Healthcare Research Data Research Articles

Use of administrative data in healthcare research.

Health research based on administrative data and the availability of regional or national administrative databases has been increasing in recent years. We will discuss the general characteristics of administrative data and specific aspects of their use for health research purposes, indicating their advantages and disadvantages. Some fields of application will be discussed and described through examples.

Time for research networks to be trained in informatics and based within informatics centres

Public investment in research is thought to underpin a lot of UK business success and there has been considerable investment tomake greater use of healthcare data for research. UK Universities, recognised to be an international success, provide much of our research infrastructure. Approximately 10 years ago it started to be recognised that the potential to carry out research within the NHS was not being realised.

The UK Freedom of Information Act (2000) in healthcare research: a systematic review

ObjectivesTo assess the use and utility of the Freedom of Information Act (2000) in healthcare research since 2005 and to determine if any particular feature of studies found led to...

Managing personal health information in distributed research network environments

BackgroundStudying rare outcomes, new interventions and diverse populations often requires collaborations across multiple health research partners. However, transferring healthcare research data from one institution to another can increase the risk of data privacy and security breaches.MethodsA working group of multi-site research programmers evaluated the need for tools to support data security and data privacy. The group determined that data privacy support tools should: 1) allow for a range of allowable Protected Health Information (PHI); 2) clearly identify what type of data should be protected under the Health Insurance Portability and Accountability Act (HIPAA); and 3) help analysts identify which protected health information data elements are allowable in a given project and how they should be protected during data transfer. Based on these requirements we developed two performance support tools to support data programmers and site analysts in exchanging research data.ResultsThe first tool, a workplan template, guides the lead programmer through effectively communicating the details of multi-site programming, including how to run the program, what output the program will create, and whether the output is expected to contain protected health information. The second performance support tool is a checklist that site analysts can use to ensure that multi-site program output conforms to expectations and does not contain protected health information beyond what is allowed under the multi-site research agreements.ConclusionsTogether the two tools create a formal multi-site programming workflow designed to reduce the chance of accidental PHI disclosure.

Information Technology for Clinical, Translational and Comparative Effectiveness Research

Summary Objectives: To summarize advances of excellent current research in the new emerging field of Clinical Research Informatics. Method: Synopsis of four key articles selected for the IMIA Yearbook 2013. The selection was performed by querying PubMed and Web of Science with predefined keywords. From the original set of 590 papers, a first subset of 461 articles which was in the scope of Clinical Research Informatics was refined into a second subset of 79 relevant articles from which 15 articles were retained for peer-review. Results: The four selected articles exemplify current research efforts conducted in the areas of data representation and management in clinical trials, secondary use of EHR data for clinical research, information technology platforms for translational and comparative effectiveness research and implementation of privacy control. Conclusions: The selected articles not only illustrate how innovative information technology supports classically organized randomized controlled trials but also demonstrate that the long promised benefits of electronic health care data for research are becoming a reality through concrete platforms and projects.

Managing and exploiting routinely collected NHS data for research

Health research using routinely collected National Health Service (NHS) data derived from electronic health records (EHRs) and health service information systems has been growing in both importance and quantity. Wide population coverage and detailed patient-level information allow this data to be applied to a variety of research questions. However, the sensitivity, complexity and scale of such data also hamper researchers from fully exploiting this potential. Here, we establish the current challenges preventing researchers from making optimal use of the data sets at their disposal, on both the legislative and practical levels, and give recommendations as to how these challenges can be overcome. A number of projects has recently been launched in the UK to address poor research data-management practices. Rapid Organisation of Healthcare Research Data (ROHRD) at Imperial College, London produced a useful prototype that provides local researchers with a one-stop index of available data sets together with relevant metadata. Increased transparency of data sets' availability and their provenance leads to better utilisation and facilitates compliance with regulatory requirements. Research data resulting from NHS data is often not utilised fully, or is handled in a haphazard manner that prevents full auditability of the research. Furthermore, lack of informatics and data management skills in research teams act as a barrier to implementing more advanced practices, such as provenance capture and detailed, regularly updated, data management strategies. Only by a concerted effort at the levels of research organisations, funding bodies and publishers, can we achieve full transparency and reproducibility of the research.

PRM19 Evaluation of Sources and Types of Patient-Reported Outcome Data for Health Care Research

PRM19 Evaluation of Sources and Types of Patient-Reported Outcome Data for Health Care Research

Envisioning a Learning Health Care System: The Electronic Primary Care Research Network, A Case Study

The learning health care system refers to the cycle of turning health care data into knowledge, translating that knowledge into practice, and creating new data by means of advanced information technology. The electronic Primary Care Research Network (ePCRN) was a project, funded by the U.S. National Institutes of Health, with the aim to facilitate clinical research using primary care electronic health records (EHRs). We identified the requirements necessary to deliver clinical studies via a distributed electronic network linked to EHRs. After we explored a variety of informatics solutions, we constructed a functional prototype of the software. We then explored the barriers to adoption of the prototype software within U.S. practice-based research networks. We developed a system to assist in the identification of eligible cohorts from EHR data. To preserve privacy, counts and flagging were performed remotely, and no data were transferred out of the EHR. A lack of batch export facilities from EHR systems and ambiguities in the coding of clinical data, such as blood pressure, have so far prevented a full-scale deployment. We created an international consortium and a model for sharing further ePCRN development across a variety of ongoing projects in the United States and Europe. A means of accessing health care data for research is not sufficient in itself to deliver a learning health care system. EHR systems need to use sophisticated tools to capture and preserve rich clinical context in coded data, and business models need to be developed that incentivize all stakeholders from clinicians to vendors to participate in the system.

Approaches for dealing with missing data in health care studies

The aims of this study were to highlight the problems associated with missing data in healthcare research and to demonstrate the use of several techniques for dealing with missing values, through the use of an illustrative example. In healthcare research studies, it is almost impossible to avoid at least some missing values during data collection, which in turn can threaten the validity of the study conclusions. A range of methods for reducing the impact of missing data on the validity of study findings have been developed, depending on the nature and patterns which the missing values may take. A discursive study. Several techniques designed to deal with missing data are described and applied to an illustrative example. These methods include complete-case analysis, available-case analysis, as well as single and multiple imputation. If research data contain missing values that are not randomly distributed, then the study results are likely to be biased unless an effective approach to dealing with the missing values is implemented. If nursing and healthcare practice is to be informed by research findings, then these findings must be reliable and valid. Researchers should report the details of missing data, and appropriate methods for dealing with missing values should be incorporated into the data analysis.

CARPE: a registry project of the German Dermatological Society (DDG) for the characterization and care of chronic hand eczema

The aim of the CARPE (German acronym: Chronisches Handekzem-Register zum Patienten-Langzeitmanagement; meaning: chronic hand eczema registry on long-term patient management) registry is to investigate characteristics and treatment modalities in patients affected by chronic hand eczema in Germany. The registry was built up under the auspices of the German Dermatological Society (Deutsche Dermatologische Gesellschaft, DDG). Patients with chronic hand eczema are prospectively assessed by dermatological examination and patient questionnaire. Socio-economic data and data on diagnostics, skin status, severity and treatment of chronic hand eczema and atopy criteria are repeatedly assessed. Here, we present baseline characteristics of the first 515 patients. 53.8 % of the patients were female, mean age was 47.3 years. The average duration of CHE was 7.7 years. 30.4 % had already received inpatient care, 31.2 % had been on sick leave in the past 12 months. 94.5 % had received topical corticosteroids prior to inclusion in the registry, 31.9 % topical calcineurin inhibitors, 38.3 % UV therapy, 28.6 % systemic antihistamines, 36.5 % systemic treatments, 14.9 % systemic corticosteroids, 25.8 % systemic retinoids. The CARPE project demonstrates the high medical burden and therapeutic challenge of chronic hand eczema and presents first data for health care research. Furthermore, the designed follow-up study will present important data about the natural history and prognosis of this chronic skin disease.

The Use of Claims Data in Healthcare Research

Background: Claims-based studies have become common during the past 15 years. The electronic records of millions of transactions include information entered on bills (claims) submitted by healthcare providers to third-party payers. They are an attractive data source to researchers; however, they contain many weaknesses that threaten the integrity of many studies that utilize them.

Patient claims and complaints data for improving patient safety

The purpose of this paper is to describe patient complaints and claims data from Swedish databases and assess their value for scientific research and practical health care improvement. The article first describes previous research into patient claims and similar schemes. It then presents three types of data on patient claims and complaints in Sweden: data generated by the Patient Insurance Fund, the Medical Responsibility Board and the Patients' Advisory Committees and considers methodological issues in using the data. The databases' value is problems related to spontaneous reporting, which makes it difficult to know how much the data correspond to general injury rates and health care patterns. Another issue is the balance between the size of study materials and the timeliness, e.g. when diagnosis-specific analysis requires data pooling over several years in order to reach adequate case numbers. Adjustment for confounders not present in the databases, e.g. data on hospital case-mix, may add to difficulties using the data in comparative analyses of safety performance. The databases' safety analysis and quality improvement value depends on understanding their function, data collection method and their limitations as a source of data about the true incidence and prevalence of injuries and safety problems. This is the first thorough review of the possibilities and limitations associated with the use of claims and complaints data in health care research and improvement.

The effect of a monetary incentive on return of a postal health and development questionnaire: a randomised trial [ISRCTN53994660

BackgroundPostal questionnaires are widely used to collect data in healthcare research but a poor response rate may reduce the validity and reliability of results. There was a lack of evidence available relating to use of a monetary incentive to improve the response rate in the healthcare setting.MethodsThe MRC ORACLE Children Study is assessing the health and development of nearly 9000 seven year old children whose mothers' joined the MRC ORACLE Trial. We carried out a randomised controlled trial of inclusion of monetary incentive (five pound voucher redeemable at many high street stores) with the reminder questionnaire to parents. This trial took place between April 2002 and November 2003. When the parents were sent the reminder questionnaire about their child's health and development they were randomly assigned by concealed computer-generated allocation stratified by week of birthday to receive a five pound voucher or no incentive. The population were 722 non-responders to the initial mailing of a 12-page questionnaire. Main outcome measures: Difference in response rate between the two groups.ResultsInclusion of the voucher with the reminder questionnaire resulted in a 11.7%(95% CI 4.7% to 18.6%) improvement in the response rate between the two groups.ConclusionThis improvement in response rate and hence the validity and reliability of results obtained appears to be justified ethically and financially.

The Utrecht Health Project: Optimization of routine healthcare data for research

Research on the impact of changes in healthcare policy, developments in community and public health and determinants of health and disease during lifetime may effectively make use of routine healthcare data. These data, however, need to meet minimal criteria for quality and completeness. Research opportunities are further improved when routine data are supplemented with a standardized 'baseline' assessment of the full population. This formed the basis for a new study initiated in a newly developed large residential area in Leidsche Rijn, part of the city of Utrecht, the Netherlands. All new inhabitants are invited by their general practitioner to participate in the Utrecht Health Project (UHP). Informed consent is obtained and an individual health profile (IHP) is made by dedicated research nurses. The IHP is the starting point for the UHP research database as well as for the primary care electronic medical records. Follow-up data are collected through continuous linkage with the computerized medical files recorded by the general practitioners. UHP staff in each practice takes care of quality management of registration as well as data handling. Currently, over 60% of invited new residents in the area have given informed consent with participation steadily increasing. The Utrecht Health Project combines key elements of traditional epidemiologic cohort studies with the current power of routine electronic medical record keeping in primary care. The research approach optimizes routine health care data for use in scientific research.

The accuracy of Medicare's hospital claims data: progress has been made, but problems remain.

Health care databases provide a widely used source of data for health care research, but their accuracy remains uncertain. We analyzed data from the 1985 National DRG Validation Study, which carefully reabstracted and reassigned ICD-9-CM diagnosis and procedure codes from a national sample of 7050 medical records, to determine whether coding accuracy had improved since the Institute of Medicine studies of the 1970s and to assess the current coding accuracy of specific diagnoses and procedures. We defined agreement as the proportion of all reabstracted records that had the same principal diagnosis or procedure coded on both the original (hospital) record and on the reabstracted record. We also evaluated coding accuracy in 1985 using the concepts of diagnostic test evaluation. Overall, the percentage of agreement between the principal diagnosis on the reabstracted record and the original hospital record, when analyzed at the third digit, improved from 73.2% in 1977 to 78.2% in 1985. However, analysis of the 1985 data demonstrated that the accuracy of diagnosis and procedure coding varies substantially across conditions. Although some diagnoses and all major surgical procedures that we examined were accurately coded, the variability in the accuracy of diagnosis coding poses a problem that must be overcome if claims-based research is to achieve its full potential.