Zero Percent of Terminally Ill Patients with Non-Cancer Receive Palliative Care Service During Hospital Admission

Zero Percent of Terminally Ill Patients with Non-Cancer Receive Palliative Care Service During Hospital Admission | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Zero Percent of Terminally Ill Patients with Non-Cancer Receive Palliative Care Service During Hospital Admission Chutima Kangtanyagan, Pasitpon Vatcharavongvan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1568169/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Terminally ill patients with non-cancer conditions admitted to a hospital may miss palliative care (PC) services opportunities. This study aimed to examine the missed opportunities for PC services among these hospitalized patients. Methods We conducted a cross-sectional study using electronic medical records of patients with non-cancer conditions admitted to internal medicine wards, intensive care units, and cardiac intensive care units. The patients who met the Supportive and Palliative Care Indicators Tool (SPICT) criteria were those with PC needs, and the patients who had advanced care plans or received PC consultation were those receiving PC service. We reported the proportions of PC needs and PC service and their associated factors with crude and adjusted odds ratios. Results Of 459 patients, 49.9% were female, and 92.6% were discharged alive. Their mean age was 63 years old, with an average of ten-day length of stay. Of the patients, 61.7% needed PC according to the SPICT’s criteria, and none received PC services. The patients with dementia/frailty, kidney disease, and heart disease had the highest missed opportunities (100%, 96.8%, and 91.3%, respectively). Age, the number of discharge medications, and length of stay were associated with PC needs, but some of these associations disappeared in subgroup analysis. Conclusion None of the terminally ill patients with non-cancer conditions in our study received PC services. The high proportions of patients with dementia/frailty, kidney disease, and heart disease missed such opportunities. A long length of stay and high numbers of discharge medications were associated with PC needs. Doctors and nurses can use these two factors as a trigger to assess PC needs among these patients. palliative care terminally ill health services accessibility hospitalization Figures Figure 1 Introduction Palliative care (PC) is “an approach that improves the quality of life of patients (adults and children) and their families who are facing problems associated with a life-threatening illness 1 ,” including both cancer and non-cancer conditions. Despite more morbidities and mortality of non-cancer conditions than cancer ones from global data 2 , terminally ill patients with non-cancer conditions have lower opportunities to receive PC services (either PC consultation or initiation) than those with cancer conditions 3 . In contrast to cancers, doctors and patients commonly see non-cancer conditions as controllable diseases and do not foresee the dying process from these conditions. This perception jeopardizes the opportunities for doctors, patients, and family members to discuss advanced care planning (ACP). For example, hepatologists and gastroenterologists reported that their cultural perceptions, patients’ unrealistic expectations about treatment outcomes, and consultation time-constraint were significant barriers to ACP discussion. These barriers could result in late or no ACP and missed opportunities for PC. Patients with the non-cancer illness have lower emergency visits, hospitalization, and admission to intensive care units than their counterparts 4 . Patients with a terminal illness may miss an opportunity to receive PC services. The Supportive and Palliative Care Indicators Tool (SPICT) helps doctors identify patients to whom they should offer the palliative service or initiate a palliative care approach 5 . The SPICT includes general conditions, cancers, and non-cancer conditions. The last clinical indicators are dementia, frailty, neurological diseases, heart and vascular diseases, respiratory diseases, kidney disease, and liver disease with specific conditions. For example, patients with frailty, who cannot perform self-care, have difficulty swallowing, or report frequent falls, should be advised about PC services and ACP. Doctors also need to review medications and treatment plans. The SPICT has high sensitivity (78%) and specificity (72%) in identifying hospital inpatients who may benefit from PC services and ACP 6 . Many studies found that the SPICT helped doctors identify PC needs in patients with chronic non-cancer conditions. A single-center study in Japan reports that 9.2% of elderly patients in a family practice clinic needed a PC approach 7 . These patients had heart/vascular disease, dementia/frailty, and respiratory disease. Renal nurses educated to use the SPICT could identify 16% of patients with a renal disease requiring PC 8 . Of these patients, 72% died within six months of the study with an advance directive. A community-based study in India reports that the SPICT identified 4.31% of the general population and 20% of individuals with chronic conditions requiring PC 9 . The most common chronic conditions were heart disease (37.5%), dementia/frailty (29.5%), and respiratory diseases (19.3%). Patients with chronic conditions such as liver disease, 10 heart disease, 11 COPD, 12 and renal disease, 8 benefit from the SPICT to access PC services from health care providers. Despite increased awareness of PC for patients with chronic conditions, inequity in access to PC services or integrating the PC approach in routine care seems common. Less is known about how many terminally-ill patients with chronic conditions admitted for non-cancer conditions miss opportunities to receive PC services. This study aimed to close this gap by examining the number of patients admitted to internal medicine departments for non-cancer conditions and identified those who met the SPICT criteria for PC but missed the opportunities to receive PC services. The secondary objective was to identify associated factors to PC needs and missed opportunities. Methods Study design and setting We conducted a cross-sectional study in 2018 reviewing patients’ electronic medical records with approval from the Human Research Ethics Committee of Thammasat University (Medicine) (MTU-EC-CF-0-018/63) and permission from the Dean of Thammasat University Hospital (TUH). The TUH is a 600-bed university hospital in Pathum-Thani, a perimeter of Bangkok, Thailand. A PC service in the TUH started in 2017, providing PC consultation to inpatients before expanding service to outpatients. Participants and data collection We included patients with the following criteria: 1) admitted in internal medicine wards, intensive care unit (ICU), and cardiac intensive care unit (CICU), 2) admitted during the 2018 fiscal year (between October 2017 and September 2018), 3) did not have cancer or admitted because of cancer condition. The patients aged 17 or younger were excluded. The sample size needed in this study was 385 patients with a p-value of 0.05 and a power of 0.80. We adjusted the sample size to 462 to compensate for the possibility of having incomplete medical records (the records did not contain sufficient clinical information). We contacted a health informatics unit to select patients according to the inclusion and exclusion criteria, extracted requested data, locked a file with a password, and submitted the digital file to the first author (CK). The first author checked, cleaned, and transferred the data to another datasheet for analysis. We used systematic random sampling to randomly selected the patients. Data requested included demographic data, discharge status, the number of discharge medications, length of stay, International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD 10), and palliative care consultation (yes or no). The first author reviewed the patients’ medical records to assess if the patients should receive PC service and if the patients had advance directives (yes or no). Criteria for PC service We used criteria from SPICT for non-cancer patients to identify which patients should receive PC service. If the patients’ conditions from medical records (ICD 10 or health information) met at least one of the criteria in Table 1 , they should receive PC service. The health conditions included in SPICT were heart disease, valvular disease, respiratory disease, liver disease, kidney disease, neurological disease, dementia, and frailty. We did not use a surprise question or general indicators as PC service criteria because most medical records did not contain this information. If the first author could not decide if the patients should receive PC service, the second author (a palliative care specialist) would review medical records and discuss them with the first author for the final decision. Table 1 The Supportive and Palliative Care Indicators tool’s criteria used in this study Heart/vascular Disease - Heart failure or extensive, untreatable coronary artery disease; With breathlessness or chest pain with minimal effort. - Severe, inoperable peripheral vascular disease. Respiratory disease - Severe, Chronic lung disease; breathlessness at rest or minimal effort between exacerbations. - Persistent hypoxia needing long-term oxygen therapy. - Has needed ventilation for respiratory failure or ventilation is contraindicated. Liver Disease - Cirrhosis with one or more complications in the past year : Diuretic resistant ascites Hepatic encephalopathy Hepatorenal syndrome Bacterial peritonitis Recurrent variceal bleeds - A liver transplant is not possible. Kidney disease - Stage 4 or 5 chronic kidney disease (eGFR < 30ml/min) with deteriorating health. - Kidney failure complicates other life-limiting conditions or treatments. - Stopping or not starting dialysis. Neurological disease - Progressive deterioration in physical and/or cognitive function despite optimal therapy. - Speech problems with increasing difficulty communicating and/or progressive difficulty with swallowing. - Recurrent aspirate pneumonia; breathless or respiratory failure. - Persistent paralysis after stroke with significant loss of function and ongoing disability. Dementia / Frailty - Unable to dress, walk or eat without help. - Eating and drinking less; difficulty with swallowing. - Urinary and fecal incontinence. - Not able to communicate by speaking; little social incontinence. - Frequent falls; fractured femur. - Recurrent febrile episodes or infections; aspiration pneumonia. Data analysis We described the patients’ demographic and hospital-related data using frequency, percentages, means, and standard deviation. The patients with PC consultation or advance directive were defined as those with PC service and were described using proportions. The patients who should receive PC service but did not have PC service were defined as a missed opportunity for PC service. We described data according to disease or health conditions for the cardiovascular system, respiratory system, liver, kidney, neurological, and dementia/frailty. We conducted a logistic regression analysis with a subgroup analysis to identify variables associated with patients who met the SPICT criteria and missed opportunities for PC service. Results Participants Of 462 patients, three were excluded from the study because of insufficient information to decide if the patients met or did not meet the SPICT’s criteria. The mean age was 63 (standard deviation or SD = 17.5), and the average length of stay was ten days (SD = 12) (Table 2 ). Of 459 patients, 49.9% were female, and 92.6% were alive when discharged from the hospital. Table 2 The patients’ characteristics ( n = 459) Variables Numbers (%) Age – mean (SD) 63.5 (17.5) Length of stay – mean (SD) 9.8 (11.6) Numbers of medications at discharge – mean (SD) 7.1 (4.6) Numbers of diagnoses per patient – mean (SD) 1.1 (0.4) Female 229 (49.9) Discharge status Alive 425 (92.6) Diagnoses Heart disease 150 (32.7) Neurological disease 132 (28.8) Kidney disease 62 (13.5) Respiratory disease 38 (8.3) Liver disease 16 (3.5) Dementia/frailty 13 (2.8) Met The SPICT * criteria 283 (61.7) Missed opportunity for PC * service 283 (100) * Abbreviation: SPICT - Supportive and Palliative Care Indicators tool, PC – palliative care Factors associated with the patients who met the SPICT criteria Of 459 patients, 61.7% met the SPICT criteria. The highest proportions of diagnoses in patients who should receive PC service were dementia/frailty (100%), kidney disease (96.8%), and heart disease (91.3%) (Fig. 1 ). None of these patients (283), who met the SPICT’s criteria, received PC service. In a logistic regression analysis, age (adjusted odds ratio or aOR = 1.04, 95% confident interval or 95%CI = 1.02–1.06), the number of discharge medications (aOR = 1.09, 95%CI = 1.01–1.18), and length of stay (aOR = 1.05, 95%CI = 1.01–1.09) were associated with the patients who met the SPICT criteria (Table 3 ). Logistic regression analysis for the missed opportunity for PC service could not be conducted because 100% of the patients, who met the SPICT criteria, did not receive PC service. Table 3 Logistic regression analysis for the patients who should receive palliative care service ( n = 459) Variables Crude OR * 95%CI * Adjusted OR * 95%CI * Sex (Female) 0.77 0.53–1.12 1.36 0.77–2.47 Age 1.04 1.03–1.06 1.04 1.02–1.06 The number of discharge medications 1.10 1.05–1.15 1.09 1.01–1.18 Length of stay 1.04 1.02–1.06 1.05 1.01–1.09 Alive upon discharge 0.47 0.21–1.06 0.26 0.07–1.18 * Abbreviations: OR – odds ratio, 95%CI – 95% confident interval Subgroup analysis Subgroup analysis shows that each disease has different factors associated with the patients who met the SPICT criteria (Table 4 ). The number of discharge medications for patients with heart disease was related to those who should receive PC service (aOR = 1.22, 95%CI = 1.06–1.41). Age was associated with those with an indication for PC service in patients with respiratory disease (aOR = 1.13, 95%CI = 1.03–1.24) and neurological disease (aOR = 1.04, 95%CI = 1.01–1.07), while female sex was related to neurological disease only (aOR = 2.51, 95%CI = 1.03–6.14). Table 4 Logistic regression with subgroup analysis for the patients who should receive palliative care service Variables Crude OR * 95%CI * Adjusted OR * 95%CI * Heart disease ( n = 150) Sex (Female) 1.21 0.38–3.89 1.18 0.33–4.22 Age 1.02 0.98–1.06 1.00 0.96–1.04 Length of stay 1.36 1.04–1.78 1.26 0.99–1.62 The number of discharge medications 1.22 1.06–1.41 1.19 1.01–1.09 Respiratory disease ( n = 38) Sex (Female) 1.00 0.27–3.73 0.14 0.01–2.17 Age 1.09 1.03–1.15 1.13 1.03–1.24 Length of stay 1.14 1.00 *** -1.30 1.31 0.98–1.76 The number of discharge medications 1.14 0.97–1.35 1.09 0.88–1.35 Liver disease ( n = 16) Sex (Female) 1.80 0.21–15.41 1.82 0.18–18.31 Age 1.05 0.96–1.15 1.05 0.95–1.15 Length of stay 1.02 0.96–1.07 1.01 0.94–1.08 The number of discharge medications 1.09 0.89–1.32 1.01 0.77–1.32 Kidney disease ( n = 62) Sex (Female) 0.94 0.06–15.66 1.16 0.02–72.3 Age 1.08 0.99–1.17 1.17 0.96–1.42 Length of stay 0.97 0.91–1.03 0.89 0.77–1.04 The number of discharge medications 1.13 0.88–1.45 1.32 0.88–1.98 Neurological disease ( n = 132) Sex (Female) 2.49 1.09–5.73 2.51 1.03–6.14 Age 1.05 1.02–1.08 1.04 1.01–1.07 Length of stay 1.06 1.00 *** -1.12 1.05 1.00 ** -1.11 The number of discharge medications 1.04 0.94–1.15 1.04 0.93–1.17 * Abbreviations: OR – odds ratio, 95%CI – 95% confident interval ** value is less than 1.000 *** value is greater than 1.000 Discussion This study examined the missed opportunity for PC service, either consultation or initiation, in terminally-ill inpatients with non-cancer conditions admitted to the hospital. We used the criteria from the SPICT to determine which patients should receive PC service. The patients missed the opportunity for PC service if they met the SPICT criteria but did not have an advance directive or PC consultation. Of 459 patients, 61.7% met the SPICT criteria, and none of these patients received PC service. To our surprise, zero patients eligible for PC service did not have an advance directive or PC consultation. A previous study found that many inpatients, particularly those with non-cancer illnesses, miss an opportunity to receive PC service 13 . The findings indicate that about 67% of the decedent patients dying in a hospital did not receive PC consultation, and those having PC consultation received the service too late (about eight days before death). This inequity in PC consultation among patients with non-cancer conditions is the main concern in many countries 3 , 14 , 15 . For example, a nine-year observation study reports that less than 30% of terminally-ill patients with non-cancer conditions admitted to the hospital received PC consultation service, though a trend was improved from less than 1% in 2011 to 27.7% in 2019 15 . Patients with non-cancer conditions were six times less likely to be registered in PC service than those with cancer 14 . We could not compare the difference in sex, age, and other variables regarding the missed opportunity for PC service because none of our patients received the service, and to the best of our knowledge, no study examines these associations. Nevertheless, previous studies found that patients’ poor knowledge and lack of awareness about PC of patients 16 and health care providers’ skills to identify PC needs in patients with non-cancer conditions 17 – 19 are the main barriers to the PC service. In our study, the patients with dementia/frailty, kidney disease, and heart disease had the highest percentages of missed opportunities to receive PC service. According to the WHO’s 2020 global report on palliative care, these three diseases accounted for 29.1% of patients with palliative care needs 20 . For patients with dementia/frailty, no study directly examined missed opportunities for PC services. Nevertheless, one study in the UK reported that almost 65% of patients with dementia in nursing homes did not access hospice before death 21 . For patients with kidney disease, one study shows that PC consultation rates were low for patients with kidney diseases (14.7% for estimated glomerular filtration rate or eGFR < 60 mL/minutes, 57.1% for eGFR < 15 mL/minutes, and 28.9% for those stopping hemodialysis) 22 . For patients with heart disease, Gadoud et al. reported that 93% of patients with heart failure in primary care did not receive PC service, compared to 52% of those with cancer 23 . Another study found that more than 90% of hospitalized patients missed the opportunity to receive PC service 24 . With low access to PC service, patients with these conditions miss a chance of advance care planning, resulting in high hospitalization rates, low utilization of hospice, and poorly controlled symptoms 25 , 26 . Timely PC consultation and initiation are keys to the quality of life in terminally-ill patients, particularly at the end of life 4 , 22 . Although the SPICT 5 , surprise question, and other tools 27 can help doctors and nurses detect patients who need and receive benefits from PC service in the early phase, missed opportunities can occur 27 . One study reports the varied accuracy of screening tools, such as the SPICT, with sensitivity ranging from 3.2–94% and specificity ranging from 26.4–99% 28 . The findings show that some available tools are not sensitive enough to trigger doctors and nurses to initiate PC service. Furthermore, PC needs identified from these screening tools do not reflect the reality that patients will receive PC service 27 , 28 . As aforementioned, patients with non-cancer have a high chance of missed opportunities for receiving PC service because of many barriers 29 , 30 , including lack of valid screening tools and screening system 27 . Our study found associated factors that might trigger doctors and nurses to use the SPICT and surprise questions in their patients. These factors included sex, age, length of stay, and the number of discharged medications. However, the last three factors can be the most practical triggers for doctors and nurses to assess PC needs and initiate PC service. Educating doctors and nurses to use these factors to identify patients with PC needs as the first step of PC initiation may increase the opportunities for the patients who need PC to receive timely services and, hence, improve quality of life and symptom control. Not many studies examined factors associated with PC needs in patients with non-cancer conditions, and our study found that the associated factors were different from disease to disease. For example, age was related to PC needs in patients with respiratory and neurological diseases but not those with heart, liver, and kidney diseases. However, these findings from our study were the secondary objectives with a lack of statistical power to test the hypothesis. Nevertheless, these findings urge us to explore who is most likely to miss opportunities for PC service. There were limitations to this study. First, this study used data from medical records. Though we reviewed all relevant data, unrecorded information could not be collected, leading to the wrong assumption as no ACP and no PC consultation. Second, we examined only patients admitted to internal medicine wards, ICU, and CICU. PC needs and services in patients with non-cancer conditions in other wards, such as surgery and obstetrics-gynecology, may differ. Last, missed opportunities in our study may happen from the lack of PC awareness and knowledge among doctors and nurses because we gathered the data one year after the hospital had provided the PC service. However, we believe that the proportion of patients with non-cancer conditions admitted to a hospital and receiving PC service is still low. Conclusion None of the terminally-ill patients with non-cancer conditions admitted to the hospital in our study received PC service, though they needed it. Patients with dementia/frailty, kidney disease, and heart disease were prone to miss the opportunities to receive PC service. The longer the length of stay and the more the discharged medications, the higher probability the patients will need PC. Doctors and nurses need to be aware of these associated factors and screening tools for PC to increase access to PC services among patients with non-cancer conditions. Declarations Acknowledgment We are grateful to the hospital staff for facilitating data collection. We would like to thank Miss Termsook Rakseethong, a palliative care nurse specialist, for giving us advice on medical record review. Declaration of Interest The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article. Funding The authors received no financial support for this article’s research, authorship, and publication. ORCID Chutima Kangtanyagan: https://orcid.org/0000-0002-3704-6841 Pasitpon Vatcharavongvan: https://orcid.org/0000-0002-8655-7154 References Sepúlveda C, Marlin A, Yoshida T, Ullrich A. 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Identification of patients with potential palliative care needs: a systematic review of screening tools in primary care. Palliat Med. 2020;34(8):989–1005. Kichler CM, Cothran FA, Phillips MA. Effect of a Palliative Screening Tool on Referrals: An Approach to Increase Access to Palliative Care Services. Journal of Hospice & Palliative Nursing. 2018;20(6):548–553. doi: 10.1097/njh.0000000000000475 Dalgaard KM, Bergenholtz H, Nielsen ME, Timm H. Early integration of palliative care in hospitals: A systematic review on methods, barriers, and outcome. Palliative and Supportive Care. 2014;12(6):495–513. doi: 10.1017/S1478951513001338 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1568169","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":99340654,"identity":"e91430b2-b713-4332-a5f5-6cd632af1568","order_by":0,"name":"Chutima Kangtanyagan","email":"","orcid":"https://orcid.org/0000-0002-3704-6841","institution":"KamPhaeng Phet Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chutima","middleName":"","lastName":"Kangtanyagan","suffix":""},{"id":99340655,"identity":"19987c8f-1964-4951-9850-ae884176fa91","order_by":1,"name":"Pasitpon Vatcharavongvan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYJCCAyCCH0RU2KAK4tYCkpZsYGZgOJPGIAERS8CvBWyiwQFitZizH394+OMOmzzj8+cPfjiQwFAH1PvwA+OPOzi1WPbkGBw4eCat2OxGMrMEUIuEwQE2YwmGhGc4tRgcyGE4cLDtcOK2G8wM0h9/gLQwmAEddhi3lvPPH4C1bO4/zPwDYgv7N/xabiQYgLVsYEhmgzqMB78tljPeGBw4eyYtccaNZDOLAwkSkjMP8xRLJKTh1mLOn/74Q+UOm8T+/oOPbxxIsOHnO96+8cMHGzwOAxGMDXA+MFqA8cOQgFMDppZRMApGwSgYBZgAAIUsYNwZHFo/AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-8655-7154","institution":"Thammasat University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Pasitpon","middleName":"","lastName":"Vatcharavongvan","suffix":""}],"badges":[],"createdAt":"2022-04-18 08:00:45","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-1568169/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1568169/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":20502755,"identity":"e6492e87-68f8-446c-80ae-eace484cbd40","added_by":"auto","created_at":"2022-04-19 14:15:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":14547,"visible":true,"origin":"","legend":"\u003cp\u003ePercentages of the patients who should receive palliative care service by diagnoses\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-1568169/v1/384b20e1b03af4fc9865573e.png"},{"id":20502756,"identity":"14f3033f-202a-4c66-a091-7207a78bd578","added_by":"auto","created_at":"2022-04-19 14:15:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":303110,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1568169/v1/1831e67f-b308-436c-bd09-64349ca0c9fa.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eZero Percent of Terminally Ill Patients with Non-Cancer Receive Palliative Care Service During Hospital Admission\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePalliative care (PC) is \u0026ldquo;an approach that improves the quality of life of patients (adults and children) and their families who are facing problems associated with a life-threatening illness\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e,\u0026rdquo; including both cancer and non-cancer conditions. Despite more morbidities and mortality of non-cancer conditions than cancer ones from global data \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, terminally ill patients with non-cancer conditions have lower opportunities to receive PC services (either PC consultation or initiation) than those with cancer conditions \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In contrast to cancers, doctors and patients commonly see non-cancer conditions as controllable diseases and do not foresee the dying process from these conditions. This perception jeopardizes the opportunities for doctors, patients, and family members to discuss advanced care planning (ACP). For example, hepatologists and gastroenterologists reported that their cultural perceptions, patients\u0026rsquo; unrealistic expectations about treatment outcomes, and consultation time-constraint were significant barriers to ACP discussion. These barriers could result in late or no ACP and missed opportunities for PC. Patients with the non-cancer illness have lower emergency visits, hospitalization, and admission to intensive care units than their counterparts \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePatients with a terminal illness may miss an opportunity to receive PC services. The Supportive and Palliative Care Indicators Tool (SPICT) helps doctors identify patients to whom they should offer the palliative service or initiate a palliative care approach \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The SPICT includes general conditions, cancers, and non-cancer conditions. The last clinical indicators are dementia, frailty, neurological diseases, heart and vascular diseases, respiratory diseases, kidney disease, and liver disease with specific conditions. For example, patients with frailty, who cannot perform self-care, have difficulty swallowing, or report frequent falls, should be advised about PC services and ACP. Doctors also need to review medications and treatment plans. The SPICT has high sensitivity (78%) and specificity (72%) in identifying hospital inpatients who may benefit from PC services and ACP \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMany studies found that the SPICT helped doctors identify PC needs in patients with chronic non-cancer conditions. A single-center study in Japan reports that 9.2% of elderly patients in a family practice clinic needed a PC approach \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. These patients had heart/vascular disease, dementia/frailty, and respiratory disease. Renal nurses educated to use the SPICT could identify 16% of patients with a renal disease requiring PC \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Of these patients, 72% died within six months of the study with an advance directive. A community-based study in India reports that the SPICT identified 4.31% of the general population and 20% of individuals with chronic conditions requiring PC \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. The most common chronic conditions were heart disease (37.5%), dementia/frailty (29.5%), and respiratory diseases (19.3%). Patients with chronic conditions such as liver disease, \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e heart disease, \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e COPD, \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e and renal disease, \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e benefit from the SPICT to access PC services from health care providers.\u003c/p\u003e \u003cp\u003eDespite increased awareness of PC for patients with chronic conditions, inequity in access to PC services or integrating the PC approach in routine care seems common. Less is known about how many terminally-ill patients with chronic conditions admitted for non-cancer conditions miss opportunities to receive PC services. This study aimed to close this gap by examining the number of patients admitted to internal medicine departments for non-cancer conditions and identified those who met the SPICT criteria for PC but missed the opportunities to receive PC services. The secondary objective was to identify associated factors to PC needs and missed opportunities.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design and setting\u003c/p\u003e\n\u003cp\u003eWe conducted a cross-sectional study in 2018 reviewing patients\u0026rsquo; electronic medical records with approval from the Human Research Ethics Committee of Thammasat University (Medicine) (MTU-EC-CF-0-018/63) and permission from the Dean of Thammasat University Hospital (TUH). The TUH is a 600-bed university hospital in Pathum-Thani, a perimeter of Bangkok, Thailand. A PC service in the TUH started in 2017, providing PC consultation to inpatients before expanding service to outpatients.\u003c/p\u003e\n\u003cp\u003eParticipants and data collection\u003c/p\u003e\n\u003cp\u003eWe included patients with the following criteria: 1) admitted in internal medicine wards, intensive care unit (ICU), and cardiac intensive care unit (CICU), 2) admitted during the 2018 fiscal year (between October 2017 and September 2018), 3) did not have cancer or admitted because of cancer condition. The patients aged 17 or younger were excluded. The sample size needed in this study was 385 patients with a p-value of 0.05 and a power of 0.80. We adjusted the sample size to 462 to compensate for the possibility of having incomplete medical records (the records did not contain sufficient clinical information).\u003c/p\u003e\n\u003cp\u003eWe contacted a health informatics unit to select patients according to the inclusion and exclusion criteria, extracted requested data, locked a file with a password, and submitted the digital file to the first author (CK). The first author checked, cleaned, and transferred the data to another datasheet for analysis. We used systematic random sampling to randomly selected the patients. Data requested included demographic data, discharge status, the number of discharge medications, length of stay, International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD 10), and palliative care consultation (yes or no). The first author reviewed the patients\u0026rsquo; medical records to assess if the patients should receive PC service and if the patients had advance directives (yes or no).\u003c/p\u003e\n\u003cp\u003eCriteria for PC service\u003c/p\u003e\n\u003cp\u003eWe used criteria from SPICT for non-cancer patients to identify which patients should receive PC service. If the patients\u0026rsquo; conditions from medical records (ICD 10 or health information) met at least one of the criteria in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, they should receive PC service. The health conditions included in SPICT were heart disease, valvular disease, respiratory disease, liver disease, kidney disease, neurological disease, dementia, and frailty. We did not use a surprise question or general indicators as PC service criteria because most medical records did not contain this information. If the first author could not decide if the patients should receive PC service, the second author (a palliative care specialist) would review medical records and discuss them with the first author for the final decision.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe Supportive and Palliative Care Indicators tool\u0026rsquo;s criteria used in this study\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"1\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHeart/vascular Disease\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Heart failure or extensive, untreatable coronary artery disease; With breathlessness or chest pain with minimal effort.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Severe, inoperable peripheral vascular disease.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRespiratory disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Severe, Chronic lung disease; breathlessness at rest or minimal effort between exacerbations.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Persistent hypoxia needing long-term oxygen therapy.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Has needed ventilation for respiratory failure or ventilation is contraindicated.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiver Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Cirrhosis with one or more complications in the past year :\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003eDiuretic resistant ascites\u003c/li\u003e\n \u003cli\u003eHepatic encephalopathy\u003c/li\u003e\n \u003cli\u003eHepatorenal syndrome\u003c/li\u003e\n \u003cli\u003eBacterial peritonitis\u003c/li\u003e\n \u003cli\u003eRecurrent variceal bleeds\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- A liver transplant is not possible.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKidney disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Stage 4 or 5 chronic kidney disease (eGFR\u0026thinsp;\u0026lt;\u0026thinsp;30ml/min) with deteriorating health.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Kidney failure complicates other life-limiting conditions or treatments.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Stopping or not starting dialysis.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeurological disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Progressive deterioration in physical and/or cognitive function despite optimal therapy.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Speech problems with increasing difficulty communicating and/or progressive difficulty with swallowing.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Recurrent aspirate pneumonia; breathless or respiratory failure.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Persistent paralysis after stroke with significant loss of function and ongoing disability.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDementia / Frailty\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Unable to dress, walk or eat without help.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Eating and drinking less; difficulty with swallowing.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Urinary and fecal incontinence.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Not able to communicate by speaking; little social incontinence.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Frequent falls; fractured femur.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e- Recurrent febrile episodes or infections; aspiration pneumonia.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eData analysis\u003c/h2\u003e\n \u003cp\u003eWe described the patients\u0026rsquo; demographic and hospital-related data using frequency, percentages, means, and standard deviation. The patients with PC consultation or advance directive were defined as those with PC service and were described using proportions. The patients who should receive PC service but did not have PC service were defined as a missed opportunity for PC service. We described data according to disease or health conditions for the cardiovascular system, respiratory system, liver, kidney, neurological, and dementia/frailty. We conducted a logistic regression analysis with a subgroup analysis to identify variables associated with patients who met the SPICT criteria and missed opportunities for PC service.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eParticipants\u003c/p\u003e\n\u003cp\u003eOf 462 patients, three were excluded from the study because of insufficient information to decide if the patients met or did not meet the SPICT\u0026rsquo;s criteria. The mean age was 63 (standard deviation or SD\u0026thinsp;=\u0026thinsp;17.5), and the average length of stay was ten days (SD\u0026thinsp;=\u0026thinsp;12) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Of 459 patients, 49.9% were female, and 92.6% were alive when discharged from the hospital.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe patients\u0026rsquo; characteristics (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;459)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumbers\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge \u0026ndash; mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of stay \u0026ndash; mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumbers of medications at discharge \u0026ndash; mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumbers of diagnoses per patient \u0026ndash; mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(49.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDischarge status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e425\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(92.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiagnoses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurological disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKidney disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDementia/frailty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMet The SPICT\u003csup\u003e*\u003c/sup\u003e criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(61.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMissed opportunity for PC\u003csup\u003e*\u003c/sup\u003e service\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e* Abbreviation: SPICT - Supportive and Palliative Care Indicators tool, PC \u0026ndash; palliative care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eFactors associated with the patients who met the SPICT criteria\u003c/p\u003e\n\u003cp\u003eOf 459 patients, 61.7% met the SPICT criteria. The highest proportions of diagnoses in patients who should receive PC service were dementia/frailty (100%), kidney disease (96.8%), and heart disease (91.3%) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). None of these patients (283), who met the SPICT\u0026rsquo;s criteria, received PC service. In a logistic regression analysis, age (adjusted odds ratio or aOR\u0026thinsp;=\u0026thinsp;1.04, 95% confident interval or 95%CI\u0026thinsp;=\u0026thinsp;1.02\u0026ndash;1.06), the number of discharge medications (aOR\u0026thinsp;=\u0026thinsp;1.09, 95%CI\u0026thinsp;=\u0026thinsp;1.01\u0026ndash;1.18), and length of stay (aOR\u0026thinsp;=\u0026thinsp;1.05, 95%CI\u0026thinsp;=\u0026thinsp;1.01\u0026ndash;1.09) were associated with the patients who met the SPICT criteria (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Logistic regression analysis for the missed opportunity for PC service could not be conducted because 100% of the patients, who met the SPICT criteria, did not receive PC service.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic regression analysis for the patients who should receive palliative care service (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;459)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCrude OR\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted OR\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.53\u0026ndash;1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u0026ndash;2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u0026ndash;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u0026ndash;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of discharge medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u0026ndash;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u0026ndash;1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u0026ndash;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u0026ndash;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlive upon discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u0026ndash;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u0026ndash;1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003eAbbreviations: OR \u0026ndash; odds ratio, 95%CI \u0026ndash; 95% confident interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eSubgroup analysis\u003c/p\u003e\n\u003cp\u003eSubgroup analysis shows that each disease has different factors associated with the patients who met the SPICT criteria (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). The number of discharge medications for patients with heart disease was related to those who should receive PC service (aOR\u0026thinsp;=\u0026thinsp;1.22, 95%CI\u0026thinsp;=\u0026thinsp;1.06\u0026ndash;1.41). Age was associated with those with an indication for PC service in patients with respiratory disease (aOR\u0026thinsp;=\u0026thinsp;1.13, 95%CI\u0026thinsp;=\u0026thinsp;1.03\u0026ndash;1.24) and neurological disease (aOR\u0026thinsp;=\u0026thinsp;1.04, 95%CI\u0026thinsp;=\u0026thinsp;1.01\u0026ndash;1.07), while female sex was related to neurological disease only (aOR\u0026thinsp;=\u0026thinsp;2.51, 95%CI\u0026thinsp;=\u0026thinsp;1.03\u0026ndash;6.14).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic regression with subgroup analysis for the patients who should receive palliative care service\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCrude OR\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted OR\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eHeart disease (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u0026ndash;3.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u0026ndash;4.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026ndash;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u0026ndash;1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u0026ndash;1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u0026ndash;1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of discharge medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u0026ndash;1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u0026ndash;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eRespiratory disease (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27\u0026ndash;3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u0026ndash;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u0026ndash;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u0026ndash;1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003csup\u003e***\u003c/sup\u003e-1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026ndash;1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of discharge medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u0026ndash;1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u0026ndash;1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eLiver disease (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u0026ndash;15.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u0026ndash;18.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u0026ndash;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u0026ndash;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u0026ndash;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u0026ndash;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of discharge medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u0026ndash;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u0026ndash;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eKidney disease (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u0026ndash;15.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u0026ndash;72.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u0026ndash;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u0026ndash;1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91\u0026ndash;1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u0026ndash;1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of discharge medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u0026ndash;1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u0026ndash;1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eNeurological disease (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex (Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u0026ndash;5.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03\u0026ndash;6.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u0026ndash;1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u0026ndash;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003csup\u003e***\u003c/sup\u003e-1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003csup\u003e**\u003c/sup\u003e-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe number of discharge medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u0026ndash;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93\u0026ndash;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003csup\u003e*\u003c/sup\u003eAbbreviations: OR \u0026ndash; odds ratio, 95%CI \u0026ndash; 95% confident interval\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e**\u003c/sup\u003evalue is less than 1.000\u003c/p\u003e\n \u003cp\u003e\u003csup\u003e***\u003c/sup\u003evalue is greater than 1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the missed opportunity for PC service, either consultation or initiation, in terminally-ill inpatients with non-cancer conditions admitted to the hospital. We used the criteria from the SPICT to determine which patients should receive PC service. The patients missed the opportunity for PC service if they met the SPICT criteria but did not have an advance directive or PC consultation. Of 459 patients, 61.7% met the SPICT criteria, and none of these patients received PC service.\u003c/p\u003e \u003cp\u003eTo our surprise, zero patients eligible for PC service did not have an advance directive or PC consultation. A previous study found that many inpatients, particularly those with non-cancer illnesses, miss an opportunity to receive PC service \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The findings indicate that about 67% of the decedent patients dying in a hospital did not receive PC consultation, and those having PC consultation received the service too late (about eight days before death). This inequity in PC consultation among patients with non-cancer conditions is the main concern in many countries \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. For example, a nine-year observation study reports that less than 30% of terminally-ill patients with non-cancer conditions admitted to the hospital received PC consultation service, though a trend was improved from less than 1% in 2011 to 27.7% in 2019 \u003csup\u003e15\u003c/sup\u003e. Patients with non-cancer conditions were six times less likely to be registered in PC service than those with cancer \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. We could not compare the difference in sex, age, and other variables regarding the missed opportunity for PC service because none of our patients received the service, and to the best of our knowledge, no study examines these associations. Nevertheless, previous studies found that patients\u0026rsquo; poor knowledge and lack of awareness about PC of patients \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and health care providers\u0026rsquo; skills to identify PC needs in patients with non-cancer conditions\u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e are the main barriers to the PC service.\u003c/p\u003e \u003cp\u003eIn our study, the patients with dementia/frailty, kidney disease, and heart disease had the highest percentages of missed opportunities to receive PC service. According to the WHO\u0026rsquo;s 2020 global report on palliative care, these three diseases accounted for 29.1% of patients with palliative care needs \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. For patients with dementia/frailty, no study directly examined missed opportunities for PC services. Nevertheless, one study in the UK reported that almost 65% of patients with dementia in nursing homes did not access hospice before death \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. For patients with kidney disease, one study shows that PC consultation rates were low for patients with kidney diseases (14.7% for estimated glomerular filtration rate or eGFR\u0026thinsp;\u0026lt;\u0026thinsp;60 mL/minutes, 57.1% for eGFR\u0026thinsp;\u0026lt;\u0026thinsp;15 mL/minutes, and 28.9% for those stopping hemodialysis) \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. For patients with heart disease, Gadoud et al. reported that 93% of patients with heart failure in primary care did not receive PC service, compared to 52% of those with cancer \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Another study found that more than 90% of hospitalized patients missed the opportunity to receive PC service \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. With low access to PC service, patients with these conditions miss a chance of advance care planning, resulting in high hospitalization rates, low utilization of hospice, and poorly controlled symptoms \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTimely PC consultation and initiation are keys to the quality of life in terminally-ill patients, particularly at the end of life \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Although the SPICT \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, surprise question, and other tools \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e can help doctors and nurses detect patients who need and receive benefits from PC service in the early phase, missed opportunities can occur \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. One study reports the varied accuracy of screening tools, such as the SPICT, with sensitivity ranging from 3.2\u0026ndash;94% and specificity ranging from 26.4\u0026ndash;99% \u003csup\u003e28\u003c/sup\u003e. The findings show that some available tools are not sensitive enough to trigger doctors and nurses to initiate PC service. Furthermore, PC needs identified from these screening tools do not reflect the reality that patients will receive PC service \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. As aforementioned, patients with non-cancer have a high chance of missed opportunities for receiving PC service because of many barriers \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, including lack of valid screening tools and screening system \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Our study found associated factors that might trigger doctors and nurses to use the SPICT and surprise questions in their patients. These factors included sex, age, length of stay, and the number of discharged medications. However, the last three factors can be the most practical triggers for doctors and nurses to assess PC needs and initiate PC service. Educating doctors and nurses to use these factors to identify patients with PC needs as the first step of PC initiation may increase the opportunities for the patients who need PC to receive timely services and, hence, improve quality of life and symptom control.\u003c/p\u003e \u003cp\u003eNot many studies examined factors associated with PC needs in patients with non-cancer conditions, and our study found that the associated factors were different from disease to disease. For example, age was related to PC needs in patients with respiratory and neurological diseases but not those with heart, liver, and kidney diseases. However, these findings from our study were the secondary objectives with a lack of statistical power to test the hypothesis. Nevertheless, these findings urge us to explore who is most likely to miss opportunities for PC service.\u003c/p\u003e \u003cp\u003eThere were limitations to this study. First, this study used data from medical records. Though we reviewed all relevant data, unrecorded information could not be collected, leading to the wrong assumption as no ACP and no PC consultation. Second, we examined only patients admitted to internal medicine wards, ICU, and CICU. PC needs and services in patients with non-cancer conditions in other wards, such as surgery and obstetrics-gynecology, may differ. Last, missed opportunities in our study may happen from the lack of PC awareness and knowledge among doctors and nurses because we gathered the data one year after the hospital had provided the PC service. However, we believe that the proportion of patients with non-cancer conditions admitted to a hospital and receiving PC service is still low.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNone of the terminally-ill patients with non-cancer conditions admitted to the hospital in our study received PC service, though they needed it. Patients with dementia/frailty, kidney disease, and heart disease were prone to miss the opportunities to receive PC service. The longer the length of stay and the more the discharged medications, the higher probability the patients will need PC. Doctors and nurses need to be aware of these associated factors and screening tools for PC to increase access to PC services among patients with non-cancer conditions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the hospital staff for facilitating data collection. We would like to thank Miss Termsook Rakseethong, a palliative care nurse specialist, for giving us advice on medical record review.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no financial support for this article\u0026rsquo;s research, authorship, and publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eORCID\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChutima Kangtanyagan: https://orcid.org/0000-0002-3704-6841\u003c/p\u003e\n\u003cp\u003ePasitpon Vatcharavongvan: https://orcid.org/0000-0002-8655-7154\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSep\u0026uacute;lveda C, Marlin A, Yoshida T, Ullrich A. 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Palliative and Supportive Care. 2014;12(6):495\u0026ndash;513. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1017/S1478951513001338\u003c/span\u003e\u003cspan address=\"10.1017/S1478951513001338\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Thammasat University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"palliative care, terminally ill, health services accessibility, hospitalization","lastPublishedDoi":"10.21203/rs.3.rs-1568169/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1568169/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTerminally ill patients with non-cancer conditions admitted to a hospital may miss palliative care (PC) services opportunities. This study aimed to examine the missed opportunities for PC services among these hospitalized patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e We conducted a cross-sectional study using electronic medical records of patients with non-cancer conditions admitted to internal medicine wards, intensive care units, and cardiac intensive care units. The patients who met the Supportive and Palliative Care Indicators Tool (SPICT) criteria were those with PC needs, and the patients who had advanced care plans or received PC consultation were those receiving PC service. We reported the proportions of PC needs and PC service and their associated factors with crude and adjusted odds ratios.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf 459 patients, 49.9% were female, and 92.6% were discharged alive. Their mean age was 63 years old, with an average of ten-day length of stay. Of the patients, 61.7% needed PC according to the SPICT\u0026rsquo;s criteria, and none received PC services. The patients with dementia/frailty, kidney disease, and heart disease had the highest missed opportunities (100%, 96.8%, and 91.3%, respectively). Age, the number of discharge medications, and length of stay were associated with PC needs, but some of these associations disappeared in subgroup analysis.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eNone of the terminally ill patients with non-cancer conditions in our study received PC services. The high proportions of patients with dementia/frailty, kidney disease, and heart disease missed such opportunities. A long length of stay and high numbers of discharge medications were associated with PC needs. Doctors and nurses can use these two factors as a trigger to assess PC needs among these patients.\u003c/p\u003e","manuscriptTitle":"Zero Percent of Terminally Ill Patients with Non-Cancer Receive Palliative Care Service During Hospital Admission","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-04-19 14:15:35","doi":"10.21203/rs.3.rs-1568169/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9b2c2d93-b477-4806-917e-9a7b13682fdf","owner":[],"postedDate":"April 19th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-04-19T14:15:35+00:00","versionOfRecord":[],"versionCreatedAt":"2022-04-19 14:15:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1568169","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1568169","identity":"rs-1568169","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}