Timothy G. Ferris

Use of electronic health records in U.S. hospitals.

BACKGROUND Despite a consensus that the use of health information technology should lead to more efficient, safer, and higher-quality care, there are no reliable estimates of the prevalence of adoption of electronic health records in U.S. hospitals. METHODS We surveyed all acute care hospitals that are members of the American Hospital Association for the presence of specific electronic-record functionalities. Using a definition of electronic health records based on expert consensus, we determined the proportion of hospitals that had such systems in their clinical areas. We also examined the relationship of adoption of electronic health records to specific hospital characteristics and factors that were reported to be barriers to or facilitators of adoption. RESULTS On the basis of responses from 63.1% of hospitals surveyed, only 1.5% of U.S. hospitals have a comprehensive electronic-records system (i.e., present in all clinical units), and an additional 7.6% have a basic system (i.e., present in at least one clinical unit). Computerized provider-order entry for medications has been implemented in only 17% of hospitals. Larger hospitals, those located in urban areas, and teaching hospitals were more likely to have electronic-records systems. Respondents cited capital requirements and high maintenance costs as the primary barriers to implementation, although hospitals with electronic-records systems were less likely to cite these barriers than hospitals without such systems. CONCLUSIONS The very low levels of adoption of electronic health records in U.S. hospitals suggest that policymakers face substantial obstacles to the achievement of health care performance goals that depend on health information technology. A policy strategy focused on financial support, interoperability, and training of technical support staff may be necessary to spur adoption of electronic-records systems in U.S. hospitals.

Limited English Proficiency and Breast and Cervical Cancer Screening in a Multiethnic Population

OBJECTIVES We examined the relationship between ability to speak English and receipt of Papanicolaou tests, clinical breast examinations, and mammography in a multiethnic group of women in the United States. METHODS We used longitudinal data from the Study of Women Across the Nation to examine receipt of breast and cervical cancer screening among Chinese, Japanese, Hispanic, and White women who reported reading and speaking (1) only a language other than English, (2) another language more fluently than English, or (3) only English or another language and English with equal fluency. Logistic regression was used to analyze the data. RESULTS Reading and speaking only a language other than English and reading and speaking another language more fluently than English, were significantly and negatively associated with receipt of breast and cervical cancer screening in unadjusted models. Although these findings were attenuated in adjusted models, not speaking English well or at all remained negatively associated with receipt of cancer screening. CONCLUSIONS These findings suggest that language barriers contribute to health disparities by impeding adequate health communication.

Patient–Physician Connectedness and Quality of Primary Care

Context Continuity of care is a basic tenet of high-quality primary care, but the relationship between quality of care and the connection between patient and physician has not been rigorously studied. Contribution The researchers defined whether 155590 adults in a primary care network received most of their care from a specific physician, practice, or neither. Patients who were connected to a particular physician were more likely to have received recommended care than patients who were connected to a practice but not a physician. Caution The study involved only 1 network, which is one of many potential definitions of continuity, and selected quality measures. The Editors Persistent deficiencies exist in the quality of health care in the United States (14). Because primary care physicians are the first source of health care for most patients to receive preventive and chronic illness care, efforts to measure and improve quality of care have often focused on these physicians (57). In practice, however, many patients receive episodic care from different physicians (812). Patients without a regular source of care are less likely to receive care consistent with guidelines (1320). Continuity of care is a shared responsibility between physicians and patients. Even if physicians or practices treated all patients similarly, patients vary in their ability and willingness to adhere to recommendations. Performance measures originally designed for use in large populations are increasingly used to assess the quality of practices and individual physicians. One concern with this approach is that physicians who care for patients who are less willing or able to adhere to recommendations will seem to perform less well. To investigate this possibility, we developed the concept of physicianpatient connectedness. We use the term connectedness to describe the closeness of the relationship between a patient and an individual physician on the basis of a model predicting how likely a physician is to identify a patient as my patient. We hypothesized that patients highly connected to a specific physician would be more likely to receive care consistent with guidelines, according to common performance measures. We further hypothesized that differences in connectedness may contribute to health care disparities to the extent that connectedness is correlated with race or ethnicity and insurance status. We investigated these hypotheses in a network of primary care physicians affiliated with a large teaching hospital. We used a previously developed and validated algorithm (21, 22) to determine the connectedness of more than 150000 patients with a specific physician. The algorithm used the designated primary care physician field from the practice registration system along with patient age, time since most recent visit, and in-state residence. We then examined variation in the proportion of connected patients among practices and the association of connectedness with the performance of commonly used measures of health care quality. Methods Study Setting and Sample The Massachusetts General Hospital (Boston, Massachusetts) adult primary care network includes 181 primary care physicians working in 13 clinically and demographically diverse practices (4 community health centers and 9 hospital-affiliated practices). The practices use the same electronic billing and scheduling systems, and physicians have the same compensation plan and staffing resources. Patients must designate a primary care physician when registering for care. We identified all patients with a visit to 1 of these practices from 1 January 2003 to 31 December 2005 by using electronic billing records. During this time, 169024 unique patients were seen for 994431 visits. We excluded patients if they were younger than 18 years (n= 1924), had died (determined on the basis of review of social security records) (n= 2817), or were registered as having a primary care physician outside of the Massachusetts General Hospital network (n= 8693). The Massachusetts General Hospital institutional review board approved the study. Connecting Patients With Primary Care Physicians and Practices Figure 1 shows the process used to connect patients with a specific physician or practice. We previously developed and validated an algorithm to connect patients with a specific physician by having 18 primary care physicians review a list of all patients seen over 3 years (mean, 1029 patients per physician; range, 226 to 2372 patients per physician) and designate which patients they considered to be my patient (21, 22). The algorithm primarily uses the primary care physician designee field from the hospital registration system. However, as a stand-alone variable, its specificity (84.9%) would result in too many patients on a list being incorrectly identified as being connected to that physician (21). As a result, the final algorithm combined the primary care physician designee field with a logistic regression model that included patient age, time since most recent visit, in-state residence, and physician practice style (21). We defined the physician practice style variable according to the proportion of all visits by patients registered to the physician. Thus, physicians who were the registered provider for at least 70% of the patients they saw were categorized as following a solo-practice style, whereas physicians who were the registered provider for fewer than 70% of the patients they saw were designated as having a collaborative-practice style. The model variables were designed to provide a highly specific list of patients for a given physician (overall specificity, 93.7%; positive predictive value, 96.5% [range, 90.1% to 100%]) (21). Figure 1. Method of connecting patients with specific primary care physicians or practices. MGH = Massachusetts General Hospital; PCP = primary care physician. The square boxes represent the patient population seen in the MGH primary care network and their initial assessment based on listed provider. The hexagonal boxes represent the algorithms that connect patients to a specific physician or practice. The rounded boxes represent the disposition of the primary care population based on patientphysician connectedness. * Patients younger than 18 years and those who were deceased are also included in this category. Patients who could not be connected to a specific physician were connected to the primary care practice in which they received most of their care. Patients were not connected to a specific physician because they had a primary care physician in a given practice but did not meet threshold criteria (using the patientphysician connectedness algorithm), were only seen by physicians other than their registered primary care physician, were followed by a resident physician, or received care in a given practice but were not registered with a primary care physician in that practice. Patients who were followed by a resident physician were assigned to the practice in which the resident provided care. We developed criteria for connecting patients to individual practices by consensus in collaboration with physician practice representatives (Table 1). Patients who could not be assigned to either a physician or a practice with these methods were designated as unconnected. Table 1. Criteria Used to Define Whether Patients Not Connected to a Specific Physician Were Connected to a Specific Primary Care Practice Patient and Provider Characteristics and Performance Measures We obtained data from an electronic record repository for Massachusetts General Hospital and affiliated institutions (23). Available patient characteristics included date of birth, sex, race or ethnicity, primary language spoken, insurance status, number of outpatient office visits during the previous 3 years, and months since most recent outpatient visit. We obtained physician characteristics (age, sex, practice location, and years since medical school graduation) from the hospital registrar database. Physician performance measures focused on cancer screening and chronic disease management. Cancer screening measures were mammography for women age 42 to 69 years in the previous 2 years and without previous bilateral mastectomy; Papanicolaou cervical screening in the previous 3 years for women age 21 to 64 years without hysterectomy; and colonoscopy within 10 years, sigmoidoscopy or double-contrast barium enema within 5 years, or home fecal occult blood testing within 1 year for patients age 52 to 69 years without total colectomy. For patients with diabetes, we assessed 2 measures: hemoglobin A1c (HbA1c) and low-density lipoprotein cholesterol measured in the previous year (24). For patients with coronary artery disease, we assessed low-density lipoprotein cholesterol measured in the previous year (25). For persons who had HbA1c and low-density lipoprotein cholesterol testing, we also assessed the most recent value available and categorized HbA1c level as less than 8.0% or not and low-density lipoprotein cholesterol level as less than 2.59 mmol/L (<100 mg/dL) or not (26). We extracted data for these measures from electronic laboratory and imaging reports or billing data within the Partners Healthcare System on the basis of Healthcare Effectiveness Data and Information Set criteria (27). Statistical Analysis We first grouped patients by connectedness status and compared characteristics of physician-connected, practice-connected, and unconnected patients. To account for the repeated measures of patients from the same physician, we used generalized estimating equations techniques with compound symmetry correlation structure (PROC GENMOD [SAS, version 9.1.3, SAS Institute, Cary, North Carolina]) (28) in all statistical analyses for clustering effects. The physician was considered as the unit of cluster for physician-connected patients, and each patient was considered as an individual cluster for practice-connected patients. Becaus

Who is using chronic acid suppression therapy and why

OBJECTIVES:Acid suppression medications have become one of the most commonly prescribed classes of therapeutic agents. Because little data exists describing the chronic use of these agents among a general population, we sought to determine the patterns of use of proton pump inhibitors (PPIs) and histamine type 2 receptor antagonists (H2RAs) in clinical practice, as well as the distribution and severity of symptoms in patients prescribed these therapies.METHODS:Pharmacy billing data from two insurers were used to identify all patients on chronic (>90 days) PPIs and H2RAs within a large, eastern Massachusetts provider network. Patient demographics, diagnoses, frequency of office visits, and information about diagnostic testing were obtained from billing databases. A questionnaire addressing recent upper GI symptoms, over-the-counter medication use, and gastroenterologist consultations was mailed to a 1,139 patient subset (35%) of eligible patients. We compared the diagnoses of patients on chronic therapy with those of the general population of the network. We also compared the frequency of symptoms and diagnostic testing between those prescribed H2RAs and PPIs.RESULTS:From a total population of 168,727 adult patients, we identified 4,684 (2.8%) prescribed chronic acid suppression therapy, with 47% taking H2RAs and 57% taking PPIs (4% filled prescriptions for both simultaneously). A relevant GI diagnosis was found using billing data for only 61% of patients, mainly for gastroesophageal reflux disease (38%) and dyspepsia (42%), with many patients carrying both diagnoses. Our survey (response rate 59%) revealed that more than 30% of responders experienced heartburn or reflux more than twice a week, and more than half experienced symptoms of dyspepsia at least once a week. Diagnostic testing was uncommon, with only 19% having undergone esophagogastroduodenoscopy within the prior 2 yr.CONCLUSIONS:Acid suppression medications were used chronically by a large number of patients within this population. A significant proportion of patients on chronic PPI or H2RA lacked definitive upper GI diagnoses in their billing data. The high symptom burden and low use of diagnostic testing indicates opportunities for improvement in the care of patients on chronic acid suppression therapy.

Options for slowing the growth of health care costs.

The authors review potential strategies to contain health care costs and assess each proposals potential for success. Modifications in reimbursement to reward the practice of evidence-based medicine, expansion of the use of electronic medical records, and standardization of billing transactions to reduce administrative costs are among the strategies they view as most promising.

The role of quality improvement in strengthening health systems in developing countries

Quality of care was recognized as a key element for improved health outcomes and efficiency in the World Health Organizations (WHO) widely adopted framework for health system strengthening in resource-poor countries. Although modern approaches to improving quality are increasingly used globally, their adoption remains sporadic in developing countries. Healthcare leaders and improvement experts representing 15 countries met in October 2008 to catalyze the adoption of quality improvement (QI) methods to improve healthcare quality in resource-poor settings. This paper describes the evidence used to frame deliberations, the proceedings and a proposal for incorporating QI methods into plans for strengthening health systems. The conference participants presented case reports and reviewed a growing body of evidence from peer-reviewed journals demonstrating that QI methods can make significant contributions in resource poor settings. Deliberations focused on the barriers to adoption of QI methods and potential strategies for addressing those barriers. Attendees concluded that QI has the potential to optimize the use of limited resources available from governments and global initiatives targeted at achieving shared aims. Demonstrable improvements in quality may encourage greater investment in health systems in developing countries by increasing donor, population and governmental confidence that resources are being used well.

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

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

Effectiveness of a guideline to reduce vancomycin use in the neonatal intensive care unit.

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.

Are Minority Children the Last to Benefit from a New Technology? Technology Diffusion and Inhaled Corticosteriods for Asthma

Background: The Centers for Disease Control and Prevention recommend hospitals develop guidelines for the appropriate use of vancomycin as part of comprehensive antimicrobial stewardship. The objective of this study was to evaluate the effectiveness and safety of a guideline to restrict vancomycin use in the neonatal intensive care unit (NICU). Methods: A vancomycin use guideline was introduced in 2 tertiary care NICUs with low incidences of methicillin-resistant Staphylococcus aureus infections. We compared all infants >72 hours of age who were evaluated for late-onset infection before and after implementation of this guideline. Results: Vancomycin start rates were reduced from 6.9 to 4.5 per 1000 patient-days (35% reduction; P = 0.01) at Brigham and Womens Hospital, and from 17 to 6.4 per 1000 patient-days (62% reduction; P < 0.0001) at Massachusetts General Hospital. The number of infants exposed to vancomycin decreased from 5.2 to 3.1 per 1000 patient-days (40% reduction; P = 0.008) at Brigham and Womens Hospital, and 10.8 to 5.5 per 1000 patient-days (49% reduction; P = 0.009) at Massachusetts General Hospital. Causes of infection, duration of bacteremia, and incidence of complications or deaths attributable to late-onset infection did not change significantly at either institution. Conclusions: Implementation of a NICU vancomycin use guideline significantly reduced exposure of newborns to vancomycin without adversely affecting short-term patient safety. Further studies are required to evaluate the long-term effect of vancomycin restriction on NICU patient safety and microbial ecology, particularly among institutions with higher rates of methicillin-resistant Staphylococcus aureus infections.

Insurance and Quality of Care for Children With Acute Asthma

Background:Racial and ethnic disparities in health and health care have been well documented, but few studies have addressed how disparities may change over time. Objective:We sought to determine the change in relative rates over time of corticosteroid metered dose inhaler (MDI) use in minority and nonminority populations with asthma. Design and Setting:We used a cross-sectional survey for 5 periods of 2 years’ each (1989–1990, 1991–1992, 1993–1994, 1995–1996, 1997–1998) using the National Ambulatory Medical Care Surveys (NAMCS). Participants:A total of 3671 visits by adults and children with asthma to U.S. office-based physicians comprised our sample. Main Outcome Measure:We sought to measure differences in inhaled corticosteroid use for minority and nonminority adults and children controlling for gender, specialty, U.S. region, and type of insurance. Results:Minority patients with asthma were less than half as likely as nonminority patients to have had a steroid MDI prescribed during 1989–1990. By 1995–1996, minority and nonminority patients with asthma were equally likely to have had a steroid MDI prescribed. Although differences between black and white patients resolved, differences between white and Hispanic patients persisted even after adjusting for insurance. Children initially were less likely than adults with asthma to have steroid MDI prescribed, and this difference persisted. Minority children had the greatest delay in adoption of steroid MDIs. Conclusion:Steroid MDIs diffused into minority and nonminority adult and child populations at different rates.