J Robotic Surg DOI 10.1007/s11701-015-0508-1
LETTER TO THE EDITOR
Getting smarter with patient positioning L. R. Kidd1 • T. Deen1
Received: 22 December 2014 / Accepted: 9 March 2015 Ó Springer-Verlag London 2015
Keywords
Patient safety Education Positioning
Dear Editor, Re: Getting smarter with patient positioning The development and acquisition of technical skills are a complex process [1], and arguably no surgical technique is evolving and developing as quickly as robotic surgery. It therefore seems prudent that key environmental variations are minimised to aid both skill acquisition and technique refinement. Patient positioning is one such component, ensuring adequate surgical visualisation whilst minimising the physiological implications of the steep Trendelenburg position [2]. Because of the potential challenges associated with patient positioning, an assessment of bed angle estimation accuracy by anaesthetists was performed in the robotic surgery suite. A series of 25 patients underwent positioning in the steep Trendelenburg by regular ‘‘robotic’’ anaesthetists for routine robotic surgery. Median target angle was 24°. The mean root square difference between ‘‘estimated’’ and ‘‘target’’ angles was 2.7°; standard deviation was 2.2°. Error range varied from -4° to ?9°. No complications during or as a result of positioning errors were recorded. In the majority of cases, the angle was estimated with a reasonable degree of accuracy (standard deviation 2.2°) suggesting that this group of ‘‘robotic’’ anaesthetists is generally good at angle estimation. However, outliers & L. R. Kidd [email protected] 1
Anaesthetics Department, Royal Devon and Exeter Hospital, Barrack Road, Exeter, Devon, UK
clearly occur—and it is these events that place patients at increased risk. Comparison was made with a bed with an inbuilt inclinometer (Arcoma 0047-TM4ST, Arcoma North America, Calif., USA). In this case, the mean root square difference between the measured and product specification [3] limits of angulation (±15° Trendelenburg and lateral) was 0.63°, with a standard deviation of 0.29°. The recent generation of mobile ‘smartphones’ often incorporates a micro-electro-mechanical-system accelerometer, which can accurately sense acceleration and inclination. The availability of various software applications for smartphones which read and display the accelerometer signal allows them to be used in a wide range of potential clinical applications, such as a goniometer for measuring knee [4], lumbar spine [5] and shoulder range of movements [6]. We therefore recommend the routine use of an iPhone or similarly available inclinometer whenever performing patient positioning for robotic surgery. The smart technology is in our pocket—we should maximise it. Many thanks Lawrence R. Kidd and T. Deen Conflict of interest conflict of interest.
Kidd LR and Deen T declare that they have no
Ethical approval Following institutional Research and Design involvement and following completion of the Health Research Authority/Medical Research Council decision tree, ethical approval was waived.
References 1. Van Hove PD, Tuijthof GJ, Verdaasdonk EG, Stassen LP, Dankelman J (2010) Objective assessment of technical surgical skills. Br J Surg 97(7):972–987
123
J Robotic Surg 2. Awad H, Walker CM, Shaikh M, Dimitrova GT, Abaza R, O’Hara J (2012) Anesthetic considerations for robotic prostatectomy: a review of the literature. J Clin Anesth 24(6):494–504 3. http://www.josephmedical.net/documents/acoma-medstone/Arcom a%20Medstone%20Elite%20Technical%20Manual.pdf. Accessed 2 Feb 2015 4. Ferriero G, Vercelli S, Sartorio F, Mun˜oz Lasa S, Ilieva E, Brigatti E, Ruella C, Foti C (2013) Reliability of a smartphone-based
123
goniometer for knee joint goniometry. Int J Rehabil Res 36(2):146–151 5. Driscoll M, Fortier-Tougas C, Labelle H, Parent S, Mac-Thiong JM (2014) Evaluation of an apparatus to be combined with a smartphone for the early detection of spinal deformities. Scoliosis 25(9):10 6. Shin SH, du Ro H, Lee OS, Oh JH, Kim SH (2012) Within-day reliability of shoulder range of motion measurement with a smartphone. Man Ther 17(4):298–304
LETTER TO THE EDITOR
Getting smarter with patient positioning L. R. Kidd1 • T. Deen1
Received: 22 December 2014 / Accepted: 9 March 2015 Ó Springer-Verlag London 2015
Keywords
Patient safety Education Positioning
Dear Editor, Re: Getting smarter with patient positioning The development and acquisition of technical skills are a complex process [1], and arguably no surgical technique is evolving and developing as quickly as robotic surgery. It therefore seems prudent that key environmental variations are minimised to aid both skill acquisition and technique refinement. Patient positioning is one such component, ensuring adequate surgical visualisation whilst minimising the physiological implications of the steep Trendelenburg position [2]. Because of the potential challenges associated with patient positioning, an assessment of bed angle estimation accuracy by anaesthetists was performed in the robotic surgery suite. A series of 25 patients underwent positioning in the steep Trendelenburg by regular ‘‘robotic’’ anaesthetists for routine robotic surgery. Median target angle was 24°. The mean root square difference between ‘‘estimated’’ and ‘‘target’’ angles was 2.7°; standard deviation was 2.2°. Error range varied from -4° to ?9°. No complications during or as a result of positioning errors were recorded. In the majority of cases, the angle was estimated with a reasonable degree of accuracy (standard deviation 2.2°) suggesting that this group of ‘‘robotic’’ anaesthetists is generally good at angle estimation. However, outliers & L. R. Kidd [email protected] 1
Anaesthetics Department, Royal Devon and Exeter Hospital, Barrack Road, Exeter, Devon, UK
clearly occur—and it is these events that place patients at increased risk. Comparison was made with a bed with an inbuilt inclinometer (Arcoma 0047-TM4ST, Arcoma North America, Calif., USA). In this case, the mean root square difference between the measured and product specification [3] limits of angulation (±15° Trendelenburg and lateral) was 0.63°, with a standard deviation of 0.29°. The recent generation of mobile ‘smartphones’ often incorporates a micro-electro-mechanical-system accelerometer, which can accurately sense acceleration and inclination. The availability of various software applications for smartphones which read and display the accelerometer signal allows them to be used in a wide range of potential clinical applications, such as a goniometer for measuring knee [4], lumbar spine [5] and shoulder range of movements [6]. We therefore recommend the routine use of an iPhone or similarly available inclinometer whenever performing patient positioning for robotic surgery. The smart technology is in our pocket—we should maximise it. Many thanks Lawrence R. Kidd and T. Deen Conflict of interest conflict of interest.
Kidd LR and Deen T declare that they have no
Ethical approval Following institutional Research and Design involvement and following completion of the Health Research Authority/Medical Research Council decision tree, ethical approval was waived.
References 1. Van Hove PD, Tuijthof GJ, Verdaasdonk EG, Stassen LP, Dankelman J (2010) Objective assessment of technical surgical skills. Br J Surg 97(7):972–987
123
J Robotic Surg 2. Awad H, Walker CM, Shaikh M, Dimitrova GT, Abaza R, O’Hara J (2012) Anesthetic considerations for robotic prostatectomy: a review of the literature. J Clin Anesth 24(6):494–504 3. http://www.josephmedical.net/documents/acoma-medstone/Arcom a%20Medstone%20Elite%20Technical%20Manual.pdf. Accessed 2 Feb 2015 4. Ferriero G, Vercelli S, Sartorio F, Mun˜oz Lasa S, Ilieva E, Brigatti E, Ruella C, Foti C (2013) Reliability of a smartphone-based
123
goniometer for knee joint goniometry. Int J Rehabil Res 36(2):146–151 5. Driscoll M, Fortier-Tougas C, Labelle H, Parent S, Mac-Thiong JM (2014) Evaluation of an apparatus to be combined with a smartphone for the early detection of spinal deformities. Scoliosis 25(9):10 6. Shin SH, du Ro H, Lee OS, Oh JH, Kim SH (2012) Within-day reliability of shoulder range of motion measurement with a smartphone. Man Ther 17(4):298–304
