Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy.

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.

Availability of prices for shoppable services on hospital internet sites.

OBJECTIVES: A regulation from CMS required that, starting January 1, 2021, all US hospitals publicly display the cash price and minimum and minimum negotiated charge for 300 "shoppable services." We evaluated compliance with CMS requirements among highly respected US hospitals. STUDY DESIGN: We conducted a cross-sectional study of hospital websites. METHODS: We evaluated the public websites of the 20 hospitals listed in the 2020-2021 US News & World Report honor roll between February 1 and February 14, 2021. We selected 2 imaging studies (brain MRI and abdominal ultrasound) and 3 hospital services (cardiac valve surgery, total joint replacement, and vaginal childbirth). For each service and hospital, we determined whether the discounted cash price and minimum negotiated charge were displayed and, if displayed, what the prices were. RESULTS: Among our 20 hospitals, 13 (65%) displayed the cash prices for the MRI and ultrasound, 8 (40%) for valve surgery, 10 (50%) for joint replacement, and 10 (50%) for childbirth. Only 1 (5%) displayed the minimum negotiated price for the 2 imaging studies and none for any of the hospital services. The mean (range) cash price for MRI was $3793 ($464-$6215) and for ultrasound was $767 ($136-$1391). The mean (range) cash price for cardiac surgery was $236,125 ($72,250-$349,782); for joint replacement, $46,008 ($22,170-$71,985); and for childbirth, $19,568 ($7314-$29,068). CONCLUSIONS: In an early assessment, a significant percentage of US hospitals were not in compliance with new price transparency legislation. Moreover, there is wide variation in prices among hospitals for identical services. These price differences suggest the potential for significant cost savings for patients.

Recommendations for the safe, effective use of adaptive CDS in the US healthcare system: an AMIA position paper.

The development and implementation of clinical decision support (CDS) that trains itself and adapts its algorithms based on new data-here referred to as Adaptive CDS-present unique challenges and considerations. Although Adaptive CDS represents an expected progression from earlier work, the activities needed to appropriately manage and support the establishment and evolution of Adaptive CDS require new, coordinated initiatives and oversight that do not currently exist. In this AMIA position paper, the authors describe current and emerging challenges to the safe use of Adaptive CDS and lay out recommendations for the effective management and monitoring of Adaptive CDS.

Assessment of Health Information Technology-Related Outpatient Diagnostic Delays in the US Veterans Affairs Health Care System: A Qualitative Study of Aggregated Root Cause Analysis Data.

Importance: Diagnostic delay in the outpatient setting is an emerging safety priority that health information technology (HIT) should help address. However, diagnostic delays have persisted, and new safety concerns associated with the use of HIT have emerged. Objective: To analyze HIT-related outpatient diagnostic delays within a large, integrated health care system. Design, Setting, and Participants: This cohort study involved qualitative content analysis of safety concerns identified in aggregated root cause analysis (RCA) data related to HIT and outpatient diagnostic delays. The setting was the US Department of Veterans Affairs using all RCAs submitted to the Veterans Affairs (VA) National Center for Patient Safety from January 1, 2013, to July 31, 2018. Main Outcomes and Measures: Common themes associated with the role of HIT-related safety concerns were identified and categorized according to the Health IT Safety framework for measuring, monitoring, and improving HIT safety. This framework includes 3 related domains (ie, safe HIT, safe use of HIT, and using HIT to improve safety) situated within an 8-dimensional sociotechnical model accounting for interacting technical and nontechnical variables associated with safety. Hence, themes identified enhanced understanding of the sociotechnical context and domain of HIT safety involved. Results: Of 214 RCAs categorized by the terms delay and outpatient submitted during the study period, 88 were identified as involving diagnostic delays and HIT, from which 172 unique HIT-related safety concerns were extracted (mean [SD], 1.97 [1.53] per RCA). Most safety concerns (82.6% [142 of 172]) involved problems with safe use of HIT, predominantly sociotechnical factors associated with people, workflow and communication, and a poorly designed human-computer interface. Fewer safety concerns involved problems with safe HIT (14.5% [25 of 172]) or using HIT to improve safety (0.3% [5 of 172]). The following 5 key high-risk areas for diagnostic delays emerged: managing electronic health record inbox notifications and communication, clinicians gathering key diagnostic information, technical problems, data entry problems, and failure of a system to track test results. Conclusions and Relevance: This qualitative study of a national RCA data set suggests that interventions to reduce outpatient diagnostic delays could aim to improve test result management, interoperability, data visualization, and order entry, as well as to decrease information overload.

Application Programming Interfaces in Health Care: Findings from a Current-State Sociotechnical Assessment.

OBJECTIVE: Interest in application programming interfaces (APIs) is increasing as key stakeholders look for technical solutions to interoperability challenges. We explored three thematic areas to assess the current state of API use for data access and exchange in health care: (1) API use cases and standards; (2) challenges and facilitators for read and write capabilities; and (3) outlook for development of write capabilities. METHODS: We employed four methods: (1) literature review; (2) expert interviews with 13 API stakeholders; (3) review of electronic health record (EHR) app galleries; and (4) a technical expert panel. We used an eight-dimension sociotechnical model to organize our findings. RESULTS: The API ecosystem is complicated and cuts across five of the eight sociotechnical model dimensions: (1) app marketplaces support a range of use cases, the majority of which target providers' needs, with far fewer supporting patient access to data; (2) current focus on read APIs with limited use of write APIs; (3) where standards are used, they are largely Fast Healthcare Interoperability Resources (FHIR); (4) FHIR-based APIs support exchange of electronic health information within the common clinical data set; and (5) validating external data and data sources for clinical decision making creates challenges to provider workflows. CONCLUSION: While the use of APIs in health care is increasing rapidly, it is still in the pilot stages. We identified five key issues with implications for the continued advancement of API use: (1) a robust normative FHIR standard; (2) expansion of the common clinical data set to other data elements; (3) enhanced support for write implementation; (4) data provenance rules; and (5) data governance rules. Thus, while APIs are being touted as a solution to interoperability challenges, they remain an emerging technology that is only one piece of a multipronged approach to data access and use.

Application Programming Interfaces (APIs) in Health Care: Findings from a Current-State Assessment.

Interest in application programming interfaces (APIs) as a means to increase health data access and exchange among patients, health care providers, and payers has become an important area for development. In an effort to better understand the various contexts in which APIs can be applied, we explored different use cases. While APIs and our collective understanding of the best ways to implement and use them continue to develop, in the coming years the use of proprietary and standards-based APIs could be key to the sustainability of applied clinical informatics research, as well as associated improvements in patient engagement, clinical decision making, efficiency, quality and safety of the healthcare delivery system.

Changes in hospital bond ratings after the transition to a new electronic health record.

Objective: To assess the impact of electronic health record (EHR) implementation on hospital finances. Materials and Methods: We analyzed the impact of EHR implementation on bond ratings and net income from service to patients (NISP) at 32 hospitals that recently implemented a new EHR and a set of controls. Results: After implementing an EHR, 7 hospitals had a bond downgrade, 7 had a bond upgrade, and 18 had no changes. There was no difference in the likelihood of bond rating changes or in changes to NISP following EHR go-live when compared to control hospitals. Discussion: Most hospitals in our analysis saw no change in bond ratings following EHR go-live, with no significant differences observed between EHR implementation and control hospitals. There was also no apparent difference in NISP. Conclusions: Implementation of an EHR did not appear to have an impact on bond ratings at the hospitals in our analysis.

Enabling Health Reform through Regional Health Information Exchange: A Model Study from China.

Objective. To investigate and share the major challenges and experiences of building a regional health information exchange system in China in the context of health reform. Methods. This study used interviews, focus groups, a field study, and a literature review to collect insights and analyze data. The study examined Xinjin's approach to developing and implementing a health information exchange project, using exchange usage data for analysis. Results. Within three years and after spending approximately $2.4 million (15 million RMB), Xinjin County was able to build a complete, unified, and shared information system and many electronic health record components to integrate and manage health resources for 198 health institutions in its jurisdiction, thus becoming a model of regional health information exchange for facilitating health reform. Discussion. Costs, benefits, experiences, and lessons were discussed, and the unique characteristics of the Xinjin case and a comparison with US cases were analyzed. Conclusion. The Xinjin regional health information exchange system is different from most of the others due to its government-led, government-financed approach. Centralized and coordinated efforts played an important role in its operation. Regional health information exchange systems have been proven critical for meeting the global challenges of health reform.

Reducing Unnecessary Shoulder MRI Examinations Within a Capitated Health Care System: A Potential Role for Shoulder Ultrasound.

PURPOSE: MRI is frequently overused. The aim of this study was to analyze shoulder MRI ordering practices within a capitated health care system and explore the potential effects of shoulder ultrasound substitution. METHODS: We reviewed medical records of 237 consecutive shoulder MRI examinations performed in 2013 at a Department of Veterans Affairs tertiary care hospital. Using advanced imaging guidelines, we assessed ordering appropriateness of shoulder MRI and estimated the proportion of examinations for which musculoskeletal ultrasound could have been an acceptable substitute, had it been available. We then reviewed MRI findings and assessed if ultrasound with preceding radiograph would have been adequate for diagnosis, based on literature reports of shoulder ultrasound diagnostic performance. RESULTS: Of the 237 examinations reviewed, 106 (45%) were deemed to be inappropriately ordered, most commonly because of an absent preceding radiograph (n = 98; 92%). Nonorthopedic providers had a higher frequency of inappropriate ordering (44%) relative to orthopedic specialists (17%) (P = .016; odds ratio = 3.15, 95% confidence interval = 1.24-8.01). In the 237 examinations, ultrasound could have been the indicated advanced imaging modality for 157 (66%), and most of these (133/157; 85%) could have had all relevant pathologies characterized when combined with radiographs. Regardless of indicated modality, ultrasound could have characterized 80% of all cases ordered by nonorthopedic providers and 50% of cases ordered by orthopedic specialists (P = .007). CONCLUSIONS: Advanced shoulder imaging is often not ordered according to published appropriateness criteria. While nonorthopedic provider orders were more likely to be inappropriate, inappropriateness persisted among orthopedic providers. A combined ultrasound and radiograph evaluation strategy could accurately characterize shoulder pathologies for most cases.

Problem list completeness in electronic health records: A multi-site study and assessment of success factors.

OBJECTIVE: To assess problem list completeness using an objective measure across a range of sites, and to identify success factors for problem list completeness. METHODS: We conducted a retrospective analysis of electronic health record data and interviews at ten healthcare organizations within the United States, United Kingdom, and Argentina who use a variety of electronic health record systems: four self-developed and six commercial. At each site, we assessed the proportion of patients who have diabetes recorded on their problem list out of all patients with a hemoglobin A1c elevation>=7.0%, which is diagnostic of diabetes. We then conducted interviews with informatics leaders at the four highest performing sites to determine factors associated with success. Finally, we surveyed all the sites about common practices implemented at the top performing sites to determine whether there was an association between problem list management practices and problem list completeness. RESULTS: Problem list completeness across the ten sites ranged from 60.2% to 99.4%, with a mean of 78.2%. Financial incentives, problem-oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture were identified as success factors at the four hospitals with problem list completeness at or near 90.0%. DISCUSSION: Incomplete problem lists represent a global data integrity problem that could compromise quality of care and put patients at risk. There was a wide range of problem list completeness across the healthcare facilities. Nevertheless, some facilities have achieved high levels of problem list completeness, and it is important to better understand the factors that contribute to success to improve patient safety. CONCLUSION: Problem list completeness varies substantially across healthcare facilities. In our review of EHR systems at ten healthcare facilities, we identified six success factors which may be useful for healthcare organizations seeking to improve the quality of their problem list documentation: financial incentives, problem oriented charting, gap reporting, shared responsibility, links to billing codes, and organizational culture.

Cross-vendor evaluation of key user-defined clinical decision support capabilities: a scenario-based assessment of certified electronic health records with guidelines for future development.

OBJECTIVE: Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems. METHODS: We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin. RESULTS: Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules. CONCLUSION: Significant improvements in the EHR certification and implementation procedures are necessary.

The use of sequential pattern mining to predict next prescribed medications.

BACKGROUND: Therapy for certain medical conditions occurs in a stepwise fashion, where one medication is recommended as initial therapy and other medications follow. Sequential pattern mining is a data mining technique used to identify patterns of ordered events. OBJECTIVE: To determine whether sequential pattern mining is effective for identifying temporal relationships between medications and accurately predicting the next medication likely to be prescribed for a patient. DESIGN: We obtained claims data from Blue Cross Blue Shield of Texas for patients prescribed at least one diabetes medication between 2008 and 2011, and divided these into a training set (90% of patients) and test set (10% of patients). We applied the CSPADE algorithm to mine sequential patterns of diabetes medication prescriptions both at the drug class and generic drug level and ranked them by the support statistic. We then evaluated the accuracy of predictions made for which diabetes medication a patient was likely to be prescribed next. RESULTS: We identified 161,497 patients who had been prescribed at least one diabetes medication. We were able to mine stepwise patterns of pharmacological therapy that were consistent with guidelines. Within three attempts, we were able to predict the medication prescribed for 90.0% of patients when making predictions by drug class, and for 64.1% when making predictions at the generic drug level. These results were stable under 10-fold cross validation, ranging from 89.1%-90.5% at the drug class level and 63.5-64.9% at the generic drug level. Using 1 or 2 items in the patient's medication history led to more accurate predictions than not using any history, but using the entire history was sometimes worse. CONCLUSION: Sequential pattern mining is an effective technique to identify temporal relationships between medications and can be used to predict next steps in a patient's medication regimen. Accurate predictions can be made without using the patient's entire medication history.

Factors associated with radiation therapy incidents in a large academic institution.

BACKGROUND: This study evaluated factors associated with radiation therapy (RT) planning and delivery incidents at a large academic institution. METHODS AND MATERIALS: The RT incidents (including near-misses) were recorded using an electronic incident reporting system from April 1, 2011 to April 30, 2013. Each incident's origin was categorized according to the step in the treatment process (simulation, physician prescription, treatment planning, scheduling, treatment delivery, and other) in which it occurred. The incident database was linked to the RT delivery (record and verify) database to evaluate the effect of various factors on the rate of RT incidents. RESULTS: There were 189 reported RT incidents (including near-misses) among 326,448 fractions, of which there were 70 (37%) treatment planning incidents and 56 (30%) treatment delivery incidents. The rates of total incidents, planning incidents, and delivery incidents were 136.0, 50.4, and 40.3 per 10,000 patients, respectively. Logistic multivariate analysis showed that fewer work days from plan approval to treatment start, fewer fractions, higher number of prescription items, and longer beam duration were significantly associated with radiation planning incidents. Multivariate analysis also showed that first day of treatment, fewer fractions, higher number of prescription items, and longer beam duration were significantly associated with treatment delivery incidents; intensity modulated radiation therapy was associated with a lower rate of treatment delivery incidents. CONCLUSIONS: More complicated radiation plans, fewer fractions, first day of treatment, and rushed processes were associated with higher risk of RT incidents. We hope that a national incident reporting database will lead to greater understanding of factors influencing the rate of RT incidents.

Electronic health record-related safety concerns: a cross-sectional survey.

Federal electronic health record (EHR)-related initiatives are leading to rapid increases in their adoption. Despite their benefits, EHRs also introduce new risks that can lead to serious safety events. We conducted a Web-based survey of the American Society for Healthcare Risk Management and the American Health Lawyers Association to elicit perceptions regarding the frequency and types of EHR-related serious safety events. We received 369 responses. The majority (66%) worked for large hospitals and health systems with varying degrees of EHR adoption. More than half (53%) of respondents reported at least one EHR-related serious safety event in the previous 5 years, and 10% reported more than 20 events. EHR workflow (63%), user familiarity with the EHR system (63%), and integration with existing systems (59%) were most frequently endorsed as variables associated with EHR-related serious safety events. Because EHR-related safety concerns are underreported, organizations should consider implementing robust measures of EHR safety within their institution as a key step for mitigating these concerns.

The Medicare Electronic Health Record Incentive Program: provider performance on core and menu measures.

OBJECTIVE: To measure performance by eligible health care providers on CMS's meaningful use measures. DATA SOURCE: Medicare Electronic Health Record Incentive Program Eligible Professionals Public Use File (PUF), which contains data on meaningful use attestations by 237,267 eligible providers through May 31, 2013. STUDY DESIGN: Cross-sectional analysis of the 15 core and 10 menu measures pertaining to use of EHR functions reported in the PUF. PRINCIPAL FINDINGS: Providers in the dataset performed strongly on all core measures, with the most frequent response for each of the 15 measures being 90-100 percent compliance, even when the threshold for a particular measure was lower (e.g., 30 percent). PCPs had higher scores than specialists for computerized order entry, maintaining an active medication list, and documenting vital signs, while specialists had higher scores for maintaining a problem list, recording patient demographics and smoking status, and for providing patients with an after-visit summary. In fact, 90.2 percent of eligible providers claimed at least one exclusion, and half claimed two or more. CONCLUSIONS: Providers are successfully attesting to CMS's requirements, and often exceeding the thresholds required by CMS; however, some troubling patterns in exclusions are present. CMS should raise program requirements in future years.

Characteristics of health IT outage and suggested risk management strategies: an analysis of historical incident reports in China.

BACKGROUND: The healthcare industry has become increasingly dependent on using information technology (IT) to manage its daily operations. Unexpected downtime of health IT systems could therefore wreak havoc and result in catastrophic consequences. Little is known, however, regarding the nature of failures of health IT. OBJECTIVE: To analyze historical health IT outage incidents as a means to better understand health IT vulnerabilities and inform more effective prevention and emergency response strategies. METHODS: We studied news articles and incident reports publicly available on the internet describing health IT outage events that occurred in China. The data were qualitatively analyzed using a deductive grounded theory approach based on a synthesized IT risk model developed in the domain of information systems. RESULTS: A total of 116 distinct health IT incidents were identified. A majority of them (69.8%) occurred in the morning; over 50% caused disruptions to the patient registration and payment collection functions of the affected healthcare facilities. The outpatient practices in tertiary hospitals seem to be particularly vulnerable to IT failures. Software defects and overcapacity issues, followed by malfunctioning hardware, were among the principal causes. CONCLUSIONS: Unexpected health IT downtime occurs more and more often with the widespread adoption of electronic systems in healthcare. Risk identification and risk assessments are essential steps to developing preventive measures. Equally important is institutionalization of contingency plans as our data show that not all failures of health IT can be predicted and thus effectively prevented. The results of this study also suggest significant future work is needed to systematize the reporting of health IT outage incidents in order to promote transparency and accountability.

Exploring the sociotechnical intersection of patient safety and electronic health record implementation.

OBJECTIVE: The intersection of electronic health records (EHR) and patient safety is complex. To examine the applicability of two previously developed conceptual models comprehensively to understand safety implications of EHR implementation in the English National Health Service (NHS). METHODS: We conducted a secondary analysis of interview data from a 30-month longitudinal, prospective, case study-based evaluation of EHR implementation in 12 NHS hospitals. We used a framework analysis approach to apply conceptual models developed by Sittig and Singh to understand better EHR implementation and use: an eight-dimension sociotechnical model and a three-phase patient safety model (safe technology, safe use of technology, and use of technology to improve safety). RESULTS: The intersection of patient safety and EHR implementation and use was characterized by risks involving technology (hardware and software, clinical content, and human-computer interfaces), the interaction of technology with non-technological factors, and improper or unsafe use of technology. Our data support that patient safety improvement activities as well as patient safety hazards change as an organization evolves from concerns about safe EHR functionality, ensuring safe and appropriate EHR use, to using the EHR itself to provide ongoing surveillance and monitoring of patient safety. DISCUSSION: We demonstrate the face validity of two models for understanding the sociotechnical aspects of safe EHR implementation and the complex interactions of technology within a healthcare system evolving from paper to integrated EHR. CONCLUSIONS: Using sociotechnical models, including those presented in this paper, may be beneficial to help stakeholders understand, synthesize, and anticipate risks at the intersection of patient safety and health information technology.

Patient access to medical records and healthcare outcomes: a systematic review.

OBJECTIVES: We conducted a systematic review to determine the effect of providing patients access to their medical records (electronic or paper-based) on healthcare quality, as defined by measures of safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity. METHODS: Articles indexed in PubMed from January 1970 to January 2012 were reviewed. Twenty-seven English-language controlled studies were included. Outcomes were categorized as measures of effectiveness (n=19), patient-centeredness (n=16), and efficiency (n=2); no study addressed safety, timeliness, or equity. RESULTS: Outcomes were equivocal with respect to several aspects of effectiveness and patient-centeredness. Efficiency outcomes in terms of frequency of in-person and telephone encounters were mixed. Access to health records appeared to enhance patients' perceptions of control and reduced or had no effect on patient anxiety. CONCLUSION: Although few positive findings generally favored patient access, the literature is unclear on whether providing patients access to their medical records improves quality.