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 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.
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.
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.
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.
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
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 propose a unifying set of definitions for prescription adherence research utilizing electronic health record prescribing databases, prescription dispensing databases, and pharmacy claims databases and to provide a conceptual framework to operationalize these definitions consistently across studies.
We reviewed recent literature to identify definitions in electronic database studies of prescription-filling patterns for chronic oral medications. We then develop a conceptual model and propose standardized terminology and definitions to describe prescription-filling behavior from electronic databases.
The conceptual model we propose defines two separate constructs: medication adherence and persistence. We define primary and secondary adherence as distinct sub-types of adherence. Metrics for estimating secondary adherence are discussed and critiqued, including a newer metric (New Prescription Medication Gap measure) that enables estimation of both primary and secondary adherence.
Terminology currently used in prescription adherence research employing electronic databases lacks consistency. We propose a clear, consistent, broadly applicable conceptual model and terminology for such studies. The model and definitions facilitate research utilizing electronic medication prescribing, dispensing, and/or claims databases and encompasses the entire continuum of prescription-filling behavior.
Employing conceptually clear and consistent terminology to define medication adherence and persistence will facilitate future comparative effectiveness research and meta-analytic studies that utilize electronic prescription and dispensing records.
medication adherence; medication persistence; medication discontinuation; refill compliance; refill persistence; administrative; database; electronic health record; computerized medical record systems
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
Multi-institutional collaborations are necessary in order to create large and robust data sets that are needed to answer important comparative effectiveness research (CER) questions. Before scientific work can begin, a complex maze of administrative and regulatory requirements must be efficiently navigated to avoid project delays.
Staff from research, regulatory, and administrative teams involved in three HMO Research Network (HMORN) multi-institutional collaborations developed and employed novel approaches: to secure and maintain Institutional Review Board (IRB) approvals; to enable data sharing, and to expedite subawards for two data-only minimal risk studies. These novel approaches accelerated required processes and approvals while maintaining regulatory, human subjects, and institutional protections.
Outcomes from the processes described here are compared with processes outlined in the research and regulatory literature and with processes that have been used in previous multisite research collaborations.
Conclusion and Discussion:
Research, regulatory, and administrative staff are essential contributors to the success of multi-institutional collaborations. Their flexibility, creativity, and effective communication skills can lead to the development of efficient approaches to achieving the necessary oversight for these complex projects. Elements of these specific strategies can be adapted and used by other research networks. Other efforts in these areas should be evaluated and shared. The processes that help develop a “learning research system” play an important and complementary role in sustaining multi-institutional research collaborations.
Data agreement; Institutional Review Board; Subcontract; Subaward; Administrative Efficiency
As multi-institutional research networks assume a central role in clinical research, they must address the challenge of sustainability. Despite its importance, the concept of network sustainability has received little attention in the literature, and the sustainability strategies of durable scientific networks have not been described.
The Health Maintenance Organization Research Network (HMORN) is a consortium of 18 research departments in integrated health care delivery systems with over 15 million members in the United States and Israel. The HMORN has coordinated federally funded scientific networks and studies since 1994. This case study describes the HMORN approach to sustainability, proposes an operational definition of network sustainability, and identifies 10 essential elements that can enhance sustainability.
The sustainability framework proposed here is drawn from prior publications on organizational issues by HMORN investigators and from the experience of recent HMORN leaders and senior staff.
Conclusion and Discussion:
Network sustainability can be defined as (1) the development and enhancement of shared research assets to facilitate a sequence of research studies in a specific content area or multiple areas, and (2) a community of researchers and other stakeholders who reuse and develop those assets. Essential elements needed to develop the shared assets of a network include: network governance; trustworthy data and processes for sharing data; shared knowledge about research tools; administrative efficiency; physical infrastructure; and infrastructure funding. The community of researchers within a network is enhanced by: a clearly defined mission, vision and values; protection of human subjects; a culture of collaboration; and strong relationships with host organizations. While the importance of these elements varies based on the membership and goals of a network, this framework for sustainability can enhance strategic planning within the network and can guide relationships with external stakeholders.
Clinical research; comparative effectiveness research; health maintenance organization; organizational change; program sustainability; data systems
There are no evidence-based recommendations for statin continuation or discontinuation near the end of life. However, some expert opinion recommends continuing statins prescribed for secondary versus primary prevention of cardiovascular disease.
Our aim was to explore statin prescribing patterns in a longitudinal cohort of individuals with life-limiting illness, and to evaluate differences in these patterns based on secondary versus primary prevention of cardiovascular disease.
Design and setting
This study was a retrospective cohort analysis of 539 persons in an integrated, not-for-profit health maintenance organization (HMO) setting who were receiving statins at diagnosis of a cancer with 0% to 25% predicted 5-year survival. Of the cohort patients, 343 were taking statins for secondary prevention and 196 for primary prevention of cardiovascular disease. Measurements included number and timing of statin refills between diagnosis and date of death, disenrollment, or the end of the observation period.
Four hundred and ninety-six cohort members died within the observation period. Fifty-eight percent of the secondary prevention and 62% of the primary prevention group had at least one statin refill after diagnosis. There were no significant differences between groups for number of days between diagnosis and last refill, or between last refill and death. Two deaths were attributable to cardiovascular causes in each group.
Our retrospective cohort analysis of persons with incident poor-prognosis cancer describes diminished, but persistent statin refills after diagnosis. Neither timing of statin discontinuation nor cardiovascular mortality differed by prescribing indication. There may be an opportunity to reevaluate medication burden in persons taking statins for primary prevention, and it is unclear whether continuing statins prescribed for secondary prevention affects cardiovascular outcomes.
The HMO Research Network (HMORN) Virtual Data Warehouse (VDW) is a public, non-proprietary, research-focused data model implemented at 17 health care systems across the United States. The HMORN has created a governance structure and specified policies concerning the VDW’s content, development, implementation, and quality assurance. Data extracted from the VDW have been used by thousands of studies published in peer-reviewed journal articles. Advances in software supporting care delivery and claims processing and the availability of new data sources have greatly expanded the data available for research, but substantially increased the complexity of data management. The VDW data model incorporates software and data advances to ensure that comprehensive, up-to-date data of known quality are available for research. VDW governance works to accommodate new data and system complexities. This article highlights the HMORN VDW data model, its governance principles, data content, and quality assurance procedures. Our goal is to share the VDW data model and its operations to those wishing to implement a distributed interoperable health care data system.
Informatics; Data Reuse; Health Information Technology; Research Networks; Standardized Data Collection
Former inmates are at high risk for death from drug overdose, especially in the immediate post-release period. The purpose of the study is to understand the drug use experiences, perceptions of overdose risk, and experiences with overdose among former prisoners.
This qualitative study included former prison inmates (N = 29) who were recruited within two months after their release. Interviewers conducted in-person, semi-structured interviews which explored participants' experiences and perceptions. Transcripts were analyzed utilizing a team-based method of inductive analysis.
The following themes emerged: 1) Relapse to drugs and alcohol occurred in a context of poor social support, medical co-morbidity and inadequate economic resources; 2) former inmates experienced ubiquitous exposure to drugs in their living environments; 3) intentional overdose was considered "a way out" given situational stressors, and accidental overdose was perceived as related to decreased tolerance; and 4) protective factors included structured drug treatment programs, spirituality/religion, community-based resources (including self-help groups), and family.
Former inmates return to environments that strongly trigger relapse to drug use and put them at risk for overdose. Interventions to prevent overdose after release from prison may benefit from including structured treatment with gradual transition to the community, enhanced protective factors, and reductions of environmental triggers to use drugs.
Drug use; Overdose; Prisoners; Relapse; Prison re-entry