Asleep or not asleep? Evaluation of the Quality of Patients’ Sleep in Critical Care Nursing

Sleep is important for the recovery of a critically ill patient, as lack of sleep is known to influence negatively a person’s cardiovascular system, mood, orientation, and metabolic and immune function and thus, it may prolong patients’ intensive care unit (ICU) and hospital stay. Intubated and mechanically ventilated patients suffer from fragmented and light sleep. However, it is not known well how non-intubated patients sleep. The evaluation of the patients’ sleep may be compromised by their fatigue and still position with no indication if they are asleep or not. The purpose of this study was to evaluate ICU patients’ sleep evaluation methods, the quality of non-intubated patients’ sleep, and the sleep evaluations performed by ICU nurses. The aims were to develop recommendations of patients’ sleep evaluation for ICU nurses and to provide a description of the quality of non-intubated patients’ sleep. The literature review of ICU patients’ sleep evaluation methods was extended to the end of 2014. The evaluation of the quality of patients’ sleep was conducted with four data: A) the nurses’ narrative documentations of the quality of patients’ sleep (n=114), B) the nurses’ sleep evaluations (n=21) with a structured observation instrument C) the patients’ self-evaluations (n=114) with the Richards-Campbell Sleep Questionnaire, and D) polysomnographic evaluations of the quality of patients’ sleep (n=21). The correspondence of data A with data C (collected 4–8/2011), and data B with data D (collected 5–8/2009) were analysed. Content analysis was used for the nurses’ documentations and statistical analyses for all the other data. The quality of non-intubated patients’ sleep varied between individuals. In many patients, sleep was light, awakenings were frequent, and the amount of sleep was insufficient as compared to sleep in healthy people. However, some patients were able to sleep well. The patients evaluated the quality of their sleep on average neither high nor low. Sleep depth was evaluated to be the worst and the speed of falling asleep the best aspect of sleep, on a scale 0 (poor sleep) to 100 (good sleep). Nursing care was mostly performed while the patients were awake, and thus the disturbing effect was low. The instruments available for nurses to evaluate the quality of patients’ sleep were limited and measured mainly the quantity of sleep. Nurses’ structured observatory evaluations of the quality of patients’ sleep were correct for approximately two thirds of the cases, and only regarding total sleep time. Nurses’ narrative documentations of the patients’ sleep corresponded with patients’ self-evaluations in just over half of the cases. However, nurses documented several dimensions of sleep that are not included in the present sleep evaluation instruments. They could be classified according to the components of the nursing process: needs assessment, sleep assessment, intervention, and effect of intervention. Valid, more comprehensive sleep evaluation methods for nurses are needed to evaluate, document, improve and study patients’ quality of sleep.

Business intelligence viewpoint on managerial decision-making : Ill-structured problems and decision support systems

Vaikka liiketoimintatiedon hallintaa sekä johdon päätöksentekoa on tutkittu laajasti, näiden kahden käsitteen yhteisvaikutuksesta on olemassa hyvin rajallinen määrä tutkimustietoa. Tulevaisuudessa aiheen tärkeys korostuu, sillä olemassa olevan datan määrä kasvaa jatkuvasti. Yritykset tarvitsevat jatkossa yhä enemmän kyvykkyyksiä sekä resursseja, jotta sekä strukturoitua että strukturoimatonta tietoa voidaan hyödyntää lähteestä riippumatta. Nykyiset Business Intelligence -ratkaisut mahdollistavat tehokkaan liiketoimintatiedon hallinnan osana johdon päätöksentekoa. Aiemman kirjallisuuden pohjalta, tutkimuksen empiirinen osuus tunnistaa liiketoimintatiedon hyödyntämiseen liittyviä tekijöitä, jotka joko tukevat tai rajoittavat johdon päätöksentekoprosessia. Tutkimuksen teoreettinen osuus johdattaa lukijan tutkimusaiheeseen kirjallisuuskatsauksen avulla. Keskeisimmät tutkimukseen liittyvät käsitteet, kuten Business Intelligence ja johdon päätöksenteko, esitetään relevantin kirjallisuuden avulla – tämän lisäksi myös dataan liittyvät käsitteet analysoidaan tarkasti. Tutkimuksen empiirinen osuus rakentuu tutkimusteorian pohjalta. Tutkimuksen empiirisessä osuudessa paneudutaan tutkimusteemoihin käytännön esimerkein: kolmen tapaustutkimuksen avulla tutkitaan sekä kuvataan toisistaan irrallisia tapauksia. Jokainen tapaus kuvataan sekä analysoidaan teoriaan perustuvien väitteiden avulla – nämä väitteet ovat perusedellytyksiä menestyksekkäälle liiketoimintatiedon hyödyntämiseen perustuvalle päätöksenteolle. Tapaustutkimusten avulla alkuperäistä tutkimusongelmaa voidaan analysoida tarkasti huomioiden jo olemassa oleva tutkimustieto. Analyysin tulosten avulla myös yksittäisiä rajoitteita sekä mahdollistavia tekijöitä voidaan analysoida. Tulokset osoittavat, että rajoitteilla on vahvasti negatiivinen vaikutus päätöksentekoprosessin onnistumiseen. Toisaalta yritysjohto on tietoinen liiketoimintatiedon hallintaan liittyvistä positiivisista seurauksista, vaikka kaikkia mahdollisuuksia ei olisikaan hyödynnetty. Tutkimuksen merkittävin tulos esittelee viitekehyksen, jonka puitteissa johdon päätöksentekoprosesseja voidaan arvioida sekä analysoida. Despite the fact that the literature on Business Intelligence and managerial decision-making is extensive, relatively little effort has been made to research the relationship between them. This particular field of study has become important since the amount of data in the world is growing every second. Companies require capabilities and resources in order to utilize structured data and unstructured data from internal and external data sources. However, the present Business Intelligence technologies enable managers to utilize data effectively in decision-making. Based on the prior literature, the empirical part of the thesis identifies the enablers and constraints in computer-aided managerial decision-making process. In this thesis, the theoretical part provides a preliminary understanding about the research area through a literature review. The key concepts such as Business Intelligence and managerial decision-making are explored by reviewing the relevant literature. Additionally, different data sources as well as data forms are analyzed in further detail. All key concepts are taken into account when the empirical part is carried out. The empirical part obtains an understanding of the real world situation when it comes to the themes that were covered in the theoretical part. Three selected case companies are analyzed through those statements, which are considered as critical prerequisites for successful computer-aided managerial decision-making. The case study analysis, which is a part of the empirical part, enables the researcher to examine the relationship between Business Intelligence and managerial decision-making. Based on the findings of the case study analysis, the researcher identifies the enablers and constraints through the case study interviews. The findings indicate that the constraints have a highly negative influence on the decision-making process. In addition, the managers are aware of the positive implications that Business Intelligence has for decision-making, but all possibilities are not yet utilized. As a main result of this study, a data-driven framework for managerial decision-making is introduced. This framework can be used when the managerial decision-making processes are evaluated and analyzed.