Anesthesia information management systems: past, present, and future of anesthesia records

Documenting a patient's anesthetic in the medical record is quite different from summarizing an office visit, writing a surgical procedure note, or recording other clinical encounters. Some of the biggest differences are the frequent sampling of physiologic data, volume of data, and diversity of data collected. The goal of the anesthesia record is to accurately and comprehensively capture a patient's anesthetic experience in a succinct format. Having ready access to physiologic trends is essential to allowing anesthesiologists to make proper diagnoses and treatment decisions. Although the value provided by anesthesia information management systems and their functions may be different than other electronic health records, the real benefits of an anesthesia information management system depend on having it fully integrated with the other health information technologies. An anesthesia information management system is built around the electronic anesthesia record and incorporates anesthesia-relevant data pulled from disparate systems such as laboratory, billing, imaging, communication, pharmacy, and scheduling. The ability of an anesthesia information management system to collect data automatically enables anesthesiologists to reliably create an accurate record at all times, regardless of other concurrent demands. These systems also have the potential to convert large volumes of data into actionable information for outcomes research and quality-improvement initiatives. Developing a system to validate the data is crucial in conducting outcomes research using large datasets. Technology innovations outside of healthcare, such as multitouch interfaces, near-instant software response times, powerful but simple search capabilities, and intuitive designs, have raised the bar for users' expectations of health information technology.     

Disclosure of adverse events and errors in healthcare: an ethical perspective.

Adverse events and medical errors affecting patient care are recognised internationally as major problems in medicine. The failure of health care professionals and health institutes to address this problem has threatened to undermine public confidence in the health care system as a whole. Less focus has been directed at the ethical issues raised by negative outcomes of care, specifically the issue of disclosure. Efforts to prevent negative outcomes of care must be supplemented by policies of increased honesty and openness with patients and their families about adverse incidents. Disclosure should be made easier, not riskier, for healthcare practitioners so clinicians can learn from mistakes and improve patient care. Ethical guidelines for error disclosure must distinguish between disciplinary action and reporting of adverse incidents. Disclosure of negative outcomes requires tact and good communication skills. Healthcare institutions should provide training for the clinicians in this area, if necessary. As a general rule, patients should be informed of unexpected adverse incidents as soon as possible. Medical staff should be rewarded for adverse event reporting and protected from institutional retaliation on account of errors made in health care.     

The Impact of Patient Access to Their Electronic Health Record on Medication Management Safety: A Narrative Review

IntroductionAs the American’s Federal Health Insurance Portability and Accountability Act (HIPAA) stated that patients should be allowed to review their medical records, and as information technology is ever more widely used by healthcare professionals and patients, providing patients with online access to their own medical records through a patient portal is becoming increasingly popular. Previous research has been done regarding the impact on the quality and safety of patients’ care, rather than explicitly on medication safety, when providing those patients with access to their electronic health records (EHRs).AimThis narrative review aims to summarise the results from previous studies on the impact on medication management safety concepts of adult patients accessing information contained in their own EHRs.ResultA total of 24 studies were included in this review. The most two commonly studied measures of safety in medication management were: (a) medication adherence and (b) patient-reported experience. Other measures, such as: discrepancies, medication errors, appropriateness and Adverse Drug Events (ADEs) were the least studied.ConclusionThe results suggest that providing patients with access to their EHRs can improve medication management safety. Patients pointed out improvements to the safety of their medications and perceived stronger medication control. The data from these studies lay the foundation for future research.     

Integrating pharmacists into Aboriginal Community Controlled Health Services (IPAC project): Protocol for an interventional,non-randomised study to improve chronic disease outcomes

BackgroundAboriginal and Torres Strait Islander peoples experience a higher burden of chronic disease yet have poorer access to needed medicines than other Australians. Adverse health outcomes from these illnesses can be minimised with improved prescribing quality. This project aims to improve quality of care outcomes for Aboriginal and Torres Strait Islander adult patients with chronic disease by integrating a pharmacist within primary health care teams in Aboriginal Community Controlled Health Services (ACCHSs).MethodologyThis non-randomised, prospective, pre and post quasi-experimental study, will be pragmatic, community-based and participatory, comparing outcomes and costs using paired patient data. Pharmacists will be integrated at 22 sites for approximately 15 months to conduct patient-related and practice-related activities through 10 core roles: providing medication management reviews, assessing adherence and medication appropriateness, providing medicines information and education and training, collaborating with healthcare teams, delivering preventive care, liaising with stakeholders, providing trnsitional care, and undertaking a drug utilisation review. With patients’ consent, de-identified client-level data will be extracted from clinical information systems and pharmacists will record deidentified activity in an electronic logbook. Primary expected outcomes include improvements in biometric indices (glycated haemoglobin, systolic and diastolic blood pressure, lipids, cardiovascular risk, albumin-creatinine ratio) from baseline to end of study. Expected secondary outcomes include improvements in estimated glomerular filtration rate, prescribing indices (appropriateness, overuse and underuse), medication adherence, self-assessed health, and health service utilisation indices. A qualitative assessment of stakeholder and patient perceptions and a cost-effectiveness analysis will be undertaken.DiscussionNumerous inquiries have recommended evaluating the impact of pharmacists integrated within primary health care settings. This study is the first to explore this impact on the health of Aboriginal and Torres Strait Islander peoples who are medically underserved. Evaluation of innovative integrated workforce models is necessary to address the challenges of delivering quality care together with this population.     

Framework to enable pharmacist access to health care data using Blockchain technology and artificial intelligence

BackgroundDecentralization and authentication are embedded in blockchain technology, which utilizes artificial intelligence (AI) to ensure seamless sharing of data among different health care providers while safeguarding data privacy. Although community pharmacists are highly accessible to patients and possess robust clinical knowledge, they are limited in the clinical services they can provide owing to their lack of access to patient health records. We proposed a blockchain- and AI-based conceptual framework by performing a scoping review of successful blockchain integration in health systems.ObjectiveTo formulate a conceptual framework based on a scoping review to improve access to health care data in the community pharmacy setting through the adoption of blockchain technology and AI.MethodsWe performed a scoping review of literature based on Preferred Reporting Items for Systematic reviews and Meta-Analyses review criteria to identify the specific areas where blockchain can be implemented in health systems. We utilized the Pharmacists’ Patient Care Process (PPCP) to identify 2 critical areas for blockchain integration that can support community pharmacists to access patient electronic health records and implement patient-specific information in clinical decision-making.ResultsWe included 7 articles out of 70 articles in our final review. The 2 areas in the PPCP identified for the use of blockchain on the basis of the literature review were “Assess” and “Implement.” Our proposed model involves pharmacists using AI and blockchain technology to comprehensively assess any concerns with the prescribed medication through access to laboratory results for patients and then implement a plan based on a comprehensive assessment of the patient’s health record.ConclusionsUtilizing blockchain to securely share health data with community pharmacies has the potential to improve patient outcomes, optimize medication safety, and amplify pharmacists’ roles in patient care. Future research should focus on implementing the model in the real-world settings.     

The Tennessee medication therapy management program: A hybrid type 2 effectiveness-implementation trial study protocol

BackgroundPharmacist-led medication therapy management (MTM) programs are considered evidence-based and have clearly defined core components. Despite this, MTM programs are often implemented without fidelity due to notable implementation barriers, such as physician-pharmacist relationships and pharmacist access to patient medical records. To improve MTM implementation, the Tennessee Medicaid program developed a MTM intervention that incorporates implementation strategies to address some of the known barriers to implementation (e.g., formalizing pharmacist-physician relationships through collaborative practice agreements, ensuring pharmacists’ access to medical records).ObjectivesThe purpose of this hybrid type 2 effectiveness-implementation study is to (1) assess the effectiveness of the MTM pilot program in Tennessee (e.g., medication adherence, healthcare utilization, quality and cost of care) and (2) assess the implementation of the MTM pilot program (e.g., feasibility, appropriateness, acceptability, penetration).MethodsThe Tennessee MTM pilot program is being assessed as a hybrid type 2 effectiveness-implementation study with a quasi-experimental design. A mixed methods approach (QUAN + QUAL) for the purpose of complementarity (e.g., answering related research questions). Data will include surveys, interviews, MTM platform encounter information, and medical and pharmacy claims. Initial analyses will include data between January 2018 and December 2019.ConclusionThe study will further add to the evidence base of MTM interventions by testing an intervention that addresses known barriers to implementation and simultaneously collecting data on effectiveness and implementation to speed up MTM translation. The Tennessee MTM program is expected to serve as a guide to other states seeking to expand pharmacist-delivered clinical services to their Medicaid members, particularly those intending to incorporate MTM into programs seeking to improve primary care delivery. Further, by improving the implementation of MTM, the pilot program is expected to improve the reliability of MTM program benefits including healthcare quality and cost and patient outcomes.     

Characteristics of Opiate Users Leaving Detoxification Treatment Against Medical Advice

ABSTRACT

Substance-dependent patients leaving against medical advice (AMA) pose a unique challenge to detoxification programs. Most notably, AMA patients fail to access residential or outpatient treatment needed after detoxification and often return to detoxification treatment multiple times which has deleterious results for the patient and is taxing to the healthcare system. Using retrospective data from 89 daily opiate-using detoxification patients completing detoxification and 95 patients leaving AMA, we sought to identify patient characteristics useful in predicting AMA discharges from detoxification. Bivariate analyses indicated that AMA patients reported drug use did not impair their health, were injection drug users, younger and had fewer previous treatment admissions. Binomial logistic regression indicated that AMA patients were more likely to be unemployed and report that drug use did not impair their health. Patients completing detoxification were less likely to be injection drug users and less likely to be self-referred to treatment. Identifying patients at risk of leaving AMA provides an opportunity for clinicians to intervene in an effort to increase treatment engagement for these patients.     

Zoned Out: “NIMBYism”, addiction services and municipal governance in British Columbia

In Canada, Provincial Governments have jurisdiction over delivery of healthcare including harm reduction services and Methadone Maintenance Therapy (MMT). While policy directives and funding come from the provincial capital, individuals’ access to these services happens in neighbourhoods and municipalities spread out across the province. In some cases, public health objectives targeted at people living with addictions and the rights to equitable access to healthcare are at odds with the vision that residents, business associations and other interest groups have for their neighbourhood or city.This paper looks at the cases of four British Columbia municipalities, Mission, Surrey, Coquitlam and Abbotsford, where local governments have used zoning provisions to restrict access to harm reduction services and drug substitution therapies including MMT. This paper will contextualize these case studies in a survey of zoning and bylaw provisions related to harm reduction and MMT across British Columbia, and examine the interplay between municipal actions and public discourses that affect access to healthcare for people living with addictions. Finally, this paper will explore possible legal implications for municipalities that use their zoning and permitting powers to restrict access to health care for people with addictions, as well as public engagement strategies for healthcare advocates that have the potential to reduce resistance to health services for people living with addictions in communities across the province.     

AMA's drug information data base: program capabilities and opportunities for clinical pharmacy

The AMA drug information base (AMA-DIB) is reviewed and the impact of computerized drug data bases on the practice of clinical pharmacy is discussed. The AMA-DIB is an on-line data base derived from the fifth edition of AMA Drug Evaluations. Thus, it represents consensus information. The data base consists of individual drug records, pharmacologic class records, and therapeutic class records. It is accessed via commands using keyword searches. Computerized on-line drug data bases will have an impact on the practice of clinical pharmacy. Information resource services will either discontinue or proliferate, depending on the quality of the service and the ability of the directors to adapt to future needs. Patient monitoring services will discover that these data bases allow easier access to more information, but the computer will not be able to transfer the data to direct patient care. Thus, their professional roles will remain intact. Clinical pharmacy researchers, in contrast, will notice little or no impact on their practice.     

利用补充真实世界数据研究获得更深层次的认识

摘 要随着患者、医护人员、药品注册人员和政策决定者对现实世界中各种诊疗手段的安全性和有效性相关证据的迫切需求,我们需要新的研究设计来高效有效地对此类问题进行评估。与此同时,越来越多的二手数据可以用来提供此种相关证据,常用的二手数据包括电子医疗档案和医疗保险数据等。补充真实世界数据研究同时利用了现有二手数据和通过医生/患者收集的一手数据,并将两者进行结合。在现有数据的基础上,补充真实世界数据研究可以集中精力收集缺失的重要信息来满足研究目的。本文将对补充真实世界数据研究进行介绍,包括研究设计要素,研究的优点和局限性,实施要点以及应用实例等。     

Designing solutions for securing patient privacy--meeting the demands of health care in the 21st century.

OBJECTIVES: To define the issues surrounding patient privacy, examine the political context in which debate is taking place, and present a novel technology model for addressing privacy, confidentiality, and security in 21st century health care. SUMMARY: The discussion of privacy addresses one of the basic issues in health care today--the tension between the needs of the individual patient for privacy and confidentiality and the needs of society to effectively manage health care practices and control health care costs. Patient concerns for privacy, confidentiality, and security are legitimate, and can usually be reduced to issues that potentially affect an individual's employment, ability to get and maintain health coverage, and have control over his or her records and care. These concerns, combined with several precipitating events, are forcing the issue of privacy into the political arena, where new health policy decisions will be made. The debate must be framed within a principle-centered approach that focuses on boundaries, security, consumer control, accountability, and public responsibility. A global, distributed electronic health record management model that provides location-independent, secured, authenticated access to relevant patient care records by qualified health care professionals on a need-to-know basis provides solutions. Information asset considerations should be designed to equitably represent the ownership needs of corporate entities, society, and the individual. CONCLUSION: A secure electronic health record structure that systematically ensures a high level of accountability combined with thoughtful dialogue among key stakeholders in the public policy development process can offer the privacy outcomes we seek.     

How Population Health Management and Big Data Can Rock Your World

Hospitals and health systems like yours have been aggressively pursuing a range of information systems over the last several decades. Cited goals are often efficiency, lower costs, better decisions, and better patient outcomes. But how do these systems purportedly lead to population-level improvements in care? In this column, we address the connections that are anticipated as well as challenges to be expected along the way.Let’s start with some definitions. Population health management, according to a leading outcomes management provider, is the “aggregation of patient data across multiple health information technology resources, the analysis of that data into a single, actionable patient record, and the actions through which care providers can improve both clinical and financial outcomes.”¹ While we like this definition because systems are used in a way that patient care is provided to individual patients, we think that the intelligence gained from each patient encounter can concurrently be applied throughout the continuum of care for any population being served. Big data is a buzzword in health care, even though other industries have been using the analysis of huge quantities of digitized data for many years. In health care, the rapid adoption of the electronic health record (EHR) provides an opportunity to finally having a real chance for improving health outcomes and controlling costs.The definition of big data varies, but we will define it as the “ability to access and analyze information that holds the key to more efficient, higherquality health care while significantly shortening the time between research and translation into practice.”² Big data is made possible because health care is now moving toward being a real digital enterprise to leverage the collective power of information. In our examination of health system technology devices that have been deployed for the last 10 years, we discovered that some had the ability to be networked but many were not. The EHR can now be the data hub for providers while supporting care provision by consolidating and analyzing these digital warehouses of real-time data to discover trends and make predictions.In a previous column, we described these processes as enterprise performance management. At a strategic level, a health system would generate critical success factors and key performance indicators that would lead to outcomes improvement. At an operational level, data would be gathered as a byproduct of rendering patient care to determine how well these indicators of success were being met. The system would generate e-mails to managers to give them feedback on any success factors assigned to them. Exception reports could include deficiencies, meeting of goals, and exceeding expectations. When best practices were identified within the enterprise, the methods being utilized to exceed expectations could then be used to address the problems experienced in units where expectations were not being met.In our experience, niche industries are being generated by the inability of EHR vendors to address both the developmental needs to improve their core product for its primary purpose of patient care and to add all of the population health and data analysis capabilities required. Add to this the fact that the individuals who are needed at the health system level to work with data analysis are the same people that Google and Microsoft are recruiting as quickly as possible. Thus, entrepreneurs look at the needs of health care and bring the skills and expertise necessary to the task. The expectation is that the EHR vendors who are going to cooperate by providing the needed data will eventually wrap the capabilities of these consultants into the everyday functions found in their systems.The complexity inherent in population health management is quite high. The data sources and their divergent information standards bring about the first challenge. Again, starting with a specific EHR, integration or interfaces must be established with any ambulatory electronic medical record being utilized by employed or affiliated providers. Each of these medical records could utilize one of 10 standards to include HL7, CCR, CCD, and so on that will need to be translated and normalized to be of any use for analysis. Next, we have separate computerized prescriber order entry systems, labs, imaging, health information exchanges, payers, and claims data. Each of these data sources must be integrated and normalized before they provide any real utility.Now we need to talk about clinical decision support systems. As a provider, you are probably already aware of the problem we call flag fatigue where alerts and warnings interrupt your provision of care for your patients. The challenge for an enterprise decision support system will be to ensure that the right provider is involved in the appropriate intervention at the appropriate point in the care process in the appropriate facility for the appropriate patient at the appropriate time. Get your mind around this complexity. Now think about multidisciplinary care team coordination and communication. How are we going to know who did what, when, and how?Alerts that are needed in population health management can also start when care gaps are identified. They can start when a patient steps on a digital scale that transmits a 10-lb weight gain due to heart failure–related edema. The alert may take place because patient outreach is indicated and an assignment for this task must be made. Action may be needed due to a patient’s entry in a notes section of a patient portal. Alerts may occur because quality reporting is either missing or the values entered have triggered the need for a response.Right now, we’re spending most of our time putting these data in and straddling the current reimbursement system that is so heavily based on fee-forservice care provision while preparing for anticipated, future ways of providing care. To understand how life will be different as these changes take place, look at those health systems that have already gone through significant population health management transitions and who use big data routinely to improve their operations.We have been attending presentations by health systems that have started with the care provision of their own employees as a way to get some small population experience in the area and then moved on to larger populations they were able to attract. Just Google “population health management” and explore testimonials on how care provision has changed among these frontrunners. Some will definitely rock your world or at least give you a few “ah-ha” moments. We would enjoy hearing your comments and questions on this topic. You can reach Bill at felkebg@auburn.edu or Brent at foxbren@auburn.edu.     

The role of insurance claims databases in drug therapy outcomes research

The use of insurance claims databases in drug therapy outcomes research holds great promise as a cost-effective alternative to post-marketing clinical trials. Claims databases uniquely capture information about episodes of care across healthcare services and settings. They also facilitate the examination of drug therapy effects on cohorts of patients and specific patient subpopulations. However, there are limitations to the use of insurance claims databases including incomplete diagnostic and provider identification data. The characteristics of the population included in the insurance plan, the plan benefit design, and the variables of the database itself can influence the research results. Given the current concerns regarding the completeness of insurance claims databases, and the validity of their data, outcomes research usually requires original data to validate claims data or to obtain additional information. Improvements to claims databases such as standardisation of claims information reporting, addition of pertinent clinical and economic variables, and inclusion of information relative to patient severity of illness, quality of life, and satisfaction with provided care will enhance the benefit of such databases for outcomes research.     

Going Virtual During a Pandemic: An Academic Psychiatry Department’s Experience with Telepsychiatry

Background:The novel coronavirus pandemic (COVID-19) led healthcare providers, including mental health providers, across the U.S. to swiftly shift to telemedicine.Objectives:This shift gave our Department of Psychiatry a chance to better understand key challenges and opportunities vis-à-vis virtual mental healthcare. We aimed to obtain provider feedback on the use of telepsychiatry and to learn from the provider perspective about patient experiences with video visits. This information will be used to inform the telemedicine strategy at a systems level within our psychiatry department, our academic health system, as well as the field of telemedicine as a whole. Design and Sample:A 22-item online questionnaire comprising 16 quantitative and six qualitative items was distributed to providers currently using video visits to provide care.Results:A total of 89 mental health providers completed the questionnaire. Outcomes demonstrated that while providers perceive challenges associated with virtual care (e.g., fatigue, technology-related issues, and age-related concerns), they also recognize a number of benefits to themselves and their patients (e.g., convenience and increased access). Overall, provider satisfaction, comfort, and willingness to use telepsychiatry was high.Conclusions:The vast majority of providers adapted quickly to the use of virtual platforms; many endorse advantages that suggest virtual care will continue to be a modality they provide in the future, post-COVID-19. It will be important to continue to evaluate aspects of virtual care that may limit clinical assessments and to optimize use to improve access, convenience, and cost-efficiency of mental healthcare delivery.     

Improving medication reconciliation in the 21st century

Approximately 7000 deaths occur yearly in the United States as a result of medication errors, and 1.5 million people are harmed by adverse drug events at a cost of $3.5 billion per year. Computerized order entry has been shown to decrease the number of medication errors by 55% to 80 % in the hospital. This has led many to advocate the use of electronic medical records in both the inpatient and outpatient setting. However, there is little evidence at present that electronic medical records reduce adverse drug events in the outpatient setting. This may be largely due to the quality of medication lists in the medical record: Among complicated patients, complete agreement between the medication list and what the patient is actually taking occurs in only 5% of patients. Unless there is improved medication reconciliation, it will be difficult to realize the potential safety benefits of information technology. An accurate medication list requires a healthcare team dedicated to obtaining and maintaining this information.     

The New US Federal Privacy Rules and Impact on Research

With the standardization of electronic claims for administrative simplification comes a concern that private information about health conditions and treatments could be released to those who are not involved with treatment, payment, or the operations of healthcare providers. Information may be published, or information may be used to discriminate against individuals in employment, receipt of healthcare, or other settings. To protect against unwanted disclosure and use of individual health information, new US federal rules have been released that establish what, when, to whom, by whom, and how health information may be disclosed and used. The rules are complex and many questions have been raised about their implementation. These Privacy Rules, promulgated under the Health Insurance Portability and Accountability Act of 1996 (HIPAA), prohibit the use or disclosure of ‘Protected Health Information’ by ‘Covered Entities’ unless specifically permitted by these rules. Covered Entities include providers (who conduct at least one electronic healthcare transaction), health plans and healthcare clearing houses. Protected Health Information includes individually identifiable information about a person’s condition, treatment or payment for treatment. Specific permitted pathways for disclosure and use of Protected Health Information include: (i) patient authorization; (ii) an Institutional Review Board or Privacy Board-approved waiver or alteration of authorization; (iii) a limited dataset; (iv) de-identified data; (v) reviews preparatory to research or on decedents; and (vi) disclosure to entities subject to US FDA jurisdiction.     

The Personalized Medicine Coalition

The concept of personalized medicine--that medical care can be tailored to the genomic and molecular profile of the individual--has repercussions that extend far beyond the technology that makes it possible. The adoption of personalized medicine will require changes in healthcare infrastructure, diagnostics and therapeutics business models, reimbursement policy from government and private payers, and a different approach to regulatory oversight. Personalized medicine will shift medical practices upstream from the reactive treatment of disease, to proactive healthcare management including screening, early treatment, and prevention, and will alter the roles of both physician and patient. It will create a greater reliance on electronic medical records and decision support systems in an industry that has a long history of resistance to information technology. Personalized medicine requires a systems approach to implementation. But in a healthcare economy that is highly decentralized and market driven, it is incumbent upon the stakeholders themselves to advocate for a consistent set of policies and legislation that pave the way for the adoption of personalized medicine. To address this need, the Personalized Medicine Coalition (PMC) was formed as a nonprofit umbrella organization of pharmaceutical, biotechnology, diagnostic, and information technology companies, healthcare providers and payers, patient advocacy groups, industry policy organizations, major academic institutions, and government agencies. The PMC provides a structure for achieving consensus positions among these stakeholders on crucial public policy issues, a role which will be vital to translating personalized medicine into widespread clinical practice. In this article, we outline the goals of the PMC, and the strategies it will take to foster communication, debate, and consensus on issues such as genetic discrimination, the reimbursement structures for pharmacogenomic drugs and diagnostics, regulation, physician training and medical school curricula, and public education.