Engaging stakeholders in the research process has the potential to improve quality of care and the patient care experience.Online patient community surveys can elicit important topic areas for comparative effectiveness research.Stakeholder meetings with substantial patient representation, as well as representation from health care delivery systems and research funding agencies, are a valuable tool for selecting and refining pilot research and quality improvement projects.Giving patient stakeholders a deciding vote in selecting pilot research topics helps ensure their ‘voice’ is heard.Researchers and health care leaders should continue to develop best-practices and strategies for increasing patient involvement in comparative effectiveness and delivery science research.
stakeholder engagement; diabetes; patient engagement; comparative effectiveness research
Examining trends in cardiovascular events (CVE) and mortality in U.S. health systems can guide the design of targeted clinical and public health strategies to reduce CVE and mortality rates.
Methods and Results
We conducted an observational cohort study from 2005–2011 among 1.25 million diabetic subjects and 1.25 million nondiabetic subjects from 11 health systems that participate in the SUrveillance, PREvention and ManagEment of Diabetes Mellitus (SUPREME-DM) DataLink. Annual rates (per 1000 person-years) of myocardial infarction/acute coronary syndrome (MI/ACS; ICD-9 410.0–410.91, 411.1–411.8), stroke (ICD-9 430–432.9, 433–434.9), heart failure (HF; ICD-9 428–428.9), and all-cause mortality were monitored by diabetes status, age, sex, race/ethnicity, and a prior CV history.
We observed significant declines in CVE and mortality rates in subjects with and without diabetes. However, there was substantial variation by age, sex, race/ethnicity, and prior CV history. Mortality declined from 44.7 to 27.1 (p<.0001) for those with DM and CVD, from 11.2 to 10.9 (p=.03) for those with DM only, and from 18.9 to 13.0 (p<.0001) for those with CVD only. Yet, in the approximately 85% of subjects with neither DM nor CVD, overall mortality (7.0 to 6.8; p=.10) and stroke rates (1.6 to 1.6; p=.77) did not decline and HF rates increased (0.9 to 1.15; p=.0005).
To sustain improvements in MI, stroke, HF, and mortality, health systems that have successfully focused on care improvement in high risk adults with diabetes and/or CVD must broaden their improvement strategies to target lower risk adults who have not yet developed diabetes or CVD.
diabetes mellitus; myocardial infarction; stroke; heart failure; public health surveillance
Pulmonary fibrosis (PF) is a rare, progressive disease that affects patients and their loved ones on many levels. We sought to better understand the needs and interests of PF patients and their loved ones (collectively “reader-participants”) by systematically analyzing their engagement with the World Wide Web (the current version referred to as Web 2.0).
Data were collected from three PF-focused, interactive websites hosted by physician-investigators with expertise in PF. All data generated by reader-participants for approximately 10 months were downloaded and then analyzed using qualitative content analysis methods.
PF experts posted 38 blog entries and reader-participants posted 40 forum entries. Blogs received 363 responses, and forum entries received 108 responses from reader-participants. Reader-participants primarily used the three websites to seek information from or offer a contribution to the PF community. Information was sought about PF symptoms, diagnosis, prognosis, treatments, research, pathophysiology, and disease origin; reader-participants also made requests for new posts and pleas for research and sought clarification on existing content. Contributions included personal narratives about experiences with PF, descriptions of activities or behaviors found to be helpful with PF symptoms, resources or information about PF, and supportive comments to other PF sufferers.
PF patients and their loved ones engage the Web 2.0 environment at these PF-focused sites to satisfy their needs to better understand PF and its impacts and to support others facing similar challenges. Clinicians may find it beneficial to encourage PF patients’ involvement in internet forums that foster dynamic, bi-directional information sharing.
Electronic supplementary material
The online version of this article (doi:10.1186/s12890-016-0167-7) contains supplementary material, which is available to authorized users.
Pulmonary fibrosis; Internet; Web forum; Online health information; Blog; Caregiver
The objective of this study was to assess the incidence of major cardiovascular (CV) hospitalization events and all-cause deaths among adults with diabetes with or without CV disease (CVD) associated with inadequately controlled glycated hemoglobin (A1C), high LDL cholesterol (LDL-C), high blood pressure (BP), and current smoking.
RESEARCH DESIGN AND METHODS
Study subjects included 859,617 adults with diabetes enrolled for more than 6 months during 2005–2011 in a network of 11 U.S. integrated health care organizations. Inadequate risk factor control was classified as LDL-C ≥100 mg/dL, A1C ≥7% (53 mmol/mol), BP ≥140/90 mm Hg, or smoking. Major CV events were based on primary hospital discharge diagnoses for myocardial infarction (MI) and acute coronary syndrome (ACS), stroke, or heart failure (HF). Five-year incidence rates, rate ratios, and average attributable fractions were estimated using multivariable Poisson regression models.
Mean (SD) age at baseline was 59 (14) years; 48% of subjects were female, 45% were white, and 31% had CVD. Mean follow-up was 59 months. Event rates per 100 person-years for adults with diabetes and CVD versus those without CVD were 6.0 vs. 1.7 for MI/ACS, 5.3 vs. 1.5 for stroke, 8.4 vs. 1.2 for HF, 18.1 vs. 40 for all CV events, and 23.5 vs. 5.0 for all-cause mortality. The percentages of CV events and deaths associated with inadequate risk factor control were 11% and 3%, respectively, for those with CVD and 34% and 7%, respectively, for those without CVD.
Additional attention to traditional CV risk factors could yield further substantive reductions in CV events and mortality in adults with diabetes.
The Patient Outcomes Research to Advance Learning (PORTAL) Network was established with funding from the Patient-Centered Outcomes Research Institute (PCORI) in 2014. The PORTAL team adapted governance structures and processes from past research network collaborations. We will review and outline the structures and processes of the PORTAL governance approach and describe how proactively focusing on priority areas helped us to facilitate an ambitious research agenda.
For years a variety of funders have supported large-scale infrastructure grants to promote the use of clinical datasets to answer important comparative effectiveness research (CER) questions. These awards have provided the impetus for health care systems to join forces in creating clinical data research networks. Often, these scientific networks do not develop governance processes proactively or systematically, and address issues only as problems arise. Even if network leaders and collaborators foresee the need to develop governance approaches, they may underestimate the time and effort required to develop sound processes. The resulting delays can impede research progress.
Because the PORTAL sites had built trust and a foundation of collaboration by participating with one another in past research networks, essential elements of effective governance such as guiding principles, decision making processes, project governance, data governance, and stakeholders in governance were familiar to PORTAL investigators. This trust and familiarity enabled the network to rapidly prioritize areas that required sound governance approaches: responding to new research opportunities, creating a culture of trust and collaboration, conducting individual studies, within the broader network, assigning responsibility and credit to scientific investigators, sharing data while protecting privacy/security, and allocating resources. The PORTAL Governance Document, complete with a Toolkit of Appendices is included for reference and for adaptation by other networks.
As a result of identifying project-based governance priorities (IRB approval, subcontracting, selection of new research including lead PI and participating sites, and authorship) and data governance priorities (reciprocal data use agreement, analytic plan procedures, and other tools for data governance), PORTAL established most of its governance structure by Month 6 of the 18 month project. This allowed science to progress and collaborators to experience first-hand how the structures and procedures functioned in the remaining 12 months of the project, leaving ample time to refine them and to develop new structures or processes as necessary.
The use of procedures and processes with which participating investigators and their home institutions were already familiar allowed project and regulatory requirements to be established quickly to protect patients, their data, and the health care systems that act as stewards for both. As the project progressed, PORTAL was able to test and adjust the structures it put place, and to make substantive revisions by Month 17. As a result, priority processes have been predictable, transparent and effective.
Strong governance practices are a stewardship responsibility of research networks to justify the trust of patients, health plan members, health care delivery organizations, and other stakeholders. Well-planned governance can reduce the time necessary to initiate the scientific activities of a network, a particular concern when the time frame to complete research is short. Effective network and data governance structures protect patient and institutional data as well as the interests of investigators and their institutions, and assures that the network has built an environment to meet the goals of the research.
Governance; Comparative Effectiveness Research; Research Networks; Patient-Centered Outcomes Research
An observational cohort analysis was conducted within the Surveillance, Prevention, and Management of Diabetes Mellitus (SUPREME-DM) DataLink, a consortium of 11 integrated health-care delivery systems with electronic health records in 10 US states. Among nearly 7 million adults aged 20 years or older, we estimated annual diabetes incidence per 1,000 persons overall and by age, sex, race/ethnicity, and body mass index. We identified 289,050 incident cases of diabetes. Age- and sex-adjusted population incidence was stable between 2006 and 2010, ranging from 10.3 per 1,000 adults (95% confidence interval (CI): 9.8, 10.7) to 11.3 per 1,000 adults (95% CI: 11.0, 11.7). Adjusted incidence was significantly higher in 2011 (11.5, 95% CI: 10.9, 12.0) than in the 2 years with the lowest incidence. A similar pattern was observed in most prespecified subgroups, but only the differences for persons who were not white were significant. In 2006, 56% of incident cases had a glycated hemoglobin (hemoglobin A1c) test as one of the pair of events identifying diabetes. By 2011, that number was 74%. In conclusion, overall diabetes incidence in this population did not significantly increase between 2006 and 2010, but increases in hemoglobin A1c testing may have contributed to rising diabetes incidence among nonwhites in 2011.
diabetes mellitus; glycated hemoglobin; hemoglobin A1c; incidence; trends
Cardiovascular disease is a major cause of morbidity and mortality for women and men with diabetes. Previous cross-sectional studies of prevalent diabetes have found that women are less likely to meet ADA and AHA guidelines for control of cardiovascular risk factors (hemoglobin A1c, LDL cholesterol, and blood pressure), but have not studied the critical period immediately after diagnosis.
To assess gender differences in cardiovascular risk factors at the time of diabetes diagnosis (baseline) and one year later (follow-up), we conducted a retrospective cohort study of 6,547 individuals with incident diabetes in an integrated care delivery system. We assessed mean cardiovascular risk factor values by gender and adjusted odds ratios of attaining ADA goals.
Compared with men, at baseline women had lower hemoglobin A1c (7.9% vs. 8.2%, P<0.001), higher LDL cholesterol (118.9 vs. 111.5 mg/dL, P < 0.001), higher systolic blood pressure (131.9 vs. 130.5 mmHg, P<0.001), and lower diastolic blood pressure (79.1 vs. 79.7 mmHg, P=0.006). At follow-up, the hemoglobin A1c gender gap had closed (6.9% vs. 6.9%, P=0.39), and the gender gaps had decreased for blood pressure (129.8/77.0 vs. 128.9/77.6, P=0.009) and LDL cholesterol (104.0 vs 98.2 mg/dL, P<0.001). These associations varied by age. Adjusted odds ratios showed similar relationships.
In this cohort of individuals with incident diabetes, men and women had important differences in risk factor control at the time of diabetes diagnosis. These differences varied by age, and decreased over time.
Funding agencies and researchers increasingly recognize the importance of patient stakeholder engagement in research. Despite calls for greater patient engagement, few studies have engaged a broad-based online community of patient stakeholders in the early stages of the research development process.
The objective of our study was to inform a research priority-setting agenda by using a Web-based survey to gather perceptions of important and difficult aspects of diabetes care from patient members of a social networking site-based community.
Invitations to participate in a Web-based survey were sent by email to members of the PatientsLikeMe online diabetes community. The survey asked both quantitative and qualitative questions addressing individuals’ level of difficulty with diabetes care, provider communication, medication management, diet and exercise, and relationships with others. Qualitative responses were analyzed using content analysis.
Of 6219 PatientsLikeMe members with diabetes who were sent survey invitations, 1044 (16.79%) opened the invitation and 320 (5.15% of 6219; 30.65% of 1044) completed the survey within 23 days. Of the 320 respondents, 33 (10.3%) reported having Type 1 diabetes; 107 (33.4%), Type 2 diabetes and taking insulin; and 180 (56.3%), Type 2 diabetes and taking oral agents or controlling their diabetes with lifestyle modifications. Compared to 2005-2010 National Health and Nutrition Examination Survey data for individuals with diabetes, our respondents were younger (mean age 55.8 years, SD 9.9 vs 59.4 years, SE 0.5); less likely to be male (111/320, 34.6% vs 48.4%); and less likely to be a racial or ethnic minority (40/312, 12.8% vs 37.5%). Of 29 potential challenges in diabetes care, 19 were categorized as difficult by 20% or more of respondents. Both quantitative and qualitative results indicated that top patient challenges were lifestyle concerns (diet, physical activity, weight, and stress) and interpersonal concerns (trying not to be a burden to others, getting support from family/friends). In our quantitative analysis, similar concerns were expressed across patient subgroups.
Lifestyle and interpersonal factors were particularly challenging for our online sample of adults with Type 1 or Type 2 diabetes. Our study demonstrates the innovative use of social networking sites and online communities to gather rapid, meaningful, and relevant patient perspectives that can be used to inform the development of research agendas.
social networking; diabetes mellitus; quality of health care; patient centered outcome research
Medication nonadherence is a major obstacle to better control of glucose, blood pressure (BP), and LDL cholesterol in adults with diabetes. Inexpensive effective strategies to increase medication adherence are needed.
RESEARCH DESIGN AND METHODS
In a pragmatic randomized trial, we randomly assigned 2,378 adults with diabetes mellitus who had recently been prescribed a new class of medication for treating elevated levels of glycated hemoglobin (A1C) ≥8% (64 mmol/mol), BP ≥140/90 mmHg, or LDL cholesterol ≥100 mg/dL, to receive 1) one scripted telephone call from a diabetes educator or clinical pharmacist to identify and address nonadherence to the new medication or 2) usual care. Hierarchical linear and logistic regression models were used to assess the impact on 1) the first medication fill within 60 days of the prescription; 2) two or more medication fills within 180 days of the prescription; and 3) clinically significant improvement in levels of A1C, BP, or LDL cholesterol.
Of the 2,378 subjects, 89.3% in the intervention group and 87.4% in the usual-care group had sufficient data to analyze study outcomes. In intent-to-treat analyses, intervention was not associated with significant improvement in primary adherence, medication persistence, or intermediate outcomes of care. Results were similar across subgroups of patients defined by age, sex, race/ethnicity, and study site, and when limiting the analysis to those who completed the intended intervention.
This low-intensity intervention did not significantly improve medication adherence or control of glucose, BP, or LDL cholesterol. Wide use of this strategy does not appear to be warranted; alternative approaches to identify and improve medication adherence and persistence are needed.
Despite consensus that mentorship is a critical determinant of career success, many academic health centers do not provide formal training for their mentors. In part, this problem arises from a lack of evidence-based mentorship training curricula. In this issue of Academic Medicine, Pfund and colleagues from sixteen Clinical Translational Science Award (CTSA) institutions report the results of a randomized, controlled trial (RCT) that addressed this research gap. In their study, mentors randomized to undertake a formal mentoring curriculum reported significant gains in self-assessed competencies. These improvements were corroborated by the most critical and objective observers of mentorship skills: their own mentees.
Evidence-based curricula will not transform research mentorship in isolation. An organization-wide culture of mentorship is necessary to meet the mentorship needs of all research trainees and faculty. The development of a culture of mentorship requires attention to structural issues such as the provision of protected time, physical resources, and targeted funding in addition to evidence-based curricula. Organizations must monitor the implementation of these structures in the day-to-day process of mentorship. Finally, institutions must develop measures to track outcomes for both mentors and mentees, and create incentives to achieve those outcomes. In the current environment of constrained research funding and competing demands from clinical and educational programs, a substantive organizational commitment to mentorship is necessary to assure that the next generation of mentees achieves success in translational research.
The Centers for Medicare and Medicaid Services (CMS) recently added medication adherence to antihypertensives, antihyperlipidemics, and oral antihyperglycemics to its Medicare STAR quality measures. These CMS metrics exclude patients with <2 medication fills (i.e. “early non-adherence”) and patients concurrently taking insulin. This study examined the proportion of diabetes patients prescribed cardiovascular disease (CVD) medications excluded from STAR adherence metrics, and assessed the relationship of both STAR-defined adherence and exclusion from STAR metrics with CVD risk factor control.
Cross-sectional, population-based analysis of 129,040 diabetics ≥65 in 2010 from three Kaiser Permanente regions.
We estimated adjusted risk ratios to assess the relationship between achieving STAR adherence, and exclusion from STAR adherence metrics, with CVD risk factor control(A1c<8.0%, LDL-C<100mg/dL, systolic blood pressure (SBP)<130mmHg) in diabetics.
STAR metrics excluded 27% of diabetes patients prescribed oral medications. STAR-defined non-adherence was negatively associated with CVD risk factor control (RR=0.95, 0.84, 0.96 for A1c, LDL-C, and SBP control; p<0.001). Exclusion from STAR metrics due to early non-adherence was also strongly associated with poor control (RR=0.83, 0.56, 0.87 for A1c, LDL-C, and SBP control; p<0.001). Exclusion for insulin use was negatively associated with A1c control (RR=0.78; p<.0001).
Medicare STAR adherence measures underestimate the prevalence of medication non-adherence in diabetes, and exclude patients at high risk for poor CVD outcomes. Up to 3 million elderly diabetes patients may be excluded from these measures nationally. Quality measures designed to encourage effective medication use should focus on all patients treated for CVD risk.
Nomograms for prostate and colorectal cancer are included in the Surveillance, Epidemiology, and End Results (SEER) Cancer Survival Calculator, under development by the National Cancer Institute. They are based on the National Cancer Institute’s SEER data, coupled with Medicare data, to estimate the probabilities of surviving or dying from cancer or from other causes based on a set of patient and tumor characteristics. The nomograms provide estimates of survival that are specific to the characteristics of the tumor, age, race, gender, and the overall health of a patient. These nomograms have been internally validated using the SEER data. In this paper, we externally validate the nomograms using data from Kaiser Permanente Colorado.
The SEER Cancer Survival Calculator was externally validated using time-dependent area under the Receiver Operating Characteristic curve statistics and calibration plots for retrospective cohorts of 1102 prostate cancer and 990 colorectal cancer patients from Kaiser Permanente Colorado.
The time-dependent area under the Receiver Operating Characteristic curve statistics were computed for one, three, five, seven, and 10 year(s) postdiagnosis for prostate and colorectal cancer and ranged from 0.77 to 0.89 for death from cancer and from 0.72 to 0.81 for death from other causes. The calibration plots indicated a very good fit of the model for death from cancer for colorectal cancer and for the higher risk group for prostate cancer. For the lower risk groups for prostate cancer (<10% chance of dying of prostate cancer in 10 years), the model predicted slightly worse prognosis than observed. Except for the lowest risk group for colorectal cancer, the models for death from other causes for both prostate and colorectal cancer predicted slightly worse prognosis than observed.
The results of the external validation indicated that the colorectal and prostate cancer nomograms are reliable tools for physicians and patients to use to obtain information on prognosis and assist in establishing priorities for both treatment of the cancer and other conditions, particularly when a patient is elderly and/or has significant comorbidities. The slightly better than predicted risk of death from other causes in a health maintenance organization (HMO) setting may be due to an overall healthier population and the integrated management of disease relative to the overall population (as represented by SEER).
Accurate estimation of the probability of dying of cancer versus other causes is needed to inform goals of care for cancer patients. Further, prognosis may also influence health-care utilization. This paper describes health service utilization patterns of subgroups of prostate cancer and colorectal cancer (CRC) patients with different relative probabilities of dying of their cancer or other conditions.
A retrospective cohort of cancer patients from Kaiser Permanente Colorado were divided into three groups using the predicted probabilities of dying of cancer and other causes calculated by the nomograms in the National Cancer Institute Surveillance, Epidemiology and End Results Cancer Survival Calculator. Demographic, disease-related characteristics, and health service utilization patterns were described across subgroups.
The cohort consisted of 2092 patients (1102 prostate cancer and 990 CRC). A new diagnosis of cancer increased utilization of cancer-related services with rates as high as 9.1/1000 person-days for prostate cancer and 36.2/1000 person-days for CRC. Little change was observed in the number of primary and other specialty care visits from prediagnosis to 1 and 2 years postdiagnosis.
We found that although a new diagnosis of cancer increased utilization of cancer-related services for an extended time period, the timing of cancer diagnosis did not appear to affect other types of utilization. Future research should assess the reason for the lack of impact of cancer and unrelated comorbid conditions on utilization and whether desired outcomes of care were achieved.
Numerous population-based surveys indicate that overweight and obese patients can benefit from lifestyle counseling during routine clinical care.
To determine if natural language processing (NLP) could be applied to information in the electronic health record (EHR) to automatically assess delivery of counseling related to weight management in clinical health care encounters.
The MediClass system with NLP capabilities was used to identify weight management counseling in EHR encounter records. Knowledge for the NLP application was derived from the 5As framework for behavior counseling: Ask (evaluate weight and related disease), Advise at-risk patients to lose weight, Assess patients’ readiness to change behavior, Assist through discussion of weight loss methods and programs and Arrange follow-up efforts including referral. Using samples of EHR data in 1/1/2007-3/31/2011 period from two health systems, the accuracy of the MediClass processor for identifying these counseling elements was evaluated in post-partum visits of 600 women with gestational diabetes mellitus (GDM) compared to manual chart review as gold standard. Data were analyzed in 2013.
Mean sensitivity and specificity for each of the 5As compared to the gold standard was at or above 85%, with the exception of sensitivity for Assist which was measured at 40% and 60% respectively for each of the two health systems. The automated method identified many valid cases of Assist not identified in the gold standard.
The MediClass processor has performance capability sufficiently similar to human abstractors to permit automated assessment of counseling for weight loss in post-partum encounter records.
behavior change; weight-loss counseling; GDM; natural language processing; electronic health records
Few studies have directly investigated the association of clinicians’ implicit (unconscious) bias with health care disparities in clinical settings.
To determine if clinicians’ implicit ethnic or racial bias is associated with processes and outcomes of treatment for hypertension among black and Latino patients, relative to white patients.
RESEARCH DESIGN AND PARTICIPANTS
Primary care clinicians completed Implicit Association Tests of ethnic and racial bias. Electronic medical records were queried for a stratified, random sample of the clinicians’ black, Latino and white patients to assess treatment intensification, adherence and control of hypertension. Multilevel random coefficient models assessed the associations between clinicians’ implicit biases and ethnic or racial differences in hypertension care and outcomes.
Standard measures of treatment intensification and medication adherence were calculated from pharmacy refills. Hypertension control was assessed by the percentage of time that patients met blood pressure goals recorded during primary care visits.
One hundred and thirty-eight primary care clinicians and 4,794 patients with hypertension participated. Black patients received equivalent treatment intensification, but had lower medication adherence and worse hypertension control than white patients; Latino patients received equivalent treatment intensification and had similar hypertension control, but lower medication adherence than white patients. Differences in treatment intensification, medication adherence and hypertension control were unrelated to clinician implicit bias for black patients (P = 0.85, P = 0.06 and P = 0.31, respectively) and for Latino patients (P = 0.55, P = 0.40 and P = 0.79, respectively). An increase in clinician bias from average to strong was associated with a relative change of less than 5 % in all outcomes for black and Latino patients.
Implicit bias did not affect clinicians’ provision of care to their minority patients, nor did it affect the patients’ outcomes. The identification of health care contexts in which bias does not impact outcomes can assist both patients and clinicians in their efforts to build trust and partnership.
Electronic supplementary material
The online version of this article (doi:10.1007/s11606-014-2795-z) contains supplementary material, which is available to authorized users.
hypertension; healthcare disparities; discrimination; implicit bias; race/ethnicity; quality
To review the published, peer-reviewed literature on clinical research data warehouse governance in distributed research networks (DRNs).
Materials and methods
Medline, PubMed, EMBASE, CINAHL, and INSPEC were searched for relevant documents published through July 31, 2013 using a systematic approach. Only documents relating to DRNs in the USA were included. Documents were analyzed using a classification framework consisting of 10 facets to identify themes.
6641 documents were retrieved. After screening for duplicates and relevance, 38 were included in the final review. A peer-reviewed literature on data warehouse governance is emerging, but is still sparse. Peer-reviewed publications on UK research network governance were more prevalent, although not reviewed for this analysis. All 10 classification facets were used, with some documents falling into two or more classifications. No document addressed costs associated with governance.
Even though DRNs are emerging as vehicles for research and public health surveillance, understanding of DRN data governance policies and procedures is limited. This is expected to change as more DRN projects disseminate their governance approaches as publicly available toolkits and peer-reviewed publications.
While peer-reviewed, US-based DRN data warehouse governance publications have increased, DRN developers and administrators are encouraged to publish information about these programs.
Data governance; Data warehouse; Research networks; Clinical research; Data privacy
The Centers for Medicare and Medicaid Services provide significant incentives to health plans that score well on Medicare STAR metrics for cardiovascular disease risk factor medication adherence. Information on modifiable health system-level predictors of adherence can help clinicians and health plans develop strategies for improving Medicare STAR scores, and potentially improve cardiovascular disease outcomes.
To examine the association of Medicare STAR adherence metrics with system-level factors.
A cross-sectional study.
A total of 129,040 diabetes patients aged 65 years and above in 2010 from 3 Kaiser Permanente regions.
Adherence to antihypertensive, antihyperlipidemic, and oral antihyperglycemic medications in 2010, defined by Medicare STAR as the proportion of days covered ≥80%.
After controlling for individual-level factors, the strongest predictor of achieving STAR-defined medication adherence was a mean prescribed medication days’ supply of >90 days (RR=1.61 for antihypertensives, oral antihyperglycemics, and statins; all P<0.001). Using mail order pharmacy to fill medications >50% of the time was independently associated with better adherence with these medications (RR=1.07, 1.06, 1.07; P<0.001); mail order use had an increased positive association among black and Hispanic patients. Medication copayments ≤$10 for 30 days’ supply (RR=1.02, 1.02, 1.02; P<0.01) and annual individual out-of-pocket maximums ≤$2000 (RR=1.02, 1.01, 1.02; P<0.01) were also significantly associated with higher adherence for all 3 therapeutic groupings.
Greater medication days’ supply and mail order pharmacy use, and lower copayments and out-of-pocket maximums, are associated with better Medicare STAR adherence. Initiatives to improve adherence should focus on modifiable health system-level barriers to obtaining evidence-based medications.
adherence; quality measurement; quality improvement
To compare cardiovascular disease risk factor testing rates and intermediate outcomes of care between American Indian/Alaska Native (AI/AN) patients with diabetes and non-Hispanic Caucasians enrolled in nine commercial integrated delivery systems in the USA.
Research design and methods
We used modified Poisson regression models to compare the annual testing rates and risk factor control levels for glycated haemoglobin (HbA1c), low-density lipoprotein cholesterol (LDL-C), and systolic blood pressure (SBP); number of unique diabetes drug classes; insulin use; and oral diabetes drug medication adherence between insured AI/AN and non-Hispanic white adults with diabetes aged ≥18 in 2011.
5831 AI/AN patients (1.8% of the cohort) met inclusion criteria. After adjusting for age, gender, comorbidities, insulin use, and geocoded socioeconomic status, AI/AN patients had similar rates of annual HbA1c, LDL-C, and SBP testing, and LDL-C and SBP control, compared with non-Hispanic Caucasians. However, AI/AN patients were significantly more likely to have HbA1c >9% (>74.9 mmol/mol; RR=1.47, 95% CI 1.38 to 1.58), and significantly less likely to adhere to their oral diabetes medications (RR=0.90, 95% CI 0.88 to 0.93) compared with non-Hispanic Caucasians.
AI/AN patients in commercial integrated delivery systems have similar blood pressure and cholesterol testing and control, but significantly lower rates of HbA1c control and diabetes medication adherence, compared with non-Hispanic Caucasians. As more AI/ANs move to urban and suburban settings, clinicians and health plans should focus on addressing disparities in diabetes care and outcomes in this population.
American Indian(s); Health Care Delivery
Former prison inmates are at risk for HIV and Hepatitis C (HCV). This study was designed to understand how former inmates perceived their risk of HIV and HCV after release from prison, the behaviors and environmental factors that put patients at risk for new infection and the barriers to accessing health care.
Qualitative study utilizing individual, face-to-face, semi-structured interviews exploring participants’ perceptions and behaviors putting them at risk for HIV and HCV and barriers to engaging in regular medical care after release. Interview transcripts were coded and analyzed utilizing a team-based general inductive approach.
Participants were racially and ethnically diverse and consisted of 20 men and 9 women with an age range of 22–57 years who were interviewed within the first two months after their release from prison to the Denver, Colorado community. Four major themes emerged: 1) risk factors including unprotected sex, transactional sex, and drug use were prevalent in the post-release period; 2) engagement in risky behavior occurred disproportionately in the first few days after release; 3) former inmates had educational needs about HIV and HCV; and 4) former inmates faced major challenges in accessing health care and medications.
Risk factors for HIV and HCV were prevalent among former inmates immediately after release. Prevention efforts should focus on education, promotion of safe sex and needle practices, substance abuse treatment, and drug- free transitional housing. Improved coordination between correctional staff, parole officers and community health care providers may improve continuity of care.
Disparities in health care are of great concern, with much attention focused on the potential for unconscious (implicit) bias to play a role in this problem. Some initial studies have been conducted, but the empirical research has lagged. This article provides a research roadmap that spans investigations of the presence of implicit bias in health care settings, identification of mechanisms through which implicit bias operates, and interventions that may prevent or ameliorate its effects. The goal of the roadmap is to expand and revitalize efforts to understand implicit bias and, ultimately, eliminate health disparities. Concrete suggestions are offered for individuals in different roles, including clinicians, researchers, policymakers, patients, and community members.
A combination of quantitative data and illustrative narratives may allow cancer survivorship researchers to disseminate their research findings more broadly. We identified recent, methodologically rigorous quantitative studies on return to work after cancer, summarized the themes from these studies, and illustrated those themes with narratives of individual cancer survivors.
We reviewed English-language studies of return to work for adult cancer survivors through June, 2008, and identified 13 general themes from papers that met methodological criteria (population-based sampling, prospective and longitudinal assessment, detailed assessment of work, evaluation of economic impact, assessment of moderators of work return, and large sample size). We drew survivorship narratives from a prior qualitative research study to illustrate these themes.
Nine quantitative studies met 4 or more of our 6 methodological criteria. These studies suggested that most cancer survivors could return to work without residual disabilities. Cancer site, clinical prognosis, treatment modalities, socioeconomic status, and attributes of the job itself influenced the likelihood of work return. Three narratives - a typical survivor who returned to work after treatment, an individual unable to return to work, and an inspiring survivor who returned to work despite substantial barriers - illustrated many of the themes from the quantitative literature while providing additional contextual details.
Illustrative narratives can complement the findings of cancer survivorship research if researchers are rigorous and transparent in the selection, analysis, and retelling of those stories.
Cancer; oncology; survivorship; work function; quality of life; qualitative research; narrative medidicne; review
To understand the burden of medication use for newly-diagnosed diabetes patients both before and after diabetes diagnosis, and to identify subpopulations of newly-diagnosed diabetes patients who face a relatively high drug burden.
Eleven U.S. integrated health systems.
196,654 insured adults aged ≥20 diagnosed with newly-diagnosed diabetes from 1/1/2005 – 12/31/2009.
Main Outcome Measure
Number of unique therapeutic classes of drugs dispensed in the 12 months prior to, and 12 months post, the diagnosis of diabetes in 5 categories: overall, antihypertensive, antihyperlipidemic, mental health, and antihyperglycemic (post-period only).
The mean number of drug classes used by newly-diagnosed diabetes patients is high before diagnosis (5.0), and increases significantly afterwards (6.6, p<.001). Eighty-one percent of this increase is due to antihyperglycemic initiation and increased use of medications to control hypertension and lipid levels. Multivariate analyses showed that overall drug burden after diabetes diagnosis was higher in female, older, white, and obese patients, as well as among those with higher A1cs and comorbidity levels (p<.001 for all comparisons). The overall number of drug classes used by newly-diagnosed diabetes patients after diagnosis decreased slightly between 2005 and 2009 (p<.001).
Diabetes patients face significant drug burden to control diabetes and other comorbidities, and our data indicate an increased focus on cardiovascular disease risk factor control after diabetes diagnosis. However, total drug burden may be slightly decreasing over time. This information can be valuable to pharmacists working with newly-diagnosed diabetes patients to address their increasing drug regimen complexity.
diabetes; medication burden; surveillance
Although many studies have identified patient characteristics or chronic diseases associated with medication adherence, the clinical utility of such predictors has rarely been assessed. We attempted to develop clinical prediction rules for adherence with antihypertensive medications in two health care delivery systems.
Methods and Results
Retrospective cohort studies of hypertension registries in an inner-city health care delivery system (N = 17176) and a health maintenance organization (N = 94297) in Denver, Colorado. Adherence was defined by acquisition of 80% or more of antihypertensive medications.
A multivariable model in the inner-city system found that adherent patients (36.3% of the total) were more likely than non-adherent patients to be older, white, married, and acculturated in US society, to have diabetes or cerebrovascular disease, not to abuse alcohol or controlled substances, and to be prescribed less than three antihypertensive medications. Although statistically significant, all multivariate odds ratios were 1.7 or less, and the model did not accurately discriminate adherent from non-adherent patients (C-statistic = 0.606). In the health maintenance organization, where 72.1% of patients were adherent, significant but weak associations existed between adherence and older age, white race, the lack of alcohol abuse, and fewer antihypertensive medications. The multivariate model again failed to accurately discriminate adherent from non-adherent individuals (C-statistic = 0.576).
Although certain socio-demographic characteristics or clinical diagnoses are statistically associated with adherence to refills of antihypertensive medications, a combination of these characteristics is not sufficiently accurate to allow clinicians to predict whether their patients will be adherent with treatment.
drugs; hypertension; prevention
Although racial and ethnic minorities are more likely to be involved with the criminal justice system than whites in the USA, critical scientific gaps exist in our understanding of the relationship between the criminal justice system and the persistence of racial/ethnic health disparities. Individuals engaged with the criminal justice system are at risk for poor health outcomes. Furthermore, criminal justice involvement may have direct or indirect effects on health and health care. Racial/ethnic health disparities may be exacerbated or mitigated at several stages of the criminal justice system. Understanding and addressing the health of individuals involved in the criminal justice system is one component of a comprehensive strategy to reduce population health disparities and improve the health of our urban communities.
Prisons; Health disparities; Health care delivery