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Effect of a home monitoring system on hospitalization and resource use for patients with heart failure
Effect of a home monitoring system on hospitalization and resource use for patients with heart failure Paul A. Heidenreich, MD, MS,a Christine M. Ruggerio, RN, MSN,b and Barry M. Massie, MDc Palo Alto and San Francisco, Calif
Background Heart failure has a large medical and economic impact on the elderly. Past studies have shown that high-intensity multidisciplinary interventions at academic medical centers can reduce future hospitalizations. Our pilot study examined the effects of a low-intensity monitoring program on hospitalizations and cost of care for patients with heart failure treated by community physicians. Methods We enrolled 68 patients with heart failure (mean age 73 ± 13 years, 53% male) monitored by 31 physicians in a multidisciplinary program of patient education, daily self-monitoring, and physician notification of abnormal weight gain, vital signs, and symptoms. Comparisons of medical claims were made between the patients who received the intervention and a control group of 86 patients matched to the intervention group on medical claims during the preceding year.
Results Compared with the prior year, medical claims per year decreased in the intervention group ($8500 ± $13,000 to $7400 ± $11,400), whereas they increased in the control group ($9200 ± $15,000 to $18,800 ± $34,000, P < .05). Similar differences were observed for hospitalizations and total hospital days. The program’s effectiveness was unrelated to age, sex, or type of left ventricular dysfunction. Conclusions These findings suggest that a multidisciplinary program of patient education, monitoring, and physician notification can reduce resource use in patients with heart failure managed in a community setting. (Am Heart J 1999;138:633-40.)
See related Editorial on page 599. Heart failure is a major and growing health problem. Approximately 1 in 100 of the general population and 1 in 10 of the elderly are afflicted.1 Heart failure also accounts for a large proportion of medical expenditures2,3 and is now the most common indication for hospitalization in the Medicare population. Rehospitalization after a heart failure admission is also common, particularly in the elderly, 45% of whom are readmitted within 6 months.4 Because of the large medical and economic impact of heart failure, new strategies have been developed to reduce readmission rates. Several studies have found that multidisciplinary treatment, including patient education, social service consultation medication review, and intensive outpatient follow-up can improve compliFrom the aCardiology Section Department of the Veterans Affairs Medical Center, Palo Alto; the bSchool of Nursing and the Department of Medicine and Cardiovascular Research Institute at the University of California; and the cCardiology Division Department of the Veterans Affairs Medical Center, San Francisco. Supported by LifeMasters® Supported SelfCare SM, Inc., Newport Beach, Calif. Dr Heidenreich received support from the Agency for Health Care Policy and Research (training grant 00028-10). Submitted May 11, 1998; accepted July 28, 1998. Reprint requests: Paul Heidenreich, MD, MS, 111C Cardiology, Palo Alto VA Medical Center, 3801 Miranda Ave, Palo Alto, CA 94304. Copyright © 1999 by Mosby, Inc. 0002-8703/99/$8.00 + 0 4/1/94907
ance5 and reduce admission rates after hospital discharge.6-8 This focus on improved outpatient care is consistent with current clinical practice guidelines that recommend aggressive outpatient management for patients with left ventricular systolic dysfunction.9 In a pilot study, we demonstrated that a multidimensional program of patient education, monitoring, and physician notification was successful in reducing hospitalizations and length of stay for patients monitored in a heart failure clinic at an academic medical center.8 The purpose of this study was to determine if a similar program can be successful in the community setting, where care is provided through multiple private physician offices.
Methods Patients The study was conducted within a multispecialty medical group with 85 physicians and 15,000 patients in northern California. This group consists of multiple small practices (largely primary care) and functions as an independent practice association. Patients were eligible for the study if they were cared for by a physician within the medical group and their physician both agreed to participation and stated that the patient had a history of symptomatic heart failure. Potential patients with heart failure were identified with a claims database from April 1994 through October 1995. Recruitment began in early 1996. The patients’ physicians were contacted if the patient had a heart failure–related claim greater than $50, a hospitalization for heart failure, or an emergency room
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634 Heidenreich, Ruggerio, and Massie
Table I. Characteristics of the 68 enrolled patients Age (y) Male (%) Widowed (%) Medical history Diabetes (%) History of MI or revascularization (%) Sodium <136 mmol/dL (%)* Creatinine >1.5 mg/dL (%)* Echocardiography* Moderate systolic dysfunction (%) Left ventricular hypertrophy (%) Medications ACE inhibitor or hydralazine (%) Digoxin (%) Diuretic (%) Number of medications
73 ± 13 59 25 32 44 27 24 55 48 75 57 88 8±3
MI, Myocardial infarction. *Data are available for a subset of patients (sodium, 46%; creatinine, 44%; echocardiography, 58%).
visit for heart failure during the 19-month period. There were 128 patients identified; 26 of these were enrolled. The remaining 102 patients were not enrolled because the patient’s physician stated that the patient did not have symptomatic heart failure or would not agree to have the patient participate (n = 87), the patient had left the medical group (n = 10), or the patient refused (n = 5). An additional 42 patients were enrolled at the request of individual medical group physicians whose patients were not identified by the 19-month window. Thus a total of 68 patients participated in the program. All patients had class II to III New York Heart Association heart failure. There was no requirement for depressed systolic function. Echocardiographic estimates of systolic function and hypertrophy were obtained from laboratory reports from the last 5 years. Data were available only from the primary referral laboratory. The systolic function was considered moderately reduced if the estimated ejection fraction was between 30% and 45%, and mildly reduced if the ejection fraction was between 45% and 55%. All patient medications, comorbid conditions, age, sex, and marital status were recorded from patient interviews.
Home monitoring Each patient received a digital scale and an automatic blood pressure cuff and was instructed in their use. Each day the patient called a toll-free number and entered the systolic and diastolic blood pressure, pulse, weight, and any symptoms into a computerized voice answering system. A computer algorithm then checked the patient’s vital signs with an acceptable range previously set by the physician. If values were outside the accepted range, or if new symptoms of shortness of breath, chest pain, or edema were reported, then the computer paged a nurse who confirmed the reported data by calling the patient. Once confirmed, the abnormality was described in a 1-page fax to the physician. The fax also included a graph of recent vital signs, current medications, and the patient’s phone number. The program was designed to be an aid to, and not a replacement for, physician services. To maintain the doctor-patient relationship the program did not contact the physician at the
request of the patient. Patients were told to contact their doctors directly if they were concerned about their health. Each physician with a participating patient completed a form indicating at what level of blood pressure, heart rate, or weight gain they wished to be notified by fax. Default values were 200 mm Hg and 120 mm Hg for upper systolic and diastolic blood pressure, and 90 mm Hg and 40 mm Hg for lower systolic and diastolic blood pressure, 150 beats/min and 50 beats/min for upper and lower heart rate, and 5 pounds per week for weight gain.
Patient education Each patient received weekly educational mailings and a 10-minute call from a nurse. The mailings described 52 different topics related to heart failure (1 each week for 1 year), including diet, exercise, common therapies, as well as simple anatomy and physiology. The mailed materials were then discussed during the weekly telephone call, and the educational points were reinforced. New symptoms, medication changes, and visits to the physician were also recorded. The nurse provided only education, and did not suggest any changes in medical management. Each patient was offered an alpha-numeric pager that provided personalized medication reminders.
Quality of life and satisfaction Each patient was asked to complete the SF-36 survey.10 The SF-36 is a nonspecific health status questionnaire with 8 dimensions (physical functioning, social functioning, pain, mental health, vitality, role limitations from physical problems, role limitations from emotional problems, and general health). The survey was administered at baseline and then at 3 months after starting the program. In addition, patients completed satisfaction questionnaires after 3 months in the program.
Resource use We used 2 approaches to assess the effect of the program on resource use. First, the average claims per year before the intervention were compared with the claims per year during the intervention. Because this approach may be affected by regression to the mean, improvements in technology, and disease progression, we used a control group derived from the same medical group who had a heart failure–related claim between April 1994 and May 1995, and who generated at least 1 claim after March 1996 (indicating they were enrolled in the medical group for at least 3 months). These patients were matched 2:1 to intervention patients based on sex and 1995 claims. Analysis of these groups determined that age and other measures of resource use were similar. This process limited regression to the mean by using partially separate periods for identification of high claims patients (April 1994 to May 1995) and baseline measurements (January 1995 to December 1995). The main outcome of interest was the difference in total claims per year from 1995 to 1996 (the intervention year). Total claims were used instead of heart failure claims because of inaccuracies in coding of diagnoses. In preliminary analysis we found that many admissions for heart failure (based on patient and physician description) were not coded as heart failure (poor sensitivity). A similar problem was noted for the
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Figure 1
Claims during intervention period for program and matched control groups. Kaplan-Meier plot shows cumulative percentage of patients at each level of total claims per patient per year. Area above curve is a measure of mean claims per patient per year. A difference between program and control groups is observed throughout claim distribution.
Table II. Outcome of physician notification* Patient problem Chest pain Dyspnea Weight gain Hypertension Hypotension Bradycardia Lightheadedness Other Total
n (%)
Cardiac medication change within 3 days (%)
Admission within 3 weeks (%)
54 (18) 54 (18) 46 (16) 44 (15) 34 (12) 17 (6) 14 (5) 54 (18) 294
15 11 20 9 12 12 7 16 13
6 17 11 2 3 12 14 6 9
*One symptom per physician notification.
specificity of coding. Furthermore, a reduction in heart failure claims that is not associated with a reduction in total claims is of unclear benefit. Claims, hospitalizations, and length of stay were determined from data provided by the medical group for 1995 and 1996. The total claims, hospitalizations, and hospital days were divided by the time period for which claims existed. These values were then converted to claims, hospitalizations, and hospital days per year. The resulting claims per year were compared for 1995 and 1996 for both pro-
gram and control groups. Differences in mean hospitalizations per year, hospital days per year, and total claims per year between control and intervention patients were made with and without weighting by the follow-up time period. Time in the program was known exactly; however, time in the control group could only be inferred from patient claims. This is a potential source of bias, although we believe it to be minimal given that the period between claims was on average short compared to the period of observation.
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Table III. Differences in resource use between program and control groups Variable n Age (y) Male (%) Baseline (1995) Total claims/year Ln (claims/year) Admissions/year Hospital days/year Intervention period Total claims/year Ln (claims/year) Admissions/year Hospital days/year
Program
Control
P value
43 74 ± 13 58
86 75 ± 11 58
.7 >.9
$8500 ± $13,000 7.7 ± 1.9 2.4 ± 3.3 8.6 ± 19
$9200 ± $15,000 7.7 ± 1.9 1.8 ± 3.3 8.9 ± 21
$7400 ± $11,700 7.7 ± 1.6 1.9 ± 3.8 4.8 ± 10
$18,800 ± $34,000 8.4 ± 1.9 3.4 ± 6.7 17 ± 38
.8 >.9 0.4 >.9 .04 .06 .19 .05
Ln, Natural logarithm.
Table IV. Independent predictors of total claims per year Total claims per year predictors
Estimate
95% Confidence interval
Age (per year) Female Sodium <136 mmol/L Creatinine >1.5 mg/dL Diabetes
–$374 $5300 $9000 $8500 $4600
–$692 to –$55 $1300-$9400 $13,100-$4900 $13,400-$3600 $8500-$720
P value .02 .01 .0001 .001 .02
Total model adjusted R2 = 0.52.
Statistical analysis Differences in proportions were compared with the χ2 test. Comparisons between the control and program groups were evaluated with t tests for continuous variables (claims, admissions, length of stay). Comparisons were made with and without weighting for time spent in the program. Because the distribution of claims data are frequently skewed (nonnormal) we repeated the analysis with the natural logarithm of claims per year. Adjustment for the effect of patient age was performed by multiple regression. The multivariate analysis was repeated with the logarithm of the dependent variable for nonnormally distributed continuous variables. Survival rates (6–month and 12-month) for the patients in the program were determined by the Kaplan-Meier method. Survival data were not available for the control group. A 2-tailed P value of < .05 was considered statistically significant.
Results During the study period 68 patients were enrolled and were followed up for a mean of 7.4 ± 3 months (range 11 days to 10.9 months). These patients were cared for by 31 physicians (24 primary care physicians, 7 cardiologists). Characteristics of the enrolled patients are listed in Table I. An echocardiographic assessment of left ventricular function was available for 55%. This number may be an underestimate because reports were obtained from
one referral echocardiography laboratory. Left ventricular function was at least moderately reduced in 60%, mildly reduced in 20%, and normal in 20%. There were 294 physician notifications for abnormal symptoms or signs in 53 patients (Table II). This corresponds to 1 notification per patient every 3 months. The most common reasons for physician notification were worsening dyspnea (18%) and new or different chest pain (18%). Signs and symptoms of heart failure (worsening dyspnea, edema, weight gain) accounted for 34% of notifications. For every physician notification there were 6 other computer-detected abnormalities in which the nurse contacted the patient and determined that the vital sign or symptom data were not accurately entered. Approximately 1 in 8 notifications was followed by a change in the patient’s medical regimen (Table II). Weight gain was more commonly followed by a medication change than other abnormalities. Patients were admitted within 2 weeks after 10% of the physician notifications. The patient abnormalities most frequently associated with subsequent admission were dyspnea and lightheadedness. An abnormal blood pressure reading (hypotension or hypertension) was rarely followed by admission.
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Figure 2
Change in claims from baseline to intervention period for program and control groups. A reduction in claims is noted for program patients, whereas a significant increase occurred for control patients. Data are means with standard error bars.
There were 57 admissions in 33 patients during follow-up. Admissions related to symptoms of congestive heart failure accounted for 28%, whereas 16% were for chest pain (including acute myocardial infarction). Physicians received notification of a patient abnormality within 14 days before admission in 75% of the heart failure and 17% of the non–heart failure admissions.
Hospital claims and admissions Average claims per year during the intervention period were significantly lower for the patients in the program (Table III, Figure 1). When compared with the year before enrollment (1995), total claims during the intervention were also significantly lower for the patients enrolled in the program compared with control group patients. The average change in total claims from the preintervention to the intervention period was a $1500 decrease for enrolled patients compared with an $8000 increase for control patients. (Figure 2). Similar findings were observed for total hospital days and admissions (Table III). The cost of the program was estimated to be less than $200 per patient per month. Using this upper limit for the cost of the program, the cost per patient per year in
1996 was $9800 ($7400 + $200 × 12). This cost of care for program patients remains significantly below the mean cost of care for controls during the same period ($18,800). To determine if the program’s benefit was limited to patients with high baseline use we compared patients with 1995 claims above and below $5000. For the high claims patients (>$5000 per year during 1995), the program participants had an $8000 per year reduction in claims in 1996 compared with a $10,300 increase for those in the control group. For low claims patients (≤5000 per year during 1995), the difference was smaller, with a $4400 per year increase for the program patients and a $9100 per year increase for the control patients. We also examined subgroups based on age, sex, and left ventricular function to determine if there were specific subgroups that did not benefit from the program. The drop in claims for patients in the program compared with those in the control group remained significant for men (mean $10,500 savings) and patients older than 75 years (mean $16,000 savings). Trends for a benefit with the program existed for women and younger patients; however, they did not reach statistical significance. For patients with an echocardiographic study
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Table V. Quality of life (SF-36) Dimension General health Physical functioning Bodily pain Vitality Mental health Role functioning, physical Role functioning, emotional Social functioning
Baseline
90 days
Reference population (no heart failure)22
P value*
55 ± 23 46 ± 27 59 ± 28 44 ± 24 72 ± 20 30 ± 39 59 ± 47 64 ± 30
52 ± 21 45 ± 24 58 ± 28 44 ± 21 71 ± 18 38 ± 42 70 ± 45 62 ± 29
74 74 81 67 84 75 91 88
.8 .8 .7 .6 .9 .4 .1 .3
*Comparison is between baseline and 3 month follow-up.
within the last 5 years there was no difference in program benefit between those with and without systolic dysfunction. Because echocardiographic data were not available for the control group, a control-intervention claims difference could not be determined.
Predictors of increased resource utilization We examined different patient characteristics to determine predictors of total claims during the intervention period (Table IV). We found that older age, female sex, diabetes, high serum creatinine levels, and low serum sodium levels were independently predictive of an increase in claims from baseline. Widowed or single patients demonstrated a nonsignificant increase in claims during the intervention period compared with married patients.
Quality of life Results of the SF-36 questionnaire at baseline and during the intervention are shown in Table V. In general there was little change in quality of life measures during the program. No quality of life data were available for the control group.
Follow up Survival rate was 92% ± 4% at 6 months and 82% ± 10% at 12 months for enrolled patients. No survival data were available for the control group. The program was designed as a 1-year study; however, all patients were allowed to continue in the program for a second year. Eleven patients stopped the program early (before 12 months) because they died (n = 5), left the medical group (n = 3), were dissatisfied (n = 2), or the physician was dissatisfied (n = 1). Compliance with the daily vital sign and symptom entry was quite high. Overall patients called in daily with vital sign and symptom data 85% of the time (range 35% to 100%). Patients were also highly satisfied with the program; at 90 days the mean ± SD overall satisfaction score was 4.75 ± 0.4 on a scale of 0 to 5, with 5 as the highest rating.
Discussion This study demonstrates that a system of patient education, home monitoring, and early physician notification of patient problems can be used successfully in the community setting. This investigation also suggests that the program can reduce resource use and hospitalizations while maintaining quality of life. Of note is that the program participants were monitored by 31 different physicians, the majority of whom were primary care physicians. This observation contrasts with prior reports of programs designed to prevent heart failure hospitalizations in which patients were usually monitored in special heart failure clinics or by specialists in an academic setting.6,8,11
Program components This program was designed to improve the health status of patients with symptomatic heart failure by providing patient education, monitoring patients signs and symptoms, and notifying physicians quickly of any patient abnormality. Specific goals from the educational intervention included reduced salt and saturated fat intake, compliance with medications, and improved detection of heart failure signs such as edema, orthopnea, and fatigue. These follow recently published guidelines for patients with heart failure by the Agency for Health Care Policy and Research.2 Although we did not have any direct measure of the effectiveness of the educational intervention, prior studies in these patients have suggested that compliance5 and diet7 can be improved by nurse-directed prevention programs. Our method of patient monitoring was unusual in that patients recorded their vital signs and symptoms daily by phoning a computerized database. Computer algorithms that used alarm values set by each physician notified the nursing staff if any patient data were abnormal. Once the abnormalities were confirmed, the physician was notified by fax. Although physician notification was infrequent (average of once every 3 months), they were followed by admission in 10% and preceded 75% of heart failure admissions. To the best of our knowledge this program is the first
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to use computerized telemedicine for patients with heart failure. Despite the potential difficulties this elderly population faced (lack of familiarity with computers, having to enter information with a touch-tone phone) the compliance rate for daily data entry was more than 80%. The use of computerized communication has been evaluated in several studies of patients with diabeties12-15 and patients in a cardiac rehabilitation program.16 The diabetes trials documented improved glucose control and knowledge of diabetes compared with patients not using computerized interaction. Our program uses other modes of telemedicine,17 including telephone follow-up, education, counseling, and medication reminders with electronic alpha-numeric pagers. We found no reports of medication reminders with electronic pagers; however, several studies in patients with cardiac disorders have used telephone follow-up and counseling.16,18 Our study differs in several aspects from previous studies that have noted reduced resource use with multidimensional programs for patients with heart failure. Several of these programs were limited to patients with severe heart failure11 or were limited to discharge planning.6 We used a matched control group to assess the effectiveness of our program in reducing hospitalization. We felt this to be important because of the effects of regression to the mean in any study comparing outcomes before and after an intervention. Several reports of noncontrolled interventions have found larger decreases in hospitalizations than were found with this study. This may represent differences in the program or setting in which it was implemented, regression to the mean, or other unknown factors. Second, all medical care was provided by the patient’s physician, and the program’s nurses served only as counselors and educators. This is in contrast to the program reported by West et al,7 which used nurse practitioners to aid in medication management with the supervision of physicians. Because our program does not require direct supervision by the primary physician, it is easily adaptable to a wide range of health care providers and clinical practice settings. This study provided insight into the outcome of many common patient sign and symptom abnormalities. We found that complaints of shortness of breath and lightheadedness were more likely to be followed by an admission (14% to 17%) than blood pressure abnormalities (2% to 3%) or complaints of chest pain (6%). Physicians modified the patient’s medical regimen most commonly for chest pain and weight gain. Although our study cannot determine if this degree of intervention is appropriate, our findings suggest that patients with dyspnea or lightheadedness may benefit from closer follow-up. Our knowledge of physician intervention was limited and based on patient reported changes in medications. Thus the 33% intervention rate for cardiovascular medication changes
Heidenreich, Ruggerio, and Massie 639
may be an underestimate of what the physician actually prescribed. Physicians received notification of an abnormality within a brief period of time before hospitalization for heart failure in 75% of admissions. Our study could not determine if patients received appropriate therapy after physician notification of a patient abnormality, but it is possible that more aggressive intervention would have avoided hospitalization.
Limitations This study has several limitations. Because the program-control comparison was nonrandomized it is possible that the groups differed substantially in ways that we did not identify. Although we believe our matching process limited any bias, the reduction in claims and hospitalizations observed with the program should be considered preliminary pending a larger randomized trial. Our study did not evaluate differences in survival rate between the program and control groups. However, because we determined costs per time of survival, a difference in death rates could not explain the difference in costs observed. Because most deaths are associated with increased expenditures,19,20 it is unlikely that the control group had a significantly greater survival than the program group. Our study was unable to determine what part of the program was responsible for the observed reduction in resource use. It is likely that both improved patient education and early physician notification of patient problems were important, but the relative contributions are unknown. One question regarding any intervention for heart failure is the applicability of the results to patients not enrolled in the study. We believe the patient population in this study was similar to patients with heart failure in the United States today. Our study was conducted in the community setting in patients who were elderly and frequently required the assistance of family members. Furthermore, the quality of life scores at baseline are similar to those reported in a prior study of elderly patients with heart failure.21 However, the intervention group was limited to patients who volunteered for the study, thus universal application of the program may not achieve similar reductions in hospitalizations and costs. In summary, this study suggests that a multidisciplinary program of patient monitoring, education, and physician notification can lead to a reduction in hospitalization and medical claims in a population of elderly patients with mixed causes of heart failure. Although previous experiences with these types of interventions have largely occurred in the setting of special heart failure programs or academic centers, our results indicate that they can be implemented in the community in a variety of practice settings.
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References 1. Kupari M, Lindroos M, Iivanainen AM, Heikkila J, Tilvis R. Congestive heart failure in old age: prevalence, mechanisms and 4-year prognosis in the Helsinki Ageing Study. J Intern Med 1997;241:387-94. 2. AHCPR. Heart failure: evaluation and care of patients with left-ventricular systolic dysfunction. Rockville (MD): AHCPR Publication No. 94-0612. 1994. 3. Ho KK, Pinsky JL, Kannel WB, Levy D. The epidemiology of heart failure: the Framingham Study. J Am Coll Cardiol 1993;22:6A-13A. 4. Krumholz HM, Parent EM, Tu N, Vaccarino V, Wang Y, Radford MJ, et al. Readmission after hospitalization for congestive heart failure among Medicare beneficiaries. Arch Intern Med 1997; 157:99-104. 5. Rich MW, Gray DB, Beckham V, Wittenberg C, Luther P. Effect of a multidisciplinary intervention on medication compliance in elderly patients with congestive heart failure. Am J Med 1996; 101:270-6. 6. Rich MW, Beckham V, Wittenberg C, Leven CL, Freedland KE, Carney RM. A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure. N Engl J Med 1995; 333:1190-5. 7. West JA, Miller NH, Parker KM, Senneca D, Ghandour G, Clark M, et al. A comprehensive management system for heart failure improves clinical outcomes and reduces medical resource utilization. Am J Cardiol 1997;79:58-63. 8. Shah NB, Der E, Ruggerio C, Heidenreich PA, Massie BM. Prevention of hospitalizations for heart failure with an interactive home monitoring program. Am Heart J 1998;135:373-8. 9. Guidelines for the evaluation and management of heart failure. Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Evaluation and Management of Heart Failure). J Am Coll Cardiol 1995;26:1376-98. 10. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992;30:473-83. 11. Fonarow GC, Stevenson LW, Walden JA, Livingston NA, Steimle
12.
13.
14.
15.
16.
17.
18.
19. 20. 21.
22.
AE, Hamilton MA, et al. Impact of a comprehensive heart failure management program on hospital readmission and functional status of patients with advanced heart failure. J Am Coll Cardiol 1997;30:725-32. Turnin MC, Beddok RH, Clottes JP, Martini PF, Abadie RG, Buisson JC, et al. Telematic expert system Diabeto. New tool for diet selfmonitoring for diabetic patients. Diabetes Care 1992;15:204-12. Billiard A, Rohmer V, Roques MA, Joseph MG, Suraniti S, Giraud P, et al. Telematic transmission of computerized blood glucose profiles for IDDM patients. Diabetes Care 1991;14:130-4. Ahring KK, Ahring JP, Joyce C, Farid NR. Telephone modem access improves diabetes control in those with insulin- requiring diabetes. Diabetes Care 1992;15:971-5. Shultz EK, Bauman A, Hayward M, Holzman R. Improved care of patients with diabetes through telecommunications. Ann NY Acad Sci 1992;670:141-5. Capone RJ, Stablein D, Visco J, Wagner G, Gorkin L, Follick MJ. The effects of a transtelephonic surveillance and prehospital emergency intervention system on the 1-year course following acute myocardial infarction. Am Heart J 1988;116:1606-15. Balas EA, Jaffrey F, Kuperman GJ, Boren SA, Brown GD, Pinciroli F, et al. Electronic communication with patients. Evaluation of distance medicine technology. JAMA 1997;278:152-9. DeBusk RF, Miller NH, Superko HR, Dennis CA, Thomas RJ, Lew HT, et al. A case-management system for coronary risk factor modification after acute myocardial infarction. Ann Intern Med 1994;120:721-9. Emanuel EJ, Emanuel LL. The economics of dying. The illusion of cost savings at the end of life. N Engl J Med 1994;330:540-4. Lubitz JD, Riley GF. Trends in Medicare payments in the last year of life. N Engl J Med 1993;328:1092-6. Jenkinson C, Jenkinson D, Shepperd S, Layte R, Petersen S. Evaluation of treatment for congestive heart failure in patients aged 60 years and older using generic measures of health status (SF-36 and COOP charts). Age Ageing 1997;26:7-13. Lyons RA, Perry HM, Littlepage BN. Evidence for the validity of the short-form 36 questionnaire (SF-36) in an elderly population. Age Ageing 1994;23:182-4.
Background Heart failure has a large medical and economic impact on the elderly. Past studies have shown that high-intensity multidisciplinary interventions at academic medical centers can reduce future hospitalizations. Our pilot study examined the effects of a low-intensity monitoring program on hospitalizations and cost of care for patients with heart failure treated by community physicians. Methods We enrolled 68 patients with heart failure (mean age 73 ± 13 years, 53% male) monitored by 31 physicians in a multidisciplinary program of patient education, daily self-monitoring, and physician notification of abnormal weight gain, vital signs, and symptoms. Comparisons of medical claims were made between the patients who received the intervention and a control group of 86 patients matched to the intervention group on medical claims during the preceding year.
Results Compared with the prior year, medical claims per year decreased in the intervention group ($8500 ± $13,000 to $7400 ± $11,400), whereas they increased in the control group ($9200 ± $15,000 to $18,800 ± $34,000, P < .05). Similar differences were observed for hospitalizations and total hospital days. The program’s effectiveness was unrelated to age, sex, or type of left ventricular dysfunction. Conclusions These findings suggest that a multidisciplinary program of patient education, monitoring, and physician notification can reduce resource use in patients with heart failure managed in a community setting. (Am Heart J 1999;138:633-40.)
See related Editorial on page 599. Heart failure is a major and growing health problem. Approximately 1 in 100 of the general population and 1 in 10 of the elderly are afflicted.1 Heart failure also accounts for a large proportion of medical expenditures2,3 and is now the most common indication for hospitalization in the Medicare population. Rehospitalization after a heart failure admission is also common, particularly in the elderly, 45% of whom are readmitted within 6 months.4 Because of the large medical and economic impact of heart failure, new strategies have been developed to reduce readmission rates. Several studies have found that multidisciplinary treatment, including patient education, social service consultation medication review, and intensive outpatient follow-up can improve compliFrom the aCardiology Section Department of the Veterans Affairs Medical Center, Palo Alto; the bSchool of Nursing and the Department of Medicine and Cardiovascular Research Institute at the University of California; and the cCardiology Division Department of the Veterans Affairs Medical Center, San Francisco. Supported by LifeMasters® Supported SelfCare SM, Inc., Newport Beach, Calif. Dr Heidenreich received support from the Agency for Health Care Policy and Research (training grant 00028-10). Submitted May 11, 1998; accepted July 28, 1998. Reprint requests: Paul Heidenreich, MD, MS, 111C Cardiology, Palo Alto VA Medical Center, 3801 Miranda Ave, Palo Alto, CA 94304. Copyright © 1999 by Mosby, Inc. 0002-8703/99/$8.00 + 0 4/1/94907
ance5 and reduce admission rates after hospital discharge.6-8 This focus on improved outpatient care is consistent with current clinical practice guidelines that recommend aggressive outpatient management for patients with left ventricular systolic dysfunction.9 In a pilot study, we demonstrated that a multidimensional program of patient education, monitoring, and physician notification was successful in reducing hospitalizations and length of stay for patients monitored in a heart failure clinic at an academic medical center.8 The purpose of this study was to determine if a similar program can be successful in the community setting, where care is provided through multiple private physician offices.
Methods Patients The study was conducted within a multispecialty medical group with 85 physicians and 15,000 patients in northern California. This group consists of multiple small practices (largely primary care) and functions as an independent practice association. Patients were eligible for the study if they were cared for by a physician within the medical group and their physician both agreed to participation and stated that the patient had a history of symptomatic heart failure. Potential patients with heart failure were identified with a claims database from April 1994 through October 1995. Recruitment began in early 1996. The patients’ physicians were contacted if the patient had a heart failure–related claim greater than $50, a hospitalization for heart failure, or an emergency room
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Table I. Characteristics of the 68 enrolled patients Age (y) Male (%) Widowed (%) Medical history Diabetes (%) History of MI or revascularization (%) Sodium <136 mmol/dL (%)* Creatinine >1.5 mg/dL (%)* Echocardiography* Moderate systolic dysfunction (%) Left ventricular hypertrophy (%) Medications ACE inhibitor or hydralazine (%) Digoxin (%) Diuretic (%) Number of medications
73 ± 13 59 25 32 44 27 24 55 48 75 57 88 8±3
MI, Myocardial infarction. *Data are available for a subset of patients (sodium, 46%; creatinine, 44%; echocardiography, 58%).
visit for heart failure during the 19-month period. There were 128 patients identified; 26 of these were enrolled. The remaining 102 patients were not enrolled because the patient’s physician stated that the patient did not have symptomatic heart failure or would not agree to have the patient participate (n = 87), the patient had left the medical group (n = 10), or the patient refused (n = 5). An additional 42 patients were enrolled at the request of individual medical group physicians whose patients were not identified by the 19-month window. Thus a total of 68 patients participated in the program. All patients had class II to III New York Heart Association heart failure. There was no requirement for depressed systolic function. Echocardiographic estimates of systolic function and hypertrophy were obtained from laboratory reports from the last 5 years. Data were available only from the primary referral laboratory. The systolic function was considered moderately reduced if the estimated ejection fraction was between 30% and 45%, and mildly reduced if the ejection fraction was between 45% and 55%. All patient medications, comorbid conditions, age, sex, and marital status were recorded from patient interviews.
Home monitoring Each patient received a digital scale and an automatic blood pressure cuff and was instructed in their use. Each day the patient called a toll-free number and entered the systolic and diastolic blood pressure, pulse, weight, and any symptoms into a computerized voice answering system. A computer algorithm then checked the patient’s vital signs with an acceptable range previously set by the physician. If values were outside the accepted range, or if new symptoms of shortness of breath, chest pain, or edema were reported, then the computer paged a nurse who confirmed the reported data by calling the patient. Once confirmed, the abnormality was described in a 1-page fax to the physician. The fax also included a graph of recent vital signs, current medications, and the patient’s phone number. The program was designed to be an aid to, and not a replacement for, physician services. To maintain the doctor-patient relationship the program did not contact the physician at the
request of the patient. Patients were told to contact their doctors directly if they were concerned about their health. Each physician with a participating patient completed a form indicating at what level of blood pressure, heart rate, or weight gain they wished to be notified by fax. Default values were 200 mm Hg and 120 mm Hg for upper systolic and diastolic blood pressure, and 90 mm Hg and 40 mm Hg for lower systolic and diastolic blood pressure, 150 beats/min and 50 beats/min for upper and lower heart rate, and 5 pounds per week for weight gain.
Patient education Each patient received weekly educational mailings and a 10-minute call from a nurse. The mailings described 52 different topics related to heart failure (1 each week for 1 year), including diet, exercise, common therapies, as well as simple anatomy and physiology. The mailed materials were then discussed during the weekly telephone call, and the educational points were reinforced. New symptoms, medication changes, and visits to the physician were also recorded. The nurse provided only education, and did not suggest any changes in medical management. Each patient was offered an alpha-numeric pager that provided personalized medication reminders.
Quality of life and satisfaction Each patient was asked to complete the SF-36 survey.10 The SF-36 is a nonspecific health status questionnaire with 8 dimensions (physical functioning, social functioning, pain, mental health, vitality, role limitations from physical problems, role limitations from emotional problems, and general health). The survey was administered at baseline and then at 3 months after starting the program. In addition, patients completed satisfaction questionnaires after 3 months in the program.
Resource use We used 2 approaches to assess the effect of the program on resource use. First, the average claims per year before the intervention were compared with the claims per year during the intervention. Because this approach may be affected by regression to the mean, improvements in technology, and disease progression, we used a control group derived from the same medical group who had a heart failure–related claim between April 1994 and May 1995, and who generated at least 1 claim after March 1996 (indicating they were enrolled in the medical group for at least 3 months). These patients were matched 2:1 to intervention patients based on sex and 1995 claims. Analysis of these groups determined that age and other measures of resource use were similar. This process limited regression to the mean by using partially separate periods for identification of high claims patients (April 1994 to May 1995) and baseline measurements (January 1995 to December 1995). The main outcome of interest was the difference in total claims per year from 1995 to 1996 (the intervention year). Total claims were used instead of heart failure claims because of inaccuracies in coding of diagnoses. In preliminary analysis we found that many admissions for heart failure (based on patient and physician description) were not coded as heart failure (poor sensitivity). A similar problem was noted for the
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Figure 1
Claims during intervention period for program and matched control groups. Kaplan-Meier plot shows cumulative percentage of patients at each level of total claims per patient per year. Area above curve is a measure of mean claims per patient per year. A difference between program and control groups is observed throughout claim distribution.
Table II. Outcome of physician notification* Patient problem Chest pain Dyspnea Weight gain Hypertension Hypotension Bradycardia Lightheadedness Other Total
n (%)
Cardiac medication change within 3 days (%)
Admission within 3 weeks (%)
54 (18) 54 (18) 46 (16) 44 (15) 34 (12) 17 (6) 14 (5) 54 (18) 294
15 11 20 9 12 12 7 16 13
6 17 11 2 3 12 14 6 9
*One symptom per physician notification.
specificity of coding. Furthermore, a reduction in heart failure claims that is not associated with a reduction in total claims is of unclear benefit. Claims, hospitalizations, and length of stay were determined from data provided by the medical group for 1995 and 1996. The total claims, hospitalizations, and hospital days were divided by the time period for which claims existed. These values were then converted to claims, hospitalizations, and hospital days per year. The resulting claims per year were compared for 1995 and 1996 for both pro-
gram and control groups. Differences in mean hospitalizations per year, hospital days per year, and total claims per year between control and intervention patients were made with and without weighting by the follow-up time period. Time in the program was known exactly; however, time in the control group could only be inferred from patient claims. This is a potential source of bias, although we believe it to be minimal given that the period between claims was on average short compared to the period of observation.
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636 Heidenreich, Ruggerio, and Massie
Table III. Differences in resource use between program and control groups Variable n Age (y) Male (%) Baseline (1995) Total claims/year Ln (claims/year) Admissions/year Hospital days/year Intervention period Total claims/year Ln (claims/year) Admissions/year Hospital days/year
Program
Control
P value
43 74 ± 13 58
86 75 ± 11 58
.7 >.9
$8500 ± $13,000 7.7 ± 1.9 2.4 ± 3.3 8.6 ± 19
$9200 ± $15,000 7.7 ± 1.9 1.8 ± 3.3 8.9 ± 21
$7400 ± $11,700 7.7 ± 1.6 1.9 ± 3.8 4.8 ± 10
$18,800 ± $34,000 8.4 ± 1.9 3.4 ± 6.7 17 ± 38
.8 >.9 0.4 >.9 .04 .06 .19 .05
Ln, Natural logarithm.
Table IV. Independent predictors of total claims per year Total claims per year predictors
Estimate
95% Confidence interval
Age (per year) Female Sodium <136 mmol/L Creatinine >1.5 mg/dL Diabetes
–$374 $5300 $9000 $8500 $4600
–$692 to –$55 $1300-$9400 $13,100-$4900 $13,400-$3600 $8500-$720
P value .02 .01 .0001 .001 .02
Total model adjusted R2 = 0.52.
Statistical analysis Differences in proportions were compared with the χ2 test. Comparisons between the control and program groups were evaluated with t tests for continuous variables (claims, admissions, length of stay). Comparisons were made with and without weighting for time spent in the program. Because the distribution of claims data are frequently skewed (nonnormal) we repeated the analysis with the natural logarithm of claims per year. Adjustment for the effect of patient age was performed by multiple regression. The multivariate analysis was repeated with the logarithm of the dependent variable for nonnormally distributed continuous variables. Survival rates (6–month and 12-month) for the patients in the program were determined by the Kaplan-Meier method. Survival data were not available for the control group. A 2-tailed P value of < .05 was considered statistically significant.
Results During the study period 68 patients were enrolled and were followed up for a mean of 7.4 ± 3 months (range 11 days to 10.9 months). These patients were cared for by 31 physicians (24 primary care physicians, 7 cardiologists). Characteristics of the enrolled patients are listed in Table I. An echocardiographic assessment of left ventricular function was available for 55%. This number may be an underestimate because reports were obtained from
one referral echocardiography laboratory. Left ventricular function was at least moderately reduced in 60%, mildly reduced in 20%, and normal in 20%. There were 294 physician notifications for abnormal symptoms or signs in 53 patients (Table II). This corresponds to 1 notification per patient every 3 months. The most common reasons for physician notification were worsening dyspnea (18%) and new or different chest pain (18%). Signs and symptoms of heart failure (worsening dyspnea, edema, weight gain) accounted for 34% of notifications. For every physician notification there were 6 other computer-detected abnormalities in which the nurse contacted the patient and determined that the vital sign or symptom data were not accurately entered. Approximately 1 in 8 notifications was followed by a change in the patient’s medical regimen (Table II). Weight gain was more commonly followed by a medication change than other abnormalities. Patients were admitted within 2 weeks after 10% of the physician notifications. The patient abnormalities most frequently associated with subsequent admission were dyspnea and lightheadedness. An abnormal blood pressure reading (hypotension or hypertension) was rarely followed by admission.
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Figure 2
Change in claims from baseline to intervention period for program and control groups. A reduction in claims is noted for program patients, whereas a significant increase occurred for control patients. Data are means with standard error bars.
There were 57 admissions in 33 patients during follow-up. Admissions related to symptoms of congestive heart failure accounted for 28%, whereas 16% were for chest pain (including acute myocardial infarction). Physicians received notification of a patient abnormality within 14 days before admission in 75% of the heart failure and 17% of the non–heart failure admissions.
Hospital claims and admissions Average claims per year during the intervention period were significantly lower for the patients in the program (Table III, Figure 1). When compared with the year before enrollment (1995), total claims during the intervention were also significantly lower for the patients enrolled in the program compared with control group patients. The average change in total claims from the preintervention to the intervention period was a $1500 decrease for enrolled patients compared with an $8000 increase for control patients. (Figure 2). Similar findings were observed for total hospital days and admissions (Table III). The cost of the program was estimated to be less than $200 per patient per month. Using this upper limit for the cost of the program, the cost per patient per year in
1996 was $9800 ($7400 + $200 × 12). This cost of care for program patients remains significantly below the mean cost of care for controls during the same period ($18,800). To determine if the program’s benefit was limited to patients with high baseline use we compared patients with 1995 claims above and below $5000. For the high claims patients (>$5000 per year during 1995), the program participants had an $8000 per year reduction in claims in 1996 compared with a $10,300 increase for those in the control group. For low claims patients (≤5000 per year during 1995), the difference was smaller, with a $4400 per year increase for the program patients and a $9100 per year increase for the control patients. We also examined subgroups based on age, sex, and left ventricular function to determine if there were specific subgroups that did not benefit from the program. The drop in claims for patients in the program compared with those in the control group remained significant for men (mean $10,500 savings) and patients older than 75 years (mean $16,000 savings). Trends for a benefit with the program existed for women and younger patients; however, they did not reach statistical significance. For patients with an echocardiographic study
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Table V. Quality of life (SF-36) Dimension General health Physical functioning Bodily pain Vitality Mental health Role functioning, physical Role functioning, emotional Social functioning
Baseline
90 days
Reference population (no heart failure)22
P value*
55 ± 23 46 ± 27 59 ± 28 44 ± 24 72 ± 20 30 ± 39 59 ± 47 64 ± 30
52 ± 21 45 ± 24 58 ± 28 44 ± 21 71 ± 18 38 ± 42 70 ± 45 62 ± 29
74 74 81 67 84 75 91 88
.8 .8 .7 .6 .9 .4 .1 .3
*Comparison is between baseline and 3 month follow-up.
within the last 5 years there was no difference in program benefit between those with and without systolic dysfunction. Because echocardiographic data were not available for the control group, a control-intervention claims difference could not be determined.
Predictors of increased resource utilization We examined different patient characteristics to determine predictors of total claims during the intervention period (Table IV). We found that older age, female sex, diabetes, high serum creatinine levels, and low serum sodium levels were independently predictive of an increase in claims from baseline. Widowed or single patients demonstrated a nonsignificant increase in claims during the intervention period compared with married patients.
Quality of life Results of the SF-36 questionnaire at baseline and during the intervention are shown in Table V. In general there was little change in quality of life measures during the program. No quality of life data were available for the control group.
Follow up Survival rate was 92% ± 4% at 6 months and 82% ± 10% at 12 months for enrolled patients. No survival data were available for the control group. The program was designed as a 1-year study; however, all patients were allowed to continue in the program for a second year. Eleven patients stopped the program early (before 12 months) because they died (n = 5), left the medical group (n = 3), were dissatisfied (n = 2), or the physician was dissatisfied (n = 1). Compliance with the daily vital sign and symptom entry was quite high. Overall patients called in daily with vital sign and symptom data 85% of the time (range 35% to 100%). Patients were also highly satisfied with the program; at 90 days the mean ± SD overall satisfaction score was 4.75 ± 0.4 on a scale of 0 to 5, with 5 as the highest rating.
Discussion This study demonstrates that a system of patient education, home monitoring, and early physician notification of patient problems can be used successfully in the community setting. This investigation also suggests that the program can reduce resource use and hospitalizations while maintaining quality of life. Of note is that the program participants were monitored by 31 different physicians, the majority of whom were primary care physicians. This observation contrasts with prior reports of programs designed to prevent heart failure hospitalizations in which patients were usually monitored in special heart failure clinics or by specialists in an academic setting.6,8,11
Program components This program was designed to improve the health status of patients with symptomatic heart failure by providing patient education, monitoring patients signs and symptoms, and notifying physicians quickly of any patient abnormality. Specific goals from the educational intervention included reduced salt and saturated fat intake, compliance with medications, and improved detection of heart failure signs such as edema, orthopnea, and fatigue. These follow recently published guidelines for patients with heart failure by the Agency for Health Care Policy and Research.2 Although we did not have any direct measure of the effectiveness of the educational intervention, prior studies in these patients have suggested that compliance5 and diet7 can be improved by nurse-directed prevention programs. Our method of patient monitoring was unusual in that patients recorded their vital signs and symptoms daily by phoning a computerized database. Computer algorithms that used alarm values set by each physician notified the nursing staff if any patient data were abnormal. Once the abnormalities were confirmed, the physician was notified by fax. Although physician notification was infrequent (average of once every 3 months), they were followed by admission in 10% and preceded 75% of heart failure admissions. To the best of our knowledge this program is the first
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to use computerized telemedicine for patients with heart failure. Despite the potential difficulties this elderly population faced (lack of familiarity with computers, having to enter information with a touch-tone phone) the compliance rate for daily data entry was more than 80%. The use of computerized communication has been evaluated in several studies of patients with diabeties12-15 and patients in a cardiac rehabilitation program.16 The diabetes trials documented improved glucose control and knowledge of diabetes compared with patients not using computerized interaction. Our program uses other modes of telemedicine,17 including telephone follow-up, education, counseling, and medication reminders with electronic alpha-numeric pagers. We found no reports of medication reminders with electronic pagers; however, several studies in patients with cardiac disorders have used telephone follow-up and counseling.16,18 Our study differs in several aspects from previous studies that have noted reduced resource use with multidimensional programs for patients with heart failure. Several of these programs were limited to patients with severe heart failure11 or were limited to discharge planning.6 We used a matched control group to assess the effectiveness of our program in reducing hospitalization. We felt this to be important because of the effects of regression to the mean in any study comparing outcomes before and after an intervention. Several reports of noncontrolled interventions have found larger decreases in hospitalizations than were found with this study. This may represent differences in the program or setting in which it was implemented, regression to the mean, or other unknown factors. Second, all medical care was provided by the patient’s physician, and the program’s nurses served only as counselors and educators. This is in contrast to the program reported by West et al,7 which used nurse practitioners to aid in medication management with the supervision of physicians. Because our program does not require direct supervision by the primary physician, it is easily adaptable to a wide range of health care providers and clinical practice settings. This study provided insight into the outcome of many common patient sign and symptom abnormalities. We found that complaints of shortness of breath and lightheadedness were more likely to be followed by an admission (14% to 17%) than blood pressure abnormalities (2% to 3%) or complaints of chest pain (6%). Physicians modified the patient’s medical regimen most commonly for chest pain and weight gain. Although our study cannot determine if this degree of intervention is appropriate, our findings suggest that patients with dyspnea or lightheadedness may benefit from closer follow-up. Our knowledge of physician intervention was limited and based on patient reported changes in medications. Thus the 33% intervention rate for cardiovascular medication changes
Heidenreich, Ruggerio, and Massie 639
may be an underestimate of what the physician actually prescribed. Physicians received notification of an abnormality within a brief period of time before hospitalization for heart failure in 75% of admissions. Our study could not determine if patients received appropriate therapy after physician notification of a patient abnormality, but it is possible that more aggressive intervention would have avoided hospitalization.
Limitations This study has several limitations. Because the program-control comparison was nonrandomized it is possible that the groups differed substantially in ways that we did not identify. Although we believe our matching process limited any bias, the reduction in claims and hospitalizations observed with the program should be considered preliminary pending a larger randomized trial. Our study did not evaluate differences in survival rate between the program and control groups. However, because we determined costs per time of survival, a difference in death rates could not explain the difference in costs observed. Because most deaths are associated with increased expenditures,19,20 it is unlikely that the control group had a significantly greater survival than the program group. Our study was unable to determine what part of the program was responsible for the observed reduction in resource use. It is likely that both improved patient education and early physician notification of patient problems were important, but the relative contributions are unknown. One question regarding any intervention for heart failure is the applicability of the results to patients not enrolled in the study. We believe the patient population in this study was similar to patients with heart failure in the United States today. Our study was conducted in the community setting in patients who were elderly and frequently required the assistance of family members. Furthermore, the quality of life scores at baseline are similar to those reported in a prior study of elderly patients with heart failure.21 However, the intervention group was limited to patients who volunteered for the study, thus universal application of the program may not achieve similar reductions in hospitalizations and costs. In summary, this study suggests that a multidisciplinary program of patient monitoring, education, and physician notification can lead to a reduction in hospitalization and medical claims in a population of elderly patients with mixed causes of heart failure. Although previous experiences with these types of interventions have largely occurred in the setting of special heart failure programs or academic centers, our results indicate that they can be implemented in the community in a variety of practice settings.
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References 1. Kupari M, Lindroos M, Iivanainen AM, Heikkila J, Tilvis R. Congestive heart failure in old age: prevalence, mechanisms and 4-year prognosis in the Helsinki Ageing Study. J Intern Med 1997;241:387-94. 2. AHCPR. Heart failure: evaluation and care of patients with left-ventricular systolic dysfunction. Rockville (MD): AHCPR Publication No. 94-0612. 1994. 3. Ho KK, Pinsky JL, Kannel WB, Levy D. The epidemiology of heart failure: the Framingham Study. J Am Coll Cardiol 1993;22:6A-13A. 4. Krumholz HM, Parent EM, Tu N, Vaccarino V, Wang Y, Radford MJ, et al. Readmission after hospitalization for congestive heart failure among Medicare beneficiaries. Arch Intern Med 1997; 157:99-104. 5. Rich MW, Gray DB, Beckham V, Wittenberg C, Luther P. Effect of a multidisciplinary intervention on medication compliance in elderly patients with congestive heart failure. Am J Med 1996; 101:270-6. 6. Rich MW, Beckham V, Wittenberg C, Leven CL, Freedland KE, Carney RM. A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure. N Engl J Med 1995; 333:1190-5. 7. West JA, Miller NH, Parker KM, Senneca D, Ghandour G, Clark M, et al. A comprehensive management system for heart failure improves clinical outcomes and reduces medical resource utilization. Am J Cardiol 1997;79:58-63. 8. Shah NB, Der E, Ruggerio C, Heidenreich PA, Massie BM. Prevention of hospitalizations for heart failure with an interactive home monitoring program. Am Heart J 1998;135:373-8. 9. Guidelines for the evaluation and management of heart failure. Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Evaluation and Management of Heart Failure). J Am Coll Cardiol 1995;26:1376-98. 10. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 1992;30:473-83. 11. Fonarow GC, Stevenson LW, Walden JA, Livingston NA, Steimle
12.
13.
14.
15.
16.
17.
18.
19. 20. 21.
22.
AE, Hamilton MA, et al. Impact of a comprehensive heart failure management program on hospital readmission and functional status of patients with advanced heart failure. J Am Coll Cardiol 1997;30:725-32. Turnin MC, Beddok RH, Clottes JP, Martini PF, Abadie RG, Buisson JC, et al. Telematic expert system Diabeto. New tool for diet selfmonitoring for diabetic patients. Diabetes Care 1992;15:204-12. Billiard A, Rohmer V, Roques MA, Joseph MG, Suraniti S, Giraud P, et al. Telematic transmission of computerized blood glucose profiles for IDDM patients. Diabetes Care 1991;14:130-4. Ahring KK, Ahring JP, Joyce C, Farid NR. Telephone modem access improves diabetes control in those with insulin- requiring diabetes. Diabetes Care 1992;15:971-5. Shultz EK, Bauman A, Hayward M, Holzman R. Improved care of patients with diabetes through telecommunications. Ann NY Acad Sci 1992;670:141-5. Capone RJ, Stablein D, Visco J, Wagner G, Gorkin L, Follick MJ. The effects of a transtelephonic surveillance and prehospital emergency intervention system on the 1-year course following acute myocardial infarction. Am Heart J 1988;116:1606-15. Balas EA, Jaffrey F, Kuperman GJ, Boren SA, Brown GD, Pinciroli F, et al. Electronic communication with patients. Evaluation of distance medicine technology. JAMA 1997;278:152-9. DeBusk RF, Miller NH, Superko HR, Dennis CA, Thomas RJ, Lew HT, et al. A case-management system for coronary risk factor modification after acute myocardial infarction. Ann Intern Med 1994;120:721-9. Emanuel EJ, Emanuel LL. The economics of dying. The illusion of cost savings at the end of life. N Engl J Med 1994;330:540-4. Lubitz JD, Riley GF. Trends in Medicare payments in the last year of life. N Engl J Med 1993;328:1092-6. Jenkinson C, Jenkinson D, Shepperd S, Layte R, Petersen S. Evaluation of treatment for congestive heart failure in patients aged 60 years and older using generic measures of health status (SF-36 and COOP charts). Age Ageing 1997;26:7-13. Lyons RA, Perry HM, Littlepage BN. Evidence for the validity of the short-form 36 questionnaire (SF-36) in an elderly population. Age Ageing 1994;23:182-4.