Christine Vogeli

Electronic Health Records’ Limited Successes Suggest More Targeted Uses

Understanding whether electronic health records, as currently adopted, improve quality and efficiency has important implications for how best to employ the estimated

Multiple Chronic Conditions: Prevalence, Health Consequences, and Implications for Quality, Care Management, and Costs

20 billion in health information technology incentives authorized by the American Recovery and Reinvestment Act of 2009. We examined electronic health record adoption in U.S. hospitals and the relationship to quality and efficiency. Across a large number of metrics examined, the relationships were modest at best and generally lacked statistical or clinical significance. However, the presence of clinical decision support was associated with small quality gains. Our findings suggest that to drive substantial gains in quality and efficiency, simply adopting electronic health records is likely to be insufficient. Instead, policies are needed that encourage the use of electronic health records in ways that will lead to improvements in care.

Primary Medication Non-Adherence: Analysis of 195,930 Electronic Prescriptions

Persons with multiple chronic conditions are a large and growing segment of the US population. However, little is known about how chronic conditions cluster, and the ramifications of having specific combinations of chronic conditions. Clinical guidelines and disease management programs focus on single conditions, and clinical research often excludes persons with multiple chronic conditions. Understanding how conditions in combination impact the burden of disease and the costs and quality of care received is critical to improving care for the 1 in 5 Americans with multiple chronic conditions. This Medline review of publications examining somatic chronic conditions co-occurring with 1 or more additional specific chronic illness between January 2000 and March 2007 summarizes the state of our understanding of the prevalence and health challenges of multiple chronic conditions and the implications for quality, care management, and costs.

Physician professionalism and changes in physician-industry relationships from 2004 to 2009.

ABSTRACTBACKGROUNDNon-adherence to essential medications represents an important public health problem. Little is known about the frequency with which patients fail to fill prescriptions when new medications are started (“primary non-adherence”) or predictors of failure to fill.OBJECTIVEEvaluate primary non-adherence in community-based practices and identify predictors of non-adherence.PARTICIPANTS75,589 patients treated by 1,217 prescribers in the first year of a community-based e-prescribing initiative.DESIGNWe compiled all e-prescriptions written over a 12-month period and used filled claims to identify filled prescriptions. We calculated primary adherence and non-adherence rates for all e-prescriptions and for new medication starts and compared the rates across patient and medication characteristics. Using multivariable regressions analyses, we examined which characteristics were associated with non-adherence.MAIN MEASURESPrimary medication non-adherence.KEY RESULTSOf 195,930 e-prescriptions, 151,837 (78%) were filled. Of 82,245 e-prescriptions for new medications, 58,984 (72%) were filled. Primary adherence rates were higher for prescriptions written by primary care specialists, especially pediatricians (84%). Patients aged 18 and younger filled prescriptions at the highest rate (87%). In multivariate analyses, medication class was the strongest predictor of adherence, and non-adherence was common for newly prescribed medications treating chronic conditions such as hypertension (28.4%), hyperlipidemia (28.2%), and diabetes (31.4%).CONCLUSIONSMany e-prescriptions were not filled. Previous studies of medication non-adherence failed to capture these prescriptions. Efforts to increase primary adherence could dramatically improve the effectiveness of medication therapy. Interventions that target specific medication classes may be most effective.

Effect of Electronic Prescribing With Formulary Decision Support on Medication Use and Cost

BACKGROUND One tenet of medical professionalism is managing conflicts of interest related to physician-industry relationships (PIRs). Since 2004 much has been done at the institutional, state, and national levels to limit PIRs. This study estimates the nature, extent, consequences, and changes in PIRs nationally. METHODS We performed a national survey of a stratified random sample of 2938 primary care physicians (internal medicine, family practice, and pediatrics) and specialists (cardiology, general surgery, psychiatry, and anesthesiology). A total of 1891 physicians completed the survey, yielding an overall response rate of 64.4%. The main outcome measure was prevalence of several types of PIRs and comparison with PIRs in 2004. RESULTS Overall, 83.8% of all respondents reported some type of relationship with industry during the previous year. Approximately two-thirds (63.8%) received drug samples, 70.6% food and beverages, 18.3% reimbursements, and 14.1% payments for professional services. Since 2004 the percentage of each of these benefits has decreased significantly. Higher rates of PIRs are significantly and inversely associated with low levels of Medicare spending. CONCLUSION Among a random sample of physicians, the prevalence of self-reported PIRs in 2009 was 83.8%, which was lower than in 2004.

Gender differences in tobacco use in Africa, Asia, the Pacific, and Latin America

BACKGROUND Electronic prescribing (e-prescribing) with formulary decision support (FDS) prompts prescribers to prescribe lower-cost medications and may help contain health care costs. In April 2004, 2 large Massachusetts insurers began providing an e-prescribing system with FDS to community-based practices. METHODS Using 18 months (October 1, 2003, to March 31, 2005) of administrative data, we conducted a pre-post study with concurrent controls. We first compared the change in the proportion of prescriptions for 3 formulary tiers before and after e-prescribing began, then developed multivariate longitudinal models to estimate the specific effect of e-prescribing when controlling for baseline differences between intervention and control prescribers. Potential savings were estimated using average medication costs by formulary tier. RESULTS More than 1.5 million patients filled 17.4 million prescriptions during the study period. Multivariate models controlling for baseline differences between prescribers and for changes over time estimated that e-prescribing corresponded to a 3.3% increase (95% confidence interval, 2.7%-4.0%) in tier 1 prescribing. The proportion of prescriptions for tiers 2 and 3 (brand-name medications) decreased correspondingly. e-Prescriptions accounted for 20% of filled prescriptions in the intervention group. Based on average costs for private insurers, we estimated that e-prescribing with FDS at this rate could result in savings of

Racial and Ethnic Disparities within and between Hospitals for Inpatient Quality of Care: An Examination of Patient-Level Hospital Quality Alliance Measures

845,000 per 100,000 patients. Higher levels of e-prescribing use would increase these savings. CONCLUSIONS Clinicians using e-prescribing with FDS were significantly more likely to prescribe tier 1 medications, and the potential financial savings were substantial. Widespread use of e-prescribing systems with FDS could result in reduced spending on medications.

Physician Acquiescence to Patient Demands for Brand-Name Drugs: Results of a National Survey of Physicians

This paper reviews historical, anthropological and contemporary survey data concerning gender differences in tobacco use in Africa, Asia, the Pacific, and Latin America. In many cultural groups in these regions, tobacco use has been substantially more common among men than among women. In some groups, tobacco use has been about equally common for both sexes. No evidence was found of any group in which tobacco use has been substantially more common among women. The widespread pattern of greater tobacco use by men appears to be linked to general features of sex roles. For example, men have often had greater social power than women, and this has been expressed in greater restrictions on womens behavior, including social prohibitions against womens smoking. These social prohibitions against womens smoking have strongly inhibited womens tobacco use and thus have been a major cause of gender differences in tobacco use. Gender differences in tobacco use have varied in magnitude, depending on the type of tobacco use and the particular cultural group, age group and historical period considered. Causes of the variation in gender differences in tobacco use include variation in womens status and variation in the social significance and benefits attributed to particular types of tobacco use in different cultures. Contact with Western cultures appears to have increased or decreased gender differences in smoking, depending on the specific circumstances. The patterns of gender differences in tobacco use in non-Western societies are similar in many ways to the patterns observed in Western societies, but there are several important differences.(ABSTRACT TRUNCATED AT 250 WORDS)

A four-system comparison of patients with chronic illness: the Military Health System, Veterans Health Administration, Medicaid, and commercial plans

Background. Little is known about whether disparities occur within or between hospitals for national Hospital Quality Alliance (HQA) measures. Methods. We examined patient-level data from 4,450 non-federal hospitals in the U.S. for over 2.3 million Black, Hispanic, Asian, American Indian/Alaska Native, and Native Hawaiian/Pacific Islander patients who received care for acute myocardial infarction, heart failure, or pneumonia in 2005. Results. There were 37 out of 95 findings of disparities after adjusting for patient characteristics. Eleven of the disparities were explained entirely by where minorities received care and the magnitude for 25 of the others was substantially reduced after adjusting for site of care. Discussion. Adjusting for between-hospital quality differences accounted for a large proportion of the disparities. Where disparities exist, the primary cause may be that minorities are more likely to receive care in lower-performing hospitals. Policies to reduce disparities should include targeting resources to facilities serving a high percentage of minority patients.

Policies and Management of Conflicts of Interest Within Medical Research Institutional Review Boards: Results of a National Study

and Kushel. Statistical analysis: Vijayaraghavan. Obtained funding: Bangsberg, Miaskowski, and Kushel. Administrative, technical, and material support: Penko, Bangsberg, Miaskowski, and Kushel. Study supervision: Bangsberg and Kushel. Conflict of Interest Disclosures: None reported. Funding/Support: This study was funded by a grant from the National Institute of Drug Abuse R01DA022550, and a grant from the National Institute of Mental Health R01MH54907. The Tenderloin Center for Clinical Research was supported by the University of California, San Francisco (UCSF),Clinical andTranslational Institute grant, NIH/NCRR UCSF-CTSI UL1 RR024131. Dr Vijayaraghavan is supported by a postdoctoral fellowship from the Cancer Prevention and Control Division, Moores Cancer Center, University of California, San Diego. Role of the Sponsor: The funders had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript. Previous Presentation: Results from this study were presented in an oral presentation at the Annual Meeting of the Society of General Internal Medicine; May 12, 2012; Orlando, Florida. Additional Contributions: We thank the research assistants for conducting the patient interviews; the participants for their contribution to this study; and Eric Vittinghoff, PhD, and David Guzman, MSPH, for their contributions toward the statistical analysis and interpretation of data, and for their comments on an earlier draft of the manuscript. Online-Only Material: The eTable is available at http: //www.jamainternalmed.com.