scholarly journals Digitization of Measurement Based Care Pathways in Mental Health through REDCap and Electronic Health Record Integration (Preprint)

2020 ◽  
Author(s):  
Steve Hawley ◽  
David Rotenberg ◽  
Joanna Yu ◽  
Nikola Bogetic ◽  
Natalia Potapova ◽  
...  
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Data Quality ◽  
Real Time ◽  
Fold Increase ◽  
Self Report ◽  
Care Pathways ◽  
Health Record ◽  
Measurement Based Care ◽  
Clinician Attitudes

BACKGROUND The delivery of standardized self-report assessments is essential for measurement-based care (MBC) in mental health. Paper-based methods of MBC data collection may result in transcription errors, missing data, and other data quality issues when entered into the patient electronic health record (EHR). OBJECTIVE To address these issues, a dedicated instance of REDCap, a free, widely used electronic data capture platform, was established to enable the deployment of digitized self-assessments in clinical care pathways to inform clinical decision making. METHODS REDCap was integrated with the primary clinical information system to facilitate real-time transfer of discrete data and descriptive reports from REDCap into the EHR. Both technical and administrative components were required for complete implementation. A technology acceptance survey was also administered to capture physician and clinician attitudes towards the new system. RESULTS Integration of REDCap with the EHR transitioned clinical workflows from paper-based to electronic data collection. This resulted in significant time-savings, improved data quality and valuable real-time information delivery. Digitization of self-report assessments at each appointment contributed to clinic-wide implementation of the Major Depressive Disorder Integrated Care Pathway (MDD-ICP). This digital transformation facilitated a 4-fold increase in physician adoption of this ICP workflow and a 3-fold increase in patient enrollment resulting in an overall significant increase in MDD-ICP capacity. Physician and Clinician attitudes were overall positive with almost all respondents agreeing that the system was useful to their work. CONCLUSIONS REDCap provided an intuitive patient interface for collection of self-report measures, real-time access to results to inform clinical decisions, and an extensible backend for systems integration. The approach scaled effectively and expanded to high-impact clinics throughout the hospital, allowing for broad deployment of complex workflows and standardized assessments leading to accumulation of harmonized data across clinics and care pathways. REDCap is a flexible tool that can be effectively leveraged to facilitate automatic transfer of self-report data to the EHR. However, thoughtful governance is required to complement the technical implementation to ensure that data standardization, data quality, patient safety, and privacy are maintained.

Prevalence of Self-Reported Depression Symptoms and Perceived Anxiety Among Community-Dwelling U.S. Adults Reporting Tinnitus

2020 ◽  
Vol 5 (4) ◽  
pp. 959-970
Author(s):  
Kelly M. Reavis ◽  
James A. Henry ◽  
Lynn M. Marshall ◽  
Kathleen F. Carlson
Keyword(s):  
Mental Health ◽  
Fold Increase ◽  
Community Dwelling ◽  
Self Report ◽  
Depression Symptoms ◽  
Community Based Interventions ◽  
Data Set ◽  
Health Distress ◽  
Validated Questionnaire ◽  
Mental Health Distress

Purpose The aim of this study was to examine the relationship between tinnitus and self-reported mental health distress, namely, depression symptoms and perceived anxiety, in adults who participated in the National Health and Nutrition Examinations Survey between 2009 and 2012. A secondary aim was to determine if a history of serving in the military modified the associations between tinnitus and mental health distress. Method This was a cross-sectional study design of a national data set that included 5,550 U.S. community-dwelling adults ages 20 years and older, 12.7% of whom were military Veterans. Bivariable and multivariable logistic regression was used to estimate the association between tinnitus and mental health distress. All measures were based on self-report. Tinnitus and perceived anxiety were each assessed using a single question. Depression symptoms were assessed using the Patient Health Questionnaire, a validated questionnaire. Multivariable regression models were adjusted for key demographic and health factors, including self-reported hearing ability. Results Prevalence of tinnitus was 15%. Compared to adults without tinnitus, adults with tinnitus had a 1.8-fold increase in depression symptoms and a 1.5-fold increase in perceived anxiety after adjusting for potential confounders. Military Veteran status did not modify these observed associations. Conclusions Findings revealed an association between tinnitus and both depression symptoms and perceived anxiety, independent of potential confounders, among both Veterans and non-Veterans. These results suggest, on a population level, that individuals with tinnitus have a greater burden of perceived mental health distress and may benefit from interdisciplinary health care, self-help, and community-based interventions. Supplemental Material https://doi.org/10.23641/asha.12568475

Protocol for Remote Assessment of Lung Disease and Impact on Physical and Mental Health (RALPMH) (Preprint)

2021 ◽  
Author(s):  
Yatharth Ranjan ◽  
Malik Althobiani ◽  
Joseph Jacob ◽  
Michele Orini ◽  
Richard Dobson ◽  
...  
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Real Time ◽  
Remote Monitoring ◽  
Wearable Devices ◽  
Physical And Mental Health ◽  
Disease Trajectory ◽  
Passive Data ◽  
Active Data ◽  
Finger Pulse

BACKGROUND Chronic Lung disorders like COPD and IPF are characterised by exacerbations which are a significant problem: unpleasant for patients, and sometimes severe enough to cause hospital admission (and therefore NHS pressures) and death. Reducing the impact of exacerbations is very important. Moreover, due to the COVID-19 pandemic, the vulnerable populations with these disorders are at high risk and hence their routine care cannot be done properly. Remote monitoring offers a low cost and safe solution of gaining visibility into the health of people in their daily life. Thus, remote monitoring of patients in their daily lives using mobile and wearable devices could be useful especially in high vulnerability groups. A scenario we consider here is to monitor patients and detect disease exacerbation and progression and investigate the opportunity of detecting exacerbations in real-time with a future goal of real-time intervention. OBJECTIVE The primary objective is to assess the feasibility and acceptability of remote monitoring using wearable and mobile phones in patients with pulmonary diseases. The aims will be evaluated over these areas: Participant acceptability, drop-out rates and interpretation of data, Detection of clinically important events such as exacerbations and disease progression, Quantification of symptoms (physical and mental health), Impact of disease on mood and wellbeing/QoL and The trajectory-tracking of main outcome variables, symptom fluctuations and order. The secondary objective of this study is to provide power calculations for a larger longitudinal follow-up study. METHODS Participants will be recruited from 2 NHS sites in 3 different cohorts - COPD, IPF and Post hospitalised Covid. A total of 60 participants will be recruited, 20 in each cohort. Data collection will be done remotely using the RADAR-Base mHealth platform for different devices - Garmin wearable devices, smart spirometers, mobile app questionnaires, surveys and finger pulse oximeters. Passive data collected includes wearable derived continuous heart rate, SpO2, respiration rate, activity, and sleep. Active data collected includes disease-specific PROMs, mental health questionnaires and symptoms tracking to track disease trajectory in addition to speech sampling, spirometry and finger Pulse Oximetry. Analyses are intended to assess the feasibility of RADAR-Base for lung disorder remote monitoring (include quality of data, a cross-section of passive and active data, data completeness, the usability of the system, acceptability of the system). Where adequate data is collected, we will attempt to explore disease trajectory, patient stratification and identification of acute clinically interesting events such as exacerbations. A key part of this study is understanding the potential of real-time data collection, here we will simulate an intervention using the Exacerbation Rating Scale (ERS) to acquire responses at-time-of-event to assess the performance of a model for exacerbation identification from passive data collected. RESULTS RALPMH study provides a unique opportunity to assess the use of remote monitoring in the study of lung disorders. The study is set to be started in mid-May 2021. The data collection apparatus, questionnaires and wearable integrations have been set up and tested by clinical teams. While waiting for ethics approval, real-time detection models are currently being constructed. CONCLUSIONS RALPMH will provide a reference infrastructure for the use of wearable data for monitoring lung diseases. Specifically information regarding the feasibility and acceptability of remote monitoring and the potential of real-time remote data collection and analysis in the context of chronic lung disorders. Moreover, it provides a unique standpoint to look into the specifics of novel coronavirus without burdensome interventions. It will help plan and inform decisions in any future studies that make use of remote monitoring in the area of Respiratory health. CLINICALTRIAL https://www.isrctn.com/ISRCTN16275601

scholarly journals Information for mental health systems: an instrument for policy-making and system service quality

2016 ◽  
Vol 26 (4) ◽  
pp. 383-394 ◽  
Author(s):  
A. Lora ◽  
A. Lesage ◽  
S. Pathare ◽  
I. Levav
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Human Rights ◽  
Information Systems ◽  
Data Collection ◽  
Health Services ◽  
Service Quality ◽  
Data Quality ◽  
System Level ◽  
Low Middle Income Countries

Aims.Information is crucial in mental healthcare, yet it remains undervalued by stakeholders. Its absence undermines rationality in planning, makes it difficult to monitor service quality improvement, impedes accountability and human rights monitoring. For international organizations (e.g., WHO, OECD), information is indispensable for achieving better outcomes in mental health policies, services and programs. This article reviews the importance of developing system level information with reference to inputs, processes and outputs, analyzes available tools for collecting and summarizing information, highlights the various goals of information gathering, discusses implementation issues and charts the way forward.Methods.Relevant publications and research were consulted, including WHO studies that purport to promote the use of information systems to upgrade mental health care in high- and low-middle income countries.Results.Studies have shown that once information has been collected by relevant systems and analyzed through indicator schemes, it can be put to many uses. Monitoring mental health services, represents a first step in using information. In addition, studies have noted that information is a prime resource in many other areas such as evaluation of quality of care against evidence based standards of care. Services data may support health services research where it is possible to link mental health data with other health and non-health databases. Information systems are required to carefully monitor involuntary admissions, restrain and seclusion, to reduce human rights violations in care facilities. Information has been also found useful for policy makers, to monitor the implementation of policies, to evaluate their impact, to rationally allocate funding and to create new financing models.Conclusions.Despite its manifold applications, Information systems currently face many problems such as incomplete recording, poor data quality, lack of timely reporting and feedback, and limited application of information. Corrective action is needed to upgrade data collection in outpatient facilities, to improve data quality, to establish clear rules and norms, to access adequate information technology equipment and to train health care personnel in data collection. Moreover, it is necessary to shift from mere administrative data collection to analysis, dissemination and use by relevant stakeholders and to develop a “culture of information” to dismantle the culture of intuition and mere tradition. Clinical directors, mental health managers, patient and family representatives, as well as politicians should be educated to operate with information and not just intuition.

PP447 Informing The Development And Evaluation Of An Evidence-Based Service Delivery Model For Mental Health Patients With Complex Needs

2021 ◽  
Vol 37 (S1) ◽  
pp. 37-38
Author(s):  
Pooja Saini ◽  
Antony Martin ◽  
Jason C. McIntyre ◽  
Laura Sambrook ◽  
Hana Roks ◽  
...  
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Health Service ◽  
Medical Records ◽  
Service Use ◽  
Care Pathways ◽  
Service Users ◽  
Alternative Care ◽  
Complex Needs ◽  
Patient Health

IntroductionMental health services for adults have been developed to provide community-based interventions. There is a recognized unmet need in some of the most complex patients that may not be adequately met by existing mental health services provision. Research is warranted to consider the best model of service delivery for this group of service users. The aims of this research were to examine the profile and history of service users defined as having complex needs as well as their service use and associated costs in the Cheshire and Wirral Partnership NHS Foundation Trust (CWP).MethodsA diverse group of stakeholders were invited to provide feedback on the content and design of the proforma for data collection from the medical records of service users. The rationale of the data collection was described to ensure relevant patient-level cost information was collected to identify and quantify the relevant resources consumed, to inform the evaluation of direct medical costs, direct non-medical costs, and indirect costs for each patient. The proforma was designed to also permit comparisons of clinical and service use outcomes for evaluation of patient health and non-health outcomes associated with alternative care pathways.ResultsStakeholder feedback comprised representatives from the CWP, patients, commissioners, the Local Authority, and housing. Relevant data for extraction from patient medical records were identified and a proforma was developed. The following items were identified for inclusion: baseline demographic data, service user data (family background, contact with the criminal justice system, social history), and clinical data (diagnosis, treatment, hospital visits, and other health service use).ConclusionsA proforma was developed with diverse stakeholder involvement to inform data collection on the resource use and cost impact associated with alternative care pathways in the National Health Service and other sectors of the economy. Based on the proforma developed and data extracted, an exploration of patient health and non-health outcomes associated with alternative care pathways will be conducted to inform service evaluation and to promote patient centric care.

scholarly journals Impact of COVID-19-like symptoms on occurrence of anxiety/depression during lockdown among the French general population

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0255158
Author(s):  
Murielle Mary-Krause ◽  
Joel José Herranz Bustamante ◽  
Mégane Héron ◽  
Astrid Juhl Andersen ◽  
Tarik El Aarbaoui ◽  
...  
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Self Report ◽  
Depression Symptoms ◽  
Health Related ◽  
Mental Health Difficulties ◽  
Generalized Estimation Equation ◽  
Study Participants ◽  
Anxiety Depression

Background The outbreak of the COVID-19 epidemic lead to high levels of morbidity and mortality around the globe. Consequences of this outbreak and possible associated infection are an increase in mental health disorders and an increased likelihood of internalizing problems, particularly depression. However, to date few studies have tested this hypothesis while taking into account individuals’ preexisting mental health difficulties. Methods We used longitudinal data collected among 729 persons in the context of the French TEMPO cohort between March and June 2020 (7 waves of data collection). COVID-19-like symptoms as well as anxiety/depression (assessed by the Adult Self Report), were reported at each wave of data collection. To study the relationship between COVID-19-like symptoms and anxiety/depression, we used generalized estimation equation (GEE) models controlled for socio-demographic and health-related characteristics, including anxiety/depression prior to 2020. Results Overall, 27.2% of study participants reported anxiety/depression during lockdown. 17.1% of participants reported COVID-19-like symptoms during the course of follow-up, 7.3% after the beginning of lockdown, with an average number of 2.7 symptoms, and 3.6% reported respiratory distress. In multivariate analyses, nearly all the considered indicators of COVID-19-like symptoms were associated with higher odds of symptoms of anxiety/depression (symptoms Yes/No: OR = 1.66, 95% CI = 1.08–2.55; symptoms after the beginning of lockdown: OR = 1.91, 95% CI = 1.03–3.52; number of symptoms: OR for each additional symptom = 1.19, 95% CI = 1.02–1.39. This relationship exists after taking into account prior symptoms of anxiety/depression, which are associated with a 5-fold increased likelihood of psychological distress. And this impact is stronger among men than women. Conclusions Our study shows higher risk of anxiety/depression among persons who experienced COVID-19-like symptoms, even after accounting for prior mental health difficulties. COVID-19 infection could have both a direct and indirect impact on the occurrence of psychological difficulties, and this association should be studied in greater detail.

scholarly journals College student’s social anxiety: a study of the young people mental health in digital age

2021 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Cahyaning Suryaningrum
Keyword(s):  
Mental Health ◽  
College Students ◽  
Social Anxiety ◽  
Young People ◽  
Data Collection ◽  
Self Report ◽  
Male College ◽  
Liebowitz Social Anxiety Scale ◽  
And Gender ◽  
Quantitative Descriptive

Purpose of this study is to analyze whether in the current era social anxiety problems are still developing among college students and whether there are any differences in the level of social anxiety was based on the year of entry (new college students - old college students) and gender. This research is a quantitative-descriptive and comparative studies. Hypotheses are there is no difference in social anxiety level based on the year of entry nor gender. The subjects are undergraduate college students totaled 364 people. Instrument used for data collection is Liebowitz Social Anxiety Scale-Self Report (LSAs-SR). Results showed that 76.9% of the subjects experienced social anxiety. There is no difference in the level of social anxiety among new college students and old college college students nor between male college students and college students.

scholarly journals Data Collection and Labeling of Real-Time IoT-Enabled Bio-Signals in Everyday Settings for Mental Health Improvement

2021 ◽  
Author(s):  
Ali Tazarv ◽  
Sina Labbaf ◽  
Amir M. Rahmani ◽  
Nikil Dutt ◽  
Marco Levorato
Keyword(s):  
Mental Health ◽  
Data Collection ◽  
Real Time ◽  
Health Improvement

Data collection for care pathways in the Cleveland Clinic Health System.

2016 ◽  
Vol 34 (7_suppl) ◽  
pp. 115-115
Author(s):  
Katherine Glass ◽  
Chad W Cummings ◽  
Marc A. Shapiro ◽  
Dennis Urbanek ◽  
Brian James Bolwell
Keyword(s):  
Pilot Study ◽  
Data Collection ◽  
Health System ◽  
Real Time ◽  
Care Pathway ◽  
Care Pathways ◽  
Integration Of Care ◽  
Chemotherapeutic Regimen ◽  
Tumor Registry ◽  
Oncology Care

115 Background: Care pathways are established methods of reducing healthcare costs and disparities in oncology care. To demonstrate their impact, health systems must measure and report data on care pathway adherence and outcomes in near real-time. Automating data abstraction across a health system for oncology is difficult due to the amount and detail of data required. Manual abstraction of data is considered slow and costly. Many consider Electronic Medical Record (EMR) integration of care pathways essential in order to successfully implement and assess. Methods: 7 medical oncology care pathways and 45 medical oncologists across the health system were selected for a pilot study to assess the feasibility of implementing care pathways throughout the enterprise. The pilot study also allowed for testing of data collection capabilities. Patients eligible for the care pathways were prospectively identified by manual review of physician calendars. A small number of data points were manually abstracted from the patient EMR at the time of identification. Endpoints of interest, such as hospitalization rates, chemotherapy administered, time to treatment, and costs of care were reconciled through pre-existing databases within pharmacy, research, and finance. Tumor registry data identified a retrospective cohort. Results: Over 1,000 patients were prospectively identified for the care pathway pilot between 1/1/2014 and 12/31/2014. The tumor registry identified 700 additional retrospective patients. The rapid analyses possible as a result of these efforts demonstrated physician adherence, improved patient outcomes, and significant cost savings. In one example, a care pathway for metastatic non-small cell lung cancer reduced charges by more than $98,000/patient by recommending patients receive one standardized chemotherapeutic regimen. Conclusions: Timely data collection for oncology care pathways is feasible and cost effective without EMR integration. Manual identification of patients combined with pre-existing data sources allowed for near-real time analysis of care pathways and provided valuable information about care pathway impact. Institutions can implement and assess care pathways with resources already available to them.

scholarly journals Quality of Hospital Electronic Health Record (EHR) Data Based on the International Consortium for Health Outcomes Measurement (ICHOM) in Heart Failure: Pilot Data Quality Assessment Study

10.2196/27842 ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. e27842
Author(s):  
Hannelore Aerts ◽  
Dipak Kalra ◽  
Carlos Sáez ◽  
Juan Manuel Ramírez-Anguita ◽  
Miguel-Angel Mayer ◽  
...  
Keyword(s):  
Heart Failure ◽  
Pilot Study ◽  
Data Collection ◽  
Health Outcomes ◽  
Data Quality ◽  
Quality Assessment ◽  
Temporal Stability ◽  
Health Record ◽  
Outcomes Measurement ◽  
Data Quality Assessment

Background There is increasing recognition that health care providers need to focus attention, and be judged against, the impact they have on the health outcomes experienced by patients. The measurement of health outcomes as a routine part of clinical documentation is probably the only scalable way of collecting outcomes evidence, since secondary data collection is expensive and error-prone. However, there is uncertainty about whether routinely collected clinical data within electronic health record (EHR) systems includes the data most relevant to measuring and comparing outcomes and if those items are collected to a good enough data quality to be relied upon for outcomes assessment, since several studies have pointed out significant issues regarding EHR data availability and quality. Objective In this paper, we first describe a practical approach to data quality assessment of health outcomes, based on a literature review of existing frameworks for quality assessment of health data and multistakeholder consultation. Adopting this approach, we performed a pilot study on a subset of 21 International Consortium for Health Outcomes Measurement (ICHOM) outcomes data items from patients with congestive heart failure. Methods All available registries compatible with the diagnosis of heart failure within an EHR data repository of a general hospital (142,345 visits and 12,503 patients) were extracted and mapped to the ICHOM format. We focused our pilot assessment on 5 commonly used data quality dimensions: completeness, correctness, consistency, uniqueness, and temporal stability. Results We found high scores (>95%) for the consistency, completeness, and uniqueness dimensions. Temporal stability analyses showed some changes over time in the reported use of medication to treat heart failure, as well as in the recording of past medical conditions. Finally, the investigation of data correctness suggested several issues concerning the characterization of missing data values. Many of these issues appear to be introduced while mapping the IMASIS-2 relational database contents to the ICHOM format, as the latter requires a level of detail that is not explicitly available in the coded data of an EHR. Conclusions Overall, results of this pilot study revealed good data quality for the subset of heart failure outcomes collected at the Hospital del Mar. Nevertheless, some important data errors were identified that were caused by fundamentally different data collection practices in routine clinical care versus research, for which the ICHOM standard set was originally developed. To truly examine to what extent hospitals today are able to routinely collect the evidence of their success in achieving good health outcomes, future research would benefit from performing more extensive data quality assessments, including all data items from the ICHOM standards set and across multiple hospitals.

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