Person: Wright, Adam
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Wright, Adam
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Publication Ability to Generate Patient Registries Among Practices With and Without Electronic Health Records(JMIR Publications Inc., 2009-08-10) Wright, Adam; McGlinchey, Elizabeth A; Poon, Eric G; Jenter, Chelsea A; Bates, David; Simon, Steven R; Simon, StevenBackground: The ability to generate registries of patients with particular clinical attributes, such as diagnoses or medications taken, is central to measuring and improving the quality of health care. However, it is not known how many providers have the ability to generate such registries. Objectives: To assess the proportion of physician practices that can construct registries of patients with specific diagnoses, laboratory results, or medications, and to determine the relationship between electronic health record (EHR) usage and the ability to perform registry functions. Methods: We conducted a mail survey of a stratified random sample of physician practices in Massachusetts in the northeastern United States (N = 1884). The survey included questions about the physicians’ ability to generate diagnosis, laboratory result, and medication registries; the presence of EHR; and usage of specific EHR features. Results: Theresponseratewas71%(1345/1884).Overall,79.8%ofphysicianpracticesreportedbeingabletogenerateregistries of patients by diagnosis; 56.1% by laboratory result; and 55.8% by medication usage. In logistic regression analyses, adjusting for urban/rural location, practice size and ownership, teaching status, hospital affiliation, and specialty, physician practices with an EHR were more likely to be able to construct diagnosis registries (adjusted odds ratio [OR] 1.53, 95% confidence interval [CI] 1.25 - 1.86), laboratory registries (OR 1.42, 95% CI 1.22 - 1.66), and medication registries (OR 2.30, 95% CI 1.96 - 2.70). Conclusions: Many physician practices were able to generate registries, but this capability is far from universal. Adoption of EHRs appears to be a useful step toward this end, and practices with EHRs are considerably more likely to be able to carry out registry functions. Because practices need registries to perform broad-based quality improvement, they should consider adopting EHRs that have built-in registry functionality.Publication Preoperative Hyponatremia and Perioperative Complications(American Medical Association (AMA), 2012-10-22) Leung, Alexander A.; McAlister, Finlay A.; Rogers, Selwyn O.; Pazo, Valeria; Bates, David W.; Wright, AdamBackground Although hyponatremia has been linked to increased morbidity and mortality in a variety of medical conditions, its association with perioperative outcomes remains uncertain. Methods To determine whether preoperative hyponatremia is a predictor of 30-day perioperative morbidity and mortality, we conducted a cohort study using the American College of Surgeons National Surgical Quality Improvement Program database to identify 964 263 adults undergoing major surgery from more than 200 hospitals (from January 1, 2005, to December 31, 2010) and observed them for 30-day perioperative outcomes. We used multivariable logistic regression to estimate relative risks for death, major coronary events, wound infections, and pneumonia occurring within 30 days of surgery and quantile regression to estimate differences in average length of hospital stay. Results A total of 75 423 patients with preoperative hyponatremia (sodium level <135 mEq/L [to convert to millimoles per liter, multiply by 1.0]) were compared with 888 840 patients with normal baseline sodium levels (135-144 mEq/L). Preoperative hyponatremia was associated with a higher risk of 30-day mortality (5.2% vs 1.3%; adjusted odds ratio [aOR], 1.44; 95% CI, 1.38-1.50), and this finding was consistent in all the subgroups. This association was particularly marked in patients undergoing nonemergency surgery (aOR, 1.59; 95% CI, 1.50-1.69; P < .001 for interaction) and American Society of Anesthesiologists class 1 and 2 patients (aOR, 1.93; 95% CI, 1.57-2.36; P < .001 for interaction). Furthermore, hyponatremia was associated with a greater risk of perioperative major coronary events (1.8% vs 0.7%; aOR, 1.21; 95% CI, 1.14-1.29), wound infections (7.4% vs 4.6%; 1.24; 1.20-1.28), and pneumonia (3.7% vs 1.5%; 1.17; 1.12-1.22) and prolonged median lengths of stay by approximately 1 day. Conclusion Preoperative hyponatremia is a prognostic marker for perioperative 30-day morbidity and mortality. Hyponatremia is common, is potentially reversible, and has important consequences in a variety of clinical conditions. Furthermore, the concept of “asymptomatic” hyponatremia has been questioned, as even those with mild hyponatremia are recognized to be at increased risk for serious adverse outcomes. Among hospitalized patients, the presence of hyponatremia has been associated with increased mortality, prolonged lengths of stay, and greater utilization costs. However, most existing studies have focused on patients admitted to medical services. As such, the association between preoperative hyponatremia and perioperative outcomes remains largely unexplored. Although the preoperative period offers unique opportunities for physicians to perform risk stratification, anticipate complications, improve perioperative care, and, in some cases, intervene on modifiable risks, the implications of hyponatremia detected preoperatively are unclear. Therefore, we designed this study to evaluate the prognostic implications of preoperative hyponatremia on selected perioperative outcomes across a broad range of surgical conditions.Publication Electronic problem list documentation of chronic kidney disease and quality of care(BioMed Central, 2014) Samal, Lipika; Linder, Jeffrey A; Bates, David; Wright, AdamBackground: Chronic kidney disease (CKD) is increasingly common and under-recognized in primary care clinics, leading to low rates of stage-appropriate monitoring and treatment. Our objective was to determine whether electronic problem list documentation of CKD is associated with monitoring and treatment. Methods: This is a cross-sectional observational study of patients with stage 3 or 4 CKD, defined as two past estimated glomerular filtration rates (eGFR) 15-60 mL/min/1.73 m2 separated by 90 days and collected between 2007-2008. We examined the association of problem list documentation with: 1) serum eGFR monitoring test, 2) urine protein or albumin monitoring test, 3) an angiotensin converting enzyme inhibitor or angiotensin receptor blocker (ACE/ARB) prescription, 4) mean systolic blood pressure (BP), and 5) BP control. Results: Out of 3,149 patients with stage 3 or 4 CKD, only 16% of patients had CKD documented on the problem list. After adjustment for eGFR, gender, and race/ethnicity and after clustering by physician, problem list documentation of CKD was associated with serum eGFR testing (97% with problem list documentation vs. 94% without problem list documentation, p = 0.02) and urine protein testing (47% with problem list documentation vs. 40% without problem list documentation, p = 0.04). After adjustment, problem list documentation was not associated with ACE/ARB prescription, mean systolic BP, or BP control. Conclusions: Documentation of CKD on the electronic problem list is rare. Patients with CKD documentation have better stage-appropriate monitoring of the disease, but do not have higher rates of blood pressure treatment or better blood pressure control. Interventions aimed at increasing documentation of CKD on the problem list may improve stage-appropriate monitoring, but may not improve clinical outcomes.Publication Standard practices for computerized clinical decision support in community hospitals: a national survey(BMJ Group, 2012) Ash, Joan S; McCormack, James L; Sittig, Dean F; Wright, Adam; McMullen, Carmit; Bates, DavidObjective: Computerized provider order entry (CPOE) with clinical decision support (CDS) can help hospitals improve care. Little is known about what CDS is presently in use and how it is managed, however, especially in community hospitals. This study sought to address this knowledge gap by identifying standard practices related to CDS in US community hospitals with mature CPOE systems. Materials and Methods Representatives of 34 community hospitals, each of which had over 5 years experience with CPOE, were interviewed to identify standard practices related to CDS. Data were analyzed with a mix of descriptive statistics and qualitative approaches to the identification of patterns, themes and trends. Results: This broad sample of community hospitals had robust levels of CDS despite their small size and the independent nature of many of their physician staff members. The hospitals uniformly used medication alerts and order sets, had sophisticated governance procedures for CDS, and employed staff to customize CDS. Discussion The level of customization needed for most CDS before implementation was greater than expected. Customization requires skilled individuals who represent an emerging manpower need at this type of hospital. Conclusion: These results bode well for robust diffusion of CDS to similar hospitals in the process of adopting CDS and suggest that national policies to promote CDS use may be successful.Publication A qualitative study of the activities performed by people involved in clinical decision support: recommended practices for success(BMJ Publishing Group, 2014) Wright, Adam; Ash, Joan S; Erickson, Jessica L; Wasserman, Joe; Bunce, Arwen; Stanescu, Ana; St Hilaire, Daniel; Panzenhagen, Morgan; Gebhardt, Eric; McMullen, Carmit; Middleton, Blackford; Sittig, Dean FObjective: To describe the activities performed by people involved in clinical decision support (CDS) at leading sites. Materials and methods We conducted ethnographic observations at seven diverse sites with a history of excellence in CDS using the Rapid Assessment Process and analyzed the data using a series of card sorts, informed by Linstone's Multiple Perspectives Model. Results: We identified 18 activities and grouped them into four areas. Area 1: Fostering relationships across the organization, with activities (a) training and support, (b) visibility/presence on the floor, (c) liaising between people, (d) administration and leadership, (e) project management, (f) cheerleading/buy-in/sponsorship, (g) preparing for CDS implementation. Area 2: Assembling the system with activities (a) providing technical support, (b) CDS content development, (c) purchasing products from vendors (d) knowledge management, (e) system integration. Area 3: Using CDS to achieve the organization's goals with activities (a) reporting, (b) requirements-gathering/specifications, (c) monitoring CDS, (d) linking CDS to goals, (e) managing data. Area 4: Participation in external policy and standards activities (this area consists of only a single activity). We also identified a set of recommendations associated with these 18 activities. Discussion All 18 activities we identified were performed at all sites, although the way they were organized into roles differed substantially. We consider these activities critical to the success of a CDS program. Conclusions: A series of activities are performed by sites strong in CDS, and sites adopting CDS should ensure they incorporate these activities into their efforts.Publication Measuring agreement between decision support reminders: the cloud vs. the local expert(BioMed Central, 2014) Dixon, Brian Edward; Simonaitis, Linas; Perkins, Susan M; Wright, Adam; Middleton, BlackfordBackground: A cloud-based clinical decision support system (CDSS) was implemented to remotely provide evidence-based guideline reminders in support of preventative health. Following implementation, we measured the agreement between preventive care reminders generated by an existing, local CDSS and the new, cloud-based CDSS operating on the same patient visit data. Methods: Electronic health record data for the same set of patients seen in primary care were sent to both the cloud-based web service and local CDSS. The clinical reminders returned by both services were captured for analysis. Cohen’s Kappa coefficient was calculated to compare the two sets of reminders. Kappa statistics were further adjusted for prevalence and bias due to the potential effects of bias in the CDS logic and prevalence in the relative small sample of patients. Results: The cloud-based CDSS generated 965 clinical reminders for 405 patient visits over 3 months. The local CDSS returned 889 reminders for the same patient visit data. When adjusted for prevalence and bias, observed agreement varied by reminder from 0.33 (95% CI 0.24 – 0.42) to 0.99 (95% CI 0.97 – 1.00) and demonstrated almost perfect agreement for 7 of the 11 reminders. Conclusions: Preventive care reminders delivered by two disparate CDS systems show substantial agreement. Subtle differences in rule logic and terminology mapping appear to account for much of the discordance. Cloud-based CDSS therefore show promise, opening the door for future development and implementation in support of health care providers with limited resources for knowledge management of complex logic and rules.Publication Variation in high-priority drug-drug interaction alerts across institutions and electronic health records(Oxford University Press, 2016) McEvoy, Dustin S; Sittig, Dean F; Hickman, Thu-Trang; Aaron, Skye; Ai, Angela; Amato, Mary; Bauer, David W; Fraser, Gregory M; Harper, Jeremy; Kennemer, Angela; Krall, Michael A; Lehmann, Christoph U; Malhotra, Sameer; Murphy, Daniel R; O’Kelley, Brandi; Samal, Lipika; Schreiber, Richard; Singh, Hardeep; Thomas, Eric J; Vartian, Carl V; Westmorland, Jennifer; McCoy, Allison B; Wright, AdamObjective: The United States Office of the National Coordinator for Health Information Technology sponsored the development of a “high-priority” list of drug-drug interactions (DDIs) to be used for clinical decision support. We assessed current adoption of this list and current alerting practice for these DDIs with regard to alert implementation (presence or absence of an alert) and display (alert appearance as interruptive or passive). Materials and methods: We conducted evaluations of electronic health records (EHRs) at a convenience sample of health care organizations across the United States using a standardized testing protocol with simulated orders. Results: Evaluations of 19 systems were conducted at 13 sites using 14 different EHRs. Across systems, 69% of the high-priority DDI pairs produced alerts. Implementation and display of the DDI alerts tested varied between systems, even when the same EHR vendor was used. Across the drug pairs evaluated, implementation and display of DDI alerts differed, ranging from 27% (4/15) to 93% (14/15) implementation. Discussion: Currently, there is no standard of care covering which DDI alerts to implement or how to display them to providers. Opportunities to improve DDI alerting include using differential displays based on DDI severity, establishing improved lists of clinically significant DDIs, and thoroughly reviewing organizational implementation decisions regarding DDIs. Conclusion: DDI alerting is clinically important but not standardized. There is significant room for improvement and standardization around evidence-based DDIs.Publication Multiple perspectives on clinical decision support: a qualitative study of fifteen clinical and vendor organizations(BioMed Central, 2015) Ash, Joan S; Sittig, Dean F; McMullen, Carmit K; Wright, Adam; Bunce, Arwen; Mohan, Vishnu; Cohen, Deborah J; Middleton, BlackfordBackground: Computerized clinical decision support (CDS) can help hospitals to improve healthcare. However, CDS can be problematic. The purpose of this study was to discover how the views of clinical stakeholders, CDS content vendors, and EHR vendors are alike or different with respect to challenges in the development, management, and use of CDS. Methods: We conducted ethnographic fieldwork using a Rapid Assessment Process within ten clinical and five health information technology (HIT) vendor organizations. Using an inductive analytical approach, we generated themes from the clinical, content vendor, and electronic health record vendor perspectives and compared them. Results: The groups share views on the importance of appropriate manpower, careful knowledge management, CDS that fits user workflow, the need for communication among the groups, and for mutual strategizing about the future of CDS. However, views of usability, training, metrics, interoperability, product use, and legal issues differed. Recommendations for improvement include increased collaboration to address legal, manpower, and CDS sharing issues. Conclusions: The three groups share thinking about many aspects of CDS, but views differ in a number of important respects as well. Until these three groups can reach a mutual understanding of the views of the other stakeholders, and work together, CDS will not reach its potential.Publication Nephrology co-management versus primary care solo management for early chronic kidney disease: a retrospective cross-sectional analysis(BioMed Central, 2015) Samal, Lipika; Wright, Adam; Waikar, Sushrut; Linder, Jeffrey ABackground: Primary care physicians (PCPs) typically manage early chronic kidney disease (CKD), but recent guidelines recommend nephrology co-management for some patients with stage 3 CKD and all patients with stage 4 CKD. We sought to compare quality of care for co-managed patients to solo managed patients. Methods: We conducted a retrospective cross-sectional analysis. Patients included in the study were adults who visited a PCP during 2009 with laboratory evidence of CKD in the preceding two years, defined as two estimated glomerular filtration rates (eGFR) between 15–59 mL/min/1.73 m2 separated by 90 days. We assessed process measures (serum eGFR test, urine protein/albumin test, angiotensin converting enzyme inhibitor or angiotensin receptor blocker [ACE/ARB] prescription, and several tests monitoring for complications) and intermediate clinical outcomes (mean blood pressure and blood pressure control) and performed subgroup analyses by CKD stage. Results: Of 3118 patients, 11 % were co-managed by a nephrologist. Co-management was associated with younger age (69 vs. 74 years), male gender (46 % vs. 34 %), minority race/ethnicity (black 32 % vs. 22 %; Hispanic 13 % vs. 8 %), hypertension (75 % vs. 66 %), diabetes (42 % vs. 26 %), and more PCP visits (5.0 vs. 3.9; p < 0.001 for all comparisons). After adjustment, co-management was associated with serum eGFR test (98 % vs. 94 %, p = <0.0001), urine protein/albumin test (82 % vs 36 %, p < 0.0001), and ACE/ARB prescription (77 % vs. 69 %, p = 0.03). Co-management was associated with monitoring for anemia and metabolic bone disease, but was not associated with lipid monitoring, differences in mean blood pressure (133/69 mmHg vs. 131/70 mmHg, p > 0.50) or blood pressure control. A subgroup analysis of Stage 4 CKD patients did not show a significant association between co-management and ACE/ARB prescription (80 % vs. 73 %, p = 0.26). Conclusion: For stage 3 and 4 CKD patients, nephrology co-management was associated with increased stage-appropriate monitoring and ACE/ARB prescribing, but not improved blood pressure control.Publication Measuring patient-perceived quality of care in US hospitals using Twitter(BMJ Publishing Group, 2016) Hawkins, Jared; Brownstein, John; Tuli, Gaurav; Runels, Tessa; Broecker, Katherine; Nsoesie, Elaine O; McIver, David J; Rozenblum, Ronen; Wright, Adam; Bourgeois, Florence; Greaves, FelixBackground: Patients routinely use Twitter to share feedback about their experience receiving healthcare. Identifying and analysing the content of posts sent to hospitals may provide a novel real-time measure of quality, supplementing traditional, survey-based approaches. Objective: To assess the use of Twitter as a supplemental data stream for measuring patient-perceived quality of care in US hospitals and compare patient sentiments about hospitals with established quality measures. Design: 404 065 tweets directed to 2349 US hospitals over a 1-year period were classified as having to do with patient experience using a machine learning approach. Sentiment was calculated for these tweets using natural language processing. 11 602 tweets were manually categorised into patient experience topics. Finally, hospitals with ≥50 patient experience tweets were surveyed to understand how they use Twitter to interact with patients. Key results Roughly half of the hospitals in the US have a presence on Twitter. Of the tweets directed toward these hospitals, 34 725 (9.4%) were related to patient experience and covered diverse topics. Analyses limited to hospitals with ≥50 patient experience tweets revealed that they were more active on Twitter, more likely to be below the national median of Medicare patients (p<0.001) and above the national median for nurse/patient ratio (p=0.006), and to be a non-profit hospital (p<0.001). After adjusting for hospital characteristics, we found that Twitter sentiment was not associated with Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) ratings (but having a Twitter account was), although there was a weak association with 30-day hospital readmission rates (p=0.003). Conclusions: Tweets describing patient experiences in hospitals cover a wide range of patient care aspects and can be identified using automated approaches. These tweets represent a potentially untapped indicator of quality and may be valuable to patients, researchers, policy makers and hospital administrators.