Impact of narcotics information management system on inappropriate benzodiazepine receptor agonist prescriptions: A quasi-experimental analysis in South Korea.

AIMS: The South Korean government implemented the narcotics information management system (NIMS) on 18 May 2018 to manage benzodiazepine receptor agonists (BzRAs) and narcotics effectively and establish a reporting mechanism for these drugs. This study assessed the effects of NIMS on inappropriate use of BzRAs. METHODS: Using national patient sample data from 2016 to 2020, we analysed adult outpatients who were prescribed oral BzRAs. We conducted a time series and segmented regression analysis using selected indicators to analyse the monthly variations related to the inappropriate use of these medications. RESULTS: The study revealed no significant changes in the indicators of inappropriate BzRA use following the NIMS implementation. Contrary to expectations, there was a significant increase in the proportion of patients exceeding defined daily dose (DDD) and in those receiving concurrent prescriptions of multiple BzRAs, following the implementation of NIMS. The immediate impact of the COVID-19 pandemic was an increase in DDD exceedance; however, overall, this did not significantly affect BzRA use. CONCLUSIONS: The introduction of NIMS did not significantly enhance the management of BzRA misuse. Additional measures, including continuous monitoring, system improvements and comprehensive education for prescribers and patients, are recommended to ensure the appropriate use of psychotropic medications.

[Design and Application of an IVD Reagent Management Information Systems Based on Unique Code].

The management of in vitro diagnostic (IVD) reagents in hospitals often faces issues such as the lack of a unified coding system, unclear consumption patterns, and unknown cost-to-income ratios. It is necessary to employ information systems to achieve comprehensive, detailed, and traceable management of IVD reagents. An information management system for IVD reagents based on unique coding is introduced, which integrates admission, acceptance, and consumption processes through unique codes. The system calculates the income per experimental item based on the consumption of IVD reagents and the charge for each experimental item. The system enhances the efficiency of the IVD reagent supply chain management and promotes detailed oversight of IVD reagent usage.

Development of automated metabolite control using mid-infrared probe for bioprocesses and vaccine manufacturing.

Automation of metabolite control in fermenters is fundamental to develop vaccine manufacturing processes more quickly and robustly. We created an end-to-end process analytical technology and quality by design-focused process by replacing manual control of metabolites during the development of fed-batch bioprocesses with a system that is highly adaptable and automation-enabled. Mid-infrared spectroscopy with an attenuated total reflectance probe in-line, and simple linear regression using the Beer-Lambert Law, were developed to quantitate key metabolites (glucose and glutamate) from spectral data that measured complex media during fermentation. This data was digitally connected to a process information management system, to enable continuous control of feed pumps with proportional-integral-derivative controllers that maintained nutrient levels throughout fed-batch stirred-tank fermenter processes. Continuous metabolite data from mid-infrared spectra of cultures in stirred-tank reactors enabled feedback loops and control of the feed pumps in pharmaceutical development laboratories. This improved process control of nutrient levels by 20-fold and the drug substance yield by an order of magnitude. Furthermore, the method is adaptable to other systems and enables soft sensing, such as the consumption rate of metabolites. The ability to develop quantitative metabolite templates quickly and simply for changing bioprocesses was instrumental for project acceleration and heightened process control and automation. ONE-SENTENCE SUMMARY: Intelligent digital control systems using continuous in-line metabolite data enabled end-to-end automation of fed-batch processes in stirred-tank reactors.

Social network analysis for medical narcotics in South Korea: focusing on patients and healthcare organizations.

BACKGROUND: Medical narcotics must be administered under medical supervision because of their potential for misuse and abuse, leading to more dangerous and addictive substances. The control of medical narcotics requires close monitoring to ensure that they remain safe and effective. This study proposes a methodology that can effectively identify the overprescription of medical narcotics in hospitals and patients. METHODS: Social network analysis (SNA) was applied to prescription networks for medical narcotics. Prescription data were obtained from the Narcotics Information Management System in South Korea, which contains all data on narcotic usage nationwide. Two-mode networks comprising hospitals and patients were constructed based on prescription data from 2019 to 2021 for the three most significant narcotics: appetite suppressants, zolpidem, and propofol. Two-mode networks were then converted into one-mode networks for hospitals. Network structures and characteristics were analyzed to identify hospitals suspected of overprescribing. RESULTS: The SNA identified hospitals that overprescribed medical narcotics. Patients suspected of experiencing narcotic addiction seek treatment in such hospitals. The structure of the network was different for the three narcotics. While appetite suppressants and propofol networks had a more centralized structure, zolpidem networks showed a less centralized but more fragmented structure. During the analysis, two types of hospitals caught our attention: one with a high degree, meaning that potential abusers have frequently visited the hospital, and the other with a high weighted degree, meaning that the hospital may overprescribe. For appetite suppressants, these two types of hospitals matched 84.6%, compared with 30.0% for propofol. In all three narcotics, clinics accounted for the largest share of the network. Patients using appetite suppressants were most likely to visit multiple locations, whereas those using zolpidem and propofol tended to form communities around their neighborhoods. CONCLUSIONS: The significance of this study lies in its analysis of nationwide narcotic use reports and the differences observed across different types of narcotics. The social network structure between hospitals and patients varies depending on the composition of the medical narcotics. Therefore, these characteristics should be considered when controlling medication with narcotics. The results of this study provide guidelines for controlling narcotic use in other countries.

Impact of the Narcotics Information Management System on Opioid Use Among Outpatients With Musculoskeletal and Connective Tissue Disorders: Quasi-Experimental Study Using Interrupted Time Series.

BACKGROUND: Opioids have traditionally been used to manage acute or terminal pain. However, their prolonged use has the potential for abuse, misuse, and addiction. South Korea introduced a new health care IT system named the Narcotics Information Management System (NIMS) with the objective of managing all aspects of opioid use, including manufacturing, distribution, sales, disposal, etc. OBJECTIVE: This study aimed to assess the impact of NIMS on opioid use. METHODS: We conducted an analysis using national claims data from 45,582 patients diagnosed with musculoskeletal and connective tissue disorders between 2016 and 2020. Our approach included using an interrupted time-series analysis and constructing segmented regression models. Within these models, we considered the primary intervention to be the implementation of NIMS, while we treated the COVID-19 outbreak as the secondary event. To comprehensively assess inappropriate opioid use, we examined 4 key indicators, as established in previous studies: (1) the proportion of patients on high-dose opioid treatment, (2) the proportion of patients receiving opioid prescriptions from multiple providers, (3) the overlap rate of opioid prescriptions per patient, and (4) the naloxone use rate among opioid users. RESULTS: During the study period, there was a general trend of increasing opioid use. After the implementation of NIMS, significant increases were observed in the trend of the proportion of patients on high-dose opioid treatment (coefficient=0.0271; P=.01) and in the level of the proportion of patients receiving opioid prescriptions from multiple providers (coefficient=0.6252; P=.004). An abrupt decline was seen in the level of the naloxone use rate among opioid users (coefficient=-0.2968; P=.04). While these changes were statistically significant, their clinical significance appears to be minor. No significant changes were observed after both the implementation of NIMS and the COVID-19 outbreak. CONCLUSIONS: This study suggests that, in its current form, the NIMS may not have brought significant improvements to the identified indicators of opioid overuse and misuse. Additionally, the COVID-19 outbreak exhibited no significant influence on opioid use patterns. The absence of real-time monitoring feature within the NIMS could be a key contributing factor. Further exploration and enhancements are needed to maximize the NIMS' impact on curbing inappropriate opioid use.

MoCab: A Model Management System Based on FHIR for Clinical Decision Support.

MoCab is a framework that deploys high-accuracy medical models across various health information systems (HISs) using fast healthcare interoperability resources (FHIR). MoCab simplifies the process by importing and configuring stored models and retrieving data for prediction. Two case studies illustrate how MoCab can be used to support decision-making. The proposed framework increases model reusability across EHRs and improves the clinical decision-making process.

[Survey on the Number and Percentage of MR Safety Labeling Changed for Implantable Medical Devices].

PURPOSE: The purposes of this study were to investigate the number and percentage of items that changed magnetic resonance (MR) safety information labeling for implantable medical devices (IMDs) and to confirm the importance of checking the latest MR safety information database (117 types and 10031 items). METHODS: We investigated the number and percentage of MR safety labeling changed for IMDs in the MR safety information database as of December 2021 and August 2022. RESULTS: IMDs of MR Safety Unlabeled decreased from 4116 items (41.1%) to 859 items (8.6%). IMDs of MR Conditional increased from 4141 items (41.3%) to 5896 items (58.8%). CONCLUSIONS: Since there have been changes in the MR safety labeling for many IMDs, this study shows that it is important to confirm the latest MR safety information for IMDs.

Comprehensive information management system for a medical research cohort biobank based on quality by design.

BACKGROUND: With the development of big health and big data, cohort research has become a medical research hotspot. As an important repository of human genetic resources, biobanks must adapt to the requirements of large-scale and efficient operation. Thus, biobanks urgently need to design and build a legal, convenient, and efficient information management system. METHODS: This study applies the concept of "quality by design" to build a comprehensive biobank information management system based on the analysis of user requirements, legal and regulatory risks, and industry-standard requirements. The system integrates the management of scientific research projects, biological specimens, clinical information, quality control, and multi-dimensional information query and development. After 10 months of its operation, the comprehensive management system was evaluated through statistical analysis of the efficiency of the construction of the pregnancy-birth cohort and the quality of genetic resources. RESULTS: Since the system's launch, the statistics on cohort construction efficiency show that the enrollment rate of eligible pregnant women has increased, and the rate of missing volunteers has dropped. The time needed to establish a 1000-person cohort (with complete biological samples and clinical information in early, middle, and late pregnancy) was reduced, and the effective tracking rate of the samples was 77.42%. The error rate of the deep cryogenic refrigerator decreased, with a clinical information integrity rate of 96.47%. CONCLUSIONS: The comprehensive biobank information management system constructed with the "quality by design" concept is well suited to meet the requirements of medical research. This study provides a solution for designing a comprehensive information system for medical institutions' biobanks.

SAP BusinessObjects in Medical Informatics.

Electronic health record (EHR) generates a large amount of data filled with opportunities to enhance documentation compliance, quality improvement, and other metrics. Various software tools exist, but many clinicians are unaware of them. Our institution switched from a hybrid of paper and multiple small EHRs to one all-inclusive EHR system. We faced significant challenges beyond the typical new software deployment phase that affected our departmental regulatory compliance, quality measures, and research initiatives. We aimed to navigate these issues through the use of medical informatics. We used a multidimensional database software analysis tool called SAP BusinessObjects® (SAP SE. Released 2020. SAP BusinessObjects, Version 14.2.8.3671. Waldorf, Germany) to design automated queries for the patient database to generate various reports for our department. As a result, We improved our anesthesia documentation non-compliance from 13-17% of all cases to 4% within months. We have also used this tool to automatically generate various reports such as preoperative beta-blocker administrations, caseloads, case complications, procedure logs, and medication records. Even today many departments rely on manual checks for even the most basic documentation and quality metric compliance, which can be time consuming and costly. Using medical informatics tools is a highly efficient alternative. Fortunately, many software tools exist within most modern EHR packages, and most people can learn to use these tools productively.

Anesthesia quality indicators to measure and improve your practice: a modified delphi study.

BACKGROUND: Implementation of the new competency-based post-graduate medical education curriculum has renewed the push by medical regulatory bodies in Canada to strongly advocate and/or mandate continuous quality improvement (cQI) for all physicians. Electronic anesthesia information management systems contain vast amounts of information yet it is unclear how this information could be used to promote cQI for practicing anesthesiologists. The aim of this study was to create a refined list of meaningful anesthesia quality indicators to assist anesthesiologists in the process of continuous self-assessment and feedback of their practice. METHODS: An initial list of quality indicators was created though a literature search. A modified-Delphi (mDelphi) method was used to rank these indicators and achieve consensus on those indicators considered to be most relevant. Fourteen anesthesiologists representing different regions across Canada participated in the panel. RESULTS: The initial list contained 132 items and through 3 rounds of mDelphi the panelists selected 56 items from the list that they believed to be top priority. In the fourth round, a subset of 20 of these indicators were ranked as highest priority. The list included items related to process, structure and outcome. CONCLUSION: This ranked list of anesthesia quality indicators from this modified Delphi study could aid clinicians in their individual practice assessments for continuous quality improvement mandated by Canadian medical regulatory bodies. Feasibility and usability of these quality indicators, and the significance of process versus outcome measures in assessment, are areas of future research.

Quantifying and Interpreting Inequality in Surgical Site Infections per Quarter Among Anesthetizing Locations and Specialties.

Background Earlier studies have shown that prevention of surgical site infection can achieve net cost savings when targeted to operating rooms with the most surgical site infections. Methodology This retrospective cohort study included all 231,057 anesthetics between May 2017 and June 2022 at a large teaching hospital. The anesthetics were administered in operating rooms, procedure rooms, radiology, and other sites. The 8,941 postoperative infections were identified from International Classification of Diseases diagnosis codes relevant to surgical site infections documented during all follow-up encounters over 90 days postoperatively. To quantify the inequality in the counts of infections among anesthetizing locations, the Gini index was used, with the Gini index being proportional to the sum of the absolute pairwise differences among anesthetizing locations in the counts of infections. Results The Gini index for infections among the 112 anesthetizing locations at the hospital was 0.64 (99% confidence interval = 0.56 to 0.71). The value of 0.64 is so large that, for comparison, it exceeds nearly all countries' Gini index for income inequality. The 50% of locations with the fewest infections accounted for 5% of infections. The 10% of locations with the most infections accounted for 40% of infections and 15% of anesthetics. Among the 57 operating room locations, there was no association between counts of cases and infections (Spearman correlation coefficient r = 0.01). Among the non-operating room locations (e.g., interventional radiology), there was a significant association (Spearman r = 0.79). Conclusions Targeting specific anesthetizing locations is important for the multiple interventions to reduce surgical site infections that represent fixed costs irrespective of the number of patients (e.g., specialized ventilatory systems and nightly ultraviolet-C disinfection).

Impacts of Digital Information Management Systems on Green Transformation of Manufacturing Enterprises.

Under the background of increasingly prominent environmental problems, the establishment and application of digital information management systems established by the digital economy have brought new opportunities and challenges to the green transformation of manufacturing enterprises. Considering the micro level of Chinese manufacturing enterprises, does the adoption of information management systems really promote the improvement of the green transformation level of manufacturing enterprises? This paper takes the adoption of digital information management systems by China's enterprises as a "quasi natural" experiment and uses the Difference-in-Difference and Propensity Score Matching model (PSM-DID) to explore its impact on the green transformation of manufacturing enterprises and its mechanism. The study found that the adoption of digital information management systems by enterprises significantly improved the green transformation level of manufacturing enterprises, especially the symbolic green transformation level, and had no significant positive effect on the substantive green transformation level. The mechanism analysis shows that manufacturing enterprises can achieve green transformation by adopting information management systems to improve the digital level, strengthen green innovation ability, and increase the redundant resources of enterprises. The heterogeneity analysis based on the internal governance and external environment of enterprises shows that the adoption of digital information management systems by manufacturing enterprises has significantly improved the green transformation level of non-state-owned enterprises, enterprises with high corporate governance, non-heavily polluting enterprises, and enterprises in the eastern region. The research conclusion enriches the research related to digitalization and green transformation of enterprises and has important inspiration for Chinese manufacturing enterprises to use digitalization capabilities to seek green sustainable development under the wave of digital economy development.

Narcotics information management system in South Korea: system development and innovation.

BACKGROUND: As the misuse and abuse of medical narcotics are increasing in South Korea, an information system for the integrated information management of medical narcotic drugs across the nation is needed. This paper presents the development process of the Narcotics Information Management System (NIMS) for the monitoring of medical narcotics usage and the results of its implementation. METHODS: As the NIMS enforces that all narcotics handlers digitally report all information on handling medical narcotic drugs, the functional requirements of the NIMS have been identified in accordance with the Narcotics Control Act. In addition to the functional requirements, the non-functional requirements of the NIMS have been elicited by major narcotics handlers and their associations. The non-functional requirements include privacy, availability, connectivity, interoperability, and data integrity. The system design with entity-relationship diagrams and its implementation processes have been presented. RESULTS: The NIMS encompasses all narcotic handlers, which comprise exporting, importing, and pharmaceutical companies; wholesalers; hospitals and clinics; and pharmacies, collecting over 120 million cases annually. It enables transparent monitoring throughout the life cycle, from manufacturing, sales, purchase, and disposal of narcotics. As a result, the number of prescriptions for medical narcotics has been reduced by 9.2%. CONCLUSIONS: To the best of our knowledge, the NIMS is the world's first system to manage all information on the total life cycle of medical narcotics, including imports, production, distribution, use, and disposal of drugs. This system has enabled the safety management and monitoring of medical narcotic drugs. Additionally, it provides consistent and transparent information to physicians and patients, leading to the autonomous safety management of narcotics. The successful development of the NIMS can provide guidelines for implementing a narcotics management system in other countries.

Development and usage of an anesthesia data warehouse: lessons learnt from a 10-year project.

This paper describes the development and implementation of an anesthesia data warehouse in the Lille University Hospital. We share the lessons learned from a ten-year project and provide guidance for the implementation of such a project. Our clinical data warehouse is mainly fed with data collected by the anesthesia information management system and hospital discharge reports. The data warehouse stores historical and accurate data with an accuracy level of the day for administrative data, and of the second for monitoring data. Datamarts complete the architecture and provide secondary computed data and indicators, in order to execute queries faster and easily. Between 2010 and 2021, 636 784 anesthesia records were integrated for 353 152 patients. We reported the main concerns and barriers during the development of this project and we provided 8 tips to handle them. We have implemented our data warehouse into the OMOP common data model as a complementary downstream data model. The next step of the project will be to disseminate the use of the OMOP data model for anesthesia and critical care, and drive the trend towards federated learning to enhance collaborations and multicenter studies.

Nurse educators' and students' experiences on electronic patient records: A multiple-methods study.

BACKGROUND: The storage of patient records in electronic media is one of the most outstanding developments of the 21st century. This transformation in health required the teaching staff and students in nursing to adapt to this change. OBJECTIVES: To determine nurse educators' and students' views and experiences about electronic patient records. METHODS: A multiple-method approach was used in the study. The research sample consisted of 133 nurse educators and 366 nursing students from three public and three non-profit private universities in Ankara during the fall term of the 2019-2020 academic year. In the quantitative stage, data were collected with a data collection form prepared by the researcher. Data were obtained via semi-structured interviews with 14 nurse educators and 14 students at the qualitative stage. Descriptive statistics (number, percentage) were used to analyze quantitative data, and the content analysis method was used to analyze the qualitative data. RESULTS: 91 % of the nurse educators and 96.4 % of the students stated that they learned about electronic patient records through observation in a clinical setting. >70 % of the participants noted that including subject matters about electronic patient records in the nursing curriculum would be beneficial. In the qualitative phase, most nurse educators and students (n > 9) reported that they could not access the system because they did not have credentials. They stated that their experiences depended on the current users and were limited to observation; therefore, regulations regarding access to electronic patient records should be made. CONCLUSIONS: The views and experiences of the nurse educators and students about the electronic medical record system were limited to getting help from observing clinical nurses since they could not be registered users in the system. Therefore, it is recommended to expand the teaching related to electronic patient records in the nursing education program, develop educational software, and make arrangements to provide access to electronic data during clinical applications.

Optimal design and application of information management system of biobank in hospitals / 中华医学科研管理杂志

Objective:To establish a standardized information management system (IMS) for preserving, managing, querying, and performing statistics on biospecimens and their clinical data, which is conducive to improving the utilization of biobank.Methods:Under the premise of ensuring operating environment and data security, a database-based data logic relationship model is created and applied to the IMS to manage and analyze biospecimens and their supporting clinical information of patients enrolled in the biobank of our center.Results:To ensure the establishment of the follow-up cohort, biospecimens and clinical information of inpatients and outpatients were continuously collected in the biobank of our center. Since December 2014, more than 270 000 biospecimens from inpatient, outpatient, and scientific research have been preserved. The IMS optimized by this model efficiently completes the basic work of the biobank. At the same time, the data can be queried jointly and in batches, and then converted into a report format for statistical analysis.Conclusions:The IMS of our center is suitable for application and popularization as a construction and management model for the hospital-level biobank, which meets the daily work of the biobank and diverse research needs, and provides a convenient platform and rich resources for the development of precision medicine.

Utilizing Modular Biobanking Software in Different Types of Biobanking Activities.

Biobanking defines all activities linked to bioresource management-whether of human, animal, microbial, or environmental origin-which means that any biobank information management system should take into account the multistep life cycle of the samples: from acquisition, through preparation, storage, to distribution to the end users (medical or research teams). Different types of biobanks can use diverse approaches, making it difficult to find software that can handle all types of scenarios. Modul-Bio has developed MBioLIMS BioBanking®, a software dedicated to biobanking, as a modular solution so that our various clients can access the functionalities and scale in a system to match their needs. These projects range from biobanks setup and managed by academic institutions, hospitals, and private companies to small and large clinical trials across different countries, as well as to whole campus or organization solutions for multiple biorepositories. Each solution differs in size, requirements, and number of users, from small biobanks with a few members of staff accessing the software to large operations with multiple sites that can collect and ship samples to a centralized site. This article explores different projects that use Modul-Bio's software in a myriad of ways to manage the complete life cycle of biospecimens and associated data.

Anesthesiologists in the Ether: Technology and Telemedicine in Anesthesiology.

A new frontier in veterinary anesthesia telehealth has begun. With the adoption of electronic anesthetic records and video, phone, and chat consultations, an anesthesiologist can be integrated into the care team of any patient, anywhere in the world. This article reviews the benefits of adopting an electronic anesthetic record system, and the ways that practitioners can incorporate a virtual anesthesiologist into their care team.

Trends in decompensated cirrhosis and hepatocellular carcinoma among people with a hepatitis B notification in New South Wales.

Background & Aims: Population-level trends and factors associated with HBV-related decompensated cirrhosis (DC), hepatocellular carcinoma (HCC), and liver-related mortality are crucial to evaluate the impacts of therapeutic interventions. Methods: Trends in HBV-DC and -HCC diagnoses and liver-related mortality in New South Wales, Australia, were determined through linkage of HBV notifications (1993-2017) to hospital admissions (2001-2018), mortality (1993-2018), and cancer registry (1994-2014) databases. Late HBV notification was defined as notification at or within 2 years of a DC or HCC diagnosis. Cox proportional-hazards regression and multivariable logistic regression analyses were performed to evaluate associated factors. Results: Among 60,660 people with a HBV notification, 1,276 (2.0%) DC and 1,087 (1.8%) HCC diagnoses, and 1,219 (2.0%) liver-related deaths were documented. Since the early 2000s, the number of DC and HCC diagnoses increased; however, age-standardised incidence decreased from 2.64 and 1.95 in 2003 to 1.14 and 1.09 per 1,000 person-years in 2017, respectively. Similarly, age-standardised liver mortality decreased from 2.60 in 2003 to 1.14 per 1,000 person-years in 2017. Among people with DC and HCC diagnoses, late HBV notification declined from 41% and 40% between 2001-2009 to 29% and 25% in 2010-2018, respectively. Predictors of DC diagnosis included older age (birth <1944, adjusted hazard ratio [aHR] 2.06, 95% CI 1.57-2.69), alcohol use disorder (aHR 4.82, 95% CI 3.96-5.87) and HCV co-infection (aHR 1.88, 95% CI 1.53-2.31). Predictors of HCC diagnosis included older age (birth <1944, aHR 3.94, 95% CI 2.91-5.32) and male sex (aHR 3.79, 95% CI 3.05-4.71). Conclusion: In an era of improved antiviral therapies, the risk of HBV-related liver morbidity and mortality has declined. HCV co-infection and alcohol use disorder are key modifiable risk factors associated with the burden of HBV. Lay summary: Rising hepatitis B-related morbidity and mortality is a major public health concern. However, the development of highly effective medicines against hepatitis B virus (HBV) has brought renewed optimism for its elimination by 2030. This study shows a steady decline in HBV-related liver morbidity and mortality in New South Wales, Australia. Moreover, late hepatitis notification has also declined, allowing individuals with HBV to have access to timely antiviral treatment. Despite this, hepatitis C co-infection and alcohol use disorder are key modifiable risk factors associated with HBV disease burden. To attain the desired benefits from highly effective antiviral treatment, managing comorbidities, including hepatitis C and high alcohol use, must improve among individuals with hepatitis B.

An mHealth-Based Health Management Information System Among Health Workers in Volta and Eastern Regions of Ghana: Pre-Post Comparison Analysis.

BACKGROUND: Despite the increasing attention to electronic health management information systems (HMISs) in global health, most African countries still depend on inefficient paper-based systems. Good Neighbors International and Evaluate 4 Health have recently supported the Ghana Health Service on the rollout of a mobile health-based HMIS called the e-Tracker system in 2 regions in Ghana. The e-Tracker is an Android-based tracker capture app that electronically manages maternal and child health (MCH) data. The Ghana Health Service has implemented this new system in Community Health Planning and Services in the 2 regions (Volta and Eastern). OBJECTIVE: This study aims to evaluate changes in health workers' capacity and behavior after using the e-Tracker to deliver MCH services. Specifically, the study assesses the changes in knowledge, attitude, and practice (KAP) of the health workers toward the e-Tracker system by comparing the pre- and postsurvey results. METHODS: The KAP of frontline health workers was measured through self-administered surveys before and after using the e-Tracker system to assess their capacity and behavioral change toward the system. A total of 1124 health workers from the Volta and Eastern regions responded to the pre-post surveys. This study conducted the McNemar chi-square test and Wilcoxon signed-rank test for a pre-post comparison analysis. In addition, random-effects ordered logistic regression analysis and random-effects panel analysis were conducted to identify factors associated with KAP level. RESULTS: The pre-post comparison analysis showed significant improvement in health workers' capacity, with higher knowledge and practice levels after using the e-Tracker system. As for knowledge, there was a 9.9%-point increase (from 559/1109, 50.41% to 669/1109, 60.32%) in the proportion of the respondents who were able to generate basic statistics on the number of children born in a random month within 30 minutes. In the practice section, the percentage of respondents who had scheduled clientencounters increased from 91.41% (968/1059) to 97.83% (1036/1059). By contrast, responses to the attitude (acceptability) became less favorable after experiencing the actual system. For instance, 48.53% (544/1121) initially expressed their preferences for an electronic system; however, the proportion decreased to 33.45% (375/1121) after the intervention. Random-effects ordered logistic regression showed that days of overwork were significantly associated with health workers' attitudes toward the e-Tracker system. CONCLUSIONS: This study provides empirical evidence that the e-Tracker system is conducive to enhancing capacity in MCH data management for providing necessary MCH services. However, the change in attitude implies that the users appear to feel less comfortable using the new system. As Ghana plans to scale up the electronic HMIS system using the e-Tracker to the national level, strategies to enhance health workers' attitudes are necessary to sustain this new system.