the Department of Health Policy and Management. Her work includes safety and quality of care in nursing homes and assisted living facilities and the age-friendliness of communities. She can be reached at [email protected].

Steven Handler is an assistant Professor with the University of Pittsburgh in the Department of Biomedical Informatics and Division of Geriatric Medicine. His research focuses on the development, implementation, and assessment of clinical decision support systems to improve medication and patient safety primarily in the nursing home setting.



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