Management implications for the perioperative surgical home related to inpatient case cancellations and add-on case scheduling on the day of surgery.

BACKGROUND: The American Society of Anesthesiologists has embraced the concept of the Perioperative Surgical Home as a means through which anesthesiologists can add value to the health systems in which they practice. One key listed element of the Perioperative Surgical Home is to support "scheduling initiatives to reduce cancellations and increase efficiency." In this study, we explored the potential benefits of the Perioperative Surgical Home with respect to inpatient cancellations and add-on case scheduling. We evaluated 6 hypotheses related to the timing of inpatient cancellations and preoperative anesthesia evaluations. METHODS: Inpatient cancellations were studied during 26 consecutive 4-week intervals between July 2012 and June 2014 at a tertiary care academic hospital. All timestamps related to scheduling, rescheduling, and cancellation activities were retrieved from the operating room (OR) case scheduling system. Timestamps when patients were seen by anesthesia residents were obtained from the preoperative evaluation system database. Batch mean methods were used to calculate means and SE. For cases cancelled, we determined whether, for "most" (>50%) cancellations, a subsequent procedure (of any type) was performed on the patient within 7 days of the cancellation. Comparisons with most and other fractions were assessed using the 1 group, 1-sided Student t test. We evaluated whether a few procedures were highly represented among the cancelled cases via the Herfindahl (Simpson's) index, comparing it with <0.15. The rate of scheduling activity was assessed by computing the number of OR scheduling office decisions in each 1-hour bin between 6:00 AM and 3:59 PM. These values were compared with ≥1 decision per hour at the study hospital. RESULTS: Data from 24,735 scheduled inpatient cases were assessed. Cases cancelled after 7 AM on the day before or at any time on the scheduled day of surgery accounted for 22.6% ± 0.5% (SE) of the scheduled minutes all scheduled cases, and 26.8% ± 0.4% of the case volume (i.e., number of cases). Most (83.1% ± 0.6%, P < 10) cases performed were evaluated on the day before surgery. Most (67.6% ± 1.6%, P < 10) minutes of cancelled cases were evaluated on the day before surgery. Most (62.3% ± 1.5%, P < 10) cases were seen earlier than 6:00 PM of the day before surgery. The Herfindahl index among cancelled procedures was 0.021 ± 0.001 (P < 10 compared not only to <0.15 but also to <0.05), showing large heterogeneity among the cancelled procedures. A subsequent procedure was not performed for most cancelled cases (50.6% ± 0.9% compared with >50%, P = 0.12), implying that the indication for the cancelled procedure no longer existed or the patient/family decided not to proceed with surgery. When only cancellations on the scheduled day of surgery were considered, the cancellation rate was 14.0% ± 0.3% of scheduled inpatient minutes and 11.8% ± 0.2% of scheduled inpatient cases. There were 0.59 ± 0.02 OR schedule decisions per hour per 10 ORs between 6:00 AM and 3:59 PM (P < 10, corresponding to ≥1 decision per hour at the 36 OR study hospital). CONCLUSIONS: The study hospital had a high inpatient cancellation rate, despite the fact that most patients whose cases were cancelled were seen by an anesthesia resident by 6:00 PM of the day before surgery. This finding suggests that further efforts to reduce the cancellations by seeing patients sooner on the day before surgery, or seeing even more patients the day before surgery, would not be an economically useful focus of the Perioperative Surgical Home. The wide heterogeneity among cancelled cases indicates that focusing on a few procedures would not materially affect the overall cancellation rate. The relatively low rate of subsequent performance of a procedure on patients whose cases had been cancelled suggests that trying to decrease the cancellation rate might be medically counterproductive. The hourly rate of decisions in the scheduling office during regular work hours on the day of surgery highlights the importance of decisions made at the OR control desk and scheduling office throughout the day to reduce the hours of overused OR time. These data suggest that efforts of the Perioperative Surgical Home related to inpatient cancellations should focus on management decision-making to mitigate the disruptions to the planned OR schedule caused by inpatient case cancellations and add-on cases, more so than on efforts to reduce inpatient cancellation rates.

Decision support using anesthesia information management system records and accreditation council for graduate medical education case logs for resident operating room assignments.

Our goal in this study was to develop decision support systems for resident operating room (OR) assignments using anesthesia information management system (AIMS) records and Accreditation Council for Graduate Medical Education (ACGME) case logs and evaluate the implementations. We developed 2 Web-based systems: an ACGME case-log visualization tool, and Residents Helping in Navigating OR Scheduling (Rhinos), an interactive system that solicits OR assignment requests from residents and creates resident profiles. Resident profiles are snapshots of the cases and procedures each resident has done and were derived from AIMS records and ACGME case logs. A Rhinos pilot was performed for 6 weeks on 2 clinical services. One hundred sixty-five requests were entered and used in OR assignment decisions by a single attending anesthesiologist. Each request consisted of a rank ordered list of up to 3 ORs. Residents had access to detailed information about these cases including surgeon and patient name, age, procedure type, and admission status. Success rates at matching resident requests were determined by comparing requests with AIMS records. Of the 165 requests, 87 first-choice matches (52.7%), 27 second-choice matches (16.4%), and 8 third-choice matches (4.8%) were made. Forty-three requests were unmatched (26.1%). Thirty-nine first-choice requests overlapped (23.6%). Full implementation followed on 8 clinical services for 8 weeks. Seven hundred fifty-four requests were reviewed by 15 attending anesthesiologists, with 339 first-choice matches (45.0%), 122 second-choice matches (16.2%), 55 third-choice matches (7.3%), and 238 unmatched (31.5%). There were 279 overlapping first-choice requests (37.0%). The overall combined match success rate was 69.4%. Separately, we developed an ACGME case-log visualization tool that allows individual resident experiences to be compared against case minimums as well as resident peer groups. We conclude that it is feasible to use ACGME case-log data in decision support systems for informing resident OR assignments. Additional analysis will be necessary to assess the educational impact of these systems.

Implementing computerised workload data collection in rural primary health care.

OBJECTIVE: Describes the implementation of a computerised information system to collect workload data and discusses feedback from staff evaluation of use and value. DESIGN: Feedback interviews following service implementation. SETTING: Remote rural primary health care, Scotland. SUBJECTS: Thirty-three primary health care staff. MAIN OUTCOME MEASURES: Not relevant, as the study was service development with qualitative evaluation. RESULTS: Findings of evaluation interviews indicate a number of themes common to remote rural practice that make implementing a computerised information system problematical. These include: logistical problems caused by small practice teams and wide areas covered; inadequate allowance for recording of blurred roles and the wide range of non-clinical duties carried out; lack of local contextual and cultural information, which is necessary to make sense of data collected. Remote rural health professionals found reports from the system of limited value as they felt they already had good knowledge of local activities and had few opportunities, due to small teams, to use data for service redesign. CONCLUSION: Remote rural primary care is underpinned by a number of organisational and philosophical features that require understanding when considering the implementation of initiatives developed in an urban working environment.

A framework for the evaluation of Internet-based diabetes management.

BACKGROUND: While still in its infancy, Internet-based diabetes management shows great promise for growth. However, the following aspects must be considered: what are the key metrics for the evaluation of a diabetes-management site? how should these sites grow in the future and what services should they offer? OBJECTIVES: The purpose of this paper is to examine the needs of the patient and the health care professional in an Internet-based diabetes-management solution and how these needs are translated into services offered. METHODS: An evaluation framework was constructed based on a literature review that identified the requirements for an Internet-based-diabetes-management solution. The requirements were grouped into 5 categories: Monitoring, Information, Personalization, Communication, and Technology. Two of the market leaders (myDiabetes and LifeMasters) were selected and were evaluated with the framework. The Web sites were evaluated independently by 5 raters using the evaluation framework. All evaluations were performed from November 1, 2001 through December 15, 2001. RESULTS: The agreement level between raters ranged from 60% to 100%. The multi-rater reliability (kappa) was 0.75 for myDiabetes and 0.65 for LifeMasters, indicating substantial agreement. The results of the evaluations indicate that LifeMasters is a more-complete solution than myDiabetes in all dimensions except Information, where both sites were equivalent. LifeMasters satisfied 32 evaluation criteria while myDiabetes satisfied 24 evaluation criteria, out of a possible 40 in the framework. CONCLUSIONS: The framework is based on the recognition that the management of diabetes via the Internet is based on several integrated dimensions: Monitoring, Information, Personalization, Communication, and Technology. A successful diabetes-management system should efficiently integrate all dimensions. The evaluation found that LifeMasters is successful in integrating the health care professional in the management of diabetes and that MyDiabetes is quite effective in providing a communication channel for community creation (however, communication with the health care professional is lacking).

A computer-generated measure of nursing workload for the emergency department based on discharge diagnosis.

A computer-based system which automatically generates nursing workload figures for the Emergency Department is described. This system uses measures derived from the GRASPR system, linked to the discharge diagnosis, to generate total workload figures, obviating the need for data collection or input beyond the initial implementation.

Case mix type as a predictor of nursing workload.

In the current health care service, the need to measure nursing workload has become the subject of major debate. Attempts have been made to relate workload and nurse staffing, however, despite there being systems for this there appears to be no single recognized formula. Case mix groups have been advocated as a useful tool for measuring nursing workload, particularly in Canada where work continues. Case mix groups work on the basis that patients who are clinically similar and use equivalent resources are grouped using procedure and diagnostic codes. The retrospective study examines the relationship between case mix, resource utilization and nursing effort to determine whether future workload could be predicted using these parameters. The sample included 798 patients and 30 nurses over the period 1993-1994 with analysis of data from the Patient Administration System (PAS) and TEAMWORK, which purports to measure nurse workload. Results showed that there was little relationship between nursing workload and case mix grouping and recommendations are made for future research.

Computerized staff scheduling: opportunities and obstacles to success.

Staff scheduling can be a process fraught with failure, drudgery, and frustration. While computerization of staff scheduling can greatly enhance the process, computerization alone is not a panacea. Successful scheduling depends on the existence of effective management systems, including FTE and position control, proper request management, well-defined data, and work-flow and time-line management. The best espresso in the world requires good coffee beans.

Different systems, different costs? An examination of the comparability of workload measurement systems.

This study examines the equivalence of the hours of care estimates of four patient classification/workload measurement systems. Although the hours of care estimates of the systems were similar, differences between the estimates could be as great as 4.53 hours per day for the same patient. The researchers developed relational statements that made hours of care estimates equivalent for all systems studied. System differences can have a profound impact on nursing unit and department budgets, if not adjusted.

Validity and reliability of a pediatric hematology oncology patient acuity tool.

Appropriate use of nursing resources in the pediatric hematology and oncology inpatient settings demands a patient acuity system that is easy to use and accurate, and that objectively measures nursing care needs of a specialized patient population. Structured survey of 13 comprehensive cancer centers and a review of the literature show no valid and reliable acuity tools for this pediatric population. The purpose of this project was to study the validity and reliability of a newly developed pediatric hematology and oncology acuity system designed to quantify patient care needs. A new acuity tool for this pediatric population was developed based on the patient classification tool used at Johns Hopkins Hospital Oncology Center (JHHOC). The levels of care from the JHHOC tool were adopted, with therapeutic indicators modified to reflect nursing diagnoses relevant to the pediatric inpatient. Nursing care hours required for each level of care were also identified. Validity was studied using a content validity index (CVI). Experts from the pediatric unit where the tool would be used were asked whether each therapeutic indicator was assigned to the correct level of care (1 thru 5) based on patient care hours. CVIs for items ranged from .5 to 1.0; the overall CVI for the tool was .93. Interrater reliability was studied using two raters from the unit. Data were collected for 150 patient observations on a 12-bed pediatric hematology and oncology inpatient and short-stay outpatient unit. The resulting Pearson correlation coefficient was r = .97 (P less than .001).(ABSTRACT TRUNCATED AT 250 WORDS)

Knowledge-based schedule formulation and maintenance under uncertainty.

This paper is concerned with the dual sequential problems of (1) determining an acceptable personnel schedule over a specified time period, and (2) adjusting that schedule during the course of its execution in reaction to daily changes in both demand and available personnel. The first problem is schedule formulation; the second sequential problem is schedule execution. A rule-based, hierarchical system has been developed for first modeling and then solving both the schedule formulation and the schedule execution problems as a two-phase dependent process. The system is applied to the scheduling and staffing of nurses. A double-blind evaluation was conducted, which ascertained the quality of the resultant schedules in terms of maintainability, coverage, and personal satisfaction. The evaluation indicates that for units on which personnel changes have occurred, the prototype appears to perform as well as human schedulers.

Selecting a labor information system. What to ask, what to avoid.

Payroll expenses may account for over half of all of a hospital's expenses. Manual time card processing requires an abundance of staff time and can often result in costly errors. To alleviate this problem, many healthcare facilities are implementing computerized labor information systems. To minimize the risk of selecting the wrong system, hospital administrators should ask the following questions before committing to any computerized labor information system: Is the software designed for hospital use and easily adaptable to each hospital's unique policies? How flexible is the software's reporting system? Does it include automatic scheduling that creates generic schedules? Does the system have the capability of securing time and attendance records and documenting the audit trail? Does the system include an accurate and reliable badge reader? What type of hardware is best for the particular hospital--microcomputer, minicomputer, or mainframe? Finally, to guarantee successful software installation, the vendor should have extensive experience and documentation in the system's implementation.