Surgical audit is one of the mainstays of reflective practice and improving patient outcomes. Audit allows for the capture of operative results, operation numbers, billing information, and complications. In Australia, it is mandatory to maintain a logbook when undertaking surgical training with the Royal Australasian College of Surgeons (RACS); RACS provides a minimum and extended suggested data set for both trainee and consultant logbooks [1].

Owing to the increasing complexity of health care, electronic information systems are recommended to be utilized to capture clinical data. The use of hospital medical record systems relies heavily on accurate data being captured by staff and may not include the required fields or enough detail to facilitate successful audit of practice [1]. Hence, RACS recommends that surgeons maintain personal logbooks [1]. Many surgeons utilize technology, such as mobile phones, to collect these data; however, on recent review, the applications available in the Australian market fall short of both the suggested minimum and extended data set, highlighting the need for a better surgical logbook tool [2].

The most commonly reported barrier to successful logbook-keeping is the time required for data entry and maintenance [3]. A key difficulty is navigating the balance between increased data capture for more complete and useable information and the extended amount of time required to enter such data. Data overload is “a danger to a successful audit” and this balance must be carefully considered when designing an audit tool [1]. The RACS minimum data set consists of 12 data points, and the extended data set contains 24 data points [1].

In Australia, the primary surgical audit tool for trainees and consultants is the Morbidity Audit and Logbook Tool (MALT) and is mandatory for surgical trainees in certain colleges [4]. MALT contains both the minimum and extended data set and is a useful tool in audit and reflective practice. However, there are some barriers to mobile access to MALT, including a multistep login process, reliance on an internet connection, and the absence of a mobile app, which may limit its use in prospective data capture [2].

It is unclear what proportion of surgeons prospectively maintain a logbook versus those who carry out a retrospective review prior to a regular audit. Prospective record-keeping has the added advantage of being more accurate and resolves issues regarding the evaluation of operative volumes due to computerized or paper-based medical record systems, which may be missed if coded incorrectly, or in procedures with multiple surgeons or specialties [5]. Mobile apps offer an accessible, rapid, and easy-to-use method of prospective record keeping.

Electronic data capture tools have been widely adopted by researchers in medicine and provide an effective way of prospectively collecting data for storage and tabulation [6]. More than 100 different data capture tools are currently available, ranging from those specifically designed for capturing clinical data, such as REDCap, to informal survey software, such as SurveyMonkey and Google Forms [7]. Formal data collection tools such as REDCap and Open Data Kit are usually compliant with established national data security regulations; however, they often have a requirement for some knowledge of computer programming, with an associated learning curve [8]. Nonclinical tools such as SurveyMonkey and Google Forms require an active internet connection and lack end-to-end encryption [8]. Despite these concerns, many institutions have utilized simple data capture tools owing to the simplicity of their implementation and their cost-effectiveness [9].

While RACS provides a guideline regarding the minimum and extended criteria required for a logbook, certain surgeons and specialties may benefit from customization, allowing for further categorization of operative data for personal or research purposes and more efficient data entry [3].

The iOS Shortcuts app (hereinafter referred to as “Shortcuts”) was released in 2019 and allows users to create custom macros allowing for data entry, manipulation, and storage on any iOS-compatible devices [10]. Rather than computer programming, Shortcuts provides the user with a list of tasks to select, which are then customized and transformed to a workflow to be activated by the user. The software utilizes end-to-end encryption when transmitting data and is stored on an encrypted and secure iCloud server.

There is currently no literature describing the potential use of Shortcuts in the collection of clinical data. This feasibility study highlights the utility of the application and demonstrates its functionality in the creation of a surgical logbook tool.

A custom shortcut was designed using the freely available iOS Shortcuts app on an iPad Pro (11-inch) device running on iOS 13.7.

A Numbers (Apple, Cupertino) Spreadsheet document was created in a suitable folder of the iPad storage with the address “/Shortcuts/Logbook/Logbook.numbers” (Multimedia Appendix 1). A sheet and table-titled logbook were created (Multimedia Appendix 1, Sheet 1). An additional file and table were created for the extended data sheet (Multimedia Appendix 2). These files have been provided as a Microsoft Excel spreadsheet to facilitate review from both Windows and Apple devices; however, the shortcut tool requires the Apple Numbers file format to operate successfully.

Using Shortcuts, we generated a workflow macro for the logbook. The workflow consists of multiple data entry blocks, consisting of a prompt for the user with a question, followed by the appearance of a text box accepting the user-entered data, and finally storage as a variable (Figure 1). There are three ways this system is used: a free text entry (Figure 2) and 2 menu choice operations; that is, list or menu (Figures 2 and 3). An agile software development approach was utilized with iterative design, development, testing, and refinement [11].

In total, 2 shortcuts were designed with 2 separate receiving spreadsheets, first with the minimum RACS recommended data set, both of which are freely available through the iCloud service [12,13].

For the purpose of evaluation, a timer was started at the initiation of the shortcut and stopped upon data storage, in order to determine the time taken to use this tool. This timer was excluded for the provided example shortcuts and spreadsheets.

Upon conclusion of the shortcut, the Numbers spreadsheet was opened, and the listed variables were stored as a new row with variables entered into each subsequent column.

A second spreadsheet was created to demonstrate the analytical capability of the logbook tool for audit purposes. This example data analysis tool is provided in Multimedia Appendix 1 (Sheet 2). Prefilled formulas were created for case numbers, operation categories, patient gender, complications and grades, and length of stay, and automatically updated as new cases were entered.

The tool was practically assessed for feasibility, with a surgical registrar entering 20 mock operations into the minimum and extended data field shortcuts. The operation notes were created randomly by computer software with a selection of common operations, indications, and demographic data. Feasibility was assessed by assessing the time required for data entry, the completeness of the entered data, and the accuracy of the filled spreadsheet with the required clinical data.

Shortcuts performed well during testing and has been shown to collect both complete and useful data. The average data entry time for an operation across both minimum and extended data sets was 100 seconds.

In total, 20 cases were recorded with the minimum and extended data sets. The average time for completion of the minimum data set was 65 seconds, with a total time of 21 minutes 43 seconds for 20 cases. The average time for completion of the extended data set was 135 seconds, with a total time of 46 minutes 58 seconds for 20 cases. There was a mean difference of 68 seconds per case between the minimum and extended data sets compared to the minimum data set (P<.001; 2-tailed t₁₉=17.52; 95% CI 61.6-77.7). Table 1 summarizes the time requirements for data entry with the Shortcut.

The built-in example data analysis table functioned well, having captured the entered data and presented basic statistical analysis in real time. Multimedia Appendix 1 (Sheet 2) summarizes the data fields used. On analyzing the spreadsheet, 100% of the required fields were filled successfully, since the shortcut design does not allow incomplete data to be entered.