Quality of Care in Hospitals and the Use of Mobile-Based Personal Health Record Applications: An Exploratory Study Using National Hospital Evaluation Data.

The use of mobile-based personal health record (m-PHR) applications at the hospital level has been minimally studied. This study aimed to investigate the relationship between m-PHR use and quality of care. A cross-sectional study design was employed, analyzing data from 99 hospitals. Two data sources were utilized: a previous m-PHR investigation conducted from 26 May to 30 June 2022 and a hospital evaluation dataset on quality of care. The use of m-PHR applications was measured by the number of m-PHR application downloads. Three independent variables were assessed: quality of care in the use of antibiotic drugs, injection drugs, and polypharmacy with ≥6 drugs. A generalized linear model was used for the analysis. The hospitals providing high-quality care, as evaluated based on the rate of antibiotic prescription (relative risk [RR], 3.328; 95% confidence interval [CI], 1.840 to 6.020; p < 0.001) and polypharmacy (RR, 2.092; 95% CI, 1.027 to 4.261; p = 0.042), showed an increased number of m-PHR downloads. Among the hospital covariates, public foundation status and being part of multi-hospital systems were associated with the number of m-PHR downloads (p < 0.05). This exploratory study found a positive relationship between quality of care and m-PHR use. Hospitals providing high-quality care may also excel in various activities, including m-PHR application use.

Feasibility of extracting cancer stage and metastasis codes from health insurance claims of outpatients and expressibility in ICD-11: a cross-sectional study using national health insurance data from South Korea.

OBJECTIVES: This study aimed to evaluate the incidence of health insurance claims recording the cancer stage and TNM codes representing tumor extension size (T), lymph node metastasis (N), and distant metastasis (M) for patients diagnosed with cancer and to determine whether this extracted data could be applied to the new ICD-11 codes. DESIGN: A cross-sectional study design was used, with the units of analysis as individual outpatients. Two dependent variables were extraction feasibility of cancer stage and TNM metastasis information from each claim. Expressibility of the two variables in ICD-11 was descriptively analysed. SETTING AND PARTICIPANTS: The study was conducted in South Korea and study participants were outpatients: lung cancer (LC) (46616), stomach cancer (SC) (50103) and colorectal cancer (CC) (54707). The data set consisted of the first health insurance claim of each patient visiting a hospital from 1 July to 31 December 2021. RESULTS: The absolute extraction success rates for cancer stage based on claims with cancer stage was 33.3%. The rates for stage for LC, SC and CC were 30.1%, 35.5% and 34.0%, respectively. The rate for TNM was 11.0%. The relative extraction success rates for stage compared with that for CC (the reference group) were lower for patients with LC (adjusted OR (aOR), 0.803; 95% CI 0.782 to 0.825; p<0.0001) but higher for SC (aOR 1.073; 95% CI 1.046 to 1.101; p<0.0001). The rates of TNM compared that for CC were 40.7% lower for LC (aOR, 0.593; 95% CI 0.569 to 0.617; p<0.0001) and 43.0% lower for SC (aOR 0.570; 95% CI 0.548 to 0.593; p<0.0001). There were limits to expressibility in ICD-11 regarding the detailed cancer stage and TNM metastasis codes. CONCLUSION: Extracting cancer stage and TNM codes from health insurance claims were feasible, but expressibility in ICD-11 codes was limited. WHO may need to create specific cancer stage and TNM extension codes for ICD-11 due to the absence of current rules in ICD-11.

Factors associated with the download and use of mobile personal health record applications in Korean hospitals.

The use of mobile personal health records (m-PHR) has been little studied at the organizational level. This study was to investigate the relationships of various hospital-related factors with m-PHR use in Korean hospitals. Downloads of m-PHR applications for 101 hospitals were examined from May 26 to 30 June 2022. The dependent variable was the number of m-PHR downloads, and the major independent variables included six technological, organizational, and environmental factors. As technological factors, the number of computed tomography and magnetic resonance imagery devices were significantly associated with downloads (RR = 1.119, CI = 1.022-1.226, p = 0.016; and RR = 1.155; 95% CI = 1.024-1.302, p = 0.019, respectively). At the organizational level, the number of physicians, adjusting for the number of beds, and the number of medical information management staff showed significant associations (RR = 1.059, CI = 1.019-1.100, p = 0.004; and RR = 1.026, CI = 1.002-1.050, p = 0.033, respectively). From an environmental standpoint, downloads were positively associated with the proportion of the local population of working age (20-59 years) (RR = 1.102, CI 1.022-1.189, p = 0.012). Healthcare policymakers should pay close attention to these factors to advocate for the widespread use of m-PHR applications.

Hospitals' Adoption of Mobile-Based Personal Health Record Systems and Patients' Characteristics: A Cross-Sectional Study Analyzing National Healthcare Big Data.

Insufficient information exists on the associations between hospitals' adoption of mobile-based personal health record (mPHR) systems and patients' characteristics. This study explored the associations between patients' characteristics and hospitals' adoption of mPHR systems in Korea. This cross-sectional study used 316 hospitals with 100 or more beds as the unit of analysis. Previously collected data on mPHR adoption from May 1 to June 30, 2020 were analyzed. National health insurance claims data for 2019 were also used to analyze patients' characteristics. The dependent variable was mPHR system adoption (0 vs 1) and the main independent variables were the number of patients, age distribution, and proportions of patients with cancer, diabetes, and hypertension among inpatients and outpatients. The number of inpatients was significantly associated with mPHR adoption (adjusted odds ratio [aOR]: 1.174; 1.117-1.233, P < .001), as was the number of outpatients (aOR: 1.041; 1.028-1.054, P < .001). The proportion of inpatients aged 31 to 60 years to those aged 31 years and older was also associated with hospital mPHR adoption (aOR: 1.053; 1.022-1.085, P = .001). mPHR system adoption was significantly associated with the proportion of inpatients (aOR: 1.089; 1.012-1.172, P = .024) and outpatients (aOR: 1.138; 1.026-1.263, P = .015) with cancer and outpatients (aOR: 1.271; 1.101-1.466, P = .001) with hypertension. Although mPHR systems are useful for the management of chronic diseases such as diabetes and hypertension, the number of patients, younger age distribution, and the proportion of cancer patients were closely associated with hospitals' introduction of mPHR systems.

Changes in healthcare use by age groups of patients and locations of healthcare institutions after the COVID-19 pandemic in Korea: Analyzing healthcare big data.

Objectives: The COVID-19 pandemic affected healthcare use globally. However, there have been few studies examining how it affected age-specific healthcare use by patients as related to the locations of healthcare institutions. We explore changes in healthcare use while focusing on age-specific patient groups and facility locations after the COVID-19 pandemic. Methods: We compared two databases of cross-sectional outpatient health-insurance claims that have equivalent time points yearly and quarterly both before and after the COVID-19 pandemic. We categorized patients of healthcare institutions into five age groups and two facility locations. Results: The number of claims in 2020 significantly decreased by about 15% compared to 2019. The greatest reduction was for patients aged under 20 (-43.7%), followed by the 20-39 group (-15.0%) and the 40-59 group (-11.9%). Moreover, the number of claims significantly decreased in both urban and rural areas (p< 0.001); however, the magnitude of this decrease was greater in urban areas (-15.2%) than in rural areas (-10.8%). The annual decrease in healthcare use by age groups and location of facility was still supported even after controlling for institutional covariates, except for the patient group aged 80 or over in rural areas. Conclusions: We found that the COVID-19 pandemic critically affected healthcare use across age-specific population groups and different locations of healthcare institutions. It suggests there is a need for further research and policy implications as to whether the declining healthcare use among those age groups is in core health care, and as to whether there are any unmet healthcare needs.

Factors Associated with Website Operation among Small Hospitals and Medical and Dental Clinics in Korea.

OBJECTIVES: The objective of this study was to investigate the factors associated with website operation among medical facilities. METHODS: A cross-sectional study design was employed to investigate 1,519 hospitals, 33,043 medical clinics (MCs), and 18,240 dental clinics (DCs) as of 2020. The main outcome variable was analyzed according to technological, organizational, and environmental factors. RESULTS: The percentages of small hospitals, MCs, and DCs with websites were 26.4%, 9.0%, and 6.6%, respectively. For small hospitals, the nearby presence of a subway station (odds ratio [OR] = 2.772; 95% confidence interval [CI], 1.973-3.892; p < 0.0001) was the only factor significantly associated with website operation status. Among medical and dental clinics, the percentage of specialists-MCs (OR = 1.002; 95% CI, 1.000-1.004; p = 0.0175) and DCs (OR = 1.002; 95% CI, 1.001-1.004; p = 0.0061), the nearby presence of a subway station-MCs (OR = 2.954; 95% CI, 2.613-3.339; p < 0.0001) and DCs (OR = 3.444; 95% CI, 2.945-4.028; p < 0.0001), and the number of clinics in the local area-MCs (OR = 1.029; 95% CI, 1.026-1.031; p < 0.0001) and DCs (OR = 1.080; 95% CI, 1.066-1.093; p < 0.0001)-were significantly associated with website operation. CONCLUSIONS: Clinics are critically affected by internal and external factors regarding website operation relative to small hospitals. Healthcare policymakers involved with information technologies may need to pay attention to those factors associated with website dispersion among small clinics.

The Development of an Automatic Rib Sequence Labeling System on Axial Computed Tomography Images with 3-Dimensional Region Growing.

This paper proposes a development of automatic rib sequence labeling systems on chest computed tomography (CT) images with two suggested methods and three-dimensional (3D) region growing. In clinical practice, radiologists usually define anatomical terms of location depending on the rib's number. Thus, with the manual process of labeling 12 pairs of ribs and counting their sequence, it is necessary to refer to the annotations every time the radiologists read chest CT. However, the process is tedious, repetitive, and time-consuming as the demand for chest CT-based medical readings has increased. To handle the task efficiently, we proposed an automatic rib sequence labeling system and implemented comparison analysis on two methods. With 50 collected chest CT images, we implemented intensity-based image processing (IIP) and a convolutional neural network (CNN) for rib segmentation on this system. Additionally, three-dimensional (3D) region growing was used to classify each rib's label and put in a sequence label. The IIP-based method reported a 92.0% and the CNN-based method reported a 98.0% success rate, which is the rate of labeling appropriate rib sequences over whole pairs (1st to 12th) for all slices. We hope for the applicability thereof in clinical diagnostic environments by this method-efficient automatic rib sequence labeling system.

Patient Factors Associated with Different Hospice Programs in Korea: Analyzing Healthcare Big Data.

The Korean government has implemented a pilot project that introduces a new type of hospice care program called "Consultative Hospice Care" (COHC) since August 2017. The COHC is a new type of hospice program for terminally ill patients in acute care wards, which is different from the Independent Hospice Unit (IHU) care. This study aimed to compare the characteristics of two groups of hospice patients: COHC care only and both IHU care and COHC groups. Healthcare claim data from 1 April 2018 to 31 March 2020 were retrieved from the HIRA data warehouse system. The main outcome variable was patients receiving COHC only or both COHC and IHU care. The total number of hospice patients was 6482. A multivariate logistic regression analysis was used. Of 6482 hospice care recipients, 3789 (58.5%) received both COHC and IHU care. Those who received both COHC and IHU care were significantly associated with several factors: period from the first evaluation to death (adjusted odds ratio (aOR), 1.026; 95% confidence internal (CI), 1.024-1.029; p < 0.0001), disease severity measured by the Charlson Comorbidity Index (aOR, 1.032; CI, 1.017-1.047; p < 0.0001), consciousness (aOR, 3.654; CI, 3.269-4.085; p < 0.0001), and awareness of end-stage disease (aOR, 1.422; CI, 1.226-1.650; p < 0.0001). The COHC program had a critical role in hospice delivery to terminally ill patients. Policymakers on hospice care need to establish plans that promote efficient hospice care delivery systems.

Was size of healthcare institution a factor affecting changes in healthcare utilisation during the COVID-19 pandemic in Korea? A retrospective study design analysing national healthcare big data.

OBJECTIVES: Many small-sized healthcare institutions play a critical role in communities by preventing infectious diseases. This study examines how they have been impacted by the global COVID-19 pandemic compared with large hospitals. DESIGN: This study adopted a retrospective study design looking back at the healthcare utilisation of medical facilities according to size after the COVID-19 pandemic. The dependent variable was change in the number of outpatient health insurance claims before and after onset of the COVID-19 pandemic. The independent variable was an observation time point of the year 2020 compared with 2019. SETTING AND PARTICIPANTS: The study was conducted in Korea having a competitive medical provision environment under the national health insurance system. The units of analysis are hospitals and clinics: tertiary hospitals (42), general hospitals (293), small hospitals (1272) and medical clinics (27 049). This study analysed all the health insurance claim data from 1 January 2019 to 31 December 2020. RESULTS: Compared with 2019, in 2020, there were significant decreases in the number of claims (-14.9%), particularly in small hospitals (-16.8%) and clinics (-16.3%), with smaller decreases in general hospitals (-8.9%) and tertiary hospitals (-5.3%). The reduction in healthcare utilisation increased as the size of institutions decreased. The magnitude of decrease was significantly greatest in small hospitals (absolute risk (AR): 0.8317, 0.7758 to 0.8915, p<0.0001; relative risk (RR): 0.8299, 0.7750 to 0.888, p<0.0001) followed by clinics (AR: 0.8369, 0.8262 to 0.8478, p<0.0001; RR: 0.8362, 0.8255 to 0.8470, p<0.0001) even after controlling institutional covariates. CONCLUSION: The external impact of the pandemic increased incrementally as the size of healthcare institutions decreased. Healthcare policy-makers need to keep in mind the possibility that small hospitals and clinics may experience reduced healthcare utilisation in the infectious disease pandemic. This fact has political implications for how healthcare policy-makers should prepare for the next infectious disease pandemic.

Association of the Magnitude of Nurses With the Use of Health Information Exchanges: Analyzing the National Health Insurance Claim Data of Hospitals and Clinics in Korea.

BACKGROUND: Many features of health care organizations (HCOs) have been identified to be associated with health information exchange (HIE), but subcategories of organizational factors focusing on nurse workforces still need to be identified. The objective of this study is to investigate the association of number of nurses with HIE use in Korea. METHODS: This study had a retrospective study design and used health insurance claim data from June 1, 2016 to June 30, 2018. The unit of analysis was the HCO, and any health insurance claims having HIE were counted by HCO. There were a total of 1490 HCOs having any HIE and 24 026 HCOs not having HIE. For statistical analysis, two-part model was used: logistic regression for HIE participation and the generalized linear model for the volume of HIE use. RESULTS: HIE was used by 44.6% of general hospitals, and 8.6% and 5.3% of small hospitals and clinics, respectively. Both HIE use and its volume were significantly positively associated with nurse variables. The use of HIE was significantly positively associated with nurse-to-bed ratio in general hospitals (OR 1.028; 1.016 to 1.041) and in small hospitals (OR 1.021; 1.016 to 1.027), and with the number of nurses (OR 1.041; 1.028 to 1.054) in clinics (P<.001). The volume of HIE use was also positively associated with nurse-to-bed ratio in general hospitals (OR 1.010; 1.004 to 1.017) and in small hospitals (OR 1.014; 1.006 to 1.022), and with the number of nurses (OR 1.055; 1.037 to 1.073) in clinics (P<.01). CONCLUSION: This study found that there was a low rate of HIE use in small hospitals and clinics. The number of nurses was critically associated with the use of HIE and the volume of HIE claims. HIE policy makers need to be aware of this factor in seeking to accelerate HIE.

Factors of quality of care and their association with smartphone based PHR adoption in South Korean hospitals.

BACKGROUND: Healthcare organizations have begun to adopt personal health records (PHR) systems to engage patients, but little is known about factors associated with the adoption of PHR systems at an organizational level. The objective of this study is to investigate factors associated with healthcare organizations' adoption of PHR systems in South Korea. METHODS: The units of analysis were hospitals with more than 100 beds. Study data of 313 hospitals were collected from May 1 to June 30, 2020. The PHR adoption status for each hospital was collected from PHR vendors and online searches. Adoption was then confirmed by downloading the hospital's PHR app and the PHR app was examined to ascertain its available functions. One major outcome variable was PHR adoption status at hospital level. Data were analysed by logistic regressions using SAS 9.4 version. RESULTS: Out of 313 hospitals, 103 (32.9%) hospitals adopted PHR systems. The nurse-patient ratio was significantly associated with PHR adoption (OR 0.758; 0.624 to 0.920, p = 0.005). The number of health information management staff was associated with PHR adoption (OR 1.622; 1.228 to 2.141, p = 0.001). The number of CTs was positively associated with PHR adoption (OR 5.346; 1.962 to 14.568, p = 0.001). Among the hospital characteristics, the number of beds was significantly related with PHR adoption in the model of standard of nursing care (OR 1.003; 1.001 to 1.005, p < 0.001), HIM staff (OR 1.004; 1.002 to 1.006, p < 0.001), and technological infrastructure (OR 1.050; 1.003 to 1.006, p < 0.001). CONCLUSIONS: One-third of study hospitals had adopted PHR systems. Standard of nursing care as well as information technology infrastructure in terms of human resources for health information management and advanced technologies were significantly associated with adoption of PHR systems. A favourable environment for adopting new technologies in general may be associated with the adoption and use of PHR systems.

Factors of Hospitals Associated With an Independent Hospice Care Unit: A Quantitative Empirical Study.

Few studies have examined why some hospitals operate independent hospice units (IHUs) and others do not. This study aims to investigate the organizational factors of hospitals having IHU. The units of analysis were individual hospitals. The study had a cross-sectional design and used health insurance claims data of 349 hospitals in Korea from January 1 to December 31, 2019. The dependent variable was whether a hospital operated an IHU. The independent variables were the percentage of patients with cancer, overall severity of patients, percentage of patients 60 years and older, health care cost per patient, percentage of inpatients, and nurse staffing level. Independent hospice units were present at 21.2% of the hospitals (74/349). The odds of having an IHU were significantly associated with the following factors: the percentage of patients with cancer (odds ratio [OR], 1.228; 95% confidence interval [CI], 1.071-1.408; P = .003), disease severity (OR, 5.129; 95% CI, 2.477-10.622; P < .001), percentage of patients 60 years and older (OR, 1.053; 95% CI, 1.015-1.092; P = .006), health care cost per patient (OR, 1.018; 95% CI, 1.009-1.027; P < .001), and nurse staffing level (OR, 0.439; 95% CI, 0.292-0.661; P < .001). The organizational factors of hospitals operating IHUs were similar to those of hospice facilities.

Changes in Nurse Staffing Grades of Korean Hospitals during COVID-19 Pandemic.

The global COVID-19 pandemic is creating challenges to manage staff ratios in clinical units. Nurse staffing level is an important indicator of the quality of care. This study aimed to identify any changes in the nurse staffing levels in the general wards of hospitals in Korea during the COVID-19 pandemic. The unit of analysis was the hospitals. This longitudinal study observed the quarterly change of the nurse staffing grades in 969 hospitals in 2020. The nurse staffing grades ranged from 1 to 7 according to the nurse-patient ratio measured by the number of patients (or beds) per nurse. The major dependent and independent variables were the change of nurse staffing grades and three quarterly observation points being compared with those during the 1st quarter (1Q) of 2020, respectively. A generalized linear model was used. Unexpectedly, the nurse staffing grades significantly improved (2Q: RR, 27.2%; 95% confidence interval (CI), 15.1-27.6; p < 0.001; 3Q: RR, 95% CI, 20.2%; 16.9-21.6; p < 0.001; 4Q: RR, 26.6%; 95% CI, 17.8-39.6; p < 0.001) quarterly, indicating that the nurse staffing levels increased. In the comparison of grades at 2Q, 3Q, and 4Q with those at 1Q, most figures improved in tertiary, general, and small hospitals (p < 0.05), except at 3Q and 4Q of general hospitals. In conclusion, the nurse staffing levels did not decrease, but nursing shortage might occur.

Review of National-Level Personal Health Records in Advanced Countries.

OBJECTIVES: This review article examines international examples of personal health records (PHRs) in advanced countries and discusses the implications of these examples for the establishment and utilization of PHRs in South Korea. METHODS: This article synthesized PHR case reports of Organization for Economic Co-operation and Development (OECD) member countries, the Global Digital Health Partnership website on PHRs, and patient portals of individual countries to review the status of PHR services. The concept and significance of PHRs were also discussed with respect to PHR utilization status in European Union and OECD countries. RESULTS: A review of international PHR services showed that the countries shared common points regarding the establishment of Electronic Health Records and national health information infrastructure. In addition, the countries provided services centered on primary healthcare institutions and public hospitals. However, promoting more positive participation and increasing the PHR acceptance rate requires workflow integration, including Electronic Medical Records, the provision of incentives, and the preparation of a supportive legal framework. CONCLUSIONS: South Korea is also conducting a national-level PHR project. Since the scope of PHRs is extensive and a wide range of PHR services must be connected, an extensive trial-and-error process will be necessary. A long-term strategy should be prepared, and necessary resources should be secured to establish national-level PHRs.

Automatic Pancreatic Cyst Lesion Segmentation on EUS Images Using a Deep-Learning Approach.

The automatic segmentation of the pancreatic cyst lesion (PCL) is essential for the automated diagnosis of pancreatic cyst lesions on endoscopic ultrasonography (EUS) images. In this study, we proposed a deep-learning approach for PCL segmentation on EUS images. We employed the Attention U-Net model for automatic PCL segmentation. The Attention U-Net was compared with the Basic U-Net, Residual U-Net, and U-Net++ models. The Attention U-Net showed a better dice similarity coefficient (DSC) and intersection over union (IoU) scores than the other models on the internal test. Although the Basic U-Net showed a higher DSC and IoU scores on the external test than the Attention U-Net, there was no statistically significant difference. On the internal test of the cross-over study, the Attention U-Net showed the highest DSC and IoU scores. However, there was no significant difference between the Attention U-Net and Residual U-Net or between the Attention U-Net and U-Net++. On the external test of the cross-over study, all models showed no significant difference from each other. To the best of our knowledge, this is the first study implementing segmentation of PCL on EUS images using a deep-learning approach. Our experimental results show that a deep-learning approach can be applied successfully for PCL segmentation on EUS images.

Analysis of Platforms and Functions of Mobile-Based Personal Health Record Systems.

OBJECTIVES: Little is known about the platforms and functionalities of mobile-based personal health record (PHR) applications. The objective of this study was to investigate these two features of PHR systems. METHODS: The unit of analysis was general hospitals with more than 100 beds. This study was based on a PHR survey conducted from May 1 to June 30, 2020 and the National Health Insurance administrative data as of March 31, 2020. The study considered the platform, Android and iPhone operation system (iOS), and types of functionalities of PHR systems. Among the 316 target hospitals, 103 hospitals had adopted PHR systems. A logistic regression analysis was used. RESULTS: This study found that 103 hospitals had adopted mobile-based PHR systems for their patients. Sixty-four hospitals (62.1%) were adopting both Android and iOS, but 36 (35.0%) and 3 (2.9%) hospitals were adopting Android only or iOS only, respectively. The PHR systems of hospitals adopting both platforms were more likely to have functions for viewing prescriptions, clinical diagnostic test results, and upcoming appointment status compared to those adopting a single platform (p < 0.001). The number of beds (odds ratio [OR] = 1.004; confidence interval [CI], 1.001-1.007; p = 0.0029) and the number of computed tomography systems (CTs) per 100 beds (OR = 6.350; CI, 1.006-40.084; p = 0.0493) were significantly associated with the adoption of both platforms. CONCLUSIONS: More than 60% of hospitals had adopted both Android and iOS platforms for their patients in Korea. Hospitals adopting both platforms had additional functionalities and significant association with the number of beds and CTs.

Association between Full Electronic Medical Record System Adoption and Drug Use: Antibiotics and Polypharmacy.

OBJECTIVES: We investigated associations between full Electronic Medical Record (EMR) system adoption and drug use in healthcare organizations (HCOs) to explore whether EMR system features such as electronic prescribing, medicines reconciliation, and decision support, might be related to drug use by using the relevant nation-wide data. METHODS: The study design was cross-sectional. Survey data of the level of adoption of EMR systems were collected for the Organization for Economic Co-operation and Development benchmarking information and communication technologies (ICT) study between November 2013 and January 2014, in Korea. Survey respondents were hospital chief information officers and medical practitioners in primary care clinics. From the national health insurance administrative dataset, two outcomes, the rate of antibiotic prescription and polypharmacy with ≥6 drugs, were extracted. RESULTS: We found that full EMR adoption showed a 16.1% lower antibiotic drug prescription than partial adoption including paper-based medical charts in the hospital only (p = 0.041). Between EMR adoption status and polypharmacy prescription, only those clinics which fully adopted EMR showed significant associations with higher polypharmacy prescriptions (36.9%, p = 0.001). CONCLUSIONS: The findings suggested that there might be some confounding effects present and sophisticated ICT may provide some benefits to the quality of care even with some mixed results. Although a negative relationship between full EMR system adoption and antibiotic drug use was only significant in hospitals, EMR system functions searching drugs or listing specific patients might facilitate antibiotic drug use reduction. Positive relationships between full EMR system adoption and polypharmacy rate in general hospitals and clinics, but not hospitals, require further research.

Clinical Decision Support Functions and Digitalization of Clinical Documents of Electronic Medical Record Systems.

OBJECTIVES: The objective of this study was to investigate the clinical decision support (CDS) functions and digitalization of clinical documents of Electronic Medical Record (EMR) systems in Korea. This exploratory study was conducted focusing on current status of EMR systems. METHODS: This study used a nationwide survey on EMR systems conducted from July 25, 2018 to September 30, 2018 in Korea. The unit of analysis was hospitals. Respondents of the survey were mainly medical recorders or staff members in departments of health insurance claims or information technology. This study analyzed data acquired from 132 hospitals that participated in the survey. RESULTS: This study found that approximately 80% of clinical documents were digitalized in both general and small hospitals. The percentages of general and small hospitals with 100% paperless medical charts were 33.7% and 38.2%, respectively. The EMR systems of general hospitals are more likely to have CDS functions of warnings regarding drug dosage, reminders of clinical schedules, and clinical guidelines compared to those of small hospitals; this difference was statistically significant. For the lists of digitalized clinical documents, almost 93% of EMR systems in general hospitals have the inpatient progress note, operation records, and discharge summary notes digitalized. CONCLUSIONS: EMRs are becoming increasingly important. This study found that the functions and digital documentation of EMR systems still have a large gap, which should be improved and made more sophisticated. We hope that the results of this study will contribute to the development of more sophisticated EMR systems.

Association between Electronic Medical Record System Adoption and Healthcare Information Technology Infrastructure.

OBJECTIVES: The objective of this study was to investigate the relationship between the level of Electronic Medical Record (EMR) system adoption and healthcare information technology (IT) infrastructure. METHODS: Both survey and various healthcare administrative datasets in Korea were used. The survey was conducted during the period from June 13 to September 25, 2017. The chief information officers of hospitals were respondents. Among them, 257 general hospitals and 273 small hospitals were analyzed. A logistic regression analysis was conducted using the SAS program. RESULTS: The odds of having full EMR systems in general hospitals statistically significantly increased as the number of IT department staff members increased (odds ratio [OR] = 1.058, confidence interval [CI], 1.003-1.115; p = 0.038). The odds of having full EMR systems was significantly higher for small hospitals that had an IT department than those of small hospitals with no IT department (OR = 1.325; CI, 1.150-1.525; p < 0.001). Full EMR system adoption had a positive relationship with IT infrastructure in both general hospitals and small hospitals, which was statistically significant in small hospitals. The odds of having full EMR systems for small hospitals increased as IT infrastructure increased after controlling the covariates (OR = 1.527; CI, 1.317-4.135; p = 0.004). CONCLUSIONS: This study verified that full EMR adoption was closely associated with IT infrastructure, such as organizational structure, human resources, and various IT subsystems. This finding suggests that political support related to these areas is indeed necessary for the fast dispersion of EMR systems into the healthcare industry.

Association between Health Information Technology and Case Mix Index.

OBJECTIVES: Health information technology (IT) can assist healthcare providers in ordering medication and adhering to guidelines while improving communication among providers and the quality of care. However, the relationship between health IT and Case Mix Index (CMI) has not been thoroughly investigated; therefore, this study aimed to clarify this relationship. METHODS: To examine the effect of health IT on CMI, a generalized estimation equation (GEE) was applied to two years of California hospital data. RESULTS: We found that IT was positively associated with CMI, indicating that increased IT adoption could lead to a higher CMI or billing though DRG up-coding. This implies that hospitals' revenue could increase around $40,000 by increasing IT investment by 10%. CONCLUSIONS: The positive association between IT and CMI implies that IT adoption itself could lead to higher patient billings. Generally, a higher CMI in a hospital indicates that the hospital provides expensive services with higher coding and therefore receives more money from patients. Therefore, measures to prevent upcoding through IT systems should be implemented.