Category:BMI-512-W-08

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Evaluating public health uses of health information exchange

Jason S. Shapiro

The potential of health information exchange (HIE) to improve the public health and public health activities may seem obvious, but current literature provides little evidence proving these effects. This article provides general evaluation methods for measuring the impact of HIE on public health in six use cases. For each use case the author gives a brief description for the case then discusses potential approaches to the evaluation of these use cases.

1. Mandated reporting of laboratory diagnoses. Measuring the volume of relevant data transmitted using Electronic laboratory reporting directly to health departments would be a primary measure of success in this use case (i.e. recall): relevant ∩ retrieved/relevant. If feasible, a pre- and post-implementation study, could be conducted to demonstrate any change in the frequency of mandated reporting of laboratory diagnoses using HIE laboratory data. Additional metrics of interest could look at changes in efficiency, completeness and timeliness of reporting.

2. Mandated reporting of physician-based diagnoses Recall would be difficult to measure in this use case since measuring all relevant cases for the denominator would be time consuming and expensive. Another measure of interest is to evaluate the performance of the system (i.e. the precision): relevant ∩ retrieved/retrieved. Measurement of precision would require a log file capturing all potential clinician reportable diseases detected by the system, followed by manual review to determine which cases are relevant. Another useful evaluative measure might be to determine the volume of reporting pre- and post-implementation in much the same way that was suggested above for mandated reporting of laboratory diagnoses, as well as the efficiency, completeness and timeliness of reporting.

3. Public health investigation Because implementation of this use case will vary depending on the extent to which the HIE incorporates clinical data, recommendation of a specific evaluation is difficult. One possibility is to do a qualitative or semi-qualitative study of the public health investigator’s experience through surveys, semi-structured interviews or observational techniques. In addition if this were done across multiple HIE projects, analysis might permit the development of a set of standard practices for HIE implementations to help identify the data elements and user interface features that are most essential to this use case.

4. Disease-based non-reportable laboratory data Because this use case will rely on the development of faster, less expensive, and more accessible assays to clinicians, and these are being developed and deployed in parallel with HIE systems, they will likely act as a confounder, making it difficult to construct an evaluation plan that incorporates a pre-implementation phase. Of most interest here is the gathering and analysis of empirical data to make new discoveries regarding the epidemiology of these common pathogens.

5. Antibiotic-resistant organism surveillance Since the intervention here is the dissemination of a community-wide antibiogram, A study evaluating the rates of local antibiotic resistance patterns before and after the implementation of a community- wide antibiogram would be of interest. Similarly, studies could be done pre- and post-implementation on a hospital level to see if an antibiotic-resistant organism (ARO) notification system leads to earlier identification and isolation of ARO-infected patients, and to see if hospital rates of nosocomial ARO infections decrease. 6. Population-level quality monitoring Again, this use case would require a pre- and post implementation study. A number of organizations have developed, or are developing, standard sets of quality measures that could be used for evaluation. Conclusion This paper describes preliminary suggestions for measuring the impact of HIE on public health in specific use cases. There are other secondary and tertiary benefits to improved public health that would be much more difficult to measure. During the early phases of development of regional HIE, the projects will be limited in scope due to only partial penetration of local markets and therefore only partial data capture. Measures likely to be affected during this early phase are efficiency measures and costs. These early measures may be used to calculate a return on investment of the initial implementation costs. As these HIE systems mature and begin to share data with one another, and a truly interoperable nationwide health information network (NHIN) begins to coalesce, quality and safety effects will begin to accrue and be measurable.

Limitations and Strengths This article provides general evaluation methods for measuring the impact of HIE on public health in only six use cases and in two of this six cases , the author mention that it is difficult to construct an evaluation plan. The good thing here is that he describe the use cases in some details and he also states some other benefits of the suggested evaluation measures in guiding and encouraging the process of HIE development and implementation.


by Ahmed Mahmoud

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