Legal and Ethical Issues Associated With Challenges in the Implementation of the Electronic Medical Record System and Its Current Laws in India

Electronic health records (EHR) have revolutionized healthcare by providing efficient access to patient information, but their implementation poses various challenges. This paper examines the ethical and legal issues surrounding EHR adoption, particularly focusing on the healthcare landscape in India. Ethical considerations, including patient autonomy, confidentiality, beneficence, and justice, must guide EHR implementation to protect patient rights and privacy. Legal issues such as medical errors, malpractice, data breaches, and billing inaccuracies underscore the importance of robust policies and security measures. Threats to EHRs, such as phishing attacks, malware, encryption vulnerabilities, and insider threats, emphasize the need for comprehensive cybersecurity strategies. Overcoming challenges in EHR implementation requires meticulous planning, financial investment, staff training, and stakeholder support. Despite the complexities involved, the benefits of EHR adoption in improving patient care and operational efficiency justify the efforts required to address legal, ethical, and technical concerns. Embracing EHRs while mitigating associated risks is essential for delivering high-quality healthcare in the digital age.

Hepatitis A Vaccination Coverage Among People With Chronic Liver Disease in England (HEALD): Protocol for a Retrospective Cohort Study

BACKGROUND

Hepatitis A outbreaks in the United Kingdom are uncommon. Most people develop mild to moderate symptoms that resolve, without sequelae, within months. However, in high-risk groups, including those with underlying chronic liver disease (CLD), hepatitis A infection can be severe, with a higher risk of mortality and morbidity. The Health Security Agency and the National Institute of Health and Care Excellence recommend preexposure hepatitis A vaccination given in 2 doses to people with CLD, regardless of its cause. There are currently no published reports of vaccination coverage for people with CLD in England or internationally.

OBJECTIVE

This study aims to describe hepatitis A vaccination coverage in adults with CLD in a UK primary care setting and compare liver disease etiology, sociodemographic characteristics, and comorbidities in people who are and are not exposed to the hepatitis A vaccine.

METHODS

We will conduct a retrospective cohort study with data from the Primary Care Sentinel Cohort of the Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub database, which is nationally representative of the English population. We will include people aged 18 years and older who have been registered in general practices in the Research and Surveillance Centre network and have a record of CLD between January 1, 2012, and December 31, 2022, including those with alcohol-related liver disease, chronic hepatitis B, chronic hepatitis C, nonalcohol fatty liver disease, Wilson disease, hemochromatosis, and autoimmune hepatitis. We will carefully curate variables using the Systematized Nomenclature of Medicine Clinical Terms. We will report the sociodemographic characteristics of those who are vaccinated. These include age, gender, ethnicity, population density, region, socioeconomic status (measured using the index of multiple deprivation), obesity, alcohol consumption, and smoking. Hepatitis A vaccination coverage for 1 and 2 doses will be calculated using an estimate of the CLD population as the denominator. We will analyze the baseline characteristics using descriptive statistics, including measures of dispersion. Pairwise comparisons of case-mix characteristics, comorbidities, and complications will be reported according to vaccination status. A multistate survival model will be fitted to estimate the transition probabilities among four states: (1) diagnosed with CLD, (2) first dose of hepatitis A vaccination, (3) second dose of hepatitis A vaccination, and (4) death. This will identify any potential disparities in how people with CLD get vaccinated.

RESULTS

The Research and Surveillance Centre population comprises over 8 million people. The reported incidence of CLD is 20.7 cases per 100,000. International estimates of hepatitis A vaccine coverage vary between 10% and 50% in this group.

CONCLUSIONS

This study will describe the uptake of the hepatitis A vaccine in people with CLD and report any disparities or differences in the characteristics of the vaccinated population.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/51861.

Optimizing Patient Record Linkage in a Master Patient Index Using Machine Learning: Algorithm Development and Validation

BACKGROUND

To provide quality care, modern health care systems must match and link data about the same patient from multiple sources, a function often served by master patient index (MPI) software. Record linkage in the MPI is typically performed manually by health care providers, guided by automated matching algorithms. These matching algorithms must be configured in advance, such as by setting the weights of patient attributes, usually by someone with knowledge of both the matching algorithm and the patient population being served.

OBJECTIVE

We aimed to develop and evaluate a machine learning-based software tool, which automatically configures a patient matching algorithm by learning from pairs of patient records previously linked by humans already present in the database.

METHODS

We built a free and open-source software tool to optimize record linkage algorithm parameters based on historical record linkages. The tool uses Bayesian optimization to identify the set of configuration parameters that lead to optimal matching performance in a given patient population, by learning from prior record linkages by humans. The tool is written assuming only the existence of a minimal HTTP application programming interface (API), and so is agnostic to the choice of MPI software, record linkage algorithm, and patient population. As a proof of concept, we integrated our tool with SantéMPI, an open-source MPI. We validated the tool using several synthetic patient populations in SantéMPI by comparing the performance of the optimized configuration in held-out data to SantéMPI's default matching configuration using sensitivity and specificity.

RESULTS

The machine learning-optimized configurations correctly detect over 90% of true record linkages as definite matches in all data sets, with 100% specificity and positive predictive value in all data sets, whereas the baseline detects none. In the largest data set examined, the baseline matching configuration detects possible record linkages with a sensitivity of 90.2% (95% CI 88.4%-92.0%) and specificity of 100%. By comparison, the machine learning-optimized matching configuration attains a sensitivity of 100%, with a decreased specificity of 95.9% (95% CI 95.9%-96.0%). We report significant gains in sensitivity in all data sets examined, at the cost of only marginally decreased specificity. The configuration optimization tool, data, and data set generator have been made freely available.

CONCLUSIONS

Our machine learning software tool can be used to significantly improve the performance of existing record linkage algorithms, without knowledge of the algorithm being used or specific details of the patient population being served.

Step-Wise Management of Anemia in Patients With Chronic Kidney Disease in Primary Care: Qualitative Study

INTRODUCTION

Anemia is common in chronic kidney disease (CKD) and is associated with increased cardiovascular risk and reduced quality of life, but is often sub-optimally managed. Most patients are managed in primary care alongside other comorbidities. Interventions to improve the management of anemia in CKD in this setting are needed.

METHODS

We conducted a qualitative study to evaluate how an audit-based education (ABE) intervention might improve the management of anemia in CKD. We explored outcomes that would be relevant to practitioners and patients, that exposed variation of practice from National Institute for Health and Care Excellence (NICE) guidelines, and whether the intervention was feasible and acceptable.

RESULTS

Practitioners (n = 5 groups) and patients (n = 7) from 4 London general practices participated in discussions. Practitioners welcomed the evidence-based step-wise intervention. However, prescribing erythropoiesis-stimulating agents (ESAs) was felt to be outside of their scope of practice. There was a gap between NICE guidance and clinical practice in primary care. Iron studies were not well understood and anemia management was often conservative or delayed. Patients were often unaware of having CKD, and were more concerned about their other comorbidities, but largely trusted their GPs to manage them appropriately.

CONCLUSIONS

The first steps of the intervention were welcomed by practitioners, but they expressed concerns about independently prescribing ESAs. Renal physicians and GPs could develop shared care protocols for ESA use in primary care. There is scope to improve awareness of renal anemia, and enhance knowledge of guideline recommendations; and our intervention should be modified accordingly.

Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study

BACKGROUND

Most studies of long COVID (symptoms of COVID-19 infection beyond 4 weeks) have focused on people hospitalized in their initial illness. Long COVID is thought to be underrecorded in UK primary care electronic records.

OBJECTIVE

We sought to determine which symptoms people present to primary care after COVID-19 infection and whether presentation differs in people who were not hospitalized, as well as post-long COVID mortality rates.

METHODS

We used routine data from the nationally representative primary care sentinel cohort of the Oxford-Royal College of General Practitioners Research and Surveillance Centre (N=7,396,702), applying a predefined long COVID phenotype and grouped by whether the index infection occurred in hospital or in the community. We included COVID-19 infection cases from March 1, 2020, to April 1, 2021. We conducted a before-and-after analysis of long COVID symptoms prespecified by the Office of National Statistics, comparing symptoms presented between 1 and 6 months after the index infection matched with the same months 1 year previously. We conducted logistic regression analysis, quoting odds ratios (ORs) with 95% CIs.

RESULTS

In total, 5.63% (416,505/7,396,702) and 1.83% (7623/416,505) of the patients had received a coded diagnosis of COVID-19 infection and diagnosis of, or referral for, long COVID, respectively. People with diagnosis or referral of long COVID had higher odds of presenting the prespecified symptoms after versus before COVID-19 infection (OR 2.66, 95% CI 2.46-2.88, for those with index community infection and OR 2.42, 95% CI 2.03-2.89, for those hospitalized). After an index community infection, patients were more likely to present with nonspecific symptoms (OR 3.44, 95% CI 3.00-3.95; P<.001) compared with after a hospital admission (OR 2.09, 95% CI 1.56-2.80; P<.001). Mental health sequelae were more strongly associated with index hospital infections (OR 2.21, 95% CI 1.64-2.96) than with index community infections (OR 1.36, 95% CI 1.21-1.53; P<.001). People presenting to primary care after hospital infection were more likely to be men (OR 1.43, 95% CI 1.25-1.64; P<.001), more socioeconomically deprived (OR 1.42, 95% CI 1.24-1.63; P<.001), and with higher multimorbidity scores (OR 1.41, 95% CI 1.26-1.57; P<.001) than those presenting after an index community infection. All-cause mortality in people with long COVID was associated with increasing age, male sex (OR 3.32, 95% CI 1.34-9.24; P=.01), and higher multimorbidity score (OR 2.11, 95% CI 1.34-3.29; P<.001). Vaccination was associated with reduced odds of mortality (OR 0.10, 95% CI 0.03-0.35; P<.001).

CONCLUSIONS

The low percentage of people recorded as having long COVID after COVID-19 infection reflects either low prevalence or underrecording. The characteristics and comorbidities of those presenting with long COVID after a community infection are different from those hospitalized. This study provides insights into the presentation of long COVID in primary care and implications for workload.

Developing a Long COVID Phenotype for Postacute COVID-19 in a National Primary Care Sentinel Cohort: Observational Retrospective Database Analysis

BACKGROUND

Following COVID-19, up to 40% of people have ongoing health problems, referred to as postacute COVID-19 or long COVID (LC). LC varies from a single persisting symptom to a complex multisystem disease. Research has flagged that this condition is underrecorded in primary care records, and seeks to better define its clinical characteristics and management. Phenotypes provide a standard method for case definition and identification from routine data and are usually machine-processable. An LC phenotype can underpin research into this condition.

OBJECTIVE

This study aims to develop a phenotype for LC to inform the epidemiology and future research into this condition. We compared clinical symptoms in people with LC before and after their index infection, recorded from March 1, 2020, to April 1, 2021. We also compared people recorded as having acute infection with those with LC who were hospitalized and those who were not.

METHODS

We used data from the Primary Care Sentinel Cohort (PCSC) of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database. This network was recruited to be nationally representative of the English population. We developed an LC phenotype using our established 3-step ontological method: (1) ontological step (defining the reasoning process underpinning the phenotype, (2) coding step (exploring what clinical terms are available, and (3) logical extract model (testing performance). We created a version of this phenotype using Protégé in the ontology web language for BioPortal and using PhenoFlow. Next, we used the phenotype to compare people with LC (1) with regard to their symptoms in the year prior to acquiring COVID-19 and (2) with people with acute COVID-19. We also compared hospitalized people with LC with those not hospitalized. We compared sociodemographic details, comorbidities, and Office of National Statistics-defined LC symptoms between groups. We used descriptive statistics and logistic regression.

RESULTS

The long-COVID phenotype differentiated people hospitalized with LC from people who were not and where no index infection was identified. The PCSC (N=7.4 million) includes 428,479 patients with acute COVID-19 diagnosis confirmed by a laboratory test and 10,772 patients with clinically diagnosed COVID-19. A total of 7471 (1.74%, 95% CI 1.70-1.78) people were coded as having LC, 1009 (13.5%, 95% CI 12.7-14.3) had a hospital admission related to acute COVID-19, and 6462 (86.5%, 95% CI 85.7-87.3) were not hospitalized, of whom 2728 (42.2%) had no COVID-19 index date recorded. In addition, 1009 (13.5%, 95% CI 12.73-14.28) people with LC were hospitalized compared to 17,993 (4.5%, 95% CI 4.48-4.61; P<.001) with uncomplicated COVID-19.

CONCLUSIONS

Our LC phenotype enables the identification of individuals with the condition in routine data sets, facilitating their comparison with unaffected people through retrospective research. This phenotype and study protocol to explore its face validity contributes to a better understanding of LC.

Early and ongoing stable glycaemic control is associated with a reduction in major adverse cardiovascular events in people with type 2 diabetes: A primary care cohort study

AIM

To determine whether achieving early glycaemic control, and any subsequent glycaemic variability, was associated with any change in the risk of major adverse cardiovascular events (MACE).

MATERIALS AND METHODS

A retrospective cohort analysis from the Oxford-Royal College of General Practitioners Research and Surveillance Centre database-a large, English primary care network-was conducted. We followed newly diagnosed patients with type 2 diabetes, on or after 1 January 2005, aged 25 years or older at diagnosis, with HbA1c measurements at both diagnosis and after 1 year, plus five or more measurements of HbA1c thereafter. Three glycaemic bands were created: groups A (HbA1c < 58 mmol/mol [<7.5%]), B (HbA1c ≥ 58 to 75 mmol/mol [7.5%-9.0%]) and C (HbA1c ≥ 75 mmol/mol [≥9.0%]). Movement between bands was determined from diagnosis to 1 year. Additionally, for data after the first 12 months, a glycaemic variability score was calculated from the number of successive HbA1c readings differing by 0.5% or higher (≥5.5 mmol/mol). Risk of MACE from 1 year postdiagnosis was assessed using time-varying Cox proportional hazards models, which included the first-year transition and the glycaemic variability score.

RESULTS

From 26 180 patients, there were 2300 MACE. Compared with group A->A transition over 1 year, those with C->A transition had a reduced risk of MACE (HR 0.75; 95% CI 0.60-0.94; P = .014), whereas group C->C had HR 1.21 (0.81-1.81; P = .34). Compared with the lowest glycaemic variability score, the greatest variability increased the risk of MACE (HR 1.51; 1.11-2.06; P = .0096).

CONCLUSION

Early control of HbA1c improved cardiovascular outcomes in type 2 diabetes, although subsequent glycaemic variability had a negative effect on an individual's risk.

Decluttering the problem list in electronic health records

DISCLAIMER

In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

PURPOSE

The purpose of this study was to evaluate the current state of problem list maintenance at an academic medical center.

SUMMARY

We included problem list data for patients who had at least 2 face-to-face encounters at Vanderbilt University Medical Center or its clinics between January 1, 2018, and December 31, 2019. We used the frequency of problem list additions, resolutions, deletions, duplicate problems (exact and SNOMED CT duplicates), inconsistencies (contradicting stages of disease state), and items that could be documented elsewhere in the electronic health record as surrogate markers of problem list maintenance. Descriptive statistics were used to summarize the results. A total of 546,510 patients met inclusion criteria. There were 3,762 (0.7%) patients who had the exact same active problem listed more than once. SNOMED CT code duplications occurred in the records for 56,399 (10.5%) patients. Of the patients with asthma, 2.5% (223/8,779) had contradicting asthma stages active on their problem list, and 6.4% (950/14,950) of patients with chronic kidney disease (CKD) had contradicting CKD stages. In addition, 17,205 (3.1%) patients had 20,365 active family history problems and 39,464 (7.2%) patients had an allergy documented on their problem list. On average, there were 43.7 (95% confidence interval [CI], 14-73.4) additions, 8.7 (95% CI, 0.1-17.4) resolutions, and 2.1 (95% CI, 0-4.6) deletions of problems per 100 face-to-face encounters, inpatient or outpatient.

CONCLUSION

Our study suggests areas for improvement for problem list maintenance. Further studies into semantic duplication and clinical decision support tools to encourage problem list maintenance and deduplication are needed.

Real Life Clinical Management and Survival in Advanced Cutaneous Melanoma: The Italian Clinical National Melanoma Registry Experience

Background

Cutaneous melanoma (CM) is one of the most aggressive types of skin cancer. Currently, innovative approaches such as target therapies and immunotherapies have been introduced in clinical practice. Data of clinical trials and real life studies that evaluate the outcomes of these therapeutic associations are necessary to establish their clinical utility. The aim of this study is to investigate the types of oncological treatments employed in the real-life clinical management of patients with advanced CM in several Italian centers, which are part of the Clinical National Melanoma Registry (CNMR).

Methods

Melanoma-specific survival and overall survival were calculated. Multivariate Cox regression models were used to estimate the hazard ratios adjusting for confounders and other prognostic factors.

Results

The median follow-up time was 36 months (range 1.2-185.1). 787 CM were included in the analysis with completed information about therapies. All types of immunotherapy showed a significant improved survival compared with all other therapies (p=0.001). 75% was the highest reduction of death reached by anti-PD-1 (HR=0.25), globally immunotherapy was significantly associated with improved survival, either for anti-CTLA4 monotherapy or combined with anti-PD-1 (HR=0.47 and 0.26, respectively) and BRAFI+MEKI (HR=0.62).

Conclusions

The nivolumab/pembrolizumab in combination of ipilimumab and the addition of ant-MEK to the BRAFi can be considered the best therapies to improve survival in a real-world-population. The CNMR can complement clinical registries with the intent of improving cancer management and standardizing cancer treatment.

Integrating molecular point-of-care testing for influenza into primary care: a mixed-methods feasibility study

Background

Molecular point-of-care testing (POCT) for influenza in primary care could influence clinical care and patient outcomes.

Aim

To assess the feasibility of incorporating influenza POCT into general practice in England.

Design and setting

A mixed-methods study conducted in six general practices that had not previously participated in respiratory virology sampling, which are part of the Royal College of General Practitioners Research and Surveillance Centre English sentinel surveillance network, from February 2019 to May 2019.

Method

A sociotechnical perspective was adopted using the Public Health England POCT implementation toolkit and business process modelling notation to inform qualitative analysis. Quantitative data were collected about the number of samples taken, their representativeness, and the virology results obtained, comparing them with the rest of the sentinel system over the same weeks.

Results

A total of 312 POCTs were performed; 276 were used for quantitative analysis, of which 60 were positive for influenza and 216 were negative. The average swabbing rate was 0.4 per 1000 population and swab positivity was between 16.7% (n = 14/84) and 41.4% (n = 12/29). Given a positive influenza POCT result, the odds ratio of receiving an antiviral was 14.1 (95% confidence intervals [CI] = 2.9 to 70.0, P<0.001) and of receiving an antibiotic was 0.4 (95% CI = 0.2 to 0.8, P = 0.01), compared with patients with a negative result. Qualitative analysis showed that it was feasible for practices to implement POCT, but there is considerable variation in the processes used.

Conclusion

Testing for influenza using POCT is feasible in primary care and may improve antimicrobial use. However, further evidence from randomised trials of influenza POCT in general practice is needed.

Emergence of a Novel Coronavirus (COVID-19): Protocol for Extending Surveillance Used by the Royal College of General Practitioners Research and Surveillance Centre and Public Health England

Background

The Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) have successfully worked together on the surveillance of influenza and other infectious diseases for over 50 years, including three previous pandemics. With the emergence of the international outbreak of the coronavirus infection (COVID-19), a UK national approach to containment has been established to test people suspected of exposure to COVID-19. At the same time and separately, the RCGP RSC’s surveillance has been extended to monitor the temporal and geographical distribution of COVID-19 infection in the community as well as assess the effectiveness of the containment strategy.

Objectives

The aims of this study are to surveil COVID-19 in both asymptomatic populations and ambulatory cases with respiratory infections, ascertain both the rate and pattern of COVID-19 spread, and assess the effectiveness of the containment policy.

Methods

The RCGP RSC, a network of over 500 general practices in England, extract pseudonymized data weekly. This extended surveillance comprises of five components: (1) Recording in medical records of anyone suspected to have or who has been exposed to COVID-19. Computerized medical records suppliers have within a week of request created new codes to support this. (2) Extension of current virological surveillance and testing people with influenza-like illness or lower respiratory tract infections (LRTI)—with the caveat that people suspected to have or who have been exposed to COVID-19 should be referred to the national containment pathway and not seen in primary care. (3) Serology sample collection across all age groups. This will be an extra blood sample taken from people who are attending their general practice for a scheduled blood test. The 100 general practices currently undertaking annual influenza virology surveillance will be involved in the extended virological and serological surveillance. (4) Collecting convalescent serum samples. (5) Data curation. We have the opportunity to escalate the data extraction to twice weekly if needed. Swabs and sera will be analyzed in PHE reference laboratories.

Results

General practice clinical system providers have introduced an emergency new set of clinical codes to support COVID-19 surveillance. Additionally, practices participating in current virology surveillance are now taking samples for COVID-19 surveillance from low-risk patients presenting with LRTIs. Within the first 2 weeks of setup of this surveillance, we have identified 3 cases: 1 through the new coding system, the other 2 through the extended virology sampling.

Conclusions

We have rapidly converted the established national RCGP RSC influenza surveillance system into one that can test the effectiveness of the COVID-19 containment policy. The extended surveillance has already seen the use of new codes with 3 cases reported. Rapid sharing of this protocol should enable scientific critique and shared learning.

International Registered Report Identifier (IRRID)

DERR1-10.2196/18606

Determinants of inter-practice variation in childhood asthma and respiratory infections: cross-sectional study of a national sentinel network

OBJECTIVES

Respiratory infections are associated with acute exacerbations of asthma and accompanying morbidity and mortality. In this study we explore inter-practice variations in respiratory infections in children with asthma and study the effect of practice-level factors on these variations.

DESIGN

Cross-sectional study.

SETTING

We analysed data from 164 general practices in the Royal College of General PractitionersResearch and Surveillance Centresentinel network in England.

PARTICIPANTS

Children 5-12 years.

INTERVENTIONS

None. In this observational study, we used regression analysis to explore the impact of practice-level determinants on the number of respiratory infections in children with asthma.

PRIMARY AND SECONDARY OUTCOME MEASURES

We describe the distribution of childhood asthma and the determinants of upper/lower respiratory tract infections in these children.

RESULTS

83.5% (137/164) practices were in urban locations; the mean number of general practitioners per practice was 7; and the mean duration since qualification 19.7 years. We found almost 10-fold difference in the rate of asthma (1.5-11.8 per 100 children) and 50-fold variation in respiratory infection rates between practices. Larger practices with larger lists of asthmatic children had greater rates of respiratory infections among these children.

CONCLUSION

We showed that structural/environmental variables are consistent predictors of a range of respiratory infections among children with asthma. However, contradictory results between measures of practice clinical care show that a purely structural explanation for variability in respiratory infections is limited. Further research is needed to understand how the practice factors influence individual risk behaviours relevant to respiratory infections.

Automated Differentiation of Incident and Prevalent Cases in Primary Care Computerised Medical Records (CMR)

Identifying incident (first or new) episodes of illness is critical in sentinel networks to inform about the seasonal onset of diseases and to give early warning of epidemics, as well as differentiating change in health service utilization from change in pattern of disease. The most reliable way of differentiating incident from prevalent cases is through the clinician assigning episode type to the patient's computerized medical record (CMR). However, episode type assignment is often made inconsistently. The objective of this collaborative study between the Royal College of General Practitioners Research and Surveillance Centre (RCGP RSC), University of Surrey and the National Physical Laboratory (NPL) is to develop a methodology to reconstruct missing or miscoded episode types. The data, gathered from the RCGP RSC network of over 230 practices, are analyzed and poor episode typing reconstructed by disease type. The methodology is tested in practices with good episode type data quality. This method could be used to improve prediction of epidemics, and to improve the quality of historical rates retrospectively.

Measuring Quality of Healthcare Outcomes in Type 2 Diabetes from Routine Data: a Seven-nation Survey Conducted by the IMIA Primary Health Care Working Group

Background: The Institute of Medicine framework defines six dimensions of quality for healthcare systems: (1) safety, (2) effectiveness, (3) patient centeredness, (4) timeliness of care, (5) efficiency, and (6) equity. Large health datasets provide an opportunity to assess quality in these areas. Objective: To perform an international comparison of the measurability of the delivery of these aims, in people with type 2 diabetes mellitus (T2DM) from large datasets. Method: We conducted a survey to assess healthcare outcomes data quality of existing databases and disseminated this through professional networks. We examined the data sources used to collect the data, frequency of data uploads, and data types used for identifying people with T2DM. We compared data completeness across the six areas of healthcare quality, using selected measures pertinent to T2DM management. Results: We received 14 responses from seven countries (Australia, Canada, Italy, the Netherlands, Norway, Portugal, Turkey and the UK). Most databases reported frequent data uploads and would be capable of near real time analysis of healthcare quality.The majority of recorded data related to safety (particularly medication adverse events) and treatment efficacy (glycaemic control and microvascular disease). Data potentially measuring equity was less well recorded. Recording levels were lowest for patient-centred care, timeliness of care, and system efficiency, with the majority of databases containing no data in these areas. Databases using primary care sources had higher data quality across all areas measured. Conclusion: Data quality could be improved particularly in the areas of patient-centred care, timeliness, and efficiency. Primary care derived datasets may be most suited to healthcare quality assessment.

Will mHealth Revolutionize Health and Clinical Management and Open up New Horizons for Mental Health?

OBJECTIVES

To summarize recent research and emerging trends in the field of Health and Clinical management and propose a selection of best papers for year 2015.

METHODS

A literature review has been conducted by the two section editors and computerized provider order entry systems from bibliographic databases regards to health clinical management. As a result, a list of 15 candidate papers has been elaborated and a peer-reviewed has been performed by external reviewers. A consensus meeting has been organized between the two section editors and the editorial board to conclude the selection of the 3 best papers.

RESULTS

Starting with 1803 papers published in 2015, the full selection process ended with three papers from international peer-reviewed journals for the Health and Clinical Management section.

CONCLUSION

IoT and Cloudification have a direct impact on health and clinical management this year. Telepsychiatry benefits directly from this development and take advantages of the improvement of smart homes and of the generalization of mHealth solutions. Social networks are starting to be integrated as valuable source of information that are complementary to clinical data for reasoning-based solutions.

Use of Text Searching for Trigger Words in Medical Records to Identify Adverse Drug Reactions within an Intensive Care Unit Discharge Summary

PURPOSE

To evaluate the performance of using trigger words (e.g. clues to an adverse drug reaction) in unstructured, narrative text to detect adverse drug reactions (ADRs) and compare the use of these trigger words to a targeted chart review for ADR detection within the intensive care unit (ICU) discharge summary note.

MATERIALS

A retrospective medical record review was conducted. Evaluation of ADRs occurred in two phases - targeted chart review of the ICU discharge summary notes in Phase 1 and targeted chart review using specific words and phrases as triggers for ADRs in Phase 2.

RESULTS

Four hundred ADRs were documented in 223 patients for Phase 1. For Phase 2, there were 219 ADRs identified in 120 patients. 138 real or accurate ADRs were identified from Phase 1 and 47 duplicate events. 34 ADRs from Phase 2 were not identified in Phase 1. Fifteen of the ADRs were inaccurately presumed in Phase 2. Fifty-eight of 127 text triggers identified at least one ADR. Low and moderate frequency trigger words were more likely to have PPVs > 5%.

CONCLUSIONS

Targeted chart review using specific words and phrases as triggers for ADRs is a reasonable approach to identify ADRs and may save time compared to other methods after further refinement leads to a more accurately performing trigger word list.

Usability Evaluation of a Clinical Decision Support System for Geriatric ED Pain Treatment

BACKGROUND

Older adults are at risk for inadequate emergency department (ED) pain care. Unrelieved acute pain is associated with poor outcomes. Clinical decision support systems (CDSS) hold promise to improve patient care, but CDSS quality varies widely, particularly when usability evaluation is not employed.

OBJECTIVE

To conduct an iterative usability and redesign process of a novel geriatric abdominal pain care CDSS. We hypothesized this process would result in the creation of more usable and favorable pain care interventions.

METHODS

Thirteen emergency physicians familiar with the Electronic Health Record (EHR) in use at the study site were recruited. Over a 10-week period, 17 1-hour usability test sessions were conducted across 3 rounds of testing. Participants were given 3 patient scenarios and provided simulated clinical care using the EHR, while interacting with the CDSS interventions. Quantitative System Usability Scores (SUS), favorability scores and qualitative narrative feedback were collected for each session. Using a multi-step review process by an interdisciplinary team, positive and negative usability issues in effectiveness, efficiency, and satisfaction were considered, prioritized and incorporated in the iterative redesign process of the CDSS. Video analysis was used to determine the appropriateness of the CDS appearances during simulated clinical care.

RESULTS

Over the 3 rounds of usability evaluations and subsequent redesign processes, mean SUS progressively improved from 74.8 to 81.2 to 88.9; mean favorability scores improved from 3.23 to 4.29 (1 worst, 5 best). Video analysis revealed that, in the course of the iterative redesign processes, rates of physicians' acknowledgment of CDS interventions increased, however most rates of desired actions by physicians (such as more frequent pain score updates) decreased.

CONCLUSION

The iterative usability redesign process was instrumental in improving the usability of the CDSS; if implemented in practice, it could improve geriatric pain care. The usability evaluation process led to improved acknowledgement and favorability. Incorporating usability testing when designing CDSS interventions for studies may be effective to enhance clinician use.

The Symbolic Functions of Nurses' Cognitive Artifacts on a Medical Oncology Unit

Acute care nurses continue to rely on personally created paper-based tools-their "paper brains"-to support work during a shift, although standardized handoff tools are recommended. This interpretive descriptive study examines the functions these paper brains serve beyond handoff in the medical oncology unit at a cancer specialty hospital. Thirteen medical oncology nurses were each shadowed for a single shift and interviewed afterward using a semistructured technique. Field notes, transcribed interviews, images of nurses' paper brains, and analytic memos were inductively coded, and analysis revealed paper brains are symbols of patient and nurse identity. Caution is necessary when attempting to standardize nurses' paper brains as nurses may be resistant to such changes due to their pride in constructing personal artifacts to support themselves and their patients.

Patients' Online Access to Their Primary Care Electronic Health Records and Linked Online Services: Implications for Research and Practice

Online access to medical records and linked services, including requesting repeat prescriptions and booking appointments, enables patients to personalize their access to care. However, online access creates opportunities and challenges for both health professionals and their patients, in practices and in research. The challenges for practice are the impact of online services on workload and the quality and safety of health care. Health professionals are concerned about the impact on workload, especially from email or other online enquiry systems, as well as risks to privacy. Patients report how online access provides a convenient means through which to access their health provider and may offer greater satisfaction if they get a timely response from a clinician. Online access and services may also result in unforeseen consequences and may change the nature of the patient-clinician interaction. Research challenges include: (1) Ensuring privacy, including how to control inappropriate carer and guardian access to medical records; (2) Whether online access to records improves patient safety and health outcomes; (3) Whether record access increases disparities across social classes and between genders; and (4) Improving efficiency. The challenges for practice are: (1) How to incorporate online access into clinical workflow; (2) The need for a business model to fund the additional time taken. Creating a sustainable business model for a safe, private, informative, more equitable online service is needed if online access to records is to be provided outside of pay-for-service systems.

A 2015 Medical Informatics Perspective on Health and Clinical Management: Will Cloud and Prioritization Solutions Be the Future of Health Data Management?

OBJECTIVES

Summarize current excellent research and trends in the field of Health and Clinical management.

METHODS

Synopsis of the articles selected for the IMIA Yearbook 2015 RESULTS: Three papers from international peer-reviewed journals have been selected for the Health and Clinical Management section.

CONCLUSION

Telemedicine is still very active in Health and clinical management, but the new tendencies on which we focus this year were firstly the introduction of cloud for health data management, with some specific security problems, and secondly an emerging expectation of prioritization tools in health care Management.

Learning from the crowd while mapping to LOINC

OBJECTIVE

To describe the perspectives of Regenstrief LOINC Mapping Assistant (RELMA) users before and after the deployment of Community Mapping features, characterize the usage of these new features, and analyze the quality of mappings submitted to the community mapping repository.

METHODS

We evaluated Logical Observation Identifiers Names and Codes (LOINC) community members' perceptions about new "wisdom of the crowd" information and how they used the new RELMA features. We conducted a pre-launch survey to capture users' perceptions of the proposed functionality of these new features; monitored how the new features and data available via those features were accessed; conducted a follow-up survey about the use of RELMA with the Community Mapping features; and analyzed community mappings using automated methods to detect potential errors.

RESULTS

Despite general satisfaction with RELMA, nearly 80% of 155 respondents to our pre-launch survey indicated that having information on how often other users had mapped to a particular LOINC term would be helpful. During the study period, 200 participants logged into the RELMA Community Mapping features an average of 610 times per month and viewed the mapping detail pages a total of 6686 times. Fifty respondents (25%) completed our post-launch survey, and those who accessed the Community Mapping features unanimously indicated that they were useful. Overall, 95.3% of the submitted mappings passed our automated validation checks.

CONCLUSION

When information about other institutions' mappings was made available, study participants who accessed it agreed that it was useful and informed their mapping choices. Our findings suggest that a crowd-sourced repository of mappings is valuable to users who are mapping local terms to LOINC terms.

Quality of care for OA: the effect of a point-of-care consultation recording template

Objective. The aims of this study were to determine the feasibility of introducing a computerized template for identifying quality of care during an OA consultation, describe quality of OA care in practices in which the template was introduced and assess the effect of the template on routinely recorded clinician behaviour in those practices.

Methods. A computerized template to assist the recording of care in consultations for patients with OA was installed in eight general practices. Eligible patients were those ≥45 years of age consulting for clinical OA during a 6 month period. The main outcomes were frequency of template triggering, achievement of quality indicators during the consultation (assessment of pain and function, assessment for first-line analgesics, provision of information, exercise advice, consideration of physiotherapy referral, weight loss advice) and change in routinely recorded clinician behaviour (diagnostic coding, prescribing, referral, use of radiography, weight records) compared with the 12 months prior to template installation.

Results. The template was triggered for 1730 patients. Achievement of indicators ranged from 36% (for consideration of physiotherapy referral) to 63% (for pain assessment), with substantial variability between clinicians. There was an increase in prescription of recommended first-line analgesics following the template installation: paracetamol [odds ratio (OR) 1.49 (95% CI 1.22, 1.82) compared with pre-template] and topical NSAIDs [OR 1.95 (95% CI 1.61, 2.35)].

Conclusion. This new template is a feasible tool for capturing data during OA consultations to aid assessment of quality of care. It was associated with significant improvements in recommended care processes. However, strategies are needed to ensure consistent approaches between clinicians.

Trial registration.http://www.controlled-trials.com/ISRCTN06984617/mosaics.

Trends on integrating framework of applications or data. Findings from the section on health and clinical management

OBJECTIVE

To summarize current excellent research and trends in the field of Health and Clinical management.

METHODS

Synopsis of the articles selected for the IMIA Yearbook 21014 RESULTS: A comprehensive review of papers published in 2013 was performed by querying PubMed. 1079 were reviewed as papers without authors, without abstract or smaller than 4 pages were excluded from the selection. The editors reviewed all papers and 15 papers selected and provided to to international reviewers. Four papers from international peer-reviewed journals were finally selected for the Health and Clinical Management section.

CONCLUSION

Many telemedicine applications are tested nowadays in medical situation, but the challenges emphasized by the best papers selection focus on the ability of proposing integrative frameworks for applications or data in order to handle efficiency of health and clinical management.

Big Data Usage Patterns in the Health Care Domain: A Use Case Driven Approach Applied to the Assessment of Vaccination Benefits and Risks. Contribution of the IMIA Primary Healthcare Working Group

BACKGROUND

Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive.

OBJECTIVE

To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines.

METHOD

We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars.

RESULTS

We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowdsourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the "internet of things", and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources.

CONCLUSIONS

Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.

Prevalence and epidemiology of diabetes in Canadian primary care practices: a report from the Canadian Primary Care Sentinel Surveillance Network

OBJECTIVE

The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is a large, validated national primary care Electronic Medical Records (EMR)-based database. Our objective was to describe the epidemiology of diabetes in this Canadian sample.

METHODS

We analyzed the records of 272 469 patients10 years of age and older, with at least 1 primary care clinical encounter between January 1, 2011, and December 31, 2012. We calculated the age-gender standardized prevalence of diabetes. We compared health care utilization and comorbidities for 7 selected chronic conditions in patients with and without diabetes. We also examined patterns of medication usage.

RESULTS

The estimated population prevalence of diabetes was 7.6%. Specifically, we studied 25 425 people with diabetes who had at least 1 primary care encounter in 2 years. On average, patients with diabetes had 1.42 times as many practice encounters as patients without diabetes (95% CI 1.42 to 1.43, p<0.0001). Patients with diabetes had 1.29 times as many other comorbid conditions as those without diabetes (95% CI 1.27 to 1.31, p<0.0001). We found that 85.2% of patients taking hypoglycemic medications were taking metformin, and 51.8% were taking 2 or more classes of medications.

CONCLUSIONS

This study is the first national Canadian report describing the epidemiology of diabetes using primary care EMR-based data. We found significantly higher rates of primary care use, and greater numbers of comorbidities in patients with diabetes. Most patients were on first-line hypoglycemic medications. Data routinely recorded in EMRs can be used for surveillance of chronic diseases such as diabetes in Canada. These results can enable comparisons with other national EMR-based datasets.

Enhancing continuity in care: an implemantation of the ASTM E2369-05 Standard Specification for Continuity of Care Record in a homecare application

Sharing of healthcare related information among the different healthcare providers is a crucial aspect for the continuity of the provided care The purpose of this study is the presentation of a system appropriate to be used upon the transition or the referral of a patient, and especially in transition from hospital to homecare. The function of the developed system is based upon the creation of a structured subset of data, concerning the most relevant facts about a patient's healthcare, organized and transportable, in order to be employed during the post-discharge homecare period, enabling simultaneously the planning and the optimal documentation of the provided homecare. The structure and the content of the created data sets are complying with the ASTM E2369-0 Standard, Specification for Continuity of Care Record.

Optimizing data analysis tools to support healthcare workers in Peru

Large healthcare projects in developing countries need to track data for clinical care, patient outcomes, medication supplies, and research. These heterogeneous information needs are compounded by the wide range of skills and experience of staff. We describe analysis tools designed to bridge these requirements in a tuberculosis (TB) treatment project in Peru.