The Role of Dementia as Cause of Death: Certifiers' Opinions versus Automated Coding.

BACKGROUND: Dementia is a major cause of death in many countries today. The way in which countries code causes of death determines the occurrence of dementia in statistics. The change over from manual to automated coding is accompanied by a 7-19% increase in the occurrence of dementia as the underlying cause of death. Because of this sudden change, researchers, physicians, policy makers, and press question the validity of the outcome of automated coding. Therefore, the role of dementia as a cause of death was investigated. METHODS: A questionnaire was sent to a random sample of 700 certifiers who mentioned "dementia" on a death certificate in the second half of 2017. They were asked questions about the role of dementia as a cause of death. For each certificate, the opinion of the certifier was compared with the outcome of automated coding. RESULTS: A response of 65% (n = 446) was obtained. The automated coding system selected dementia as the underlying cause of death 9.5% points (95% CI: 5.8-14.4%) more often than the certifier would do. This finding in the sample corresponded to an overestimation of dementia in the cause-of-death statistics with 22.7% (95% CI: 18-28%). Main reason for this overestimation was the selection of dementia as the underlying cause of death by the automated coding system, while it was noted as the contributory cause of death on part 2 of the death certificate by the certifier. CONCLUSION: For international comparisons of data on dementia as a cause of death, the outcome of automated coding can be used as the system adheres to international (ICD-10) guidelines and reduces coding variations in and between countries. However, for interpreting the local (national) impact of dementia as a cause of death, the opinion of the certifier should be taken into account.

A systematic review of methods for determining cross-sectional active medications using pharmacy databases.

PURPOSE: Pharmacy dispensing databases are often used to identify patients' medications at a particular time point, for example to measure prescribing quality or the impact of medication use on clinical outcomes. We performed a systematic review of studies that examined methods to assess medications in use at a specific point in time. METHODS: Comprehensive literature search to identify studies that compared active medications identified using pharmacy databases to medications identified using nonautomated data sources. Two investigators independently reviewed abstracts and full-text material. RESULTS: Of 496 studies screened, 29 studies evaluating 50 comparisons met inclusion criteria. Twenty-nine comparisons evaluated fixed look-back period approaches, defining active medications as those filled in a specified period prior to the index date (range 84-730 days). Fourteen comparisons evaluated medication-on-hand approaches, defining active medications as those for which the most recent fill provided sufficient supply to last through the study index date. Sensitivity ranged from 48% to 93% for fixed look-back period approaches and 35% to 97% for medication-on-hand approaches. Interpretation of comparative performance of methods was limited by use of different reference sources, target medication classes, and databases across studies. In four studies with head-to-head comparisons of these methods, sensitivity of the medication-on-hand approach was a median of 7% lower than the corresponding fixed look-back approach. CONCLUSIONS: The reported accuracy of methods for identifying active medications using pharmacy databases differs greatly across studies. More direct comparisons of common approaches are needed to establish the accuracy of methods within and across populations, medication classes, and databases.

The Italian Registry of GH Treatment: electronic Clinical Report Form (e-CRF) and web-based platform for the national database of GH prescriptions.

BACKGROUND: In Italy, the utilization and the reimbursement of Growth Hormone (rGH) therapy by the National Health System (Servizio Sanitario Nazionale) are regulated by the "Note #39" included in the "Notes for the use of drugs" by the Italian Medicines Agency (AIFA), which are published in the Official Gazette, thus having the force of law. The "Note #39" establishes the diagnosis for which the reimbursement is granted and confirms the assignment of the national health surveillance on the use of GH therapy to the Italian National Institute of Health, requesting its computerization. AIM: The aim of this work was to realize a dedicated electronic Clinical Report Form based on the mandatory data requested by the Note #39 and allowing the online reporting of the rGH prescriptions by the regional accredited centers. RESULTS AND CONCLUSIONS: This interface is at the base of the national database of the Italian Registry of GH Treatment, which allows obtaining and managing correct and complete data to provide public health surveillance on GH therapy, both at national and local levels, necessary for policymakers decisions. In addition, this national database could be a useful instrument for improving knowledge about aspects of this treatment still under discussion.

Adherence to growth hormone (GH) therapy in naïve to treatment GH-deficient children: data of the Italian Cohort from the Easypod Connect Observational Study (ECOS).

BACKGROUND: With the use of non-objective measurement, adherence to growth hormone (GH) therapy has been reported suboptimal in a large proportion of patients, and poor adherence has been shown to affect short-term growth response in patients receiving GH treatment. OBJECTIVE: The Easypod™ electronic device allows objective measurement of adherence. In this study, we report 3-year prospective adherence data of the Italian cohort of naïve GH deficient (GHD) children extrapolated from the Easypod Connect Observational Study (ECOS) database. PATIENTS AND METHODS: Seventy-three GHD children naïve to GH treatment were included in the analysis. 22 Italian centers participated in the study. RESULTS: Mean adherence rate was consistently above 85% across the 3-year observation period. Particularly, mean adherence was 88.5%, 86.6%, and 85.7% after 1, 2 and 3 years, respectively. Mean (± SD) height-SDS increase after the first year was 0.41 (± 0.38). CONCLUSIONS: The majority of naïve GHD children starting GH treatment with Easypod maintained an adherence rate > 85% up to 3 years. Easypod is a useful tool to follow-up patients' adherence allowing timely intervention to improve optimal treatment for these patients.

Change in staff anesthesiologists' opinions of an Anesthesia Information Management System (AIMS).

Following introduction of an Anesthesia Information Management System (AIMS) at a tertiary care, academic health sciences centre, a quality assurance initiative was conducted to assess staff opinions of the AIMS using a previously published, anonymous survey tool at 1 and 5 years following AIMS introduction. At 5 years compared to 1 year after implementation of AIMS, the majority (18 of 24, 75%) of responses to the survey questions had a statistically significant change (P < 0.05) in the proportion of respondents favoring AIMS compared to the 1 year survey. Domains noted to be more favorable 5 years compared to 1 year after AIMS introduction included patient safety in the Operating Rooms and Post-Anesthesia Care Unit, quality of handover and overall documentation, and communication amongst healthcare workers. The ideal time period at which to assess AIMS after introduction is not clear.

[Quality of the diagnoses' coding (main or associated diagnoses) in the medico-administrative database for psychiatric care (RIM-P) in 2015 and 2016, France]. / Qualité du codage des diagnostics et motifs de prise en charge (principal et associés) dans le recueil d'informations médicalisé en psychiatrie (RIM-P) en 2015 et 2016, France.

BACKGROUND: Based on the observation of the misuse of ICD-10 to code the diagnoses in the RIM-P (lack of completeness, conformity and diversity), the Technical Agency for information on Hospital Care (ATIH), which provides tools for collecting medical information, conducted two actions in 2016. First, a chapter devoted to the instructions of coding has been written in the methodological guide of production of the RIM-P, second, a variable "type psy" was added to the ICD-10 nomenclature's file framing ICD-10 coding in the RIM-P. The purpose of this study is to describe the quality of diagnosis coding using ICD-10 in the RIM-P in 2015 and 2016. METHODS: The quality of diagnosis coding using ICD-10 in the summaries of activity of the RIM-P national databases was described in 2015 and 2016. The study focused on the completeness, the conformity and the diversity of coding. RESULTS: Between 2015 and 2016, the percentage of summaries without primary diagnosis ("DP") decreased slightly for full-time (5.2% vs. 3.8%), part-time (6.3% vs. 4.9%) inpatient stays and outpatient care (9.9% vs. 8.9%). ICD-10 codes used to code DP or associated diagnosis ("DA"), while prohibited, mainly belong to Chapter V Mental and behavioral disorders. Per year, only one-third of the summaries and one-half of patients had two or more ICD-10 codes reported for inpatient stays (one-fifth of the summaries and one-fourth of the patients for outpatient care). In addition, per year and per facility, the average number of distinct ICD-10 codes used to fill "DP" or "DA" was approximately half as important in part-time hospitalization, as in full-time hospitalization or for outpatient care. Moreover, 90% of the health facilities used<550 distinct ICD-10 codes in full-time inpatient stays,<270 in part-time inpatient stays and<950 for outpatient care to code the "DP" or the "DA". The diversity of ICD-10 codes used was low and similar between 2015 and 2016, especially to describe the socio-economic environment, resistance to treatment or non-compliance. CONCLUSION: This study emphasizes the need for a collective effort to improve the diversity of the diagnoses' coding in the RIM-P.

Mining electronic health records: towards better research applications and clinical care.

Clinical data describing the phenotypes and treatment of patients represents an underused data source that has much greater research potential than is currently realized. Mining of electronic health records (EHRs) has the potential for establishing new patient-stratification principles and for revealing unknown disease correlations. Integrating EHR data with genetic data will also give a finer understanding of genotype-phenotype relationships. However, a broad range of ethical, legal and technical reasons currently hinder the systematic deposition of these data in EHRs and their mining. Here, we consider the potential for furthering medical research and clinical care using EHR data and the challenges that must be overcome before this is a reality.

CDSS-RM: a clinical decision support system reference model.

Clinical Decision Support Systems (CDSS) provide aid in clinical decision making and therefore need to take into consideration human, data interactions, and cognitive functions of clinical decision makers. The objective of this paper is to introduce a high level reference model that is intended to be used as a foundation to design successful and contextually relevant CDSS systems. The paper begins by introducing the information flow, use, and sharing characteristics in a hospital setting, and then it outlines the referential context for the model, which are clinical decisions in a hospital setting. Important characteristics of the Clinical decision making process include: (i) Temporally ordered steps, each leading to new data, which in turn becomes useful for a new decision, (ii) Feedback loops where acquisition of new data improves certainty and generates new questions to examine, (iii) Combining different kinds of clinical data for decision making, (iv) Reusing the same data in two or more different decisions, and (v) Clinical decisions requiring human cognitive skills and knowledge, to process the available information. These characteristics form the foundation to delineate important considerations of Clinical Decision Support Systems design. The model includes six interacting and interconnected elements, which formulate the high-level reference model (CDSS-RM). These elements are introduced in the form of questions, as considerations, and are examined with the use of illustrated scenario-based and data-driven examples. The six elements /considerations of the reference model are: (i) Do CDSS mimic the cognitive process of clinical decision makers? (ii) Do CDSS provide recommendations with longitudinal insight? (iii) Is the model performance contextually realistic? (iv) Is the 'Historical Decision' bias taken into consideration in CDSS design? (v) Do CDSS integrate established clinical standards and protocols? (vi) Do CDSS utilize unstructured data? The CDSS-RM reference model can contribute to optimized design of modeling methodologies, in order to improve response of health systems to clinical decision-making challenges.

Adherence to standardized assessments through a complexity-based model for categorizing rehabilitation©: design and implementation in an acute hospital.

BACKGROUND: The use of measurement instruments has become a major issue in physical therapy, but their use in daily practice is rare. The aim of this paper is to describe adherence to standardized assessments by physical therapists using a complexity-based model for categorizing rehabilitation (CMCR) at the Clínica Alemana of Santiago, an acute hospital in Chile. METHODS: This retrospective cohort study used 145,968 participant records that were stored in the inpatient database between July 2011 and December 2015. Adherence to the CMCR by 31 physical therapists working with intensive care unit (ICU) and non-ICU inpatients was assessed every quarter using the electronic patient records (EPR). This instrument (CMCR) linked clinical functional assessment to the degree of severity, thereby setting a score used to categorize patients as low, medium and high complexity. 96,400 instances of inpatient care where the physician recommended physical therapy were categorized. This was from a total of 145,968 instances of inpatient care recorded throughout the duration of the study (17 quarters). Trends in adherence were analyzed using a Prais-Winsten regression (a first-order autoregressive model). The trends were compared using a repeated measures ANOVA for mixed models with a significance level of 0.05. The use of the CMCR was included as one of the organization's quality indicators associated with the hospital's accreditation processes. RESULTS: Adherence increased by 1.48% every quarter (p = 0.005) for both ICU and non-ICU patients. On average, adherence with ICU patients was 16.98% greater than with non-ICU patients. Although adherence was always greater with ICU patients, the rate of increase with non-ICU patients was significantly greater: 1.62% (p = 0.007) vs. 1.28% (p = 0.003), respectively. CONCLUSION: The CMCR facilitated adherence to standardized assessments by physical therapists working with ICU and non-ICU inpatients in an acute hospital, while linking this instrument to the organization's quality management process proved to be an effective strategy for the duration of this study (17 quarters).

Quantitative Analysis of Uncertainty in Medical Reporting: Part 3: Customizable Education, Decision Support, and Automated Alerts.

In order to better elucidate and understand the causative factors and clinical implications of uncertainty in medical reporting, one must first create a referenceable database which records a number of standardized metrics related to uncertainty language, clinical context, technology, and provider and patient data. The resulting analytics can in turn be used to create context and user-specific reporting guidelines, real-time decision support, educational resources, and quality assurance measures. If this technology can be directly integrated into reporting technology and workflow, the goal is to proactively improve clinical outcomes at the point of care.

CodeMapper: semiautomatic coding of case definitions. A contribution from the ADVANCE project.

BACKGROUND: Assessment of drug and vaccine effects by combining information from different healthcare databases in the European Union requires extensive efforts in the harmonization of codes as different vocabularies are being used across countries. In this paper, we present a web application called CodeMapper, which assists in the mapping of case definitions to codes from different vocabularies, while keeping a transparent record of the complete mapping process. METHODS: CodeMapper builds upon coding vocabularies contained in the Metathesaurus of the Unified Medical Language System. The mapping approach consists of three phases. First, medical concepts are automatically identified in a free-text case definition. Second, the user revises the set of medical concepts by adding or removing concepts, or expanding them to related concepts that are more general or more specific. Finally, the selected concepts are projected to codes from the targeted coding vocabularies. We evaluated the application by comparing codes that were automatically generated from case definitions by applying CodeMapper's concept identification and successive concept expansion, with reference codes that were manually created in a previous epidemiological study. RESULTS: Automated concept identification alone had a sensitivity of 0.246 and positive predictive value (PPV) of 0.420 for reproducing the reference codes. Three successive steps of concept expansion increased sensitivity to 0.953 and PPV to 0.616. CONCLUSIONS: Automatic concept identification in the case definition alone was insufficient to reproduce the reference codes, but CodeMapper's operations for concept expansion provide an effective, efficient, and transparent way for reproducing the reference codes.

Tolerability and efficacy of perampanel in children with refractory epilepsy.

AIM: There are few reports on the tolerability and efficacy of perampanel, a new antiepileptic drug with a novel mechanism of action, in children and adolescents. We aimed to describe our experience with perampanel add-on and mono-therapy in children with refractory epilepsy. METHOD: Computerized medical records of children treated with perampanel in the paediatric neurology clinic from December 2012 to October 2015 were reviewed. RESULTS: Twenty-four children treated with perampanel (15 females, 9 males) aged 1 year 6 months to 17 years (mean 10y, standard deviation [SD] 4y 5mo) were identified. Adverse events were more common in children aged 12 years or older (89%) compared to younger children (53%), and were mainly behavioural. Ten (42%) children had 50 per cent or higher seizure reduction, two (8%) children had 33 per cent seizure reduction, and seizures were less severe in one (4%) child. Perampanel was discontinued in 13 (54%) children mostly due to adverse events. The mean duration of follow-up in the remaining 11 children was 8.1 months (SD 5.2) (range 1.3-17mo). INTERPRETATION: Perampanel is associated with a relatively high rate of behavioural adverse events mostly in adolescents with refractory epilepsy.

Ceiling effect in EMR system assimilation: a multiple case study in primary care family practices.

BACKGROUND: There has been indisputable growth in adoption of electronic medical record (EMR) systems in the recent years. However, physicians' progress in using these systems has stagnated when measured with maturity scales. While this so-called ceiling effect has been observed and its consequences described in previous studies, there is a paucity of research on the elements that could explain such an outcome. We first suggest that in the context of EMR systems we are in presence of a "tiered ceiling effect" and then we show why such phenomenon occurs. METHODS: We conducted in-depth case studies in three primary care medical practices in Canada where physicians had been using EMR systems for 3 years or more. A total of 37 semi-structured interviews were conducted with key informants: family physicians (about half of the interviews), nurses, secretaries, and administrative managers. Additional information was obtained through notes taken during observations of users interacting with their EMR systems and consultation of relevant documents at each site. We used abductive reasoning to infer explanations of the observed phenomenon by going back and forth between the case data and conceptual insights. RESULTS: Our analysis shows that a ceiling effect has taken place in the three clinics. We identified a set of conditions preventing the users from overcoming the ceiling. In adopting an EMR system, all three clinics essentially sought improved operational efficiency. This had an influence on the criteria used to assess the systems available on the market and eventually led to the adoption of a system that met the specified criteria without being optimal. Later, training sessions focussed on basic functionalities that minimally disturbed physicians' habits while helping their medical practices become more efficient. Satisfied with the outcome of their system use, physicians were likely to ignore more advanced EMR system functionalities. This was because their knowledge about EMR systems came almost exclusively from a single source of information: their EMR system vendors. This knowledge took the form of interpretations of what the innovation was (know-what), with little consideration of the rationales for innovation adoption (know-why) or hands-on strategies for adopting, implementing and assimilating the innovation in the organization (know-how). CONCLUSIONS: This paper provides a holistic view of the technological innovation process in primary care and contends that limited learning, satisficing behaviours and organizational inertia are important factors leading to the ceiling effect frequently experienced in the EMR system assimilation phase.

[Methods of data selection from the French medical information system program for trauma patient's analysis: Burns and traumatic brain injuries]. / Méthodes de sélection des données du PMSI pour l'analyse des victimes de traumatismes : brûlures et lésions cérébrales traumatiques.

BACKGROUND: Data from the French medical information system program in medicine, surgery, obstetrics and dentistry can be adapted in some cases and under certain conditions, to account for hospitalizations for injuries. Two areas have been explored: burn and traumatic brain injury victims. METHODS: An algorithm selecting data from the Medical information system program was established and implemented for several years for the study of burn victims. The methods of selection of stays for traumatic brain injuries, which are the subject of a more recent exploration, are described. RESULTS: Production of results in routine on the hospitalization for burns. Expected production of results on the hospitalization for traumatic brain injuries. CONCLUSION: In both cases, the knowledge obtained from these utilizations of the Medical information system program contributes to epidemiological surveillance and prevention and are useful for health care organization.

[The psychiatric hospital discharge database (RIM-P): An essential tool for the surveillance of hospitalization after a suicide attempt]. / Le Recueil d'information médicalisé en psychiatrie (RIM-P) : un outil nécessaire pour la surveillance des hospitalisations suite à une tentative de suicide.

BACKGROUND: Epidemiological surveillance of suicide attempts is essential for monitoring indicator trends in the evaluation of prevention actions. As part of this surveillance, analysis of data from hospitalization for suicide attempts is particularly useful. METHODS: For the first time, data from two national hospital discharge databases, the "Programme de médicalisation des systèmes d'information en médecine, chirurgie, obstétrique" (PMSI-MCO) and the " Recueil d'information médicalisé en psychiatrie" (RIM-P) have been analyzed jointly. All patients aged 10 or more hospitalized in 2012 in medicine, surgery or psychiatry departments in metropolitan France have were included. RESULTS: Through 2012, 89,072 patients (62% females and 38% males) totalized 134,051 hospital stays following a suicide attempt, with 93.4% (n=83,196) in medicine or surgery wards and 32.1% (n=28,594) in psychiatry wards (solely or transferred after a stay in medicine or surgery). However, among the patients transferred to psychiatry after hospitalization in medicine or surgery for suicide attempt, 82.4% had no suicide attempt code noted at their discharge from psychiatry. One or more psychiatric diagnoses were observed in 75% of the patients hospitalized for suicide attempt. The most common diagnoses in men and in women were mood disorders (46%), particularly depression (42%; 44% in women and 38% in men). Mental disorders related to alcohol use were noted in more than a quarter of the patients, more frequently in men (37%) than in women (21%). Some diagnoses were rarely noted in medicine or surgery, such as anxiety disorders and disorders of adult personality and behavior. CONCLUSION: Improvement of the epidemiological surveillance of suicide attempts requires a systematic coding of hospitalizations in psychiatry as well as in medicine and surgery. Data from hospitalization in psychiatry yield a more precise identification of psychiatric co-morbidities associated with suicide attempts. The frequent presence of mental problems associated with suicide attempts should encourage clinicians to search for these symptoms systematically as soon as possible after admission of the patient.

[Study of algorithms to identify schizophrenia in the SNIIRAM database conducted by the REDSIAM network]. / Étude des algorithmes de repérage de la schizophrénie dans le Sniiram par le réseau REDSIAM.

BACKGROUND: The aim of the REDSIAM network is to foster communication between users of French medico-administrative databases and to validate and promote analysis methods suitable for the data. Within this network, the working group "Mental and behavioral disorders" took an interest in algorithms to identify adult schizophrenia in the SNIIRAM database and inventoried identification criteria for patients with schizophrenia in these databases. METHODS: The methodology was based on interviews with nine experts in schizophrenia concerning the procedures they use to identify patients with schizophrenia disorders in databases. The interviews were based on a questionnaire and conducted by telephone. RESULTS: The synthesis of the interviews showed that the SNIIRAM contains various tables which allow coders to identify patients suffering from schizophrenia: chronic disease status, drugs and hospitalizations. Taken separately, these criteria were not sufficient to recognize patients with schizophrenia, an algorithm should be based on all of them. Apparently, only one-third of people living with schizophrenia benefit from the longstanding disease status. Not all patients are hospitalized, and coding for diagnoses at the hospitalization, notably for short stays in medicine, surgery or obstetrics departments, is not exhaustive. As for treatment with antipsychotics, it is not specific enough as such treatments are also prescribed to patients with bipolar disorders, or even other disorders. It seems appropriate to combine these complementary criteria, while keeping in mind out-patient care (every year 80,000 patients are seen exclusively in an outpatient setting), even if these data are difficult to link with other information. Finally, the experts made three propositions for selection algorithms of patients with schizophrenia. CONCLUSION: Patients with schizophrenia can be relatively accurately identified using SNIIRAM data. Different combinations of the selected criteria must be used depending on the objectives and they must be related to an appropriate length of time.

[Algorithms based on medico-administrative data in the field of endocrine, nutritional and metabolic diseases, especially diabetes]. / Algorithmes basés sur les données médico-administratives dans le champ des maladies endocriniennes, nutritionnelles et métaboliques, et en particulier du diabète.

BACKGROUND: Medico-administrative databases represent a very interesting source of information in the field of endocrine, nutritional and metabolic diseases. The objective of this article is to describe the early works of the Redsiam working group in this field. METHODS: Algorithms developed in France in the field of diabetes, the treatment of dyslipidemia, precocious puberty, and bariatric surgery based on the National Inter-schema Information System on Health Insurance (SNIIRAM) data were identified and described. RESULTS: Three algorithms for identifying people with diabetes are available in France. These algorithms are based either on full insurance coverage for diabetes or on claims of diabetes treatments, or on the combination of these two methods associated with hospitalizations related to diabetes. Each of these algorithms has a different purpose, and the choice should depend on the goal of the study. Algorithms for identifying people treated for dyslipidemia or precocious puberty or who underwent bariatric surgery are also available. CONCLUSION: Early work from the Redsiam working group in the field of endocrine, nutritional and metabolic diseases produced an inventory of existing algorithms in France, linked with their goals, together with a presentation of their limitations and advantages, providing useful information for the scientific community. This work will continue with discussions about algorithms on the incidence of diabetes in children, thyroidectomy for thyroid nodules, hypothyroidism, hypoparathyroidism, and amyloidosis.

[Using cancer case identification algorithms in medico-administrative databases: Literature review and first results from the REDSIAM Tumors group based on breast, colon, and lung cancer]. / Recherche d'algorithmes d'identification des cancers dans les bases médico-administratives : premiers résultats des travaux du groupe REDSIAM Tumeurs sur les cancers du sein, du côlon-rectum et du poumon.

BACKGROUND: The development and use of healthcare databases accentuates the need for dedicated tools, including validated selection algorithms of cancer diseased patients. As part of the development of the French National Health Insurance System data network REDSIAM, the tumor taskforce established an inventory of national and internal published algorithms in the field of cancer. This work aims to facilitate the choice of a best-suited algorithm. METHOD: A non-systematic literature search was conducted for various cancers. Results are presented for lung, breast, colon, and rectum. Medline, Scopus, the French Database in Public Health, Google Scholar, and the summaries of the main French journals in oncology and public health were searched for publications until August 2016. An extraction grid adapted to oncology was constructed and used for the extraction process. RESULTS: A total of 18 publications were selected for lung cancer, 18 for breast cancer, and 12 for colorectal cancer. Validation studies of algorithms are scarce. When information is available, the performance and choice of an algorithm are dependent on the context, purpose, and location of the planned study. Accounting for cancer disease specificity, the proposed extraction chart is more detailed than the generic chart developed for other REDSIAM taskforces, but remains easily usable in practice. CONCLUSIONS: This study illustrates the complexity of cancer detection through sole reliance on healthcare databases and the lack of validated algorithms specifically designed for this purpose. Studies that standardize and facilitate validation of these algorithms should be developed and promoted.

[Required Framework for the Collection of Real-life Data: An Example from University Eye Hospital Munich]. / Rahmenbedingungen zur Sammlung von "Real-Life"-Daten am Beispiel der Augenklinik der Universität München.

Background The importance of evaluating real-life data is constantly increasing. Currently available computer systems better allow for analyses of data, as more and more data is available in a digital form. Before a project for real-life data analyses is started, technical considerations and staff, legal, and data protection procedures need to be addressed. In this manuscript, experiences made at the University Eye Hospital in Munich will be shared. Materials and Methods Legal requirements, as found in laws and guidelines governing documentation and data privacy, are highlighted. Technical requirements for information technology infrastructure and software are defined. A survey conducted by the German Ophthalmological Society, among German eye hospitals investigating the current state of digitalization, was conducted. Also, staff requirements are outlined. Results A database comprising results of 330,801 patients was set up. It includes all diagnoses, procedures, clinical findings and results from diagnostic devices. This database was approved by the local data protection officer. In less than half of German eye hospitals (n = 21) that participated in the survey (n = 54), a complete electronic documentation is done. Fourteen institutions are completely paper-based, and the remainder of the hospitals used a mixed system. Conclusion In this work, we examined the framework that is required to develop a comprehensive database containing real-life data from clinics. In future, these databases will become increasingly important as more and more innovation are made in decision support systems. The base for this is comprehensive and well-curated databases.

Measuring the operational impact of digitized hospital records: a mixed methods study.

BACKGROUND: Digitized (scanned) medical records have been seen as a means for hospitals to reduce costs and improve access to records. However, clinical usability of digitized records can potentially have negative effects on productivity. METHODS: Data were collected during follow-up outpatient consultations in two NHS hospitals by non-clinical observers using a work sampling approach in which pre-defined categories of clinician time usage were specified. Quantitative data was analysed using two-way ANOVA models and the Mann-Whitney U test. A focus group was held with clinicians to qualitatively explore their experiences using digitized medical records. The quantitative and qualitative results were synthesized. RESULTS: Four hundred six consultations were observed. Using paper records, there was a significant difference in consultation times between hospitals (p = 0.016) and a significant difference in consultation times between specialties within hospitals (p = 0.003). Using digitized records there was a significant difference in consultation times between specialties within a hospital (p = 0.001). Excluding outliers, there was no significant difference between consultation times using digitized records compared with consultations using paper records in the same hospital, either at site (p > =0.285) or specialty level (p > =0.122). With digitized records at site A, two out of three specialties showed a significant increase in time spent searching computer records (p < =0.010, Δ = 01:50-07:10) and one specialty had a corresponding reduction in time spent searching paper records (p = 0.015, Δ = -00:28). Site B showed a notable increase in direct patient care (p < 0.001, Δ = 04:20-06:00) and time spent searching computer records (p < =0.043, Δ = 00:10-01:40) and reductions in the other time categories. The focus group confirmed that the most recent clinical letter was a vital document in the patient record, often containing most of the required information. Concerns were expressed about consistency of scanning practice, causing uncertainty about what could be relied upon to exist in the digitized record. Benefits of digitized records included: access from multiple locations, better prepared ward rounds, improved inpatient handovers and an improved timeline of patient events. Limitations of digitized records included: increased complexity of creating a patient summary, display of specialised content such as hand-drawn diagrams, inability to quickly flick through the pages to find relevant content. CONCLUSIONS: Digitized medical records can be implemented without detrimental operational impact. Inherent differences between specialties can outweigh the differences between paper and digitized records. Clear and consistent operational processes are vital for the reliability and usability of digitized medical records. Divergent views about usability (such as whether patient summary information is better or worse) may reflect familiarity with features of the digitized record.