Authors:Klesta Hoxha, Yuen W Hung, Bridget R Irwin, Karen A Grépin Abstract: Health Information Management Journal, Ahead of Print. Background:Routine health information systems (RHISs) are crucial to informing decision-making at all levels of the health system. However, the use of RHIS data in low- and middle-income countries (LMICs) is limited due to concerns regarding quality, accuracy, timeliness, completeness and representativeness.Objective:This study systematically reviewed technical, behavioural and organisational/environmental challenges that hinder the use of RHIS data in LMICs and strategies implemented to overcome these challenges.Method:Four electronic databases were searched for studies describing challenges associated with the use of RHIS data and/or strategies implemented to circumvent these challenges in LMICs. Identified articles were screened against inclusion and exclusion criteria by two independent reviewers.Results:Sixty studies met the inclusion criteria and were included in this review, 55 of which described challenges in using RHIS data and 20 of which focused on strategies to address these challenges. Identified challenges and strategies were organised by their technical, behavioural and organisational/environmental determinants and by the core steps of the data process. Organisational/environmental challenges were the most commonly reported barriers to data use, while technical challenges were the most commonly addressed with strategies.Conclusion:Despite the known benefits of RHIS data for health system strengthening, numerous challenges continue to impede their use in practice.Implications:Additional research is needed to identify effective strategies for addressing the determinants of RHIS use, particularly given the disconnect identified between the type of challenge most commonly described in the literature and the type of challenge most commonly targeted for interventions. Citation: Health Information Management Journal PubDate: 2020-06-30T10:30:44Z DOI: 10.1177/1833358320928729
Authors:Niamh McGrath, Barbara Foley, Caroline Hurley, Maria Ryan, Rachel Flynn Abstract: Health Information Management Journal, Ahead of Print. Safe and reliable healthcare depends on access to health information that is accurate, valid, reliable, timely, relevant, legible and complete. National data collections are repositories of health and social care data and play a crucial role in healthcare planning and clinical decision-making. We describe the development of an evidence-informed multi-method quality improvement program aimed to improve the quality of health and social care data in Ireland. Specific components involved: development of guidance to support implementation of health information standards; review program to assess compliance with standards; and educating health information stakeholders about health data and information quality. Observations from implementation of the program indicate enhanced health information stakeholder awareness of, and increased adoption of information management standards. The methodology used in the review program has proved to be a robust approach to identify areas of good practice and opportunities for improvement in information management practices. There has been positive adoption of the program among organisations reviewed and acceptance of the proposed recommendations. Early indications are that this multi-method approach will drive improvements in information management practices, leading to an improvement in health and social care data quality in Ireland. Aspects of this approach may be adapted to meet the needs of other countries. Citation: Health Information Management Journal PubDate: 2020-06-26T08:50:55Z DOI: 10.1177/1833358320926422
Authors:Cameron Coleman, David Gotz, Samantha Eaker, Elaine James, Thomas Bice, Shannon Carson, Saif Khairat Abstract: Health Information Management Journal, Ahead of Print. Background:Some physicians in intensive care units (ICUs) report that electronic health records (EHRs) can be cumbersome and disruptive to workflow. There are significant gaps in our understanding of the physician–EHR interaction.Objective:To better understand how clinicians use the EHR for chart review during ICU pre-rounds through the characterisation and description of screen navigation pathways and workflow patterns.Method:We conducted a live, direct observational study of six physician trainees performing electronic chart review during daily pre-rounds in the 30-bed medical ICU at a large academic medical centre in the Southeastern United States. A tailored checklist was used by observers for data collection.Results:We observed 52 distinct live patient chart review encounters, capturing a total of 2.7 hours of pre-rounding chart review activity by six individual physicians. Physicians reviewed an average of 8.7 patients (range = 5–12), spending a mean of 3:05 minutes per patient (range = 1:34–5:18). On average, physicians visited 6.3 (±3.1) total EHR screens per patient (range = 1–16). Four unique screens were viewed most commonly, accounting for over half (52.7%) of all screen visits: results review (17.9%), summary/overview (13.0%), flowsheet (12.7%), and the chart review tab (9.1%). Navigation pathways were highly variable, but several common screen transition patterns emerged across users. Average interrater reliability for the paired EHR observation was 80.0%.Conclusion:We observed the physician–EHR interaction during ICU pre-rounds to be brief and highly focused. Although we observed a high degree of “information sprawl” in physicians’ digital navigation, we also identified common launch points for electronic chart review, key high-traffic screens and common screen transition patterns.Implications:From the study findings, we suggest recommendations towards improved EHR design. Citation: Health Information Management Journal PubDate: 2020-06-01T11:12:40Z DOI: 10.1177/1833358320920589
Authors:Witold H Polanski, Adrian Danker, Amir Zolal, David Senf-Mothes, Gabriele Schackert, Dietmar Krex Abstract: Health Information Management Journal, Ahead of Print. Background:Electronic health records (EHRs) may be controversial but they have the potential to improve patient care. We investigated whether the introduction of an electronic template-based admission form for the collection of information about the patient’s medical history and neurological and clinical state at admission in the neurosurgical unit might have an impact on the quality of documentation in a discharge record and the amount of time taken to produce this documentation.Method:A new digital template-based admission form (EHR) was developed and assessed with QNOTE, an assessment tool of medical notes with standardised criteria and the possibility to benchmark the quality of documentations. This was compared to 30 prior paper-based handwritten documentations (HWD) regarding the utilisation of these medical notes for dictation of medical discharge records.Results:Implementation of the EHR significantly improved the quality of patient admission documentation with a QNOTE mean grand score of 87 ± 22 (p < 0.0001) compared to prior HWD with 44 ± 30. The mean documentation time for HWD was 8.1 min ± 4.1 min and the dictation time for discharge records was 10.6 min ± 3.5 min. After implementation of EHR, the documentation time increased slightly to 9.6 min ± 2.3 min (n.s.), while the time for dictation of discharge records was reduced to 5.1 min ± 1.2 min (p < 0.0001). There was a clear correlation between a higher quality of documentation and a higher needed documentation time as well as higher quality of documentation and lower dictation times of discharge records.Conclusion:Implementation of the EHR improved the quality of patient admission documentation and reduced the dictation time of discharge records.Implications:It is crucial to involve stakeholders and users of EHRs in a timely manner during the stage of development and implementation phase to ensure optimal results and better usability. Citation: Health Information Management Journal PubDate: 2020-05-20T11:11:28Z DOI: 10.1177/1833358320920990
Authors:Michelle A Krahe, Malcolm Wolski, Sharon Mickan, Julie Toohey, Paul Scuffham, Sheena Reilly Abstract: Health Information Management Journal, Ahead of Print. Background:Data sharing presents new opportunities across the spectrum of research and is vital for science that is open, where data are easily discoverable, accessible, intelligible, reproducible, replicable and verifiable. Despite this, it is yet to become common practice. Global efforts to develop practical guidance for data sharing and open access initiatives are underway, however evidence-based studies to inform the development and implementation of effective strategies are lacking.Objective:This study sought to determine the barriers and facilitators to data sharing among health researchers and to identify the target behaviours for designing a behaviour change intervention strategy.Method:Data were drawn from a cross-sectional survey of data management practices among health researchers from one Australian research institute. Determinants of behaviour were theoretically derived using well-established behavioural models.Results:Data sharing practices have been described for 77 researchers, and 6 barriers and 4 facilitators identified. The primary barriers to data sharing included perceived negative consequences and lack of competency to share data. The primary facilitators to data sharing included trust in others using the data and social influence related to public benefit. Intervention functions likely to be most effective at changing target behaviours were also identified.Conclusion:Results of this study provide a theoretical and evidence-based process to understand the behavioural barriers and facilitators of data sharing among health researchers.Implications:Designing interventions that specifically address target behaviours to promote data sharing are important for open researcher practices. Citation: Health Information Management Journal PubDate: 2020-05-05T11:53:28Z DOI: 10.1177/1833358320917207
Authors:Görkem Sarıyer, Mustafa Gökalp Ataman Abstract: Health Information Management Journal, Ahead of Print. Background:Emergency departments (EDs) play an important role in health systems since they are the front line for patients with emergency medical conditions who frequently require diagnostic tests and timely treatment.Objective:To improve decision-making and accelerate processes in EDs, this study proposes predictive models for classifying patients according to whether or not they are likely to require a diagnostic test based on referral diagnosis, age, gender, triage category and type of arrival.Method:Retrospective data were categorised into four output patient groups: not requiring any diagnostic test (group A); requiring a radiology test (group B); requiring a laboratory test (group C); requiring both tests (group D). Multivariable logistic regression models were used, with the outcome classifications represented as a series of binary variables: test (1) or no test (0); in the case of group A, no test (1) or test (0).Results:For all models, age, triage category, type of arrival and referral diagnosis were significant predictors whereas gender was not. The main referral diagnosis with high model coefficients varied by designed output groups (groups A, B, C and D). The overall accuracies of the logistic regression models for groups A, B, C and D were, respectively, 74.11%, 73.07%, 82.47% and 85.79%. Specificity metrics were higher than the sensitivities for groups B, C and D, meaning that these models were better able to predict negative outcomes.Implications:These results provide guidance for ED triage staff, researchers and practitioners in making rapid decisions regarding patients’ diagnostic test requirements based on specified variables in the predictive models. This is critical in ED operations planning as it potentially decreases waiting times, while increasing patient satisfaction and operational performance. Citation: Health Information Management Journal PubDate: 2020-03-30T11:31:27Z DOI: 10.1177/1833358320908975
Authors:John A Woods, Claire E Johnson, Samuel F Allingham, Hanh T Ngo, Judith M Katzenellenbogen, Sandra C Thompson Abstract: Health Information Management Journal, Ahead of Print. Background:Data quality is fundamental to the integrity of quantitative research. The role of external researchers in data quality assessment (DQA) remains ill-defined in the context of secondary use for research of large, centrally curated health datasets. In order to investigate equity of palliative care provided to Indigenous Australian patients, researchers accessed a now-historical version of a national palliative care dataset developed primarily for the purpose of continuous quality improvement.Objectives:(i) To apply a generic DQA framework to the dataset and (ii) to report the process and results of this assessment and examine the consequences for conducting the research.Method:The data were systematically examined for completeness, consistency and credibility. Data quality issues relevant to the Indigenous identifier and framing of research questions were of particular interest.Results:The dataset comprised 477,518 records of 144,951 patients (Indigenous N = 1515; missing Indigenous identifier N = 4998) collected from participating specialist palliative care services during a period (1 January 2010–30 June 2015) in which data-checking systems underwent substantial upgrades. Progressive improvement in completeness of data over the study period was evident. The data were error-free with respect to many credibility and consistency checks, with anomalies detected reported to data managers. As the proportion of missing values remained substantial for some clinical care variables, multiple imputation procedures were used in subsequent analyses.Conclusion and implications:In secondary use of large curated datasets, DQA by external researchers may both influence proposed analytical methods and contribute to improvement of data curation processes through feedback to data managers. Citation: Health Information Management Journal PubDate: 2020-03-27T10:31:23Z DOI: 10.1177/1833358320908957
Authors:Reece Hinchcliff, Deborah Debono, David Carter, Miriam Glennie, Hamish Robertson, Joanne Travaglia Abstract: Health Information Management Journal, Ahead of Print. Background:Assessment processes applied within some health service accreditation programs have been criticised at times for being inaccurate, inconsistent or inefficient. Such criticism has inspired the development of innovative assessment methods.Objective:The Australian Commission on Safety and Quality in Health Care considered the use of three such methods: short-notice or unannounced methods; patient journey or tracer methods; and attestation by governing bodies.Method:A systematic search and synthesis of published peer-reviewed and grey literature associated with these methods.Results and Conclusion:The published literature demonstrates that the likely benefits of these three assessment methods warrant further evaluation, real-world trials and stakeholder consultation to determine the most appropriate models to introduce into national accreditation programs.Implications:The subsequent introduction of models of short-notice assessments and attestation by governing bodies into the Australian Health Service Safety and Quality Accreditation Scheme in January 2019 demonstrates how the findings presented in this article influenced the national change in assessment practice, providing an example of evidence-informed accreditation development. Citation: Health Information Management Journal PubDate: 2020-03-24T11:06:37Z DOI: 10.1177/1833358320910890
Authors:Kara Cappetta, Luise Lago, Jan Potter, Lyn Phillipson Abstract: Health Information Management Journal, Ahead of Print. Background:Under-coding of dementia during hospitalisation results in an inability to identify all patients with dementia using hospital administrative data. Clinical coding can be viewed as a proxy for management; therefore, under-coding indicates dementia was not considered in the patient’s management. While under-coding of dementia is well established, there is sparse evidence on whether dementia is coded in subsequent hospitalisations among patients with a known diagnosis.Objective:(a) To describe patterns of dementia coding over 5 years after a first-coded (i.e. index) admission for dementia; (b) to identify factors associated with clinical coding of dementia; and (c) to identify patient subgroups at risk of not being coded to inform future interventions to improve hospital identification and management of dementia.Method:Retrospective study of longitudinal hospital data from 1 July 2006 to 30 June 2015 for 7919 patients hospitalised during the 5 years’ post-index admission for dementia in a regional local health district of New South Wales, Australia.Results:Dementia was coded in 63.9% of admissions in the 12 months following index admission for dementia; this decreased to 53.7% after 5 years. Patients were 20% more likely to have dementia actively managed when it co-occurred with delirium. Under-coding varied across conditions, with dementia more likely to be coded in admissions for falls and pneumonitis, and less likely for heart failure, pneumonia and urinary tract infection (UTI).Conclusion:The frequency with which dementia was not coded highlights opportunities to improve identification and management of dementia through dementia-specific care, enhanced clinical protocols, and interventions focused around heart failure, pneumonia and UTI admissions. Citation: Health Information Management Journal PubDate: 2020-01-23T10:53:24Z DOI: 10.1177/1833358319897928
Authors:Kellie-Anne Crameri, Lynne Maher, Pieter Van Dam, Sarah Prior Abstract: Health Information Management Journal, Ahead of Print. Background:Online electronic records such as patient portals and personally controlled electronic health records (PEHRs) have been widely viewed as a key component to modernising the delivery of healthcare but the uptake of such systems has been slow.Objective:The purpose of this literature review was to determine what influences consumers to engage and interact with their clinical data online.Method:A scoping literature review following PRISMA guidelines was completed. Electronic patient record research published between January 2009 and December 2018 was included. Following screening and full-text reviews, a total of 64 records were included in this review.Results:Three key areas of influence on consumer engagement with their clinical data online emerged: demographic factors affecting consumer interaction with PEHRs; consumers’ perceived benefits and detriments of PEHR use; and the influence of PEHR use on consumer empowerment and responsibility.Discussion:Consumer motivation and readiness for engaging with their clinical data online and their long-term ongoing use of these systems requires further exploration.Conclusion:As worldwide rates of consumer interactions with individual online clinical data remain low, what influences consumer engagement with a PEHR remains unknown. Further research into the consumer perspective of, and interaction with, a PEHR, needs to be undertaken to determine if factors such as frequent usage of the system by consumers leads to improved clinical outcomes. Citation: Health Information Management Journal PubDate: 2020-01-10T09:53:55Z DOI: 10.1177/1833358319895369
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