Standardizing Race, Ethnicity, and Preferred Language Data Collection in Hospital Information Systems: Results and Implications for Healthcare Delivery and Policy

2012 ◽  
Vol 34 (2) ◽  
pp. 44-52 ◽  
Author(s):  
Rohit Bhalla ◽  
Brandon G. Yongue ◽  
Brian P. Currie
2012 ◽  
Vol 51 (03) ◽  
pp. 210-220 ◽  
Author(s):  
B. De La Iglesia ◽  
S. Donell ◽  
V. Rayward-Smith ◽  
J. Bettencourt-Silva

SummaryBackground: The information present in Hospital Information Systems (HIS) is heterogeneous and is used primarily by health practitioners to support and improve patient care. Conducting clinical research, data analyses or knowledge discovery projects using electronic patient data in secondary care centres relies on accurate data collection, which is often an ad-hoc process poorly described in the literature.Objectives: This paper aims at facilitating and expanding on the process of retrieving and collating patient-centric data from multiple HIS for the purpose of creating a research database. The development of a process roadmap for this purpose illustrates and exposes the constraints and drawbacks of undertaking such work in secondary care centres.Methods: A data collection exercise was carried using a combined approach based on segments of well established data mining and knowledge discovery methodologies, previous work on clinical data integration and local expert consultation. A case study on prostate cancer was carried out at an English regional National Health Service (NHS) hospital.Results: The process for data retrieval described in this paper allowed patient-centric data, pertaining to the case study on prostate cancer, to be successfully collected from multiple heterogeneous hospital sources, and collated in a format suitable for further clinical research.Conclusions: The data collection exercise described in this paper exposes the lengthy and difficult journey of retrieving and collating patient-centric, multi-source data from a hospital, which is indeed a non-trivial task, and one which will greatly benefit from further attention from researchers and hospital IT management.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 6018-6018
Author(s):  
Paula Aristizabal ◽  
Foyinsola Ani ◽  
Erica Del Muro ◽  
Teresa Cassidy ◽  
M Elena Martinez ◽  
...  

Abstract Introduction: Disparities in the quality of care provided to minorities has been documented in the literature. Reliable racial/ethnic reporting is critical, as initiatives to address healthcare disparities remain priorities on the national agenda. Hispanic children have been cited as having a higher incidence of leukemia/lymphoma but poorer survival rates. Accurate attribution of disease incidence and outcome to specific populations is central to ensuring appropriate access to care, family communication, resource distribution and funding for research. Analysis of 2000-2010 Hematology/Oncology data at Rady Children's Hospital San Diego (RCHSD) found a 13.02% discrepancy rate for race/ethnicity accuracy and 21% self-report rate. RCHSD is a pediatric medical center serving San Diego, Imperial, and southern Riverside counties in California, where Hispanic children comprise 42% of the population. While there is consensus regarding the importance of self-reporting of race/ethnicity, we identified both significant lack of self-reported race/ethnicity data and varied forms used to collect patient demographics at our site. Research has shown that most observers including administrative staff will accurately identify individuals as white or black, but Hispanic and multiracial individuals are often misidentified. Purpose: The Global Aim of this study was to improve resource allocation, patient-provider engagement and access to race/ethnicity and language data for research through correct race/ethnicity/language attribution. Our SMART aim was to implement a uniform and accurate system for data collection on race/ethnicity and language for the hematology/oncology population at our hospital with a reduction of missing and discrepant data to <2% within 6 months. Design/Methods: We conducted a quality improvement pilot project to achieve our Global Aim. Plan-Do -Study-Act method was used. P: Key stakeholders used Fishbone analysis and flow charting and several barriers to processes and possible interventions were identified. A new single form (English and Spanish) was created to obtain self-reported race/ethnicity and information on preferred language of written medical information, and preferred spoken language. A decision map to aid parents in question answering and information sheet were also created. Staff was trained to assist parents and document in the Electronic Medical Record (EMR). D: Self-reported data was obtained from 200 patients during a 6-week period. S: Pre and Post rates of self-reported race/ethnicity and language data completion and accuracy rates were compared. Accuracy rates for race/ethnicity and language were calculated by comparing existing demographic information in the EMR system at RCHSD versus demographic information collected with the new form. A: Data was presented to Hospital Quality Council; plan to embed tools in EMR and pilot a second population. Results: We found that race/ethnicity information was not collected in a uniform and consistent manner. Seven different demographic data collection forms were replaced by the new form. Discrepancy rate was reduced to 1.2%, a reduction of 90% (chi-square 19.073, p<0.001) and self-report rate was increased to 97%, an increase of 76% (chi-square 191.318, p<0.001). Forty-eight percent of individuals self-identified as Hispanic, 13% preferred Spanish as the language for spoken and written medical material, and in 21% patients, Spanish was the language spoken at home. Conclusions: Identifying barriers, reducing variability with a single data collection tool, and adjunct tools improved race/ethnicity/language accuracy. Next steps include definitive implementation and expansion to entire hospital. Collecting accurate information on patients' race/ethnicity and language should be a universal practice, enabling to understand and address disparities in childhood cancer. Disclosures No relevant conflicts of interest to declare.


2019 ◽  
Vol 49 (2-3) ◽  
pp. 117-126 ◽  
Author(s):  
Halima Samra ◽  
Alice Li ◽  
Ben Soh ◽  
Mohammed Al Zain

Background: Although in recent times the Saudi government has paid much attention to the adaptation of hospital information systems (HIS) and electronic medical records (EMR), the importance of utilising HIS to enhance medical research has been neglected. Objective: We aimed to (i) investigate the current state of medical research in Saudi Arabia, (ii) identify possible issues that hinder improvement of medical research and (iii) identify possible solutions to enhance the role of HIS in medical research in Saudi Arabia. Method: We used a questionnaire and structured interview approach. Questionnaires were distributed to Saudi healthcare professionals. One hundred responses to our questionnaire were captured by the online Google Form designed specifically for our survey. Structured interviews with two IT professionals were conducted regarding technical aspects of their hospital data management systems. Results: Six themes contributing to the inefficacy of HIS in medical research in Saudi Arabia emerged from the data: incorrect datasets, difficult data collection and storage, poor data analytics, a lack of system interoperability across different HIS for universal access and negative perception of the usefulness of HIS for medical research. Conclusion and implications: Our findings suggest (i) cloud-based HIS would support efficient, reliable and integrated data collection and storage across all hospitals in Saudi Arabia; (ii) EMR data sources should be seamlessly linked to avoid incomplete, fragmented or erroneous EMR in Saudi Arabia; and (iii) collaboration between all hospitals in Saudi Arabia to adopt a uniform standard to support interoperability and improve data exchange and integration is necessary.


2015 ◽  
Vol 23 (3) ◽  
pp. 627-634 ◽  
Author(s):  
Simon J Craddock Lee ◽  
James E Grobe ◽  
Jasmin A Tiro

Background Measurement of patient race/ethnicity in electronic health records is mandated and important for tracking health disparities. Objective Characterize the quality of race/ethnicity data collection efforts. Methods For all cancer patients diagnosed (2007–2010) at two hospitals, we extracted demographic data from five sources: 1) a university hospital cancer registry, 2) a university electronic medical record (EMR), 3) a community hospital cancer registry, 4) a community EMR, and 5) a joint clinical research registry. The patients whose data we examined (N = 17 834) contributed 41 025 entries (range: 2–5 per patient across sources), and the source comparisons generated 1–10 unique pairs per patient. We used generalized estimating equations, chi-squares tests, and kappas estimates to assess data availability and agreement. Results Compared to sex and insurance status, race/ethnicity information was significantly less likely to be available (χ2 &gt; 8043, P &lt; .001), with variation across sources (χ2 &gt; 10 589, P &lt; .001). The university EMR had a high prevalence of “Unknown” values. Aggregate kappa estimates across the sources was 0.45 (95% confidence interval, 0.45–0.45; N = 31 276 unique pairs), but improved in sensitivity analyses that excluded the university EMR source (κ = 0.89). Race/ethnicity data were in complete agreement for only 6988 patients (39.2%). Pairs with a “Black” data value in one of the sources had the highest agreement (95.3%), whereas pairs with an “Other” value exhibited the lowest agreement across sources (11.1%). Discussion Our findings suggest that high-quality race/ethnicity data are attainable. Many of the “errors” in race/ethnicity data are caused by missing or “Unknown” data values. Conclusions To facilitate transparent reporting of healthcare delivery outcomes by race/ethnicity, healthcare systems need to monitor and enforce race/ethnicity data collection standards.


1999 ◽  
Vol 38 (03) ◽  
pp. 200-206 ◽  
Author(s):  
Y. Ogushi ◽  
Y. Okada ◽  
M. Kimura ◽  
I Kumamoto ◽  
Y. Sekita ◽  
...  

AbstractQuestionnaire surveys were sent to hospital managers, designed to shape the policy for future hospital information systems in Japan. The answers show that many hospitals use dedicated management systems, especially for patient registration and accounting, and personnel, food control, pharmacy and financial departments. In many hospitals, order-entry systems for laboratory tests and prescriptions are well developed. Half of the hospitals have patient databases used for inquiries of basic patient information, history of outpatient care and hospital care. The most obvious benefit is the reduction of office work, due to effective hospital information system. Many hospital managers want to use the following sub systems in the future for automatic payment, waiting time display, patient records search, automatic prescription verification, drug side-effect monitoring, and graphical display of patient record data.


1998 ◽  
Vol 37 (01) ◽  
pp. 16-25 ◽  
Author(s):  
P. Ringleb ◽  
T. Steiner ◽  
P. Knaup ◽  
W. Hacke ◽  
R. Haux ◽  
...  

Abstract:Today, the demand for medical decision support to improve the quality of patient care and to reduce costs in health services is generally recognized. Nevertheless, decision support is not yet established in daily routine within hospital information systems which often show a heterogeneous architecture but offer possibilities of interoperability. Currently, the integration of decision support functions into clinical workstations is the most promising way. Therefore, we first discuss aspects of integrating decision support into clinical workstations including clinical needs, integration of database and knowledge base, knowledge sharing and reuse and the role of standardized terminology. In addition, we draw up functional requirements to support the physician dealing with patient care, medical research and administrative tasks. As a consequence, we propose a general architecture of an integrated knowledge-based clinical workstation. Based on an example application we discuss our experiences concerning clinical applicability and relevance. We show that, although our approach promotes the integration of decision support into hospital information systems, the success of decision support depends above all on an adequate transformation of clinical needs.


1974 ◽  
Author(s):  
Stanley E. Jacobs ◽  
Lou Phillips ◽  
Marion J. Ball ◽  
John W. Anderson

2019 ◽  
Vol 26 (1) ◽  
pp. 420-434 ◽  
Author(s):  
Lizawati Salahuddin ◽  
Zuraini Ismail ◽  
Ummi Rabaah Hashim ◽  
Nor Haslinda Ismail ◽  
Raja Rina Raja Ikram ◽  
...  

This study aims to investigate healthcare practitioner behaviour in adopting Health Information Systems which could affect patients’ safety and quality of health. A qualitative study was conducted based on a semi-structured interview protocol on 31 medical doctors in three Malaysian government hospitals implementing the Total Hospital Information Systems. The period of study was between March and May 2015. A thematic qualitative analysis was performed on the resultant data to categorize them into relevant themes. Four themes emerged as healthcare practitioners’ behaviours that influence the unsafe use of Hospital Information Systems. The themes include (1) carelessness, (2) workarounds, (3) noncompliance to procedure, and (4) copy and paste habit. By addressing these behaviours, the hospital management could further improve patient safety and the quality of patient care.


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