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A New Approach for Measuring Quality of Care for Women With Hypertension
Steven M. Asch, MD, MPH;
Eve A. Kerr, MD, MPH;
Pablo Lapuerta, MD;
Anandi Law, PhD;
Elizabeth A. McGlynn, PhD
Arch Intern Med. 2001;161:1329-1335.
ABSTRACT
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Background Guidelines for care of hypertensive patients have proliferated recently,
yet quality assessment remains difficult in the absence of well-defined measurement
systems. Existing systems have not always linked process measures to blood
pressure outcomes.
Methods A quality measurement system was developed and tested on hypertensive
women in a West Coast health plan. An expert panel selected clinically detailed,
evidence-explicit indicators using a modified Delphi method. Thirteen indicators
(1 screening, 5 diagnostic, 5 treatment, and 2 follow-up indicators) were
selected by this process. Trained nurses used a laptop-based tool to abstract
data from medical records for the most recent 2 years of care.
Results Of 15 004 eligible patients with hypertensive and other chronic
disease codes, 613 patients were sampled, all eligible for the screening indicator.
Of these, 234 women with an average blood pressure of 140/90 mm Hg or more,
or a documented diagnosis of hypertension, were studied for the remaining
indicators. The average woman received 64% of the recommended care.
Most patients did not receive adequate initial history, physical examination,
or laboratory tests. Only 37% of hypertensive women with persistent elevations
to more than 160/90 mm Hg had changes in therapy or lifestyle recommended.
The average adherence proportion to all indicators was lower in patients with
uncontrolled blood pressure (>140/90 mm Hg) than in those with controlled
blood pressure (54% vs 73%; P<.001).
Conclusions Quality of hypertensive care falls short of indicators based on randomized
controlled trials and national guidelines. Poor performance in essential care
processes is associated with poor blood pressure control.
INTRODUCTION
TREATMENT of hypertension has contributed to a reduction in cardiovascular
mortality during the past 3 decades, increasing life expectancy in the United
States by 5 years.1 Despite overwhelming evidence
of the benefits of controlling hypertension and the availability of a plethora
of practice guidelines, almost half of the US hypertensive population remains
untreated and less than 27% of hypertensive patients achieve the recommended
blood pressure (BP) target of 140/90 mm Hg.2
Lack of access and poor patient adherence to prescribed regimens explain part
of this deficit, but quality problems in care processes contribute as well.3-5
Existing systems that assess quality of care have some limitations.
They often use a "leading indicator" approach, collecting data for only a
few dimensions of quality of care. For example, hypertensive quality monitoring
systems often focus exclusively on treatment and ignore the contribution of
other clinical functions, such as screening, diagnosis, and follow-up.4 More generally, quality monitoring systems may fail
to collect sufficient clinical detail to evaluate provider decision making,
relying instead on less precise but easily obtained electronic data. The scientific
rationale for indicators and the selection process is either lacking or not
specified. Furthermore, few monitoring systems have been applied selectively
to women, even though women account for a majority of visits to physicians.6-7
To address these limitations, an alternate approach (the quality assessment
[QA] tool) was developed to assess quality of care. More than 1000 clinically
detailed indicators for men, women, children, and adolescents in about 50
clinical areas, including hypertension, were developed.7
The project took a comprehensive approach to measuring process quality for
hypertensive care, including screening for high BP at physician visits, diagnostic
examination of hypertensive patients, appropriate use of both nonpharmacologic
and pharmacologic therapies, adequate monitoring of treatment and response
over time, control of BP levels, and provision of adequate follow-up.8 The evidence linking each indicator to desired outcomes
was assessed by means of proved quantitative models to measure expert opinion.2, 9
This article describes performance of the new measurement system when
applied to hypertensive female patients in a single health maintenance organization
(HMO). It describes the frequency of quality deficits in hypertension care
and evaluates the association of these deficits with BP control.
METHODS
DEVELOPING QUALITY-OF-CARE INDICATORS FOR HYPERTENSION
The methods used to construct the QA tool indicators are described elsewhere.8, 10 Explicit process indicators for quality
of care of hypertensive patients were developed on the basis of a review of
the scientific literature covering the continuum of care from initial screening
through diagnosis, treatment, and follow-up. Draft indicators were chosen
on the basis of the following criteria:
- Link to desirable outcomes of reduced BP, stroke, and myocardial
infarction
- Clinical importance
- Strength of evidence supporting use of the process
- Importance and likelihood of accurate documentation of component
variables
- Appropriateness of holding providers accountable for indicated
care
- Generalizability to a variety of clinical settings
A panel of physicians reviewed the indicators and the supporting evidence.
The 9 members were recommended by relevant specialty societies and practiced
in internal medicine, cardiology, pulmonology, geriatrics, and family medicine
in academic, managed care, and other community settings throughout the country.
They rated each draft indicator's feasibility and validity on a 9-point Likert
scale, both before and during a face-to-face meeting.10
Indicators were included in the final set if their final median validity score
was 7 or higher and median feasibility score was 4 or higher.
Of the 10 draft hypertension indicators, the panel process modified
the text of 7 (including dropping 5 subparts), accepted 3 unchanged, and added
3. Examples of the dropped indicator subparts included certain initial laboratory
examinations (eg, calcium, uric acid, and electrocardiography) and a requirement
that patients with stage 3 hypertension receive lifestyle modification before
pharmacotherapy.2
The final 13 quality-of-care indicators included 1 screening indicator,
5 diagnostic indicators, 5 treatment indicators, and 2 follow-up indicators
(Table 1). Six were supported
by randomized controlled trials and 7 by expert opinion, such as the Joint
National Committee guidelines.2, 11
Diagnostic indicators reflect current knowledge and practice with respect
to categorizing patients accordin g to the following factors: BP measurement
and risk stratification as recommended by the Joint National Committee guidelines
(indicators 2, 3, and 6), searching for secondary hypertension (indicators
3 and 5), looking for potential effects of certain drugs on BP (indicator
4), and establishing a metabolic baseline for monitoring adverse effects of
antihypertensive therapy (indicator 5). Treatment indicators included patient
counseling for nonpharmacologic high BP management (indicators 7 and 8), conditions
for prescribing antihypertensive medication (indicators 9 and 10), and recommended
medication for specific comorbidities (indicator 11). Finally, follow-up indicators
reflected the importance of regular monitoring of hypertensive patients to
control the disease (indicators 12 and 13) (Table 1).
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Indicators of Quality of Care for Women in a Health Maintenance Organization
During a 2-Year Period*
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TESTING QUALITY-OF-CARE INDICATORS IN AN HMO
The variables needed to calculate these indicators were incorporated
into medical record abstraction software by means of a branching logic to
improve data collection efficiency. Adherence to the selected quality-of-care
indicators was evaluated in a female population as part of a larger study
of the quality of women's health care. Medical record data for female patients
in a group-model HMO were reviewed during a 2-year period.
SUBJECTS
The target population included all women continuously enrolled for at
least 13 months who visited a provider at a single HMO site at least once
during calendar years 1996 and 1997. Annual indicators were calculated with
the most recent 13-month period, allowing some room for patient scheduling
and other difficulties. With the use of presence or absence of relevant International Classification of Diseases, Ninth Revision,
codes for encounter data during this period, the target population was divided
into 3 strata according to age and presence or absence of specific chronic
conditions. The numbers of eligible patients in each strata were as follows:
stratum 1 (<52 years and current diagnosis of hypertension, diabetes, asthma,
or breast mass), 1130 patients; stratum 2 (<52 years and none of the chronic
conditions listed in stratum 1), 13 194 patients; and stratum 3 ( 52
years and current diagnosis of hypertension), 680 patients.
Patients were then randomly sampled in each stratum. In total, 613 patients
(271 in stratum 1, 243 in stratum 2, and 99 in stratum 3) were selected for
this study.
DATA COLLECTION
Nurses hired specifically for this project were trained to use the data
collection software. Data were abstracted simultaneously for all providers
from centrally located medical records. Data included all BP measurements
performed during the study period, all medications prescribed, number and
dates of physician visits, and other variables needed to calculate the quality-of-care
indicators for preventive care (not reported herein) and hypertension. Average
abstraction time was approximately 42 minutes per patient, about 30% of which
was relevant to hypertension alone.
DATA ANALYSES
Person-weights were calculated for each sample stratum and assigned
to individuals selected within that stratum to extrapolate results so that
they would represent the entire eligible plan population. Sample person-weights
were calculated as the inverse of the ratio of the number sampled to the number
in the stratum. Both weighted and unweighted patient numbers are presented,
although means, proportions, and SEs are adjusted for sample weights.
Abstracted data were then analyzed to determine the eligibility of each
patient for every indicator. Eligibility was determined from a set of specific
predetermined criteria for each indicator. The entire study population satisfied
criteria for indicator 1, the screening indicator. For the other 12 indicators,
patients must have had a recorded diagnosis of hypertension or an average
BP greater than 140/90 mm Hg during the study period, depending on the indicator.
For example, to be eligible for indicator 3a (Table 1), there had to be a progress note indicating that hypertension
was a new diagnosis. In many cases, stage of hypertension from the sixth report
of the Joint National Committee2 had to be
calculated to determine eligibility. Stage 1 or mild hypertension includes
patients with average systolic BP (SBP) of 140 to 159 mm Hg or average diastolic
BP (DBP) of 90 to 99 mm Hg; stage 2 (moderate), SBP of 160 to 179 mm Hg or
DBP of 100 to 109 mm Hg; and stage 3 (severe), SBP of 180 to 209 mm Hg or
DBP of 110 to 119 mm Hg. If systolic and diastolic stages conflicted, the
higher of the 2 was chosen. If stage was not calculable from the record (BP
measurement missing), the patient was not eligible for the indicator.
Adherence to indicators was similarly determined. For example, for indicator
3a, the patient had to have the presence or absence of any of the following
noted sometime during the study period: family or personal history of coronary
artery disease, cerebrovascular accident, diabetes, or hyperlipidemia. Eligible
women who received the care defined in each indicator were counted and total
adherence (percentage of eligible patients who received the care) to each
indicator was calculated. Standard errors were calculated by means of binomial
assumptions, correcting for design effects.
The screening indicator was excluded from summary scores. Summary scores
were calculated as the proportion of indicators for which each patient was
eligible where the patient received the recommended care. For example, if
a woman was eligible for 3 indicators but received the indicated care for
only 2, her summary score would be 67%. Alternative calculations of the summary
score using the indicator rather than the person as the unit of analysis were
also performed. In these calculations, the total number of indications in
the population formed the denominator, while the total number of instances
in which patients received the indicated care formed the numerator.
The average adherence scores were divided into tertiles, and the association
with the proportion of patients with adequate control (average BP,  140/90
mm Hg) was calculated for each tertile. Similarly, the average adherence was
calculated for patients with controlled (average, 140/90 mm Hg) and uncontrolled
(>140/90 mm Hg) BP. A  2 statistic was used to determine whether
average adherences for the comparisons were statistically different. Analyses
were performed with SAS software package (SAS Institute Inc, Cary, NC).
SENSITIVITY ANALYSES
Sensitivity analyses were performed by varying eligibility criteria
for 3 indicators. For treatment indicators 7 and 8, only new hypertensive
patients rather than all hypertensive patients were included. For follow-up
indicator 13, the definition of persistent elevation was changed from an SBP
of greater than 160 mm Hg to an SBP of greater than 140 mm Hg.
RESULTS
POPULATION
With the screening indicator, 467 eligible women were included in the
study. The hypertensive population, ie, patients eligible for the nonscreening
indicators (indicators 2-13), included 234 subjects. All means, proportions,
and SEs are adjusted for design effects. This hypertensive population had
been enrolled in the plan for an average of 8.6 years and for 22 months of
the 24-month study period. They had an average of 4.1 other acute or chronic
medical diagnoses each (eg, upper respiratory tract infection and diabetes)
during the 2-year study period. The average age was 49 years, and 73% had
an average SBP of greater than 140 mm Hg or an average DBP of greater than
90 mm Hg.
INDICATORS OF CARE
Eligibility and adherence data for each indicator are reported in Table 1. Eligibility varied greatly between
indicators. All 467 patients were eligible for the screening criteria. For
the diagnosis indicators, eligibility ranged between 1 and 160 of 234 hypertensive
patients. The number of women eligible for treatment indicators varied between
5 and 119, and follow-up indicators had the highest number of patients eligible
(234 and 151 for indicators 12 and 13, respectively).
Adherence proportions also varied greatly between indicators, from 0%
to 100%. Although some data on initial history and physical examination of
patients were documented, no patient had a comprehensive set of information
recorded (indicator 3). Medical counseling for nonpharmacologic management
of hypertension was recorded for only 3.7% of patients with mild to moderate
(stage 1-2) hypertension (indicator 7). At least some laboratory tests were
performed for a large proportion of patients, but they were comprehensive
for only 4.1% of the eligible population (indicator 5). Many patients with
persistent uncontrolled mild to moderate hypertension after 6 months of lifestyle
modifications did not receive any pharmacotherapy (indicator 9). About half
of hypertensive patients with diabetes received appropriate antihypertensive
treatment (indicator 11).
SUMMARY SCORES
Excluding indicator 1, hypertensive patients were eligible for an average
of 3 hypertension indicators. The average woman received care for 64% of the
indicators for which she was eligible. When the summary score was calculated
at the indicator rather than the person level, 60% of all indications for
care were satisfied.
None of the women in the lowest tertile of quality summary scores had
a controlled average BP (140/90 mm Hg) (Figure 1). Slightly more than a quarter (26%) had controlled BP
in the middle tertiles of quality, and 38% had controlled BP in the top tertile
of quality. Similarly, providers achieved a 73% score on indicators for which
they were eligible for women with average SBP of less than 140 mm Hg and DBP
of less than 90 mm Hg, compared with 54% for those with BP above 140/90 mm
Hg (P<.001). Changing the systolic threshold to
a less stringent threshold of 160 mm Hg did not affect the direction or statistical
significance of these results. The direction and statistical significance
persisted if only indicators based on randomized controlled trials were incorporated
into the summary score and if only nontreatment indicators were incorporated.
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Control status of blood pressure (BP) in hypertensive women as a
function of quality of care.
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SENSITIVITY ANALYSES
Because infrequently prescribed treatments in patients with long-standing
hypertension might have been overlooked, sensitivity of the results for 2
treatment indicators (indicators 7 and 8) to include only patients with newly
diagnosed hypertension was tested. For treatment indicator 7, the number of
eligible patients decreased (from 119 to 32) and the proportion receiving
indicated care increased (from 3.7% to 32.5%). The same sensitivity analysis
performed on treatment indicator 8 did not demonstrate any major difference
between new hypertensive patients and all hypertensive patients.
Since the development of the QA tool, changes in optimal care for hypertensive
patients with diabetes have occurred and calcium channel blockers may not
be a suitable treatment for this category of patients.12-13
The impact of dropping calcium channel blockers as a recommended treatment
for hypertensive patients with diabetes was assessed (indicator 11). Of the
7 patients who were eligible for this indicator, all 3 patients who received
care received only an angiotensin-converting enzyme inhibitor as therapy.
Thus, dropping the patients treated with calcium channel blockers had no impact
on the results.
The results for follow-up indicator 13 were insensitive to changing
the definition of persistent SBP elevation from 160 to 140 mm Hg; the adherence
proportion for both thresholds was very similar (35.1% vs 36.6%).
COMMENT
This study described the development of a new measurement system to
assess the quality of care for hypertension. Its component indicators were
clinically detailed, were subjected to rigorous evidence-explicit review,
and covered a continuum of care from screening through diagnosis, treatment,
and follow-up. Testing this part of the QA tool on a cohort of women enrolled
in a single HMO showed that care fell far short of the national guidelines.
Better performance in essential care process as assessed by the quality indicators
was associated with better BP control.
We found that the average hypertensive woman received 64% of recommended
care. This is consistent with a recent review of quality-of-care studies in
the United States, which reported that about 60% of patients received the
care recommended for their chronic diseases.14
Our results are also consistent with the average adherence rate for selected
clinical measures from the Health Plan Employer Data Information Set (HEDIS)
reported by the National Committee for Quality Assurance, which fell in the
60% to 70% range.15
Our study was designed to measure overall quality of hypertensive care
rather than to generate estimates at the individual indicator level. Nonetheless,
the pattern of deficits across the hypertensive care spectrum deserves mention.
Screening for elevated BP was performed on 84.2% of patients, a better result
than that reported by Ornstein and Jenkins.16
Almost all patients received annual follow-up. However, diagnostic procedures
at initial history, physical examination, and laboratory testing were documented
for less than a quarter of sampled patients; the number of new hypertensive
patients in the study was small, though, decreasing our precision. Many hypertensive
patients who should have received lifestyle interventions or pharmacotherapy
did not, even when analysis was restricted to new hypertensive patients to
assess ongoing infrequent prescriptions. Perhaps of even greater concern is
that only a third of those whose BP remained elevated (SBP of 140 or 160
mm Hg) after 6 months of therapy had any change in their therapy. Since a
long-term reduction of 5 to 6 mm Hg in DBP is associated with 35% to 40% lower
risk of stroke and 20% to 25% lower risk of coronary heart disease,17 a dramatic need for more aggressive treatment is
indicated.
Patients with uncontrolled hypertension received less of the indicated
care than did patients with controlled BP, suggesting a relationship between
process (quality of care measured by indicators) and outcome (BP levels) of
care. Linking process and outcome is an important goal of quality-of-care
assessment.4 However, previous attempts have
not always established a link between quality of hypertensive care and control
of hypertension. Haynes and colleagues18 reported
a positive link between 3 items of antihypertensive treatment and reducing
BP levels: decision to treat, vigor of prescribed medication, and compliance.
Using chart review analyses, Berlowitz and colleagues4
examined the care of hypertensive men in Veterans Affairs settings and made
the link between more intensive medical therapy and better BP control. Our
study is the first, to our knowledge, to link a broad measure of quality of
care to outcome. This relationship persisted if indicators measuring the quality
of therapy were excluded, leaving only diagnostic, screening, and follow-up
measures, although inferences about causation are premature in the absence
of longitudinal data.
The broader nature of these measures points the way to improving quality.
Leading quality standards such as HEDIS focus on the intermediate outcome
of BP,19 but in the absence of data on care
processes, providers may not be aware of what behavioral changes are likely
to improve outcome. Systems like the one presented herein allow for focused
evaluation of care for hypertensive patients and can be used longitudinally
to evaluate targeted quality improvement interventions.7
The quality measurement instrument reported herein has some limitations.
First, some care may have been delivered but poorly documented and thus not
detected by our instrument, biasing quality estimates downward. Nevertheless,
chronic disease care is increasingly delivered by teams of providers rather
than by a single individual, especially in managed care settings. This makes
clear documentation essential and the failure to document potentially detrimental
to patient care. The component indicators were selected explicitly so that
the absence of documentation was in and of itself evidence of poor quality.
Second, although some indicators are clearly more closely linked to outcomes
than are others, each indicator was weighted equally in its contribution to
the overall quality score in this first test of the QA tool. We elected to
use equal weights because we did not have a compelling method for assigning
differential weights. Third, we tested the instrument in only 613 patients
in a single health plan, and more extensive testing is under way. Fourth,
there are no randomized controlled trials supporting or refuting some of the
indicators. However, as much as 70% to 80% of all care delivered lacks such
support,20 and so rigorously conducted expert
panel methodology is a viable tool to extend the reach of quality measurement
instruments. Finally, optimal care of patients is evolving as research data
are being published. Since the development of the QA tool, recommendations
on management of hypertensive patients have changed (eg, calcium channel blockers
may not be a suitable treatment for hypertensive patients with diabetes12-13), and indicators need to be updated
regularly to capture the most recent advances in medical care.
Finally, the clinically detailed indicators presented herein require
chart review, a more costly process than pure electronic data analysis. However,
as part of a global measure designed to analyze charts of patients unselected
for condition, the hypertensive portion of the QA tool will benefit from maximizing
the amount of relevant data analyzed per abstracted case. We have estimated
that the QA tool will require half the sample size of the average HEDIS report,
substantially reducing costs.7 Systems with
similar sampling schemes cost $15 000 to $25 000 per measurement
cycle for 300 to 500 records, an amount within the resources of most plan
quality assessment budgets.21
Future work will develop methods of weighting indicators according to
their relative importance to patient outcomes. Further research should also
explore the validity and generalizability of the results by expanding evaluation
of the tool to other populations and larger sample sizes. Examining the correlation
of quality of care for hypertension with that for other conditions also may
provide valuable information about which factors most significantly affect
the quality of care within a health plan.
CONCLUSIONS
Using a new approach of detailed evaluation of quality of care in an
HMO indicates that physicians may not be aggressive enough in managing hypertension.
Data obtained with a performance evaluation system such as the QA tool can
pinpoint deficiencies in health care and provide critical insight to guide
quality improvement efforts.
AUTHOR INFORMATION
Accepted for publication October 3, 2000.
This study was supported by grants from Bristol-Myers Squibb, Princeton,
NJ; the Agency for Health Care Research and Quality, Washington, DC; the California
HealthCare Foundation, Oakland; and the Health Care Financing Administration,
Baltimore, Md. Drs Asch's and Kerr's time is supported by career development
awards from the Veterans Affairs Health Services Research and Development
Service, Washington.
Presented in part at the meeting of the American College of Cardiology,
Anaheim, Calif, March 14, 2000.
We thank Peggy Wallace, Alison DeCristofaro, Jennifer Hicks, and Karen
Connor for invaluable research assistance and Micki Fujisaki for her skilled
programming efforts.
This article was prepared with the assistance of BioMedCom Consultants
Inc, Montreal, Quebec.
Corresponding author and reprints: Steven M. Asch, MD, MPH, RAND,
1700 Main St, Santa Monica, CA 90407 (e-mail: sasch{at}rand.org).
From the Veterans Affairs Greater Los Angeles Health Care System, Los
Angeles, Calif (Dr Asch); Department of Medicine, University of California,
Los Angeles (Dr Asch); Center for Research on Quality in Health Care, RAND,
Santa Monica, Calif (Drs Asch, Kerr, Law, and McGlynn); Bristol-Myers Squibb
Pharmaceutical Research Institute, Princeton, NJ (Dr Lapuerta); Veterans Affairs
Center for Practice Management and Outcomes Research, Veterans Affairs Ann
Arbor Health Care System, Ann Arbor, Mich (Dr Kerr); Department of Medicine,
University of Michigan, Ann Arbor (Dr Kerr); and Western University of Health
Sciences, Pomona, Calif (Dr Law). Dr Asch is a consultant for Bristol-Myers
Squibb.
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