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How Health Information Systems Are Improving Patient Care

Today’s hospital health information systems greatly expand the ability to collect and store patient data with the goal of improving care. Patient data, which ranges from diagnoses, treatment plans, adverse reactions, allergies, test results and vaccinations, gives healthcare providers a complete and organized framework from which to base their interaction with patients.

Informed Decisions by the Right People at the Right Time

The primary functions of health information systems, as outlined by the World Health Organization, are to collect, compile and analyze data, and package and communicate the results to others to assist in the decision-making process. In a one-on-one setting, this could mean improving physician access to lab results and reducing barriers between observations made by different healthcare providers. In a larger setting, the decision-making process can be augmented through the implementation of a hospital-wide clinical decision support system that retrieves bundles of data, applies rules to the data through customized filters and informs the appropriate individuals at the appropriate time. Data can vary from vital signs taken throughout the day to on-demand laboratory results.

Multidimensional Care, Data Across the Spectrum

Modern medical systems involve individuals other than healthcare providers; they also include policymakers and decision-makers from the ground up. This is why health information systems involve data collection and analysis at four major intersections: individual, health facility, population and public surveillance levels. The individual level involves scenarios that promote the care of individual patients. The overarching goal at the patient level is to provide the right care at the right time by the right individual, a treatment approach that stands to cut down waste and significantly improve healthcare delivery through personalized care. The health facility level focuses on collecting information on a system-wide level, such as readmission rates, medical errors, treatment outcomes, quality data, drug procurement information, etc. and allows upper management to better understand resource needs and adapt accordingly.

The population and public surveillance levels take bigger-picture approaches by looking at how policy is affecting the nation's general health. Population management is the aggregation of patient data across multiple health information technology resources, the analysis of that data into actionable patient information, and the strategies through which care providers can improve both clinical and financial outcomes. For example, practices aggregate data across different patient populations, such as all patients with diabetes, COPD, heart disease, obesity, etc., in order to monitor and compare results to better manage care.

Public health surveillance is focused on the continuous, systematic collection, analysis and interpretation of health-related data needed to define problems and provide timely solutions. Healthcare providers leverage this range of data to make informed decisions such as knowing where to disseminate additional vaccines to combat a temporary surge of infection as in the case of epidemics like the 2008 H1N1 outbreak.

Health information systems are a crucial part of modern healthcare. These systems compile a wide range of data from individual patients, including medical history, diagnoses, treatments, allergies and more. They also provide information to analyze metrics for a hospital or the population at large. Not only do health information systems improve patient outcomes, but the information gathered by these systems also gives a picture of the economic aspects of healthcare and shows areas where providers can improve.

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Sources:

http://www.who.int/healthinfo/statistics/toolkit_hss/EN_PDF_Toolkit_HSS_InformationSystems.pdf

http://www.stfm.org/fmhub/fm2010/May/R.%20Lamar358.pdf

http://www.cdc.gov/nchs/data/dhcs/EMR_workshop_summary.pdf


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