MediSign: Using a Web-Based SignOut System To Improve Provider ...

MediSign: Using a Web-Based SignOut System To Improve Provider Identification Joseph Kannry, MD, Carlton Moore, MD Center for Medical Informatics, Mount Sinai Medical Center, NY, NY Abstract: Continuity of care necessitates communication between the primary providers of inpatient and outpatient care. Communication requires identification of providers in addition to clinical information. We have constructed a webbased SignOut System to improve provider identification. The web-based SignOut System correctly identified the provider for 100% (34/34) of patients in 1997 and 93%(37/40) ofpatients in 1998. The hospital bed census correctly identified the attending provider for 50% (17/34) of patients in 1997 and 73%(29/40) in 1998. When analyzed by attending type (i.e., service and private) the SignOut System correctly identified 86% of service providers in contrast to the hospital bed census that correctly identified 57% of service providers. Both the SignOut System (100%) and the hospital bed census (95%) had superior results in identifying private attendings. The web-based technology provides a familiar user interface and ubiquitous workstation access.

patients and physician assignment is complex and changes rapidly. We propose a new paradigm, provider-centered provider identification. Providers themselves actively and correctly identify their patients. Accurate provider identification facilitates the communication between providers that is necessary for continuity of care. We have developed a World Wide Web (WWW) based signout and interim discharge summary system for medical housestaff5 which employs the new paradigm of provider identification by providers. Housestaff SignOut's have been successfully computerized before the advent of the WWW 6-8 and on the WWW9' I0. However, our system focused on capturing and storing clinical information about the patient's hospitalization directly from inpatient providers during the hospitalization. More importantly our system stored inpatient provider information during hospitalization. Hiltz 1I also tracks inpatient provider information but only for housestaff. After the patient is discharged, an interim discharge summary that contains clinical and provider information from the last signout (day of discharge) is accessible via the hospital's Intranet. Background The Outpatient Primary Care Provider (PCP) at Mount Sinai has no reliable means of accessing information about a patient's recent hospitalization. Discharge summaries, a means of communication between providers, are not always available online at our institution. Additionally, discharge summaries may not always contain the information outpatient providers require1' 2, 12, 13 Contacting Inpatient Providers is a daunting task at Mount Sinai as well as other sites 1. When an outpatient provider at our institution reviews an admission to Medicine, he/she has to determine which of 24 housestaff and 3 service attendings were caring for the patient in question. There are three (General) Medicine Services. Each Medicine Service has 8 housestaff (4 intern-resident pairs) with a total of 24 housestaff for 3 Medicine Services. Each Medicine Service has 1 service attending with a total of 3 service attendings for 3 Medicine Services. However, there are no "service cases" as all

Introduction Continuity of care requires communication between primary inpatient and outpatient providers. Yet, studies have found that primary care physicians were frequently unaware of discharge plans for their hospitalized patientsl. Mageean2 examined all hospital discharge communications for patients from one general practice over a three-month period. In Mageean's study, over half the patients contacted their general practitioners before the general practitioner had received information about the hospitalization. No information was received by the general practitioner for 11% of the discharged patients. A study by Sands3 noted the frustrations of outpatient physicians with discharge medication lists. These lists often had changes that were not communicated to outpatient providers. Finally, in a study by Bowling4, physicians felt that inpatient and outpatient provider communication was a prerequisite of quality care. The prevailing paradigm of provider identification is hospital-centered identification. The hospital determines, as best as it can, which physicians are assigned to which patient. However, in academic medical centers the relationship between

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any hospital workstation. After entering two passwords, housestaff are presented with a Medicine Service (e.g., 10W, 6W, GI) selection screen (Figure 1). Upon selecting a service, users are taken to a SignOut specific to the selected service (Figure 2). Clicking on a patient name generates a data entry screen (Figure 3). One of the mandatory data entry fields is attending name. Blank attending entries are rejected. In an attempt to reduce repetitive data entry

admissions are assigned to an attending (i.e., service or private) and not to a service. Housestaff and service attendings rotate by blocks (months). At our institution, at the end of every working day, inpatient housestaff must signout to the on-call team. Prior to development of the web-based SignOut System, signout was accomplished by using word processing programs. Residents used word processors to make patient lists and include information that the on-call team needed to be aware of for the night or the weekend such as relevant histories, medications and other issues of concern. The signout was saved on a local computer in the oncall room, and updated everyday. When a patient was discharged from the hospital, all signout information was deleted. Method Before software development was undertaken, we identified five design objectives: 1 )Provide functionality equal to the previous SignOut System and to avoid a major disruption in the Medicine housestaff daily routine. Data entry was not a deterrent as residents were not only typing their signouts on word processors but spending a great deal of energy on formatting the signouts. The appearance of the computerized signout was designed to closely resemble the original signout as much as possible. 2)Capture clinical information and provide this information immediately in real time. 3)Create an interim discharge summary that accurately identified inpatient providers and provided some clinical information. 4)Provide immediate access to the interim discharge summary. 5)Use a technology that would provide seamless access regardless of location and a familiar user interface. This technology was the World Wide Web 14. Since Web browsers generate a familiar user interface requiring minimal training, we developed the SignOut System using HyperText Markup Language (HTML) for form development. We used Stormcloud Development Corporation's WebDBC 3.0 to connect the forms to a Microsoft ®Access 97 Database and create dynamic signout pages that prompt the user for the pertinent patient information. WebDBC processes requests from forms and converts these requests via ISAPI and ODBC into database queries. The system is accessed via Mount Sinai's Intranet by using Netscape 4.x. The system runs on a Microsoft ® Windows NT Server 4.0 Service Pack 3. Secure access is provided for by a two-password identification system. Housestaff access the SignOut System by selecting the Mount Sinai Online Icon (Intranet) from

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in the attending field, there is a drop down list of the names of the three service attendings. However, any other attending name may be manually entered. After patients are discharged from the hospital, housestaff will delete the patient from the list of active patients on the SignOut by selecting delete patient on the data entry screen (See figure 3). Upon deletion from the SignOut, housestaff are prompted to complete interim discharge summaries which are populated with information from the last signout entry in order

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provider for 93%(37/40) of patients. The 3 incorrectly identified attendings in the SignOut System were service attendings and a result of "switch-over" error. At the beginning of each block a "switch-over" occurs in which new attendings replace the previous block's attendings. Errors occur when the list of service attendings is not updated for the new block (Fig. 3). The hospital bed census identified the provider for 73% (29/40) of patients. We then further analyzed provider identification by type of attending: service and private. The SignOut System correctly identified the service attending for 86% (18/21) of IMA patients. However, the three errors (mentioned above) were "switch-over" errors. If we correct for "switch-over" errors because the attending type, service, does not change, the identification rate is 100%. The hospital bed census correctly identified the service attending for 57% (12/21) of IMA patients. If we correct for "switch-over" error, the correct identification rate becomes 63%. All other hospital errors were the result of identifying the wrong attending. The SignOut System correctly identified private attendings for 100% (19/19) of patients while the hospital bed census identified private attendings for 95% (18/19) of patients. Discussion The SignOut System identified the service attending provider on 100%(1997) and 84%(1998) of patients because the system relies upon data entry by the primary inpatient caregivers; the resident-intern team. When patients are admitted to one of the Medicine Services, patients are assigned a residentintern team based on a pre-defined call schedule. The resident-intern team will actively seek to identify the attending responsible for care because all decisions must be discussed with the patient's attending. Since SignOut usage is part of everyday workflow, attending provider identification is part of that workflow. If one corrects for "switch-over" errors the identification rate for service attendings in both studies is 100% and 100%. Private attendings are identified correctly by the SignOut for 100% of patients and by the hospital census for 95% of patients. In both systems, identification of private attending providers is part of workflow. Private patients are usually admitted by their private physician, and private physicians make themselves rapidly known to housestaff. In contrast, IMA patients are admitted to service attendings that may need to be informed about the admission by housestaff. The problems with the hospital bed census, particularly in regard to IMA patients, 50% and 57%

to reduce data entry time. Primary care physicians in our outpatient clinics can access the interim discharge summary through our Intranet. System performance was assessed by two studies of attending provider identification. Attending provider information can easily be obtained from both the hospital bed census and the SignOut System and then compared to a gold standard. In the first analysis done in July 1997 the gold standard was the attending's patient log. In the second analysis in 1998, the gold standard was an IRB approved chart review. Results The first analysis of provider identification was done during the initial two-week trial rollout in one General Medicine Service (8 housestaff and 1 service attending) late July 1997. The analysis was restricted to attending provider identification. The gold standard for provider identification was a log of patients by the service attending (JK) of all of JK's patients seen during the 2-week trial period. Housestaff were not prompted to enter or correct information by JK. Of the 34 patients we analyzed attending provider information for, the SignOut correctly identified service providers in 100% of patients while the hospital census identified 50%. A subsequent study of provider identification, for attendings (private and service) was undertaken for all patients admitted to the 3 General Medicine Services in Block 5 (October 19November 12th, 1998). The gold standard was a chart review, with IRB approval, in which attending providers were identified by examining admit notes, admit orders, transfer notes, and discharge notes and/or summaries for provider names. We also noted the provider name stamped on the admit, transfer, and discharge notes by the hospital. The addressograph stamp is nearly identical to the hospital bed census as changes made in the census generate a new addressograph stamp. There were 159 admissions during Block 5 and 40 of the 159 charts were randomly selected for review. The chart distribution, though random, was unequal among the three services: 10 W 73%, 6W 15%, GI/General Medicine 13%. Of the 40 charts, the distribution between service and private attendings was 52.5% service and 47.5% private. Medicine service attendings are members of the IMA (Internal Medicine Associates) practice and are assigned all admitted IMA patients while on service. IMA patients are defined as patients known to the practice as well as patients without hospital follow-up by an outside provider. Using the chart as the gold standard, the SignOut system correctly identified the

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the emergency room is the doctor who will follow the patient in the hospital. This is not necessarily true for IMA patients. The third assumption is that if a patient does not know who his/her doctor is, the patient is assigned a service attending. Severely ill patients may not be able to communicate or may not have been asked about providers. Correction of errors in the hospital-centered system is cumbersome. Error correction requires the provider, who is busy with patient care, to make a list of all errors and then contact appropriate personnel to make corrections. Our provider-centered system provides quick corrections of errors by direct and simplified input. Ironically, billing which is of great importance to the hospital may be delayed because the appropriate physician can not be contacted to complete the chart. An interesting relationship exists between data entry in the SignOut System and the relevance of the data to everyday care. If the data affects daily care, data will be entered correctly and corrections will be made rapidly. For example, housestaff on call check test results and this requires accurate spelling of names and medical record numbers. In our chart review, the spelling of all but one patient name was correct in the SignOut System. All unit numbers in the SignOut System were not only correct but had the extra digit often required to check lab results. The three "switch-over" errors (i.e., prior block attending identified instead of present block) on IMA patients were not corrected because housestaff knew to simply contact the new (block) service attending. However, when attending assignments changed during a block because of reassignment to a different specialty, corrections were made. Limitations of our two studies include: one specialty (Medicine) at one institution (Mount Sinai) and a small patient sample size in both studies; 34 and 40 patients. It can also be argued that JK was a confounding variable in the first analysis in 1997. Therefore our results may not be generalizable. Additionally, our present development mechanism is time consuming and not easily portable because it requires us to develop specialty specific screens and databases for each specialty requesting the SignOut System. We have presently developed the system for Medicine, Oncology, Nephrology, Pediatrics, and ADS (Attending Directed Service). This customization mechanism would hinder porting it to other institutions such as NYU whom we recently merged with. Finally, while present information security is adequate for our Intranet, our security is inadequate for remote access via Internet.

identification rate, can have potentially serious consequences as consultants, social work, families, relatives, floor managers and other services use the bed census to identify and contact attendings. The small difference between the two studies is surprising given the differences in methodology. The first study looked at patients on only one service (6W/9W) and focused in identifying identification errors related to one physician, JK. The second study analyzed results from patients admitted to three services with three different service attendings. Two types of error can occur from the perspective of one service attending. One type is error of correct assignment or inclusion errors. The hospital bed census assigns (includes) patients to Doctor Jones that are not under his care. Dr. Jones assumes management for the case and inappropriately manages another attending's patients, as well as creating potential billing conflicts. Additionally, consultants waste valuable time discussing the case with the wrong attending. The other type of error is one of incorrect assignment or errors of exclusion. The hospital bed census incorrectly assigns (excludes) a patient to Dr. Jones and assigns the patient to another physician Dr Smith. Dr. Smith is unaware of the patient because he has not admitted the patient and Dr. Jones is unaware that the patient needs to be seen by him. Dr. Jones will ultimately find out about the patient from the housestaff but may end up seeing the patient much later in the day because he was unaware of the patient. The hospital bed census is a hospital centered provider identification system. This system is prone to errors because it relies on ancillary personnel in the emergency room, and in central listing (which assigns beds) to identify attending providers. These personnel cannot identify inappropriate provider-patient assignments nor will they contact housestaff and update the system unless prompted to do so. In our provider centered identification system, the inpatient providers, housestaff are entering the information and can change the information if the information is incorrect. These providers understand the complex web of relationships and can spot inappropriate assignments. The hospital-centered system has three underlying assumptions. The first assumption is all patients know which doctor sent them to the emergency room. An attending or housestaff can send an IMA patient to the emergency room but may not be the admitting provider. The second assumption is that the doctor who sent the patient to

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In cooperation with the Hospital, we are developing an improved SignOut System, version 2.x to address existing deficiencies as well as support further research into provider identification. For example, to serve the needs of multiple specialties and provide rapid development, an extensive data model is being developed. This model will attempt to capture the complex web of relationships between providers. The only anticipated customization in version 2.x will be specialty-specific user interfaces. The new system will also be more robust and flexible by employing JavaScript for programming and Oracle® as the database. "Switch-over errors" will be remedied by linking attending names to time ranges (blocks). As a result the system will automatically update attending names at the beginning of each block. Version 2.x will interface directly with the ADT (Admitting, Discharge, and Transfer system) and the hospital bed census. By interfacing with ADT, data entry will be reduced as names, unit numbers, and room assignments will be supplied to the SignOut System. By interfacing with the hospital bed census, the SignOut System will update attending provider names in the census. Before updating provider information in the census system, the SignOut system will store but not display the initial provider name entered into the census by hospital personnel. It is our hope that by storing the initial entry, we will simplify future comparison studies. Finally, the new SignOut System will allow us to evaluate the quantitative and qualitative effects of our system on communication. To quantitatively evaluate our system, we need to determine which patient records were accessed in the interim discharge summary. To qualitatively evaluate the effect of our system we need to identify and contact outpatient users of the interim discharge summary system. Version 2.x will support assessment of communication by having an exhaustive audit trail. Conclusion We have developed a SignOut system that can improve communication by identifying providers and supplying some clinical information in real time. The WWW paradigm allows access to information regardless of computing platform or location, provides a familiar user interface, and meets security and confidentiality requirements through appropriate user verification. Inpatient providers, at Sinai and elsewhere, have no reliable means of communicating requests to outpatient providers1' 15. The first step in improving communication between inpatient and outpatient providers is provider identification. The SignOut System's success in identifying providers is

directly derived from direct data entry by providers as a part of routine workflow. References 1. Balla JI, Jamieson WE. Improving the continuity of care between general practitioners and public hospitals. Med J Aust 1994;161(11-12):656-9. 2. Mageean RJ. Study of "discharge communications" from hospital. Br Med J (Clin Res Ed) 1986;293(6557): 1283-4. 3. Sands DZ, Safran C. Closing the loop of patient care--a clinical trial of a computerized discharge medication program. Proc Annu Symp Comput AppI Med Care 1994:841-5. 4. Bowling A, Jacobson B, Southgate L, Formby J. General practitioners' views on quality specifications for "outpatient referrals and care contracts". Bmj 1991 ;303(6797):292-4. 5. Moore C, Kannry J. Improving Continuity of Care Using A Web Based Signout and Discharge. In: Masys DR, ed. 1997 Annual Fall AMIA Symposium. Nashville, TN: Hanley & Belfus, Inc., 1997:975. 6. Frazer TS. "Doctor's notes": a computerized method for managing inpatient care. Fam Med 1988;20(3):223-4. 7. Ram R, Block B. Signing out patients for offhours coverage: comparison of manual and computer-aided methods. Proc Annu Symp Comput Appl Med Care 1992:114-8. 8. Petersen LA, Orav EJ, Teich JM, O'Neil AC, Brennan TA. Using a computerized sign-out program to improve continuity of inpatient care and prevent adverse events. Jt Comm J Qual Improv 1998;24(2):77-87. 9. Reider J, Norton P. Computerized Sign-out: A Web-based Solution. In: Chute CG, ed. Proceedings AMIA 1998 Annual Symposium. Orlando, Fla.: hanley & Belfus, Inc., 1998:1060. 10. Cimino JJ, Socratous SA, Grewal R. The informatics superhighway: prototyping on the World Wide Web. Proc Annu Symp Comput Appl Med Care 1995:111 5. 11. Hiltz FL, Teich JM. Coverage List: a providerpatient database supporting advanced hospital information services. Proc Annu Symp Comput Appl Med Care

1994:809-13. 12. Bolton P, Mira M, Kennedy P, Lahra MM. The quality of communication between hospitals and general practitioners: an assessment [In Process Citation]. J Qual Clin Pract 1998;18(4):241-7. 13. King MH, Barber SG. Towards better discharge summaries: brevity and structure. West Engl Med J 1991;106(2):40-1, 55. 14. Cimino JJ, Socratous SA, Clayton PD. Internet as clinical information system: application development using the World Wide Web [see comments] [published erratum appears in J Am Med Inform Assoc 1996 Jan-Feb;3(1):41]. J Am Med Inform Assoc 1995;2(5):273-84. 15. Anderson MA, Helms L. An assessment of discharge planning models: communication in referrals for home care. Orthop Nurs 1993; 12(4):41-9.

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