Impact of family-centered tailoring of pediatric diabetes self-management resources.

BACKGROUND: The American Diabetes Association recommends a family-centered approach that addresses each family's specific type 1 diabetes self-management barriers. OBJECTIVE: To assess an intervention that tailored delivery of self-management resources to families' specific self-management barriers. SUBJECTS: At two sites, 214 children 8-16 years old with type 1 diabetes and their parent(s) were randomized to receive tailored self-management resources (intervention, n = 106) or usual care (n = 108). METHODS: Our intervention (1) identified families' self-management barriers with a validated survey, (2) tailored self-management resources to identified barriers, and (3) delivered the resources as four group sessions coordinated with diabetes visits. Mixed effects models with repeated measures were fit to A1c as well as parent and child QOL during the intervention and 1 year thereafter. RESULTS: Participants were 44% youth (8-12 years) and 56% teens (13-16 years). No intervention effect on A1c or QOL was shown, combining data from sites and age groups. Analyzing results by site and age group, post-intervention A1c for teens at one site declined by 0.06 more per month for intervention teens compared to usual care (P < 0.05). In this group, post-intervention A1c declined significantly when baseline A1c was >8.5 (-0.08, P < 0.05), with an even larger decline when baseline A1c was >10 (-0.19, P < 0.05). In addition, for these teens, the significant improvements in A1c resulted from addressing barriers related to motivation to self-manage. Also at this site, mean QOL increased by 0.61 points per month more during the intervention for parents of intervention youth than for usual care youth (P < 0.05). CONCLUSIONS: Tailored self-management resources may improve outcomes among specific populations, suggesting the need to consider families' self-management barriers and patient characteristics before implementing self-management resources.

Application of participatory ergonomics to the redesign of the family-centred rounds process.

Participatory ergonomics (PE) can promote the application of human factors and ergonomics (HFE) principles to healthcare system redesign. This study applied a PE approach to redesigning the family-centred rounds (FCR) process to improve family engagement. Various FCR stakeholders (e.g. patients and families, physicians, nurses, hospital management) were involved in different stages of the PE process. HFE principles were integrated in both the content (e.g. shared mental model, usability, workload consideration, systems approach) and process (e.g. top management commitment, stakeholder participation, communication and feedback, learning and training, project management) of FCR redesign. We describe activities of the PE process (e.g. formation and meetings of the redesign team, data collection activities, intervention development, intervention implementation) and present data on PE process evaluation. To demonstrate the value of PE-based FCR redesign, future research should document its impact on FCR process measures (e.g. family engagement, round efficiency) and patient outcome measures (e.g. patient satisfaction).

Sequence patterns in the resolution of clinical instabilities in community-acquired pneumonia and association with outcomes.

BACKGROUND: In patients hospitalized with community-acquired pneumonia (CAP), indicators of clinical instability at discharge (fever, tachycardia, tachypnea, hypotension, hypoxia, decreased oral intake and altered mental status) are associated with poor outcomes. It is not known whether the order of indicator stabilization is associated with outcomes. OBJECTIVES: To describe variation in the sequences, including whether and in what order, indicators of clinical instability resolve among patients hospitalized with CAP, and to assess associations between patterns of stabilization and patient-level outcomes. DESIGN/PARTICIPANTS / MAIN MEASURES: Chart review ascertained whether and when indicators stabilized and other data for 1,326 adult CAP patients in six U.S. academic medical centers. The sequences of indicator stabilization were characterized using sequence analysis and grouped using cluster analysis. Associations between sequence patterns and 30-day mortality, length of stay (LOS), and total costs were modeled using regression analysis. KEY RESULTS: We found 986 unique sequences of indicator stabilization. Sequence analysis identified eight clusters of sequences (patterns) derived by the order or speed in which instabilities resolved or remained at discharge and inpatient mortality. Two of the clusters (56% of patients) were characterized by almost complete stabilization prior to discharge alive, but differing in the rank orders of four indicators and time to maximum stabilization. Five other clusters (42% of patients) were characterized by one to three instabilities at discharge with variable orderings of indicator stabilization. In models with fast and almost complete stabilization as the referent, 30-day mortality was lowest in clusters with slow and almost complete stabilization or tachycardia or fever at discharge [OR = 0.73, 95% CI = (0.28-1.92)], and highest in those with hypoxia with instabilities in mental status or oral intake at discharge [OR = 3.99, 95% CI = (1.68-9.50)]. CONCLUSIONS: Sequences of clinical instability resolution exhibit great heterogeneity, yet certain sequence patterns may be associated with differences in days to maximum stabilization, mortality, LOS, and hospital costs.

Rationale and design of the Multicenter Medication Reconciliation Quality Improvement Study (MARQUIS).

BACKGROUND: Unresolved medication discrepancies during hospitalization can contribute to adverse drug events, resulting in patient harm. Discrepancies can be reduced by performing medication reconciliation; however, effective implementation of medication reconciliation has proven to be challenging. The goals of the Multi-Center Medication Reconciliation Quality Improvement Study (MARQUIS) are to operationalize best practices for inpatient medication reconciliation, test their effect on potentially harmful unintentional medication discrepancies, and understand barriers and facilitators of successful implementation. METHODS: Six U.S. hospitals are participating in this quality improvement mentored implementation study. Each hospital has collected baseline data on the primary outcome: the number of potentially harmful unintentional medication discrepancies per patient, as determined by a trained on-site pharmacist taking a "gold standard" medication history. With the guidance of their mentors, each site has also begun to implement one or more of 11 best practices to improve medication reconciliation. To understand the effect of the implemented interventions on hospital staff and culture, we are performing mixed methods program evaluation including surveys, interviews, and focus groups of front line staff and hospital leaders. DISCUSSION: At baseline the number of unintentional medication discrepancies in admission and discharge orders per patient varies by site from 2.35 to 4.67 (mean=3.35). Most discrepancies are due to history errors (mean 2.12 per patient) as opposed to reconciliation errors (mean 1.23 per patient). Potentially harmful medication discrepancies averages 0.45 per patient and varies by site from 0.13 to 0.82 per patient. We discuss several barriers to implementation encountered thus far. In the end, we anticipate that MARQUIS tools and lessons learned have the potential to decrease medication discrepancies and improve patient outcomes. TRIAL REGISTRATION: Clinicaltrials.gov identifier NCT01337063.

Safer Type 1 Diabetes Care at Home: SEIPS-based Process Mapping with Parents and Clinicians.

Introduction: The limited data indicate that pediatric medical errors in the outpatient setting, including at home, are common. This study is the first step of our Ambulatory Pediatric Patient Safety Learning Lab to address medication errors and treatment delays among children with T1D in the outpatient setting. We aimed to identify failures and potential solutions associated with medication errors and treatment delays among outpatient children with T1D. Methods: A transdisciplinary team of parents, safety researchers, and clinicians used Systems Engineering Initiative for Patient Safety (SEIPS) based process mapping of data we collected through in-home medication review, observation of administration, chart reviews, parent surveys, and failure modes and effects analysis (FMEA). Results: Eight (57%) of the 14 children who had home visits experienced 18 errors (31 per 100 medications). Four errors in two children resulted in harm, and 13 had the potential for harm. Two injuries occurred when parents failed to treat severe hypoglycemia and lethargy, and two were due to repeated failures to administer insulin at home properly. In SEIPS-based process maps, high-risk errors occurred during communication between the clinic and home or in management at home. Two FMEAs identified interventions to better communicate with families and support home care, especially during evolving illness. Conclusion: Using SEIPS-based process maps informed by multimodal methods to identify medication errors and treatment delays, we found errors were common. Better support for managing acute illness at home and improved communication between the clinic and home are potentially high-yield interventions.

What works in medication reconciliation: an on-treatment and site analysis of the MARQUIS2 study.

BACKGROUND: The second Multicenter Medication Reconciliation Quality Improvement Study demonstrated a marked reduction in medication discrepancies per patient. The aim of the current analysis was to determine the association of patient exposure to each system-level intervention and receipt of each patient-level intervention on these results. METHODS: This study was conducted at 17 North American Hospitals, the study period was 18 months per site, and sites typically adopted interventions after 2-5 months of preintervention data collection. We conducted an on-treatment analysis (ie, an evaluation of outcomes based on patient exposure) of system-level interventions, both at the category level and at the individual component level, based on monthly surveys of implementation site leads at each site (response rate 65%). We then conducted a similar analysis of patient-level interventions, as determined by study pharmacist review of documented activities in the medical record. We analysed the association of each intervention on the adjusted number of medication discrepancies per patient in admission and discharge orders, based on a random sample of up to 22 patients per month per site, using mixed-effects Poisson regression with hospital site as a random effect. We then used a generalised linear mixed-effects model (GLMM) decision tree to determine which patient-level interventions explained the most variance in discrepancy rates. RESULTS: Among 4947 patients, patient exposure to seven of the eight system-level component categories was associated with modest but significant reductions in discrepancy rates (adjusted rate ratios (ARR) 0.75-0.97), as were 15 of the 17 individual system-level intervention components, including hiring, reallocating and training personnel to take a best possible medication history (BPMH) and training personnel to perform discharge medication reconciliation and patient counselling. Receipt of five of seven patient-level interventions was independently associated with large reductions in discrepancy rates, including receipt of a BPMH in the emergency department (ED) by a trained clinician (ARR 0.40, 95% CI 0.37 to 0.43), admission medication reconciliation by a trained clinician (ARR 0.57, 95% CI 0.50 to 0.64) and discharge medication reconciliation by a trained clinician (ARR 0.64, 95% CI 0.57 to 0.73). In GLMM decision tree analyses, patients who received both a BPMH in the ED and discharge medication reconciliation by a trained clinician experienced the lowest discrepancy rates (0.08 per medication per patient). CONCLUSION AND RELEVANCE: Patient-level interventions most associated with reductions in discrepancies were receipt of a BPMH of admitted patients in the ED and admission and discharge medication reconciliation by a trained clinician. System-level interventions were associated with modest reduction in discrepancies for the average patient but are likely important to support patient-level interventions and may reach more patients. These findings can be used to help hospitals and health systems prioritise interventions to improve medication safety during care transitions.

Worklife and satisfaction of hospitalists: toward flourishing careers.

BACKGROUND: The number of hospitalists in the US is growing rapidly, yet little is known about their worklife to inform whether hospital medicine is a viable long-term career for physicians. OBJECTIVE: Determine current satisfaction levels among hospitalists. DESIGN: Survey study. METHODS: A national random stratified sample of 3,105 potential hospitalists plus 662 hospitalist employees of three multi-state hospitalist companies were administered the Hospital Medicine Physician Worklife Survey. Using 5-point Likert scales, the survey assessed demographic information, global job and specialty satisfaction, and 11 satisfaction domains: workload, compensation, care quality, organizational fairness, autonomy, personal time, organizational climate, and relationships with colleagues, staff, patients, and leader. Relationships between global satisfaction and satisfaction domains, and burnout symptoms and career longevity were explored. RESULTS: There were 816 hospitalist responses (adjusted response rate, 25.6%). Correcting for oversampling of pediatricians, 33.5% of respondents were women, and 7.4% were pediatricians. Overall, 62.6% of respondents reported high satisfaction (≥4 on a 5-point scale) with their job, and 69.0% with their specialty. Hospitalists were most satisfied with the quality of care they provided and relationships with staff and colleagues. They were least satisfied with organizational climate, autonomy, compensation, and availability of personal time. In adjusted analysis, satisfaction with organizational climate, quality of care provided, organizational fairness, personal time, relationship with leader, compensation, and relationship with patients predicted job satisfaction. Satisfaction with personal time, care quality, patient relationships, staff relationships, and compensation predicted specialty satisfaction. Job burnout symptoms were reported by 29.9% of respondents who were more likely to leave and reduce work effort. CONCLUSIONS: Hospitalists rate their job and specialty satisfaction highly, but burnout symptoms are common. Hospitalist programs should focus on organizational climate, organizational fairness, personal time, and compensation to improve satisfaction and minimize attrition.

Effects of a refined evidence-based toolkit and mentored implementation on medication reconciliation at 18 hospitals: results of the MARQUIS2 study.

BACKGROUND: The first Multicenter Medication Reconciliation Quality Improvement (QI) Study (MARQUIS1) demonstrated that mentored implementation of a medication reconciliation best practices toolkit decreased total unintentional medication discrepancies in five hospitals, but results varied by site. The objective of this study was to determine the effects of a refined toolkit on a larger group of hospitals. METHODS: We conducted a pragmatic quality improvement study (MARQUIS2) at 18 North American hospitals or hospital systems from 2016 to 2018. Incorporating lessons learnt from MARQUIS1, we implemented a refined toolkit, offering 17 system-level and 6 patient-level interventions. One of eight physician mentors coached each site via monthly calls and performed one to two site visits. The primary outcome was number of unintentional medication discrepancies in admission or discharge orders per patient. Time series analysis used multivariable Poisson regression. RESULTS: A total of 4947 patients were sampled, including 1229 patients preimplementation and 3718 patients postimplementation. Both the number of system-level interventions adopted per site and the proportion of patients receiving patient-level interventions increased over time. During the intervention, patients experienced a steady decline in their medication discrepancy rate from 2.85 discrepancies per patient to 0.98 discrepancies per patient. An interrupted time series analysis of the 17 sites with sufficient data for analysis showed the intervention was associated with a 5% relative decrease in discrepancies per month over baseline temporal trends (adjusted incidence rate ratio: 0.95, 95% CI 0.93 to 0.97, p<0.001). Receipt of patient-level interventions was associated with decreased discrepancy rates, and these associations increased over time as sites adopted more system-level interventions. CONCLUSION: A multicentre medication reconciliation QI initiative using mentored implementation of a refined best practices toolkit, including patient-level and system-level interventions, was associated with a substantial decrease in unintentional medication discrepancies over time. Future efforts should focus on sustainability and spread.

Medication Safety in Two Intensive Care Units of a Community Teaching Hospital After Electronic Health Record Implementation: Sociotechnical and Human Factors Engineering Considerations.

OBJECTIVE: The aim of the study was to assess the impact of Electronic Health Record (EHR) implementation on medication safety in two intensive care units (ICUs). METHODS: Using a prospective pre-post design, we assessed 1254 consecutive admissions to two ICUs before and after an EHR implementation. Each medication event was evaluated with regard to medication error (error type, medication-management stage) and impact on patient (severity of potential or actual harm). RESULTS: We identified 4063 medication-related events either pre-implementation (2074 events) or post-implementation (1989 events). Although the overall potential for harm due to medication errors decreased post-implementation only 2 of the 3 error rates were significantly lower post-implementation. After EHR implementation, we observed reductions in rates of medication errors per admission at the stages of transcription (0.13-0, P < 0.001), dispensing (0.49-0.16, P < 0.001), and administration (0.83-0.56, P = 0.011). Within the ordering stage, 4 error types decreased post-implementation (orders with omitted information, error-prone abbreviations, illegible orders, failure to renew orders) and 4 error types increased post-implementation (orders of wrong drug, orders containing a wrong start or stop time, duplicate orders, orders with inappropriate or wrong information). Within the administration stage, we observed a reduction of late administrations and increases in omitted administrations and incorrect documentation. CONCLUSIONS: Electronic Health Record implementation in two ICUs was associated with both improvement and worsening in rates of specific error types. Further safety improvements require a nuanced understanding of how various error types are influenced by the technology and the sociotechnical work system of the technology implementation. Recommendations based on human factors engineering principles are provided for reducing medication errors.

Remembering Ben-Tzion Karsh's scholarship, impact, and legacy.

Dr. Ben-Tzion (Bentzi) Karsh was a mentor, collaborator, colleague, and friend who profoundly impacted the fields of human factors and ergonomics (HFE), medical informatics, patient safety, and primary care, among others. In this paper we honor his contributions by reflecting on his scholarship, impact, and legacy in three ways: first, through an updated simplified bibliometric analysis in 2020, highlighting the breadth of his scholarly impact from the perspective of the number and types of communities and collaborators with which and whom he engaged; second, through targeted reflections on the history and impact of Dr. Karsh's most cited works, commenting on the particular ways they impacted our academic community; and lastly, through quotes from collaborators and mentees, illustrating Dr. Karsh's long-lasting impact on his contemporaries and students.

Hospital readmission in general medicine patients: a prediction model.

BACKGROUND: Previous studies of hospital readmission have focused on specific conditions or populations and generated complex prediction models. OBJECTIVE: To identify predictors of early hospital readmission in a diverse patient population and derive and validate a simple model for identifying patients at high readmission risk. DESIGN: Prospective observational cohort study. PATIENTS: Participants encompassed 10,946 patients discharged home from general medicine services at six academic medical centers and were randomly divided into derivation (n = 7,287) and validation (n = 3,659) cohorts. MEASUREMENTS: We identified readmissions from administrative data and 30-day post-discharge telephone follow-up. Patient-level factors were grouped into four categories: sociodemographic factors, social support, health condition, and healthcare utilization. We performed logistic regression analysis to identify significant predictors of unplanned readmission within 30 days of discharge and developed a scoring system for estimating readmission risk. RESULTS: Approximately 17.5% of patients were readmitted in each cohort. Among patients in the derivation cohort, seven factors emerged as significant predictors of early readmission: insurance status, marital status, having a regular physician, Charlson comorbidity index, SF12 physical component score, >or=1 admission(s) within the last year, and current length of stay >2 days. A cumulative risk score of >or=25 points identified 5% of patients with a readmission risk of approximately 30% in each cohort. Model discrimination was fair with a c-statistic of 0.65 and 0.61 for the derivation and validation cohorts, respectively. CONCLUSIONS: Select patient characteristics easily available shortly after admission can be used to identify a subset of patients at elevated risk of early readmission. This information may guide the efficient use of interventions to prevent readmission.

Adverse Event Reporting: Harnessing Residents to Improve Patient Safety.

OBJECTIVES: Reporting of adverse and near miss events are essential to identify system level targets to improve patient safety. Resident physicians historically report few events despite their role as front-line patient care providers. We sought to evaluate barriers to adverse event reporting in an effort to improve reporting. Our main outcomes were as follows: resident attitudes about event reporting and the frequency of event reporting before and after interventions to address reporting barriers. METHODS: We surveyed first year residents regarding barriers to adverse event reporting and used this input to construct a fishbone diagram listing barriers to reporting. Barriers were addressed, and resident event reporting was compared before and after efforts were made to reduce obstacles to reporting. RESULTS: First year residents (97%) recognized the importance of submitting event reports; however, the majority (85%) had not submitted an event report in the first 6 months of residency. Only 7% of residents specified that they had not witnessed an adverse event in 6 months, whereas one third had witnessed 10 or more events. The main barriers were as follows: lack of knowledge about how to submit events (38%) and lack of time to submit reports (35%). After improving resident education around event reporting and simplifying the reporting process, resident event reporting increased 230% (68 to 154 annual reports, P = 0.025). CONCLUSIONS: We were able to significantly increase resident event reporting by educating residents about adverse events and near misses and addressing the primary barriers to event reporting. Moving forward, we will continue annual resident education about patient safety, focus on improving feedback to residents who submit reports, and empower senior residents to act as role models to junior residents in patient safety initiatives.

It's time to bring human factors to primary care policy and practice.

Primary health care is a complex, highly personal, and non-linear process. Care is often sub-optimal and professional burnout is high. Interventions intended to improve the situation have largely failed. This is due to a lack of a deep understanding of primary health care. Human Factors approaches and methods will aid in understanding the cognitive, social and technical needs of these specialties, and in designing and testing proposed innovations. In 2012, Ben-Tzion Karsh, Ph.D., conceived a transdisciplinary conference to frame the opportunities for research human factors and industrial engineering in primary care. In 2013, this conference brought together experts in primary care and human factors to outline areas where human factors methods can be applied. The results of this expert consensus panel highlighted four major research areas: Cognitive and social needs, patient engagement, care of community, and integration of care. Work in these areas can inform the design, implementation, and evaluation of innovations in Primary Care. We provide descriptions of these research areas, highlight examples and give suggestions for future research.

Association of communication between hospital-based physicians and primary care providers with patient outcomes.

BACKGROUND: Patients admitted to general medicine inpatient services are increasingly cared for by hospital-based physicians rather than their primary care providers (PCPs). This separation of hospital and ambulatory care may result in important care discontinuities after discharge. We sought to determine whether communication between hospital-based physicians and PCPs influences patient outcomes. METHODS: We approached consecutive patients admitted to general medicine services at six US academic centers from July 2001 to June 2003. A random sample of the PCPs for consented patients was contacted 2 weeks after patient discharge and surveyed about communication with the hospital medical team. Responses were linked with the 30-day composite patient outcomes of mortality, hospital readmission, and emergency department (ED) visits obtained through follow-up telephone survey and National Death Index search. We used hierarchical multi-variable logistic regression to model whether communication with the patient's PCP was associated with the 30-day composite outcome. RESULTS: A total of 1,772 PCPs for 2,336 patients were surveyed with 908 PCPs responses and complete patient follow-up available for 1,078 patients. The PCPs for 834 patients (77%) were aware that their patient had been admitted to the hospital. Of these, direct communication between PCPs and inpatient physicians took place for 194 patients (23%), and a discharge summary was available within 2 weeks of discharge for 347 patients (42%). Within 30 days of discharge, 233 (22%) patients died, were readmitted to the hospital, or visited an ED. In adjusted analyses, no relationship was seen between the composite outcome and direct physician communication (adjusted odds ratio 0.87, 95% confidence interval 0.56 - 1.34), the presence of a discharge summary (0.84, 95% CI 0.57-1.22), or PCP awareness of the index hospitalization (1.08, 95% CI 0.73-1.59). CONCLUSION: Analysis of communication between PCPs and inpatient medical teams revealed much room for improvement. Although communication during handoffs of care is important, we were not able to find a relationship between several aspects of communication and associated adverse clinical outcomes in this multi-center patient sample.

An On-Treatment Analysis of the MARQUIS Study: Interventions to Improve Inpatient Medication Reconciliation.

It is unclear which medication reconciliation interventions are most effective at reducing inpatient medication discrepancies. Five United States hospitals' interdisciplinary quality improvement (QI) teams were virtually mentored by QI-trained physicians. Sites implemented one to seven evidence-based interventions in 791 patients during the 25-month implementation period. Three interventions were associated with significant decreases in potentially harmful discrepancy rates: (1) defining clinical roles and responsibilities, (2) training, and (3) hiring staff to perform discharge medication reconciliation. Two interventions were associated with significant increases in potentially harmful discrepancy rates: training staff to take medication histories and implementing a new electronic health record (EHR). Hospitals should focus first on hiring and training pharmacy staff to assist with medication reconciliation at discharge and delineating roles and responsibilities of clinical staff. We caution hospitals implementing a large vendor EHR, as medication discrepancies may increase. Finally, the effect of medication history training on discrepancies needs further study.

Do hospitalists or physicians with greater inpatient HIV experience improve HIV care in the era of highly active antiretroviral therapy? Results from a multicenter trial of academic hospitalists.

BACKGROUND: Little is known about the effect of provider type and experience on outcomes, resource use, and processes of care of hospitalized patients with human immunodeficiency virus (HIV) infection. Hospitalists are caring for this population with increasing frequency. METHODS: Data from a natural experiment in which patients were assigned to physicians on the basis of call cycle was used to study the effects of provider type-that is, hospitalist versus nonhospitalist-and HIV-specific inpatient experience on resource use, outcomes, and selected measures of processes of care at 6 academic institutions. Administrative data, inpatient interviews, 30-day follow-up interviews, and the National Death Index were used to measure outcomes. RESULTS: A total of 1207 patients were included in the analysis. There were few differences in resource use, outcomes, and processes of care by provider type and experience with HIV-infected inpatients. Patients who received hospitalist care demonstrated a trend toward increased length of hospital stay compared with patients who did not receive hospitalist care (6.0 days vs. 5.2 days; P = .13). Inpatient providers with moderate experience with HIV-infected patients were more likely to coordinate care with outpatient providers (odds ratio, 2.40; P = .05) than were those with the least experience with HIV-infected patients, but this pattern did not extend to providers with the highest level of experience. CONCLUSION: Provider type and attending physician experience with HIV-infected inpatients had minimal effect on the quality of care of HIV-infected inpatients. Approaches other than provider experience, such as the use of multidisciplinary inpatient teams, may be better targets for future studies of the outcomes, processes of care, and resource use of HIV-infected inpatients.

Effects of a multifaceted medication reconciliation quality improvement intervention on patient safety: final results of the MARQUIS study.

BACKGROUND: Unintentional discrepancies across care settings are a common form of medication error and can contribute to patient harm. Medication reconciliation can reduce discrepancies; however, effective implementation in real-world settings is challenging. METHODS: We conducted a pragmatic quality improvement (QI) study at five US hospitals, two of which included concurrent controls. The intervention consisted of local implementation of medication reconciliation best practices, utilising an evidence-based toolkit with 11 intervention components. Trained QI mentors conducted monthly site phone calls and two site visits during the intervention, which lasted from December 2011 through June 2014. The primary outcome was number of potentially harmful unintentional medication discrepancies per patient; secondary outcome was total discrepancies regardless of potential for harm. Time series analysis used multivariable Poisson regression. RESULTS: Across five sites, 1648 patients were sampled: 613 during baseline and 1035 during the implementation period. Overall, potentially harmful discrepancies did not decrease over time beyond baseline temporal trends, adjusted incidence rate ratio (IRR) 0.97 per month (95% CI 0.86 to 1.08), p=0.53. The intervention was associated with a reduction in total medication discrepancies, IRR 0.92 per month (95% CI 0.87 to 0.97), p=0.002. Of the four sites that implemented interventions, three had reductions in potentially harmful discrepancies. The fourth site, which implemented interventions and installed a new electronic health record (EHR), saw an increase in discrepancies, as did the fifth site, which did not implement any interventions but also installed a new EHR. CONCLUSIONS: Mentored implementation of a multifaceted medication reconciliation QI initiative was associated with a reduction in total, but not potentially harmful, medication discrepancies. The effect of EHR implementation on medication discrepancies warrants further study. TRIAL REGISTRATION NUMBER: NCT01337063.

Meaningful use's benefits and burdens for US family physicians.

Objective: The federal meaningful use (MU) program was aimed at improving adoption and use of electronic health records, but practicing physicians have criticized it. This study was aimed at quantifying the benefits (ie, usefulness) and burdens (ie, workload) of the MU program for practicing family physicians. Materials and Methods: An interdisciplinary national panel of experts (physicians and engineers) identified the work associated with MU criteria during patient encounters. They conducted a national survey to assess each criterion's level of patient benefit and compliance burden. Results: In 2015, 480 US family physicians responded to the survey. Their demographics were comparable to US norms. Eighteen of 31 MU criteria were perceived as useful for more than half of patient encounters, with 13 of those being useful for more than two-thirds. Thirteen criteria were useful for less than half of patient encounters. Four useful criteria were reported as having a high compliance burden. Discussion: There was high variability in physicians' perceived benefits and burdens of MU criteria. MU Stage 1 criteria, which are more related to basic/routine care, were perceived as beneficial by most physicians. Stage 2 criteria, which are more related to complex and population care, were perceived as less beneficial and more burdensome to comply with. Conclusion: MU was discontinued, but the merit-based incentive payment system within the Medicare Access and CHIP Reauthorization Act of 2015 adopted its criteria. For many physicians, MU created a significant practice burden without clear benefits to patient care. This study suggests that policymakers should not assess MU in aggregate, but as individual criteria for open discussion.