Potentially inappropriate medication prescribing based on 2019 Beers criteria and the impact of pharmacist intervention in elderly patients with kidney diseases: A report from Iran.

Background and Aims: A potentially inappropriate medication (PIM) is a pharmaceutical agent that poses a greater risk of harm than potential benefit to elderly patients. This study aimed to detect PIMs and their risk factors in hospitalized elderly patients with kidney disease. Methods: This cross-sectional study assessed medication orders of elderly patients (≥65 years old) with kidney diseases admitted to the hospital. In the first 6 months, we retrospectively evaluated all medications to identify PIMs according to the 2019 Beers criteria. In the second phase, a clinical pharmacist prospectively evaluated all medications and suggested modifications as needed. Data were analyzed to determine risk factors for prescribing PIMs. Results: Based on our evaluation of 258 patients, we observed that the utilization of PIMs was prevalent among the study population. Of the total patients evaluated, 273 instances of PIM use were identified, with only 23.3% of patients not having any PIMs. Notably, proton pump inhibitors and benzodiazepines were the most frequently prescribed PIMs. The risk of experiencing a PIM was significantly amplified by a higher degree of polypharmacy, with odds approximately 2.68 times higher (p < 0.01). Several factors were found to be associated with an increased likelihood of having a PIM, including being male, undergoing hemodialysis, having chronic kidney disease or other comorbidities, and having an extended hospital stay. The second phase of study, in terms of addressing these issues, physicians adhered to 67.5% of the 120 recommendations made by pharmacists regarding the discontinuation of PIM usage. Conclusion: High prevalence of PIMs was detected in our study population. Preventing medication-associated harms in the elderly can reduce the financial burden imposed on healthcare systems. Therefore, routine evaluation of medications with clinical pharmacists and/or implementation of computerized medication decision support systems is recommended to prevent PIMs use.

Potential drug-drug interactions in a multi-center study of death cases of COVID-19: The significance of appropriate drug choice.

OBJECTIVES: The prevalence, types, severity, risk ratings, and common pairs of involved drugs, and the most important potential drug-drug interactions (pDDIs) in coronavirus disease 2019 (-COVID-19) deceased cases were evaluated. MATERIALS AND METHODS: We reviewed the medical records of 157 confirmed COVID-19 deceased cases hospitalized in 27 province-wide hospitals. Patients' demographics and clinical data (including comorbidities, vital signs, length of in-hospital survival, electrocardiograms (ECGs), medications, and lab test results) were extracted. The online Lexi-interact database and Stockley's drug interactions reference were used to detect pDDIs retrospectively. The QTc interval and total Tisdale risk score were also calculated. Descriptive analysis, analysis of variance, Fisher exact test, and multivariate analysis were conducted for data analysis. RESULTS: Of 157 study cases, 63% were male, had a mean age of 68 years, and 55.7% had one or more underlying diseases. All patients had polypharmacy, with 69.2% having ≥ 15 drugs/day. We detected 2,416 pDDIs in patients' records, of which 658 (27.2%) were interactions with COVID drugs. Lopinavir/ritonavir among -COVID drugs and fentanyl among non-COVID drugs were commonly involved in the interactions. pDDIs was significantly higher in the polypharmacy group of ≥ 15 medications (p < 0.001). A majority (83%) had received drug(s) with the QTc prolongation effect, of whom 67% had actual QTc prolongations in their ECGs. The regression analysis showed that by increasing 6.7% in polypharmacy, one day increase in-hospital survival can be expected. Moreover, an increase of 2.3% in white blood cells or 10.5% in serum potassium level decreased in-hospital survival by 1%. CONCLUSION: The findings underscored the importance of careful drug choice, especially in the hectic search for early treatments in pandemics of novel diseases. Close monitoring of patients' drug choice is warranted for reducing pDDIs and their adverse effects in any new disease outbreak.

A qualitative study of factors influencing ePHR adoption by caregivers and care providers of Alzheimer's patients: An extension of the unified theory of acceptance and use of technology model.

Background and Aims: As the nowadays provision of many healthcare services relies on technology, a better understanding of the factors contributing to the acceptance and use of technology in health care is essential. For Alzheimer's patients, an electronic personal health record (ePHR) is one such technology. Stakeholders should understand the factors affecting the adoption of this technology for its smooth implementation, adoption, and sustainable use. So far, these factors have not fully been understood for Alzheimer's disease (AD)-specific ePHR. Therefore, the present study aimed to understand these factors in ePHR adoption based on the perceptions and views of care providers and caregivers involved in AD care. Methods: This qualitative study was conducted from February 2020 to August 2021 in Kerman, Iran. Seven neurologists and 13 caregivers involved in AD care were interviewed using semi-structured and in-depth interviews. All interviews were conducted through phone contacts amid Covid-19 imposed restrictions, recorded, and transcribed verbatim. The transcripts were coded using thematic analysis based on the unified theory of acceptance and use of technology (UTAUT) model. ATLAS.ti8 was used for data analysis. Results: The factors affecting ePHR adoption in our study comprised subthemes under the five main themes of performance expectancy, effort expectancy, social influence, facilitating conditions of the UTAUT model, and the participants' sociodemographic factors. From the 37 facilitating factors and 13 barriers identified for ePHR adoption, in general, the participants had positive attitudes toward the ease of use of this system. The stated obstacles were dependent on the participants' sociodemographic factors (such as age and level of education) and social influence (including concern about confidentiality and privacy). In general, the participants considered ePHRs efficient and useful in increasing neurologists' information about their patients and managing their symptoms in order to provide better and timely treatment. Conclusion: The present study gives a comprehensive insight into the acceptance of ePHR for AD in a developing setting. The results of this study can be utilized for similar healthcare settings with regard to technical, legal, or cultural characteristics. To develop a useful and user-friendly system, ePHR developers should involve users in the design process to take into account the functions and features that match their skills, requirements, and preferences.

Information Adequacy in Histopathology Request Forms: A Milestone in Making a Communication Bridge Between Confusion and Clarity in Medical Diagnosis.

OBJECTIVE: Information contained in request forms for histopathological examinations plays a critical role in the microscopic interpretation of tissue changes. Despite its importance, studies have shown inadequacies in the information communicated by clinicians. This study aimed to determine how well the necessary information is provided on the histopathology request forms and to compare its variability among different departments of a hospital. MATERIAL AND METHOD: A retrospective, 3-month, cross-sectional study was conducted to evaluate all consecutive histopathology request forms received from different departments of a tertiary, academic hospital for three months, regarding the documentation of 12 criteria. RESULTS: None of the 2040 requests received had all the required items. Four items of specimen description, laboratory and imaging findings, and physician contact number were available only in less than 12.5% (range between 0.05 to 12.45%) of the requests. However, four other items of patient name and contact number, physician name, and anatomical site of the lesion were documented in more than 90%. The median number of the documented items was the highest in the surgery and orthopedics (9 items) and the lowest in the pulmonology department (7 items). Comparison between departments showed that the documentation of items in the surgery department were significantly better than that of the ENT, urology, and internal medicine departments (p < 0.001). Also, the internal medicine department was significantly different from all other departments (p < 0.001) except neurosurgery (p=0.88). CONCLUSION: Our results point out a serious gap in the adequacy of pathology request forms, especially clinical items. Given the implication of such information to ensure patient safety, further studies are recommended to evaluate the impact of educational and supportive computerized interventions such as clinician education and barcoding and specimen tracking systems to help fill in the required items completely.

Clinical Breast Cancer Registry of IR. Iran (CBCR-IR): Study Protocol and First Results.

BACKGROUND: Breast cancer (BC), as a significant global health problem, is the most common cancer in women. Despite the importance of clinical cancer registries in improving the quality of cancer care and cancer research, there are few reports on them from low- and middle-income countries. We established a multicenter clinical breast cancer registry in Iran (CBCR-IR) to collect data on BC cases, the pattern of care, and the quality-of-care indicators in different hospitals across the country. METHODS: We established a clinical cancer registry in 12 provinces of Iran. We defined the organizational structure, developed minimal data sets and data dictionaries, verified data sources and registration processes, and developed the necessary registry software. During this registry, we studied the clinical characteristics and outcomes of patients with cancer who were admitted from 2014 onwards. RESULTS: We registered 13086 BC cases (7874 eligible cases) between 1.1.2014 and 1.1.2022. Core needle biopsy from the tumor (61.25%) and diagnostic mammography (68.78%) were the two most commonly used diagnostic methods. Stage distribution was 2.03% carcinoma in situ, 12% stage I, 44.65% stage II, 21.32% stage III, and 4.61% stage IV; stage information was missing in 1532 patients (19.46%). Surgery (95.01%) and chemotherapy (79.65%) were the most common treatments for all patients. CONCLUSION: The information provided by this registry can be used to evaluate and improve the quality of care for BC patients. It will be scaled up to the national level as an important resource for measuring quality of care and conducting clinical cancer research in Iran.

Objectives, Outcomes, Facilitators, and Barriers of Telemedicine Systems for Patients with Alzheimer's Disease and their Caregivers and Care Providers: A Systematic Review.

BACKGROUND: Alzheimer's disease is an extremely expensive chronic disease, which is rapidly becoming a major cause of mortality in adults. For over two decades, telemedicine has been used to assist patients and their caregivers to manage this disease. The present study aimed to evaluate the objectives, outcomes, facilitators, and barriers influencing the use of telemedicine systems for patients with Alzheimer's disease and their caregivers and care providers. METHODS: In this systematic review, we searched for the original articles published in databases such as PubMed, Web of Science, and Scopus until November 2021 using relevant keywords. A qualitative content analysis was performed the based on the theory of planned behavior and the health belief model using the ATLAS.ti software. RESULTS: In total, 1191 articles were identified, and 60 articles were included in this study. While having different objectives, most of the studies compared telemedicine systems to in-person visits (21.43%) and assessed the feasibility of the implemented method (16.07%). The overall outcomes of telemedicine in the articles were classified as cost-effectiveness (e.g., reduced commute, fuel, and time to access care), clinical outcomes (e.g., lower anxiety, stress, and depression), and patient, caregiver, and healthcare provider satisfaction. In total, 19 facilitators and 12 barriers influencing the use of telemedicine for patients with Alzheimer's disease and their caregivers were identified. CONCLUSION: According to the results, telemedicine systems could be implemented for various reasons. Developing a clear framework of the drivers and barriers before the implementation of these systems could improve decision-making prior to the design and implementation of telemedicine systems.

Patient empowerment through a user-centered design of an electronic personal health record: a qualitative study of user requirements in chronic kidney disease.

BACKGROUND: To improve chronic disease outcomes, self-management is an effective strategy. An electronic personal health record (ePHR) is a promising tool with the potential to support chronic patient's education, counseling, and self-management. Fitting ePHRs within the daily practices of chronic care providers and chronic patients requires user-centered design approaches. We aimed to understand users' needs and requirements in chronic kidney disease (CKD) care to consider in the design of an ePHR to facilitate its implementation, adoption, and use. METHODS: A qualitative study was conducted in a major Iranian nephrology center including inpatient and outpatient settings in 2019. We conducted 28 semi-structured interviews with CKD patients, nurses, and adult nephrologists. To confirm or modify the requirements extracted from the interviews, a focus group was also held. Data were analyzed to extract especially those requirements that can facilitate implementation, adoption, and sustained use based on the PHR adoption model and the unified theory of acceptance and use of technology. RESULTS: Participants requested an ePHR that provides access to up to date patient information, facilitates patient-provider communication, and increases awareness about patient individualized conditions. Participants expected a system that is able to cater to low patient e-health literacy and high provider workload. They requested the ePHR to include purposeful documentation of medical history, diagnostic and therapeutic procedures, tailored educational content, and scheduled care reminders. Messaging function, tailored educational content to individual patients' conditions, and controlled access to information were highly valued in order to facilitate its implementation, adoption, and use. CONCLUSIONS: We focused on the ePHR's content and functionalities in the face of facilitators and/or barriers envisioned for its adoption in nephrology care. Designers and implementers should value CKD patients' needs and requirements for self-management such as providing personalized education and counseling (on the basis of their condition and risk factors), health literacy, and disease progression levels. The socio-technical aspects of care also need further attention to facilitate ePHR's adoption.

Prediction of future gene expression profile by analyzing its past variation pattern.

A number of initial Hematopoietic Stem Cells (HSC) are considered in a container that are able to divide into HSCs or differentiate into various types of descendant cells. In this paper, a method is designed to predict an approximate gene expression profile (GEP) for future descendant cells resulted from HSC division/differentiation. First, the GEP prediction problem is modeled into a multivariate time series prediction problem. A novel method called EHSCP (Extended Hematopoietic Stem Cell Prediction) is introduced which is an artificial neural machine to solve the problem. EHSCP accepts the initial sequence of measured GEPs as input and predicts GEPs of future descendant cells. This prediction can be performed for multiple stages of cell division/differentiation. EHSCP considers the GEP sequence as time series and computes correlation between input time series. Two novel artificial neural units called PLSTM (Parametric Long Short Term Memory) and MILSTM (Multi-Input LSTM) are designed. PLSTM makes EHSCP able to consider this correlation in output prediction. Since there exist thousands of time series in GEP prediction, a hierarchical encoder is proposed that computes this correlation using 101 MILSTMs. EHSCP is trained using 155 datasets and is evaluated on 39 test datasets. These evaluations show that EHSCP surpasses existing methods in terms of prediction accuracy and number of correctly-predicted division/differentiation stages. In these evaluations, number of correctly-predicted stages in EHSCP was 128 when as many as 8 initial stages were given.

Evaluation of blended medical education from lecturers' and students' viewpoint: a qualitative study in a developing country.

BACKGROUND: To improve the quality of education, many academic medical institutions are investing in the application of blended education to support new teaching and learning methods. To take necessary measures to implement the blended learning smoothly, and to achieve its goals, we aimed to identify its strengths, weaknesses, opportunities, and threats (SWOT) from its key users' viewpoints. METHODS: A qualitative study consisting of 24 interviews with lecturers and students and document analysis was conducted at Urmia University of Medical Sciences, in Iran, in 2018. The SWOT framework was used to analyze the data. RESULTS: The most important strengths were the promotion of lecturer-student interactions, the focus on students' learning needs and self-learning, and problem-solving skills. The supports of university executives, alignment with the national health education transformation plan, and access to the shared infrastructures of the national virtual medical science university were opportunities to facilitate its implementation. However, this endeavor had weaknesses such as bottlenecks in technical, organizational, and human resource infrastructures and lack of culture readiness. The threats envisioned for its maintenance were its dependency on the education transformation plan and the lack of an independent e-learning center for better planning and support services, lack of proper evaluation and supervision of virtual activities, and insufficiency of the privileges considered for users. CONCLUSIONS: One of the important implications of this study is that different aspects surrounding blended learning might work as a double-edge sword from time to time, which requires a thorough overview. While retaining the strengths and enjoying the opportunities in such interventions, the weaknesses should be recognized and threats are faced and addressed. Therefore, if the SWOT items are considered mindfully, they can help to adopt the right implementation strategies to reap full benefits.

Translation of evidence into kidney transplant clinical practice: managing drug-lab interactions by a context-aware clinical decision support system.

BACKGROUND: Drug-laboratory (lab) interactions (DLIs) are a common source of preventable medication errors. Clinical decision support systems (CDSSs) are promising tools to decrease such errors by improving prescription quality in terms of lab values. However, alert fatigue counteracts their impact. We aimed to develop a novel user-friendly, evidence-based, clinical context-aware CDSS to alert nephrologists about DLIs clinically important lab values in prescriptions of kidney recipients. METHODS: For the most frequently prescribed medications identified by a prospective cross-sectional study in a kidney transplant clinic, DLI-rules were extracted using main pharmacology references and clinical inputs from clinicians. A CDSS was then developed linking a computerized prescription system and lab records. The system performance was tested using data of both fictitious and real patients. The "Questionnaire for User Interface Satisfaction" was used to measure user satisfaction of the human-computer interface. RESULTS: Among 27 study medications, 17 needed adjustments regarding renal function, 15 required considerations based on hepatic function, 8 had drug-pregnancy interactions, and 13 required baselines or follow-up lab monitoring. Using IF & THEN rules and the contents of associated alert, a DLI-alerting CDSS was designed. To avoid alert fatigue, the alert appearance was considered as interruptive only when medications with serious risks were contraindicated or needed to be discontinued or adjusted. Other alerts appeared in a non-interruptive mode with visual clues on the prescription window for easy, intuitive notice. When the system was used for real 100 patients, it correctly detected 260 DLIs and displayed 249 monitoring, seven hepatic, four pregnancy, and none renal alerts. The system delivered patient-specific recommendations based on individual lab values in real-time. Clinicians were highly satisfied with the usability of the system. CONCLUSIONS: To our knowledge, this is the first study of a comprehensive DLI-CDSS for kidney transplant care. By alerting on considerations in renal and hepatic dysfunctions, maternal and fetal toxicity, or required lab monitoring, this system can potentially improve medication safety in kidney recipients. Our experience provides a strong foundation for designing specialized systems to promote individualized transplant follow-up care.

Barriers to patient, provider, and caregiver adoption and use of electronic personal health records in chronic care: a systematic review.

BACKGROUND: Electronic personal health records (ePHRs) are defined as electronic applications through which individuals can access, manage, and share health information in a private, secure, and confidential environment. Existing evidence shows their benefits in improving outcomes, especially for chronic disease patients. However, their use has not been as widespread as expected partly due to barriers faced in their adoption and use. We aimed to identify the types of barriers to a patient, provider, and caregiver adoption/use of ePHRs and to analyze their extent in chronic disease care. METHODS: A systematic search in Medline, PubMed, Science Direct, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Central Register of Controlled Trials, and the Institute of Electrical and Electronics Engineers (IEEE) database was performed to find original studies assessing barriers to ePHR adoption/use in chronic care until the end of 2018. Two researchers independently screened and extracted data. We used the PHR adoption model and the Unified Theory of Acceptance and Use of Technology to analyze the results. The Mixed Methods Appraisal Tool (MMAT) version 2018 was used to assess the quality of evidence in the included studies. RESULTS: Sixty publications met our inclusion criteria. Issues found hindering ePHR adoption/use in chronic disease care were associated with demographic factors (e.g., patient age and gender) along with key variables related to health status, computer literacy, preferences for direct communication, and patient's strategy for coping with a chronic condition; as well as factors related to medical practice/environment (e.g., providers' lack of interest or resistance to adopting ePHRs due to workload, lack of reimbursement, and lack of user training); technological (e.g., concerns over privacy and security, interoperability with electronic health record systems, and lack of customized features for chronic conditions); and chronic disease characteristics (e.g., multiplicities of co-morbid conditions, settings, and providers involved in chronic care). CONCLUSIONS: ePHRs can be meaningfully used in chronic disease care if they are implemented as a component of comprehensive care models specifically developed for this care. Our results provide insight into hurdles and barriers mitigating ePHR adoption/use in chronic disease care. A deeper understating of the interplay between these barriers will provide opportunities that can lead to an enhanced ePHR adoption/use.

Preventing potential drug-drug interactions through alerting decision support systems: A clinical context based methodology.

BACKGROUND: The effectiveness of the clinical decision support systems (CDSSs) is hampered by frequent workflow interruptions and alert fatigue because of alerts with little or no clinical relevance. In this paper, we reported a methodology through which we applied knowledge from the clinical context and the international recommendations to develop a potential drug-drug interaction (pDDI) CDSS in the field of kidney transplantation. METHODS: Prescriptions of five nephrologists were prospectively recorded through non-participatory observations for two months. The Medscape multi-drug interaction checker tool was used to detect pDDIs. Alongside the Stockley's drug interactions reference, our clinicians were consulted with respect to the clinical relevance of detected pDDIs. We performed semi-structured interviews with five nephrologists and one informant nurse. Our clinically relevant pDDIs were checked with the Dutch "G-Standard". A multidisciplinary team decided the design characteristics of pDDI-alerts in a CDSS considering the international recommendations and the inputs from our clinical context. Finally, the performance of the CDSS in detecting DDIs was evaluated iteratively by a multidisciplinary research team. RESULTS: Medication data of 595 patients with 788 visits were collected and analyzed. Fifty-two types of interactions were most common, comprising 90% of all pDDIs. Among them 33 interactions (comprising 77% of all pDDIs) were rated as clinically relevant and were included in the CDSS's knowledge-base. Of these pDDIs, 73% were recognized as either pseudoduplication of drugs or not a pDDI when checked with the Dutch G-standard. Thirty-three alerts were developed and physicians were allowed to customize the appearance of pDDI-alerts based on a proposed algorithm. CONCLUSION: Clinical practice contexts should be studied to understand the complexities of clinical work and to learn the type, severity and frequency of pDDIs. In order to make the alerts more effective, clinicians' points of view concerning the clinical relevance of pDDIs are critical. Moreover, flexibility should be built into a pDDI-CDSS to allow clinicians to customize the appearance of pDDI-alerts based on their clinical context.

Predicting the function of transplanted kidney in long-term care processes: Application of a hybrid model.

BACKGROUND: A tool that can predict the estimated glomerular filtration rate (eGFR) in routine daily care can help clinicians to make better decisions for kidney transplant patients and to improve transplantation outcome. In this paper, we proposed a hybrid prediction model for predicting a future value for eGFR during long-term care processes. METHODS: Longitudinal, historical data of 942 transplant patients who received a kidney between 2001 and 2016 at Urmia kidney transplant center was used to develop a hybrid model. The model was based on three primary models: multi-layer perceptron (MLP), linear regression (LR), and a model that predicted a smoothed value of eGFR. The hybrid model used at-hand, longitudinal data of physical examinations and laboratory test values available at each visit. Two different datasets, a generalized dataset (GData) and a personalized dataset (PData), were created. Then, in both datasets, two data subsets of development and validation were created. For prediction, all records related to the fourth to tenth previous visits of patients in time order from the target date, i.e., window size (WS) = 4-10, were used. The performance of the models was evaluated using Mean Square Error (MSE) and Mean Absolute Error (MAE). The differences between the models were evaluated with the F-test and the Akaike Information Criterion (AIC). RESULTS: The datasets contained 35,066 records, totally. The GData contained 26,210 and 8856 records and the PData had 24,079 and 9103 records in the development and validation datasets, respectively. In the hybrid model, the MSE and MAE were 153 and 8.9 in the GData, and 113 and 7.5 in the PData, respectively. The model performance improved using a wider WS of historical records (from 4 to 10). When the WS of ten was used the MSE and MAE declined to 141 and 8.5 in the GData and to 91 and 6.9 in the PData, respectively. In both datasets, the F-test showed that the hybrid model was significantly different from other models. The AIC showed that the hybrid model had a better performance than that of others. CONCLUSIONS: The hybrid model can predict a reliable future value for eGFR. Our results showed that longitudinal covariates help the models to produce better results. Smoothing eGFR values and using a personalized dataset to develop the models also improved the models' performances. They can be considered as a step forward towards personalized medicine.

A dynamic model for predicting graft function in kidney recipients' upcoming follow up visits: A clinical application of artificial neural network.

BACKGROUND: Predicting the function of transplanted kidneys would help clinicians in individualized medical interventions. We aimed to develop and validate a predictive tool for a future value of estimated glomerular filtration rate (eGFR) at upcoming visits. METHODS: We used static and time-dependent covariates as inputs of artificial neural network based prediction models for predicting an eGFR value for an upcoming visit. We included 675 kidney recipients, who received transplant in the Urmia kidney transplant center in 2001-2013 and were longitudinally cared for in 2001-2017. The first 75% of records of longitudinal data of each patient were used to develop the prediction models and the remaining last 25% for evaluating its performance. Models' performances were evaluated by Mean Square Error (MSE) and Mean Absolute Error (MAE). RESULTS: The development and validation datasets included 18,773 and 7038 records of historical data, respectively. The most accurate model included 3 static covariates of recipients' gender and donors' age and gender as well as 11 dynamic covariates of recipients including current age, time since transplant, serum creatinine, fasting blood sugar, weight and blood pressures available at each visit time. The performance of prediction models in the validation cohort was improved when history window of time dependent variables' recent values was increased from 1 to 10 (an MSE decline from 161 to 99). CONCLUSIONS: Our best performed model is able to dynamically predict a future eGFR value for kidney recipients' upcoming visits. Integrating such a clinical tool into daily workflow of outpatient clinics can potentially support clinicians in optimal and individualized decision makings.

Impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay, and mortality in intensive care units: a systematic review and meta-analysis.

OBJECTIVE: To conduct a systematic review and meta-analysis of the impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay (LOS), and mortality in intensive care units (ICUs). METHODS: We searched for English-language literature published between January 2000 and January 2016 using Medline, Embase, and CINAHL. Titles and abstracts of 586 unique citations were screened. Studies were included if they: (1) reported results for an ICU population; (2) evaluated the impact of CPOE or the addition of CDSSs to an existing CPOE system; (3) reported quantitative data on medication errors, ICU LOS, hospital LOS, ICU mortality, and/or hospital mortality; and (4) used a randomized controlled trial or quasi-experimental study design. RESULTS: Twenty studies met our inclusion criteria. The transition from paper-based ordering to commercial CPOE systems in ICUs was associated with an 85% reduction in medication prescribing error rates and a 12% reduction in ICU mortality rates. Overall meta-analyses of LOS and hospital mortality did not demonstrate a significant change. DISCUSSION AND CONCLUSION: Critical care settings, both adult and pediatric, involve unique complexities, making them vulnerable to medication errors and adverse patient outcomes. The currently limited evidence base requires research that has sufficient statistical power to identify the true effect of CPOE implementation. There is also a critical need to understand the nature of errors arising post-CPOE and how the addition of CDSSs can be used to provide greater benefit to delivering safe and effective patient care.

The impact of health information technology on organ transplant care: A systematic review.

BACKGROUND: Health Information Technology (HIT) has a potential to promote transplant care. However, a systematic appraisal on how HIT application has so far affected transplant care is greatly missing from the literature. We systematically reviewed trials that evaluated HIT impact on process and patient outcomes as well as costs in organ transplant care. METHODS: A systematic search was conducted in OVID versions of MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane, and IEEE databases from January 1990 to December 2015. Studies were included if they: (i) evaluated HIT interventions; (ii) reported results for organ transplant population; (iii) reported quantitative data on process, patient, and cost outcomes; and (iv) used a randomized controlled trial or quasi-experimental study design. RESULTS: Primarily, 12,440 publications were identified; from which ten met inclusion criteria. Among HIT systems, uses of clinical decision support systems (CDSS) targeting different aspects of the complex organ transplant care were common. In terms of process outcomes, HIT positively impacted the timeliness of care, laboratory and medication management practices such as promoting therapeutic or diagnostic protocol compliance by clinicians, and reducing medication errors. Regarding patient outcomes, HIT demonstrated a beneficial impact on the percentage of post-transplant patients with normal lab values and decreasing immunosuppressive toxicity and also deviation from the predefined immunosuppressive therapeutic window. However, in terms of mortality, readmission, rejection, and antiviral resistance rates, the impact was not clearly established in the literature. Finally, these systems were associated with savings in the costs of transplant care in three studies. CONCLUSION: This is the first study reviewing HIT impact on transplant care outcomes. CDSSs have mainly been reported to support transplant care in realizing the above-mentioned benefits. However, to make conclusions, more evidence with less risk of bias is warranted. Several gaps in the literature, including comparison of the impact of commercial systems in different transplant settings, was identified which can motivate future research.

Effects of Face-to-Face and Telephone-Based Family-Oriented Education on Self-Care Behavior and Patient Outcomes in Type 2 Diabetes: A Randomized Controlled Trial.

BACKGROUND: Education of patients and their families is the cornerstone of effective diabetes care. The present study aimed to compare the effects of a face-to-face and telephone-based family-oriented educational program on self-care behavior and patient outcomes in type 2 diabetes patients. METHODS: In the present randomized controlled trial, 90 type 2 diabetes patients were randomly divided into three groups of 30 participants: a face-to-face education group, a telephone-based education group, and a control group. The educational program lasted for 3 months. Outcomes evaluated included self-care, fasting blood sugar, hemoglobin A1c, cholesterol, and triglyceride. RESULTS: The overall self-care scores in the intervention groups were significantly higher than that in the control group (P = 0.0001). In addition, lipid profiles significantly improved in the interventions compared to the control (P < 0.05). Comparing the two interventions showed better results for the face-to-face group regarding dietary adherence and physical activity, but the latter group had comparable results in blood glucose monitoring, foot care, and cholesterol level. CONCLUSIONS: This study shows the beneficiary effects of a family-oriented education on self-care and patient outcomes. It also shows the potential value of low-cost telephone technology in delivering effective diabetes care.

Towards Realizing Benefits of Information Technology in Organ Transplant: A Review.

Organ transplantation comprises of many phases, processes, and activities and involves multiple stakeholders. Effective management of such a complex and costly medical domain requires an efficient, multifaceted solution. Although, Information Technology (IT) can basically play an important role here, it is not clear how IT potentials have been deployed so far. We systematically reviewed MEDLINE, EMBASE, CINAHL, The Cochrane and IEEE databases and identified 27 publications describing IT application in organ transplantation. Although the IT coverage spans over waiting list management, donor-recipient matching, and inpatient and outpatient medication and lab monitoring practices, the coverage is still patchy and whole process IT support is missing in practice.

What makes an information system more preferable for clinicians? a qualitative comparison of two systems.

Two different information systems with respect to their ability to afford clinicians' needs in the chemotherapy medication process were implemented in a large Dutch academic hospital. A commercially available Computerized Physician Order Entry (CPOE) system was not appreciated because clinicians believed that it could not support complex chemotherapy process. Later, a home-grown IT system with the capability of prescribing chemotherapy medications based on standard care protocols was appreciated and fully used by clinicians. We evaluated both systems from their users' perspective to find the sources of clinicians' preference and to trace them back to their Systems Development Life Cycle (SDLC).

Reporting qualitative research in health informatics: REQ-HI recommendations.

To develop a set of recommendations for authors of qualitative studies in the field of health informatics, we conducted an extensive literature search and also manually checked major journals in the field of biomedical informatics and qualitative research looking for papers, checklists, and guidelines pertaining to assessing and reporting of qualitative studies. We synthesized the found criteria to develop an initial set of reporting recommendations that are particularly relevant to qualitative studies of health information technology systems. This paper presents a preliminary version of these recommendations. We are planning to refine and revise this version using comments and suggestions of experts in evaluation of health informatics applications and publish a detailed set of recommendations.