Appl Clin Inform 2013; 04(03): 445-453
DOI: 10.1055/s-0037-1618865
Case Report
Schattauer GmbH

Matching Clinicians to Operative Cases

A Novel Application of a Patient Acuity Score
A. Was
1   Lucile Packard Children‘s Hospital at Stanford, Pediatrics, Palo Alto, California, United States
,
J. Wanderer
2   Vanderbilt University, Anesthesiology, Nashville, Tennessee, United States
› Author Affiliations
Further Information

Correspondence to:

Adam Was, MD
Lucile Packard Children’s Hospital
725 Welch Road, Palo Alto, CA, 94304
Phone: (650)497–8134   
Fax: (650)497–8228   

Publication History

received: 19 January 2013

accepted: 13 June 2013

Publication Date:
18 December 2017 (online)

 

Summary

Background: Patient and surgical case complexity are important considerations in creating appropriate clinical assignments for trainees in the operating room (OR). The American Society of Anesthesiologists (ASA) Physical Status Classification System is the most commonly used tool to classify patient illness severity, but it requires manual evaluation by a clinician and is highly variable. A Risk Stratification System for surgical patients was recently published which uses administrative billing codes to calculate four Risk Stratification Indices (RSIs) and provides an objective surrogate for patient complexity that does not require clinical evaluation. This risk score could be helpful when assigning operating room cases.

Objective: This is a technical feasibility study to evaluate the process and potential utility of incorporating an automatic risk score calculation into a web-based tool for assigning OR cases.

Methods: We created a web service implementation of the RSI model for one-year mortality and automatically calculated the RSI values for patients scheduled to undergo an operation the following day. An analysis was conducted on data availability for the RSI model and the correlation between RSI values and ASA physical status.

Results: In a retrospective analysis of 46,740 patients who received surgery in the year preceding the web tool implementation, RSI values were generated for 20,638 patients (44%). The Spear-man’s rank correlation coefficient between ASA physical status classification and one-year mortality RSI values was 0.404.

Conclusions: We have shown that it is possible to create a web-based tool that uses existing billing data to automatically calculate risk scores for patients scheduled to undergo surgery. Such a risk scoring system could be used to match patient acuity to physician experience, and to provide improved patient and clinician experiences. The web tool could be improved by expanding the input database or utilizing procedure booking codes rather than billing data.


#

 


#

Conflict of Interest

The authors declare that they have no conflicts of interest in the research.

  • References

  • 1 ASA Physical Status Classification System. http://www.asahq.org/Home/For-Members/Clinical-Information/ASA-Physical-Status-Classification-System.
  • 2 Balstad A, Springer P. Quantifying case management workloads: Development of the PACE tool.. Lippincott’s case management : managing the process of patient care 2006; 6: 291-302 quiz 3-4.
  • 3 Callaghan LA, Cartwright DW, O’Rourke P, Davies MW. Infant to staff ratios and risk of mortality in very low birthweight infants.. Archives of disease in childhood Fetal and neonatal edition 2003; 2: F94-7.
  • 4 Curtin LL. An integrated analysis of nurse staffing and related variables: effects on patient outcomes.. Online journal of issues in nursing 2003; 3: 5.
  • 5 Dalton JE, Kurz A, Turan A, Mascha EJ, Sessler DI, Saager L. Development and validation of a risk quantification index for 30-day postoperative mortality and morbidity in noncardiac surgical patients.. Anesthesiology 2011; 6: 1336-44. doi: 10.1097/ALN.0b013e318219d5f9.
  • 6 Dexter F, Wachtel RE, Epstein RH. Impact of average patient acuity on staffing of the phase I PACU.. Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses / American Society of PeriAnesthesia Nurses 2006; 5: 303-10. doi: 10.1016/j.jopan.2006.07.007.
  • 7 Gedmintas A, Bost N, Keijzers G, Green D, Lind J. Emergency care workload units: a novel tool to compare emergency department activity.. Emergency medicine Australasia : EMA 2010; 5: 442-8. doi: 10.1111/j.1742-6723.2010.01322.x.
  • 8 Goj K, Knapik P, Kucewicz-Czech E, Lubon D. [The TISS-28 scoring system for assessment of cardiac surgical postoperative intensive care].. Anestezjologia intensywna terapia 2009; 1: 37-40.
  • 9 Gross JC, Faulkner EA, Goodrich SW, Kain ME. A patient acuity and staffing tool for stroke rehabilitation inpatients based on the FIM instrument.. Rehabilitation nursing : the official journal of the Association of Rehabilitation Nurses 2001; 3: 108-13. 10 Haney E, Nicolaidis C, Hunter A, Chan BK, Cooney TG, Bowen JL, Relationship between resident workload and self-perceived learning on inpatient medicine wards: a longitudinal study. BMC medical education 2006: 35. doi: 10.1186/1472-6920-6-35.
  • 11 Harper K, McCully C. Acuity systems dialogue and patient classification system essentials.. Nursing administration quarterly 2007; 4: 284-99. doi: 10.1097/01. NAQ.0000290426.41690.cb.
  • 12 Haynes SR, Lawler PG. An assessment of the consistency of ASA physical status classification allocation.. Anaesthesia 1995; 3: 195-9.
  • 13 Hsia DC, Krushat WM, Fagan AB, Tebbutt JA, Kusserow RP. Accuracy of diagnostic coding for Medicare patients under the prospective-payment system.. The New England journal of medicine 1988; 6: 352-5. doi: 10.1056/NEJM198802113180604.
  • 14 Innes GD, Stenstrom R, Grafstein E, Christenson JM. Prospective time study derivation of emergency physician workload predictors.. Cjem 2005; 5: 299-308.
  • 15 Land MJ, Guzzetti PJ, May FJ. Balancing workload and staffing in satellite pharmacies by using a patient acuity index.. Hospital pharmacy 1983; 6: 305-7 10-1.
  • 16 Lloyd SS, Rissing JP. Physician and coding errors in patient records.. JAMA : the journal of the American Medical Association 1985; 10: 1330-6.
  • 17 Mamaril ME, Sullivan E, Clifford TL, Newhouse R, Windle PE. Safe staffing for the post anesthesia care unit: weighing the evidence and identifying the gaps.. Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses / American Society of PeriAnesthesia Nurses 2007; 6: 393-9. doi: 10.1016/j.jopan.2007.08.007.
  • 18 O’Connor G, Geary U, Moriarty J. Critical care in the emergency department.. European journal of emergency medicine : official journal of the European Society for Emergency Medicine 2009; 6: 296-300. doi: 10.1097/MEJ.0b013e32831090bd.
  • 19 O’Malley KJ, Cook KF, Price MD, Wildes KR, Hurdle JF, Ashton CM. Measuring diagnoses: ICD code accuracy.. Health services research. 2005 ; 5 Pt 2: 1620-39. doi: 10.1111/j.1475-6773.2005.00444.x.
  • 20 Ravikumar TS, Sharma C, Marini C, Steele Jr., GD, Ritter G, Barrera R, Kim M, Safyer SM, Vandervoort K, De Geronimo M, Baker L, Levi P, Pierdon S, Horgan M, Maynor K, Maloney G, Wojtowicz M, Nelson K. A validated value-based model to improve hospital-wide perioperative outcomes: adaptability to combined medical/surgical inpatient cohorts.. Annals of surgery 2010; 3: 486-96 discussion 96-8. doi: 10.1097/SLA.0b013e3181f1c412.
  • 21 Rischbieth A. Matching nurse skill with patient acuity in the intensive care units: a risk management mandate.. Journal of nursing management 2006; 5: 397-404. doi: 10.1111/j.1365-2934.2006.00622.x.
  • 22 Sessler DI, Sigl JC, Manberg PJ, Kelley SD, Schubert A, Chamoun NG. Broadly applicable risk stratification system for predicting duration of hospitalization and mortality.. Anesthesiology 2010; 5: 1026-37. doi: 10.1097/ALN.0b013e3181f79a8d.
  • 23 Sessler DI, Sigl JC, Manberg PJ, Kelley SD, Schubert A, Chamoun NG. http://my.clevelandclinic.org/anesthesia/outcomes/risk-stratification-index.aspx.
  • 24 Spence K, Tarnow-Mordi W, Duncan G, Jayasuryia N, Elliott J, King J, Kite F. Measuring nursing workload in neonatal intensive care.. Journal of nursing management 2006; 3: 227-34. doi: 10.1111/j.1365-2934.2006.00609.x.
  • 25 Wanderer JP, Charnin J, Driscoll WD, Balin MT, Baker K. Decision Support Using Anesthesia Information Management System Records and Accreditation Council for Graduate Medical Education Case Logs for Resident Operating Room Assignments.. Anesth Analg 2013

Correspondence to:

Adam Was, MD
Lucile Packard Children’s Hospital
725 Welch Road, Palo Alto, CA, 94304
Phone: (650)497–8134   
Fax: (650)497–8228   

  • References

  • 1 ASA Physical Status Classification System. http://www.asahq.org/Home/For-Members/Clinical-Information/ASA-Physical-Status-Classification-System.
  • 2 Balstad A, Springer P. Quantifying case management workloads: Development of the PACE tool.. Lippincott’s case management : managing the process of patient care 2006; 6: 291-302 quiz 3-4.
  • 3 Callaghan LA, Cartwright DW, O’Rourke P, Davies MW. Infant to staff ratios and risk of mortality in very low birthweight infants.. Archives of disease in childhood Fetal and neonatal edition 2003; 2: F94-7.
  • 4 Curtin LL. An integrated analysis of nurse staffing and related variables: effects on patient outcomes.. Online journal of issues in nursing 2003; 3: 5.
  • 5 Dalton JE, Kurz A, Turan A, Mascha EJ, Sessler DI, Saager L. Development and validation of a risk quantification index for 30-day postoperative mortality and morbidity in noncardiac surgical patients.. Anesthesiology 2011; 6: 1336-44. doi: 10.1097/ALN.0b013e318219d5f9.
  • 6 Dexter F, Wachtel RE, Epstein RH. Impact of average patient acuity on staffing of the phase I PACU.. Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses / American Society of PeriAnesthesia Nurses 2006; 5: 303-10. doi: 10.1016/j.jopan.2006.07.007.
  • 7 Gedmintas A, Bost N, Keijzers G, Green D, Lind J. Emergency care workload units: a novel tool to compare emergency department activity.. Emergency medicine Australasia : EMA 2010; 5: 442-8. doi: 10.1111/j.1742-6723.2010.01322.x.
  • 8 Goj K, Knapik P, Kucewicz-Czech E, Lubon D. [The TISS-28 scoring system for assessment of cardiac surgical postoperative intensive care].. Anestezjologia intensywna terapia 2009; 1: 37-40.
  • 9 Gross JC, Faulkner EA, Goodrich SW, Kain ME. A patient acuity and staffing tool for stroke rehabilitation inpatients based on the FIM instrument.. Rehabilitation nursing : the official journal of the Association of Rehabilitation Nurses 2001; 3: 108-13. 10 Haney E, Nicolaidis C, Hunter A, Chan BK, Cooney TG, Bowen JL, Relationship between resident workload and self-perceived learning on inpatient medicine wards: a longitudinal study. BMC medical education 2006: 35. doi: 10.1186/1472-6920-6-35.
  • 11 Harper K, McCully C. Acuity systems dialogue and patient classification system essentials.. Nursing administration quarterly 2007; 4: 284-99. doi: 10.1097/01. NAQ.0000290426.41690.cb.
  • 12 Haynes SR, Lawler PG. An assessment of the consistency of ASA physical status classification allocation.. Anaesthesia 1995; 3: 195-9.
  • 13 Hsia DC, Krushat WM, Fagan AB, Tebbutt JA, Kusserow RP. Accuracy of diagnostic coding for Medicare patients under the prospective-payment system.. The New England journal of medicine 1988; 6: 352-5. doi: 10.1056/NEJM198802113180604.
  • 14 Innes GD, Stenstrom R, Grafstein E, Christenson JM. Prospective time study derivation of emergency physician workload predictors.. Cjem 2005; 5: 299-308.
  • 15 Land MJ, Guzzetti PJ, May FJ. Balancing workload and staffing in satellite pharmacies by using a patient acuity index.. Hospital pharmacy 1983; 6: 305-7 10-1.
  • 16 Lloyd SS, Rissing JP. Physician and coding errors in patient records.. JAMA : the journal of the American Medical Association 1985; 10: 1330-6.
  • 17 Mamaril ME, Sullivan E, Clifford TL, Newhouse R, Windle PE. Safe staffing for the post anesthesia care unit: weighing the evidence and identifying the gaps.. Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses / American Society of PeriAnesthesia Nurses 2007; 6: 393-9. doi: 10.1016/j.jopan.2007.08.007.
  • 18 O’Connor G, Geary U, Moriarty J. Critical care in the emergency department.. European journal of emergency medicine : official journal of the European Society for Emergency Medicine 2009; 6: 296-300. doi: 10.1097/MEJ.0b013e32831090bd.
  • 19 O’Malley KJ, Cook KF, Price MD, Wildes KR, Hurdle JF, Ashton CM. Measuring diagnoses: ICD code accuracy.. Health services research. 2005 ; 5 Pt 2: 1620-39. doi: 10.1111/j.1475-6773.2005.00444.x.
  • 20 Ravikumar TS, Sharma C, Marini C, Steele Jr., GD, Ritter G, Barrera R, Kim M, Safyer SM, Vandervoort K, De Geronimo M, Baker L, Levi P, Pierdon S, Horgan M, Maynor K, Maloney G, Wojtowicz M, Nelson K. A validated value-based model to improve hospital-wide perioperative outcomes: adaptability to combined medical/surgical inpatient cohorts.. Annals of surgery 2010; 3: 486-96 discussion 96-8. doi: 10.1097/SLA.0b013e3181f1c412.
  • 21 Rischbieth A. Matching nurse skill with patient acuity in the intensive care units: a risk management mandate.. Journal of nursing management 2006; 5: 397-404. doi: 10.1111/j.1365-2934.2006.00622.x.
  • 22 Sessler DI, Sigl JC, Manberg PJ, Kelley SD, Schubert A, Chamoun NG. Broadly applicable risk stratification system for predicting duration of hospitalization and mortality.. Anesthesiology 2010; 5: 1026-37. doi: 10.1097/ALN.0b013e3181f79a8d.
  • 23 Sessler DI, Sigl JC, Manberg PJ, Kelley SD, Schubert A, Chamoun NG. http://my.clevelandclinic.org/anesthesia/outcomes/risk-stratification-index.aspx.
  • 24 Spence K, Tarnow-Mordi W, Duncan G, Jayasuryia N, Elliott J, King J, Kite F. Measuring nursing workload in neonatal intensive care.. Journal of nursing management 2006; 3: 227-34. doi: 10.1111/j.1365-2934.2006.00609.x.
  • 25 Wanderer JP, Charnin J, Driscoll WD, Balin MT, Baker K. Decision Support Using Anesthesia Information Management System Records and Accreditation Council for Graduate Medical Education Case Logs for Resident Operating Room Assignments.. Anesth Analg 2013