This ReadMe file was generated on 2022-09-02 by Ashley Griffin.


GENERAL INFORMATION
1. Title of Dataset: Clinical, Technical, and Implementation Characteristics of Real-World Health Applications Using FHIR

2. Author information:
	Corresponding Investigator
		Name: Ashley Griffin, PhD
		Institution: Stanford University, Palo Alto, CA
		Email: griffina@stanford.edu

	Senior Investigator
		Name: Titus Schleyer, DMD, PhD
		Institution: Regenstrief Institute, Indianapolis, IN
		Email: schleyer@regenstrief.edu

3. Date of data collection: 2021-2022

4. Geographic location of data collection: The survey was distributed globally.

5. Funding source: N/A

6. Recommended citation for this dataset: Griffin, Ashley et al. (2022), Clinical, Technical, and Implementation Characteristics of Real-World Health Applications Using FHIR, Dryad, Dataset, https://doi.org/10.5061/dryad.qrfj6q5k5


DATA & FILE OVERVOEW

1. Description of dataset

Fast Healthcare Interoperability Resources (FHIR) has received vast support globally, with a growing number of use cases implemented throughout various healthcare settings. To assess the use of real-world FHIR applications (apps) implemented in practice, we distributed an electronic survey to FHIR developers. The data includes characteristics of 112 FHIR apps, including health domain, target audience, terminologies, FHIR specifications, implementation details, and types of organizations developing with FHIR. This repository includes the REDCAP survey codebook and survey dataset.

2. File list:
	File 1 name: Griffin_2022_FHIR_Survey_Data.xlsx
	File 1 description: survey dataset

	File 2 name: Griffin_2022_FHIR_Survey_Codebook.pdf
	File 2 description: survey codebook


METHODOLOGICAL INFORMATION

These data were generated from a Research Electronic Data Capture (REDCap®) electronic survey among FHIR app developers and implementers. The dataset contains characteristics of FHIR apps, including domain and target audience, FHIR specifications and terminologies, implementation details, and developing organizations. We distributed the survey globally via email using snowball sampling and to FHIR app developers among our professional contacts. 

We defined a FHIR app as a software application that uses FHIR as its interface to the data it requires and is designed for a human end user (patient, provider, or other individual) involved in patient care or related services. Inclusion criteria were apps that 1) reported using FHIR, 2) focused on healthcare (clinical, administrative, patients/caregivers, research, or educational applications), 3) had real-world users (including in pilot mode), and 4) had an English-language version available. Apps were excluded if they were in conceptual or planning phases.


DATA-SPECIFIC INFORMATION FOR: Griffin_2022_FHIR_Survey_Data.xlsx

1. Number of variables: 124

2. Number of rows/survey responses: 112

3. Missing data codes: null

4. Other relevant information: The survey contained 28 questions. All survey questions were multiple choice and allowed multiple responses except for questions on development stage and FHIR release version. Name and email addresses have been removed from the dataset. The dataset is flattened so that each variable corresponds to a survey response. Please see the survey codebook (Griffin_2022_FHIR_Survey_Codebook.pdf) for a description of each variable and response attributes (e.g., checkbox, text, radio).