Deficits in pain medication in older adults with chronic pain receiving home care: A cross-sectional study in Germany

OBJECTIVE: To analyze the pattern and appropriateness of pain medications in older adults receiving home care. METHODS: We performed a prospective cross-sectional study in patients ≥65 years old having chronic pain and receiving home care in Berlin, Germany. Data on prescribed pain medications were collected using self-reported information, nursing documents, and medication plans during interviews at home. Pain intensity was determined with the numeric rating scale (NRS) and the Pain Assessment In Advanced dementia (PAINAD) scale. The Pain Medication Appropriateness Scale score (SPMAS) was applied to evaluate inappropriateness (i.e. a score ≤67) of pain medication. RESULTS: Overall 322 patients with a mean age of 82.1 ± 7.4 years (71.4% females) were evaluated. The average pain intensity scores during the last 24 hours were 5.3 ± 2.1 and 2.3 ± 2.3 on NRS and PAINAD scale (range 0-10, respectively). Sixty (18.6%) patients did not receive any pain medication. Among the treated patients, dipyrone was the most frequently prescribed analgesic (71.4%), while 50.8% and 19.1% received systemic treatment with opioids and non-steroidal anti-inflammatory drugs, respectively. The observed median SPMAS was 47.6 (range 0-100) with 58 (18.0%) of patients achieving appropriate values. Half of the patients were treated with scheduled, while 29.9% were only treated with on-demand medications. Cognitive status had no effect on appropriateness of pain treatment. CONCLUSIONS: We observed substantial deficits in dosing patterns and appropriateness of pain medication in older adults with pain receiving home care. This applied to both patients with and without severe cognitive impairment

Extracting information from the text of electronic medical records to improve case detection: a systematic review

Background: Electronic medical records (EMRs) are revolutionizing health-related research. One key issue for study quality is the accurate identification of patients with the condition of interest. Information in EMRs can be entered as structured codes or unstructured free text. The majority of research studies have used only coded parts of EMRs for case-detection, which may bias findings, miss cases, and reduce study quality. This review examines whether incorporating information from text into case-detection algorithms can improve research quality. Methods: A systematic search returned 9659 papers, 67 of which reported on the extraction of information from free text of EMRs with the stated purpose of detecting cases of a named clinical condition. Methods for extracting information from text and the technical accuracy of case-detection algorithms were reviewed. Results: Studies mainly used US hospital-based EMRs, and extracted information from text for 41 conditions using keyword searches, rule-based algorithms, and machine learning methods. There was no clear difference in case-detection algorithm accuracy between rule-based and machine learning methods of extraction. Inclusion of information from text resulted in a significant improvement in algorithm sensitivity and area under the receiver operating characteristic in comparison to codes alone (median sensitivity 78% (codes + text) vs 62% (codes), P = .03; median area under the receiver operating characteristic 95% (codes + text) vs 88% (codes), P = .025). Conclusions: Text in EMRs is accessible, especially with open source information extraction algorithms, and significantly improves case detection when combined with codes. More harmonization of reporting within EMR studies is needed, particularly standardized reporting of algorithm accuracy metrics like positive predictive value (precision) and sensitivity (recall)

Handbuch Kommunikationsstrategien zur Schärfung des Umweltbewusstseins im Umgang mit Arzneimitteln : Forschungsvorhaben 37 08 61 400 des Umweltbundesamtes

In Germany, as in almost all industrial countries, active pharmaceutical substances can now be found in virtually all water bodies and occasionally also in drinking water. Even though the concentrations in question tend to be very low, there are initial signs of their impact on aquatic life. There is no evidence as yet of any acute consequences for human health. It is, however, impossible to rule out long-term consequences from these minimal concentrations or unexpected effects from the interaction between various active ingredients (cocktail effect). At special risk here are sensitive segments of the population such as children and the chronically ill. There is thus a need for action on precautionary grounds. The main actors in the health system are largely unaware of the problem posed by drug residues in water. Although knowledge cannot be equated with awareness – given the existence of the ‘not wanting to know' phenomenon – the first step is to generate a consolidated knowledge base. Only by creating awareness of the problem can further strategies be implemented to ultimately enlighten and bring about behavioural change. At stake here is the overall everyday handling of medications, including prescription, compliance, and drug-free disease prevention down to the doctor-patient relationship. The latter, namely, is often characterised by misunderstandings and a lack of communication about the – supposed – need to prescribe drugs. The first part of the strategy for the general public involves using various channels and media to address three different target groups. These were identified by ISOE in an empirical survey as reacting differently to the problem under review: · ‘The Deniers/Relativists' · ‘The Truth-Seekers' · ‘The Hypersensitives' The intention is to address each target group in the right tone and using the most suitable line of reasoning via specific media and with the proper degree of differentiation. The ‘Truth-Seekers' play an opinion-leading role here. They can be provided with highly differentiated information through sophisticated media which they then pass on to their dialogue partners in an appropriate form. The second part of the strategy for the general public relates to the communication of proper disposal routes for expired drugs. The goal is to confine disposal to pharmacies so that on no account are they flushed down the sink or toilet. Based on an analysis of typical errors in existing communications media on this topic, ISOE prepared recommendations for drafting proper information materials. In addressing pharmacists, the first priority is to convey hard facts: to this end we propose a PR campaign to place articles in the main specialist media. At the same time, the subject should feature in training and continuing education programmes. Another aim is to strengthen the advisory function of the pharmacies. The environmentally sensitive target group would indeed react positively to having their attention drawn to the issue of drug residues in water. For all other customers, the pharmacists can and should act as consultants: they emphasise how important it is to take medication as instructed (compliance) and use suitable pack sizes, and warn older customers in particular about the potential hazards of improper drug intake. The first stage of the communications strategy for doctors likewise revolves around knowledge. Here, however, it is important to take into account their self-image as scientists while in fact having little grasp of this specific area. The line to take is that of ‘discursive selfenlightenment'. This means that the issue of drug residues in water cannot be conveyed to doctors by laymen but must be taken up and imparted via the major media of the medical profession and by medical association officials (top-down). The second stage, namely that of raising doctors’ awareness of the problem, is likely to encounter strong resistance from some of the medical profession. They may fear a threat of interference in treatment plans from an environmental perspective and feel the need to emphasise that doctors are not responsible for environmental issues. As shown in empirical surveys by ISOE, such a defensive reaction is ultimately down to an underlying taboo: people are loath to discuss the over-prescription taking place in countless doctors' surgeries. And it is a fact that this problem cannot be tackled from the environmental perspective, although the goals of water protection are indeed consistent with the economic objectives of restraint in the deployment of drugs. Any communications measure for this target group has to bear in mind that doctors feel restricted by what they see as a ‘perpetual health reform' no matter which government is in power. On no account are they prepared to tolerate any new form of regulation, in this case for environmental reasons. An entirely different view of the problem is taken by ‘critical doctors' such as specialists in environmental health and those with a naturopathic focus. They are interested in the problem because they see a connection between the quality of our environment and our health. What is more, they have patients keen to be prescribed as few drugs as possible and who are instead interested in ‘talking medicine'. So, any communication strategy intent on tackling the difficult problem of oversubscribing drugs needs to look carefully at the experiences of these medical professionals and also at a ‘bottom-up strategy'. Implementation of strategic communications should be entrusted to an agency with experience in ‘issue management'. Knowledge of social marketing and the influencing of behaviour are further prerequisites. All important decisions should be taken by a consensus committee (‘MeriWa'1 round table), in which the medical profession, pharmacists and consumers are represented.In Deutschland und in fast allen Industrieländern finden sich mittlerweile Medikamentenwirkstoffe in nahezu allen Gewässern und vereinzelt auch im Trinkwasser. Auch wenn die Konzentrationen in der Regel sehr gering sind, lassen sich erste Anzeichen für Auswirkungen auf Wasserlebewesen nachweisen. Akute Folgen für die menschliche Gesundheit sind bisher nicht erwiesen. Es kann allerdings nicht ausgeschlossen werden, dass sich Langzeitfolgen dieser Niedrigstkonzentrationen entwickeln und unerwartete Effekte durch die Wechselwirkung zwischen verschiedenen Wirkstoffen (Cocktaileffekt) entstehen. Besonders gefährdet sind dabei sensible Bevölkerungsgruppen wie Kinder und chronisch Kranke. Es besteht daher nicht zuletzt aus Vorsorgegründen Handlungsbedarf. Das Problem der Medikamentenreste im Wasser ist bei den wichtigsten Akteuren des Gesundheitssystems weitgehend unbekannt. Auch wenn Wissen nicht mit Bewusstsein gleichgesetzt werden kann – denn es gibt auch das Phänomen des Nicht-Wissen-Wollens – geht es in einem ersten Schritt darum, fundiertes Wissen zu erzeugen. Nur auf Basis dieser Sensibilisierung können weitere Strategien umgesetzt und letztendlich Aufklärung und Verhaltensänderungen erreicht werden. Dabei geht es um die gesamte Alltagspraxis im Umgang mit Medikamenten. Diese umfasst Fragen der Verschreibung, der Compliance, der nichtmedikamentösen Krankheitsvorsorge bis hin zum Arzt-Patienten-Verhältnis. Das ist nämlich häufig von Missverständnissen und mangelnder Kommunikation über – vermeintliche – Verschreibungsnotwendigkeiten geprägt. Der erste Teil der Strategie für die Bevölkerung soll über unterschiedliche Kanäle und Medien drei unterschiedliche Zielgruppen ansprechen, die in einer empirischen Untersuchung vom ISOE identifiziert wurden und auf das angesprochene Problem ganz unterschiedlich reagieren: · ‚Die Verleugner/Relativierer‘ · ‚Die Aufklärungsinteressierten‘ · ‚Die Hypersensiblen‘ Jede Zielgruppe soll in der passenden sprachlichen und argumentativen Art und Weise durch spezifische Medien und mit dem richtigen Grad der Differenziertheit angesprochen werden. Dabei spielen „die Aufklärungsinteressierten“ eine Opinionleader-Rolle. Sie können über anspruchsvolle Medien mit sehr differenzierten Informationen versorgt werden und geben dieses Wissen dann in angemessener Form an ihre Gesprächspartner weiter. Der zweite Teil der Strategie für die Bevölkerung bezieht sich auf die Kommunikation richtiger Entsorgungswege für Altmedikamente. Ziel ist es, dass Medikamentenreste nur noch in der Apotheke, keinesfalls aber in der Spüle oder in der Toilette entsorgt werden. Auf Grundlage einer Analyse typischer Fehler in bereits bestehenden Kommunikationsmedien zu diesem Thema hat das ISOE Empfehlungen zur richtigen Konzeption von Infomaterialien erarbeitet. Bei der Ansprache der Apotheker geht es in einem ersten Schritt um die Vermittlung von Faktenwissen: Wir schlagen dazu eine PR-Kampagne vor, die Artikel in den wichtigsten Fachmedien platziert. Gleichzeitig soll das Thema auch Teil der Aus- und Fortbildung werden. Zusätzlich soll die Beraterfunktion der Apotheken gestärkt werden. Die spezielle Zielgruppe der umweltsensiblen Kunden würde durchaus positiv darauf reagieren, wenn sie auf die Problematik der Medikamentenreste im Wasser hingewiesen würde. Bei allen anderen Kunden können und sollen die Apotheker ihre Rolle als Berater wahrnehmen: Sie betonen, wie wichtig die korrekte Einnahme (Compliance) und adäquate Packungsgrößen sind und warnen ihre Kunden, insbesondere die älteren, auch vor potenziellen Fehleinnahmen. Bei der Kommunikationsstrategie für Ärzte geht es im ersten Schritt ebenfalls um Wissen. Dabei muss aber deren Selbstverständnis als Wissenschaftler bei gleichzeitig niedrigem Wissensstand in diesem speziellen Feld berücksichtigt werden. Hier muss der Weg einer ‚diskursiven Selbstaufklärung‘ beschritten werden. Das Thema Medikamentenreste im Wasser kann somit nicht von Laien von außen an die Ärzte herangetragen werden, sondern muss in wichtigen Medien der Ärzteschaft und durch Verbandsfunktionäre angenommen und kommuniziert werden (top-down). Wenn es im zweiten Schritt um eine Problemsensibilisierung geht, muss mit starkem Widerstand eines Teils der Ärzteschaft gerechnet werden. Sie könnten fürchten, dass eine Einmischung in Heilungspläne aus Umweltsicht droht und betonen, dass Ärzte nicht für Umweltfragen zuständig seien. Letztlich steht – das haben empirische Untersuchungen des ISOE gezeigt – hinter dieser Problemabwehr ein Tabu: Es soll nicht darüber gesprochen werden, dass in zahlreichen Praxen zu viel verschrieben wird. Diese Problematik kann tatsächlich nicht aus der Umweltperspektive angegangen werden. Doch decken sich hier die Ziele des Gewässerschutzes mit den ökonomischen Zielen eines sparsamen Umgangs mit Arzneimitteln. Bei jeder Kommunikationsmaßnahme für diese Zielgruppe muss berücksichtigt werden, dass sich die Ärzte von dem, was sie als ‚Dauergesundheitsreform‘ aller Regierungen wahrnehmen, gegängelt fühlen. Sie sind keinesfalls bereit, eine neue Form der Regulierung, diesmal aus Umweltgründen, hinzunehmen. Ganz anders wird das Problem von ‚kritischen Ärzten‘ wie Umweltmedizinern und von Ärzten mit Naturheilschwerpunkt gesehen. Sie interessieren sich für die Problematik, weil sie einen Zusammenhang zwischen Umweltqualität und Gesundheit sehen. Außerdem haben sie Patienten, die an möglichst wenig Medikamentenverschreibungen, dafür aber an einer ‚sprechenden Medizin‘ interessiert sind. Wenn eine Kommunikationsstrategie also auch das schwierige Problem der übermäßigen Verschreibungen angehen will, empfiehlt es sich, die Erfahrungen dieser Mediziner einzubeziehen und zusätzlich auf eine ‚Bottom-up-Strategie‘ abzuzielen. Mit der Umsetzung der strategischen Kommunikation sollte eine Agentur beauftragt werden, die Erfahrungen im ‚Issue Management‘ vorweisen kann. Weiterhin sollte die Agentur Kenntnisse im Social Marketing und der Beeinflussung von Verhalten haben. Alle wichtigen Entscheidungen sollten von einem Konsens-Gremium (Runder Tisch ‚MeriWa‘1) verabschiedet werden, in dem die Ärzteschaft, die Apotheker sowie die Verbraucherinnen und Verbraucher angemessen repräsentiert sind

Knowledge-based best of breed approach for automated detection of clinical events based on German free text digital hospital discharge letters

OBJECTIVES: The secondary use of medical data contained in electronic medical records, such as hospital discharge letters, is a valuable resource for the improvement of clinical care (e.g. in terms of medication safety) or for research purposes. However, the automated processing and analysis of medical free text still poses a huge challenge to available natural language processing (NLP) systems. The aim of this study was to implement a knowledge-based best of breed approach, combining a terminology server with integrated ontology, a NLP pipeline and a rules engine. METHODS: We tested the performance of this approach in a use case. The clinical event of interest was the particular drug-disease interaction "proton-pump inhibitor [PPI] use and osteoporosis". Cases were to be identified based on free text digital discharge letters as source of information. Automated detection was validated against a gold standard. RESULTS: Precision of recognition of osteoporosis was 94.19%, and recall was 97.45%. PPIs were detected with 100% precision and 97.97% recall. The F-score for the detection of the given drug-disease-interaction was 96,13%. CONCLUSION: We could show that our approach of combining a NLP pipeline, a terminology server, and a rules engine for the purpose of automated detection of clinical events such as drug-disease interactions from free text digital hospital discharge letters was effective. There is huge potential for the implementation in clinical and research contexts, as this approach enables analyses of very high numbers of medical free text documents within a short time period

Electronic Medical Records for Discovery Research in Rheumatoid Arthritis

Objective: Electronic medical records (EMRs) are a rich data source for discovery research but are underutilized due to the difficulty of extracting highly accurate clinical data. We assessed whether a classification algorithm incorporating narrative EMR data (typed physician notes) more accurately classifies subjects with rheumatoid arthritis (RA) compared with an algorithm using codified EMR data alone. Methods: Subjects with ≥1 International Classification of Diseases, Ninth Revision RA code (714.xx) or who had anti–cyclic citrullinated peptide (anti-CCP) checked in the EMR of 2 large academic centers were included in an “RA Mart” (n = 29,432). For all 29,432 subjects, we extracted narrative (using natural language processing) and codified RA clinical information. In a training set of 96 RA and 404 non-RA cases from the RA Mart classified by medical record review, we used narrative and codified data to develop classification algorithms using logistic regression. These algorithms were applied to the entire RA Mart. We calculated and compared the positive predictive value (PPV) of these algorithms by reviewing the records of an additional 400 subjects classified as having RA by the algorithms. Results: A complete algorithm (narrative and codified data) classified RA subjects with a significantly higher PPV of 94% than an algorithm with codified data alone (PPV of 88%). Characteristics of the RA cohort identified by the complete algorithm were comparable to existing RA cohorts (80% women, 63% anti-CCP positive, and 59% positive for erosions). Conclusion: We demonstrate the ability to utilize complete EMR data to define an RA cohort with a PPV of 94%, which was superior to an algorithm using codified data alone.National Library of Medicine (U.S.) (Award U54LM008748)National Institutes of Health (U.S.). i2b2 (Informatics for Integrating Biology and the Bedside) (Grant U54-LM008748

J Biomed Inform

We followed a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) systems that generate structured information from unstructured free text. Seven literature databases were searched with a query combining the concepts of natural language processing and structured data capture. Two reviewers screened all records for relevance during two screening phases, and information about clinical NLP systems was collected from the final set of papers. A total of 7149 records (after removing duplicates) were retrieved and screened, and 86 were determined to fit the review criteria. These papers contained information about 71 different clinical NLP systems, which were then analyzed. The NLP systems address a wide variety of important clinical and research tasks. Certain tasks are well addressed by the existing systems, while others remain as open challenges that only a small number of systems attempt, such as extraction of temporal information or normalization of concepts to standard terminologies. This review has identified many NLP systems capable of processing clinical free text and generating structured output, and the information collected and evaluated here will be important for prioritizing development of new approaches for clinical NLP.CC999999/ImCDC/Intramural CDC HHS/United States2019-11-20T00:00:00Z28729030PMC6864736694

Doctor of Philosophy

dissertationElectronic Health Records (EHRs) provide a wealth of information for secondary uses. Methods are developed to improve usefulness of free text query and text processing and demonstrate advantages to using these methods for clinical research, specifically cohort identification and enhancement. Cohort identification is a critical early step in clinical research. Problems may arise when too few patients are identified, or the cohort consists of a nonrepresentative sample. Methods of improving query formation through query expansion are described. Inclusion of free text search in addition to structured data search is investigated to determine the incremental improvement of adding unstructured text search over structured data search alone. Query expansion using topic- and synonym-based expansion improved information retrieval performance. An ensemble method was not successful. The addition of free text search compared to structured data search alone demonstrated increased cohort size in all cases, with dramatic increases in some. Representation of patients in subpopulations that may have been underrepresented otherwise is also shown. We demonstrate clinical impact by showing that a serious clinical condition, scleroderma renal crisis, can be predicted by adding free text search. A novel information extraction algorithm is developed and evaluated (Regular Expression Discovery for Extraction, or REDEx) for cohort enrichment. The REDEx algorithm is demonstrated to accurately extract information from free text clinical iv narratives. Temporal expressions as well as bodyweight-related measures are extracted. Additional patients and additional measurement occurrences are identified using these extracted values that were not identifiable through structured data alone. The REDEx algorithm transfers the burden of machine learning training from annotators to domain experts. We developed automated query expansion methods that greatly improve performance of keyword-based information retrieval. We also developed NLP methods for unstructured data and demonstrate that cohort size can be greatly increased, a more complete population can be identified, and important clinical conditions can be detected that are often missed otherwise. We found a much more complete representation of patients can be obtained. We also developed a novel machine learning algorithm for information extraction, REDEx, that efficiently extracts clinical values from unstructured clinical text, adding additional information and observations over what is available in structured text alone