Joshua M. Pevnick

The Challenge of Measuring Quality of Care From the Electronic Health Record

The electronic health record (EHR) is seen by many as an ideal vehicle for measuring quality of health care and monitoring ongoing provider performance. It is anticipated that the availability of EHR-extracted data will allow quality assessment without the expensive and time-consuming process of medical record abstraction. A review of the data requirements for the indicators in the Quality Assessment Tools system suggests that only about a third of the indicators would be readily accessible from EHR data. Other factors involving complexity of required data elements, provider documentation habits, and EHR variability make the task of quality measurement more difficult than may be appreciated. Accurately identifying eligible cases for quality assessment and validly scoring those cases with EHR-extracted data will pose significant challenges but could potentially plummet the cost and therefore expand the use of quality assessment.

The problem with medication reconciliation

‘The Problem with…’ series covers controversial topics related to efforts to improve healthcare quality, including widely recommended but deceptively difficult strategies for improvement and pervasive problems that seem to resist solution. Medication reconciliation (‘med rec’, as it is often called) refers to the ‘process of identifying the most accurate list of all medications a patient is taking … and using this list to provide correct medications for patients anywhere within the health system’.1 Two recent systematic reviews summarised the evidence for med rec interventions, finding that several med rec interventions reduced medication history errors and errors in patients’ admission and discharge medication regimens.2 ,3 Despite documented efficacy in reducing errors, there are caveats. An earlier literature review showed that the clinical significance of medication history errors varies substantially—between 11% and 59%.4 Furthermore, although errors associated with harm were prevented in those studies that examined it,2 adverse drug events (ADEs) have been infrequently examined. Also, only a few studies have shown decreased healthcare usage,5 ,6 and to our knowledge none have shown direct cost savings. Despite imperfect evidence, The US Joint Commission and Accreditation Canada initially mandated universal med rec in 2005.7 ,8 In addition to the subset of aforementioned evidence in existence at that time, these mandates were driven by frequent anecdotes of ADEs related to med rec errors and strong face-validity of preserving and communicating medication information across patient encounters. Unfortunately, although some organisations mobilised substantial resources to comply with these mandates, other organisations undoubtedly improved documentation of med rec (as per the mandate requirements) rather than actual medication safety.9 Although most studies of med rec interventions report positive results, at least one review found publication bias:2 many negative experiences associated with med rec interventions were never reported. …

Provider Stakeholders' Perceived Benefit from a Nascent Health Information Exchange: A Qualitative Analysis

We sought to better understand the perceived costs and benefits of joining a nascent health information exchange (HIE) from the perspective of potential provider organization participants. We therefore conducted semi-structured interviews with organizational representatives. Interview transcriptions were thematically coded, and coded text was subsequently aggregated to summarize the breadth and depth of responses. Although no respondents expected HIE to result in net financial benefit to their organization, all respondents recognized some potential benefits, and some respondents expected HIE to result in overall organizational benefit. Disproportionate benefit was expected for the poorest, sickest patients. Many respondents had concerns about HIE increasing the risk of data security breaches, and these concerns were most pronounced at larger organizations. We found little evidence of organizational concern regarding loss of patients to other organizations or publication of unfavorable quality data. If HIE’s greatest benefactors are indeed the poorest, sickest patients, our current health care financing environment will make it difficult to align HIE costs with benefits. To sustain HIE, state and federal governments may need to consider ongoing subsidies. Furthermore, these governments will need to ensure that policies regulating data exchange have sufficient nationwide coordination and liability limitations that the perceived organizational risks of joining HIEs do not outweigh perceived benefits. HIE founders can address organizational concerns by attempting to coordinate HIE policies with those of their largest founding organizations, particularly for data security policies. Early HIE development and promotional efforts should not only focus on potential benefits, but should also address organizational concerns.

The impact of emerging standards adoption on automated quality reporting

Current quality measurement processes are labor-intensive, involving manual chart reviews and use of paper-based quality measures that vary in format and definitions from measure to measure. Automated quality reporting is considered by many to be an important tool that will help close the gaps in the quality of US health by increasing the timeliness, effectiveness, and use of quality assessment. In 2007, the US Department of Health and Human Services Office of the National Coordinator for Health Information Technology (ONC) funded three Nationwide Health Information Network (NHIN) health information exchanges (HIE) to demonstrate the feasibility of automated quality reporting by using existing or emerging standards to aggregate information from multiple providers, transmit patient-level quality data in standardized formats, perform an automated quality assessment, and generate a quality report document for electronic transmission. Long Beach Network for Health (LBNH), a NHIN Cooperative HIE, developed a web-based, real-time quality assessment service that calculates quality of care measure using clinical data aggregated through a HIE. LBNH used a set of draft standards to demonstrate automated quality reporting, but noted three important recommendations for future work. First, greater coordination is needed around initiatives that address the gaps in electronic quality measurement standards and processes, including strong Federal involvement and guidance. Second, a harmonized, evergreen quality use case is needed to provide stakeholders with a common understanding on the constantly evolving approaches towards automated quality measurement and reporting. Finally, there needs to be substantial investment in building on existing work and developing a comprehensive set of data and messaging standards to preserve semantic interoperability of quality measure data.

Medication adherence as a predictor of 30-day hospital readmissions

Purpose The aim of this study was to test whether patient medication adherence, a modifiable risk factor obtainable at hospital admission, predicts readmission within 30 days. Patients and methods We used a retrospective cohort study design to test whether patient medication adherence to all chronic medications, as determined by the 4-item Morisky Medication Adherence Scale (MMAS-4) administered by a pharmacist at the time of hospital admission, predicts 30-day readmissions. We compared readmission rates among 385 inpatients who had their adherence assessed from February 1, 2013, to January 31, 2014. Multiple logistic regression was used to examine the benefit of adding medication adherence to previously published variables that have been shown to predict 30-day readmissions. Results Patients with low and intermediate adherence (combined) had readmission rates of 20.0% compared to a readmission rate of 9.3% for patients with high adherence (P=0.005). By adding MMAS-4 data to previously published variables that have been shown to predict 30-day readmissions, we found that patients with low and intermediate medication adherence had an adjusted 2.54-fold higher odds of readmission compared to those in patients with high adherence (95% confidence interval [CI]: 1.32–4.90, P=0.005). The model’s predictive power, as measured by the c-statistic, improved from 0.65 to 0.70 after adding adherence. Conclusion Because medication adherence assessed at hospital admission was independently associated with 30-day readmission risk, it offers potential for targeting interventions to improve adherence.

Economic Evaluation of Quality Improvement Interventions Designed to Prevent Hospital Readmission: A Systematic Review and Meta-analysis

Importance Quality improvement (QI) interventions can reduce hospital readmission, but little is known about their economic value. Objective To systematically review economic evaluations of QI interventions designed to reduce readmissions. Data Sources Databases searched included PubMed, Econlit, the Centre for Reviews & Dissemination Economic Evaluations, New York Academy of Medicines Grey Literature Report, and Worldcat (January 2004 to July 2016). Study Selection Dual reviewers selected English-language studies from high-income countries that evaluated organizational or structural changes to reduce hospital readmission, and that reported program and readmission-related costs. Data Extraction and Synthesis Dual reviewers extracted intervention characteristics, study design, clinical effectiveness, study quality, economic perspective, and costs. We calculated the risk difference and net costs to the health system in 2015 US dollars. Weighted least-squares regression analyses tested predictors of the risk difference and net costs. Main Outcomes and Measures Main outcomes measures included the risk difference in readmission rates and incremental net cost. This systematic review and data analysis is reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Results Of 5205 articles, 50 unique studies were eligible, including 25 studies in populations limited to heart failure (HF) that included 5768 patients, 21 in general populations that included 10 445 patients, and 4 in unique populations. Fifteen studies lasted up to 30 days while most others lasted 6 to 24 months. Based on regression analyses, readmissions declined by an average of 12.1% among patients with HF (95% CI, 8.3%-15.9%; P < .001; based on 22 studies with complete data) and by 6.3% among general populations (95% CI, 4.0%-8.7%; P < .001; 18 studies). The mean net savings to the health system per patient was

Organizational Challenges in Developing One of the Nationwide Health Information Network Trial Implementation Awardees

972 among patients with HF (95% CI, −

Wearable technology for cardiology: An update and framework for the future

642 to

Improving admission medication reconciliation with pharmacists or pharmacy technicians in the emergency department: a randomised controlled trial

2586; P = .23; 24 studies), and the mean net loss was

A Large-Scale Initiative Inviting Patients to Share Personal Fitness Tracker Data with Their Providers: Initial Results

169 among general populations (95% CI, −