Predicting survival in locally advanced gastric cancer using prognostic factors - neoadjuvant rectal score and downstaging depth score.

BACKGROUND: Clinical prediction models are needed to accurately predict the prognosis of patients with gastric cancer who have received neoadjuvant therapy and to determine the best treatment strategies. The aim of this study is to determine the role of two prognostic factors, the neoadjuvant rectal (NAR) score and the downstaging depth score (DDS), in predicting survival in patients with gastric cancer who received neoadjuvant therapy and underwent curative gastrectomy. METHODS: We reviewed the medical records of 129 patients who had been diagnosed with primary gastric cancer and underwent radical gastrectomy after receiving neoadjuvant therapy. We calculated the NAR score and DDS values for each patient and conducted a survival analysis to assess the accuracy of these prognostic factors in predicting overall survival. RESULTS: The median overall survival time of the patients was found to be 29 months. Patients with low NAR scores and high DDS had significantly longer overall survival. Univariate analyses based on clinical and laboratory characteristics showed that gender, surgery type, resection type, neural invasion, grade, adjuvant radiotherapy, lymphocyte level, carcinoembryonic antigen (CEA) level, NAR score, and DDS were associated with survival. Moreover, multivariate analyses showed that lymphocyte level, DDS, and NAR score were independent prognostic factors. CONCLUSION: In summary, our research indicates that NAR score and DDS may serve as useful prognostic markers for predicting overall survival in patients with locally advanced gastric cancer who receive neoadjuvant chemotherapy followed by curative surgery. Patients with high DDS and low NAR scores were found to have better prognoses.

Analysing Crime Scene Data, Medical Records and Forensic Information to Determine the Causes of Suicides.

OBJECTIVE:  To analyse crime scene data, medical records, and forensic information to unveil insights into the causes and traits of suicides. STUDY DESIGN:  Descriptive study. Place and Duration of the Study: Department of Family Medicine, Kayseri City Hospital, Kayseri, Turkiye, between January 2020 to December 2021. METHODOLOGY:  A suicide investigation team (doctor, social worker, psychologist) was created to study cases and conduct on-site psychological autopsies. Triggered by emergency calls, the team interviewed suicide victims' relatives using semi-structured questionnaires, gathering data on personal details, time, method, and potential motives. Medical records revealed psychiatric history and medication use, while national judicial systems were reviewed for legal records. RESULTS:  A total of 158 fatal suicides were studied. Males accounted for 73.4%, females 26.6%. The leading cause was psychiatric illness (43%), chiefly depression (39%). Suicide peaked in the fall, especially in September, mainly at 23:00-23:59. Home was the common site (58.9%), and hanging was the primary method (44.3%). Prior hospitalisation for suicide attempts was 7.5%. Criminal records were held by 16.4% (26 individuals). CONCLUSION:  The results support the idea that suicides have seasonal patterns and that there are temporal windows of increased risk for suicide. KEY WORDS:  Suicide reasons, Suicide time, Psychological autopsy, Seasonal and temporal patterns.

Application of virtual diagnosis and treatment combined with medical record teaching method in standardized training of general practitioner.

The aim of this study was to explore the effect of virtual diagnosis and treatment combined with the medical record teaching method in standardized training of general practitioners. Eighty students who had standardized general practice training, from March 2020 to March 2022, in the grassroots practice base of general practitioner training in the affiliated Hospital of our Medical College were retrospectively analyzed and divided into 2 groups according to the teaching method that they received. The differences in assessment scores, critical thinking, clinical thinking ability, learning autonomy ability, and classroom teaching effectiveness were compared, and the students' satisfaction with teaching was investigated. The scores of theoretical knowledge, skill operation, medical history collection, and case analysis in the study group were notably higher (P < .05). In the study group, scores in truth-seeking, openness to knowledge, analytical ability, systematic ability, self-confidence, curiosity, and cognitive maturity were significantly higher (P < .05). A notable improvement was observed in the study group's scores on systematic thinking ability and evidence-based thinking ability, as well as the scores on critical thinking ability after teaching (P < .05). The scores of learning interest, self-management, plan implementation, and cooperation ability improved notably after teaching (P < .05). Learning target, learning processes, learning effects, classroom environment construction, teaching strategy, and technology application in the study group were significantly higher than those in the control group (P < .05). The satisfaction rate in the study group was significantly higher than that in the control group (P < .05). Virtual diagnosis and treatment combined with case-based learning teaching has a very good effect in the standardized training of general practitioners. Students are generally satisfied with their learning experience, which can improve their critical thinking ability and clinical thinking skills. This teaching method is worth further popularizing.

Pruritus in primary biliary cholangitis is under-recorded in patient medical records.

OBJECTIVE: Cholestatic pruritus in primary biliary cholangitis (PBC) reduces patients' health-related quality of life (HRQoL). Despite this, existing research suggests that pruritus is under-recorded in patients' health records. This study assessed the extent to which pruritus was recorded in medical records of patients with PBC as compared with patient-reported pruritus, and whether patients reporting mild itch were less likely to have pruritus recorded. We also evaluated clinico-demographic characteristics and HRQoL of patients with medical record-documented and patient-reported pruritus. DESIGN: This cross-sectional study used clinical information abstracted from medical records, together with patient-reported (PBC-40) data from patients with PBC in the USA enrolled in the PicnicHealth cohort. Medical record-documented pruritus was classified as 'recent' (at, or within 12 months prior to, enrolment) or 'ever' (at, or any point prior to, enrolment). Patient-reported pruritus (4-week recall) was assessed using the first PBC-40 questionnaire completed on/after enrolment; pruritus severity was classified by itch domain score (any severity: ≥1; clinically significant itch: ≥7). Patient clinico-demographic characteristics and PBC-40 domain scores were described in patients with medical record-documented and patient-reported pruritus; overlap between groups was evaluated. Descriptive statistics were reported. RESULTS: Pruritus of any severity was self-reported by 200/225 (88.9%) patients enrolled; however, only 88/225 (39.1%) had recent medical record-documented pruritus. Clinically significant pruritus was self-reported by 120/225 (53.3%) patients; of these, 64/120 (53.3%) had recent medical record-documented pruritus. Patients reporting clinically significant pruritus appeared to have higher mean scores across PBC-40 domains (indicating reduced HRQoL), versus patients with no/mild patient-reported pruritus or medical-record documented pruritus. CONCLUSION: Compared with patient-reported measures, pruritus in PBC is under-recorded in medical records and is associated with lower HRQoL. Research based only on medical records underestimates the true burden of pruritus, meaning physicians may be unaware of the extent and impact of pruritus, leading to potential undertreatment.

Improving medical record completeness at Wallaga University Referral Hospital: a multidimensional quality improvement project.

BACKGROUND: Appropriately documented medical records enhance coordination, patient outcomes and clinical research. OBJECTIVE: The aim of this project was to improve Wallaga University Referral Hospital's (WURH) medical record completeness rate from 53% to 80% from 1 January 2023 to 31 August 2023. METHODS: A hospital-based interventional study was conducted at WURH. The Plan-Do-Study-Act cycle was used to test change ideas. A fishbone diagram and a driver diagram were used to identify root causes and address them. Key interventions consisted of supportive supervision, developing and distributing standardised formats, orientation for staff, establishing a chart audit team and assigning data owners. RESULT: On the completion of the project, the overall implementation of inpatient medical record completeness increased from 53% to 82%. This improvement varies from department-to-department. It increased from 51% to 79%, 53% to 79%, 46% to 81% and 64% to 91% in the departments of internal medicine, paediatrics, obstetrics and gynaecology and surgery, respectively. The project brought improvements in the completeness of physician notes (84% to 100%), physician order sheet (54% to 84%), nursing care plan (26% to 69%), admission sheet (76% to 98%), discharge summary (94% to 98%), progress note (38% to 91%), medication administration (80% to 100%), appropriate attachment of documents (78% to 93%) and documentation of vital signs (50% to 100%). CONCLUSION AND RECOMMENDATION: The rate of medical record completeness was significantly improved in the study area. This was achieved through the application of multidimensional change ideas related to health professionals, supplies, health management information systems and leadership. However, in some of the parameters, the national targets were not met. Therefore, we recommend providing regular technical updates, conducting frequent chart audits and providing supportive supervision for the enhancement of medical record completeness. It is also advisable for the hospital management to work on its sustainability.

Glass box machine learning for retrospective cohort studies using many patient records. The complex example of bleeding peptic ulcer.

Glass Box Machine Learning is, in this study, a type of partially supervised data mining and prediction technique, like a neural network in which each weight or pattern of mutually relevant weights is now replaced by a meaningful "probabilistic knowledge element." We apply it to retrospective cohort studies using large numbers of structured medical records to help select candidate patients for future cohort studies and similar clinical trials. Here it is applied to aid analysis of approaches to aid Deep Learning, but the method lends itself well to direct computation of odds with "explainability" in study design that can complement "Black Box" Deep Learning. Cohort studies and clinical trials traditionally involved at least one 2 × 2 contingency table, but in the age of emerging personalized medicine and the use of machine learning to discover and incorporate further relevant factors, these tables can extend into many extra dimensions as a 2 × 2 x 2 × 2 x ….data structure by considering different conditional demographic and clinical factors of a patient or group, as well as variations in treatment. We consider this in terms of multiple 2 × 2 x 2 data substructures where each one is summarized by an appropriate measure of risk and success called DOR*. This is the diagnostic odds ratio DOR for a specified disease conditional on a favorable outcome divided by the corresponding DOR conditional on an unfavorable outcome. Bleeding peptic ulcer was chosen as a complex disease with many influencing factors, one that is still subject to controversy and that highlights the challenges of using Real World Data.

The Environmental Impacts of Electronic Medical Records Versus Paper Records at a Large Eye Hospital in India: Life Cycle Assessment Study.

BACKGROUND: Health care providers worldwide are rapidly adopting electronic medical record (EMR) systems, replacing paper record-keeping systems. Despite numerous benefits to EMRs, the environmental emissions associated with medical record-keeping are unknown. Given the need for urgent climate action, understanding the carbon footprint of EMRs will assist in decarbonizing their adoption and use. OBJECTIVE: We aimed to estimate and compare the environmental emissions associated with paper medical record-keeping and its replacement EMR system at a high-volume eye care facility in southern India. METHODS: We conducted the life cycle assessment methodology per the ISO (International Organization for Standardization) 14040 standard, with primary data supplied by the eye care facility. Data on the paper record-keeping system include the production, use, and disposal of paper and writing utensils in 2016. The EMR system was adopted at this location in 2018. Data on the EMR system include the allocated production and disposal of capital equipment (such as computers and routers); the production, use, and disposal of consumable goods like paper and writing utensils; and the electricity required to run the EMR system. We excluded built infrastructure and cooling loads (eg. buildings and ventilation) from both systems. We used sensitivity analyses to model the effects of practice variation and data uncertainty and Monte Carlo assessments to statistically compare the 2 systems, with and without renewable electricity sources. RESULTS: This location's EMR system was found to emit substantially more greenhouse gases (GHGs) than their paper medical record system (195,000 kg carbon dioxide equivalents [CO2e] per year or 0.361 kg CO2e per patient visit compared with 20,800 kg CO2e per year or 0.037 kg CO2e per patient). However, sensitivity analyses show that the effect of electricity sources is a major factor in determining which record-keeping system emits fewer GHGs. If the study hospital sourced all electricity from renewable sources such as solar or wind power rather than the Indian electric grid, their EMR emissions would drop to 24,900 kg CO2e (0.046 kg CO2e per patient), a level comparable to the paper record-keeping system. Energy-efficient EMR equipment (such as computers and monitors) is the next largest factor impacting emissions, followed by equipment life spans. Multimedia Appendix 1 includes other emissions impact categories. CONCLUSIONS: The climate-changing emissions associated with an EMR system are heavily dependent on the sources of electricity. With a decarbonized electricity source, the EMR system's GHG emissions are on par with paper medical record-keeping, and decarbonized grids would likely have a much broader benefit to society. Though we found that the EMR system produced more emissions than a paper record-keeping system, this study does not account for potential expanded environmental gains from EMRs, including expanding access to care while reducing patient travel and operational efficiencies that can reduce unnecessary or redundant care.

[The quality of dental care in children with permanent teeth trauma according to analysis of medical records in an emergency unit of a municipal dental clinic]. / Kachestvo okazaniya neotlozhnoi pomoshchi detyam s travmami postoyannykh zubov po dannym analiza dokumentatsii otdeleniya neotlozhnoi pomoshchi gorodskoi stomatologicheskoi polikliniki.

THE AIM OF THE STUDY: Was to assess the efficacy and timing of emergency dental care in children with permanent teeth trauma according to analysis of medical records in an emergency unit of a municipal dental clinic. MATERIAL AND METHODS: The study involved 320 medical records of pediatric patients admitted to emergency dental care unit of a municipal dental clinic in 2021 because of maxillofacial trauma from which 221 records of children with acute dental trauma were extracted. The quality of documentation of the medical records, rationale for diagnosis and adequacy of emergency dental treatment were analyzed. RESULTS: No records included diagnosis code according to ICD-10. Trauma history was described in the majority of records by in 67% of them no trauma time was stated with proper precision. In 67.6% of permanent teeth trauma cases emergency aid was carried out inadequately. All patients with uncomplicated crown fractures were dismissed with no treatment. In complicated crown fractures needing pulp vitality preservation the pulp was devitalized or just anesthetized. Tooth replantation in avulsion cases was not performed. In 13.5% of records the treatment was not properly described. In 67.6% of records there were no recommendations for follow-ups. CONCLUSION: There is a strong need for the improvement of knowledge of traumatic dental injuries management among Russian pediatric dentists by elaboration and implementation of protocols for dental traumas treatment.

Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan.

BACKGROUND: Efficiently identifying patients with human immunodeficiency virus (HIV) using administrative health care data (e.g., claims) can facilitate research on their quality of care and health outcomes. No prior study has validated the use of only ICD-10-CM HIV diagnosis codes to identify patients with HIV. METHODS: We validated HIV diagnosis codes among women enrolled in a large U.S. integrated health care system during 2010-2020. We examined HIV diagnosis code-based algorithms that varied by type, frequency, and timing of the codes in patients' claims data. We calculated the positive predictive values (PPVs) and 95% confidence intervals (CIs) of the algorithms using a medical record-confirmed diagnosis of HIV as the gold standard. RESULTS: A total of 272 women with ≥ 1 HIV diagnosis code in the administrative claims data were identified and medical records were reviewed for all 272 women. The PPV of an algorithm classifying women as having HIV as of the first HIV diagnosis code during the observation period was 80.5% (95% CI: 75.4-84.8%), and it was 93.9% (95% CI: 90.0-96.3%) as of the second. Little additional increase in PPV was observed when a third code was required. The PPV of an algorithm based on ICD-10-CM-era codes was similar to one based on ICD-9-CM-era codes. CONCLUSION: If the accuracy measure of greatest interest is PPV, our findings suggest that use of ≥ 2 HIV diagnosis codes to identify patients with HIV may perform well. However, health care coding practices may vary across settings, which may impact generalizability of our results.

Accounting for informative observation process in transition models of binary longitudinal outcome: Application to medical record data.

When extracting medical record data to form a retrospective cohort, investigators typically focus on a pre-specified study window, and select subjects who had hospital visits during that study window. However, such data extraction may suffer from an informative observation process, since sicker patients may have hospital visits more frequently. For example, Consecutive Pregnancy Study is a retrospective cohort study of women with multiple pregnancies in 23 Utah hospitals from 2003 to 2010, where the interest is to understand the risk factors of recurrent pregnancy outcomes, such as preterm birth. The observation process is informative in the sense that, women with adverse pregnancy outcomes may be less likely/willing/able to endure subsequent pregnancies. We proposed a three-part joint model with shared random effects structure to address this analytic complication. Particularly, a first-order transition model is used to model the longitudinal binary outcome; a gamma regression model is assumed for the inter-pregnancy intervals; a continuation ratio model specifies the probability of continuing with more births in the future. We note that the latter two parts give rise to a parametric cure-rate survival model. The performance of the proposed method was examined in extensive simulation studies, with both correctly and mis-specified models. The analyses of Consecutive Pregnancy Study data further demonstrate the inadequacies of fitting the transition model alone ignoring the informative observation process.

Outcomes of ultraminipercutaneous nephrolithotomy in infants: our experiences at a single center in an endemic region.

OBJECTIVE: In this study, we aimed to contribute to the literature by sharing the perioperative and postoperative outcomes of infants (0-24 months) who underwent ultra-mini percutaneous nephrolithotomy (PNL) for kidney stones in our clinic. METHODS: Infants under 24 months old with kidney stones of 2 cm and larger, who applied to our clinic between January 2018 and May 2023, were included in the study. The patients' demographic and clinical characteristics were obtained from the medical records. The collected data were analyzed retrospectively. RESULTS: A total of 26 patients were included in the study. The mean age of the patients was 17.3 ± 3.90 (12-24) months. The mean operation time was 50.7 ± 6.43 min. The mean stone size was 2.66 ± 0.59 cm. Stone-free was achieved in 23 patients (88.5%). In one patient (3.8%) with residual fragments, SWL was performed, and in two patients (7.7%), RIRS was performed to achieve stone-free. Postoperatively, fever was observed in 3 patients (11.5%). There were no patients requiring blood transfusion. CONCLUSIONS: In experienced centers, ultra-mini-PNL performed by experienced surgeons is an effective and reliable treatment option for infants under 24 months of age with kidney stones larger than 2 cm. It provides high-stone clearance rates and low complication rates.

Experience with a hybrid recruitment approach of patient-facing web portal screening and subsequent phone and medical record review for a neurosurgical intervention trial for chronic ischemic stroke disability (PISCES III).

BACKGROUND: Recruitment of participants is the greatest risk to completion of most clinical trials, with 20-40% of trials failing to reach the targeted enrollment. This is particularly true of trials of central nervous system (CNS) therapies such as intervention for chronic stroke. The PISCES III trial was an invasive trial of stereotactically guided intracerebral injection of CTX0E03, a fetal derived neural stem cell line, in patients with chronic disability due to ischemic stroke. We report on the experience using a novel hybrid recruitment approach of a patient-facing portal to self-identify and perform an initial screen for general trial eligibility (tier 1), followed by phone screening and medical records review (tier 2) prior to a final in-person visit to confirm eligibility and consent. METHODS: Two tiers of screening were established: an initial screen of general eligibility using a patient-facing web portal (tier 1), followed by a more detailed screen that included phone survey and medical record review (tier 2). If potential participants passed the tier 2 screen, they were referred directly to visit 1 at a study site, where final in-person screening and consent were performed. Rates of screening were tracked during the period of trial recruitment and sources of referrals were noted. RESULTS: The approach to screening and recruitment resulted in 6125 tier 1 screens, leading to 1121 referrals to tier 2. The tier 2 screening resulted in 224 medical record requests and identification of 86 qualifying participants for referral to sites. The study attained a viable recruitment rate of 6 enrolled per month prior to being disrupted by COVID 19. CONCLUSIONS: A tiered approach to eligibility screening using a hybrid of web-based portals to self-identify and screen for general eligibility followed by a more detailed phone and medical record review allowed the study to use fewer sites and reduce cost. Despite the difficult and narrow population of patients suffering moderate chronic disability from stroke, this strategy produced a viable recruitment rate for this invasive study of intracranially injected neural stem cells. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03629275.

Delirium is frequently underdiagnosed among older hospitalised patients despite available information in hospital medical records.

BACKGROUND: In-hospital delirium is associated with adverse outcomes and is underdiagnosed, limiting research and clinical follow-up. OBJECTIVE: To compare the incidence of in-hospital delirium determined by chart-based review of electronic medical records (D-CBR) with delirium discharge diagnoses (D-DD). Furthermore, to identify differences in symptoms, treatments and delirium triggers between D-CBR and D-DD. METHOD: The community-based cohort included 2,115 participants in the Hordaland Health Study born between 1925 and 1927. Between 2018 and 2022, we retrospectively reviewed hospital electronic medical records from baseline (1997-99) until death prior to 2023. D-DD and D-CBR were validated using The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria for delirium. RESULTS: Of the 2,115 participants, 638 had in-hospital delirium. The incidence rate (IR) of D-CBR was 29.8 [95% confidence interval 28, 32] per 1,000 person-years, whereas the IR by D-DD was 3.4 [2.8, 4.2]. The IR ratio was 9.14 (P < 0.001). Patients who received pharmacological treatment for delirium (n = 121, odds ratio (OR) 3.4, [2.1, 5.4], P < 0.001), who were affected by acute memory impairment (n = 149, OR 2.8, [1.8, 4.5], P < 0.001), or change in perception (n = 137, OR 2.9, [1.8, 4.6] P < 0.001) had higher odds for D-DD. In contrast, post-operative cases (OR 0.2, [0.1, 0.4], P < 0.001) had lower odds for D-DD. CONCLUSION: Underdiagnosis of in-hospital delirium was a major issue in our study, especially in less severe delirium cases. Our findings emphasise the need for integrating systematic delirium diagnostics and documentation into hospital admission and discharge routines.

AI-Generated Clinical Summaries Require More Than Accuracy.

This Viewpoint discusses AI-generated clinical summaries and the necessity of transparent development of standards for their safe rollout.

Applications of artificial intelligence in the field of oral and maxillofacial pathology: a systematic review and meta-analysis.

BACKGROUND: Since AI algorithms can analyze patient data, medical records, and imaging results to suggest treatment plans and predict outcomes, they have the potential to support pathologists and clinicians in the diagnosis and treatment of oral and maxillofacial pathologies, just like every other area of life in which it is being used. The goal of the current study was to examine all of the trends being investigated in the area of oral and maxillofacial pathology where AI has been possibly involved in helping practitioners. METHODS: We started by defining the important terms in our investigation's subject matter. Following that, relevant databases like PubMed, Scopus, and Web of Science were searched using keywords and synonyms for each concept, such as "machine learning," "diagnosis," "treatment planning," "image analysis," "predictive modelling," and "patient monitoring." For more papers and sources, Google Scholar was also used. RESULTS: The majority of the 9 studies that were chosen were on how AI can be utilized to diagnose malignant tumors of the oral cavity. AI was especially helpful in creating prediction models that aided pathologists and clinicians in foreseeing the development of oral and maxillofacial pathology in specific patients. Additionally, predictive models accurately identified patients who have a high risk of developing oral cancer as well as the likelihood of the disease returning after treatment. CONCLUSIONS: In the field of oral and maxillofacial pathology, AI has the potential to enhance diagnostic precision, personalize care, and ultimately improve patient outcomes. The development and application of AI in healthcare, however, necessitates careful consideration of ethical, legal, and regulatory challenges. Additionally, because AI is still a relatively new technology, caution must be taken when applying it to this industry.

The Scottish Medical Imaging Archive: 57.3 Million Radiology Studies Linked to Their Medical Records.

Keywords: MRI, Imaging Sequences, Ultrasound, Mammography, CT, Angiography, Conventional Radiography Published under a CC BY 4.0 license. See also the commentary by Whitman and Vining in this issue.

The impact of hospitalization on mortality in patients with connective tissue disease-associated interstitial lung disease: a medical records review study.

BACKGROUND: Interstitial lung disease (ILD) remains one of the most important causes of morbidity and mortality in patients with Connective Tissue Diseases (CTD). This study evaluated the impact of hospitalization on mortality in an ethnically and racially diverse cohort of CTD-ILD patients. METHODS: We conducted a medical records review study at Montefiore Medical Center, Bronx, NY. We included 96 patients and collected data on demographic characteristics, reasons for hospitalization, length of stay, immunosuppressant therapy use, and mortality. We stratified our patients into two cohorts: hospitalized and non-hospitalized. The hospitalized cohort was further subdivided into cardiopulmonary and non-cardiopulmonary admissions. Two-sample tests or Wilcoxon's rank sum tests for continuous variables and Chi-square or Fisher's exact tests for categorical variables were used for analyses as deemed appropriate. RESULTS: We identified 213 patients with CTD-ILD. Out of them, 96 patients met the study's inclusion criteria. The majority of patients were females (79%), and self-identified as Hispanic (54%) and Black (40%). The most common CTDs were rheumatoid arthritis (RA) (29%), inflammatory myositis (22%), and systemic sclerosis (15%). The majority (76%) of patients required at least one hospitalization. In the non-hospitalized group, no deaths were observed, however we noted significant increase of mortality risk in hospitalized group (p = 0.02). We also observed that prolonged hospital stay (> 7 days) as well as older age and male sex were associated with increased mortality. CONCLUSIONS: Prolonged (> 7 days) hospital stay and hospitalization for cardiopulmonary causes, as well as older age and male sex were associated with an increased mortality risk in our cohort of CTD-ILD patients.

Novel linkage approach to join community-acquired and national data.

BACKGROUND: Community optometrists in Scotland have performed regular free-at-point-of-care eye examinations for all, for over 15 years. Eye examinations include retinal imaging but image storage is fragmented and they are not used for research. The Scottish Collaborative Optometry-Ophthalmology Network e-research project aimed to collect these images and create a repository linked to routinely collected healthcare data, supporting the development of pre-symptomatic diagnostic tools. METHODS: As the image record was usually separate from the patient record and contained minimal patient information, we developed an efficient matching algorithm using a combination of deterministic and probabilistic steps which minimised the risk of false positives, to facilitate national health record linkage. We visited two practices and assessed the data contained in their image device and Practice Management Systems. Practice activities were explored to understand the context of data collection processes. Iteratively, we tested a series of matching rules which captured a high proportion of true positive records compared to manual matches. The approach was validated by testing manual matching against automated steps in three further practices. RESULTS: A sequence of deterministic rules successfully matched 95% of records in the three test practices compared to manual matching. Adding two probabilistic rules to the algorithm successfully matched 99% of records. CONCLUSIONS: The potential value of community-acquired retinal images can be harnessed only if they are linked to centrally-held healthcare care data. Despite the lack of interoperability between systems within optometry practices and inconsistent use of unique identifiers, data linkage is possible using robust, almost entirely automated processes.