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Reliability of blood pressure measurements: Implications for evaluating control programs
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ABSTRACTS: HIGH BLOOD PRESSURE CONTROL
A-79 Implications for Evaluating Control Programs. DONALD S. SHEPARD,Veterans Administration Outpatient Clinic, 17 Court St., Boston, Massachusetts 02108.
Reliability of Blood Pressure Measurements:
Random fluctuations in blood pressure complicate the design and evaluation of screening and treatment programs. The coefficient of reliability (G), an index of the severity of such fluctuations, is the ratio of variance of individuals’ true pressures to the variance of their measured pressures under some specified procedure. To estimate G, a statistical model was developed in which true blood pressure drifts according to a type of random walk. Correlations between blood pressure measurements at different examinations up to 18 years apart in the Framingham Study showed a pattern consistent with the model. For diastolic pressure in males, for example, the two-parameter model explained 94% of the variance among 45 correlations and estimated G for a single reading as 0.67. The model implies that elevations in true blood pressure may decline spontaneously over several years in some hypertensives. The model also shows how the reliability of an average of several readings increases (and random error decreases) with the number and type of replications. For example, two measurements at separate visits generate the same reliability as six readings at the same visit. This coefficient can be used to decide how many measurements of blood pressure should be obtained in screening, treatment, and compliance programs, and to refine before and after evaluations of such programs by correcting the statistical artifact of regression to the mean.
A-80 Long-Term
Treatment and Compliance.
JUDITH K. SKINNER, Cardiovascular Clinic, 3300 Northwest
56th, Oklahoma City, Oklahoma 73112. Long-term management of a hypertensive population by a nurse provider in a fee-for-service, private practice is, we believe, acceptable to patient compliance and reduces the morbidity of hypertension. Studies show that 50% of hypertensive patients drop out of care within 1 year and of those under care 40% do not take enough medicine to achieve systematic blood pressure reduction. Over the past 5 years 1,127 hypertensive patients have entered the hypertensive clinic. Our objective is to show how we have controlled 78% at 150/90or less and 68% at 140/90or less. Attrition averages 5% annually. The nurse conducts programs in patient education and interacts with a computer which serves to automate scheduling, data collection, review of prior experience, choice of therapy, and audit of effectiveness of the program. At any time the individual patient’s response to therapy can be displayed graphically or the entire clinic population can be reviewed and analyzed. Therapeutic modalities used are sodium restriction, weight reduction, relaxation techniques, exercise, and pharmacologic therapy. Long-term management of hypertension by a nurse provider working with clinical algorithm is effective, acceptable, and practical when coupled with suitable education, motivation, and follow-up.
A-81 in Blood Pressure Control in a Neighborhood Health Center. DONALD A. SMITH, Martin Luther King Jr. Health Center, Bronx, New York; PETER L. SCHNALL; ROCHELLE KERN.
Reasons for Variability
The Dr. Martin Luther King Jr. Health Center has developed a computerized hypertension surveillance system for 2,600 registered hypertensives which reports quarterly to physicians and teams on the percentage of their hypertensives under control (BP s 140/9Ofor age s 49; BP c 160/95for age 2 50). Overall agency control level is 67%, but 10 full time physicians vary from 55 to 90% in the percentage of their patients under control. Two questions were asked in an attempt to understand this variance: (1) What variables best correlate with the blood pressure level among treated hypertensives? (2) What variables best distinguish physicians with low-level control from those with a higher level control in their patient populations? Variables analyzed included: patient age, sex, race, Medicaid status, home address, weight, length of
ABSTRACTS: HIGH BLOOD PRESSURE CONTROL
A-79 Implications for Evaluating Control Programs. DONALD S. SHEPARD,Veterans Administration Outpatient Clinic, 17 Court St., Boston, Massachusetts 02108.
Reliability of Blood Pressure Measurements:
Random fluctuations in blood pressure complicate the design and evaluation of screening and treatment programs. The coefficient of reliability (G), an index of the severity of such fluctuations, is the ratio of variance of individuals’ true pressures to the variance of their measured pressures under some specified procedure. To estimate G, a statistical model was developed in which true blood pressure drifts according to a type of random walk. Correlations between blood pressure measurements at different examinations up to 18 years apart in the Framingham Study showed a pattern consistent with the model. For diastolic pressure in males, for example, the two-parameter model explained 94% of the variance among 45 correlations and estimated G for a single reading as 0.67. The model implies that elevations in true blood pressure may decline spontaneously over several years in some hypertensives. The model also shows how the reliability of an average of several readings increases (and random error decreases) with the number and type of replications. For example, two measurements at separate visits generate the same reliability as six readings at the same visit. This coefficient can be used to decide how many measurements of blood pressure should be obtained in screening, treatment, and compliance programs, and to refine before and after evaluations of such programs by correcting the statistical artifact of regression to the mean.
A-80 Long-Term
Treatment and Compliance.
JUDITH K. SKINNER, Cardiovascular Clinic, 3300 Northwest
56th, Oklahoma City, Oklahoma 73112. Long-term management of a hypertensive population by a nurse provider in a fee-for-service, private practice is, we believe, acceptable to patient compliance and reduces the morbidity of hypertension. Studies show that 50% of hypertensive patients drop out of care within 1 year and of those under care 40% do not take enough medicine to achieve systematic blood pressure reduction. Over the past 5 years 1,127 hypertensive patients have entered the hypertensive clinic. Our objective is to show how we have controlled 78% at 150/90or less and 68% at 140/90or less. Attrition averages 5% annually. The nurse conducts programs in patient education and interacts with a computer which serves to automate scheduling, data collection, review of prior experience, choice of therapy, and audit of effectiveness of the program. At any time the individual patient’s response to therapy can be displayed graphically or the entire clinic population can be reviewed and analyzed. Therapeutic modalities used are sodium restriction, weight reduction, relaxation techniques, exercise, and pharmacologic therapy. Long-term management of hypertension by a nurse provider working with clinical algorithm is effective, acceptable, and practical when coupled with suitable education, motivation, and follow-up.
A-81 in Blood Pressure Control in a Neighborhood Health Center. DONALD A. SMITH, Martin Luther King Jr. Health Center, Bronx, New York; PETER L. SCHNALL; ROCHELLE KERN.
Reasons for Variability
The Dr. Martin Luther King Jr. Health Center has developed a computerized hypertension surveillance system for 2,600 registered hypertensives which reports quarterly to physicians and teams on the percentage of their hypertensives under control (BP s 140/9Ofor age s 49; BP c 160/95for age 2 50). Overall agency control level is 67%, but 10 full time physicians vary from 55 to 90% in the percentage of their patients under control. Two questions were asked in an attempt to understand this variance: (1) What variables best correlate with the blood pressure level among treated hypertensives? (2) What variables best distinguish physicians with low-level control from those with a higher level control in their patient populations? Variables analyzed included: patient age, sex, race, Medicaid status, home address, weight, length of