Wilson D. Pace

Event Reporting to a Primary Care Patient Safety Reporting System: A Report From the ASIPS Collaborative

BACKGROUND We examined reports to a primary care, ambulatory, patient safety reporting system to describe types of errors reported and differences between anonymous and confidential reports. METHODS Applied Strategies for Improving Patient Safety (ASIPS) is a demonstration project designed to collect and analyze medical error reports from clinicians and staff in 2 practice-based research networks: the Colorado Research Network (CaReNet) and the High Plains Research Network (HPRN). A major component of ASIPS is a voluntary patient safety reporting system that accepts reports of errors anonymously or confidentially. Reports are coded using a multiaxial taxonomy. RESULTS Two years into this project, 33 practices with a total of 475 clinicians and staff have participated in ASIPS. Participants submitted 708 reports during this time (66% using the confidential reporting form). We successfully followed up on 84% of the confidential reports of interest within the allotted 10-day time frame. We ended up with 608 relevant, codable reports. Communication problems (70.8%), diagnostic tests (47%), medication problems (35.4%), and both diagnostic tests and medications (13.6%) were the most frequently reported errors. Confidential reports were significantly more likely than anonymous reports to contain codable data. CONCLUSION A safe and secure reporting system that relies on voluntary reporting from clinicians and staff can be successfully implemented in primary care settings. Information from confidential reports appears to be superior to that from anonymous reports and may be more useful in understanding errors and designing interventions to improve patient safety.

Effect of Preventive Messages Tailored to Family History on Health Behaviors: The Family Healthware Impact Trial

PURPOSE We wanted to determine the impact of automated family history assessment and tailored messages for coronary heart disease, stroke, diabetes, colorectal, breast, and ovarian cancer on preventive behaviors compared with a standard preventive message. METHODS The study was a cluster-randomized clinical trial that included 41 primary care practices, the majority in the Midwest, using Family Healthware, a self-administered, Web-based tool that assesses familial risk for the diseases and provides personalized risk-tailored messages. Patients in the control group received an age- and sex-specific health message related to lifestyle and screening. Smoking cessation, fruit and vegetable intake, physical activity, aspirin use, blood pressure, and cholesterol and blood glucose screening were assessed at baseline and 6 months after the intervention. RESULTS Of 4,248 participants, 3,344 (78%) completed the study. Participants were white (91%), female (70%), and insured (97%), and had a mean age of 50.6 years (range 35–65 years). Intervention participants were more likely to increase daily fruit and vegetable consumption from 5 or fewer servings a day to 5 or more servings a day (OR = 1.29; 95% confidence interval [CI], 1.05–1.58) and to increase physical activity (OR = 1.47; 95% CI, 1.08–1.98) to 5 to 6 times a week for 30 minutes or more a week. The absolute differences in proportion were 3% and 4%, respectively. Intervention participants were less likely to move from not having cholesterol screening in the last 5 years to having their cholesterol measured within 5 years (OR = 0.34; 95% CI, 0.17–0.67), with an absolute difference of 15%. CONCLUSIONS Messages tailored to an individual’s familial risk for 6 common diseases modestly increased self-reported physical activity and fruit and vegetable intake but reduced the likelihood of receiving cholesterol screening.

TRIPPD: A Practice-Based Network Effectiveness Study of Postpartum Depression Screening and Management

PURPOSE Postpartum depression is common but inadequately recognized and undertreated. Continuing depressive symptoms are associated with adverse outcomes for the woman, her infant, and family. We wanted to determine the effect of a practice-based training program for screening, diagnosis, and management of depression in postpartum mothers. METHODS In this practice-based effectiveness study, 28 practices were randomized to usual care (n = 14) or intervention (n = 14), and 2,343 women were enrolled between 5 and 12 weeks’ postpartum. The intervention sites received education and tools for postpartum depression screening, diagnosis, initiation of therapy, and follow-up within their practices. Usual-care practices received a 30-minute presentation about postpartum depression. Screening information for the usual care was obtained from baseline surveys sent directly to the central site but was not available for patient care. Outcomes were based on patient-reported outcomes (level of depressive symptoms) from surveys at 6 and 12 months, plus medical record review (diagnosis and therapy initiation). RESULTS Among the 2,343 women enrolled, 1,897 (80.1%) provided outcome information, and were included in the analysis. Overall, 654 (34.5% of 1,897) women had elevated screening scores indicative of depression, with comparable rates in the intervention and usual-care groups. Among the 654 women with elevated postpartum depression screening scores, those in the intervention practices were more likely to receive a diagnosis (P = .0006) and therapy for postpartum depression (P = .002). They also had lower depressive symptom levels at 6 (P = .07) and 12 months’ (P=.001) postpartum. CONCLUSIONS Primary care–based screening, diagnosis, and management improved mother’s depression outcomes at 12 months. This practical approach could be implemented widely with modest resources.

An Electronic Practice-Based Network for Observational Comparative Effectiveness Research

Key Summary Points The Distributed Ambulatory Research in Therapeutics Network (DARTNet) is a federated network linking health data from 8 organizations representing more than 500 clinicians and more than 400 000 patients. Electronic health record and other clinical data are aggregated, standardized, and stored within each organization, then deidentified and made available for secure queries through the Web. A full set of patient data never leaves the individual clinical sites. DARTNet can be used for observational comparative effectiveness research, which may provide important information about safe and effective health care. DARTNet tools can prompt clinicians to obtain specific information during a patient encounter. Key clinical information traditionally missing in comparative effectiveness research is now available through DARTNet. The Distributed Ambulatory Research in Therapeutics Network (DARTNet) is a federated network of electronic health data that was created to facilitate advanced observational comparative effectiveness research and examine outcomes associated with prescription medications and devices. A federated network links geographically and organizationally separate databases so that a single database query can return results from multiple databases while maintaining the privacy and confidentiality of patient data. DARTNet currently links patient-level clinical data from 8 organizations representing more than 500 clinicians and more than 400000 patients. This article presents an overview of DARTNet, explains the contributions of DARTNet to the field of comparative effectiveness research, and summarizes the initial research study and lessons learned. Overview of DARTNet The Agency for Healthcare Research and Quality funded the creation of DARTNet through its Developing Evidence to Inform Decisions about Effectiveness Network. DARTNet was created to examine outcomes associated with prescription medications, devices, and various approaches to medical care. Within each member organization, DARTNet assembles patient-level information (such as vital signs, social history, family history, and physical examination findings) from electronic health records, laboratory tests, imaging results, pharmacy utilization databases, and billing systems. All of this information is put into 1 database that is deidentified and made available for secure access through the Web. Each organizations aggregated, deidentified clinical database is linked to similar databases in other DARTNet member organizations; the relationship among these databases is the federated network. The DARTNet research team can submit a precise request for information through a database query. The query runs simultaneously on each federated database, and the results provide highly detailed information about care and outcomes for hundreds of thousands of patients across the United States. The DARTNet technology currently works with 5 brands of ambulatory electronic health records, but it is capable of working with essentially any ambulatory electronic health record. In addition to facilitating queries among the standardized and federated databases, the DARTNet system can prompt clinicians to obtain specific information during a patient encounter. This capability allows the research team to collect additional data beyond what would normally be recorded in electronic records. Thus, DARTNet is designed to combine the essential elements of observational research with elements of a practical clinical trial (1). DARTNet is also designed to help support a learning community. By comparing clinical care provided across the network, high-performing practices and systems can be identified. One expectation of DARTNet membership is that high-performing sites will share their approaches to care with other members. The DARTNet staff is working to develop methods and systems to support this process. The learning community process is one of the main reasons that clinicians and practices wish to join DARTNet. Advancing the Science of Clinical Effectiveness Research By allowing examination of routine care from many clinicians, DARTNet provides insight that would not otherwise be available. Much of the current evidence base for health care depends on the results of randomized trials; however, those trials do not adequately account for the variability seen in actual care (1). Furthermore, randomized trials are not a practical way to answer important questions about the many possible variations in chronic disease treatment (1). Patients, physicians, payers, purchasers, health care administrators, and public health policymakers need better information to compare the effectiveness of treatments and thus make sound health care decisions from the individual to the national level (1). Traditionally, observational comparative effectiveness researchers examine data sets created for other purposes, such as insurance claims data. Cohorts of patients created from large populations are then compared. Statistical matching algorithms are applied to try to account for underlying clinical differences among the groups (2, 3), and the resulting analysis provides comparisons of outcomes of treatment. Although this methodology is powerful, it has been criticized because it cannot account for important clinical information not available in claims databases (4). Two brief examples demonstrate how the findings of a comparative effectiveness study might be skewed. First, a typical observational comparative effectiveness study of oral hypoglycemic medications cannot account for body mass index differences between cohorts. In addition, a comparative effectiveness examination of liver toxicity related to a particular medication would be much more robust if it could account for the use of alcohol or acetaminophen among cohort patients. DARTNet provides key missing clinical information of this type, which will advance the field of comparative effectiveness research. Research Using DARTNet To demonstrate the capabilities of DARTNet, we conducted a retrospective cohort study of patterns of use and comparative effectiveness and safety of oral diabetes medications for adults with type 2 diabetes. In phase 1 of the study, a limited set of data elements from a commercially available, integrated medical claims database (the Ingenix National Managed Care Impact database [Ingenix, Eden Prairie, Minnesota]) was used to examine the comparative effectiveness and safety of oral diabetes medications. This is a standard approach to observational comparative effectiveness research. A secondary aim was to identify limitations in claims databases for which DARTNet could supply useful and otherwise unavailable information. Phase 2 was designed to replicate phase 1 of the study, this time using DARTNet data. For phase 2, we studied a smaller patient sample but examined a broader range of data elements. We looked at electronic health record data and tested point-of-care data collection. Phase 2 findings show that DARTNet identified similarly sized panels of diabetic patients and patients receiving various oral diabetes medications, permitting analyses of similar power to the claims-based study in phase 1. In additional, DARTNet added useful clinical data (such as body weight, height, self-reported alcohol intake, and self-reported hypoglycemic events) to the analysis of comparative effectiveness of oral diabetes medications. Lessons Learned and Next Steps Our experience in developing DARTNet indicates that the system has broad utility and power. This power derives from the systems ability to access and standardize an array of data (approximately 150 data elements at this time) from various electronic health records and other clinical databases. Nonetheless, we encountered difficulty locating particular types of data in the electronic health records. It can be challenging to standardize data from separate practices, even those using the same electronic health record (5). We also found that many data fields in electronic health records lack reasonable range checks. For instance, most electronic health records will accept a systolic blood pressure in the thousands of mm Hg. Correction of these errors, although infrequent, will require work from the developers of electronic health records. DARTNet currently relies on a third-party clinical decision support system to extract and aggregate clinical data at each organization (6). The ongoing use of extracted data for clinical purposes serves as a continuous quality control feedback process: Clinicians who rely on the clinical decision support quickly recognize errors in the data and therefore routinely correct problems. Even with the use of powerful clinical decision support tools, we encountered difficulty in our attempts to view a discrete episode of care that spans multiple encounters. Many essential features linked to a given visit, including diagnoses, medication refills, and procedures, can be lost when the data are extracted for clinical decision support purposes. To improve its ability to examine episodes of care, DARTNet will include billing data to better distinguish encounters and procedures as well as focused point-of-care data collection. Even with effective decision support tools at their disposal, practices varied greatly in clinical outcomes and performance. This could be construed as a data quality issue, but it also highlights the potential for the system to add value to members through their participation in a learning community that identifies top-performing members, disseminates best practices, and provides facilitation to enhance clinical care at the practice level. The DARTNet prototype was connected to both small offices and large group practices specifically to demonstrate that it can include a wide array of organizations with varying informatics configurations, support levels, and ability to manipulate their information management environment.

Current and future use of point-of-care tests in primary care: an international survey in Australia, Belgium, The Netherlands, the UK and the USA

Objective Despite the growing number of point-of-care (POC) tests available, little research has assessed primary care clinician need for such tests. We therefore aimed to determine which POC tests they actually use or would like to use (if not currently available in their practice). Design Cross-sectional survey. Setting Primary care in Australia, Belgium (Flanders region only), the Netherlands, the UK and the USA. Participants Primary care doctors (general practitioners, family physicians). Main measures We asked respondents to (1) identify conditions for which a POC test could help inform diagnosis, (2) from a list of tests provided: evaluate which POC tests they currently use (and how frequently) and (3) determine which tests (from that same list) they would like to use in the future (and how frequently). Results 2770 primary care clinicians across five countries responded. Respondents in all countries wanted POC tests to help them diagnose acute conditions (infections, acute cardiac disease, pulmonary embolism/deep vein thrombosis), and some chronic conditions (diabetes, anaemia). Based on the list of POC tests provided, the most common tests currently used were: urine pregnancy, urine leucocytes or nitrite and blood glucose. The most commonly reported tests respondents expressed a wish to use in the future were: D-dimer, troponin and chlamydia. The UK and the USA reported a higher actual and desired use for POC tests than Australia, Belgium and the Netherlands. Our limited data suggest (but do not confirm) representativeness. Conclusions Primary care clinicians in all five countries expressed a desire for POC tests to help them diagnose a range of acute and chronic conditions. Rates of current reported use and desired future use were generally high for a small selection of POC tests, but varied across countries. Future research is warranted to explore how specific POC tests might improve primary care.

Electronic health record functionality needed to better support primary care

Electronic health records (EHRs) must support primary care clinicians and patients, yet many clinicians remain dissatisfied with their system. This article presents a consensus statement about gaps in current EHR functionality and needed enhancements to support primary care. The Institute of Medicine primary care attributes were used to define needs and meaningful use (MU) objectives to define EHR functionality. Current objectives remain focused on disease rather than the whole person, ignoring factors such as personal risks, behaviors, family structure, and occupational and environmental influences. Primary care needs EHRs to move beyond documentation to interpreting and tracking information over time, as well as patient-partnering activities, support for team-based care, population-management tools that deliver care, and reduced documentation burden. While stage 3 MUs focus on outcomes is laudable, enhanced functionality is still needed, including EHR modifications, expanded use of patient portals, seamless integration with external applications, and advancement of national infrastructure and policies.

Concordance of Edinburgh Postnatal Depression Scale (EPDS) and Patient Health Questionnaire (PHQ-9) to Assess Increased Risk of Depression among Postpartum Women

Objectives: To compare the Edinburgh Postnatal Depression Scale (EPDS) and Patient Health Questionnaire (PHQ-9) as screening tools for postpartum depression. Methods: This study population included the first 500 women to enroll and return their packets during an ongoing study of postpartum depression. Results: The primary outcome of this study was to find rates of concordance and discordance in the EPDS and PHQ-9 categories of “normal” and “increased risk for major depressive disorder.” Overall, 97% of eligible women enrolled and 70% returned the packets that included the EPDS and PHQ-9. Four hundred eighty-one of the first 500 packets had complete data, with elevated EPDS or PHQ-9 scores in 138 and 132 women, respectively. Concordance of the EPDS and PHQ-9 were present in 399 women (83%): 326 (67.8%) had “normal” score on both, and 73 (15.2%) had elevated scores for both. Discordant scores in 82 women included 17 with elevated PHQ-9 scores but normal EPDS scores and 65 with elevated EPDS scores and PHQ-9 scores <10. In multivariate logistic regression modeling, only age >30 and low education level were predictive of discordant scores, using EPDS and PHQ-9 scores of ≥10 as elevated (odds ratio, 1.9 and P = .02; and odds ratio, 2.3 and P = .01, respectively). PHQ-9 scores of 5 to 9 have been referred to as consistent with “mild depressive symptoms” and appropriate for “watchful waiting” and repeat PHQ-9 at follow-up. Using this follow-up approach would require re-evaluation of 120 (25%) of the women screened. Conclusions: Postpartum depression screening is feasible in primary care practices, and for most women the EPDS and PHQ-9 scores were concordant. Further work is required to identify reasons for the 17% discordant scores as well as to provide definitive recommendations for PHQ-9 scores of 5 to 9.

Rates of 5 Common Antidepressant Side Effects Among New Adult and Adolescent Cases of Depression: A Retrospective US Claims Study

BACKGROUND Antidepressants are the first-line treatment for depression, yet medication-related side effects may be associated with antidepressant discontinuation before reaching a period of exposure believed to result in effectiveness. There is a gap in knowledge of the prevalence of side effects across commonly prescribed antidepressants and the effect of the type of antidepressant on the likelihood of side effects in real-world clinical practice. OBJECTIVE The aim of this study was to estimate and compare the prevalence of headaches, nausea or vomiting, agitation, sedation, and sexual dysfunction among patients diagnosed with depression who initiated monotherapy across different classes of antidepressants and to estimate the effect of the type of antidepressant on the likelihood of each of the 5 side effects. METHODS A retrospective cohort of patients aged ≥13 who were newly diagnosed with depression and began antidepressant monotherapy was created using LifeLink managed care claims from 1998 to 2008. Antidepressant groups included selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants (TCAs), monoamine oxidase inhibitors (MAOIs), bupropion, phenylpiperazine, and tetracyclic antidepressants. Prevalence of headache, nausea or vomiting, agitation, sedation, and sexual dysfunction were compared across antidepressant groups. Propensity-adjusted Cox proportional hazards regression was used to estimate the likelihood of each of the 5 side effects for each antidepressant group compared with SSRIs, adjusted for demographic, clinical, and treatment characteristics. RESULTS The study cohort included 40,017 patients (3617 adolescents, aged 13-18 years, and 36,400 adults, aged ≥19 years; mean age = 45 years; 67% female) with a new episode of depression who were initiated on antidepressant monotherapy within 30 days of diagnosis (SSRI [66%], bupropion [14%], SNRI [12%], other [8%]). The most common side effects were headache (up to 17/1000 person-months of therapy in adults and adolescents) and nausea (up to 7.2/1000 in adults, 9.3/1000 in adolescents). Relative to adults receiving SSRIs, adults receiving SNRIs had a higher risk of nausea (hazard ratio [HR] = 1.26; 95%CI,1.05-1.51). Adults (HR = 0.78; 95% CI, 0.62-0.96) and adolescents (HR = 0.43; 95% CI, 0.21-0.87) taking bupropion were less likely to experience headaches compared with adults and adolescents, respectively, taking an SSRI. Adolescents receiving a tetracyclic were more likely to experience headaches than adolescents receiving an SSRI (HR = 3.16; 95%CI, 1.13-8.84). CONCLUSIONS Prevalence and risk of the 5 side effects varied across types of antidepressants for both adults and adolescents. Results from this study were consistent with prior clinical trials, suggesting that variation in side effect profiles exists in a more generalized managed care population.

Combining Web-Based and Mail Surveys Improves Response Rates: A PBRN Study From PRIME Net

PURPOSE The advent of Web-based survey tools has provided the investigator with an alternative to paper-based survey methods that in many instances may be less expensive to implement than traditional paper-based surveys. Newer technology, however, does not diminish the importance of obtaining an adequate response rate. METHODS We analyzed response rate data obtained from a survey implemented across 3 practice-based research networks (PBRNs) in which the survey was first implemented electronically with 5 rounds of electronic solicitation for an Internet-based questionnaire and then by 2 rounds of a paper-based version mailed only to nonresponders. RESULTS Overall, 24% of the total survey responses received were in the paper mode despite intense promotion of the survey in the electronic phase. CONCLUSIONS Our results suggest there is still an important role for the use of paper-based methods in PBRN survey research. Both hard copy and electronic survey collection methods may be required to enhance clinician response rates in PBRNs.

Describing primary care encounters: the Primary Care Network Survey and the National Ambulatory Medical Care Survey.

PURPOSE The purpose of this study was to describe clinical encounters in primary care research networks and compare them with those of the National Ambulatory Medical Care Survey (NAMCS). METHODS Twenty US primary care research networks collected data on clinicians and patient encounters using the Primary Care Network Survey (PRINS) Clinician Interview (PRINS-1) and Patient Record (PRINS-2), which were newly developed based on NAMCS tools. Clinicians completed a PRINS-1 about themselves and a PRINS-2 for each of 30 patient visits. Data included patient characteristics; reason for the visit, diagnoses, and services ordered or performed. We compared PRINS data with data obtained from primary care physicians during 5 cycles of NAMCS (1997–2001). Data were weighted; PRINS reflects participating networks and NAMCS provides national estimates. RESULTS By discipline, 89% of PRINS clinicians were physicians, 4% were physicians in residency training, 5% were advanced practice nurses/nurse-practitioners, and 2% were physician’s assistants. The majority (53%) specialized in pediatrics (34% specialized in family medicine, 9% in internal medicine, and 4% in other specialties). All NAMCS clinicians were physicians, with 20% specializing in pediatrics. When NAMCS and PRINS visits were compared, larger proportions of PRINS visits involved preventive care and were made by children, members of minority racial groups, and individuals who did not have private health insurance. A diagnostic or other assessment service was performed for 99% of PRINS visits and 76% of NAMCS visits (95% confidence interval, 74.9%–78.0%). A preventive or counseling/education service was provided at 64% of PRINS visits and 37% of NAMCS visits (95% confidence interval, 35.1%–38.0%). CONCLUSIONS PRINS presents a view of diverse primary care visits and differs from NAMCS in its methods and findings. Further examinations of PRINS data are needed to assess their usefulness for describing encounters that occur in primary care research networks.