Long-Term Outcomes of a Cardiovascular and Diabetes Risk-Reduction Program Initiated by a Self-Insured Employer

June 2018 Vol 11, No 4 - Clinical, Original Research
Nicole D. White, PharmD, CDE
Associate Professor
Pharmacy Practice
Creighton University School of Pharmacy and Health Professions
Omaha, NE
Thomas L. Lenz, PharmD, FACLM
Professor
Pharmacy Practice
Creighton University School of Pharmacy and Health Professions
Omaha, NE
Maryann Z. Skrabal, PharmD, CDE
Associate Professor
Pharmacy Practice
Creighton University School of Pharmacy and Health Professions
Omaha, NE
Jessica J. Skradski, PharmD
Assistant Professor
Pharmacy Practice
Creighton University School of Pharmacy and Health Professions
Omaha, NE
Louis Lipari
PharmD candidate
Creighton University School of Pharmacy and Health Professions
Omaha, NE
Download PDF
Abstract

BACKGROUND: Cardiovascular disease remains the leading cause of death in America and poses a significant challenge for self-insured employers attempting to improve employee health and well-being while controlling healthcare costs. Disease state management programs can be an effective means of achieving these outcomes, but the durability and long-term effects of such programs have limited evaluation.

OBJECTIVE: To assess the 5-year health, economic, and quality-of-life patient outcomes of an employer-­sponsored disease state management program.

METHODS: This was a longitudinal, 5-year, quasi-experimental, pre-/postenrollment study. Self-insured health plan members with hypertension, hyperlipidemia, diabetes, or a combination of these conditions met with a pharmacist regularly (monthly for the first year, then varied by participant) to implement lifestyle medicine programs, optimize medication therapy, and facilitate the coordination of care. Biometric markers, lifestyle behaviors, quality of life, and work productivity were assessed on an annual basis.

RESULTS: The significant biometric improvements (mean) seen after 5 years of program participation compared with pre-enrollment included decreased low-density lipoprotein cholesterol levels (96.71 mg/dL vs 84.83 mg/dL, respectively), increased high-density lipoprotein cholesterol levels (39.32 mg/dL vs 46.12 mg/dL), and decreased systolic blood pressure (132.04 mm Hg vs 123.63 mm Hg) and diastolic blood pressure (85.75 mm Hg vs 75.83 mm Hg). The average exercise time increased (50 minutes weekly vs 156.04 minutes weekly), as did fruit and vegetable consumption (3.98 servings daily vs 5.27 servings daily). The program participants reported improved general health and a reduced number of unhealthy days. The combined healthcare and productivity return on investment for the program at 5 years was $9.64 for every $1 invested.

CONCLUSIONS: Significant changes in employees’ health, well-being, and health-related costs are possible through sustained participation in an employer-sponsored disease state management program.

Key Words: cardiovascular disease, cardiovascular risk, diabetes, disease management, employer-­sponsored program, healthcare cost, lifestyle behavior, quality of life, risk reduction, work productivity

Am Health Drug Benefits.
2018;11(4):177-183
www.AHDBonline.com

Manuscript received April 18, 2017
Accepted in final form October 3, 2017

Disclosures are at end of text

Cardiovascular disease (CVD) remains the leading cause of death in America, resulting in approximately 610,000 deaths each year.1 The prevalence of CVD in the United States is increasing. The American Heart Association projects that by 2030, approximately 40.5% of the US population will have CVD.2 The costs associated with the treatment of heart disease and other chronic conditions are increasing. In the previous decade, medical costs associated with CVD have increased by 6% annually, and currently comprise approximately 17% of the nation’s healthcare expenditure.2 People with chronic conditions report lower quality of life (QOL) and more unhealthy days compared with individuals without chronic disease.3 These statistics pose a significant challenge for employers attempting to control healthcare costs and improve productivity within their organization.

The Cardiovascular and Diabetes Risk-Reduction Program is a pharmacist-led disease management program designed to decrease the risk for expensive adverse health outcomes and improve the overall health, QOL, and productivity of employees of a self-insured employer. Health risk assessment data for the employer were used to determine the most common and costly conditions to target through program intervention, namely, CVD (ie, hypertension and dyslipidemia) and diabetes.

The program employs a pharmacist in the position of “ambulatist” in charge of daily operations and regular monthly check-ups with the participating employees. The ambulatist works in collaboration with an interprofessional care team consisting of a dietitian, exercise physiologist, health educator, licensed mental health provider, and the employee’s primary care physician and specialty physicians (ie, endocrinologist and/or cardiologist, if applicable).

Employees voluntarily enroll in the program with the incentive of receiving personalized health and wellness coaching and free medications on entry. Eligibility requirements include full-time employment with the program sponsor; a standing diagnosis of diabetes, hyperlipidemia, hypertension, or a combination of these; and currently receiving healthcare benefits from the employer.

The participants in the risk-reduction program attend regular (ie, at least once monthly in the first year, spread out to no less than quarterly as control of conditions is established) one-on-one appointments with a pharmacist. The visits consist of medication therapy management, implementation and adherence to 7 personalized lifestyle medicine programs (ie, physical activity, healthy eating, stress management, restorative sleep, moderate alcohol consumption, tobacco abstinence/cessation, and weight control), and chronic disease care coordination practices.

To achieve the highest level of program adherence and success, each participant is provided with educational materials, a home blood pressure monitor, a pedometer, lifestyle behavior tracking tools, free access to employer exercise facilities, monthly support group meetings, and access to a licensed mental healthcare provider. In addition, employees with diabetes received an initial consultation with a dietitian, 6 hours of American Diabetes Association–approved education classes, and access to point-of-care glycated hemoglobin (HbA1c) analyses as appropriate.

The program was initiated in the fall of 2008 at a private Midwestern university, and is offered at no charge to all eligible employees. The health effects of program participation were assessed after 1 year of participation and have been reported previously.4-7 Specifically, the 1-year health-related QOL (HRQoL) improved by 20.6% (P <.001), and the number of self-reported unhealthy days (physical and mental) decreased by 42.5% (P <.01). Cardiovascular risk (ie, general 10-year) decreased by 2.02% (P = .017), and a correlated heart and vascular age estimation decreased by 2.7 years (P = .004). Participation in the lifestyle medicine activities of exercise, fruit and vegetable intake, and stress reduction significantly improved (P <.01). Medication adherence improved 15% (P <.001), and the financial return on investment (ROI) was $4.02:$1. The current study aims to assess the durability of these outcomes based on additional data representing 5 years of program intervention.

Methods
The risk-reduction program began enrollment in August 2008. At baseline and annually thereafter for the next 5 years, the participants were assessed for changes in biometric data (ie, weight, waist circumference, blood pressure, lipid panel, HbA1c), lifestyle habits (ie, tobacco use, physical activity, fruit and vegetable intake, sleep quantity, stress rating), HRQoL, and productivity.

Contemporary methods of measurement were utilized to obtain outcomes data. Employee self-reported HRQoL is measured using a validated survey tool from the Centers for Disease Control and Prevention.8 This survey tool has been used since 1993 to measure HRQoL in the Behavior Risk Factor Surveillance System, and since 2000 in the National Health and Nutrition Examination Survey.8 The 4-question survey assesses self-reported general health and the number of physically and mentally unhealthy days experienced in the past month.

Cardiovascular risk was calculated using the general CVD (10-year risk) calculator developed by the Framingham Heart Study.9 This tool predicts the risk for experiencing one of several CVD outcomes (ie, coronary death, myocardial infarction, coronary insufficiency, angina, ischemic stroke, hemorrhagic stroke, transient ischemic attack, peripheral arterial disease, or heart failure) within the next 10 years. The tool can also be used to estimate heart and vascular age. The variables that are used in the calculation include age, sex, systolic blood pressure, treatment for hypertension, smoking status, diabetes diagnosis, high-density lipoprotein (HDL) cholesterol, and total cholesterol.

Lifestyle habits were collected via participant self-reporting in a lifestyle journal that was provided to each participant by the program.10 The participants use the journal to regularly track their amount of exercise, fruit and vegetable consumption, stress rating, amount of sleep, alcohol consumption, and tobacco use (in addition to other measures). The participants were required to track these behaviors regularly, and the lifestyle journal was reviewed at each monthly visit.

Work productivity was assessed in the study through the use of the Work Productivity and Activity Impairment questionnaire for general health.11 This validated tool tracks time away from work (ie, absenteeism), as well as decreased job performance while at work (ie, presenteeism).11

Finally, the ROI analysis was completed by a third-­party company, Health Improvement Solutions.12 The Health Improvement Solutions ROI calculator helps to determine the effectiveness of programs by evaluating cost-savings from risk reduction and program investment within the organization. The tool uses medical and productivity risk factor costs identified through a combination of research and an extensive proprietary risk factor cost database. Along with risk prevalence, Health Improvement Solutions includes program costs, such as staffing, administrative fees, consulting, and other investment costs. The median annual compensation is used to determine the health-related work productivity portion of the ROI. The program’s ROI is provided in 4 outputs: medical only, absenteeism only, presenteeism only, and overall ROI (medical and productivity combined).

Statistical Analysis
A statistical analysis was completed using the Wilcoxon signed-rank test as a nonparametric test to compare the median difference between the baseline and 5-year time points. A P value of <.05 was considered statistically significant. Descriptive analyses were also used to compare the number and percentage of employees participating in each of the lifestyle medicine activities.

Results
As of May 2016, 25 employees had completed at least 5 years of program participation and were included for assessment in the current study. The participants’ baseline data are described in Table 1.

Table 1

After 5 years of program intervention, significant improvements were achieved in various biometric measures. Specifically, reductions in low-density lipoprotein (LDL) and non-HDL cholesterol, as well as systolic and diastolic blood pressure, were demonstrated. A significant increase in HDL was observed. Cholesterol changes in the participants’ biometric measures are summarized in Table 2.

Table 2

Several lifestyle medicine–related cardiovascular risk factors were also significantly improved. The participants’ exercise time increased, as did their fruit and vegetable consumption. Furthermore, stress levels were measured on a scale of 1 to 5, with 1 indicating low stress (ie, feeling calm and in control), 3 indicating moderate stress, and 5 indicating high stress (ie, feeling frantic and out of control), and the participants’ scores decreased significantly. Changes in participant lifestyle behavior are summarized in Table 2.

The program participants reported a significantly better general health rating after 5 years of participation, using a simple rating scale (1 = excellent, 2 = very good, 3 = good, 4 = fair, 5 = poor). Similarly, participants reported statistically significant changes in the average number of unhealthy days they experienced in 1 month. The changes in participant-reported HRQoL are summarized in Table 3.

Table 3

The healthcare cost ROI for the 5-year cohort was 3.85:1 across the 5-year period. When looking at the ROI for productivity, the ratio was 1.36:1 for absenteeism, 4.43:1 for presenteeism, and 5.79:1 for total productivity (ie, absenteeism plus presenteeism). When healthcare and productivity savings were combined, the ROI was $9.64:$1, meaning that over the 5 years of program participation, this cohort eliminated health risks that led to a savings of $9.64 for every $1 invested in their health through the program. The Figure depicts the results from the 5-year ROI analysis.

Figure

Discussion

The participants in the risk-reduction program displayed various improvements in health, well-being, and work productivity after 5 years. Improvements in HRQoL, exercise, and fruit and vegetable intake, as well as in financial ROI, were demonstrated after 1 year of program participation and were durable after 5 years of follow-up.

Statistically significant improvements in LDL cholesterol, HDL and non-HDL cholesterol, as well as systolic and diastolic blood pressure, were demonstrated at the 5-year follow-up, but not after 1 year. This may suggest that the benefits of sustained lifestyle modification (ie, increased physical activity, improved nutrition) may require more than 1 year to manifest.

In addition to the significant findings previously mentioned, the risk-reduction program also showed considerable noteworthy improvements in health that were not statistically significant. For example, the average body weight decreased slightly (from 212.12 lbs at baseline to 209.71 lbs after 5 years). These findings, although not statistically significant, are noteworthy, considering that the average person gains approximately 3.35 pounds over a 4-year period.13

Another notable example includes the decrease in cardiovascular risk and heart age. After 5 years, the program participants displayed a decrease in calculated heart age from an average of 64.56 years to 62.56 years and a decrease in the calculated 10-year general CVD risk from 14.25% to 12.67%. Although neither reduction was statistically significant, both calculations are highly influenced by age and would therefore tend to increase over the course of 5 years.

Finally, participants in the risk-reduction program are more likely to meet disease and lifestyle behavior targets after participating in the program for 5 years. The changes in the achievement of guideline-based treatment goals are described in Table 4.14-19

Table 4

Limitations

These findings are limited by the small sample size and the noncontrolled study design.

Additional limitations include the volunteer status of participants and reliance on self-reported data. Individuals who actively seek out such programs are likely more inclined to make changes and adhere to therapy than the population as a whole.

Furthermore, lifestyle behavior data were obtained from a self-reported lifestyle journal.

The ROI data are uncharacteristically high compared with other disease management programs that have been published.20,21 The authors attempted to be as conservative as possible with the data included in the calculation and felt that having a third-party company perform the calculation was best to calculate an accurate assessment of ROI.

Conclusions

The results of the current study suggest that participation in a cardiovascular and diabetes risk-reduction program may improve participants’ health, QOL, and productivity, while saving money for self-insured employers. Improvements in HRQoL, exercise, fruit and vegetable consumption, and financial ROI were evident after 1 year of participation and were maintained or further improved after 5 years of program participation.

Notably, statistically significant improvements in LDL, HDL and non-HDL cholesterol, as well as systolic and diastolic blood pressure, although not observed after 1 year of follow-up, were demonstrated at the 5-year follow-up. These results suggest that sustained participation in such a program has durable and additional benefits lasting during and after program participation. These outcomes support the long-term administration of such employer-based programs.

Author Disclosure Statement
Dr White, Dr Lenz, Dr Skrabal, Dr Skradski, and Mr Lipari reported no conflicts of interest.

References
1. Centers for Disease Control and Prevention. Heart disease facts. Updated November 28, 2017. www.cdc.gov/heartdisease/facts.htm. Accessed May 9, 2018.
2. Heidenreich PA, Trogdon JG, Khavjou OA, et al. Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation. 2011;123:933-944.
3. Zahran HS, Kobau R, Moriarty DG, et al. Health-related quality of life surveillance—United States, 1993–2002. MMWR Surveill Summ. 2005;54:1-35.
4. Lenz TL, Gillespie ND, Skrabal MZ, et al. Health-related quality of life impact in employees participating in a pharmacist-run risk reduction program. Innov Pharm. 2012;3:Article 94.
5. Lenz TL, Gillespie ND, Faulkner MA, et al. Lifestyle medicine-related cardiovascular risk factor changes in employees participating in a pharmacist-run risk reduction program. Innov Pharm. 2012;3:Article 93.
6. McKenzie MC, Lenz TL, Gillespie ND, Skradski JJ. Medication adherence improvements in employees participating in a pharmacist-run risk reduction program. Innov Pharm. 2012;3:Article 92.
7. White ND, Lenz TL, Skrabal MZ, et al. Comparison of cardiovascular risk calculation tools in pharmacy practice. J Am Pharm Assoc (2003). 2013;53:408-413.
8. Centers for Disease Control and Prevention. CDC HRQOL-14 “Healthy Days Measure.” Updated October 30, 2017. www.cdc.gov/hrqol/hrqol14_measure.htm. Accessed March 17, 2017.
9. D’Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008;117:743-753. Erratum in: Circulation. 2008;118:e86.
10. Lenz TL. LIFESTYLE Journal. Omaha, NE: Prevention; 2009 [Discontinued].
11. Reilly MC, Zbrozek AS, Dukes EM. The validity and reproducibility of a work productivity and activity impairment instrument. Pharmacoeconomics. 1993;4:353-365.
12. Health Improvement Solutions. Analysis and planning. www.healthimprovementsolutions.com/analysis-and-planning. Accessed March 17, 2017.
13. Mozaffarian D, Hao T, Rimm EB, et al. Changes in diet and lifestyle and long-term weight gain in women and men. N Engl J Med. 2011;364:2392-2404.
14. James PA, Oparil S, Carter BL, et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA. 2014;311:507-520. Erratum in: JAMA. 2014;311:1809.
15. American Diabetes Association. Standards of Medical Care in Diabetes—2017. Diabetes Care. 2017;40(suppl 1):S1-S135.
16. Jacobson TA, Ito MK, Maki KC, et al. National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1-executive summary. J Clin Lipidol. 2014;8:473-488.
17. Centers for Disease Control and Prevention. About adult BMI. Updated August 29, 2017. www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/. Accessed May 14, 2018.
18. US Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans. ODPHP Publication No U0036. October 2008. https://health.gov/paguidelines/pdf/paguide.pdf. Accessed April 7, 2017.
19. US Department of Health and Human Services; US Department of Agriculture. 2015-2020 Dietary Guidelines for Americans. 8th ed. December 2015. https://health.gov/dietaryguidelines/2015/resources/2015-2020_Dietary_Guidelines.pdf. Accessed April 7, 2017.
20. Bunting BA, Lee G, Knowles G, et al. The Hickory Project: controlling healthcare costs and improving outcomes for diabetes using the Asheville Project model. Am Health Drug Benefits. 2011;4(6):343-350.
21. Bunting BA, Nayyar D, Lee C. Reducing health care costs and improving clinical outcomes using an improved Asheville Project model. Innov Pharm. 2015;6:Article 227.

Stakeholder Perspective
Influencing Patient Outcomes Through Enhanced Multidisease-Focused Interventions
Jack E. Fincham, PhD, RPh
Professor
Department of Pharmaceutical
and Administrative Sciences
Presbyterian College
School of Pharmacy
Clinton, SC

PATIENTS: The impact of chronic diseases on patients is amplified significantly through the presence of comorbidities. In addition to clinical considerations, the impact on quality of life (QOL) and cost of care are consequential. An update on cardiovascular disease (CVD) and type 2 diabetes from the American Heart Association and American Diabetes Association (ADA) indicates that the prevalence of these comorbidities has increased substantially recently.1 The economic, clinical, and QOL outcomes of these comorbid diseases have and will continue to affect patients, caregivers, payers, and society at large.

Estimates from the IQVIA Institute for Human Data Science suggest that the largest drivers of prescription drug use are the treatment of chronic diseases.2 According to this 2016 analysis, the use of antihypertension treatments increased by 40.6 million, and use of anti­diabetes agents increased by 16.3 million.2 This report projects a 2% to 5% increase in spending for prescription drugs by 2021.2 Considering the importance of CVD and diabetes, the ADA has recommended, “a patient-centered communication style that uses active listening, elicits patient preferences and beliefs, and assesses literacy, numeracy, and potential barriers to care…to optimize patient health outcomes and health-related quality of life.”3

This comorbidity has ramifications globally as well. In the Netherlands, approximately 1 in 4 patients now has at least 1 form of CVD, often with comorbid diabetes.4

PHARMACISTS/PAYERS: With the growing prevalence of chronic comorbidities, differing methods of comprehensive care provision, including the concept of “health coaching,” have been suggested to enhance patient outcomes.5 Chronic disease, which often results from poor lifestyle decision-making, has been suggested as a primary cause of death and disability in the United States. The US coaching industry has certified thousands of individuals annually, and health coaching is one component of this industry.5

Pharmacy is among the health professions that are viewing health coaching for professional certification considerations. The addition of pharmacists to primary care teams enhances cost-effective treatments, by improving blood pressure control and reducing the 10-year cardiovascular risk in patients with type 2 diabetes.6 The article by White and colleagues is a good example of this approach, as demonstrated in their pharmacists-driven long-term disease management program that resulted in significant and sustained improvements in health and reduced costs among plan members with CVD and diabetes.7

A pilot study in Australia included a process evaluation and implementation plan for incorporating pharmacists, with nondispensing roles, into general practice settings for patient recruitment and selection, pharmacist­patient consultations, and implementing pharmacists’ recommendation. The study was effective for patients and for the general practice care team.8

In Canada, the development of plans for the reimbursement of pharmacists to provide enhanced services has shown positive clinical and economic outcomes.9 This plan implementation incorporated extensive input from other health professionals in addition to pharmacists to meet the unmet needs of isolated and undertreated patients in Alberta, Canada.9

In Peru, pharmacies have been used to improve population health outcomes in patients with hypertension and diabetes; patient satisfaction assessments indicated willingness to seek additional health services from these pharmacies.10

As White and colleagues show, with the increase in patient populations with multiple comorbidities, such as CVD and diabetes, enhancing health services provisions through different professional expertise, including pharmacists, can potentially be a successful option for enhancing patient care.

A particularly interesting finding in the study by White and colleagues was the long-term impact of their pharmacist intervention, showing significant improvements in cholesterol levels after 5-year participation in the program, although not after 1 year only. The implications of this finding merit further study.

1. Fox CS, Golden SH, Anderson C, et al. Update on prevention of cardiovascular disease in adults with type 2 diabetes mellitus in light of recent evidence: a scientific statement from the American Heart Association and the American Diabetes Association. Circulation. 2015;132:691-718.
2. Aitken M, Kleinrock M. Medicines Use and Spending in the U.S.: A Review of 2016 and Outlook to 2021. IQVIA Institute for Human Data Science; May 2017. www.iqvia.com/-/media/iqvia/pdfs/institute-reports/medicines-use-and-spending-in-the-us.pdf?_=1527804838938. Accessed June 1, 2018.
3. American Diabetes Association. 3. Comprehensive medical evaluation and assessment of comorbidities. Diabetes Care. 2017;40(suppl 1):S25-S32. Erratum in: Diabetes Care. 2017;40:985.
4. Kendir C, van den Akker M, Vos R, Metsemakers J. Cardiovascular disease patients have increased risk for comorbidity: a cross-sectional study in the Netherlands. Eur J Gen Pract. 2018;24:45-50.
5. Sforzo GA. The study of health coaching: the Ithaca Coaching Project, research design, and future directions. Glob Adv Health Med. 2013;2:58-64.
6. Simpson SH, Lier DA, Majumdar SR, et al. Cost-effectiveness analysis of adding pharmacists to primary care teams to reduce cardiovascular risk in patients with type 2 diabetes. Diabet Med. 2015;32:899-906.
7. White ND, Lenz TL, Skrabal MZ, et al. Long-term outcomes of a cardiovascular and diabetes risk-reduction program initiated by a self-insured employer. Am Health Drug Benefits. 2018;11(4):177-183.
8. Benson H, Sabater-Hernández D, Benrimoj S, Williams KA. Piloting the integration of non-dispensing pharmacists in the Australian general practice setting. Int J Integr Care. 2018;18:Article 4.
9. Breault RR, Whissell JG, Hughes CA, Schindel TJ. Development and implementation of the compensation plan for pharmacy services in Alberta, Canada. J Am Pharm Assoc (2003). 2017;57:532-541.
10. Vodicka E, Antiporta DA, Yshii Y, et al. Patient acceptability of and readiness-to-pay for pharmacy-based health membership plans to improve hypertension outcomes in Lima, Peru. Res Social Adm Pharm. 2017;13:589-601.

Related Items
Trends in Utilization, Spending, and Prices of Smoking-Cessation Medications in Medicaid Programs: 25 Years Empirical Data Analysis, 1991-2015
Xiaomeng Yue, MS, BPharm, Jeff Jianfei Guo, MS, BPharm, PhD, Patricia R. Wigle, PharmD
September 2018 Vol 11, No 6 published on October 15, 2018 in Original Research, Regulatory
Analysis of Real-World Dosing Patterns for the 3 FDA-Approved Medications in the Treatment of Fibromyalgia
Craig White, PhD, Winghan Jacqueline Kwong, PharmD, PhD, Hilary Armstrong, PhD, Michael Behling, Research Associate, Jeffrey Niemira, Senor Statistician, Kathy Lang, PhD
September 2018 Vol 11, No 6 published on October 15, 2018 in Clinical, Original Research
Estimating the Real-World Cost of Diabetes Mellitus in the United States During an 8-Year Period Using 2 Cost Methodologies
Vincent J. Willey, PharmD, Sheldon Kong, PhD, Bingcao Wu, MS, Amit Raval, PhD, Todd Hobbs, MD, Andrea Windsheimer, PharmD, Gaurav Deshpande, MS, PhD, Ozgur Tunceli, PhD, Brian Sakurada, PharmD, Jonathan R. Bouchard, MS, RPh
September 2018 Vol 11, No 6 published on October 15, 2018 in Business, Original Research
Assessing the Level of Patient-Specific Treatment Recommendations in Clinical Practice Guidelines for Hemodialysis Vascular Access in the United States
Gilbert L. Queeley, PhD, Ellen S. Campbell, PhD, Askal A. Ali, PhD
July 2018 Vol 11, No 5 published on July 20, 2018 in Clinical, Original Research
The Prevalence and Payer Costs of Potentially Avoidable Emergent Care Visits for Suspected Amniotic Membrane Rupture in Pregnant Women
Christine Ferro, CHFP, Bruce S. Pyenson, FSA, MAAA, Jocelyn Lau, MPH, Mona Kelkar, MBA, Nancy Phillips, MD, Chi-Wei Lu, PhD, Percy Yeung, PhD, Gloria Bachmann, MD
July 2018 Vol 11, No 5 published on July 20, 2018 in Business, Original Research
Last modified: July 2, 2018
  •  Association for Value-Based Cancer Care
  • Value-Based Cancer Care
  • Value-Based Care in Rheumatology
  • Oncology Practice Management
  • Rheumatology Practice Management
  • Urology Practice Management
  • Inside Patient Care: Pharmacy & Clinic
  • Lynx CME