The Safety of Inpatient Health Care.

BACKGROUND: Adverse events during hospitalization are a major cause of patient harm, as documented in the 1991 Harvard Medical Practice Study. Patient safety has changed substantially in the decades since that study was conducted, and a more current assessment of harm during hospitalization is warranted. METHODS: We conducted a retrospective cohort study to assess the frequency, preventability, and severity of patient harm in a random sample of admissions from 11 Massachusetts hospitals during the 2018 calendar year. The occurrence of adverse events was assessed with the use of a trigger method (identification of information in a medical record that was previously shown to be associated with adverse events) and from review of medical records. Trained nurses reviewed records and identified admissions with possible adverse events that were then adjudicated by physicians, who confirmed the presence and characteristics of the adverse events. RESULTS: In a random sample of 2809 admissions, we identified at least one adverse event in 23.6%. Among 978 adverse events, 222 (22.7%) were judged to be preventable and 316 (32.3%) had a severity level of serious (i.e., caused harm that resulted in substantial intervention or prolonged recovery) or higher. A preventable adverse event occurred in 191 (6.8%) of all admissions, and a preventable adverse event with a severity level of serious or higher occurred in 29 (1.0%). There were seven deaths, one of which was deemed to be preventable. Adverse drug events were the most common adverse events (accounting for 39.0% of all events), followed by surgical or other procedural events (30.4%), patient-care events (which were defined as events associated with nursing care, including falls and pressure ulcers) (15.0%), and health care-associated infections (11.9%). CONCLUSIONS: Adverse events were identified in nearly one in four admissions, and approximately one fourth of the events were preventable. These findings underscore the importance of patient safety and the need for continuing improvement. (Funded by the Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.).

The Safety of Outpatient Health Care : Review of Electronic Health Records.

BACKGROUND: Despite considerable emphasis on delivering safe care, substantial patient harm occurs. Although most care occurs in the outpatient setting, knowledge of outpatient adverse events (AEs) remains limited. OBJECTIVE: To measure AEs in the outpatient setting. DESIGN: Retrospective review of the electronic health record (EHR). SETTING: 11 outpatient sites in Massachusetts in 2018. PATIENTS: 3103 patients who received outpatient care. MEASUREMENTS: Using a trigger method, nurse reviewers identified possible AEs and physicians adjudicated them, ranked severity, and assessed preventability. Generalized estimating equations were used to assess the association of having at least 1 AE with age, sex, race, and primary insurance. Variation in AE rates was analyzed across sites. RESULTS: The 3103 patients (mean age, 52 years) were more often female (59.8%), White (75.1%), English speakers (90.8%), and privately insured (70.4%) and had a mean of 4 outpatient encounters in 2018. Overall, 7.0% (95% CI, 4.6% to 9.3%) of patients had at least 1 AE (8.6 events per 100 patients annually). Adverse drug events were the most common AE (63.8%), followed by health care-associated infections (14.8%) and surgical or procedural events (14.2%). Severity was serious in 17.4% of AEs, life-threatening in 2.1%, and never fatal. Overall, 23.2% of AEs were preventable. Having at least 1 AE was less often associated with ages 18 to 44 years than with ages 65 to 84 years (standardized risk difference, -0.05 [CI, -0.09 to -0.02]) and more often associated with Black race than with Asian race (standardized risk difference, 0.09 [CI, 0.01 to 0.17]). Across study sites, 1.8% to 23.6% of patients had at least 1 AE and clinical category of AEs varied substantially. LIMITATION: Retrospective EHR review may miss AEs. CONCLUSION: Outpatient harm was relatively common and often serious. Adverse drug events were most frequent. Rates were higher among older adults. Interventions to curtail outpatient harm are urgently needed. PRIMARY FUNDING SOURCE: Controlled Risk Insurance Company and the Risk Management Foundation of the Harvard Medical Institutions.

Straight to the point: evaluation of a Point of Care Information (POCI) resource in answering disease-related questions.

Objective: To evaluate the ability of DynaMedex, an evidence-based drug and disease Point of Care Information (POCI) resource, in answering clinical queries using keyword searches. Methods: Real-world disease-related questions compiled from clinicians at an academic medical center, DynaMedex search query data, and medical board review resources were categorized into five clinical categories (complications & prognosis, diagnosis & clinical presentation, epidemiology, prevention & screening/monitoring, and treatment) and six specialties (cardiology, endocrinology, hematology-oncology, infectious disease, internal medicine, and neurology). A total of 265 disease-related questions were evaluated by pharmacist reviewers based on if an answer was found (yes, no), whether the answer was relevant (yes, no), difficulty in finding the answer (easy, not easy), cited best evidence available (yes, no), clinical practice guidelines included (yes, no), and level of detail provided (detailed, limited details). Results: An answer was found for 259/265 questions (98%). Both reviewers found an answer for 241 questions (91%), neither found the answer for 6 questions (2%), and only one reviewer found an answer for 18 questions (7%). Both reviewers found a relevant answer 97% of the time when an answer was found. Of all relevant answers found, 68% were easy to find, 97% cited best quality of evidence available, 72% included clinical guidelines, and 95% were detailed. Recommendations for areas of resource improvement were identified. Conclusions: The resource enabled reviewers to answer most questions easily with the best quality of evidence available, providing detailed answers and clinical guidelines, with a high level of replication of results across users.

Ability to Predict New-Onset Psychological Distress Using Routinely Collected Health Data: A Population-Based Cohort Study of Women Diagnosed With Breast Cancer.

Objectives: The primary objective of this study was to identify the predictors of new-onset psychological distress available in routinely collected administrative health databases for women diagnosed with breast cancer. The secondary objective was to explore whether the predictors vary based on the period of cancer care. Methods: A population-based cohort study followed 16,495 female patients with newly diagnosed breast cancer who did not experience psychological distress during the 14 months before breast cancer surgery. The incidence of psychological distress was reported overall and by type of mental health problem. Time-varying Cox proportional hazards models were developed to identify predictors of new-onset psychological distress during 2 key periods of cancer care: (1) hospital-based treatment during which women undergo treatment with breast surgery, chemotherapy, and/or radiation, and (2) 1-year transitional survivorship when women begin follow-up care. Results: The incidence of psychological distress was 16% within each period. Anxiety was present in 85.1% and 65.5% of new cases during hospital-based treatment and transitional survivorship, respectively. Predictors during both periods were younger age, receipt of axillary lymph node dissection, rheumatologic disease, and baseline menopausal symptoms, as well as new opioid dispensations, emergency department visits, and hospital contacts that occurred during follow-up. Other predictors varied based on the period of cancer care. More advanced breast cancer and type of treatment were associated with onset of psychological distress during hospital-based treatment. Psychological distress during transitional survivorship was predicted by diagnosis of localized breast disease, shorter duration of hospital-based treatment, receipt of additional hospital-based treatment in survivorship, and newly diagnosed comorbidities or symptoms. Conclusions: This study identified the predictors of new-onset psychological distress available in routinely collected administrative health databases, and showed how predictors change between hospital-based treatment and transitional survivorship periods. The results highlight the importance of developing predictive models tailored to the period of cancer care.

Evaluating Patient, Family and Public Engagement in Health Services Improvement and System Redesign.

As efforts to actively involve patients, family members and the broader public in health service improvement and system redesign have grown, increasing attention has also been paid to evaluation of their engagement in the health system. We discuss key concepts and approaches related to evaluation, drawing particular attention to different and potentially competing goals, stakeholders and epistemological entry points. Evaluation itself can be supported by an increasing number of frameworks and tools, matched to the relevant purpose and approach. The patient engagement evaluation field faces several challenges, including the need for greater specification of both the form and the context of engagement, the need to balance the measurement imperative with the relational aspects of care and the need for supportive organizations with the capacity and commitment to undertake high-quality engagement and its evaluation.

Predictors of distress in female breast cancer survivors: a systematic review.

PURPOSE: Unmanaged distress has been shown to adversely affect survival and quality of life in breast cancer survivors. Fortunately, distress can be managed and even prevented with appropriate evidence-based interventions. Therefore, the objective of this systematic review was to synthesize the published literature around predictors of distress in female breast cancer survivors to help guide targeted intervention to prevent distress. METHODS: Relevant studies were located by searching MEDLINE, Embase, PsycINFO, and CINAHL databases. Significance and directionality of associations for commonly assessed candidate predictors (n ≥ 5) and predictors shown to be significant (p ≤ 0.05) by at least two studies were summarized descriptively. Predictors were evaluated based on the proportion of studies that showed a significant and positive association with the presence of distress. RESULTS: Forty-two studies met the target criteria and were included in the review. Breast cancer and treatment-related predictors were more advanced cancer at diagnosis, treatment with chemotherapy, longer primary treatment duration, more recent transition into survivorship, and breast cancer recurrence. Manageable treatment-related symptoms associated with distress included menopausal/vasomotor symptoms, pain, fatigue, and sleep disturbance. Sociodemographic characteristics that increased the risk of distress were younger age, non-Caucasian ethnicity, being unmarried, and lower socioeconomic status. Comorbidities, history of mental health problems, and perceived functioning limitations were also associated. Modifiable predictors of distress were lower physical activity, lower social support, and cigarette smoking. CONCLUSIONS: This review established a set of evidence-based predictors that can be used to help identify women at higher risk of experiencing distress following completion of primary breast cancer treatment.

Psychotropic and Opioid Medication Use in Older Patients With Breast Cancer Across the Care Trajectory: A Population-Based Cohort Study.

BACKGROUND: Older patients with breast cancer represent a vulnerable population at higher risk of experiencing distress and pain, as well as medication-related adverse events from pharmacological treatment of these symptoms. The purpose of this study is to estimate the prevalence of psychotropic (anxiolytic, antidepressant, and antipsychotic) and opioid medication use by older women diagnosed with breast cancer. METHODS: This population-based cohort study followed 19,353 women older than 65 years diagnosed with incident, nonmetastatic breast cancer in Quebec, Canada. Data were obtained from provincial, universal health and drug insurance plans covering all medical and pharmaceutical care. Descriptive statistics were calculated for demographic information, breast cancer characteristics, and treatments. Psychotropic and opioid medication use was assessed across the care trajectory: precancer baseline, active care, and first-year survivorship. RESULTS: There was a marked increase in the prevalence of medication use from precancer baseline to active care, followed by a decrease into first-year survivorship. Anxiolytics were used most often across the care trajectory (36.3%, 50.6%, and 44.4% at baseline, active care, and survivorship, respectively). In contrast, antipsychotic and opioid medications were sought primarily during active care (4.5- and 7-fold increases from baseline, respectively), with opioid use during active care increasing dramatically over the study period (9.0% to 40.9% from 1998 to 2010). Unlike other drugs, antidepressant use peaked in active care but persisted into survivorship (14.7%, 22.4%, and 22.3% at baseline, active care, and survivorship, respectively). CONCLUSIONS: A substantial proportion of older patients with breast cancer use psychotropic and opioid medications. The different patterns of medication use represent distress and pain experienced by patients across the care trajectory. Given that medication use in this vulnerable population is associated with an increased risk of adverse events, a multidimensional approach integrating psychological interventions in cancer care may better address psychosocial needs of older patients with breast cancer.

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

BACKGROUND: Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. OBJECTIVE: The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. METHODS: Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. RESULTS: Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than others. Integration of content control improved quality of decision making (SMD 0.59 vs 0.23 for knowledge; SMD 0.39 vs 0.29 for decisional conflict). In contrast, tailoring reduced quality of decision making (SMD 0.40 vs 0.71 for knowledge; SMD 0.25 vs 0.52 for decisional conflict). Similarly, patient narratives also reduced quality of decision making (SMD 0.43 vs 0.65 for knowledge; SMD 0.17 vs 0.46 for decisional conflict). Results were varied for different types of explicit values clarification, feedback, and social support. CONCLUSIONS: Integration of media rich or interactive features into computer-based decision aids can improve quality of preference-sensitive decision making. However, this is an emerging field with limited evidence to guide use. The systematic review and thematic synthesis identified features that have been integrated into available computer-based decision aids, in an effort to facilitate reporting of these features and to promote integration of such features into decision aids. The meta-analyses and associated subgroup analyses provide preliminary evidence to support integration of specific features into future decision aids. Further research can focus on clarifying independent contributions of specific features through experimental designs and refining the designs of features to improve effectiveness.

Implementation of a Continuous Patient Monitoring System in the Hospital Setting: A Qualitative Study.

BACKGROUND: Technology can improve care delivery, patient outcomes, and staff satisfaction, but integration into the clinical workflow remains challenging. To contribute to this knowledge area, this study examined the implementation continuum of a contact-free, continuous monitoring system (CFCM) in an inpatient setting. CFCM monitors vital signs and uses the information to alert clinicians of important changes, enabling early detection of patient deterioration. METHODS: Data were collected throughout the entire implementation continuum at a community teaching hospital. Throughout the study, 3 group and 24 individual interviews and five process observations were conducted. Postimplementation alarm response data were collected. Analysis was conducted using triangulation of information sources and two-coder consensus. RESULTS: Preimplementation perceived barriers were alarm fatigue, questions about accuracy and trust, impact on patient experience, and challenges to the status quo. Stakeholders identified the value of CFCM as preventing deterioration and benefitting patients who are not good candidates for telemetry. Educational materials addressed each barrier and emphasized the shared CFCM values. Mean alarm response times were below the desired target of two minutes. Postimplementation interview analysis themes revealed lessened concerns of alarm fatigue and improved trust in CFCM than anticipated. Postimplementation challenges included insufficient training for secondary users and impact on patient experience. CONCLUSION: In addition to understanding the preimplementation anticipated barriers to implementation and establishing shared value before implementation, future recommendations include studying strategies for optimal tailoring of education to each user group, identifying and reinforcing positive process changes after implementation, and including patient experience as the overarching element in frameworks for digital tool implementation.

Accurately identifying incident cases of venous thromboembolism in the electronic health record: Performance of a novel phenotyping algorithm.

BACKGROUND: Accurate identification of incident venous thromboembolism (VTE) for quality improvement and health services research is challenging. The purpose of this study was to evaluate the performance of a novel incident VTE phenotyping algorithm defined using standard terminologies, requiring three key indicators documented in the electronic health record (EHR): VTE diagnostic code, VTE-related imaging procedure code, and anticoagulant medication code. METHODS: Retrospective chart reviews were conducted to assess the performance of the algorithm using a random sample of phenotype(+) and phenotype(-) diagnostic encounters from primary care practices and acute care sites affiliated with five hospitals across a large integrated care delivery system in Massachusetts. The performance of the algorithm was evaluated by calculating the positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity, using the phenotype(+) and phenotype(-) diagnostic encounters sample and target population data. RESULTS: Based on gold-standard manual chart review, the algorithm had a PPV of 95.2 % (95 % CI: 93.1-96.8 %), NPV of 97.1 % (95 % CI: 95.3-98.4 %), sensitivity of 91.7 % (95 % CI: 90.8-92.6 %), and specificity of 98.4 % (95 % CI: 98.1-98.6 %). The algorithm systematically misclassified a low number of specific types of encounters, highlighting potential areas for improvement. CONCLUSIONS: This novel phenotyping algorithm offers an accurate approach for identifying incident VTE in general populations using EHR data and standard terminologies, and accurately identifies the specific encounter and date of diagnosis of the incident VTE. This approach can be used for measurement of incident VTE to drive quality improvement, research to expand the evidence, and development of quality metrics and clinical decision support to improve the diagnostic process.

Achieving the "triple aim" for inborn errors of metabolism: a review of challenges to outcomes research and presentation of a new practice-based evidence framework.

Across all areas of health care, decision makers are in pursuit of what Berwick and colleagues have called the "triple aim": improving patient experiences with care, improving health outcomes, and managing health system impacts. This is challenging in a rare disease context, as exemplified by inborn errors of metabolism. There is a need for evaluative outcomes research to support effective and appropriate care for inborn errors of metabolism. We suggest that such research should consider interventions at both the level of the health system (e.g., early detection through newborn screening, programs to provide access to treatments) and the level of individual patient care (e.g., orphan drugs, medical foods). We have developed a practice-based evidence framework to guide outcomes research for inborn errors of metabolism. Focusing on outcomes across the triple aim, this framework integrates three priority themes: tailoring care in the context of clinical heterogeneity; a shift from "urgent care" to "opportunity for improvement"; and the need to evaluate the comparative effectiveness of emerging and established therapies. Guided by the framework, a new Canadian research network has been established to generate knowledge that will inform the design and delivery of health services for patients with inborn errors of metabolism and other rare diseases.

Factors determining safety culture in hospitals: a scoping review.

OBJECTIVE: To evaluate and synthesise the factors determining patient safety culture in hospitals. METHODS: The scoping review protocol was based on the criteria of the Joanna Briggs Institute. Eligibility criteria were as follows: (1) empirical study published in a peer-reviewed journal; (2) used methods or tools to assess, study or measure safety culture or climate; (3) data collected in the hospital setting and (4) studies published in English. Relevant literature was located using PubMed, CINAHL, Web of Science and PsycINFO databases. Quantitative and qualitative analyses were performed using RStudio and the R interface for multidimensional analysis of texts and questionnaires (IRaMuTeQ). RESULTS: A total of 248 primary studies were included. The most used instruments for assessing safety culture were the Hospital Survey on Patient Safety Culture (n=104) and the Safety Attitudes Questionnaire (n=63). The Maslach Burnout Inventory (n=13) and Culture Assessment Scales based on patient perception (n=9) were used in association with cultural instruments. Sixty-six articles were included in the qualitative analysis. In word cloud and similarity analyses, the words 'communication' and 'leadership' were most prominent. Regarding the descending hierarchical classification analysis, the content was categorised into two main classes, one of which was subdivided into five subclasses: class 1a: job satisfaction and leadership (15.56%), class 1b: error response (22.22%), class 1c: psychological and empowerment nurses (20.00%), class 1d: trust culture (22.22%) and class 2: innovation worker (20.00%). CONCLUSION: The instruments presented elements that remained indispensable for assessing the safety culture, such as leadership commitment, open communication and learning from mistakes. There was also a tendency for research to assess patient and family engagement, psychological safety, nurses' engagement in decision-making and innovation.

Testing of an Electronic Clinical Quality Measure for Diagnostic Delay of Venous Thromboembolism (DOVE) in Primary Care.

Venous Thromboembolism (VTE) is a serious, preventable public health problem that requires timely treatment. Because signs and symptoms are non-specific, patients often present to primary care providers with VTE symptoms prior to diagnosis. Today there are no federal measurement tools in place to track delayed diagnosis of VTE. We developed and tested an electronic clinical quality measure (eCQM) to quantify Diagnostic Delay of Venous Thromboembolism (DOVE); the rate of avoidable delayed VTE events occurring in patients with a VTE who had reported VTE symptoms in primary care within 30 days of diagnosis. DOVE uses routinely collected EHR data without contributing to documentation burden. DOVE was tested in two geographically distant healthcare systems. Overall DOVE rates were 72.60% (site 1) and 77.14% (site 2). This novel, data-driven eCQM could inform healthcare providers and facilities about opportunities to improve care, strengthen incentives for quality improvement, and ultimately improve patient safety.

Cost Savings Associated With Implementing 4 Total Joint Replacement Electronic Clinical Quality Measures Nationally: 2020-2040.

BACKGROUND: Digital transformation using widely available electronic data is a key component to improving health outcomes and customer choice and decreasing cost and measurement burden. Despite these benefits, existing information on the potential cost savings from electronic clinical quality measures (eCQMs) is limited. METHODS: We assessed the costs of implementing 4 eCQMs related to total hip and/or total knee arthroplasty into electronic health record systems across healthcare systems in the United States. We used published literature and technical expert panel consultation to calculate low-, mid-, and high-range hip and knee arthroplasty surgery projections, and used empirical testing, literature, and technical expert panel consultation to develop an economic model to assess projected cost savings of eCQMs when implemented nationally. RESULTS: Low-, mid-, and high-range projected cost savings for year's 2020, 2030, and 2040 were calculated for 4 orthopedic eCQMs. Mid-range projected cost savings for 2020 ranged from $7.9 to $31.9 million per measure per year. A breakeven of between 0.5% and 5.1% of adverse events (measure dependent) must be averted for cost savings to outweigh implementation costs. CONCLUSIONS: All measures demonstrated potential cost savings. These findings suggest that eCQMs have the potential to lower healthcare costs and improve patient outcomes without adding to physician documentation burden. The Centers for Medicare and Medicaid Services' investment in eCQMs is an opportunity to reduce adverse outcomes and excess costs in orthopedics.

Correction: Performance of a Web-Based Reference Database With Natural Language Searching Capabilities: Usability Evaluation of DynaMed and Micromedex With Watson.

[This corrects the article DOI: 10.2196/43960.].

Performance of a Web-Based Reference Database With Natural Language Searching Capabilities: Usability Evaluation of DynaMed and Micromedex With Watson.

BACKGROUND: Evidence-based point-of-care information (POCI) tools can facilitate patient safety and care by helping clinicians to answer disease state and drug information questions in less time and with less effort. However, these tools may also be visually challenging to navigate or lack the comprehensiveness needed to sufficiently address a medical issue. OBJECTIVE: This study aimed to collect clinicians' feedback and directly observe their use of the combined POCI tool DynaMed and Micromedex with Watson, now known as DynaMedex. EBSCO partnered with IBM Watson Health, now known as Merative, to develop the combined tool as a resource for clinicians. We aimed to identify areas for refinement based on participant feedback and examine participant perceptions to inform further development. METHODS: Participants (N=43) within varying clinical roles and specialties were recruited from Brigham and Women's Hospital and Massachusetts General Hospital in Boston, Massachusetts, United States, between August 10, 2021, and December 16, 2021, to take part in usability sessions aimed at evaluating the efficiency and effectiveness of, as well as satisfaction with, the DynaMed and Micromedex with Watson tool. Usability testing methods, including think aloud and observations of user behavior, were used to identify challenges regarding the combined tool. Data collection included measurements of time on task; task ease; satisfaction with the answer; posttest feedback on likes, dislikes, and perceived reliability of the tool; and interest in recommending the tool to a colleague. RESULTS: On a 7-point Likert scale, pharmacists rated ease (mean 5.98, SD 1.38) and satisfaction (mean 6.31, SD 1.34) with the combined POCI tool higher than the physicians, nurse practitioner, and physician's assistants (ease: mean 5.57, SD 1.64, and satisfaction: mean 5.82, SD 1.60). Pharmacists spent longer (mean 2 minutes, 26 seconds, SD 1 minute, 41 seconds) on average finding an answer to their question than the physicians, nurse practitioner, and physician's assistants (mean 1 minute, 40 seconds, SD 1 minute, 23 seconds). CONCLUSIONS: Overall, the tool performed well, but this usability evaluation identified multiple opportunities for improvement that would help inexperienced users.

Intelligent Telehealth in Pharmacovigilance: A Future Perspective.

Pharmacovigilance improves patient safety by detecting and preventing adverse drug events. However, challenges exist that limit adverse drug event detection, resulting in many adverse drug events being underreported or inaccurately reported. One challenge includes having access to large data sets from various sources including electronic health records and wearable medical devices. Artificial intelligence, including machine learning methods, such as natural language processing and deep learning, can detect and extract information about adverse drug events, thus automating the pharmacovigilance process and improving the surveillance of known and documented adverse drug events. In addition, with the increased demand for telehealth services, for managing both acute and chronic diseases, artificial intelligence methods can play a role in detecting and preventing adverse drug events. In this review, we discuss two use cases of how artificial intelligence methods may be useful to improve the quality of pharmacovigilance and the role of artificial intelligence in telehealth practices.

Use of linked data to assess the impact of including out-of-hospital deaths on 30-day in-hospital mortality indicators: a retrospective cohort study.

BACKGROUND: The Canadian Institute for Health Information (CIHI) annually reports on health system performance indicators, including various 30-day in-hospital mortality rates. We aimed to assess the impact of including out-of-hospital deaths on 3 CIHI indicators: 30-day acute myocardial infarction (AMI) in-hospital mortality, 30-day stroke in-hospital mortality and hospital deaths following major surgery. METHODS: We followed national cohorts of patients admitted to hospital in 1 of 9 Canadian provinces for AMI, stroke and major surgery for 30-day all-cause mortality in 2 fiscal years (2011/12 and 2016/17). We calculated descriptive statistics to characterize the cohorts. The CIHI Discharge Abstract Database was linked with the Canadian Vital Statistics Death Database using a probabilistic algorithm to identify out-of-hospital deaths. We calculated absolute numbers, relative proportions and 30-day mortality rates for in-hospital, out-of-hospital and all deaths. We compared results between fiscal years. RESULTS: We found that hospital admissions increased between fiscal years for each indicator; however, cohort characteristics remained consistent. In 2016/17, the number of out-of-hospital deaths that occurred was 325 for AMI, 545 for stroke and 820 for major surgery. The relative proportions of out-of-hospital deaths ranged from 12.3% for AMI to 14.9% for major surgery in 2016/17 (an increase from 10.6% and 13.1%, respectively, from 2011/12). In-hospital mortality rates improved over time for all 3 indicators, while out-of-hospital mortality rates remained consistent between fiscal years at 0.8% for AMI, 1.9%-2.0% for stroke and 0.2%-0.3% for major surgery. INTERPRETATION: Improvements between fiscal years were attributable to reductions in in-hospital mortality, rather than deaths occurring outside of hospitals. Trends over time were the same for each indicator irrespective of whether in-hospital mortality or all deaths were measured.

Multi-Site Testing of an Opioid Prescribing Electronic Clinical Quality Measure Following Elective Primary Total Hip and/or Total Knee Arthroplasties.

As the United States faces the third wave of the ongoing opioid epidemic, development of measures which report on prolonged opioid prescribing (POP) rates, specifically following orthopedic surgeries, are needed to better understand and improve prescribing practices at the clinician group level. Brigham and Women's Hospital (BWH) has been contracted by the Centers for Medicare and Medicaid Services (CMS) to create a novel electronic clinical quality measure (eCQM) to quantify the prolonged opioid prescribing rate of opioid episodes lasting > 42 days in patients aged 18+ years following elective primary total hip arthroplasties (THA) and/or total knee arthroplasties (TKA) for use in the Merit-Based Incentive Payment System (MIPS). When this measure was tested on two geographically distinct sites, it was found that the THA rate was 3.80% and 16.07% at sites 1 and 2, respectively, and that the TKA rate is 7.65% and 24.15% at sites 1 and 2, respectively. This manuscript reports on the testing of this eCQM between these two sites, highlighting differences in state and organizational level policies regarding opioid prescribing and documentation practices.