Physician communication via Internet-enabled technology: A systematic review.

The use of Internet-enabled technology (information and communication technology such as smartphone applications) may enrich information exchange among providers and, consequently, improve health care delivery. The purpose of this systematic review was to gain a greater understanding of the role that Internet-enabled technology plays in enhancing communication among physicians. Studies were identified through a search in three electronic platforms: the Association for Computing Machinery Digital Library, ProQuest, and Web of Science. The search identified 5140 articles; of these, 21 met all inclusion criteria. In general, physicians were satisfied with Internet-enabled technology, but consensus was lacking regarding whether Internet-enabled technology improved efficiency or made a difference to clinical decision-making. Internet-enabled technology can play an important role in enhancing communication among physicians, but the extent of that benefit is influenced by (1) the impact of Internet-enabled technology on existing work practices, (2) the availability of adequate resources, and (3) the nature of institutional elements, such as privacy legislation.

The impact of technological intensity of service provision on physician expenditures: an exploratory investigation.

Advances in technology and subsequent changes in clinical practice can lead to increases in healthcare costs. Our objective is to assess the impact that changes in the technological intensity of physician-provided health services have had on the age pattern of both the volume of services provided and the average expenditures associated with them. We based our analysis on age-sex-specific patient-level administrative records of diagnoses and treatments. These records include virtually all physician services provided in the province of Ontario, Canada in a 10-year span ending in 2004 and their associated costs. An algorithm is developed to classify services and their costs into three levels of technological intensity. We find that while the overall age-standardized level and cost of services per capita have decreased, the volume and cost of high technologically intensive treatments have increased, especially among older patients.

Predicting the impact of hospital health information technology adoption on patient satisfaction.

OBJECTIVES: To develop and explore the predictability of patient perceptions of satisfaction through the hospital adoption of health information technology (HIT), leading to a better understanding of the benefits of increased HIT investment. DATA AND METHODS: The solution proposed is based on comparing the predictive capability of artificial neural networks (ANNs) with the adaptive neuro-fuzzy inference system (ANFIS). The latter integrates artificial neural networks and fuzzy logic and can handle certain complex problems that include fuzziness in human perception, and non-normal and non-linear data. Secondary data from two surveys were combined to develop the model. Hospital HIT adoption capability and use indicators in the Canadian province of Ontario were used as inputs, while patient satisfaction indicators of healthcare services in acute hospitals were used as outputs. RESULTS: Eight different types of models were trained and tested for each of four patient satisfaction dimensions. The accuracy of each predictive model was evaluated through statistical performance measures, including root mean square error (RMSE), and adjusted coefficient of determination R(2)(Adjusted). For all four patient satisfaction indicators, the performance of ANFIS was found to be more effective (R(Adjusted)(2)=0.99) when compared with the results of ANN modeling in predicting the impact of HIT adoption on patient satisfaction (R(Adjusted)(2)=0.86-0.88). CONCLUSIONS: The impact of HIT adoption on patient satisfaction was obtained for different HIT adoption scenarios using ANFIS simulations. The results through simulation scenarios revealed that full implementation of HIT in hospitals can lead to significant improvement in patient satisfaction. We conclude that the proposed ANFIS modeling technique can be used as a decision support mechanism to assist government and policy makers in predicting patient satisfaction resulting from the implementation of HIT in hospitals.

Enabling medication management through health information technology (Health IT).

OBJECTIVES: The objective of the report was to review the evidence on the impact of health information technology (IT) on all phases of the medication management process (prescribing and ordering, order communication, dispensing, administration and monitoring as well as education and reconciliation), to identify the gaps in the literature and to make recommendations for future research. DATA SOURCES: We searched peer-reviewed electronic databases, grey literature, and performed hand searches. Databases searched included MEDLINE®, Embase, CINAHL (Cumulated Index to Nursing and Allied Health Literature), Cochrane Database of Systematic Reviews, International Pharmaceutical Abstracts, Compendex, Inspec (which includes IEEE Xplore), Library and Information Science Abstracts, E-Prints in Library and Information Science, PsycINFO, Sociological Abstracts, and Business Source Complete. Grey literature searching involved Internet searching, reviewing relevant Web sites, and searching electronic databases of grey literatures. AHRQ also provided all references in their e-Prescribing, bar coding, and CPOE knowledge libraries. METHODS: Paired reviewers looked at citations to identify studies on a range of health IT used to assist in the medication management process (MMIT) during multiple levels of screening (titles and abstracts, full text and final review for assignment of questions and data abstrction). Randomized controlled trials and cohort, case-control, and case series studies were independently assessed for quality. All data were abstracted by one reviewer and examined by one of two different reviewers with content and methods expertise. RESULTS: 40,582 articles were retrieved. After duplicates were removed, 32,785 articles were screened at the title and abstract phase. 4,578 full text articles were assessed and 789 articles were included in the final report. Of these, 361 met only content criteria and were listed without further abstraction. The final report included data from 428 articles across the seven key questions. Study quality varied according to phase of medication management. Substantially more studies, and studies with stronger comparative methods, evaluated prescribing and monitoring. Clinical decision support systems (CDSS) and computerized provider order entry (CPOE) systems were studied more than any other application of MMIT. Physicians were more often the subject of evaluation than other participants. Other health care professionals, patients, and families are important but not studied as thoroughly as physicians. These nonphysicians groups often value different aspects of MMIT, have diverse needs, and use systems differently. Hospitals and ambulatory clinics were well-represented in the literature with less emphasis placed on long-term care facilities, communities, homes, and nonhospital pharmacies. Most studies evaluated changes in process and outcomes of use, usability, and knowledge, skills, and attitudes. Most showed moderate to substantial improvement with implementation of MMIT. Economics studies and those with clinical outcomes were less frequently studied. Those articles that did address economics and clinical outcomes often showed equivocal findings on the effectiveness and cost-effectiveness of MMIT systems. Qualitative studies provided evidence of strong perceptions, both positive and negative, of the effects of MMIT and unintended consequences. We found little data on the effects of forms of medications, conformity, standards, and open source status. Much descriptive literature discusses implementation issues but little strong evidence exists. Interest is strong in MMIT and more groups and institutions will implement systems in the next decades, especially with the Federal Government's push toward more health IT to support better and more cost-effective health care. CONCLUSIONS: MMIT is well-studied, although on closer examination of the literature the evidence is not uniform across phases of medication management, groups of people involved, or types of MMIT. MMIT holds the promise of improved processes; clinical and economics studies and the understanding of sustainability issues are lacking.