Matthew D. Solomon

Comparative Effectiveness of Multivessel Coronary Bypass Surgery and Multivessel Percutaneous Coronary Intervention: A Cohort Study

BACKGROUND Randomized trials of coronary artery bypass graft (CABG) surgery and percutaneous coronary intervention (PCI) suggest that patient characteristics modify the effect of treatment on mortality. OBJECTIVE To assess whether clinical characteristics modify the comparative effectiveness of CABG versus PCI in an unselected, general patient population. DESIGN Observational treatment comparison using propensity score matching and Cox proportional hazards models. SETTING United States, 1992 to 2008. PATIENTS Medicare beneficiaries aged 66 years or older. INTERVENTION Multivessel CABG or multivessel PCI. MEASUREMENTS The CABG-PCI hazard ratio (HR) for all-cause mortality, with prespecified treatment-by-covariate interaction tests, and the absolute difference in life-years of survival in clinical subgroups after CABG or PCI, both over 5 years of follow-up. RESULTS Among 105 156 propensity score-matched patients, CABG was associated with lower mortality than PCI (HR, 0.92 [95% CI, 0.90 to 0.95]; P < 0.001). Association of CABG with lower mortality was significantly greater (interaction P ≤ 0.002 for each) among patients with diabetes (HR, 0.88), a history of tobacco use (HR, 0.82), heart failure (HR, 0.84), and peripheral arterial disease (HR, 0.85). The overall predicted difference in survival between CABG and PCI treatment over 5 years was 0.053 life-years (range, -0.017 to 0.579 life-years). Patients with diabetes, heart failure, peripheral arterial disease, or tobacco use had the largest predicted differences in survival after CABG, whereas those with none of these factors had slightly better survival after PCI. LIMITATION Treatments were chosen by patients and physicians rather than being randomly assigned. CONCLUSION Multivessel CABG is associated with lower long-term mortality than multivessel PCI in the community setting. This association is substantially modified by patient characteristics, with improvement in survival concentrated among patients with diabetes, tobacco use, heart failure, or peripheral arterial disease. PRIMARY FUNDING SOURCE National Heart, Lung, and Blood Institute.

Beta-Blocker Therapy and Cardiac Events Among Patients With Newly Diagnosed Coronary Heart Disease

BACKGROUND The effectiveness of beta-blockers for preventing cardiac events has been questioned for patients who have coronary heart disease (CHD) without a prior myocardial infarction (MI). OBJECTIVES The purpose of this study was to assess the association of beta-blockers with outcomes among patients with new-onset CHD. METHODS We studied consecutive patients discharged after the first CHD event (acute coronary syndrome or coronary revascularization) between 2000 and 2008 in an integrated healthcare delivery system who did not use beta-blockers in the year before entry. We used time-varying Cox regression models to determine the hazard ratio (HR) associated with beta-blocker treatment and used treatment-by-covariate interaction tests (p(int)) to determine whether the association differed for patients with or without a recent MI. RESULTS A total of 26,793 patients were included, 19,843 of whom initiated beta-blocker treatment within 7 days of discharge from their initial CHD event. Over an average of 3.7 years of follow-up, 6,968 patients had an MI or died. Use of beta-blockers was associated with an adjusted HR for mortality of 0.90 (95% confidence limits [CL]: 0.84 to 0.96), and an adjusted HR for death or MI of 0.92 (CL: 0.87 to 0.97). The association between beta-blockers and outcomes differed significantly between patients with and without a recent MI (HR for death: 0.85 vs. 1.02, p(int) = 0.007; and HR for death or MI: 0.87 vs. 1.03, p(int) = 0.005). CONCLUSIONS Use of beta-blockers among patients with new-onset CHD was associated with a lower risk of cardiac events only among patients with a recent MI.

Use of Medications for Secondary Prevention After Coronary Bypass Surgery Compared With Percutaneous Coronary Intervention

OBJECTIVES This study sought to compare use of evidence-based secondary preventive medications after coronary bypass surgery (CABG) and percutaneous coronary intervention (PCI). BACKGROUND Use of cardioprotective medication after coronary revascularization has been inconsistent and relatively low in older studies. METHODS We studied patients in a large integrated healthcare delivery system who underwent CABG or PCI for new onset coronary disease. We used data from health plan databases about prescriptions dispensed during the first year after initial coronary revascularization to identify patients who never filled a prescription and to calculate the medication possession ratio among patients who filled at least 1 prescription. We focused on angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARBs), beta-blockers, and statins. RESULTS Between 2000 and 2007, 8,837 patients with new onset coronary disease underwent initial CABG, and 14,516 underwent initial PCI. Patients receiving CABG were more likely than patients receiving PCI to not fill a prescription for a statin (7.1% vs. 4.8%, p < 0.0001) or for an ACEI/ARB (29.1% vs. 22.4%, p < 0.0001), but similar proportions never filled a prescription for a beta-blocker (6.4% vs. 6.1%). Among those who filled at least 1 prescription post-revascularization, patients receiving CABG had lower medication possession ratios than patients receiving PCI for ACEI/ARBs (69.4% vs. 77.8%, p < 0.0001), beta-blockers (76.1% vs. 80.6%, p < 0.0001), and statins (82.7% vs. 84.2%, p < 0.001). CONCLUSIONS Patients who received CABG were generally less likely than patients who received PCI to fill prescriptions for secondary preventive medications and to use those medications consistently in the first year after the procedure.

Association of Spontaneous Bleeding and Myocardial Infarction With Long-Term Mortality After Percutaneous Coronary Intervention

BACKGROUND Platelet inhibition after percutaneous coronary intervention (PCI) reduces the risk of myocardial infarction (MI) but increases the risk of bleeding. MIs and bleeds during the index hospitalization for PCI are known to negatively affect long-term outcomes. The impact of spontaneous bleeding occurring after discharge on long-term mortality is unknown. OBJECTIVES This study sought to examine, in a real-world cohort, the association between spontaneous major bleeding or MI after PCI and long-term mortality. METHODS We conducted a retrospective cohort study of patients ≥30 years of age who underwent a PCI between 1996 and 2008 in an integrated healthcare delivery system. We used extended Cox regression to examine the associations of spontaneous bleeding and MI with all-cause mortality, after adjustment for time-updated demographics, comorbidities, periprocedural events, and longitudinal medication exposure. RESULTS Among 32,906 patients who had a PCI and survived the index hospitalization, 530 had bleeds and 991 had MIs between 7 and 365 days post-discharge. There were 4,048 deaths over a mean follow-up of 4.42 years. The crude annual death rate after a spontaneous bleed (9.5%) or MI (7.6%) was higher than among patients who experienced neither event (2.6%). Bleeding was associated with an increased rate of death (adjusted hazard ratio [HR]: 1.61, 95% confidence interval [CI]: 1.30 to 2.00), similar to that after an MI (HR: 1.91; 95% CI: 1.62 to 2.25). The association of bleeding with death remained significant after additional adjustment for the longitudinal use of antiplatelet agents. CONCLUSIONS Spontaneous bleeding after a PCI was independently associated with higher long-term mortality, and conveyed a risk comparable to that of an MI during follow-up. This tradeoff between efficacy and safety bolsters the argument for personalizing antiplatelet therapy after PCI on the basis of the patients long-term risk of both thrombotic and bleeding events.

The relationship between laboratory-based outcome measures and mortality in end-stage renal disease: A systematic review

Despite data that traditional laboratory‐based outcome measures in dialysis are improving over time, population‐based data indicate that mortality rates are not improving in parallel. With increased focus on performance measures based on laboratory‐based outcomes (e.g., hematocrit, albumin, and parathyroid hormone), less emphasis has been placed on other markers, some of which may be stronger predictors of mortality. We performed a systematic review to interpret the predictive value of laboratory‐based outcome measures in dialysis. We identified studies with data regarding the predictive value of laboratory‐based outcomes for mortality in dialysis. We calculated the sample size‐weighted pooled relative risk of death with dichotomized “high” vs. “low” levels of each measure. We rank‐ordered predictors by scaling the pooled relative risk of each measure by its pooled standard deviation. There were 5171 titles, of which 128 (representing 44 laboratory‐based outcomes) were selected. Nine were significantly associated with mortality, in order of decreasing scaled effect size: (1) tumor necrosis factor‐α, (2) hematocrit, (3) interleukin‐6, (4) troponin T, (5) Kt/Vurea, (6) prealbumin, (7) urea reduction ratio, (8) serum albumin, and (9) C‐reactive protein. Other oft‐cited measures such as calcium phosphate product and parathyroid hormone were not significantly associated with mortality in pooled analysis. Quality improvement efforts to improve traditional laboratory‐based outcomes in end‐stage renal disease are necessary, but likely insufficient, to improve overall mortality in dialysis. Renewed consideration of cardiovascular, inflammatory, and nutritional markers that are especially strong predictors of mortality may have important implications for risk stratification and targeted therapeutic interventions.

Primary Non-adherence of Medications: lifting the veil on prescription-filling behaviors

Economists say that consumers “vote with their feet”. That is, in order to understand human behavior, we can interpret peoples underlying preferences by observing their choices. Unfortunately, in much of the social sciences, researchers are limited in their ability to directly observe people’s choices. This is particularly true when studying the problem of medication adherence. Medication “adherence” is defined as the degree of patient compliance with providers’ recommendations about the daily timing, dosage, and frequency of medication use. This differs from “persistence,” which refers to whether patients continue a treatment for the prescribed duration. Both are difficult to study. Aside from watching patients drop pills into their mouths and swallow them every day (which is clearly infeasible except for extreme circumstances such as directly observed treatment for multidrug resistant tuberculosis or HIV) researchers are left to examine surrogate measures of adherence behaviors. Typically, claims data have been mined to measure the frequency and timing of prescription refills to calculate metrics such as the medication possession ratio or gaps in therapy, techniques that make the most of available information, but provide a limited glimpse into a patients course of treatment. Physicians are left to wonder, “What did the patient really do with all the medication he picked up? Did she split pills into two to reduce side effects or save money? Is the bottle sitting full on the bathroom shelf? Did the patient start using a Canadian, Mexican, or Internet pharmacy, and is that why refills seem to have ceased?” And finally, and perhaps most importantly: “Were there prescriptions written that were never even filled in the first place?” The answer to this final question has been a conspicuously missing piece in the medication adherence story. When patients do not even fill a new prescription, it is called “primary” nonadherence to distinguish it from what is far more commonly studied, namely “secondary” nonadherence (i.e., when prescriptions are filled, but the medication is not taken as prescribed) and lack of persistence (i.e., when patients, who may have perfect primary and secondary adherence, self-discontinue therapy by not refilling their prescriptions). The study of primary nonadherence has been lacking because researchers have been unable to effectively track the entire lifespan of a new prescription. Until recently, prescriptions were almost exclusively hand-written on paper pads. Once a patient left the office with a paper prescription, it was either filled at a pharmacy, creating a traceable (sometimes computerized) administrative record, or it went unfilled with no one the wiser. We already know that poor adherence (mostly secondary nonadherence and lack of persistence) to medications is associated with worse health outcomes1,2 and increased health care costs3. Furthermore, many factors associated with poor adherence have been identified, including but not limited to increased cost-sharing4, pill burden and regimen complexity, side-effects, and patient beliefs about whether drugs actually improve their health5. Again, it is noteworthy that these studies almost universally measure the effect of interruptions (secondary nonadherence) or discontinuations (lack of persistence) with chronic medical therapies that have actually been started. Our lack of insight into the prevalence and magnitude of primary medication nonadherence also means that we may have been missing a major target for interventions to improve the quality and outcomes of patient care. Substantial evidence tells us that many patients-up to one-third or more-are aware they have a medical condition but are still poorly controlled or untreated6,7. Empirically, these numbers seem too large to be explained by skipped doses and early discontinuation. Obviously, unless a patient fills a first prescription, they will not reap the benefits of ongoing treatment. Although some research has explored the factors associated with filling a first prescription and sticking with it after a new diagnosis7,8, these studies have also relied on claims data, and could not completely or accurately identify true primary nonadherence. One recent study restricted to elderly Canadians from one province who survived a myocardial infarction demonstrated 10–20% primary nonadherence with life-saving cardiac medications9. To our knowledge this is also the only study that has linked primary nonadherence to downstream major adverse events. In this issue of the Journal, Fischer et al. begin to lift the veil on how often patients do not fill their prescriptions by measuring primary nonadherence for a large population of commercially insured outpatients10. Using a novel electronic prescription writing initiative in two large Massachusetts health plans, they tracked the difference between prescriptions written electronically in a physicians office-a critical data element previously unavailable to most researchers-and prescriptions actually filled at pharmacies on the basis of insurance claims. They collected some data on the medications, the patients, and the participating physicians to identify characteristics that may be associated with better or worse adherence. Briefly, they found that almost one-quarter of all prescriptions (electronically) written went unfilled, and, crucially, that 28.3% of all new (that is to say first) prescriptions went unfilled. After exploring multiple drug classes, they found that the least filled class was pain medications, with less than half of all prescriptions filled. However, even among new prescriptions for medicines used to treat chronic conditions associated with increased cardiovascular risk, such as hypertension, diabetes, and dyslipidemia, one-third of all new prescriptions went unfilled. These numbers are consistent with epidemiologic data about the lack of adequate control of these prevalent and deadly cardiovascular risk factors and may help to explain issues related to their undertreatment. Fischer and colleagues also begin to provide us with some insights into patient behavior: for many reasons, people avoid taking prescription medicines even when advised by a physician and after the prescription has been written. A doctrine in our profession is to do no harm, and medicines tend to be prescribed when physicians believe that the benefits outweigh the risks. Thus, there are clearly many people who, in our estimation, are not reaping potential health benefits. Because of our poor understanding of these problems, researchers have struggled to optimally design effective interventions to help ensure that patients are getting the pharmaceutical care they need by filling their first prescription, adhering to the medication as directed, and then persisting with treatment2,4. Attacking primary nonadherence must be a focus of future interventions, health policies, and careful research. There is simply too much achievable benefit not being achieved. For now, those of us prescribing on the front lines should begin to focus efforts on the encounters when patients are first diagnosed with a new chronic condition and prescribed their initial treatment regimens. This is certainly crucial for silent conditions such as hypertension, diabetes, and dyslipidemia. Although Fischer et al.’s study suggests that prescriptions written by primary care physicians are filled at a higher rate than prescriptions written by specialists, we should not necessarily take much comfort in this finding-the specialists and prescriptions written by these specialists are likely far too heterogeneous to make truly convincing comparisons with primary care physicians. Nevertheless, primary care physicians are crucial to the therapeutic alliance and so must do all that they can to ensure primary adherence. Finally, though the evidence is somewhat mixed regarding the benefits of electronic prescribing11,12, and such systems have not yet been convincingly demonstrated to either improve health outcomes or reduce costs, health information systems with e-prescribing functionality are in all of our futures. With new insights gained from studies such as Fischer et al., perhaps these new systems can be better designed and engineered to help improve initiation and adherence and persistence. Computerized telephone calls that remind patients to pick up a prescription are one possibility, as might be having far greater communication linkages between physicians and the dispensing pharmacists. In addition, future researchers can exploit the adoption of electronic medical records and other health information technologies to provide a more complete picture about the overall patient experience with medical therapy. Instead of relying on surrogates of behavior, we will be able to better directly observe people “voting with their feet”–and then figure out ways to get them to vote differently.E conomists say that consumers “vote with their feet”. That is, in order to understand human behavior, we can interpret peoples underlying preferences by observing their choices. Unfortunately, in much of the social sciences, researchers are limited in their ability to directly observe people’s choices. This is particularly true when studying the problem of medication adherence. Medication “adherence” is defined as the degree of patient compliance with providers’ recommendations about the daily timing, dosage, and frequency of medication use. This differs from “persistence,” which refers to whether patients continue a treatment for the prescribed duration. Both are difficult to study. Aside from watching patients drop pills into their mouths and swallow them every day (which is clearly infeasible except for extreme circumstances such as directly observed treatment for multidrug resistant tuberculosis or HIV) researchers are left to examine surrogate measures of adherence behaviors. Typically, claims data have been mined to measure the frequency and timing of prescription refills to calculate metrics such as the medication possession ratio or gaps in therapy, techniques that make the most of available information, but provide a limited glimpse into a patients course of treatment. Physicians are left to wonder, “What did the patient really do with all the medication he picked up? Did she split pills into two to reduce side effects or save money? Is the bottle sitting full on the bathroom shelf? Did the patient start using a Canadian, Mexican, or Internet pharmacy, and is that why refills seem to have ceased?” And finally, and perhaps most importantly: “Were there prescriptions written that were never even filled in the first place?” The answer to this final question has been a conspicuously missing piece in the medication adherence story. When patients do not even fill a new prescription, it is called “primary” nonadherence to distinguish it from what is far more commonly studied, namely “secondary” nonadherence (i.e., when prescriptions are filled, but the medication is not taken as prescribed) and lack of persistence (i.e., when patients, who may have perfect primary and secondary adherence, self-discontinue therapy by not refilling their prescriptions). The study of primary nonadherence has been lacking because researchers have been unable to effectively track the entire lifespan of a new prescription. Until recently, prescriptions were almost exclusively hand-written on paper pads. Once a patient left the office with a paper prescription, it was either filled at a pharmacy, creating a traceable (sometimes computerized) administrative record, or it went unfilled with no one the wiser. We already know that poor adherence (mostly secondary nonadherence and lack of persistence) to medications is associated with worse health outcomes and increased health care costs. Furthermore, many factors associated with poor adherence have been identified, including but not limited to increased cost-sharing, pill burden and regimen complexity, side-effects, and patient beliefs about whether drugs actually improve their health. Again, it is noteworthy that these studies almost universally measure the effect of interruptions (secondary nonadherence) or discontinuations (lack of persistence) with chronic medical therapies that have actually been started. Our lack of insight into the prevalence and magnitude of primary medication nonadherence also means that we may have been missing a major target for interventions to improve the quality and outcomes of patient care. Substantial evidence tells us that many patients-up to one-third or more-are aware they have a medical condition but are still poorly controlled or untreated. Empirically, these numbers seem too large to be explained by skipped doses and early discontinuation. Obviously, unless a patient fills a first prescription, they will not reap the benefits of ongoing treatment. Although some research has explored the factors associated with filling a first prescription and sticking with it after a new diagnosis, these studies have also relied on claims data, and could not completely or accurately identify true primary nonadherence. One recent study restricted to elderly Canadians from one province who survived a myocardial infarction demonstrated 10–20% primary nonadherence with life-saving cardiac medications. To our knowledge this is also the only study that has linked primary nonadherence to downstream major adverse events. In this issue of the Journal, Fischer et al. begin to lift the veil on how often patients do not fill their prescriptions by measuring primary nonadherence for a large population of commercially insured outpatients. Using a novel electronic prescription writing initiative in two large Massachusetts health plans, they tracked the difference between prescriptions written electronically in a physicians office-a critical data element previously unavailable to most researchers-and prescriptions actually filled at pharmacies on the basis of insurance claims. They collected some data on the medications, the patients, and the participating physicians to identify characteristics that may be associated with better or worse adherence. Published online March 2, 2010 JGIM

Comparative effectiveness of clopidogrel in medically managed patients with unstable angina and non-ST-segment elevation myocardial infarction.

OBJECTIVES This study sought to examine the effectiveness of clopidogrel in real-world, medically managed patients with unstable angina (UA) or non-ST-segment elevation myocardial infarction (NSTEMI). BACKGROUND Although clinical trials have demonstrated the efficacy of clopidogrel to reduce cardiovascular (CV) morbidity and mortality in medically managed patients with UA or NSTEMI, the effectiveness of clopidogrel in actual clinical practice is less certain. METHODS A retrospective cohort study was conducted of Kaiser Permanente Northern California members without known coronary artery disease or prior clopidogrel use who presented with UA or NSTEMI between 2003 and 2008 and were medically managed (i.e., no percutaneous coronary intervention or coronary artery bypass grafting during the index hospitalization or within 7 days post-discharge). Over 2 years of follow-up, we measured the association between clopidogrel use and all-cause mortality, hospital stay for MI, and a composite endpoint of death or MI using propensity-matched multivariable Cox analyses. RESULTS We identified 16,365 patients with incident UA (35%) or NSTEMI (65%); 36% of these patients were prescribed clopidogrel within 7 days of discharge. In 8,562 propensity score-matched patients, clopidogrel users had lower rates of all-cause mortality (8.3% vs. 13.0%; p < 0.01; adjusted hazard ratio [HR]: 0.63; 95% confidence interval [CI]: 0.54 to 0.72) and the composite of death or MI (13.5% vs. 17.4%; p < 0.01; HR: 0.74, CI: 0.66 to 0.84), but not MI alone (6.7% vs. 7.2%; p = 0.30; HR: 0.93, CI: 0.78 to 1.11), compared with nonusers of clopidogrel. The association between clopidogrel use and the composite of death or MI was significant only among patients presenting with NSTEMI (HR: 0.67; CI: 0.59 to 0.76; pint < 0.01), not among those presenting with UA (HR: 1.25; CI: 0.94 to 1.67). CONCLUSIONS In a large, community-based cohort of patients who were medically managed after UA/NSTEMI, clopidogrel use was associated with a lower risk of death and MI, particularly among patients with NSTEMI.

Burden, timing, and relationship of cardiovascular hospitalization to mortality among Medicare beneficiaries with newly diagnosed atrial fibrillation

BACKGROUND Limited data exist on the burden and relationship of cardiovascular (CV) hospitalization to mortality after newly diagnosed with atrial fibrillation (AF). METHODS Using a 20% sample of nationwide Medicare Part A and B claims data, we performed a retrospective cohort study of Medicare beneficiaries with newly diagnosed AF (2004-2008). Cox proportional hazards time-varying exposures were used to determine the risk of death among patients with CV hospitalization after AF diagnosis. RESULTS Of 228,295 patients (mean age 79.6 ± 7.4 years, 56% female), 57% had a CV hospitalization after diagnosis of AF (41% in the first year). The most common primary CV hospitalization diagnoses were AF/supraventricular arrhythmias (21%), heart failure (19%), myocardial infarction (11%), and stroke/transient ischemic attack (7.7%). Incidence rates per 1,000 person-years among patients with and without CV hospitalization were 114 and 87, respectively, for all-cause mortality. After adjustment for covariates and time to CV hospitalization, the hazard of mortality among newly diagnosed AF patients with CV hospitalization, compared with those without CV hospitalization, was higher (hazard ratio 1.22, 95% CI 1.20-1.24). CONCLUSIONS Cardiovascular hospitalization is common in the first year after AF diagnosis. Atrial fibrillation, heart failure, myocardial infarction, and stroke/transient ischemic attack account for half of primary hospitalization diagnosis. Cardiovascular hospitalization is independently associated with mortality, irrespective of time from diagnosis to first hospitalization, and represents a critical inflection point in survival trajectory. These findings highlight the importance of CV hospitalization as a marker of disease progression and poor outcomes. Efforts to clarify the determinants of hospitalization could inform interventions to reduce admissions and improve survival.

Dialysis Practices That Distinguish Top- Versus Bottom-Performing Facilities by Hemoglobin Outcomes

BACKGROUND Because there is wide variation in outcomes across dialysis facilities, it is possible that top-performing units use practices not shared by others. The Identifying Best Practices in Dialysis (IBPiD) Study seeks to identify practices that distinguish top- from bottom-performing facilities by key outcomes, including achievement of recommended hemoglobin targets. STUDY DESIGN Observational study with cross-sectional study ascertainment of predictors and outcomes. PREDICTORS Facility dialysis practices ascertained using practice surveys of dialysis staff who indicated their level of agreement that each practice occurs in their facility (1-6 on a Likert scale). SETTING & PARTICIPANTS 423 personnel in 90 dialysis facilities from 1 for-profit and 2 not-for-profit dialysis organizations. OUTCOMES Percentage of patients per month per facility with hemoglobin levels of 11-12 g/dL. We divided facilities by median into top- versus bottom-performing groups and compared mean scores for each practice using t tests. We report practices that were statistically significant and achieved at least a medium effect size (ES) >or=0.4. RESULTS 17 of 155 tested predictors were significant. Achievement of hemoglobin level targets was related most strongly to the use of chairside computers (ES, 0.8 [95% CI, 0.4-1.4]), extent/quality of educational videos (ES, 0.6 [95% CI, 0.2-1.1]), frequency of calling per diem staff if short staffed (ES, 0.6 [95% CI, 0.21-1.1]), policy that nurses pass written competency examinations before hire (ES, 0.6 [95% CI, 0.2-1.0]), and technician cannulation mastery (ES, 0.6 [95% CI, 0.2-1.1]). LIMITATIONS This is a cross-sectional study that can address only associations, not causations. Future research should measure the longitudinal predictive value of these practices. CONCLUSIONS High-performing facilities report more effective education programs, better staff management, higher staff competency, and higher use of chairside computers, a potential marker of information technology proficiency. This suggests that hemoglobin level management is enhanced by processes reflecting a coordinated multidisciplinary environment.

Practice characteristics and HMO enrollee satisfaction with specialty care: an analysis of patients with glaucoma and diabetic retinopathy.

BACKGROUND The specialists role in caring for managed care patients is likely to grow. Thus, assessing the correlates of patient satisfaction with specialty care is essential. OBJECTIVE To examine the association between characteristics of eye care practices and satisfaction with eye care among working age patients with open-angle glaucoma (OAG) or diabetic retinopathy (DR). SUBJECTS/STUDY SETTING: A total of 913 working age patients with OAG or DR enrolled in six commercial managed care health plans. The patients were treated in 144 different eye care practices. STUDY DESIGN We used a patient survey to obtain information on patient characteristics and satisfaction with eye care, measured by scores on satisfaction subscales of the 18-item Patient Satisfaction Questionnaire. We used a survey of eye care practices to obtain information on practice characteristics, including provider specialties, practice organization, financial features, and utilization and quality management systems. We estimated logistic regression models to assess the association of patient and practice characteristics with high levels of patient satisfaction. PRINCIPAL FINDINGS Treatment in a practice with a glaucoma specialist (for OAG patients) or a retina specialist (for DR patients) was associated with higher satisfaction, whereas treatment in a practice that obtained a high proportion of its revenues from capitation payments or in a group practice where providers obtained a high proportion of their incomes from bonuses was associated with lower satisfaction. CONCLUSIONS Many eye care patients prefer to be treated by specialists with expertise in their conditions. Financial arrangement features of eye care practices also are associated with patient satisfaction with care. The most likely mechanisms underlying these associations are effects on provider behavior and satisfaction, which in turn influence patient satisfaction. Managed care plans and provider groups should aim to minimize the negative impact of managed care features on patient satisfaction.