To explore nurse involvement in cardiovascular risk management (CVRM) in primary care and how this involvement was associated with the degree of structured chronic illness care.

A cross-sectional observational study in 7 European countries.

Five aspects of nurse involvement in CVRM and 35 specific components of structured chronic illness care were documented in 202 primary care practices in Austria, Belgium, Germany, the Netherlands, Slovenia, Spain, and Switzerland. An overall measure for chronic care management, range 0 to 5, was constructed, derived from elements of the Chronic Care Model (CCM). Random coefficient regression modeling was used to explore associations.

A majority of practices involved nurses for organization of CVRM in administrative tasks (82.2 %), risk factor monitoring (78.5%) and patient education (57.1%). Fewer practices involved nurses in defining protocol and the organization for CVRM (45%) or diagnosis and treatment (34.6%). With an increasing number of tasks handled by nurses, overall median adoption of CCM increased from 2.7 (95% CI, 1.5-3.6) to 4.2 (95% CI, 3.8-4.1). When the number of nurse tasks increased by 1, the adoption of CCM increased by 0.13 (

 <.05; 95% CI, 0.03-0.22). Some practices with low nurse involvement had high adoption of CCM, while variation of adoption of CCM across practices reduced substantially with an increasing level of nurse involvement.

Nurses were involved in the delivery of CVRM in varying degrees. Higher involvement of nurses was associated with higher degree of structured chronic illness care, with less variation.

Nurses were involved in the delivery of cardiovascular risk management (CVRM) in European primary care practices at varying degrees. Higher involvement of nurses was associated with better chronic care management, but some practices with low nurse involvement also provided well-structured chronic care management.

		Nurse involvement in cardiovascular risk management was limited in the sample of practices.

		Nurses were all involved in administrative tasks, recalls, and recording.

		The level of nurse involvement—rather than a nurse’s mere presence&mdash;matters for implementation of structured chronic care.

Internationally, in primary care, clinical tasks have been shifting from physicians to nurses in varying degrees. Reallocation of such tasks from family physicians (FPs) to nurses has been found to be associated with improved, or at least equivalent, quality and outcomes of chronic disease care.

 The degree of reallocation of tasks varies across countries as a result of policy, organizational, and legal factors.

 In addition, the absence of robust evidence on the impact of such reallocation in natural settings (as opposed to controlled trials and demonstration projects) is an issue in decisions to shift clinical tasks to nonphysicians.

Better structuring of primary healthcare for patients with chronic diseases is expected to result in better outcomes for patients and societies,

 if it integrates all domains (eAppendix, available at www.ajmc.com) specified by the Chronic Care Model (CCM), a model created by Wagner.

 Allocation of tasks to nurses may contribute to better implementation of structured chronic care by increasing capacity and competence in specific areas, such as coordination and patient education, compared with healthcare delivered by physicians only.

Cardiovascular disease (CVD) remains a major cause of death and disability around the world, and many preventive measures focusing on CVD have been developed for use in public health and primary care.

 Reassigning some tasks usually performed by physicians to nurses can be applied in cardiovascular risk management (CVRM).

 Nursemanaged CVRM programs have been shown to improve patients’ lifestyle, risk factor control, use of medications, and quality of life.

 These positive effects are based on the clinical knowledge and skills of nurses,

 but potentially also on their contribution to teamwork and practice organization.

Our study sought to explore the potential contribution of task allocation to primary care nurses to the implementation of structured chronic care for patients with cardiovascular conditions. The study focused on primary care practices in 7 countries to try to get meaningful results from real clinical practice settings across various healthcare systems.

This study was based on secondary analysis of data from the European Practice Assessment of Cardiovascular Risk Management Project (EPA Cardio Project), an observational study on CVRM in 315 primary care practices in 10 countries in 2008-2009.

 EPA Cardio focused on patients with CVD, patients at high risk for CVD, and healthy adults. Multiple measurement instruments were used, including chart reviews, patient surveys, and validated questionnaires on practice characteristics

 completed by FPs in the practices. For the present study, we included data from 202 practices in 7 countries: Austria, Belgium, Germany, the Netherlands, Slovenia, Spain, and Switzerland. Data from the remaining 3 countries were excluded from this analysis because the required data on nurse involvement in tasks concerning CVRM were missing.

For this study, we used data from the EPA Cardio Project’s FP questionnaires—specifically, the data on practice characteristics (practice size, number of full-time-equivalent FPs and nurses) and the diversity of tasks assigned to FPs and nurses. For our purposes, “nurses” included both nurse practitioners and advanced practice nurses, all of whom performed clinical tasks in primary care practices. We measured nurse and FP involvement in 5 specific tasks concerning CVRM: 1) administrative tasks, recalls, and recording (enrolling and selecting patients for periodic checkups, managing patient records, archiving laboratory results, and mail); 2) monitoring risk factors (periodic monitoring of blood pressure, smoking status, weight, cholesterol, etc.); 3) patient education and counseling (including discussion of control of diet and physical activity); 4) defining protocol and organization of CVD care (drafting protocols based on guidelines for CVD care, coordination of CVD consulting hours); and 5) diagnosis, risk assessment, and medical treatment (determining risk profile, periodic check-up for CVD patients, discussing medication).

These are tasks that the core group (consisting of researchers from the EPA Cardio research group) decided that nurses are presumably capable of performing.

 The tasks were measured on a dichotomous answering scale (yes/ no), and in addition, for each one, the degree of adoption of CCM was calculated using a list of 35 criteria (eAppendix).

 The measurements are translated into a score on a 0-to-5 scale based on the 5 practice-related domains derived from the CCM

, each of which has equal weight: 1) healthcare organization (7 items); 2) delivery system design (15 items); 3) decision support (3 items); 4) clinical information systems (6 items); and 5) self-management support (4 items). A higher total score means a greater degree of structured chronic illness care.

Practice size was determined from patient list size when available, and otherwise on yearly attending patient numbers. Results of both nurse practitioners and advanced practice nurses on the 5 specific CVRM tasks were combined.

Data analysis consisted of both descriptive and analytical methods. Random coefficient linear regression modeling was used to explore the effect of nurse involvement on structured illness care (adoption of CCM). The influence of the number of FP tasks and nurse tasks, nurse/FP ratio, and practice size on the adoption of CCM was also explored in the regression model. Two-level models were specified with practices nested in countries. Data analysis was performed using the SPSS 16.0 software package (Chicago, Illinois).

 shows characteristics of the practices in the 7 countries. The number of included primary care practices ranged from 21 in Switzerland and Germany to 36 in Spain. Spain had the largest mean practice size and Slovenia the smallest. In Austria, Germany, the Netherlands, and Spain, 100% of practices had a nurse employed. In Slovenia, 94.1% of practices employed a nurse, Switzerland 85.7%, and Belgium 33.3%. Overall, 89.6% (N = 177) of practices employed a nurse. The number of FP tasks varied minifrom 3.9 in Slovenia to 4.9 in Spain, while the number of nurse tasks varied from 1.5 in Belgium to 4.8 in Spain. The adoption of CCM was highest for practices in Spain and lowest for practices in Switzerland.

Considering nurse involvement in specific tasks, 

shows nurses were mostly involved in CVRM-related administrative tasks, recalls, and recording (82.2%) and least involved in diagnosis, risk assessment, and medical treatment (34.6%). FP involvement was highest in diagnosis, risk assessment, and medical treatment (99%) and lowest in administrative tasks, recalls, and recording (68%). For administrative tasks, recalls, and recording; monitoring risk factors; and patient education and counseling, most percentages of nurse involvement were above 50%. For the tasks defining protocol and organization of cardiovascular care and diagnosis, risk assessment, and medical treatment, most percentages of nurse involvement were below 50%. Considerable variation between countries was found on involvement in specific tasks of both nurses and FPs.

Relation of nurse involvement to structured chronic illness care

illustrates the number of nurse tasks related to the adoption of CCM. When more tasks were allocated to nurses, the mean adoption of CCM was higher. 

shows that the mean adoption of CCM in practices without nurse involvement was 2.6 (SD 1.3; 95% CI, 1.5-3.6) and in practices with nurse involvement on all tasks, the mean adoption of CCM was 4.0 (SD 0.5; 95% CI, 3.8-4.1). Practices without nurse involvement on CVRM-related tasks showed a minimum adoption of CCM of 0.5 and a maximum adoption of CCM of 4.4. For practices with nurse involvement on all CVRM-related tasks, the minimum and maximum were 2.4 and 4.7. In practices where nurses had only 1 CVRM-related task, that task, in the vast majority, was administrative (eAppendix available at 

). Nurses with 2 tasks mostly had administrative tasks combined with monitoring risk factors. When nurses had 3 or 4 tasks, combination of tasks varied more. The mean adoption of CCM was lowest when nurses’ tasks skewed towards the administrative (3.3, SD 0.9) and highest when the tasks included diagnosis, risk assessment, and medical treatment (4.0, SD 0.7). The eAppendix provides further explanation.

The Figure suggests visually that with increasing involvement of nurses, the variation on the adoption of CCM decreased. Low scores on the adoption of CCM were absent when nurses had more tasks. However, some practices without nurse involvement had high adoption of CCM.

 shows the results of the regression model. Number of tasks of FP and of nurse, nurse/FP ratio, and practice size were taken into account. Practice size showed no effect on the adoption of CCM (

 = .19). The analysis included 155 cases. The degree of skewness was explored for the adoption of CCM. This variable was normally distributed. Results show that the number of nurse tasks had a positive effect on the adoption of CCM. When the number of nurse tasks increased by 1, the adoption of CCM increased by 0.13 (

 <.05; 95% CI, 0.03-0.22). The regression model used in this analysis explained 19% of the variance on the adoption of CCM.

Nurses were involved in the delivery of CVRM in this sample of European primary care practices, but in varying degrees. In a vast majority of practices, nurses were involved in administrative tasks, recalls, and recording, and they were least involved in diagnosis, risk assessment, and medical treatment of cardiovascular care. Involvement of nurses in more aspects of CVRM was associated with better structured chronic illness care, but some practices with limited nurse involvement, related to administrative tasks only, also provided well-structured chronic illness care.

The variation of nurse involvement in the delivery of CVRM in this study may have several determinants. Reallocation of tasks concerning CVRM could differ among types of nurses, although previous research has shown that mid-level providers, with different educational backgrounds, perform similar tasks.

 Nurses’ levels of training and experience

 could influence the outcomes, but they were not taken into account in this study. The definition of “nurse” applied in this study could also influence the outcomes.

Nurses’ responsibility for chronic disease management may vary from practice to practice, dependent on the willingness of FPs to delegate tasks.

 Of the practices in our study with low nurse involvement (less than 2 tasks on CVRM; N = 23) and with high adoption of CCM (>3.5), none employed other nonclinical staff members performing administrative tasks or other CVRM-related tasks. Overall, nurse involvement in CVRM was mixed, but limited in the sample of practices.

Our results showed that well-structured chronic care is possible in practices with little nurse involvement. With maximum nurse involvement, there is on average better chronic care with less variation in the adoption of CCM. Successfully organizing chronic illness care may well be dependent on elements of care not accounted for in this study. Practice characteristics like team size and workload could affect the organization of chronic illness care.

Furthermore, it may be that better-organized practices are more likely to employ and retain nurses to manage chronic patients; a better-organized practice likely provides a better working climate for nurses, thus providing higher job satisfaction. Practice size could influence the organization of chronic illness care; evidence shows that in larger patient populations, more clinical tasks are performed by healthcare providers other than physicians.

 However, our study suggests practice size has no significant influence on the adoption of CCM.

Countries with strong primary care systems are expected to manage chronic conditions more effectively.

 Initiatives for improving the management of chronic conditions are in different stages of development in the participating countries. Initiatives in Austria and Belgium are in an early development stage.

 Furthermore, national location may be a factor: In some countries, initiatives to improve management of chronic conditions are introduced nationally (eg, Germany), while in others (eg, the Netherlands) this is handled through local or regional projects. All German practices included in this study employed nurses with clinical tasks (monitoring such risk factors as blood pressure, smoking status, weight, cholesterol, etc). This indicates selection bias; previous research indicates that German nurses were mainly involved in administrative tasks like arranging appointments for patients, answering telephone calls, and preparing and providing patient files.

Our findings should be interpreted with caution as our study had a number of limitations. Practices volunteered to participate in this study. This convenience sample may cause bias; it is also possible that participating practices are better organized concerning cardiovascular care management. Participating countries have differences in their overall organization of healthcare that may have caused bias; there also may have been differences, by country, in interpretation of the questionnaire. Also, in this study, only tasks concerning CVRM were considered. An inventory of tasks considering other chronic conditions such as diabetes mellitus or chronic obstructive pulmonary disease could have generated different results.

Tasks of nurses working on CVRM are predominantly administrative or include the monitoring of risk factors; they are less focused on organizational tasks. The effect of nurse involvement related to CVRM on the organization of chronic illness care is positive but modest. A metaanalysis related to the management of another chronic illness, diabetes, shows that team change is a key ingredient for improving chronic disease management on patient outcomes; it provided larger reductions in glycated hemoglobin values than other quality improvement strategies evaluated.

 Furthermore, extending the role of nurses in the organization of chronic illness care could result in cost effectiveness

 Another study investigating the clinical effectiveness of practice nurses acting as substitutes for FPs in CVRM found that practice nurses achieved equal or better results than FPs.

 If nurses are given more responsiblity for the organization of chronic illness care in general, in addition to the tasks that are directly related to patients, the adoption of CCM could become higher.

This study quantified the role of nurses in the organization of CVRM in primary care practices across Europe. More nurse involvement in CVRM was associated with better structured chronic illness care in primary care. To optimally utilize the added value of nurses in primary care, nurses should be engaged in all aspects of CVRM-related care, provided that their level of education is adequate. In general, giving nurses more responsibility for the organization of chronic illness care might engender higher job satisfaction for all staff members.

Articles

WEB EXCLUSIVE

This study sought to explore if shifting care to nurses in cardiovascular risk management in primary care is a key to more structured chronic care.

Shifting Cardiovascular Care to Nurses Results in Structured Chronic Care

Diagnosis of chronic hepatitis C virus (HCV) is a 2-step process involving hepatitis C antibody (HCVab) testing followed by viral ribonucleic acid (RNA) testing. The HCV status of those with a positive HCVab without viral testing cannot be determined. This study sought to describe the HCV-related care provided to patients in this care gap.

Retrospective cohort study of active patients with a positive HCVab test who did not complete viral testing.

Electronic medical records (EMRs) were reviewed to determine if each subject’s first positive HCVab result was acknowledged by a provider. For results acknowledged, we described provider actions in response to the result. When providers performed specific clinical actions within 1 year of the positive HCVab test, we captured the type of action taken. When the unsubstantiated diagnosis was documented in the EMR, we determined if the diagnosis was mentioned by subsequent providers.

Positive HCVab results were not acknowledged in 31% of subjects. In 35%, providers added chronic HCV to the problem list in the EMR, resulting in a higher likelihood of subsequent providers mentioning the diagnosis in their EMR documentation. In 143 subjects whose providers recommended HCV-related clinical actions within 1 year of the positive result, 45% were educated about HCV and 42% had their liver enzymes monitored.

With more widespread testing anticipated and more effective treatments available, health systems should ensure the HCV diagnostic process results in the delivery of an accurate and timely HCV diagnosis, to reduce the risk of harm to patients.

Given expanded hepatitis C virus (HCV) screening recommendations, management of positive screening results needs optimization to ensure that tested patients can benefit from recent treatment advances.

		For patients with a positive HCV antibody and no viral RNA testing, 31% of the antibody results were not acknowledged by any provider, including the ordering provider.

		HCV care was performed in the absence of viral testing, leading to unnecessary treatments or stigma in those without chronic HCV.

		An unsubstantiated diagnosis of chronic HCV in a patient’s electronic medical record’s problem list leads to a large percentage of providers referencing this diagnosis.

Chronic hepatitis C is a blood-borne virus affecting approximately 4 million Americans. After exposure to the hepatitis C virus (HCV), about 20% of people spontaneously clear the virus within the first 6 months of exposure, and the remaining 80% develop chronic HCV.

 Chronic HCV contributes significantly to the rising incidence of cirrhosis and hepatocellular carcinoma (HCC) in the United States.

The cost of care increases with the severity of liver disease and chronic HCV-related cirrhosis is now the most common indication for liver transplantation in adults.

The diagnosis of chronic HCV is a 2-step process. Step 1 is initial HCV antibody (HCVab) testing (

). If the HCVab test is positive, Step 2 is an additional test to determine if viral RNA is present in the blood;

 it is required to establish or refute the diagnosis of chronic HCV. A positive HCVab test and a positive RNA test indicate the presence of chronic HCV, whereas a positive HCVab result and a negative RNA result indicate that the exposed person has either spontaneously cleared the virus or has achieved a sustained virologic response from treatment.

Individuals who have a positive HCVab but have never completed viral testing cannot be classified as chronic or not because there is no virologic evidence to establish the diagnosis. The chronic HCV status of these patients remains unknown until viral RNA testing is complete. These individuals represent an important care gap in the management of HCV because their undetermined status can lead to missed opportunities for appropriate HCV-related care, such as alcohol cessation counseling, screening for HCC for those at risk, and/or timely receipt of potentially curative therapies.

Several recent investigations have highlighted this issue and indicated that a significant proportion of their study populations fell into this care gap.

 Additionally, recent recommendations to broaden HCV testing beyond a risk-based model to include all patients in the birth cohort of 1945-1965 would translate to an additional 20 million people being candidates for HCV testing.

 Given this volume and the need to reduce HCV-related morbidity, it is important to gain a better understanding of why RNA testing is not completed and what the consequences of this care gap are to patients.

To determine this, we conducted a retrospective cohort study of all active patients at our institution who had at least 1 positive HCVab test but who did not complete viral RNA testing to address the following questions: 1) What actions were and were not taken by medical providers after a positive HCV antibody result?, and 2) What were the downstream effects of documentation of a HCV diagnosis in the absence of viral testing?

Our cohort included all active patients who had at least 1 positive HCVab result between January 1, 1991, and January 1, 2010, but no subsequent history of completing HCV viral RNA testing at the Louis Stokes Cleveland Veterans Affairs Medical Center (LSCVAMC), its 13 associated community-based outpatient clinics, or any other Veterans Affairs (VA) facility. Active patients were defined as any patient with a medication refill or patient encounter (including test result/ vital sign) within 730 days of the date of the data query. The start and end dates were selected because 1) the availability of EMRs became more widespread in the VA system around the beginning of 1991, and 2) in early 2010, our facility implemented the VA national directive calling for HCV Reflex Testing at all VA facilities. This directive was designed to prevent additional patients from failing to complete viral testing in a timely manner, and calls for an additional blood sample to be collected when the screening antibody test is drawn.

If the antibody test is positive, the second blood sample is to be used for viral testing, circumventing the need for another blood draw to complete this step. Thus, these dates were chosen to provide the highest likelihood of ascertaining the outcomes of interest while also capturing the majority of cases.

Our locally created Hepatitis C Population Management Application was used to identify subjects for this investigation. This application captures and stores data from the VA Region 3 Data Warehouse and has been previously validated through an iterative development process. A query of this application was conducted on May 20, 2011, and identified 419 subjects.

Medical records of all subjects were systematically reviewed by a single co-investigator over a 5-month period to evaluate the outcomes of interest. Weekly meetings between this co-investigator and the senior investigator were held to ensure consistency and accuracy in the adjudication of outcomes. This investigation was reviewed and approved by the Institutional Review Board at LSCVAMC. Given the retrospective nature, obtaining informed consent was not required.

During 1999, our facility underwent transitions in medical record system configurations, resulting in uncertainties about completeness of transfer of progress notes prior to December 31, 1999. These uncertainties became apparent during our review of the 78 subjects (18.6%) who had HCVab testing prior to this date. Twenty-nine of the 78 subjects had only mental health encounter progress notes available for review while the remaining subjects had both mental health and medical provider progress notes for review. As a result, we could not determine with absolute certainty if all progress notes did transfer or if some patients had only mental healthcare during that time period. This uncertainty may limit our ability to evaluate outcomes determined by review of provider progress notes; however, since fewer than 10% of our total subjects were potentially affected and because other outcomes could still be evaluated, these patients were not excluded from the investigation.

Subject Demographics and Clinical Characteristics 

We collected the following demographic information on all subjects: age at date of data query, gender, race, and presence of current or previous alcohol abuse (by 

International Classification of Diseases, Ninth Revision, Clinical Modification 

code 350.0x) in the EMR. We collected the number of subjects with a most recent serum albumin value <3.5 g/dL, platelet count <150 X 103 /μL, alanine aminotransferase (ALT) >45 U/L, and aspartate aminotransferase (AST) >36 U/L. The value immediately preceding the query date (May 20, 2011) was chosen to provide a snapshot of the current health of this cohort. We also calculated the total number of consecutive years that each subject had received healthcare from our VA facility. The time span between the first test result, vital sign, or patient encounter ever and the date of the data query was used to calculate this parameter. These variables were able to be collected for all subjects as its determination was not dependent on review of provider documentation in progress notes (

Positive Hepatitis C Antibody Test Characteristics 

For each subject, we identified the first positive HCVab test result, then conducted a detailed review of entries to the subject’s EMR made after the date of this first positive HCVab test. For each subject’s first positive HCVab test, we determined which healthcare service (eg, inpatient medicine, psychiatry service, etc) ordered the test. The number of subsequent HCVab tests per subject was also captured.

Provider Management of Positive HCVab Screening Results 

To determine if the positive HCVab test was acknowledged by a healthcare provider, we reviewed all progress notes after the date of the first positive HCVab test. We classified an HCVab test as “acknowledged” if, at any point in time after the date of the positive result, a provider did one of the following: 1) mentioned viral RNA testing in their progress note, although the testing was never completed, or 2) completed other types of management, which included “documentation actions” and/or “clinical actions.”

“Documentation actions” were defined as provider documentation of chronic HCV in the subject’s EMR, either by recording chronic HCV in a subsequent progress note, or by entering the diagnosis of “Chronic Hepatitis C” into the subject’s problem list at any time after the positive HCVab result.

“Clinical actions” were defined as any mention of an HCV-related medical recommendation in any subsequent progress note after the positive HCVab test. To characterize the recommendations that occurred in response to the positive HCVab we captured HCV-related medical recommendations made within the 12 months after the positive HCVab test result. These included: 1) documentation of HCV education provided during a medical encounter, 2) documentation of provider request for HCV genotype testing, 3) recommendation for or administration of a Hepatitis A and/or B vaccine, 4) documentation of alcohol reduction counseling, 5) request for an alpha-fetoprotein test or imaging of the liver, 6) a referral to the HCV clinic, or 7) serial monitoring liver function tests (LFTs).

Downstream Effects of Documentation of Chronic Hepatitis C 

When a positive HCVab test result was acknowledged and the acknowledging provider performed documentation actions, we evaluated if any future medical providers referenced the unsubstantiated diagnosis of chronic HCV through their own EMR documentation.

Descriptive statistics were used to summarize subject demographics, clinical characteristics, positive HCVab test result characteristics, and clinical actions taken after positive HCVab test results. Chi-square tests of association were used to assess categorical variables.

Demographics for the 419 subjects identified by the query are listed in Table 1. The mean age of subjects was 59.6 years at the date of the query and 97% (n = 407) of subjects were male. Almost 40% (n = 163) of subjects had either a current or past history of alcohol abuse. Subjects received care at our VA for a mean of 8.1 (SD ± 3.0) years.

Positive Hepatitis C Antibody Test Characteristics

Of the 419 subjects included in the data analysis, 57% (n = 239) of the first positive HCVab tests were ordered by providers located in VA outpatient primary care settings and 32% (n = 133) were ordered by providers in mental health rehabilitation programs (

). Mental health rehabilitation programs included inpatient and outpatient substance abuse treatment, gambling rehabilitation, or domiciliary programs. Sixty-nine percent (n = 288) of subjects had their HCVab test acknowledged by a medical provider (Table 2) leaving 31% of subjects’ results never acknowledged. Forty-one percent of subjects (n = 171) had more than 1 positive HCVab test result in their medical record, and the number of positive tests ranged from 1 to 15 (Table 2). Subjects who had their first positive HCVab test ordered by a mental health provider were significantly more likely to have 3 or more positive antibody draws than those whose test was ordered by a non-mental health provider (40.6% vs 9.4%, 

Of the 419 subjects evaluated, 31% (n = 131) of subjects had an initial positive HCVab test result that was never acknowledged by any medical provider. Figure 2 illustrates the types of provider actions completed in the 69% of subjects (n = 288) for whom a medical provider acknowledged the positive HCVab test result. While in 9% (25 of 288) of these subjects, a provider mentioned the need for viral RNA testing, it was ultimately not completed. In 25% (72 of 288) of subjects, the provider performed only “documentation actions” by documenting an unsubstantiated diagnosis of chronic HCV in the progress note or adding it to the EMR problem list.

In 14 of the 288 subjects (5%), provider actions were difficult to adjudicate and could not be categorized as either documentation or clinical actions; they were placed into an “other” category (Figure 2). Subjects included in the “other” category were those in which it appeared the provider misinterpreted the positive HCVab result as a positive result for Hepatitis A or B.

In the absence of an established diagnosis of chronic HCV, in 61% (177 of 288) of subjects to whom the positive HCVab was acknowledged, a provider performed some type of chronic HCV-related medical recommendation with or without documenting chronic HCV in the subject’s medical record. For those (143 of 177) who had any type of clinical recommendation performed within 12 months of the positive HCVab test result, we captured the type of recommendation that was made or performed. In subjects with clinical recommendations within 1 year, almost half (64 of 143) received education by the acknowledging provider regarding chronic HCV. Serial monitoring of LFTs was recommended to 42% of subjects (60 of 143). The need for hepatitis A or B vaccinations was mentioned in a progress note for 25% of these 143 subjects, with 18 subjects receiving at least 1 dose, and 5 completing the entire vaccination series. A referral was placed to the HCV clinic for 24% of subjects (35 of 143), and alcohol counseling was documented in the EMR for 22% (32 of 143) of subjects. No acknowledging providers ordered a HCV genotype test despite having the ability to do so.

Management of hepatitis C screening results can be optimized to ensure that patients receive high-quality care, reducing morbidity and costs related to the virus.

Evaluating a Hepatitis C Quality Gap: Missed Opportunities for HCV-Related Care

Physical activity levels are low among older adults. Many Medicare members have access to low-cost programs including Silver Sneakers (SS) and EnhanceFitness (EF) at no additional cost, however, utilization of these programs is low. We aimed to compare characteristics of people using SS and EF to nonusers of these programs to better understand the characteristics of these 2 populations and to guide future physical activity promotion program design.

We used 2010 and 2011 electronic health records including demographic, health condition, Charlson comorbidity score, healthcare cost and utilization, and SS and EF program utilization data from 37,492 Medicare members from a large integrated health care system. Models were fit using logistic and negative binomial regression adjusting for age, gender, race, ethnicity, BMI category, and primary care clinic location.

Compared with nonusers (N = 30,733; 82%), SS users (N = 6200; 16.5%) were younger and less likely to be male, obese, or have diabetes or cardiovascular disease; they also had lower Charlson scores and fewer hospital admissions than nonusers. EF users (N = 721; 2%) were older, were less likely to be male, had lower Charlson scores, and had fewer hospital admissions compared to nonusers.

Low-cost, evidence-based physical activity programs are vastly underused by Medicare members. Our data suggest that targeting more chronically ill and obese older adults for physical activity programs might help improve the reach of existing evidencebased programs.

While physical activity levels are low among the Medicare eligible population, less than one-fifth of members in 1 healthcare system used available physical activity programs designed for older adults (Silver Sneakers and EnhanceFitness).

		People who used the Silver Sneakers program were younger, more likely to be women, less likely to be obese, and generally had fewer health conditions than those who did not.

		People who used EnhanceFitness were older, more likely to be women, and generally had similar rates of chronic conditions, except for lower rates of overall morbidity, compared with those who did not attend the program.

		Targeting people with chronic conditions, men, and people who are obese for uptake of these programs could expand their reach and population-wide impact.

Regular physical activity improves physical, mental, cognitive, and functional health.

 However, of all adults in the United States, adults over age 60 have the lowest rate (less than 5%)

 of meeting the United States Department of Health and Human Services Physical Activity Guidelines (150 minutes of moderate intensity physical activity or 75 minutes of vigorous physical activity per week). As the older adult population in the United States continues to grow, finding effective means to promote physical activity and engage older adults in existing programs is imperative to promote healthy aging.

SilverSneakers (SS) and EnhanceFitness (EF) are 2 national, evidence-based physical activity programs for older adults. SS provides members with access to 11,000 fitness facilities nationwide; more than 40 Medicare health plans offer membership as a benefit.

EF offers group exercise classes at various community locations. In 2010, there were 486 active EF sites; the YMCA is currently working on adding locations.

Both programs have been associated with lower healthcare costs in retrospective cohort studies.

 For instance, a 6-month randomized trial found that participants in EF improved some Short Form-36 measures of health status as well as depressive symptoms.

 Non-randomized studies show higher levels of physical function among people attending EF classes.

For example For example, for the 12 months preceding May 2010, 6939 people attended 10 or more EF classes nationwide.

Group Health (GH) is a nonprofit healthcare system serving over 600,000 members, predominantly in western Washington State. GH has provided coverage for EF and SS programs through Medicare Advantage for over a decade. Little has been known about the demographic and health characteristics of individuals who use EF and SS. Our goals in this study were to examine recent use patterns of the programs and to identify the characteristics of older adults who use the programs, compared with nonusers, to obtain insight into how efforts might be best targeted to improve program uptake.

Participants were between ages 65 and 99 and were continuously enrolled Medicare members of GH from January 1, 2009, through December 31, 2011. We excluded people residing in long-term care, hospice care, or skilled nursing facilities; who were wheelchair-bound; or who had serious mental health or substance use disorders (not including depression, anxiety, or dementia). This resulted in 37,492 eligible members.

Both SS and EF provide GH Medicare Clear Care HMO plan enrollees access to their programs at no additional cost. GH Medicare members can learn about SS and EF programs via benefits websites, targeted mailings, or through word of mouth. Additionally, GH primary care providers can refer patients to EF and SS through an electronically generated summary of their visit that provides a phone number to call for enrollment.

. SS provides participants with access to more than 50 fitness facilities throughout Washington State, primarily in western Washington.3 At each, the participant can access the facility as any other gym member would; this includes individual use of exercise equipment or attending any group classes offered (including SS group exercise classes).

. EF offers group exercise programs for participants at more than 50 community sites throughout western Washington, including senior centers, retirement facilities, and healthcare clinics. Instructors are certified to teach the program through a licensing process administered by Senior Services of Seattle. Each class follows a standardized format: 5 minutes of warm-up, 20-25 minutes of moderate-intensity aerobics, 20 minutes of resistance strength training, and 10 minutes of flexibility and balance exercises.

Participants can perform the exercises while seated, standing, or using an assistive device, to accommodate various functional abilities. EF has been offered by GH since 2001 and, for members who do participate, the average attendance is 7.6 classes per month.

SS and EF provided program participation data from 2006 through 2011. People were considered EF or SS program “users” if they had a record of attending the program at least twice within a calendar year. Using GH’s unique membership identification numbers, we linked program participation data from 2011 to electronic health record (EHR) data containing diagnoses, demographics, and costs and utilization data from the year prior to use (2010). For those without a visit in the previous year, we extracted diagnosis data from 2009. Those without a visit during 2009-2010 were excluded from the analysis. We compared users of SS and users of EF with nonusers of either program.

We compared these groups on demographic characteristics (age, gender, race/ethnicity); health conditions (obesity, diabetes, cardiovascular disease, falls, osteoarthritis, cancer, Charlson score); healthcare costs; and healthcare utilization obtained through electronic health record (EHR) data. When calculating body-mass index (BMI), we used the most recently available height. Members were classified into categories of weight status using BMI values for underweight (BMI <18.5), normal weight (18.5-24.9), overweight (25-29.9), and obese (30 and higher).

International Classification of Diseases, Ninth Revision, Clinical Modification

 diagnosis codes were used to define the chronic conditions of interest and were based on previously published definitions

 or consensus by the research team, which included an internal medicine physician. Charlson scores are a general measure of comorbidity which are computed based on the presence of 19 conditions weighted for seriousness; scores are predictive of mortality.

 Total healthcare costs, hospital admissions, and number of visits to primary care and specialty care in 2010 were also extracted from automated health plan data.

We described patterns of use between 2006 and 2011 using simple descriptive analyses to examine trends in the percentage of GH-enrolled individuals using SS and EF. We examined the overall use rate (total number of users that year divided by the total number eligible to use conthe programs that year) and the percentage of users who had used the program in the previous year (continuing users). The difference between the total number of users and continuing users represents the percentage of new users (users who had not used the program in the previous year).

To examine binary and categorical characteristics (demographic, BMI, and health diagnosis variables) between program users and nonusers, we fit logistic regression models. We compared means for continuous variables (cost, utilization, and Charlson scores) between users and nonusers using negative binomial regression (similar to least-squares regression with better accounting for skewness). All models were adjusted for age, gender, race, ethnicity, BMI category, and primary care clinic location (in associations for demographic and BMI variables, we adjusted for all other variables). We adjusted for primary care clinic location because some clinics may be in closer proximity to more EF or SS sites. We required a 

 < .01 for significance to control for the number of analyses performed and to reduce the rate of false positive findings. Analyses were conducted using SAS version 9.2 (Cary, North Carolina).

In 2010, the average age of the sample was 76.4 (SD = 7.5) years. 

 shows the characteristics of SS and EF users. In adjusted models, SS users were generally younger, less likely to be male, and more likely to be white. SS users were also less likely to be underweight and more likely to be normal weight or overweight. EF users were generally older and less likely to be male in adjusted models.

Out of those eligible for SS and EF, 16.5% used SS and 1.9% used EF in 2011 (data not shown). Use of EF stayed relatively stable (~2%) between 2006 and 2011, declining from 870 to 721 users. Use of SS increased from about 10% to more than 16% in that period, growing from 4043 to 6201 users). In 2011, the majority of program users were continuous users: 88% for EF, 74% for SS.

Relationship with Health Conditions, Healthcare Costs, and Utilization

In adjusted models, as shown in Table 1 and Table 2 SS users were less likely to have several chronic conditions (eg, diabetes, cardiovascular disease), were in better overall health as evidenced by lower Charlson scores, and had fewer hospital admissions than non-users. SS users had more primary and specialty care visits. There were no differences between SS users and nonusers for cancer or medical falls while there were higher rates of osteoarthritis among SS users. Charlson scores and hospital admissions were significantly lower for EF users with no other comparisons reaching statistical significance.

In a healthcare system that provides widespread access to 2 evidence-based physical activity programs for Medicare members, we found that fewer than 20% of those eligible used the programs at least twice in 2011. In addition, very few new users began EF in 2011, while about one quarter of SS users were new in 2011. SS use increased while EF use remained about the same over the 5-year period.

Users of EF and SS had several characteristics that set them apart from nonusers. Individuals who used EF or SS were more likely to be women, contrary to previous studies suggesting that SS users were more likely to be male.5,6 However, these prior studies used age- and gender- matched comparison groups. Those using EF were more likely between 75 and 85 years old, while SS users were more likely between 65 and 75 years old. Previous studies have not reported on age differences in user groups.

Individuals who used SS were less likely to be classified as underweight or obese. While patterns were similar for EF, models were not significant. Previous studies have not examined BMI differences in users and nonusers. Obesity is associated with increased healthcare costs, morbidity, and mortality,

and physical activity among obese older adults could help improve physical function and health, and reduce body weight or mitigate weight gain.

 Our finding that both EF and SS users were less likely to be classified as obese has implications because women over age 60 have the highest rate of obesity in the US (42%).

EF and SS may not appeal to or cater toward obese older adults who may have more mobility limitations, multiple chronic conditions, and less ability to be active.

We also found that, while EF users had significantly lower overall comorbidity assessed by Charlson score, they did not differ from nonusers on most of the specific chronic health conditions we examined. On the other hand, SS users had lower likelihood of cardiometabolic conditions (eg, diabetes, cardiovascular diseases) and lower Charlson scores. Overall, the findings suggest that EF is more used by patients with chronic health limitations that tend to become more common as people age, and SS may be more appealing than EF to younger and generally healthier older adults. While EF may be used more among people with chronic conditions, it is less utilized than SS overall. Innovative methods for health systems to better promote use of EF, particularly for older adults with chronic conditions, should be examined since the current system, which relies mainly on passive methods (eg, benefits websites) and physician referrals, does not appear to be highly effective in isolation.

There are several limitations to our study. We relied on medical diagnosis codes, which can be inaccurately entered into the health record. In addition, our EF user group was relatively small, which may have limited our ability to detect differences. Finally, we defined demographic and health characteristics prior to use of SS and EF, but users could have been using the program for several years prior, so essentially our data can be interpreted as cross-sectional.

Authors compared users and non-users of older adult physical activity programs (EnhanceFitness and Silver Sneakers) within a healthcare system on health conditions, utilization, and costs.

Characteristics of Older Adult Physical Activity Program Users

To examine the receipt of carotid intervention among eligible patients post stroke in the Veterans Health Administration (VA).

We examined whether veterans admitted to a VA medical center in 2007 with a diagnosis of stroke and who were eligible for intervention, received carotid intervention in a period up to 6 months after their index hospitalization. We also examined whether demographics, comorbid conditions, stroke severity and availability of vascular intervention services were independently associated with receipt of intervention.

Among the 5721 patients admitted, 253 ischemic stroke patients had evidence of some carotid stenosis and had data on side of stroke available. Among the 200 patients who had at least 50% to 99% stenosis of the carotid artery, 34 (17%) received intervention (95% confidence interval [CI], 11.79%-22.21%). In a multivariable model, black race and past history of diabetes were significantly associated with carotid intervention: An eligible black patient was 6 times more likely to NOT receive intervention compared to patients of other races (adjusted odds ratio [OR] = 6.54; 95% CI, 1.34-31.9), and a patient with diabetes was 3 times more likely to NOT receive intervention (adjusted OR = 3.38; 95% CI, 1.24-9.24) compared to nondiabetics. Stroke severity and availability of vascular surgery services was not associated with receipt of intervention.

Few patients with symptomatic carotid stenosis who were admitted with stroke to the VA received carotid intervention. Future research should be directed at improving access to this procedure among eligible patients in the VA.

Most national focus on performance measurement and quality reporting turn to simple measures such as receipt of an aspirin, a beta-blocker, or a simple lab test. Although more difficult to accurately measure, there is likely significant room for improvement around decisions about more complex measures that are just as important to a patient’s health.

		Symptomatic carotid stenosis is uncommon among Veterans admitted to a VA hospital for acute ischemic stroke.

		Among those with symptomatic carotid stenosis, a minority of patients received carotid revascularization within 6 months after stroke.

		Availability of local vascular intervention services was not associated with receiving carotid revascularization.

Stroke is the fourth leading cause of death and a leading cause of disability among adults in the US.

 Approximately 10 to 15% of ischemic strokes are attributable to atherosclerosis of the internal carotid arteries. 

 Carotid stenosis is categorized as either symptomatic or asymptomatic. Patients with recent (less than 6 months) ischemic stroke or transient ischemic attack (TIA) in the vascular distribution of a partially blocked carotid artery are defined as having symptomatic carotid stenosis, and patients who have not had either a TIA or stroke in the distribution of the stenotic artery are defined as having asymptomatic carotid stenosis.

Carotid endarterectomy (CEA) is the only surgical intervention proven in randomized controlled trials (RCTs) to reduce the risk of stroke.

 Carotid artery stenting (CAS) is a newer, less invasive, percutaneous procedure that involves angioplasty of the carotid stenosis and placement of a stent to open the stenotic area.

 For persons with symptomatic severe (>70%) carotid stenosis, the absolute risk reduction for CEA is 17% over 2 years (8.5% per year).

 This translates to an annualized number-needed-to-treat (NNT) of about 12, among the lowest annualized NNT reported for any secondary stroke intervention. In other words, CEA is highly effective at reducing the risk of subsequent stroke and is recommended in the management of patients with symptomatic severe carotid stenosis. Carotid stenting has never been compared to medical therapy. However, a large RCT that compared carotid stenting to CEA showed that patients undergoing either procedure had similar rates of a primary outcome consisting of stroke, myocardial infarction, or death during the periprocedural period, or ipsilateral stroke within 4 years of randomization.

 A recent meta-analysis concluded that these procedures should be considered “complementary rather than competing modes of therapy” and patient selection may play a role in who would benefit from either modality of intervention.

Although a number of studies have examined the appropriate use of CEA among patients who have received intervention in the Medicare program,

 very few studies have examined the underuse of this procedure in patients with stroke—those who stand to benefit the most from revascularization. To our knowledge only 1 study, published more than 15 years ago, examined the use of carotid intervention in a cohort of veterans which demonstrated underuse of CEA in both symptomatic and asymptomatic populations.

Given the large and well-accepted clinical benefit in stroke reduction, the appropriate receipt of revascularization in this high-risk population is particularly of interest.

In this study, we examined the use of carotid intervention among patients with an acute ischemic stroke in the Veterans Health Administration (VA) and determined factors associated with receipt of intervention. We specifically hypothesized that access to vascular surgery services at the VA medical center (VAMC) where patients were admitted for the management of their stroke may be associated with receipt of intervention.

As part of the VA Stroke Special Study conducted in 2007, a multidisciplinary team with members drawn from the VA Office of Quality and Performance, the VA Stroke Quality Enhancement Research Initiative (QUERI), the VA Office of Patient Care Services, and the VA Office of Nursing Services was assembled to develop stroke quality measure specifications and to develop the data collection methodology. 

 Data from the VA Stroke Special Study pertaining to carotid imaging use was used in this study. Data on availability of carotid intervention services (CEA or CAS) was obtained from the National VA SAS databases. Data on receipt of carotid intervention in the Medicare program was obtained from the Medpar and physician supplier files. We examined whether any eligible veteran received CEA using 

) code 38.12 from the Medpar file and CPT code 35301 from outpatient data. Similarly, we identified patients who received CAS using 

 codes 00.61 and 00.63 and CPT codes 37215 and 37216 6 months post stroke in the Medicare program.

A national cohort of all veterans (N = 5721) admitted to a VAMC between October 1, 2006, and September 30, 2007, with a primary discharge diagnosis of ischemic stroke were identified from VA administrative data using a modified high specificity algorithm of 

 A sample of 5000 medical records was obtained by including all veterans at small-volume centers (≤55 patients in fiscal year 2007) and an 80% random sample of veterans at high-volume centers (>55 patients in fiscal year 2007). Trained nurse abstractors confirmed a diagnosis of ischemic stroke in 3987 patients and then proceeded with a chart review of 307 data elements among the confirmed patients. Data elements especially relevant to this study from chart review include results of carotid studies, receipt of carotid intervention, comorbid conditions, code status, and stroke characteristics. Inter-rater reliability was greater than 70% for over 90% of data elements.

Among the 3987 patients, 3014 received at least 1 carotid imaging test (

). We excluded the following patients: those with a code status of do not resuscitate/ do not intubate (N = 338) or who were discharged to hospice (N = 20), because these patients would likely be too ill to receive CEA or CAS; patients with posterior circulation stroke (N = 926) because the carotid stenosis would be classified as asymptomatic (see assessing side of stroke, below); patients who had atrial fibrillation (N = 280) because the original randomized controlled trials excluded such patients; and patients with missing data on carotid stenosis (N = 2). That left 1717 patients for the analyses.

The American Academy of Neurology recommends CEA for severe (70%-99%) symptomatic stenosis and considers CEA as only moderately useful for symptomatic patients with 50%-69% stenosis.

 Current guidelines do not recommend surgery for patients with less than 50% stenosis. 

Similarly, the American Heart Association and the American Stroke Association guideline recommends carotid intervention for patients at average or low surgical risk who experience nondisabling ischemic stroke or transient cerebral ischemic symptoms, within 6 months of the event, if the stenosis of the lumen of the ipsilateral internal carotid artery is more than 70% as documented by noninvasive imaging or more than 50% as documented by catheter angiography, and the anticipated rate of perioperative stroke or mortality is less than 6%.

 We considered patients appropriate for intervention if they had documented carotid stenosis between 50% and 99% and had had a stroke in the distribution of the carotid artery. Among the 1717 patients with data on carotid imaging, 388 had stenosis of 50%-99% in at least 1 artery. However, we only had data on side of stroke for 253 (65%) of these patients and could not conclusively evaluate underuse of carotid intervention in patients without data on the side of stroke. Therefore, the main sample for the analyses included 253 patients with documented severe carotid stenosis and a stroke in the distribution of the carotid artery (Figure).

The key outcome measure was not receiving guidelinerecommended carotid intervention within 6 months of hospital discharge for acute ischemic stroke for patients with severe symptomatic carotid stenosis. The main independent variables included age, race, stroke severity based on the retrospective National Institutes of Health (NIH) Stroke Scale, comorbid conditions, and availability of vascular surgery at the VAMC where the patient was admitted for stroke. Among the 130 hospitals in the VA, 84 hospitals have vascular surgery services.

Because the vast majority of patients (>76%) in the VA receive CEA as the method for carotid revascularization, and because a recent meta-analysis suggested CEA and CAS are comparable

, we examined the combined receipt of carotid intervention rather than these procedures separately. First, we determined the proportion of eligible patients who received carotid intervention in the VA. We also examined receipt of carotid intervention up to 6 months post stroke in the Medicare program for patients aged ≥65 years.

We then examined factors associated with guidelinerecommended receipt of carotid intervention, defined as a patient with significant stenosis on the same side as his or her stroke. Because the guidelines more strongly recommend receipt of intervention for those with severe stenosis (70%-99%),

 we limited the multivariable analyses to these patients. We ran bivariate tests between not having a CEA or stent and various explanatory factors. For continuous measures, we used 2 sample

-tests or Wilcoxon’s non-parametric 2-sample test. For binary factors, we used Fisher’s exact or χ

 square tests. Factors which were statistically significant at the 0.05 level were entered into a multivariable logistic regression model. We also included factors deemed clinically important such as age >75 years, severity on the NIH stroke scale

, Charlson comorbidity score, and whether or not the hospital of the patient’s stroke admission had access to a vascular surgeon. The logistic model was fit using generalized estimating equations techniques

 to accommodate the clustering of patients within hospitals. In a sensitivity analysis, we included patients for whom side of stroke data were missing, to examine whether factors associated with underuse of imaging were consistent across this larger sample. Analyses were conducted using SAS for Windows version 9.1 (SAS Institute, Cary, North Carolina).

Receipt of Carotid Intervention among Eligible Patients 

For patients with symptomatic severe (>70%) carotid stenosis carotid endarterectomy is highly effective at reducing the risk of subsequent stroke; however few eligible Veterans appear to be receiving this procedure.

July 2014

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