Va pcmh study 6 2014[1]

Copyright 2014 American Medical Association. All rights reserved.
Implementation of the Patient-Centered Medical Home
in the Veterans Health Administration
Associations With Patient Satisfaction, Quality of Care,
Staff Burnout, and Hospital and Emergency Department Use
Karin M. Nelson, MD, MSHS; Christian Helfrich, MPH, PhD; Haili Sun, PhD; Paul L. Hebert, PhD;
Chuan-Fen Liu, MPH, PhD; Emily Dolan, PhD; Leslie Taylor, PhD; Edwin Wong, PhD; Charles Maynard, PhD;
Susan E. Hernandez, MPA; William Sanders, AA, AS; Ian Randall, MHSA; Idamay Curtis, BA;
Gordon Schectman, MD; Richard Stark, MD; Stephan D. Fihn, MD, MPH
IMPORTANCE In 2010, the Veterans Health Administration (VHA) began implementing the
patient-centered medical home (PCMH) model. The Patient Aligned Care Team (PACT)
initiative aims to improve health outcomes through team-based care, improved access, and
care management. To track progress and evaluate outcomes at all VHA primary care clinics,
we developed and validated a method to assess PCMH implementation.
OBJECTIVES To create an index that measures the extent of PCMH implementation, describe
variation in implementation, and examine the association between the implementation index
and key outcomes.
DESIGN, SETTING, AND PARTICIPANTS We conducted an observational study using data on
more than 5.6 million veterans who received care at 913 VHA hospital-based and
community-based primary care clinics and 5404 primary care staff from (1) VHA clinical and
administrative databases, (2) a national patient survey administered to a weighted random
sample of veterans who received outpatient care from June 1 to December 31, 2012, and (3) a
survey of all VHA primary care staff in June 2012. Composite scores were constructed for 8
core domains of PACT: access, continuity, care coordination, comprehensiveness,
self-management support, patient-centered care and communication, shared decision
making, and team-based care.
MAIN OUTCOMES AND MEASURES Patient satisfaction, rates of hospitalization and emergency
department use, quality of care, and staff burnout.
RESULTS Fifty-three items were included in the PACT Implementation Progress Index (Pi2
).
Compared with the 87 clinics in the lowest decile of the Pi2
, the 77 sites in the top decile
exhibited significantly higher patient satisfaction (9.33 vs 7.53; P < .001), higher performance
on 41 of 48 measures of clinical quality, lower staff burnout (Maslach Burnout Inventory
emotional exhaustion subscale, 2.29 vs 2.80; P = .02), lower hospitalization rates for
ambulatory care–sensitive conditions (4.42 vs 3.68 quarterly admissions for veterans 65
years or older per 1000 patients; P < .001), and lower emergency department use (188 vs
245 visits per 1000 patients; P < .001).
CONCLUSIONS AND RELEVANCE The extent of PCMH implementation, as measured by the Pi2
,
was highly associated with important outcomes for both patients and providers. This
measure will be used to track the effectiveness of implementing PACT over time and to
elucidate the correlates of desired health outcomes.
JAMA Intern Med. doi:10.1001/jamainternmed.2014.2488
Published online June 23, 2014.
Invited Commentary
Supplemental content at
jamainternalmedicine.com
Author Affiliations: Author
affiliations are listed at the end of this
article.
Corresponding Author: Karin M.
Nelson, MD, MSHS, Seattle Center of
Innovation for Veteran-Centered and
Value-Driven Care, VA Puget Sound
Health Care System, 1100 Olive Way,
Ste 1400, Seattle, WA 98108 (karin
.nelson@va.gov).
Research
Original Investigation
E1
Downloaded From: http://archinte.jamanetwork.com/ by a University of Iowa User on 06/24/2014

A
lthoughthepatient-centeredmedicalhome(PCMH)has
been endorsed by most major primary care groups as
a promising model to strengthen primary care, de-
crease costs, and improve quality,1
early assessment of PCMH
impact have yielded mixed results.2-10
Since 2010, the Veter-
ans Health Administration (VHA) has undertaken national
adoption of a PCMH model, called PACT (Patient Aligned Care
Team).11
The focus of PACT has been to restructure primary
care to provide team-based care that is more comprehensive,
coordinated, and patient centered.11
The PACT initiative is a multifaceted and complex inter-
vention, creating challenges to measuring implementation
across diverse clinic sites. One of the most widely recognized
PCMH recognition tools is the National Committee for Quality
Assurance(NCQA)certificationprocess,whichfocusesonprac-
ticeinfrastructureandhealthinformationtechnology,12
anarea
in which the VHA has made considerable past investments.13,14
The VHA has a universally deployed electronic health record,
electronic prescribing, patient registries, and a national qual-
ity improvement and performance measurement infrastruc-
tureforwhichallclinicsintheVHAwouldreceive“credit.”Many
national programs for coordinating care, such as home-based
primary care, integrated mental health services, and pallia-
tive care, were already widely available before PACT was ini-
tiated. The focus within the VHA has been on how effectively
these extensive resources are being applied and coordinated
to fulfill the goals of the PACT initiative.11
Our goal was to derive a comprehensive index from exist-
ing data and survey instruments that would have a low re-
spondent burden and would reflect processes and attributes
that are essential to effective primary care. Our approach dif-
fers from other PCMH measurement tools15
by incorporating
multiple data sources, including a primary care personnel sur-
vey, patient surveys, and administrative data. We sought to
develop a measure to represent areas of focus of the PACT ini-
tiative, including continuity through team-based care, patient
access, care coordination, and patient-centered care.11
We
desired an instrument that would facilitate comparisons
across clinical sites within the VHA, assist in identifying sites
that had most effectively implemented PACT, and determine
the relationship between effective implementation and
important outcomes, such as patient satisfaction, quality of
care, provider experience, and use of health care services.
Methods
Survey Instruments and Data Sources
Patient Survey
We used data from the previously validated Consumer
Assessment of Health Plans–Patient Centered Medical Home
(CAHPS PCMH) survey16
that was administered to a nationally
weighted random sample of veterans who received outpatient
care from June 1 to December 31, 2012. The CAHPS PCMH
scales have acceptable internal consistency reliability esti-
mates for access (Cronbach α, 0.74), comprehensiveness
(0.68), self-management support (0.62), patient-centered care
and communication (0.91), and shared decision making
(0.61).16
To test convergent validity, we used information on
patient satisfaction from another sample of veterans from the
Survey of the Health Experiences of Patients, an ongoing
national mailed US Department of Veterans Affairs (VA) sur-
vey that assesses the health care experiences of veterans who
receive care at the VHA and uses a stratified random sampling
method.17
The evaluation efforts are part of an going quality
improvement effort at the VHA and are not considered
research activity; they are thus not subject to institutional
review board review or waiver.
Primary Care Personnel Survey
The PACT Primary Care Personnel Survey was an internally
developed instrument designed to measure team functioning
in PACT and has been described elsewhere.18
The target popu-
lation of the survey was all VHA primary care personnel,
including the 4 occupations included in PACT teams: primary
care providers, nurse care managers, medical associates (eg,
licensed practical nurses and medical technicians), and
administrative clerks. Data were collected from May 21
through June 29, 2012. Team-based care was represented by
items from the primary care personnel survey related to del-
egation, staffing, team functioning, and team assignment.18
Administrative Data
Information about demographics, clinical characteristics, and
use of health services was obtained from the VHA Corporate
Data Warehouse for fiscal year 2012 (n = 5 653 616). Using data
from the Primary Care Management Module contained within
the Corporate Data Warehouse, we identified all patients who
were enrolled in primary care and assigned to a primary care
provider.19
WeincludedadministrativedataforimportantPACT
programmatic goals,11
including (1) access to care and use of
non–face-to-face care, such as telephone clinics and secure
messaging; (2) continuity of care; and (3) use of VHA pro-
grams to support care coordination (eg, home telemonitor-
ing, 2-day posthospital follow-up).
We used data collected by the VHA External Peer Review
Program(EPRP)duringfiscalyear2012toassessqualityofcare.
The EPRP is an audit program designed to assess clinical per-
formance using standard performance criteria. National data
are collected through manual abstraction of electronic health
recordsbyanindependentexternalcontractor.20
Previousstud-
ies have found high interrater reliability (κ = 0.9) within the
EPRP program.14
Construction of the PACT Implementation Progress Index
The method for developing the PACT Implementation Prog-
ress Index (Pi2
) and a full description of all items are provided
in eTable 1 in the Supplement. Briefly, we mapped data items
to PACT conceptual domains, calculated domain scores based
on these items, and then generated site-level rankings for each
domain. Table 1 outlines Pi2
domains and provides examples
of representative variable items. A Pi2
score was assigned to
each clinic based on the number of domains in the top and bot-
tom quartiles for the domain scores, ranging from 8 (all do-
main scores in the top quartile) to –8 (all domain scores in the
bottom quartile). Using these scores, we categorized sites in
Research Original Investigation Patient-Centered Medical Home Implementation
E2 JAMA Internal Medicine Published online June 23, 2014 jamainternalmedicine.com

the top decile of the Pi2
(score, 5 to 8) as having achieved ef-
fective implementation and those in the lowest decile of the
Pi2
(score, –7 to –5) as having been less effective.
Patient- and Provider-Level Outcome Measures
Patient satisfaction was assessed by using a single item from
the CAHPS PCMH survey16
as follows: “Using any number
from 0 to 10, where 0 is the worst provider possible and 10 is
the best provider possible, what number would you use to
rate this provider?”
Staff burnout was assessed with both a single-item mea-
sure and the emotional exhaustion subscale of the Maslach
Burnout Inventory, a widely used measure of burnout.21-23
The single item measure asks: “Overall, based on your defini-
tion of burnout, how would you rate your level of burnout,”
with 5 ordinal response options.24
We defined burnout as a
response of 3 or higher, where 3 corresponds to “I am defi-
nitely burning out and have one or more symptoms of burn-
out, such as physical and emotional exhaustion.”24
We also
used a 3-item version of the Maslach Burnout Inventory
subscale.25
Items reflecting burnout symptoms are scored
using a Likert scale ranging from 0 (never) to 6 (every day) and
summed to form a scale score. We defined burnout as a score
of 10 or higher (range, 0-18).
To assess quality of care, we examined outpatient mea-
surementsfromtheEPRPforchronicdiseasemanagement,be-
havioral health screening, and prevention services. These in-
dicators include frequently used measures of the quality of
prevention (eg, vaccinations, screening tests) and outpatient
care of chronic diseases (eg, annual retinal examinations in pa-
tients with diabetes mellitus). The performance measure-
ment for preventive services and chronic disease cohorts, sam-
pling frame, and criterion for meeting the measurement are
provided in eTable 2 in the Supplement.
The EPRP selects a random sample of patient records
from VHA facilities to monitor quality and appropriateness of
medical care.26
The sample includes veterans who used VHA
health care at least once in the 2 years before the assessment.
Patients who were sampled had at least 1 primary care or
specialty medical visit in the month being sampled. Among
eligible patients, a random sample is drawn with over-
sampling of prevalent chronic conditions (eg, diabetes, heart
failure).26
For patients at each primary care site, we determined the
numbers of emergency department or urgent care visits, VA
hospital admissions, and hospitalizations for ambulatory care–
sensitive conditions (ACSCs), which are postulated to be most
avoidable through provision of effective primary care.27
Hos-
pitalizations for ACSCs were based on Agency for Healthcare
Research and Quality Prevention Quality Indicators and were
identified through standardized protocols using Interna-
tional Classification of Diseases, Ninth Revision, diagnoses and
Current Procedural Terminology codes from inpatient VA
records.27
Table 1. PCMH Concepts and Pi2
Domains
PACT Initiative
Goals Pi2
Domains
Total
Items,
No.
Items From Each Data
Source, No.
Example Itemd
CAHPS
PCMHa
CDWb
Personnel
Surveyc
Accessible,
continuous, and
coordinated care
Access 11 6 5 0 How often did you get an appointment as soon as you needed?a
When you phoned this provider’s office, how often did you get an answer
to your medical question that same day?a
Same-day access to appointments (% of clinics)b
Enhanced access: telephone clinics (%)b
Continuity of care 3 1 2 0 How long have you been going to this provider?a
Proportion of visits to assigned primary care providerb
Care coordination 7 5 2 0 When this provider ordered a test, how often did someone from this
provider’s office follow up to give you those results?a
Did the provider seem informed and up to date about the care you got
from specialists?a
Percentage of patients contacted 2 d after hospital dischargeb
Patient-centered
care
Comprehensiveness 3 3 0 Did you and anyone in this provider’s office talk about things in your life
that worry you or cause you stress?a
Self-management
support
2 2 0 Did anyone in this provider’s office talk with you about specific goals for
your health?a
Patient-centered
care and
communication
6 6 0 How often did this provider explain things in a way that was easy to
understand?a
Shared decision
making
3 3 0 When you talked about starting a prescription medicine, did this provider
ask you what you thought was best for you?a
Team-based care Delegation, staffing,
and team
functioning
18 0 0 18 Primary care provider relies on registered nurse care manager for tasks
including gathering patient preventive services, responding to
prescription refillsc
Percentage reporting recommended staffing ratioc
Time spent in team huddles: percentage spending >30 min/dc
Total … 53 26 9 18 …
Abbreviations: CAHPS PCMH, Consumer Assessment of Health Plans–Patient
Centered Medical Home; CDW, Corporate Data Warehouse; PACT, Patient
Aligned Care Team; PCMH, patient-centered medical home; Pi2
, PACT
Implementation Progress Index.
a
CAHPS PCMH patient survey.
b
CDW data from US Department of Veterans Affairs.
c
PACT Primary Care Personnel Survey.
d
Full description in eTable 1 in the Supplement. The questions have been
shortened for the sake of brevity.
Patient-Centered Medical Home Implementation Original Investigation Research
jamainternalmedicine.com JAMA Internal Medicine Published online June 23, 2014 E3

Statistical Analysis
PI2
Properties
To test internal consistency reliability, we calculated the Cron-
bach α for all items in each domain and all 53 items that make
up the total scale.
Variation in PCMH Adoption
We evaluated bivariate comparisons of facility characteristics
and level of implementation by using χ2
tests for categorical
variables and t tests for continuous variables. We compared
sites assessed to have effectively implemented PACT with
those assessed as less effective according to type of facility
(hospital or community-based outpatient clinic), number of
patients, demographic characteristics, and Elixhauser comor-
bidity score.28
Associations With Patient and Provider Outcomes
We used a nonparametric test of trend for the ranks across or-
dered groups (an extension of the Wilcoxon rank sum test) to
test for trends in patient satisfaction and staff burnout by Pi2
scores. We tested differences in the proportions of eligible pa-
tients at each VHA clinic fulfilling each of the 48 quality indi-
cators according to the success of PACT implementation as
measured by the Pi2
. We calculated rates of services at the fa-
cility level by dividing the number of patients who satisfied
the EPRP quality measure by the number who met inclusion
criteria for each quality measure (eTable 3 in the Supple-
ment). For each of the 48 facility-level quality indicators, we
tested the trend in proportions of patients fulfilling the EPRP
qualityguidelinebythelevelofPACTimplementation.Weused
the nonparametric test for trend developed by Cuzick, which
is an extension of the Wilcoxon test.29
We adjusted for mul-
tiple comparisons using a method described by Benjamini and
Yekutieli.30
To determine whether more effective implemen-
tation (as measured by Pi2
) corresponded to higher perfor-
mance overall, we included all 48 outcome measures in a lin-
ear mixed-effects model that accounted for correlation among
outcomes from the same facility and estimated an overall
implementation effect. We adjusted for implementation in this
model as a linear term ranging from 1 to 5, corresponding to
the grouped Pi2
scores. This approach was possible because all
48 outcomes were measured on the same scale.
We examined fiscal year 2012 emergency department and
urgent care visits and total hospitalizations for sites with more
effective vs less effective implementation, adjusting for pa-
tient age, community-based outreach clinics, and Elixhauser
comorbidityscores.28
Toaccountfortemporaltrends,wemod-
eled facility-level trends for hospitalization from 2003 to 2012.
The method for examining such trends has been described
elsewhere.31
We estimated interrupted time-series models of
ACSC and all-cause hospitalizations from October 1, 2003,
through September 20, 2012, for each facility and assessed how
the trends in hospitalizations changed after the start of the
PACT initiative in April 2010. All regression models adjusted
for facility-level patient characteristics, unemployment rate in
the VA market area, quarterly dummy variables to capture sea-
sonal variation, and a linear time trend. Patient risk was mea-
sured using mean facility-level Elixhauser comorbidity scores.
Changes in admissions for ACSC and all-cause hospitaliza-
tions after implementation of the PACT initiative were calcu-
lated as the difference between the observed rate of admis-
sions and the predicted rate had the initiative not been
implemented during the 2½-year period between April 1, 2010,
and September 30, 2012. In this way, we estimated changes in
admissions that might be attributed to the PACT initiative.
Trend analyses for hospitalizations were stratified by age (≥65
and <65 years) to account for the substantial use of non-VA
health care by Medicare-eligible veterans.32
We then com-
pared the estimated change in admissions among facilities that
had effectively implemented PACT with the change in those
that had done so less effectively.
Results
The final Pi2
consisted of 53 individual items assigned to the 8
overarching PACT concepts (Table 1). Detailed descriptions of
all items and descriptive statistics are provided in eTable 1 in
the Supplement. From more than 22 000 primary care per-
sonnel at the time of the survey, 5404 (approximately 25% re-
sponse rate) from 667 sites of care completed the PACT Pri-
maryCarePersonnelSurveyduringthespringof2012.Between
June and December 2012, more than 75 000 veterans who were
enrolled in VA primary care completed the CAHPS PCMH mod-
ule included in the Survey of the Health Experiences of Pa-
tients (47% response rate).
Psychometric Properties of Pi2
The Pi2
demonstrated satisfactory levels of internal consis-
tency for total score (Cronbach α= 0.89), access (0.63), conti-
nuity (0.67), comprehensiveness (0.81), self-management
support (0.68), patient-centered care and communication
(0.95), shared decision making (0.75), and team-based care
(0.91). Similar to results reported by Scholle et al,16
the care
coordination composite had lower internal consistency
(0.51). With patient satisfaction as measured by the Survey of
the Health Experiences of Patients used as a measure of con-
vergent validity, provider ratings differed between sites with
more vs less effective implementation (mean provider rating,
9.05 vs 8.37; P < .001).
Variation in PCMH Adoption
Clinical sites that had implemented PACT more effectively
tended to have fewer patients than those that had been less
effective (Table 2). However, the type of clinic, mean patient
age, percentage of male patients, and mean Elixhauser comor-
bidity score were similar among all sites irrespective of how
well PACT had been implemented.
Associations With Patient and Provider Outcomes
Patient satisfaction was significantly higher among sites that
had effectively implemented PACT than among those that
had not (range of mean rating for satisfaction with provider,
9.33-7.53; P < .001) (Table 3 and the eFigure in the Supple-
ment). A similarly favorable pattern was observed for staff
burnout as measured by the Maslach Burnout Inventory

emotional exhaustion subscale (range, 2.29-2.80; P = .02)
(Table 3 and the eFigure in the Supplement) but not for the
1-item burnout question.
We observed significant trends in quality of care in rela-
tion to the Pi2
score. The 77 sites that achieved the most ef-
fective implementation exhibited higher clinical quality out-
come measures than less successful sites. There was a
statistically significant association (P < .05) between clinical
quality outcomes and the Pi2
score for 19 of 48 measures, and
better performance was associated with a higher Pi2
score for
allbut2.Overall,ofall48measures,41werehigheramongsites
with higher Pi2
scores. The Figure displays the difference in
thepercentageofpatientsmeetingqualitycriteriabetweensites
in the highest and lowest quintiles of Pi2
scores. The com-
bined effect estimated from the mixed-effects model showed
a significant increase in mean outcomes for facilities with
higher Pi2
scores compared with those with lower Pi2
scores
(P < .001).
InthecomparisonoftrendsacrossPi2
scores,veteranswith
chronic disease who received care at facilities with higher Pi2
scores had small but significant improvements in quality-of-
care indicators (eTable 3 in the Supplement). For example, vet-
erans with diabetes who received care at sites with the high-
est Pi2
scores were more likely to have a hemoglobin A1c value
less than 9% (range at high-implementation vs low-
implementation sites, 84.0%-81.8%; P = .04) or a low-
density lipoprotein cholesterol (LDL-C) level less than 100
mg/dL (to convert to millimoles per liter, multiply by 0.0259)
(range,70.4%-66.0%;P = .03).Veteranswithhypertensionwere
more likely to have a blood pressure reading less than 140/90
mm Hg (range, 80.2%-76.9%; P = .02). Among veterans with
ischemicheartdisease,thoseatsiteswiththehighestPi2
scores
were more likely to have LDL-C measured (range, 97.0%-
94%; P < .001), have a measured LDL-C level less than 100
mg/dL (range, 70.5%-65.3%; P < .001), and have documenta-
tionofaprescriptionforaspirinattheirmostrecentvisit(range,
92.9%-89.5%; P = .03). Veterans receiving care at sites that ex-
hibited more successful implementation of PACT were more
likely to receive an influenza vaccination (range, 68.5%-
64.2%; P < .001 for veterans aged 50-64 years), to be screened
for cervical cancer (range, 92.8%-86.7%; P = .047 for women
aged 21-64 years), or offered medications for tobacco cessa-
tion (range, 96.2%-93.4%; P < .001).
The rate of emergency department visits was signifi-
cantly lower in sites with more effective implementation than
inthosewithlesseffectiveimplementation(range,188-245vis-
its per 1000 patients; P < .001; Table 4 and eFigure in the
Supplement). Although the total numbers of hospitalizations
in fiscal year 2012 did not differ by level of implementation
(Table 4), rates of hospitalization for ACSCs during the 2½-
year period after implementation of PACT were lower among
sites that had more effectively implemented PACT than among
those that were less effective (Table 5). Among sites with Pi2
scoresinthehighestdecile,weestimatedthattherewasamean
reduction of 2.28 admissions for ACSCs per 1000 patients
younger than 65 years (a 13.4% decrease) attributable to the
Table 2. Site Characteristics by Effectiveness of PACT Implementation
Characteristic
Clinic-Level National
Mean (SD)a
Implementation, Mean (95% CI)b
P Valuec
More Effective (Pi2
, 5 to 8) Less Effective (Pi2
, –7 to −5)
Patients served, No. 5917 (6706) 2893 (2250-3535) 5467 (3910-7024) .004
CBOCs, No. (%) 735 (83.0) 72 (94.7) 73 (89.0) .19
Age, y 64.4 (3.9) 65.1 (64.2-66.0) 63.6 (62.7-64.4) .01
Female patients, % 5.4 (0.04) 6.2 (4.0-9.0) 5.9 (5.0-7.0) .77
Elixhauser score 0.76 (0.07) 0.77 (0.75-0.78) 0.76 (0.75-0.77) .43
Abbreviations: CBOCs, community-based outpatient clinics; PACT, Patient Aligned Care Team; Pi2
, PACT Implementation Progress Index.
a
Values represent mean (SD) except where otherwise indicated.
b
Values represent mean (95% CI) except where otherwise indicated.
c
P values determined with χ2
or t tests comparing more effective vs less effective implementation sites.
Table 3. Patient Satisfaction, Staff Burnout, and Pi2
Scores
Pi2
Score
Clinics,
No.
Patient Satisfaction, Mean (SD) Staff Burnout, Mean (SD)
Provider Rating From
CAHPS PCMH Survey
Provider Rating
From SHEP
Overall Health Care
Rating From SHEP MBI EE
Single-Item
Measure
5 to 8 77 9.33 (0.34) 9.05 (0.28) 8.62 (0.34) 2.29 (1.55) 0.37 (0.36)
2 to 4 213 9.02 (0.44) 8.91 (0.34) 8.49 (0.36) 2.47 (1.29) 0.36 (0.33)
−1 to 1 346 8.67 (0.46) 8.73 (0.34) 8.32 (0.35) 2.56 (1.13) 0.36 (0.29)
−4 to −2 190 8.23 (0.64) 8.55 (0.40) 8.15 (0.40) 2.63 (1.23) 0.37 (0.29)
−7 to −5 87 7.53 (0.88) 8.37 (0.45) 7.87 (0.47) 2.80 (1.42) 0.37 (0.35)
P valuea
… <.001 <.001 <.001 .02 .58
Abbreviations: CAHPS PCMH, Consumer Assessment of Health Plans–Patient Centered Medical Home; MBI EE, Maslach Burnout Inventory emotional exhaustion
subscale; Pi2
, PACT [Patient Aligned Care Team] Implementation Progress Index; SHEP, Survey of the Health Experiences of Patients.
a
P values represent test for trend.

Figure. Differences Between Sites With More Effective and Less Effective Implementation in the Percentage of Patients Meeting Quality Criteria
–6.00 0 8.00–2.00 2.00 6.004.00
% of Patients
–4.00
Source
Congestive heart failure
LVF documented
LVEF <40% on ACEI or ARB
Diabetes mellitus
Renal testing
Hypertension
Diagnosis of HTN and BP <140/90 mm Hg
Mental health screening and treatment
Alcohol misuse with timely counseling
Obesity management
Eligible patients who participated in MOVE
Immunizations
Immunization age ≥65 years
Cancer and osteoporosis screening
Colorectal cancer screening for those aged 51-75 years
Tobacco use screening and treatment
Patients using tobacco offered referral
Patients using tobacco provided with counseling
Patients using tobacco offered medications
Screened for tobacco use
Cervical cancer screening (women aged 21-64 years)
Screened for breast cancer (women aged 40-49 years)
Osteoporosis screening for women aged ≥65 years
Influenza ages 50-64 years
Pneumococcal
Obese patients screened and offered weight management (MOVE)
Annually screened for alcohol misuse, SUD
Patients positive for PTSD with timely disposition
Positive PTSD screen with timely suicide ideation/behavior evaluation
PTSD screening using the PC-PTSD
Combined scores for timely suicide evaluation if positive for PTSD or MDD
Timely evaluation for patients with positive depression screen
Annually screened for depression
Ischemic heart disease
AMI outpatient, ASA at most recent visit
AMI, LVEF <40 on ACEI or ARB
AMI discharged who received persistent β–blocker
Hyperlipidemia screen–overall
LDL-C <100 mg/dL
LDL-C measured
No diagnosis of HTN and BP <160/100 mm Hg
Diagnosis of HTN and BP <160/100 mm Hg
No diagnosis of HTN and BP ≤140/90 mm Hg
LDL-C measured within 1 y of review
Retinal examination, timely by disease
BP <160/100 mm Hg
BP <140/90 mm Hg
LDL-C <100 mg/dL
HbA1c <9%
ACEI/ARB in current medications
ASA in current medications
HbA1c annual
Foot sensory examination using monofilament
Foot pedal pulses
Foot inspection
ACEI, angiotensin-converting enzyme inhibitor; AMI, acute myocardial
infarction; ARB, argiotensin II receptor blocker; ASA, aspirin; BP, blood pressure;
HbA1c, hemoglobin A1c; HTN, hypertension; LDL-C, low-density lipoprotein
cholesterol; LVEF, left ventricular ejection fraction; LVF, left ventricular fraction;
MDD, major depressive disorder; MOVE, weight management program;
PC-PTSD, primary care posttraumatic stress disorder; PTSD, posttraumatic
stress disorder; SUD, substance use disorder.
SI conversion factor: To convert LDL-C values to millimoles per liter, multiply by
0.0259.

PACT initiative compared with a reduction in admissions of
only 0.08 for ACSCs (a 3.0% decrease) among sites with less
effective implementation. Thus, the estimated reduction in
hospitalizationsforACSCswassignificantlygreateratthemore
effective sites, although the absolute number of admissions
was relatively small (2.8 hospitalizations per 1000 patients).
For veterans older than 65 years, the projected changes in ad-
mission rates for ACSCs were more modest, and the differ-
ence among sites was small. Similar trends of smaller magni-
tude were noted for all-cause hospitalization.
Discussion
We constructed the Pi2
, a measure to assess progress in imple-
menting PCMH in the VHA, using primary care personnel sur-
veys, patient surveys, and administrative data. The index was
favorably and meaningfully associated with important out-
comes, including patient satisfaction, staff burnout, quality of
care, hospitalizations, and emergency department visits. Pa-
tient satisfaction was significantly greater (on the order of a
fullpointhigherona0-10scale)andstaffburnoutloweratsites
forwhichthePi2
indicatedmoreeffectiveimplementation.De-
spite the overall high level of clinical care provided at the VHA,
we found measurable differences between clinics by level of
PCMH implementation in terms of the proportion of veterans
meeting criteria for multiple measures of quality. In addition,
sites with the highest Pi2
scores exhibited modestly lower rates
of hospital admission for ACSCs and larger projected de-
creases in rates of admission after the start of the VHA PACT
initiative. These results are consistent with findings from a re-
cent VHA study in which clinic directors’ reports about the
medical home indicated that sites with better care coordina-
tion and support for transition had lower rates of hospitaliza-
tions for ACSCs.33
Previous studies have found a lack of association with
measurements of structural and care processes in primary
care and quality of care34,35
or patient experience.36
Thus, in
devising a method to assess the degree of PCMH implemen-
tation, we adopted an approach that differed substantially
from the widely used NCQA recognition process, including
patient-reported measures and using administrative data on
access and continuity. We chose not to use the NCQA recogni-
tion process for several reasons: the administrative burden is
too high to determine certification for more than 900 clinics
and much of the process relies on structural changes that
have already been broadly implemented across the VA, there-
fore diminishing the ability to discriminate among sites. Pre-
vious authors have noted that the NCQA measurement for
PCMH may not be able to differentiate on quality-of-care
measures.10
In contrast, our measure of PCMH implementa-
tion detects differences in quality across many clinics. Our
data support the notion that the assessment of PCMH needs
to include both patient-level and practice-level infrastructure
measures.5,6,37
The VHA has a long-standing investment in infrastruc-
ture considered a baseline prerequisite for a functioning
PCMH, including a robust quality improvement and perfor-
mance system.14
Our data are consistent with previous
reports of the high quality of clinical care provided at the
VHA.14,38
Paradoxically, this high baseline of quality makes it
more difficult to demonstrate improvements than would
probably be the case in other health systems where imple-
mentation of PCMH has been evaluated and the baseline
Table 4. Emergency Department Visits, Hospitalizations, and Pi2
Scores for Fiscal Year 2012
Pi2
Score Clinics, No.
Emergency Department Visits
per 1000 Patients, No.a
Hospitalizations per 1000
Patients, No.a
5 to 8 77 188 68
2 to 4 213 227 77
−1 to 1 346 286 87
−4 to −2 190 289 83
−7 to −5 87 245 74
P valueb
… <.001 .99
Abbreviation: Pi2
, PACT [Patient
Aligned Care Team] Implementation
Progress Index.
a
Adjusted for age, Elixhauser
comorbidity score, and
community-based outpatient
clinics.
b
P values represent test for trend.
Table 5. Effects of PACT Initiative Among Sites With More Effective or Less Effective Implementation for ACSC and Total Hospitalizations
Pi2
Scorea
Quarterly Hospital Admissions for ACSCs per 1000 Patients, No. Quarterly Total Hospital Admissions per 1000 Patients, No.
Predicted With
PACT Initiative
Predicted Without
PACT Initiative
Absolute Difference,
No. (%)b
Predicted With
PACT Initiative
Predicted Without
PACT Initiative
Absolute Difference,
No. (%)
Patients <65 y
5 to 8 2.28 2.63 −0.35 (−13.4) 26.12 27.43 −1.31 (−4.8)
−7 to −5 2.53 2.61 −0.08 (−3.0) 25.20 24.33 0.87 (3.6)
Patients >65 y
5 to 8 3.68 3.85 −0.17 (−4.6) 21.75 22.21 −0.46 (−2.1)
−7 to −5 4.42 4.33 0.09 (2.1) 23.47 22.37 1.10 (4.9)
Abbreviations: ACSC, ambulatory care sensitive condition; PACT, Patient Aligned Care Team; Pi2
, PACT Implementation Progress Index.
a
Pi2
scores of 5 to 8 indicate more effective implementation; Pi2
scores of −7 to −5, less effective implementation.
b
All differences were significant at P < .001.

quality of care was substantially lower based on comparable
measures.2
The favorable findings from our analysis may
partly reflect the extensive improvements in clinical and
resource infrastructure that the VHA has made since the
1990s, such as the use of electronic prescribing and a univer-
sal electronic health record and deployment of pharmacists,
dieticians, social workers, and mental health professionals in
many primary care clinics.
These analyses have several limitations. First, several of
the domain scores rely on self-report, which are subject to
biases, including response bias, framing bias, and others.
However, we used well-validated measures, augmented
these data with important team-based care domains from our
primary care personnel survey, and used patient report to
capture comprehensiveness of care that other measures may
not include.15,39
Second, our primary care personnel survey
had a low response rate, but our results were consistent with
those from other surveys of primary care providers40,41
and
with those from a survey of all VA employees. Third, the
cross-sectional design of the study did not permit assessing
change over time, although this is planned in future studies.
Conclusions
We found that the Pi2
score was favorably associated with pa-
tientsatisfaction,staffburnout,qualityofcare,anduseofhealth
care services. Our results may apply only to large integrated
health systems that include a robust and integrated electronic
health record and a well-developed quality improvement sys-
tem that provides feedback to clinics and providers. All pri-
mary care providers in the VHA, for example, have ready ac-
cesstodetailedinformationabouttheirpatientpanels,including
the likelihood of admission or death (updated weekly), as well
as patients’ use of a range of inpatient, outpatient, and care co-
ordination services.42
However, as accountable care organiza-
tions evolve, this type of patient-centered measurement could
be adopted by other large integrated health systems.
ARTICLE INFORMATION
Accepted for Publication: April 25, 2014.
Published Online: June 23, 2014.
doi:10.1001/jamainternmed.2014.2488.
Author Affiliations: Seattle Center of Innovation
for Veteran-Centered and Value-Driven Care, VA
Puget Sound Health Care System, Seattle,
Washington (Nelson, Helfrich, Sun, Hebert, Liu,
Dolan, Taylor, Maynard, Hernandez, Randall);
General Internal Medicine Service, VA Puget Sound
Health Care System, Seattle, Washington (Nelson,
Fihn); Department of Medicine, University of
Washington School of Medicine, Seattle (Nelson,
Fihn); Department of Health Services, University of
Washington School of Public Health, Seattle
(Helfrich, Sun, Hebert, Liu, Wong, Maynard,
Hernandez, Randall); Office of Analytics and
Business Intelligence, Veterans Health
Administration, Washington, DC (Sanders, Curtis,
Fihn); Office of Patient Care Services, US
Department of Veterans Affairs, Washington, DC
(Schectman); Office of Clinical Operations, US
Department of Veterans Affairs, Washington, DC
(Stark).
Author Contributions: Dr Nelson had full access to
all the data in the study and takes responsibility for
the integrity of the data and the accuracy of the
data analysis.
Study concept and design: Nelson, Helfrich, Hebert,
Dolan, Wong, Hernandez, Schectman, Stark, Fihn.
Acquisition, analysis, or interpretation of data: All
authors.
Drafting of the manuscript: Nelson, Helfrich,
Sanders, Fihn.
Critical revision of the manuscript for important
intellectual content: Nelson, Helfrich, Sun, Hebert,
Liu, Dolan, Taylor, Wong, Maynard, Hernandez,
Sanders, Randall, Curtis, Schectman, Stark, Fihn.
Statistical analysis: Nelson, Sun, Hebert, Liu, Dolan,
Taylor, Wong, Maynard, Sanders, Randall.
Obtained funding: Fihn.
Administrative, technical, or material support:
Nelson, Helfrich, Dolan, Hernandez, Sanders,
Randall, Curtis, Schectman, Stark, Fihn.
Study supervision: Nelson, Schectman, Fihn.
Conflict of Interest Disclosures: None reported.
Funding/Support: This work was supported by the
VHA Office of Patient Care Service.
Role of the Sponsors: This study was conducted as
part of VHA Health Care Operations in accordance
with VHA Handbooks 1605.1 and 1605.2. The study
team had full responsibility for the design and
conduct of the study; collection, management,
analysis, and interpretation of the data; and
preparation of the manuscript. The study was
reviewed through normal administrative channels.
Additional Contributions: Data for this report
were developed by the national evaluation team at
the PACT Demonstration Lab Coordinating Center
and the VHA Office of Analytics and Business
Intelligence. The VHA Office of Primary Care
Operations is responsible for PACT implementation,
and the VHA Office of Patient Care Services is
responsible for the PACT Demonstration Lab
program. John Messina, BA, was paid to assist with
data acquisition and administrative support.
Previous Presentation: This study was presented
at the Society for General Internal Medicine Annual
Meeting; April 25, 2014; San Diego, California. This
study was also presented at the Academy Health
National Meeting; June 10, 2014; San Diego,
California.
REFERENCES
1. Stange KC, Nutting PA, Miller WL, et al. Defining
and measuring the patient-centered medical home.
J Gen Intern Med. 2010;25(6):601-612.
2. Werner RM, Duggan M, Duey K, Zhu J, Stuart EA.
The patient-centered medical home: an evaluation
of a single private payer demonstration in New
Jersey. Med Care. 2013;51(6):487-493.
3. Nielsen M, Langner B, Zema C, Hacker T, Grundy
P. Benefits of implementing the primary care
patient-centered medical home: a review of cost &
quality results, 2012. http://www.pcpcc.org/guide
/benefits-implementing-primary-care-medical-home.
Patient-Centered Primary Care Collaborative,
September 2012. Accessed May 7, 2014.
4. Liss DT, Fishman PA, Rutter CM, et al. Outcomes
among chronically ill adults in a medical home
prototype. Am J Manag Care. 2013;19(10):e348-e358.
5. Day J, Scammon DL, Kim J, et al. Quality,
satisfaction, and financial efficiency associated with
elements of primary care practice transformation:
preliminary findings. Ann Fam Med. 2013;11(suppl 1):
S50-S59.
6. Jaén CR, Ferrer RL, Miller WL, et al. Patient
outcomes at 26 months in the patient-centered
medical home National Demonstration Project. Ann
Fam Med. 2010;8(suppl 1):S57-S67, S92.
7. Reid RJ, Fishman PA, Yu O, et al.
Patient-centered medical home demonstration:
a prospective, quasi-experimental, before and after
evaluation. Am J Manag Care. 2009;15(9):e71-e87.
8. Jackson GL, Powers BJ, Chatterjee R, et al. The
patient-centered medical home: a systematic
review. Ann Intern Med. 2013;158(3):169-178.
9. Solberg LI, Asche SE, Fontaine P, Flottemesch TJ,
Anderson LH. Trends in quality during medical home
transformation. Ann Fam Med. 2011;9(6):515-521.
10. Solberg LI, Asche SE, Fontaine P, Flottemesch
TJ, Pawlson LG, Scholle SH. Relationship of clinic
medical home scores to quality and patient
experience. J Ambul Care Manage. 2011;34(1):57-66.
11. Rosland AM, Nelson K, Sun H, et al. The
patient-centered medical home in the Veterans
Health Administration. Am J Manag Care. 2013;19
(7):e263-e272.
12. Berenson RA, Hammons T, Gans DN, et al.
A house is not a home: keeping patients at the
center of practice redesign. Health Aff (Millwood).
2008;27(5):1219-1230.
13. Kizer KW. The “new VA”: a national laboratory
for health care quality management. Am J Med
Quality. 1999;14(1):3-20.
14. Jha AK, Perlin JB, Kizer KW, Dudley RA. Effect
of the transformation of the Veterans Affairs Health
Care System on the quality of care. N Engl J Med.
2003;348(22):2218-2227.
15. Burton RA, Devers KJ, Berenson RA.
Patient-centered medical home recognition tools:
a comparison of ten surveys’ content and
operational details. http://www.urban.org
/publications/412338.html. Washington, DC: Urban
Institute; 2012. Accessed February 1, 2014.

16. Scholle SH, Vuong O, Ding L, et al.
Development of and field test results for the CAHPS
PCMH Survey. Med Care. 2012;50(suppl):S2-S10.
17. Wright SM, Craig T, Campbell S, Schaefer J,
Humble C. Patient satisfaction of female and male
users of Veterans Health Administration services.
J Gen Intern Med. 2006;21(3)(suppl 3):S26-S32.
18. Helfrich CD, Dolan ED, Simonetti J, et al.
Elements of team-based care in a patient-centered
medical home are associated with lower burnout
among VA primary care employees. J Gen Intern Med.
2014. doi:10.1007/s11606-013-2702-z.
19. Shen Y, Hendricks A, Zhang S, Kazis LE. VHA
enrollees’ health care coverage and use of care. Med
Care Res Rev. 2003;60(2):253-267.
20. Perlin JB, Kolodner RM, Roswell RH. The
Veterans Health Administration: quality, value,
accountability, and information as transforming
strategies for patient-centered care. Am J Manag
Care. 2004;10(11, pt 2):828-836.
21. Schaufeli WB, Enzmann D, Girault N.
Measurement of burnout: a review. In: Schaufeli
WB, ed. Professional Burnout: Recent Developments
in Theory and Research. Philadelphia, PA: Taylor &
Francis; 1993:199-215.
22. Wheeler DL, Vassar M, Worley JA, Barnes LL.
A reliability generalization meta-analysis of
coefficient alpha for the Maslach Burnout
Inventory. Educ Psychol Meas. 2011;71(1):231-244.
doi:10.1177/0013164410391579.
23. Maslach C, Jackson SE. The measurement of
experienced burnout. J Organiz Behav. 1981;2(2)
99-113. doi:10.1002/job.4030020205.
24. Rohland BM, Kruse GR, Rohrer JE. Validation of
a single-item measure of burnout against the
Maslach Burnout Inventory among physicians.
Stress Health. 2004;20(2):75-79. doi:10.1002/smi
.1002.
25. Leiter MP, Shaughnessy K. The areas of worklife
model of burnout: tests of mediation relationships.
Ergonomia. 2006;28:327-341.
26. Goulet JL, Erdos J, Kancir S, et al. Measuring
performance directly using the Veterans Health
Administration electronic medical record:
a comparison with external peer review. Med Care.
2007;45(1):73-79.
27. Agency for Healthcare Research and Quality.
Prevention quality indicators. http://www
.qualityindicators.ahrq.gov/modules/pqi_resources
.aspx. Accessed February 28, 2014.
28. Elixhauser A, Steiner C, Harris DR, Coffey RM.
Comorbidity measures for use with administrative
data. Med Care. 1998;36(1):8-27.
29. Cuzick J. A Wilcoxon-type test for trend. Stat
Med. 1985;4(1):87-90.
30. Benjamini Y, Yekutieli D. The control of the
false discovery rate in multiple testing under
dependency. Ann Stat. 2001;29:1165-1188.
31. Hebert PLLC, Wong ES, Hernandez SE, et al.
The economic effects and return on investment of
the Veterans Health Administration’s Patient
Centered Home Initiative, 2010 through 2012.
Health Aff. In press.
32. Liu CF, Chapko M, Bryson CL, et al. Use of
outpatient care in Veterans Health Administration
and Medicare among veterans receiving primary
care in community-based and hospital outpatient
clinics. Health Serv Res. 2010;45(5, pt 1):1268-1286.
33. Yoon J, Rose DE, Canelo I, et al. Medical home
features of VHA primary care clinics and avoidable
hospitalizations. J Gen Intern Med. 2013;28(9):1188-
1194.
34. Holmboe ES, Arnold GK, Weng W, Lipner R.
Current yardsticks may be inadequate for
measuring quality improvements from the medical
home. Health Aff (Millwood). 2010;29(5):859-866.
35. Friedberg MW, Safran DG, Coltin KL, Dresser M,
Schneider EC. Readiness for the patient-centered
medical home: structural capabilities of
Massachusetts primary care practices. J Gen Intern
Med. 2009;24(2):162-169.
36. Martsolf GR, Alexander JA, Shi Y, et al. The
patient-centered medical home and patient
experience. Health Serv Res. 2012;47(6):2273-2295.
37. Gray BM, Weng W, Holmboe ES. An assessment
of patient-based and practice infrastructure-based
measures of the patient-centered medical home:
do we need to ask the patient? Health Serv Res.
2012;47(1, pt 1):4-21.
38. Kerr EA, Gerzoff RB, Krein SL, et al. Diabetes
care quality in the Veterans Affairs Health Care
System and commercial managed care: the TRIAD
study. Ann Intern Med. 2004;141(4):272-281.
39. Birnberg JM, Drum ML, Huang ES, et al.
Development of a safety net medical home scale for
clinics. J Gen Intern Med. 2011;26(12):1418-1425.
40. Shanafelt TD, Boone S, Tan L, et al. Burnout
and satisfaction with work-life balance among US
physicians relative to the general US population.
Arch Intern Med. 2012;172(18):1377-1385.
41. Lewis SE, Nocon RS, Tang H, et al.
Patient-centered medical home characteristics and
staff morale in safety net clinics. Arch Intern Med.
2012;172(1):23-31.
42. Wang L, Porter B, Maynard C, et al. Predicting
risk of hospitalization or death among patients
receiving primary care in the Veterans Health
Administration. Med Care. 2013;51(4):368-373.

Va pcmh study 6 2014[1]

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

Similaire à Va pcmh study 6 2014[1]

Similaire à Va pcmh study 6 2014[1] (20)

Plus de Paul Grundy

Plus de Paul Grundy (20)

Dernier

Dernier (20)

Va pcmh study 6 2014[1]