Journal of Health Management and Informatics
Volume:9 Issue: 1, Jan 2022

One of the problems in the oral health is lack of coordination and misalignmentof teeth, so orthodontic treatments were performed to treat this issue. This treatment is timeconsuming and the need to document the processes is strongly felt. Dental informationmanagement can improve the quality of dental care and reduce the costs by preventing reprocedures.To manage the orthodontics information, the present study aimed to review aminimum orthodontics data set.

This review study was performed using the guidelines and related articlesconducted from 2001 to September 2021 through scientific databases and search engine(PubMed, ProQuest, Wiley, Google Scholar, Scopus and Science Direct) using keywordsincluding (minimum data set, health information management, dental records, orthodontics,orthodontic records, malocclusion, and maxillofacial malformations).

According to studies, demographic data, general evaluation, extra and intra oralexamination, functional examination, temporomandibular joint condition, cephalometricdata, cast analysis, evaluation data and treatment plan, progress note, unit summary, dentalhistory, and type of orthodontic treatment have suggested as minimum orthodontics dataset.

Developing minimum dataset as a standard approach for better understandingand comparing the data is necessary in the health information management. The presentstudy proposes a minimum data set for implementation of orthodontic information systemin Iran. This system will play an important role in improving the oral health indicators of thecommunity and provide access to an electronic health record.

The lockdown policy imposed in response to the COVID-19 pandemic hasrestricted various businesses, including trading, inter-state travel for purchasing/selling andsupplying goods and services, hospitality industries, and state revenue generation. The studyassessed the impacts of COVID-19 lockdown on the economy of a Nigerian low-resourcecommunity. This study was a descriptive cross-sectional survey conducted in Ado-Odo Otalocal government area (LGA) of Ogun State, Nigeria, using a structured questionnaire tocollect data on the economic impacts of COVID-19 lockdown on383 participants aged 20 to60 years in January and February. Data analysis was done using IBM-SPSS version 25. During the lockdown, 26.1% of the respondents lost their jobs, 34.5% experiencedsalary cuts, and only 6.5% got regular salaries. More than half (53.8%) of participants could notmeet their basic needs. All respondents (100.0%) stated that food prices and other necessitieswere higher during the lockdown than before. The odds of losing jobs were 18.74 [95%CI:6.20–56.60; P<0.001] and 4.32 [95%CI: 1.50–12.43; P<0.001] times higher among the staff ofprivate organizations and those doing personal businesses than among government workers.The rate of clients/customers loss was 15.21 [95%CI: 7.59–30.51; P<0.001) and 7.07 [95%CI:3.26–15.34; P<0.001] higher among self-employed and private companies than governmentestablishments. Every worker should enjoy job security to mitigate the job and income lossduring a crisis. Loans and grants should be available for small businesses, particularly toovercome the problem. Food security should be provided by subsidizing goods and providingsupports to help meet the daily needs of housholdsduring emergencies.

Digital epidemiology is introduced as a major aspect of epidemiology; itssources are digital data and it uses spaces such as Google, YouTube and Twitter as databases.In the recent Covid-19 pandemic, the use of digital epidemiology, as an early warning system,has been considered. This study aimed to investigate the context of Google Trend as an earlywarning system in the study of coronavirus outbreaks in Iran. The coronavirus epidemic in Iran started on February 24, 2020, and with somedifferences to consider the rumors in the community, we consider the date before theannouncement of all by February 16, 2020 until November 16, 2021. We searched usingkeywords related to symptoms such as “fever”, “cough” and “sore throat” and the keyword“corona symptoms”; information was extracted and entered in Microsoft Excel and thekeyword chart was drawn according to the date of each wave. Spearman correlation test wasperformed to find the correlation between keywords in SPSS version 18. The trend chart of the keywords “fever”, “cough” and “sore throat” and the keyword“corona symptoms” in different waves of coronavirus in Iran showed an increase in keywordsearches before the onset of the corona epidemic wave. Spearman correlation coefficientbetween sore throat and fever was 0.645, sore throat and cough 0.775, sore throat and coronasymptoms 0.684, between fever and cough keywords 0.435, fever and corona symptoms 0.779and between keyword cough and corona symptoms 0.503. In all these coefficients, the level oferror of the first type was 0.05 significant (P<0.001) Google Trend, a digital epidemiology tool, can be used as an effective earlywarning system to control the corona pandemic, and this field of epidemiological knowledgewith all its limitations needs further research.

Electronic medical record leads to effective information management. One ofthe most important sections of electronic medical records is the patient admission module.The aim of this study was to develop and evaluate the patient admission module in IntensiveCare Unit. This developmental-applied study was conducted in 2021 in 3 steps: 1. Determiningthe requirements, 2. Designing, developing, and implementing, and 3. Evaluating usability.In the first step, we did the literature review and asked for the expert panel’s opinion; in thesecond step, we used word, and Reactjs, Expressjs programming language, and Mongodbdatabase and Windows server; in the third step, the USE standard questionnaire was used. Module requirements were classified into two categories: functional and nonfunctionalrequirements. Functional requirements address software quality features, and nonfunctionalrequirements include general requirements, demographic information, and clinicalinformation. Demographic information was classified into two main categories: patient’sdemographic information and documented physician information. Clinical information (287data elements) in 13 main categories included the past history, vital signs, nervous system,respiratory system, cardiovascular system, genitourinary system, gastrointestinal system,hematology, integumentary system, infectious, antimicrobial drugs, problem list, and plan.Also, the results of usability evaluation showed that 87% of the physicians agreed with theuse of this module. Given the trend towards e-health in Iran, the use of electronic medical recordadmission module in intensive care units can have a significant impact on the completecollection of admission data.

Health-related quality of life (HRQOL) considerably decreases after injured.This study aimed to assess and compare the quality of life during a three years’ period afterinjury and hospital stay among the injured patients admitted in an Intensive Care Unit (ICU)for 24 hours at least with non-ICU injured patients as the control group. In this cross-sectional study, 204 injured patients treated by the injured team ofShahid Rajaee Injured Center of Shiraz, Iran, were evaluated from January 2019 to December2020. HRQOL was measured using the Medical Outcomes Study Short Form 36 (SF-36).Patients were called and asked to answer the SF-36 questionnaire according to the currentcondition. SPSS was used to analyze the data. The mean age of the ICU and non-ICU patients was 34.34 and 37.68 years,respectively. The majority of patients in both ICU and non-ICU groups were male (83.5%,88.1%) and under 60 years of age (91.3%, 92.1%). The injury severity score (ISS) was markedas critical in 66.99% of ICU patients. The mean SF-36 scores in ICU patients were lowerthan the similar indices in non-ICU patients in all dimensions (P<0.001) Except for socialfunctioning, a non-significant difference was observed between the ICU and non-ICUpatients for only two subscales. Health-related quality of life among the patients with sustained severe injurieswho were admitted to ICU decreased considerably after three years follow up. Given thatcertain factors can help identify patients in need of sufficient pain management, adequateinformation can help injury specialist teams for follow-ups.

Forecasting health status of populations aims to explain the most likely futuretrends in health, such as the life expectancy trend. Life expectancy has grown notably duringthe past 150 years. Extended survival leads to population aging that is a world-changingevent. Planning and investing in health and social services require anticipating future lifeexpectancy and the corresponding drivers. As a developing country, Iran has experienced animprovement in health and longevity. This study aims to model and forecast life expectancy atbirth up to 2035 and review the economic and policy implications of aging in Iran. This study presents a dynamic simulation modeling of life expectancy and proposesa system dynamics model to give decision-makers an understanding of the interactionsbetween different variables. The equations in the model are estimated using least-squaresalgorithms. The data are derived from the websites of “World Bank”, “Our World in Data”, and“United Nations Development Program.” The computerized simulation results forecast that total life expectancy increases byabout 4.5 years from 2018 to 2035, reaching 81.06. Although improvement in life expectancy is a success and a key goal of a healthsystem, it also suggests a rapid pace of aging in Iran with many social and economic challengesin managing the upcoming situations. However, executing appropriate policies can convertsuch threats into opportunities.

A correct understanding of the level of readiness is the key to success inimplementing an electronic health record. The aim of this study was to assess the readiness ofthe hospitals affiliated to Shiraz University of Medical Sciences for implementing electronichealth records based on the tools of the California Academy of Family Physicians tool. This descriptive-applied study was performed in 2021 in six hospitals of ShirazUniversity of Medical Sciences equipped with hospital information system in Iran. Data werecollected through interviews with managers, information technology experts, and hospitalinformation system experts through checklists in 5 areas of management, finance and budget,operational, technology, and organizational alignment. The results showed that in the assessment of general readiness, Nemazi hospital with38% and Amir hospital with 37% readiness were more suitable and moderately preparedthan other hospitals in moving towards the implementation of electronic health records, andthe rest of the hospitals did not have the necessary readiness. In management, finance andbudget, and operational capacity, most hospitals were in a weak position between 10% -30%and were not ready at all. According to the results, it is recommended that measures such as leadershipmeasures, participation and support of managers, recruitment of information technologyspecialists, budget allocation, justification of return investment, continuing educationprograms, user participation, and process support should be taken to increase the mentionedcapabilities and readiness of hospitals in the implementation of electronic health records.

The worker shortage is a critical and multifaceted challenge in the health systems (1, 2). Nevertheless, after the outbreak of the COVID-19 pandemic in 2019, the demand for healthcare workers in the hospital and healthcare sector has become more intense; the worker shortage has reached a warning threshold (3). The imbalance between supply and demand workers in health systems, on the one hand, and the increasing requests for leave of absences, a behavioral response to COVID-19, on the other hand, have exacerbated the crisis. Evidence shows that the demand for leave has increased among healthcare workers (4). Since the COVID-19 pandemic, in addition to the usual reasons for requesting leave, some risks have exacerbated this behavior; these risks include fear of contracting infectious diseases and transmission of the virus to their family and friends, risk of increase in the patient violence (5), risk of experiencing guilt following the death of a patient (6), and risk of excessive work demand. While such leaves lead to a break in the chain of COVID-19, as a hidden aspect of absenteeism, they can result in individual and organizational costs such as productivity losses, turnover, presenteeism, economic cost of providing paid sick leave, and reduction of the quality of health services. Increasing demand for leave has intensified the nursing shortage in healthcare and that creates an undesirable and stressful workplace environment (7).Leave of absence, as a right for workers, is recognized in most countries, not only when the economy is open, but also during a lockdown (8). Despite the conflict between the need to reduce the spread of the COVID-19 and the need for human contact, especially in healthcare and hospitality sector, it is necessary to identify these factors; thereare key policies that can benefit both. Regardless of the type of leave (paid/unpaid) and the reasons it (a worker’s physical or mental health problems, etc.), it is complex and explained by individual, occupational and organizational factors (3, 4, 9-13). The main aim of this letter to editor is to introduce the most important drivers of leave of absence and suggest critical policies to manage them. For this purpose, the research literature was reviewed. Table 1 shows the factors affecting the number of workers’ leave and policies to manage them.