Improving Hypertension Quality Measurement Using

Electronic Health Records

S Persell, AN Kho, JA Thompson, DW Baker

Feinberg School of Medicine

Northwestern University

Chicago, Illinois

Supported by award 1 K08 HS015647-01 from the Agency for Healthcare Research and Quality

Problems with Current Quality Measures

Simple intermediate outcome measures (e.g., blood pressure at last visit <140/90) may not reliably indicate who is truly receiving poor care

– A pt with controlled blood pressure runs out of meds and comes to clinic with BP 150/100

– A pt with coronary disease had an LDL cholesterol of 220 mg/dl, which decreased to 110 on a maximal dose of a statin but did not reach the goal of LDL < 100

Adverse Consequences

These limitations problematic as incentives based on performance measures increase

When used for internal quality improvement, measurement errors such as these may cause physicians to reject measure validity

…and the Solution?

Develop quality measures that more accurately capture what would be defined as poor care– i.e. higher specificity of failures

Electronic health records can help facilitate implementation of more complicated measures

Study Aims

To develop and apply increasingly more sophisticated measures of hypertension quality utilizing data available within an EHR

To compare the results of measured quality using simple outcome measures and more sophisticated measures

Methods

Design: retrospective observational cohort study

Setting: urban Internal Medicine practice with a commercial EHR (Epic)

Eligibility

– Hypertensive adults with 3 or more clinic visits between 7/05 and 12/06

Baseline Quality Measure

Baseline:

– Patients with hypertension recorded on their problem list, past medical history, or encounter diagnosis codes

– Blood pressure at last visit <140/90

– Blood pressure <130/80 if comorbid diabetes

Quality Measure 2:Relax Cutoff

Include last BP ≤ goal as satisfying measure

≤ 140/90

≤ 130/80 if diabetes

Quality Measure 3:Incorporate Average BP

If either the last or mean of last three BPs

are at goal, the patient is considered to

satisfy the measure

Quality Measure 4:Account for Aggressive Management

Include patients prescribed 3 or more different antihypertensive drug classes including a diuretic as satisfying the measure

– Beta blocker, calcium channel blocker, ACE or ARB, peripheral alpha blocker, centrally acting anti-adrenergic drug, or direct vasodilator

– AND diuretic

Quality Measure 5Account for Low Diastolic Blood

Pressure, A Safety Concern Studies suggest that for pts with coronary

artery disease and diabetes, lowering the diastolic BP below 70 mmHg may be harmful

Therefore, if patients with uncontrolled systolic blood pressure had diastolic pressure < 70 mmHg, they were consider to satisfy measure

Quality Measure 6:Include Patients with

Undiagnosed Hypertension Include in denominator patients with a mean

blood pressure ≥140/90 mmHg or ≥130/80

mmHg if the patient has comorbid diabetes

even if they do not have hypertension

recorded as a diagnosis

Study Population

N Age, mean (SD)

Female, %

Diagnosed hypertension

No diabetes

Diabetes

3933

1526

60 (14)

61 (12)

65

59

Undiagnosed hypertension

No diabetes

Diabetes

284

143

48 (15)

51 (12)

44

46

Variation Across Measures (no DM)

0

10

20

30

40

50

60

70

80

90

100

Per

cen

t co

ntr

olle

d

Last BP < 140/9058%

Last BP ≤ 140/9067%

Last or mean ≤ 140/90: 76%

≤ 140/90 or 3 drugs with diuretic: 83%

≤ 140/90 or 3 drugs w/ diuretic or low DBP: 84%

Include undiagnosed hypertension: 81%

0

10

20

30

40

50

60

70

80

90

100P

erce

nt c

ontr

olle

d

Last BP < 130/8030%

Last BP ≤ 130/8039%

Last or mean ≤ 130/80: 47%

≤ 130/80 or 3 drugs with diuretic: 73%

≤ 130/80 or 3 drugs w/ diuretic or low DBP: 76%

Include undiagnosed hypertension: 73%

Variation Across Measures (DM)

Results of Standard vs. Advanced Hypertension Quality Measures

58

30

8173

0102030405060708090

100

No diabetes Diabetes

Perc

en

t co

ntr

olled

Baseline Final

} Δ 23%

}Δ 43%

Limitations We used hypothetical quality measures to

demonstrate concept

Single site; generalizability not known

– Would be difficult, but not impossible, to apply measures at sites without an EHR

Data within EHRs may be incomplete

Still may miss important exceptions

– Home blood pressure controlled

Conclusions

Small changes in measure criteria produce large changes in measured quality

Many patients who did not satisfy the simple measure were receiving aggressive care

More sophisticated measures may better align external measurement with internal quality improvement

Implications More sophisticated measures may:

– Improve detection of true quality problems that need attention by MDs and other staff

– Remove incentives to stop caring for patients with resistant hypertension

– Remove incentives to unsafely or unnecessarily over treat some patients