Developing a pressure ulcer risk factor minimum data set and risk assessment framework

AIM: To agree a draft pressure ulcer risk factor Minimum Data Set to underpin the development of a new evidenced-based Risk Assessment Framework.BACKGROUND: A recent systematic review identified the need for a pressure ulcer risk factor Minimum Data Set and development and validation of an evidenced-based pressure ulcer Risk Assessment Framework. This was undertaken through the Pressure UlceR Programme Of reSEarch (RP-PG-0407-10056), funded by the National Institute for Health Research and incorporates five phases. This article reports phase two, a consensus study.DESIGN: Consensus study.METHOD: A modified nominal group technique based on the Research and Development/University of California at Los Angeles appropriateness method. This incorporated an expert group, review of the evidence and the views of a Patient and Public Involvement service user group. Data were collected December 2010-December 2011.FINDINGS: The risk factors and assessment items of the Minimum Data Set (including immobility, pressure ulcer and skin status, perfusion, diabetes, skin moisture, sensory perception and nutrition) were agreed. In addition, a draft Risk Assessment Framework incorporating all Minimum Data Set items was developed, comprising a two stage assessment process (screening and detailed full assessment) and decision pathways.CONCLUSION: The draft Risk Assessment Framework will undergo further design and pre-testing with clinical nurses to assess and improve its usability. It will then be evaluated in clinical practice to assess its validity and reliability. The Minimum Data Set could be used in future for large scale risk factor studies informing refinement of the Risk Assessment Framework

A machine learning approach for diagnostic and prognostic predictions, key risk factors and interactions

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.Machine learning (ML) has the potential to revolutionize healthcare, allowing healthcare providers to improve patient-care planning, resource planning and utilization. Furthermore, identifying key-risk-factors and interaction-effects can help service-providers and decision-makers to institute better policies and procedures. This study used COVID-19 electronic health record (EHR) data to predict five crucial outcomes: positive-test, ventilation, death, hospitalization days, and ICU days. Our models achieved high accuracy and precision, with AUC values of 91.6%, 99.1%, and 97.5% for the first three outcomes, and MAE of 0.752 and 0.257 days for the last two outcomes. We also identified interaction effects, such as high bicarbonate in arterial blood being associated with longer hospitalization in middle-aged patients. Our models are embedded in a prototype of an online decision support tool that can be used by healthcare providers to make more informed decisions. © The Author(s) 2024

Early Prediction of Alzheimers Disease Leveraging Symptom Occurrences from Longitudinal Electronic Health Records of US Military Veterans

Early prediction of Alzheimer's disease (AD) is crucial for timely intervention and treatment. This study aims to use machine learning approaches to analyze longitudinal electronic health records (EHRs) of patients with AD and identify signs and symptoms that can predict AD onset earlier. We used a case-control design with longitudinal EHRs from the U.S. Department of Veterans Affairs Veterans Health Administration (VHA) from 2004 to 2021. Cases were VHA patients with AD diagnosed after 1/1/2016 based on ICD-10-CM codes, matched 1:9 with controls by age, sex and clinical utilization with replacement. We used a panel of AD-related keywords and their occurrences over time in a patient's longitudinal EHRs as predictors for AD prediction with four machine learning models. We performed subgroup analyses by age, sex, and race/ethnicity, and validated the model in a hold-out and "unseen" VHA stations group. Model discrimination, calibration, and other relevant metrics were reported for predictions up to ten years before ICD-based diagnosis. The study population included 16,701 cases and 39,097 matched controls. The average number of AD-related keywords (e.g., "concentration", "speaking") per year increased rapidly for cases as diagnosis approached, from around 10 to over 40, while remaining flat at 10 for controls. The best model achieved high discriminative accuracy (ROCAUC 0.997) for predictions using data from at least ten years before ICD-based diagnoses. The model was well-calibrated (Hosmer-Lemeshow goodness-of-fit p-value = 0.99) and consistent across subgroups of age, sex and race/ethnicity, except for patients younger than 65 (ROCAUC 0.746). Machine learning models using AD-related keywords identified from EHR notes can predict future AD diagnoses, suggesting its potential use for identifying AD risk using EHR notes, offering an affordable way for early screening on large population.Comment: 24 page

PaniniQA: Enhancing Patient Education Through Interactive Question Answering

Patient portal allows discharged patients to access their personalized discharge instructions in electronic health records (EHRs). However, many patients have difficulty understanding or memorizing their discharge instructions. In this paper, we present PaniniQA, a patient-centric interactive question answering system designed to help patients understand their discharge instructions. PaniniQA first identifies important clinical content from patients' discharge instructions and then formulates patient-specific educational questions. In addition, PaniniQA is also equipped with answer verification functionality to provide timely feedback to correct patients' misunderstandings. Our comprehensive automatic and human evaluation results demonstrate our PaniniQA is capable of improving patients' mastery of their medical instructions through effective interactionsComment: Accepted to TACL 2023. Equal contribution for the first two authors. This arXiv version is a pre-MIT Press publication versio

Hypertension management in patients with diabetes. The need for more aggressive therapy

WSTĘP. W dużych badaniach klinicznych wykazano już potrzebę ścisłej kontroli ciśnienia tętniczego u chorych na cukrzycę. Jednak niewiele wiadomo o tym, jak w praktyce klinicznej realizowane są zasady leczenia nadciśnienia tętniczego współistniejącego z cukrzycą. W celu zbadania tego problemu postawiono pytania: 1) czy chorzy na cukrzycę osiągają niższe wartości ciśnienia tętniczego niż osoby bez współistniejącej cukrzycy; 2) czy istnieją różnice między intensywnością leczenia chorych na cukrzycę i chorych bez niej oraz 3) czy leczenie cukrzycy wpływa na podjęcie decyzji o bardziej intensywnym leczeniu nadciśnienia tętniczego. MATERIAŁ I METODY. W celu uzyskania szczegółów dotyczących postępowania w nadciśnieniu tętniczym zgromadzono dokumentację medyczną z 2-letniego okresu leczenia 800 mężczyzn, kombatantów, leczonych z powodu nadciśnienia tętniczego. Porównano intensywność leczenia i kontrolę ciśnienia tętniczego u chorych na cukrzycę i u osób bez niej. Intensywność leczenia oceniono na podstawie wcześniej stosowanej formuły opisującej prawdopodobieństwo wzrostu liczby stosowanych leków hipotensyjnych. Oceniano również, czy zwiększenie dawek leków przeciwnadciśnieniowych było mniej prawdopodobne w czasie wizyt, na których zmieniano leczenie hipoglikemizujące. WYNIKI. Z 247 chorych na nadciśnienie tętnicze i cukrzycę u 73% ciśnienie tętnicze przekraczało 140/90 mm Hg, w porównaniu z 66% osób z 526-osobowej grupy bez cukrzycy (p = 0,04). U osób chorych na cukrzycę stosowano również znamiennie (p = 0,05) mniej intensywne leczenie hipotensyjne niż u pacjentów bez tego schorzenia. Postępowania tego nie można tłumaczyć poświęceniem większej uwagi klinicystów leczeniu cukrzycy. WNIOSKI. Istnieje potrzeba szybkiej poprawy skuteczności leczenia i lepszej kontroli ciśnienia wśród chorych na cukrzycę z współistniejącym nadciśnieniem tętniczym. Konieczne są dodatkowe dane w celu zrozumienia mało agresywnej postawy klinicystów w leczeniu nadciśnienia tętniczego współistniejącego z cukrzycą.INTRODUCTION. Clinical trials have demonstrated the importance of tight blood pressure control among patients with diabetes. However, little is known regarding the management of hypertension in patients with coexisting diabetes. To examine this issue, we addressed 1) whether hypertensive patients with coexisting diabetes are achieving lower levels of blood pressure than patients without diabetes, 2) whether there are differences in the intensity of antihypertensive medication therapy provided to patients with and without diabetes, and 3) whether diabetes management affects decisions to increase antihypertensive medication therapy. MATERIAL AND METHODS. We abstracted medical records to collect detailed information on 2 years of care provided for 800 male veterans with hypertension. We compared patients with and without diabetes on intensity of therapy and blood pressure control. Intensity of therapy was described using a previously validated measure that captures the likelihood of an increase in antihypertensive medications. We also determined whether increases in antihypertensive medications were less likely at those visits in which the diabetes medications were being adjusted. RESULTS. Of the 274 hypertensive patients with diabetes, 73% had a blood pressure 140/90 mm Hg, compared with 66% in the 526 patients without diabetes (P = 0.04). Diabetic patients also received significantly (P = 0.05) less intensive antihypertensive medication therapy than patients without diabetes. Less intensive therapy in diabetic patients could not be explained by clinicians being distracted by the treatment for diabetes. CONCLUSIONS. There is an urgent need to improve hypertension care and blood pressure control in patients with diabetes. Additional information is required to understand why clinicians are not more aggressive in managing blood pressure when patients also have diabetes

Prevalence of Mild Cognitive Impairment and Alzheimers Disease Identified in Veterans in the United States.

BACKGROUND: Diagnostic codes can be instrumental for case identification in Alzheimers disease (AD) research; however, this method has known limitations and cannot distinguish between disease stages. Clinical notes may offer more detailed information including AD severity and can complement diagnostic codes for case identification. OBJECTIVE: To estimate prevalence of mild cognitive impairment (MCI) and AD using diagnostics codes and clinical notes available in the electronic healthcare record (EHR). METHODS: This was a retrospective study in the Veterans Affairs Healthcare System (VAHS). Health records from Veterans aged 65 years or older were reviewed during Fiscal Years (FY) 2010-2019. Overall, 274,736 and 469,569 Veterans were identified based on a rule-based algorithm as having at least one clinical note for MCI and AD, respectively; 201,211 and 149,779 Veterans had a diagnostic code for MCI and AD, respectively. During FY 2011-2018, likely MCI or AD diagnosis was defined by≥2 qualifiers (i.e., notes and/or codes)≥30 days apart. Veterans with only 1 qualifier were considered as suspected MCI/AD. RESULTS: Over the 8-year study, 147,106 and 207,225 Veterans had likely MCI and AD, respectively. From 2011 to 2018, yearly MCI prevalence increased from 0.9% to 2.2%; yearly AD prevalence slightly decreased from 2.4% to 2.1%; mild AD changed from 22.9% to 26.8%, moderate AD changed from 26.5% to 29.1%, and severe AD changed from 24.6% to 30.7. CONCLUSIONS: The relative distribution of AD severities was stable over time. Accurate prevalence estimation is critical for healthcare resource allocation and facilitating patients receiving innovative medicines

Association between mental health conditions and rehospitalization, mortality, and functional outcomes in patients with stroke following inpatient rehabilitation

<p>Abstract</p> <p>Background</p> <p>Limited evidence exists regarding the association of pre-existing mental health conditions in patients with stroke and stroke outcomes such as rehospitalization, mortality, and function. We examined the association between mental health conditions and rehospitalization, mortality, and functional outcomes in patients with stroke following inpatient rehabilitation.</p> <p>Methods</p> <p>Our observational study used the 2001 VA Integrated Stroke Outcomes database of 2162 patients with stroke who underwent rehabilitation at a Veterans Affairs Medical Center.</p> <p>Separate models were fit to our outcome measures that included 6-month rehospitalization or death, 6-month mortality post-discharge, and functional outcomes post inpatient rehabilitation as a function of number and type of mental health conditions. The models controlled for patient socio-demographics, length of stay, functional status, and rehabilitation setting.</p> <p>Results</p> <p>Patients had an average age of 68 years. Patients with stroke and two or more mental health conditions were more likely to be readmitted or die compared to patients with no conditions (OR: 1.44, p = 0.04). Depression and anxiety were associated with a greater likelihood of rehospitalization or death (OR: 1.33, p = 0.04; OR:1.47, p = 0.03). Patients with anxiety were more likely to die at six months (OR: 2.49, p = 0.001).</p> <p>Conclusions</p> <p>Patients with stroke with pre-existing mental health conditions may need additional psychotherapy interventions, which may potentially improve stroke outcomes post-hospitalization.</p

Risk of venous thromboembolism after total hip and knee replacement in older adults with comorbidity and co-occurring comorbidities in the Nationwide Inpatient Sample (2003-2006)

<p>Abstract</p> <p>Background</p> <p>Venous thromboembolism is a common, fatal, and costly injury which complicates major surgery in older adults. The American College of Chest Physicians recommends high potency prophylaxis regimens for individuals undergoing total hip or knee replacement (THR or TKR), but surgeons are reluctant to prescribe them due to fear of excess bleeding. Identifying a high risk cohort such as older adults with comorbidities and co-occurring comorbidities who might benefit most from high potency prophylaxis would improve how we currently perform preoperative assessment.</p> <p>Methods</p> <p>Using the Nationwide Inpatient Sample, we identified older adults who underwent THR or TKR in the U.S. between 2003 and 2006. Our outcome was VTE, including any pulmonary embolus or deep venous thrombosis. We performed multivariate logistic regression analyses to assess the effects of comorbidities on VTE occurrence. Comorbidities under consideration included coronary artery disease, congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), diabetes, and cerebrovascular disease. We also examined the impact of co-occurring comorbidities on VTE rates.</p> <p>Results</p> <p>CHF increased odds of VTE in both the THR cohort (OR = 3.08 95% CI 2.05-4.65) and TKR cohort (OR = 2.47 95% CI 1.95-3.14). COPD led to a 50% increase in odds in the TKR cohort (OR = 1.49 95% CI 1.31-1.70). The data did not support synergistic effect of co-occurring comorbidities with respect to VTE occurrence.</p> <p>Conclusions</p> <p>Older adults with CHF undergoing THR or TKR and with COPD undergoing TKR are at increased risk of VTE. If confirmed in other datasets, these older adults may benefit from higher potency prophylaxis.</p

Use of selected complementary and alternative medicine (CAM) treatments in veterans with cancer or chronic pain: a cross-sectional survey

BACKGROUND: Complementary and alternative medicine (CAM) is emerging as an important form of care in the United States. We sought to measure the prevalence of selected CAM use among veterans attending oncology and chronic pain clinics and to describe the characteristics of CAM use in this population. METHODS: The self-administered, mail-in survey included questions on demographics, health beliefs, medical problems and 6 common CAM treatments (herbs, dietary supplements, chiropractic care, massage therapy, acupuncture and homeopathy) use. We used the chi-square test to examine bivariate associations between our predictor variables and CAM use. RESULTS: Seventy-two patients (27.3%) reported CAM use within the past 12 months. CAM use was associated with more education (p = 0.02), higher income (p = 0.006), non-VA insurance (p = 0.003), additional care outside the VA (p = 0.01) and the belief that lifestyle contributes to illness (p = 0.015). The diagnosis of chronic pain versus cancer was not associated with differential CAM use (p = 0.15). Seventy-six percent of CAM non-users reported that they would use it if offered at the VA. CONCLUSION: Use of 6 common CAM treatments among these veterans is lower than among the general population, but still substantial. A large majority of veterans reported interest in using CAM modalities if they were offered at the VA. A national assessment of veteran interest in CAM may assist VA leaders to respond to patients' needs